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Develop A Responsive Layout Of Mobile App With Flutter
Develop a Responsive Layout Of Mobile App With Flutter With 3.5 billion smartphone users in 2020, expected to reach 3.8 billion in 2021, it is fair enough to say that demand for mobile apps has gracefully scaled from desktop to mobile. And this is due to the growing interest of the developers towards designing a highly responsive and interactive UI layout of applications. While back in 2015, Google rolled out with a significant change in search engine algorithm and introduced a new rule for the website to be mobile responsive first. And, from there, designers have not just understood the importance of designing the responsive architecture in both desktop and non-desktop applications but also love designing responsive UI in-app to increase user experience. However, implementing responsive UIs in the application becomes a complicated task for designers in real-life. Whether it’s about configuring changes in the app, auto-rotating the content according to the screen, or making it compatible to display on both small and large screens. At any cost, your app needs to be responsive to the layout changes. That’s where Flutter comes into the role and takes the momentum! So in this guide, we will answer: What is Responsive Design? What is Futter, Why It’s So Demanding and What it Has Evolved In to? How Flutter is Different and Help You Create a Responsive UI of the App? Conclusion: Where To Go Next? Let’s dig deep into each point to understand how to increase the responsiveness of the app with Flutter… What is Responsive App Design? Responsive design simply means using a single code set that responds to various changes to the layout of the devices. The responsive app lay out its UI according to the screen size and shape of the device. From smartwatch, phone, tablet to laptop, an app developed responsive UI can run on multiple devices without having to develop different interfaces of the application. The same app will adjust the size of the page according to the screen when the user either resizes the window on the laptop or changes the orientation of the phone or tablet. Important Elements to Focus To Create Responsive Layout In recent years, developing a responsive app has become a hot topic of the town but how to make it happen in the real world? What essential things do you need to focus on? In responsive design, there are majorly three things to consider- Size, Orientation, and Device type. When any one of these elements changes, the app UI changes. You can also choose to hire mobile app developer that can make it done for you. But.. Let’s make it simple for you to understand: In the below image, we have a logo, logo title and subtitles, two fields, action button and background image. But, when we run these components on four different devices, [small screen (480*800), medium screen (1080*1920), Large screen (1200*1920) and iPhone XR], observe the clear results. In the small device screen, the layout components are breaking and going out of screen. The title is splitting into two lines and overall reduces the design impact. While other screens are looking fine but there are few minor differences. So what’s the solution? In this blog, I’ll explain to you how to fix the UI problems of the app by using Flutter plugins. But before that! What is Flutter, Why It’s So Demanding and What it Has Evolved Into? Flutter is defined as Google’s UI toolkit that allows developers building beautiful, natively compiled applications for multiple platforms including Mobile (iOS, Android), Desktop (Linux, Mac, Windows, Google Fuchsia) and web. With the launch of Flutter in 2015, Google has not just stolen the show again but also created a buzzword in the field of app development. That is why clients from all across the world are keen hiring flutter app development company in 2021. Being based on Dart programming language and allowing developers to create an application for multiple platforms using a single codebase, Flutter is making good progress. It has become the second most popular choice of framework for developers. By introducing Flutter, Google has marked incredible success in two significant aspects — in creating a genuinely platform-independent framework for Android and iOS native apps that work great for production use. Now the question is what makes it so demanding for the app development? Here’s a list of some features and qualities that makes it so demanding: Being a cross-platform framework, it allows developers to create an app for iOS and Android by using the same code-base. Flutter is an open-source framework, so it is free to use and provide extensive documentation and community support to make it easier even for beginners to get started with Flutter. This framework is simple to learn and easy to use as it is based on Google’s in-house language that is Dart. Despite being a young framework, Flutter has become a prime choice of leading companies like Google, Alibaba, eBay, Emaar and many more. With hot reload feature, launching or updating a Flutter based app is quite simple and fast. Developers can instantly make changes in the code on emulators, simulators and hardware in a second, without having to restart the running app. It is one of the biggest reasons that make Flutter the first choice of developers for building UIs, fixing bugs and adding a new feature. Hopefully, you are convinced that Flutter has become so famous for developing applications. As far as building a responsive layout in the application, Android and iOS adopt different approaches to handle layouts for different screen sizes natively. To handle various screen sizes and pixel densities, multiple concepts are used in Android including: Android Approaches for Developing Responsive UI ConstraintLayout: For creating a flexible and creative UI design that adapts to different screen sizes and dimensions. For creating a flexible and creative UI design that adapts to different screen sizes and dimensions. SplitView: For separate layout files that fit different screen sizes and able to handle layout adjustments automatically as per the screen size of the device. For separate layout files that fit different screen sizes and able to handle layout adjustments automatically as per the screen size of the device. Fragment: For extracting your UI logic into separate components, so you don’t need to define the reason separately. For extracting your UI logic into separate components, so you don’t need to define the reason separately. VectorDrawable: For any kind of illustrations like icons, or vector graphics. iOS Approaches for Developing Responsive UI Auto Layout: Also known as Constraints that govern content in your app and automatically adjust the layout according to the specified constraints. Also known as Constraints that govern content in your app and automatically adjust the layout according to the specified constraints. Size Classes: With size classes, iOS dramatically makes layout adjustments based on the size classes of a content area. With size classes, iOS dramatically makes layout adjustments based on the size classes of a content area. UI Elements: There are few UI elements that developers use for building responsive UIs on iOS including UIStackView, UIViewController, UISplitViewController and more. How Flutter is Different and Help You Create a Responsive UI of the App? Just because we are claiming that creating responsive layouts in Flutter is quite more straightforward and easier, therefore, many of you are curious to ask these two questions instead of directly moving to hire software development company: What widgets should I Use in App That adapts to Screens of Different Sizes? How Can You Get The Information About the Screen Size and How Can You Use It While Writing the UI Code? We’ll answer these questions but let’s first talk about the second question because it is the heart of the issue. So there are here major ways to meet your goals: 1. MediaQuery One potential way to get information from the MediaQueryData of the MediaQuery root that is “InheritedWidget”. It provides some valuable information on Orientation and ScreenSize, that enables you to determine which layout to display based on the current orientation, what type of screen (mobile, tablet or Desktop), and screen size on which app is being displayed on. Now the question is how to use it? Let’s learn with the example of building a chat app in Flutter that responds to layout changes: To get started with the changes in the layout of the chat page using MediaQuery, you need first to check the orientation from MediaQuery- If it is a landscape, then you’ll have a detail page. You need to declare a child widget to use it later. If you have a details page, then you can declare the child widget as a row of widgets. For this, the row contains the list of chats as a first item. After that, the next thing in a row is the chat page showing the conversation. If you don’t have a detail page on the app, then the child will be the list of chats. Lastly, you need to assign that child widget you created as a SafeArea. Develop the app and make it run different screens and it will most likely this on Portrait and Landscape: To make it happen, you need to go into the “ChatListPage.Dart” file in the Lib folder and have to replace the content of “build (Buildcontext Context)” with these above mentioned steps. 2. LayoutBuilder The other way is to use a LayoutBuilder, a perfect alternative to MediaQuery that has been used to handle orientation changes. It is a builder widget just like a “StreamBuilder” or a “FutureBuilder”, that also gives BoxConstraints which enables you to determine the maximum and minimum height and width properties of the screen. Let’s understand how this approach will work practically: Firstly, you need to declare the LayoutBuilder as a SafeArea. You need to determine whether the details page is using the maximum width of the parent widget. If it is greater than 600, then you have to have a detail page. If you have a detail page, then declare the child as a row of widgets. For this, the row contains the list of chats as a first item. Next item in a row is the detail page showing the conversation. Lastly, if you don’t have a detail page, it’ll be the list of chats. Following these steps, you can build and test projects on different screens. So these are the two major ways to check different orientations and screen sizes. But, how to make further adjustments with text? Auto-Resizing Text Based on Parent Widget Size If you notice the text in the above landscape screenshot, the coloured text is not resized correctly as per the layout of the screen. In that case, increasing the size of the font is quite daunting as it will go over the box. But using the Flutter Widget “FittedBox”, you can rightly scale the size according to the size of the parent widget. This is how you can use this widget in a chat app: To make changes in the text size , you need to follow “BoxFit.Contain” rules and try to go over these steps: Firstly, you declare a FittedBox as a parent of the Text Widget. Secondly, as you are using the BoxFit.Contain, you can fit to make it scale as big as it can without going out of the widget box. Lastly, declare the original TEXT widget as a child. Following the steps, you can see the improvement in the text size that automatically get adjusted with the screen size. UI Architecture: Expandable and Flexible App responsiveness is directly related to making your UI flexible and expandable with the right choice of widgets. And, the plugins that are really useful inside a column or a row. To fix the broken image to the screen, firstly you need to open the “ConversationalPage.Dart” file in that Lib folder. Then discover the line with “SquareGallery()” with TODO. That widget will not appear, because it’s a child of “Column” and it doesn’t have enough information to determine its own height. So there you can wrap it in an “AspectRatio” widget to give it constraints. In case if you are not able to find such constraints, then it will give you one that only follows the ratio provided by you. Moreover, in that case, the widget might overflow. Final results, when you click on to attach the image button, then the image will come like this in both portrait and landscape screen. CustomMultiChildLayout Flutter also provides layout widget, that helps to size its child layout to a fraction of the total available space. It is especially useful inside Expandable and Flexible widgets. With CustomMultiChildLayou, you can make your layout responsive, but how? Since its a vast topic, so here we are explaining the basic code snippet below: First, you need to declare a subclass of MultiChildLayoutDelegate. Overlay the PerformLayout method, so you need to layout the children widgets using the LayoutChild and PositionChild methods. Lastly, you need to return a boolean from ShouldRelayout if the widget should perform a layout again. The choice of the method depends upon your widget’s parameters. Conclusion: Where To Go Next? Most of you are wondering that from where you can get these plugins or widgets to make you app UI responsive. You can download the material by simply clicking on the interlinks of the blog, and you can choose to get connected with our experts. Since Flutter has become a most demanding framework in the app development market, therefore, the majority of developers are looking forward to leveraging the features of Flutter. There are plenty of guides, tutorials and official docs available for responsive apps in Flutter, but understanding the technicality of those tutorials is quite challenging for a novice. Therefore, we drafted things in this blog in a simple and straightforward manner to make you understand the concept. Apart from the above mentioned widget, there are various other things that you need to know and understand. Therefore, we recommend you to hire an app development company that stands by your side at every step to make your Android/iOS app responsive with Flutter.
https://medium.com/flutter-community/develop-a-responsive-layout-of-mobile-app-with-flutter-c6a6f7013aec
['Sophia Martin']
2020-12-14 05:52:38.459000+00:00
['Mobile App Development', 'Mobile Apps', 'Technology', 'Startup', 'Flutter']
Title Develop Responsive Layout Mobile App FlutterContent Develop Responsive Layout Mobile App Flutter 35 billion smartphone user 2020 expected reach 38 billion 2021 fair enough say demand mobile apps gracefully scaled desktop mobile due growing interest developer towards designing highly responsive interactive UI layout application back 2015 Google rolled significant change search engine algorithm introduced new rule website mobile responsive first designer understood importance designing responsive architecture desktop nondesktop application also love designing responsive UI inapp increase user experience However implementing responsive UIs application becomes complicated task designer reallife Whether it’s configuring change app autorotating content according screen making compatible display small large screen cost app need responsive layout change That’s Flutter come role take momentum guide answer Responsive Design Futter It’s Demanding Evolved Flutter Different Help Create Responsive UI App Conclusion Go Next Let’s dig deep point understand increase responsiveness app Flutter… Responsive App Design Responsive design simply mean using single code set responds various change layout device responsive app lay UI according screen size shape device smartwatch phone tablet laptop app developed responsive UI run multiple device without develop different interface application app adjust size page according screen user either resizes window laptop change orientation phone tablet Important Elements Focus Create Responsive Layout recent year developing responsive app become hot topic town make happen real world essential thing need focus responsive design majorly three thing consider Size Orientation Device type one element change app UI change also choose hire mobile app developer make done Let’s make simple understand image logo logo title subtitle two field action button background image run component four different device small screen 480800 medium screen 10801920 Large screen 12001920 iPhone XR observe clear result small device screen layout component breaking going screen title splitting two line overall reduces design impact screen looking fine minor difference what’s solution blog I’ll explain fix UI problem app using Flutter plugins Flutter It’s Demanding Evolved Flutter defined Google’s UI toolkit allows developer building beautiful natively compiled application multiple platform including Mobile iOS Android Desktop Linux Mac Windows Google Fuchsia web launch Flutter 2015 Google stolen show also created buzzword field app development client across world keen hiring flutter app development company 2021 based Dart programming language allowing developer create application multiple platform using single codebase Flutter making good progress become second popular choice framework developer introducing Flutter Google marked incredible success two significant aspect — creating genuinely platformindependent framework Android iOS native apps work great production use question make demanding app development Here’s list feature quality make demanding crossplatform framework allows developer create app iOS Android using codebase Flutter opensource framework free use provide extensive documentation community support make easier even beginner get started Flutter framework simple learn easy use based Google’s inhouse language Dart Despite young framework Flutter become prime choice leading company like Google Alibaba eBay Emaar many hot reload feature launching updating Flutter based app quite simple fast Developers instantly make change code emulator simulator hardware second without restart running app one biggest reason make Flutter first choice developer building UIs fixing bug adding new feature Hopefully convinced Flutter become famous developing application far building responsive layout application Android iOS adopt different approach handle layout different screen size natively handle various screen size pixel density multiple concept used Android including Android Approaches Developing Responsive UI ConstraintLayout creating flexible creative UI design adapts different screen size dimension creating flexible creative UI design adapts different screen size dimension SplitView separate layout file fit different screen size able handle layout adjustment automatically per screen size device separate layout file fit different screen size able handle layout adjustment automatically per screen size device Fragment extracting UI logic separate component don’t need define reason separately extracting UI logic separate component don’t need define reason separately VectorDrawable kind illustration like icon vector graphic iOS Approaches Developing Responsive UI Auto Layout Also known Constraints govern content app automatically adjust layout according specified constraint Also known Constraints govern content app automatically adjust layout according specified constraint Size Classes size class iOS dramatically make layout adjustment based size class content area size class iOS dramatically make layout adjustment based size class content area UI Elements UI element developer use building responsive UIs iOS including UIStackView UIViewController UISplitViewController Flutter Different Help Create Responsive UI App claiming creating responsive layout Flutter quite straightforward easier therefore many curious ask two question instead directly moving hire software development company widget Use App adapts Screens Different Sizes Get Information Screen Size Use Writing UI Code We’ll answer question let’s first talk second question heart issue major way meet goal 1 MediaQuery One potential way get information MediaQueryData MediaQuery root “InheritedWidget” provides valuable information Orientation ScreenSize enables determine layout display based current orientation type screen mobile tablet Desktop screen size app displayed question use Let’s learn example building chat app Flutter responds layout change get started change layout chat page using MediaQuery need first check orientation MediaQuery landscape you’ll detail page need declare child widget use later detail page declare child widget row widget row contains list chat first item next thing row chat page showing conversation don’t detail page app child list chat Lastly need assign child widget created SafeArea Develop app make run different screen likely Portrait Landscape make happen need go “ChatListPageDart” file Lib folder replace content “build Buildcontext Context” mentioned step 2 LayoutBuilder way use LayoutBuilder perfect alternative MediaQuery used handle orientation change builder widget like “StreamBuilder” “FutureBuilder” also give BoxConstraints enables determine maximum minimum height width property screen Let’s understand approach work practically Firstly need declare LayoutBuilder SafeArea need determine whether detail page using maximum width parent widget greater 600 detail page detail page declare child row widget row contains list chat first item Next item row detail page showing conversation Lastly don’t detail page it’ll list chat Following step build test project different screen two major way check different orientation screen size make adjustment text AutoResizing Text Based Parent Widget Size notice text landscape screenshot coloured text resized correctly per layout screen case increasing size font quite daunting go box using Flutter Widget “FittedBox” rightly scale size according size parent widget use widget chat app make change text size need follow “BoxFitContain” rule try go step Firstly declare FittedBox parent Text Widget Secondly using BoxFitContain fit make scale big without going widget box Lastly declare original TEXT widget child Following step see improvement text size automatically get adjusted screen size UI Architecture Expandable Flexible App responsiveness directly related making UI flexible expandable right choice widget plugins really useful inside column row fix broken image screen firstly need open “ConversationalPageDart” file Lib folder discover line “SquareGallery” TODO widget appear it’s child “Column” doesn’t enough information determine height wrap “AspectRatio” widget give constraint case able find constraint give one follows ratio provided Moreover case widget might overflow Final result click attach image button image come like portrait landscape screen CustomMultiChildLayout Flutter also provides layout widget help size child layout fraction total available space especially useful inside Expandable Flexible widget CustomMultiChildLayou make layout responsive Since vast topic explaining basic code snippet First need declare subclass MultiChildLayoutDelegate Overlay PerformLayout method need layout child widget using LayoutChild PositionChild method Lastly need return boolean ShouldRelayout widget perform layout choice method depends upon widget’s parameter Conclusion Go Next wondering get plugins widget make app UI responsive download material simply clicking interlinks blog choose get connected expert Since Flutter become demanding framework app development market therefore majority developer looking forward leveraging feature Flutter plenty guide tutorial official doc available responsive apps Flutter understanding technicality tutorial quite challenging novice Therefore drafted thing blog simple straightforward manner make understand concept Apart mentioned widget various thing need know understand Therefore recommend hire app development company stand side every step make AndroidiOS app responsive FlutterTags Mobile App Development Mobile Apps Technology Startup Flutter
2,801
Cultural Innovation Accelerators
1. China is the Mammoth in the Room Forget all you know. China is fucking huge. The scariest part is that nobody knows just how far China has come. I met Edward Tse, the author of China’s Disruptors in our Shanghai Summit. He told me the one thing to take away from his book was that the Chinese knew how to innovate, they’re not just copycats anymore. The West, encumbered by bureaucracy, simply does not know what is coming. No developed country has anywhere near as advanced a mobile payments solution as China does. No developed country has anywhere near as advanced an ecommerce logistics platform as China does. When I dropship items via AliExpress on my ecommerce business Discover Qi (btw like my Facebook page #shamelessplug), it costs me $3 to get tracking and have my supplier send it straight to my customers anywhere in the world. When I don’t drop ship, I pay customs for ordering in bulk, handle packaging myself, then pay $8.80 to send a package just within Australia. It’s absolutely flipping crazy. Just as before, the Middle Kingdom has never used brute force to conquer the world (as the West did). Throughout CAMP we learnt that the Chinese think and formulate their solutions before speaking out loud. We underestimate our Chinese student compatriots, when we sit in our lecture theaters and find that none of them speak up. That’s why only a few people in CAMP knew that we had YuJia, a quietly spoken, incredibly intelligent and funny Chinese lady, sitting amongst us. YuJia is the CMO of UiSee. Heard of UiSee? Didn’t think so. They’re a Beijing-based autonomous vehicle startup. They’re rumored to be working with Didi (you know the guys who got $1B from Apple and beat the crap out of Uber), led by ex-director of Intel Labs and with over 40 AI engineers. Just as before, the Middle Kingdom has never used brute force to conquer the world (as the West did). It’s even more invisible now that it’s happening in the cloud (you’ll understand the double entendre if you read on). Get your head out of the sand. The game has changed. 2. Design Thinking Is More Important Than Ever. In an increasingly, connected world, the future of work is one that will transcend all boundaries of space and time. We will increasingly work via distance and communicate asynchronously. CAMP taught me that when you bring together multiple people from different ethnic backgrounds, cities and professions you need a framework that democratizes and captures the truths that everyone brings to the table. Design thinking is many things to many people, but for me it’s an opportunity to play at the “edges” not at the “centre”. Design thinking is many things to many people, but for me it’s an opportunity to play at the “edges” not at the “centre.” Innovation after all happens at the intersection between different schools of thought. When carried out properly, the tools of design thinking let their practitioners capture the craziest of ideas and merge them into something truly unheard of before. Throughout CAMP, many of the teams (including our own) struggled with internal conflict. Voices fought to be heard and diversity in experiences led to clashes in ideology. The only real constant was the process. Our team agreed early on to just have faith in the process. To deliver our Insights Report, we used user centered design to interview users and diverge on the discovery process. We used open questions to grasp insights at the edges and understood that qualitative data was the priority. Our research revealed that people actively avoided public open spaces if they felt unsafe or lacked transport options. But the places that they loved most about their city were spaces that let them connect with people and nature at the same time. This helped us craft our problem statement: How might we get more people to engage in public open spaces and create opportunities for businesses to leverage this engagement. We used a digital whiteboard and post-it notes (via Google Slides) to share insights and affinitise the different patterns that arose. Then we used dotmocracy to vote and discuss the different categories. In doing so, we were all able to obtain buy-in to the problem we were solving. Design thinking was crucial to our success. Because whenever we had doubts about the solutions we were forming, we would always come back to the the problem statement that we all genuinely believed in. Design Thinking enabled us to diverge but also converge together. Something that’s extremely hard to do with five very different people. 3. Problem Solving happens in the Clouds and the Dirt In the weeks leading up to CAMP’s Sydney Summit, I was listening avidly to Gary Vaynerchuk’s audiobook #AskGaryVee (11/10 would recommend!!!). I came across this concept of being in the clouds and the dirt. The Clouds is your “why” and your “what,” the Dirt is your “how.” For me it’s the perfect encapsulation of everything I’ve done to help Mad Paws a high-growth, early stage tech startup, succeed. You’ve got to have this high level strategy, this 10,000 ft view of where your business sits and what the bigger context of everything you do is. In other words, you’ve got to have your head in the clouds, not in the sand. But it’s not enough, you’ve got to hustle, you’ve got get your hands dirty and get shit done. For me, from the get go, the most daunting task our group faced as the EY Sustainable Resilient Cities think tank, was the scope of the problem we faced. Design thinkers call this a “wicked problem.” We didn’t want to be a think tank that just delivered a pretty pitch deck and a whole bunch of high level strategy and concepts. We wanted to deliver a solution that had real user validation and that had the potential to be profitable and scaleable as well. It’s extremely difficult to pitch a massive problem and convince the audience that your solution is still relevant to that problem. For us, it was the $800M burden of physical inactivity on the healthcare system. But we brought it back to the opportunities physical activity and engagement in public open spaces brought for local businesses. I felt many of the teams had identified critical problems to solve, they even had great ideas as concepts. E.g. the first runner’s up Chagri, gave a compelling and super relevant business case for Australian Agricultural businesses exporting to China. But, the core differentiator (in my opinion) was our dirty work. We got out of the proverbial building and spoke to 41 real customers and 17 real businesses. We hustled and by staying close to the users this allowed me to present a pitch with real learning and real market traction. 4. Surround Yourself with People of the Same “Religion.” Your religion can be a common belief or goal. This might sound cultish. But I’m convinced that by surrounding yourself with people of the same religion, it truly magnifies and augments you. This is another concept that came out of Gary’s book. It’s significance only really hit me as I reflected on the CAMP experience. If there’s just one thing that made CAMP worth it for me, it was the people. Our time on this planet is short. You’ve got to actively pick the people in your life that will accelerate you towards your clouds. Our time on this planet is short. You’ve got to actively pick the people in your life that will accelerate you towards your clouds. You need to let go of the ones that drag you back. It reminds me of facilitating Agile Sprint retrospectives at Mad Paws, do less of the things that don’t go well, do more of the things that do. For CAMP, our religion was the mutual belief that the answer to the world’s biggest problems could only be solved at the intersection of true cultural diversity. No matter the cultural differences, no matter what our “day jobs” were, we were all here for the same reason. It speaks to the power of cults. When you surround yourself with people of the same religion, your feel augmented by those around you. This sounds corny, but you feel like your flying. I am feeling massive surges of oxytocin and serotonin as I write this! It was an un-describable high and a beautiful, amazing moment of what happens when embracing cultural diversity IS the religion. For me, one of those highs, was when CAMPers trekked it out to a Karaoke bar in Shanghai. There was this magical moment when Bella (a German Australian) and Will (an Australian, Chinese-Timorese expat living in Shanghai) busted out an old-school Chinese karaoke duet. This was a duet that I had grown up listening to my parents sing. Then the next second the whole group was singing Wonderwall. It was an un-describable high and a beautiful, amazing moment of what happens when embracing cultural diversity IS the religion. This is a church I can certainly ascribe to. The CAMPers on Sichuan (aka “Sexual”) Hot Pot Night 5. Pitching = Performing Arts My final realization was that after 10 years of hip hop dancing, I finally found how to apply it to my professional career. Throughout CAMP we were blessed to have the guidance of the wonderful ladies of High Performance Coaching. They helped us increase our self-awareness both off the stage and on the stage. It was to my absolute surprise and delight that both Louise and Karen came from successful careers in the performing arts and here they were coaching executives on performance. On the afternoon of the final night, we were given tips on how to own the stage, breathe deeply, create presence and show confidence. As I took part in the ritualistic exercises, and stood on the stage in front of an empty set of tables it suddenly occurred to me. This was no different from the countless other times I had done hip hop performances in front of thousands at a national level. When I realized that, everything became simple. I understood the need to take the audience on a journey. I understood what it meant to look the judges in the eye and make them believe. I understood my position on the stage and what moves I needed to perform to maximize impact. And I understood that my word craft and the story I would tell, were already captured in my verbal “muscle memory”. It was zen. Once I made that quantum leap, I realized the dirt I had been working on for so long, suddenly found a purpose within my clouds. Up to that moment, I had always questioned the value of dance in my life. It had been a significant emotional burden, when I saw that other people were excelling at other things. I just loved to dance but I couldn’t reconcile it with my own career’s ambitions. However, once I made that quantum leap, I realized the dirt I had been working on for so long, suddenly found a purpose within my clouds. By connected pitching to performing arts, I knew that the stage that night would be mine (irrelevant if our team won or not). Our Team’s Winning Pitch Finishing Up and Giving Thanks Needless to say, CAMP has been a game-changing milestone in my life. When I wrote my personal life OKRs at the beginning of 2017, I set myself a personal OKR to organize a networking trip to China. hen I saw a selfie of Andrea Myles and Jack Ma on LinkedIn which I liked. I received a push notification over the cloud. Andrea reached out and despite how steep the price seemed, I just jumped the gun and went for it. I could not have imagined what would’ve unfolded. Now, I’m finally seeing how the things that I’ve been doing, my dirt, are connecting up to my destiny, the clouds.
https://medium.com/startup-grind/five-surprising-things-i-learnt-in-a-cultural-innovation-accelerator-1b42f5652764
['Christopher Nheu']
2017-07-03 18:18:00.374000+00:00
['Design', 'China', 'Startup', 'Personal Development', 'Innovation']
Title Cultural Innovation AcceleratorsContent 1 China Mammoth Room Forget know China fucking huge scariest part nobody know far China come met Edward Tse author China’s Disruptors Shanghai Summit told one thing take away book Chinese knew innovate they’re copycat anymore West encumbered bureaucracy simply know coming developed country anywhere near advanced mobile payment solution China developed country anywhere near advanced ecommerce logistics platform China dropship item via AliExpress ecommerce business Discover Qi btw like Facebook page shamelessplug cost 3 get tracking supplier send straight customer anywhere world don’t drop ship pay custom ordering bulk handle packaging pay 880 send package within Australia It’s absolutely flipping crazy Middle Kingdom never used brute force conquer world West Throughout CAMP learnt Chinese think formulate solution speaking loud underestimate Chinese student compatriot sit lecture theater find none speak That’s people CAMP knew YuJia quietly spoken incredibly intelligent funny Chinese lady sitting amongst u YuJia CMO UiSee Heard UiSee Didn’t think They’re Beijingbased autonomous vehicle startup They’re rumored working Didi know guy got 1B Apple beat crap Uber led exdirector Intel Labs 40 AI engineer Middle Kingdom never used brute force conquer world West It’s even invisible it’s happening cloud you’ll understand double entendre read Get head sand game changed 2 Design Thinking Important Ever increasingly connected world future work one transcend boundary space time increasingly work via distance communicate asynchronously CAMP taught bring together multiple people different ethnic background city profession need framework democratizes capture truth everyone brings table Design thinking many thing many people it’s opportunity play “edges” “centre” Design thinking many thing many people it’s opportunity play “edges” “centre” Innovation happens intersection different school thought carried properly tool design thinking let practitioner capture craziest idea merge something truly unheard Throughout CAMP many team including struggled internal conflict Voices fought heard diversity experience led clash ideology real constant process team agreed early faith process deliver Insights Report used user centered design interview user diverge discovery process used open question grasp insight edge understood qualitative data priority research revealed people actively avoided public open space felt unsafe lacked transport option place loved city space let connect people nature time helped u craft problem statement might get people engage public open space create opportunity business leverage engagement used digital whiteboard postit note via Google Slides share insight affinitise different pattern arose used dotmocracy vote discus different category able obtain buyin problem solving Design thinking crucial success whenever doubt solution forming would always come back problem statement genuinely believed Design Thinking enabled u diverge also converge together Something that’s extremely hard five different people 3 Problem Solving happens Clouds Dirt week leading CAMP’s Sydney Summit listening avidly Gary Vaynerchuk’s audiobook AskGaryVee 1110 would recommend came across concept cloud dirt Clouds “why” “what” Dirt “how” it’s perfect encapsulation everything I’ve done help Mad Paws highgrowth early stage tech startup succeed You’ve got high level strategy 10000 ft view business sits bigger context everything word you’ve got head cloud sand it’s enough you’ve got hustle you’ve got get hand dirty get shit done get go daunting task group faced EY Sustainable Resilient Cities think tank scope problem faced Design thinker call “wicked problem” didn’t want think tank delivered pretty pitch deck whole bunch high level strategy concept wanted deliver solution real user validation potential profitable scaleable well It’s extremely difficult pitch massive problem convince audience solution still relevant problem u 800M burden physical inactivity healthcare system brought back opportunity physical activity engagement public open space brought local business felt many team identified critical problem solve even great idea concept Eg first runner’s Chagri gave compelling super relevant business case Australian Agricultural business exporting China core differentiator opinion dirty work got proverbial building spoke 41 real customer 17 real business hustled staying close user allowed present pitch real learning real market traction 4 Surround People “Religion” religion common belief goal might sound cultish I’m convinced surrounding people religion truly magnifies augments another concept came Gary’s book It’s significance really hit reflected CAMP experience there’s one thing made CAMP worth people time planet short You’ve got actively pick people life accelerate towards cloud time planet short You’ve got actively pick people life accelerate towards cloud need let go one drag back reminds facilitating Agile Sprint retrospective Mad Paws le thing don’t go well thing CAMP religion mutual belief answer world’s biggest problem could solved intersection true cultural diversity matter cultural difference matter “day jobs” reason speaks power cult surround people religion feel augmented around sound corny feel like flying feeling massive surge oxytocin serotonin write undescribable high beautiful amazing moment happens embracing cultural diversity religion one high CAMPers trekked Karaoke bar Shanghai magical moment Bella German Australian Australian ChineseTimorese expat living Shanghai busted oldschool Chinese karaoke duet duet grown listening parent sing next second whole group singing Wonderwall undescribable high beautiful amazing moment happens embracing cultural diversity religion church certainly ascribe CAMPers Sichuan aka “Sexual” Hot Pot Night 5 Pitching Performing Arts final realization 10 year hip hop dancing finally found apply professional career Throughout CAMP blessed guidance wonderful lady High Performance Coaching helped u increase selfawareness stage stage absolute surprise delight Louise Karen came successful career performing art coaching executive performance afternoon final night given tip stage breathe deeply create presence show confidence took part ritualistic exercise stood stage front empty set table suddenly occurred different countless time done hip hop performance front thousand national level realized everything became simple understood need take audience journey understood meant look judge eye make believe understood position stage move needed perform maximize impact understood word craft story would tell already captured verbal “muscle memory” zen made quantum leap realized dirt working long suddenly found purpose within cloud moment always questioned value dance life significant emotional burden saw people excelling thing loved dance couldn’t reconcile career’s ambition However made quantum leap realized dirt working long suddenly found purpose within cloud connected pitching performing art knew stage night would mine irrelevant team Team’s Winning Pitch Finishing Giving Thanks Needless say CAMP gamechanging milestone life wrote personal life OKRs beginning 2017 set personal OKR organize networking trip China hen saw selfie Andrea Myles Jack LinkedIn liked received push notification cloud Andrea reached despite steep price seemed jumped gun went could imagined would’ve unfolded I’m finally seeing thing I’ve dirt connecting destiny cloudsTags Design China Startup Personal Development Innovation
2,802
Catharsis Submission Guidelines
How to submit? If you are already a writer with Catharsis, you know the drill — After thoroughly reviewing your draft, click on the three dots beside the Publish icon in the right hand corner of your Draft page. Select Catharsis and send. Also, please note: If your story is in alignment with the guidelines, it will be published within 48 hours without fail. If you are not a writer with us yet, you can either reply to this story/leave a comment and we’ll add you as a writer or you can send an email at [email protected] with your Medium profile link. We welcome each and every one of you to this family with open arms. We can’t wait to read your story. If you still have any questions or doubts, feel free to reply here or reach us at [email protected].
https://medium.com/catharsis-pub/catharsis-submission-guidelines-7ee75514d0df
['Navya Gupta']
2020-08-07 19:17:20.518000+00:00
['Storytelling', 'Poetry', 'Writing', 'Submission Guidelines', 'Catharsis']
Title Catharsis Submission GuidelinesContent submit already writer Catharsis know drill — thoroughly reviewing draft click three dot beside Publish icon right hand corner Draft page Select Catharsis send Also please note story alignment guideline published within 48 hour without fail writer u yet either reply storyleave comment we’ll add writer send email contactnavyaguptagmailcom Medium profile link welcome every one family open arm can’t wait read story still question doubt feel free reply reach u contactnavyaguptagmailcomTags Storytelling Poetry Writing Submission Guidelines Catharsis
2,803
A School of Emotion
To better understand what emotional intelligence is, one has to ask a basic question; how do we learn in the first place? Most of us were brought up in an academic educational system that taught us a number of basic principles. First of all, we were taught that anything worth a grade needs to be scientifically proven, measurable, and verifiable. If it can’t be repeated in a controlled environment for others to analyze, then it is just a theory, not a fact, and should be treated as such. “With the exception of teachers, few people actually wonder about new methods of delivering content, whatever that may be.” Secondly, we were led to believe that how we were taught (in terms of pedagogy) mattered far less than what we were taught. With the exception of teachers, few people actually wonder about methods of delivering content, whatever that may be. As a general rule, we were always led to believe that good teaching should be impartial, unbiased, and not reliant on the teacher’s charisma or charm. This isn’t quite the case — I’m sure you remember a childhood teacher, and probably not because of the subject they taught. Lastly, the educational system assumed that whatever we understood well would remain in our minds for as long as we needed it to. Our minds were made out to be little hard drives, capable of retaining information for as long as we wanted them to (unless banged against something hard). So what does all this have to do with our emotional education? Admittedly not a lot; since none of the above will help you on your quest towards emotional intelligence. “I’m sure you remember a childhood teacher, and probably not because of the subject they taught.” Let’s start with the obvious; the way in which we learn. Contrary to popular belief, the way in which we are thought, or by whom we are taught makes a big difference. In simpler terms, we are more likely to listen to someone who has good things to say, or knows how to ‘sugarcoat’ a bitter pill. Without knowing it, we tend to block out any information that makes us feel awkward, weak, or downright stupid. It is for this reason that when someone points out our inadequacies, we subconsciously turn a blind eye. The theory holds true both in academic and emotional education. Have you ever watched an undergraduate squirm or fidget as their lecturer chews them out in front of their peers? We tend to do that as well; all it takes is one (sometimes non-verbal) suggestion that we are not as emotionally mature as we should be. The result? We immediately go deaf, dismissing the offensive opinion as pure nonsense. Ironically, we’d prefer to knowingly listen to a well-written lie, rather than acknowledge the uncomfortable truth about our failings. “we are more likely to listen to someone who has good things to say, or knows how to ‘sugarcoat’ a bitter pill.” Our minds aren’t hard drives either — we forget things all the time. What seemed like a sure thing yesterday might feel like a possibility today and unlikely to happen tomorrow. Even things that hurt us emotionally fade over time, leaving us with feelings of self-doubt. If there is one thing we can be sure of, it’s that strong emotions and infectious enthusiasm will eventually fade and disappear completely. Very little sticks. But what about scientific proof? Surely we provide a reliable pattern to explain the way in which we react to emotional stimuli. Well, as with any scientific experiment, a key factor in obtaining reliable information would be to eliminate external forces. Precautions must be taken to minimize errors. Since we all carry different emotional baggage along our journey, this becomes impossible. It’s like trying to analyze a water molecule while underwater — you are constantly bombarded by external forces, each and every one of them competing for your attention. “we’d prefer to knowingly listen to a well-written lie, rather than acknowledge the uncomfortable truth about our failings.” So what’s the moral of the story here? If conventional teaching methods don’t apply to emotional education, can it be taught as a discipline? As with most articles within this series, the answer lies within an invitation to explore oneself, rather than a written conclusion. Think back to an event that triggered a strong, negative emotion. Was it because of what happened, or perhaps the person who triggered it? Perhaps you had been told it would happen, but chose not to listen. Did you try to attribute some theory or logic to the event, despite knowing that external forces were also at play? Acknowledging the fact that emotional intelligence requires a different approach to be mastered is already a good start. The more prepared we are, the less misguided conclusions we will arrive at. It’s only when we are able to consider uncomfortable truths, acknowledge external forces, and do away with the notion of systematic logic that we can better understand ourselves from an emotional point of view.
https://medium.com/swlh/a-school-of-emotion-cbfb91c612de
['Daniel Caruana Smith']
2020-12-24 14:30:56.314000+00:00
['Emotional Intelligence', 'Mental Health', 'Self Improvement', 'Psychology', 'Life Lessons']
Title School EmotionContent better understand emotional intelligence one ask basic question learn first place u brought academic educational system taught u number basic principle First taught anything worth grade need scientifically proven measurable verifiable can’t repeated controlled environment others analyze theory fact treated “With exception teacher people actually wonder new method delivering content whatever may be” Secondly led believe taught term pedagogy mattered far le taught exception teacher people actually wonder method delivering content whatever may general rule always led believe good teaching impartial unbiased reliant teacher’s charisma charm isn’t quite case — I’m sure remember childhood teacher probably subject taught Lastly educational system assumed whatever understood well would remain mind long needed mind made little hard drive capable retaining information long wanted unless banged something hard emotional education Admittedly lot since none help quest towards emotional intelligence “I’m sure remember childhood teacher probably subject taught” Let’s start obvious way learn Contrary popular belief way thought taught make big difference simpler term likely listen someone good thing say know ‘sugarcoat’ bitter pill Without knowing tend block information make u feel awkward weak downright stupid reason someone point inadequacy subconsciously turn blind eye theory hold true academic emotional education ever watched undergraduate squirm fidget lecturer chew front peer tend well take one sometimes nonverbal suggestion emotionally mature result immediately go deaf dismissing offensive opinion pure nonsense Ironically we’d prefer knowingly listen wellwritten lie rather acknowledge uncomfortable truth failing “we likely listen someone good thing say know ‘sugarcoat’ bitter pill” mind aren’t hard drive either — forget thing time seemed like sure thing yesterday might feel like possibility today unlikely happen tomorrow Even thing hurt u emotionally fade time leaving u feeling selfdoubt one thing sure it’s strong emotion infectious enthusiasm eventually fade disappear completely little stick scientific proof Surely provide reliable pattern explain way react emotional stimulus Well scientific experiment key factor obtaining reliable information would eliminate external force Precautions must taken minimize error Since carry different emotional baggage along journey becomes impossible It’s like trying analyze water molecule underwater — constantly bombarded external force every one competing attention “we’d prefer knowingly listen wellwritten lie rather acknowledge uncomfortable truth failings” what’s moral story conventional teaching method don’t apply emotional education taught discipline article within series answer lie within invitation explore oneself rather written conclusion Think back event triggered strong negative emotion happened perhaps person triggered Perhaps told would happen chose listen try attribute theory logic event despite knowing external force also play Acknowledging fact emotional intelligence requires different approach mastered already good start prepared le misguided conclusion arrive It’s able consider uncomfortable truth acknowledge external force away notion systematic logic better understand emotional point viewTags Emotional Intelligence Mental Health Self Improvement Psychology Life Lessons
2,804
Facta: a few steps closer to our first case study
Facta: a few steps closer to our first case study … and the changes I had to adjust to in my journey to build it Can we use science to improve our approach to journalism — to make it more transparent, accountable, useful? If journalism is the first draft of history, shouldn’t we use a more solid methodology? We could, I believe, draw inspiration from the researchers who develop hypotheses, look for data, check sources and resources, and test their assumptions before we write, shoot video or design a visualization. Some of you might argue that this is what good journalists do, and it is true. But it is not what most journalists and media do. And this is a problem. When I started my journey toward the development of Facta, our new journalistic venture, I thought I had a very clear idea of the project’s goals, as well as the process to build it. But working on it as a Tow-Knight fellow in entrepreneurial journalism at the Craig Newmark Graduate School of Journalism at CUNY, I have become increasingly aware how much I need to study, experiment, adjust and prototype. Formicablu: science made accessible through journalistic skills For years, I have been focusing on how to make science available to people who are not experts in it. The pure essence of the work my team and I have been performing at formicablu, our Italian science communication agency, since we started in 2005 has been trying different formats, techniques, data visualizations, video and digital animations to improve the accessibility of science. In a nutshell, we have used journalism and its tools to give our readers and listeners entry into the research laboratories and institutions, the data, the fascinating discovery stories and sometimes even the controversies. We have developed our own style, our own signature and our own language. We have become more and more involved in projects with a very vast array of clients who are, most of the time, partners more than customers. We have been working within EU-funded as well as national projects, with great freedom to develop communication strategies to bring science to different communities and audiences. At the same time, I have been freelancing all along, sometimes as an explainer, sometimes as a reporter, sometimes even experimenting with investigative journalism. Last year, at the European Conference of Science Journalists, I was part of a panel discussing why science journalism is rarely investigative. Well, I said, it is because we are not brave enough. We prefer quite basic explanatory science, sometimes even being content with just a sort of translational work from technical jargon into more common language. This approach is usually less controversial, and we feel part of a community, that of pro science people. Yet at the same time it rarely produces real benefits for people; it is confined to the realm of knowledge for its own sake by people who already cherish science. And I do not want that anymore. We cannot linger any longer; we have to be more committed to journalism: use our entire toolkit to investigate, report and connect; look for stories and not only for explanations; look for impacts; understand the complicated processes that lie beneath scientific enterprises; be very open about the controversies and not be content to show only good and positive results. We are perceived as being always on scientists’ side, and this should not be the case. We should be speaking for the people, for the communities, for the ones who may need science but may not be sure where to find it and how to deal with it. Facta: building transparent journalism using a scientific approach and method So I decided to start a new venture, one fully dedicated to build a better journalism. There are many reasons, some of which are explained in my previous post. And as I focus on building this new project, it becomes clearer that this time we need to bring a science toolkit into journalism. Science is not only the vault of stories and data we enjoy talking and reading about, but also a frame of mind that can help journalists improve their approach to finding facts, to evaluating them, to either confirming or discarding them. One thing is very clear: journalism today is under attack. And particularly very good journalism, brave journalism, the kind that is investigating powerful people and dark players, corporations and governments. At the same time, there is an enormous amount of very mediocre journalism out there. An enormous amount of very basic and often inaccurate “cut and paste” products. An enormous amount of journalism that doesn’t care about truth, about verification, about real significance, about impact on people. An enormous amount of journalism that is performed as a very bad, low-quality job, with no dedication, no passion, no mental commitment. And this happens for a number of reasons, some even understandable. But certainly it is not the kind of journalism our societies need. It is not the kind of journalism that is the pillar of democracy, or the key to respond to people’s needs for good quality information. While I was working on business models, value propositions, project plans, north stars and growth equations, and at the same time talking to many, many people to analyze the gaps, the critical issues in the world of journalism, I start playing with the idea that we have a potential solution at hand: using the scientific method and approach to investigate reality. My Facta team and I do have a very unfair advantage: we all have solid research backgrounds. Some in fields that are perceived as more traditionally scientific, from bio sciences to hard ones, and others in history and philosophy, equally if not even more important in fostering critical thinking and in challenging ideas and facts. We can use this advantage to investigate reality. We know how to state hypotheses and how to test them. And we know how to collect data and work with them. We know how to find scientific literature and evaluate the impact of publications and reports. We know scientists working in many different fields, and we are capable of finding our way through the research world, which, believe me, sometimes makes you feel you’re entering another dimension. And we know how to use all of these skills in our reporting, complementing them with stories explored and collected in the field. Getting ready to experiment What does Facta do? It focuses on stories relevant to the entire Mediterranean region — a region that was once the epicenter of civilization and multicultural trade and exchange, and is now a stage for wars, conflicts, the drama of migration and that of a very serious climate crisis. Facta will dive deep into topics that are relevant to at least two Mediterranean countries at a time. From the beginning, we will form a team of journalists from the involved countries and work with selected tech and scientific experts, as well as with representatives of local communities. These key players will be involved in the reporting phase to assess the continuing findings, and to give feedback and make sure the work will address their information needs. Our final output? An innovative journalistic product, in formats that will be decided depending on the story, multimedia and/or data viz, or other factors. We’ll also curate the relevant publications we use, scientific articles, reports, etc., and all the raw interviews, except those with people whose identities need to be protected for security reasons. And then we’ll publish all the data we have collected, available to all in a form that will allow interaction and selective visualization. If you are thinking that data journalism is already done this way, I can argue that this is rarely true. “Data journalism shouldn’t be pretty,” said one of the innovation experts I have interviewed recently in preparing my project. Others expressed the same idea: “It should serve the people; it should be useful to the people.” Even according to this recent publication on Digital Journalism, this is not often the case, both for lack of real transparency and for reliance on very few and often merely institutional sources of data. As a result, current data journalism is not, as a matter of fact, increasing much trust or usability. That’s why I’d like to approach it from a different perspective. Everything will be published on our website, but also in syndication with other publications, national and local. Moreover, local journalists not directly involved in the project from the beginning will still be able to access the materials to produce local stories for their audiences. Given that all ingredients and the recipe will be available, our work will be more accountable. It will serve to regain trust and to enhance transparency — a challenge, I know, and not an easy one. But one I feel quite ready to embrace, and one I hope to be working on with many of you for the next few years. (Again, thanks to Diane Nottle for polishing my English) (Image credits: Card puncher, Public Domain via Wikimedia; Woman technician, Robert Yarnall Richie [No restrictions], via Wikimedia Commons; formicablu)
https://medium.com/journalism-innovation/facta-a-few-steps-closer-to-the-first-case-study-ba38b390427d
['Elisabetta Tola']
2019-05-08 20:45:43.608000+00:00
['Scientific Thinking', 'Facta', 'Science', 'Journalism', 'Data Journalism']
Title Facta step closer first case studyContent Facta step closer first case study … change adjust journey build use science improve approach journalism — make transparent accountable useful journalism first draft history shouldn’t use solid methodology could believe draw inspiration researcher develop hypothesis look data check source resource test assumption write shoot video design visualization might argue good journalist true journalist medium problem started journey toward development Facta new journalistic venture thought clear idea project’s goal well process build working TowKnight fellow entrepreneurial journalism Craig Newmark Graduate School Journalism CUNY become increasingly aware much need study experiment adjust prototype Formicablu science made accessible journalistic skill year focusing make science available people expert pure essence work team performing formicablu Italian science communication agency since started 2005 trying different format technique data visualization video digital animation improve accessibility science nutshell used journalism tool give reader listener entry research laboratory institution data fascinating discovery story sometimes even controversy developed style signature language become involved project vast array client time partner customer working within EUfunded well national project great freedom develop communication strategy bring science different community audience time freelancing along sometimes explainer sometimes reporter sometimes even experimenting investigative journalism Last year European Conference Science Journalists part panel discussing science journalism rarely investigative Well said brave enough prefer quite basic explanatory science sometimes even content sort translational work technical jargon common language approach usually le controversial feel part community pro science people Yet time rarely produce real benefit people confined realm knowledge sake people already cherish science want anymore cannot linger longer committed journalism use entire toolkit investigate report connect look story explanation look impact understand complicated process lie beneath scientific enterprise open controversy content show good positive result perceived always scientists’ side case speaking people community one may need science may sure find deal Facta building transparent journalism using scientific approach method decided start new venture one fully dedicated build better journalism many reason explained previous post focus building new project becomes clearer time need bring science toolkit journalism Science vault story data enjoy talking reading also frame mind help journalist improve approach finding fact evaluating either confirming discarding One thing clear journalism today attack particularly good journalism brave journalism kind investigating powerful people dark player corporation government time enormous amount mediocre journalism enormous amount basic often inaccurate “cut paste” product enormous amount journalism doesn’t care truth verification real significance impact people enormous amount journalism performed bad lowquality job dedication passion mental commitment happens number reason even understandable certainly kind journalism society need kind journalism pillar democracy key respond people’s need good quality information working business model value proposition project plan north star growth equation time talking many many people analyze gap critical issue world journalism start playing idea potential solution hand using scientific method approach investigate reality Facta team unfair advantage solid research background field perceived traditionally scientific bio science hard one others history philosophy equally even important fostering critical thinking challenging idea fact use advantage investigate reality know state hypothesis test know collect data work know find scientific literature evaluate impact publication report know scientist working many different field capable finding way research world believe sometimes make feel you’re entering another dimension know use skill reporting complementing story explored collected field Getting ready experiment Facta focus story relevant entire Mediterranean region — region epicenter civilization multicultural trade exchange stage war conflict drama migration serious climate crisis Facta dive deep topic relevant least two Mediterranean country time beginning form team journalist involved country work selected tech scientific expert well representative local community key player involved reporting phase ass continuing finding give feedback make sure work address information need final output innovative journalistic product format decided depending story multimedia andor data viz factor We’ll also curate relevant publication use scientific article report etc raw interview except people whose identity need protected security reason we’ll publish data collected available form allow interaction selective visualization thinking data journalism already done way argue rarely true “Data journalism shouldn’t pretty” said one innovation expert interviewed recently preparing project Others expressed idea “It serve people useful people” Even according recent publication Digital Journalism often case lack real transparency reliance often merely institutional source data result current data journalism matter fact increasing much trust usability That’s I’d like approach different perspective Everything published website also syndication publication national local Moreover local journalist directly involved project beginning still able access material produce local story audience Given ingredient recipe available work accountable serve regain trust enhance transparency — challenge know easy one one feel quite ready embrace one hope working many next year thanks Diane Nottle polishing English Image credit Card puncher Public Domain via Wikimedia Woman technician Robert Yarnall Richie restriction via Wikimedia Commons formicabluTags Scientific Thinking Facta Science Journalism Data Journalism
2,805
Wine Classifier Using Supervised Learning with 98% Accuracy
With the information I just obtained from the graph, I already have an idea of the kind of classifier I am going to use: a Naive Bayes Classifier. This machine learning classifier performs extremely well on normally distributed data (do not believe developer who mocks it!). If the distributions are situated apart from each other, even better, it will be much easier to distinguish among the three different classes. 4. Preprocessing Given that this is a very simple dataset and the data is already in numerical form, I personally do not think I need to make any preprocessing. If you are a beginner, know that you need to preprocess data when you have to prepare it for your model (for example converting categorical data to encoded data). Extracting Labels The only thing I am going to do is extracting labels from the dataset so that I can feed it to the model. v.upload.retrieve_backup(e.K) v.extract.labels(['Wine']) e.y sample of labels 5. Splitting I will now split X (features) and y (labels) into train and test. As a default, I will use a .2 proportion for the test side. X_train, X_test, y_train, y_test = v.split(0.2) print(X_train.shape, X_test.shape, y_train.shape, y_test.shape) 6. Machine Learning Model It is now time to create my AI: Creating the Model I will be using the scikit-learn library, one of the best open-source machine learning libraries. from sklearn.naive_bayes import GaussianNB clf = GaussianNB() Training the Model I will use my train samples to find the rules that link X to y. Then, I will make an estimate on X_test and compare it with the actual results that the model has never seen: y_test. clf = clf.fit(X_train, y_train) y_predict = clf.predict(X_test) from sklearn.metrics import accuracy_score print(accuracy_score(y_test, y_predict)) 1.0 100%! Astonishing result! 7. Evaluation I have only been splitting the dataset once, but, to improve the validity of the model, I can use a cross-validation algorithm to test the model on 10 different splits, each one with different data taken from the dataset. v.statistics.cross_validation(clf, X_train, y_train, 10) Accuracy: 0.96 (+/- 0.09) [1.00, 1.00, 1.00, 0.92, 0.92, 1.00, 0.85, 0.92, 0.92, 1.00 ] Depending on the data in train and test determined by the split, the accuracy ranges from 85% to 100%, with an average of 96%. The result can vary, the top I obtained is 98% after a few attempts.
https://medium.com/towards-artificial-intelligence/wine-classifier-using-supervised-learning-with-98-accuracy-5f2e173e967e
['Michelangiolo Mazzeschi']
2020-06-05 21:01:01.157000+00:00
['Machine Learning', 'Artificial Intelligence', 'Data Science', 'Wine', 'Big Data']
Title Wine Classifier Using Supervised Learning 98 AccuracyContent information obtained graph already idea kind classifier going use Naive Bayes Classifier machine learning classifier performs extremely well normally distributed data believe developer mock distribution situated apart even better much easier distinguish among three different class 4 Preprocessing Given simple dataset data already numerical form personally think need make preprocessing beginner know need preprocess data prepare model example converting categorical data encoded data Extracting Labels thing going extracting label dataset feed model vuploadretrievebackupeK vextractlabelsWine ey sample label 5 Splitting split X feature label train test default use 2 proportion test side Xtrain Xtest ytrain ytest vsplit02 printXtrainshape Xtestshape ytrainshape ytestshape 6 Machine Learning Model time create AI Creating Model using scikitlearn library one best opensource machine learning library sklearnnaivebayes import GaussianNB clf GaussianNB Training Model use train sample find rule link X make estimate Xtest compare actual result model never seen ytest clf clffitXtrain ytrain ypredict clfpredictXtest sklearnmetrics import accuracyscore printaccuracyscoreytest ypredict 10 100 Astonishing result 7 Evaluation splitting dataset improve validity model use crossvalidation algorithm test model 10 different split one different data taken dataset vstatisticscrossvalidationclf Xtrain ytrain 10 Accuracy 096 009 100 100 100 092 092 100 085 092 092 100 Depending data train test determined split accuracy range 85 100 average 96 result vary top obtained 98 attemptsTags Machine Learning Artificial Intelligence Data Science Wine Big Data
2,806
Can Jigsaw Puzzles Really Improve Your Mental Health?
Can Jigsaw Puzzles Really Improve Your Mental Health? How puzzles can help with anxiety, ADHD, and other mental health issues Photo by Hans-Peter Gauster on Unsplash I’ve probably always had a minor anxiety issue, but since the pandemic, it’s gone into the stratosphere. It’s the kind of anxiety where, even when I remove the stressors and solve the thing I was worried about, my nervous system takes a while to catch up. My mind still races, my heart rate is elevated, my stomach hurts — sometimes it takes all day for the feeling to go away. Normally, I’d try to distract myself with something else, like a show or a book — but lately, it’s gotten so bad that I can’t even focus on those things. In the warmer months, I’d go for a run or do something active outside in order to quiet my mind. But in the dead of winter, going for a jog isn’t as appealing. So, I’ve turned to jigsaw puzzles — and apparently this is not a new idea. Is “puzzle therapy” effective? An article last year from Refinery29 explored this very issue — can puzzles really help to quell anxiety? With people now stuck at home in quarantine, the puzzle business is booming. According to a MarketWatch report, the puzzle industry (because yes, that is a thing) is expected to reach a value of $730 million by 2024. But it’s not just because people are bored — although, that is a contributing factor. It’s because puzzles are relaxing and addicting — in a good way. I myself can attest to this. At my first job, we had a puzzle table. I worked in a newsroom as a copyeditor, so the days were long and stressful. My boss set up a table next to one of the cubicles with a puzzle, and every time we’d walk by it, my coworkers and I would place a few pieces here or there. Sometimes, we’d work on it together during our lunch break. Something as simple as a puzzle was good for team bonding and morale, and it was a good way to take a quick break after a stressful client phone call. While there’s no hard and fast science or research to support the effect puzzles have on mental health, there’s no denying that there are benefits. There’s anecdotal evidence from many a jigsaw puzzler about how puzzles have helped them cope with ADHD, anxiety, insomnia, and PTSD. Some people even swear by 18,000+ piece Ravensburger puzzles — which I didn’t even know existed. They’re about the size of a medium area rug and look completely impossible. Dr. Vaile Wright, director of clinical research and quality at the American Psychological Association, said in an article for CNN that puzzles reduce stress because they distract our brain with finding patterns, which then triggers a hormone response and lowers cortisol. Puzzles also help us get “in the zone,” or into a state of flow where we are hyper-focused on the task in front of us and the rest of the world melts away. And it doesn’t have to be a jigsaw puzzle, if that’s not your pleasure — crossword puzzles, sudoku, word searches, or a Rubik’s cube can have the same effect. Reduce your screen time with a puzzle Especially cooped up in quarantine, people are looking for new ways to spend their time other than staring at a small, medium, or large screen on rotation day after day. Too much screen time can result in headaches, eye fatigue, and disrupted sleep. Remember when adult coloring books were all the rage? It’s because, like puzzles, they’re used as a way to relax and reduce stress. But unlike coloring books, puzzles can be calming and collaborative. “You can talk, someone can read nearby and still feel included, and even if you’re completely focusing, you still feel like you’re doing something together,” said Amanda Kahle, owner of the puzzle business Inner Piece, in an article for CNN. Quality time with others is a key way to beat stress and depression. The next time you crave connection, try working on a puzzle with someone instead of vegging out in front of the TV. Even if you’re quarantining alone, puzzles are a great way to focus your mind on something else, and they can even help you sleep better at night.
https://medium.com/moments-matter/can-jigsaw-puzzles-really-improve-your-mental-health-981e84442e6
['Megan Boley']
2020-12-14 13:07:15.680000+00:00
['Self', 'Mental Health', 'Mindfulness', 'Life', 'Psychology']
Title Jigsaw Puzzles Really Improve Mental HealthContent Jigsaw Puzzles Really Improve Mental Health puzzle help anxiety ADHD mental health issue Photo HansPeter Gauster Unsplash I’ve probably always minor anxiety issue since pandemic it’s gone stratosphere It’s kind anxiety even remove stressor solve thing worried nervous system take catch mind still race heart rate elevated stomach hurt — sometimes take day feeling go away Normally I’d try distract something else like show book — lately it’s gotten bad can’t even focus thing warmer month I’d go run something active outside order quiet mind dead winter going jog isn’t appealing I’ve turned jigsaw puzzle — apparently new idea “puzzle therapy” effective article last year Refinery29 explored issue — puzzle really help quell anxiety people stuck home quarantine puzzle business booming According MarketWatch report puzzle industry yes thing expected reach value 730 million 2024 it’s people bored — although contributing factor It’s puzzle relaxing addicting — good way attest first job puzzle table worked newsroom copyeditor day long stressful bos set table next one cubicle puzzle every time we’d walk coworkers would place piece Sometimes we’d work together lunch break Something simple puzzle good team bonding morale good way take quick break stressful client phone call there’s hard fast science research support effect puzzle mental health there’s denying benefit There’s anecdotal evidence many jigsaw puzzler puzzle helped cope ADHD anxiety insomnia PTSD people even swear 18000 piece Ravensburger puzzle — didn’t even know existed They’re size medium area rug look completely impossible Dr Vaile Wright director clinical research quality American Psychological Association said article CNN puzzle reduce stress distract brain finding pattern trigger hormone response lower cortisol Puzzles also help u get “in zone” state flow hyperfocused task front u rest world melt away doesn’t jigsaw puzzle that’s pleasure — crossword puzzle sudoku word search Rubik’s cube effect Reduce screen time puzzle Especially cooped quarantine people looking new way spend time staring small medium large screen rotation day day much screen time result headache eye fatigue disrupted sleep Remember adult coloring book rage It’s like puzzle they’re used way relax reduce stress unlike coloring book puzzle calming collaborative “You talk someone read nearby still feel included even you’re completely focusing still feel like you’re something together” said Amanda Kahle owner puzzle business Inner Piece article CNN Quality time others key way beat stress depression next time crave connection try working puzzle someone instead vegging front TV Even you’re quarantining alone puzzle great way focus mind something else even help sleep better nightTags Self Mental Health Mindfulness Life Psychology
2,807
Handling Outliers in Machine Learning
Methods To Find Outliers Now We have understood what an outlier is and the different types of outliers now let’s see different methods to find outliers. There are two basic methods: Percentile Box Plot Percentile In this method, we choose a minimum percentile and maximum percentile. Usually, the minimum percentile is 5%, and the maximum percentile is 95%. Then We Fetch out all the data points outside the percentile range, which means those values that are greater than 95% value or smaller than 5% value, and consider them as outliers. Example: In a dataset, if 5% is 45 and 95% is 1000, then all the values that are below 45 or greater than 1000 are considered as outliers. Practical Example: ## Let's First Create a Dummy DataFrame With Outliers lst = [random.randint(0,100) for i in range(0,100)] ## Adding a manual outlier global_outlier = [300] df = pd.DataFrame(lst+global_outlier,columns=['number']) ## Minimum Percentile Value min_val = df.quantile(0.05) ## Maximum Percentile Value max_val = df.quantile(0.95) ## Finding All the Outliers df[(df['number']<min_val[0])| (df['number']>max_val[0])] ##############OUTPUT################ number 23 2 64 1 66 99 84 2 89 99 100 300 ######YOUR OUTPUT MAY BE DIFFERENT BECAUSE WE ARE USING RANDOM MODULE TO GENERATE SAMPLE DATAFRAME#### Box Plot A box plot is a graphical display for describing the distribution of data. Box plots use the median and the lower and upper quartiles. Pandas data frame has a built-in boxplot function. Let’s use the above to create a data frame and try to find the outliers. df.boxplot(column=['number']) 300 value as an outlier Let’s use both the techniques and try to find outliers in a real dataset like Titanic. Visit my Github repo and download the cleaned version of the dataset with no nan values from here. Percentile ########## DETECTING OUTLIERS USING PERCENTILE ############### df = pd.read_csv('data/titanic_with_no_nan.csv') max_val = df.Age.quantile(0.95) min_val = df.Age.quantile(0.05) df2 = df[(df['Age']<min_val) | (df['Age']>max_val)] print("Number of Outliers Detected in Age:",df2.shape[0]) #########OUTPUT######### Number of Outliers Detected in Age: 86 Box Plot ########## DETECTING OUTLIERS USING BOX PLOT ############### df = pd.read_csv('data/titanic_with_no_nan.csv') ### LET'S USE SEABORN BOX PLOTS import seaborn as sns sns.boxplot(df['Age']) Outliers in the ‘Age’ Column in Titanic Dataset Different Ways to Handle Outliers There are two ways to handle outliers. Remove All the outliers. Replace Outliers Values with a suitable value Removing all the outliers In this method, we first find the min and max value quantiles, and then we simply remove all the values by not picking them in further processing. import matplotlib.pyplot as plt import seaborn as sns import warnings import pandas as pd warnings.filterwarnings("ignore") fig, axes = plt.subplots(1,2) plt.tight_layout(0.2) ## DataFrame df = pd.read_csv('data/titanic_with_no_nan.csv') print("Before Shape:",df.shape) ## Max and Min Quantile max_val = df.Age.quantile(0.95) min_val = df.Age.quantile(0.05) ## Removing all the outliers df2 = df[(df['Age']>min_val) & (df['Age']<max_val)] ## Visulization print("After Shape:",df2.shape) sns.boxplot(df['Age'],orient='v',ax=axes[0]) axes[0].title.set_text("Before") sns.boxplot(df2['Age'],orient='v',ax=axes[1]) axes[1].title.set_text("After") plt.show() Replacing Outliers Values with a suitable value Using Quantile Method In this method, we first find the min and max quantile. After that, we find all the values outside the quantile range and replace them with min or max quantile value accordingly. import numpy as np import matplotlib.pyplot as plt import warnings warnings.filterwarnings("ignore") fig, axes = plt.subplots(1,2) plt.tight_layout(0.2) df = pd.read_csv('data/titanic_with_no_nan.csv') print("Previous Shape With Outlier: ",df.shape) sns.boxplot(df['Age'],orient='v',ax=axes[0]) axes[0].title.set_text("Before") ########### HANDLING OUTLIER ###### max_val = df.Age.quantile(0.95) min_val = df.Age.quantile(0.05) df2 = df ####### REPLACING ALL THE Large values with MAX QUANTILE VALUE #### df2['Age'] = np.where(df2['Age']>max_val,max_val,df2['Age']) print("Shape After Removing Outliers:", df2.shape) sns.boxplot(df2['Age'],orient='v',ax=axes[1]) axes[1].title.set_text("After") plt.show() Using IQR IQR or interquartile range is a measurement of variability based on dividing the dataset into different quantiles. Quantiles are divided into Q1, Q2, and Q3, where Q1is the middle value of the first half of the dataset. Q2 is the median value, and Q3 is the middle value of the second half of the dataset. IQR is equal to Q3 minus Q1. Q1 = df.column.quantile(0.25) Q3 = df.column.quantile(0.75) IQR = Q3-Q1 After calculating IQR, we calculate the lower limit and upper limit and then simply discard all the values that are less or above the limit and replace them with lower and upper limit accordingly. NOTE: It will Also Work For Data That is Left skewed or Right Skewed df = pd.read_csv('data/titanic_with_no_nan.csv') import numpy as np import matplotlib.pyplot as plt import warnings warnings.filterwarnings("ignore") fig, axes = plt.subplots(1,2) plt.tight_layout(0.2) print("Previous Shape With Outlier: ",df.shape) sns.boxplot(df['Age'],orient='v',ax=axes[0]) axes[0].title.set_text("Before") ########### HANDLING OUTLIER ###### Q1 = df.Age.quantile(0.25) Q3 = df.Age.quantile(0.75) print(Q1,Q3) IQR = Q3-Q1 print(IQR) lower_limit = Q1 - 1.5*IQR upper_limit = Q3 + 1.5*IQR print(lower_limit,upper_limit) df2 = df df2['Age'] = np.where(df2['Age']>upper_limit,upper_limit,df2['Age']) df2['Age'] = np.where(df2['Age']<lower_limit,lower_limit,df2['Age']) print("Shape After Removing Outliers:", df2.shape) sns.boxplot(df2['Age'],orient='v',ax=axes[1]) axes[1].title.set_text("After") plt.show() Bonus Tip It is not always easy as it looks to find the outliers and then handle them. In such a situation, we can use a different machine learning model that is not sensitive to outliers. 1. Naivye Bayes Classifier--- Not Sensitive To Outliers 2. SVM-------- Not Sensitive To Outliers 3. Decision Tree Regressor or Classifier---- Not Sensitive 4. Ensemble(RF,XGboost,GB)------------Not Sensitive 5. KNN--------------------------- Not Sensitive 6. Linear Regression------------- Sensitive 7. Logistic Regression----------- Sensitive 8. Kmeans------------------------ Sensitive 9. Hierarichal------------------- Sensitive 10. PCA-------------------------- Sensitive 11. Neural Networks-------------- Sensitive Github & Notebook Link
https://medium.com/towards-artificial-intelligence/handling-outliers-in-machine-learning-f842d8f4c1dc
['Abhay Parashar']
2020-12-03 16:50:18.950000+00:00
['Machine Learning', 'Python', 'Artificial Intelligence', 'Education', 'Data Science']
Title Handling Outliers Machine LearningContent Methods Find Outliers understood outlier different type outlier let’s see different method find outlier two basic method Percentile Box Plot Percentile method choose minimum percentile maximum percentile Usually minimum percentile 5 maximum percentile 95 Fetch data point outside percentile range mean value greater 95 value smaller 5 value consider outlier Example dataset 5 45 95 1000 value 45 greater 1000 considered outlier Practical Example Lets First Create Dummy DataFrame Outliers lst randomrandint0100 range0100 Adding manual outlier globaloutlier 300 df pdDataFramelstglobaloutliercolumnsnumber Minimum Percentile Value minval dfquantile005 Maximum Percentile Value maxval dfquantile095 Finding Outliers dfdfnumberminval0 dfnumbermaxval0 OUTPUT number 23 2 64 1 66 99 84 2 89 99 100 300 OUTPUT MAY DIFFERENT USING RANDOM MODULE GENERATE SAMPLE DATAFRAME Box Plot box plot graphical display describing distribution data Box plot use median lower upper quartile Pandas data frame builtin boxplot function Let’s use create data frame try find outlier dfboxplotcolumnnumber 300 value outlier Let’s use technique try find outlier real dataset like Titanic Visit Github repo download cleaned version dataset nan value Percentile DETECTING OUTLIERS USING PERCENTILE df pdreadcsvdatatitanicwithnonancsv maxval dfAgequantile095 minval dfAgequantile005 df2 dfdfAgeminval dfAgemaxval printNumber Outliers Detected Agedf2shape0 OUTPUT Number Outliers Detected Age 86 Box Plot DETECTING OUTLIERS USING BOX PLOT df pdreadcsvdatatitanicwithnonancsv LETS USE SEABORN BOX PLOTS import seaborn sn snsboxplotdfAge Outliers ‘Age’ Column Titanic Dataset Different Ways Handle Outliers two way handle outlier Remove outlier Replace Outliers Values suitable value Removing outlier method first find min max value quantiles simply remove value picking processing import matplotlibpyplot plt import seaborn sn import warning import panda pd warningsfilterwarningsignore fig ax pltsubplots12 plttightlayout02 DataFrame df pdreadcsvdatatitanicwithnonancsv printBefore Shapedfshape Max Min Quantile maxval dfAgequantile095 minval dfAgequantile005 Removing outlier df2 dfdfAgeminval dfAgemaxval Visulization printAfter Shapedf2shape snsboxplotdfAgeorientvaxaxes0 axes0titlesettextBefore snsboxplotdf2Ageorientvaxaxes1 axes1titlesettextAfter pltshow Replacing Outliers Values suitable value Using Quantile Method method first find min max quantile find value outside quantile range replace min max quantile value accordingly import numpy np import matplotlibpyplot plt import warning warningsfilterwarningsignore fig ax pltsubplots12 plttightlayout02 df pdreadcsvdatatitanicwithnonancsv printPrevious Shape Outlier dfshape snsboxplotdfAgeorientvaxaxes0 axes0titlesettextBefore HANDLING OUTLIER maxval dfAgequantile095 minval dfAgequantile005 df2 df REPLACING Large value MAX QUANTILE VALUE df2Age npwheredf2Agemaxvalmaxvaldf2Age printShape Removing Outliers df2shape snsboxplotdf2Ageorientvaxaxes1 axes1titlesettextAfter pltshow Using IQR IQR interquartile range measurement variability based dividing dataset different quantiles Quantiles divided Q1 Q2 Q3 Q1is middle value first half dataset Q2 median value Q3 middle value second half dataset IQR equal Q3 minus Q1 Q1 dfcolumnquantile025 Q3 dfcolumnquantile075 IQR Q3Q1 calculating IQR calculate lower limit upper limit simply discard value le limit replace lower upper limit accordingly NOTE Also Work Data Left skewed Right Skewed df pdreadcsvdatatitanicwithnonancsv import numpy np import matplotlibpyplot plt import warning warningsfilterwarningsignore fig ax pltsubplots12 plttightlayout02 printPrevious Shape Outlier dfshape snsboxplotdfAgeorientvaxaxes0 axes0titlesettextBefore HANDLING OUTLIER Q1 dfAgequantile025 Q3 dfAgequantile075 printQ1Q3 IQR Q3Q1 printIQR lowerlimit Q1 15IQR upperlimit Q3 15IQR printlowerlimitupperlimit df2 df df2Age npwheredf2Ageupperlimitupperlimitdf2Age df2Age npwheredf2Agelowerlimitlowerlimitdf2Age printShape Removing Outliers df2shape snsboxplotdf2Ageorientvaxaxes1 axes1titlesettextAfter pltshow Bonus Tip always easy look find outlier handle situation use different machine learning model sensitive outlier 1 Naivye Bayes Classifier Sensitive Outliers 2 SVM Sensitive Outliers 3 Decision Tree Regressor Classifier Sensitive 4 EnsembleRFXGboostGBNot Sensitive 5 KNN Sensitive 6 Linear Regression Sensitive 7 Logistic Regression Sensitive 8 Kmeans Sensitive 9 Hierarichal Sensitive 10 PCA Sensitive 11 Neural Networks Sensitive Github Notebook LinkTags Machine Learning Python Artificial Intelligence Education Data Science
2,808
Data Scientists, The 5 Graph Algorithms that you should know
1. Connected Components A graph with 3 connected components We all know how clustering works? You can think of Connected Components in very layman’s terms as a sort of a hard clustering algorithm which finds clusters/islands in related/connected data. As a concrete example: Say you have data about roads joining any two cities in the world. And you need to find out all the continents in the world and which city they contain. How will you achieve that? Come on give some thought. The connected components algorithm that we use to do this is based on a special case of BFS/DFS. I won’t talk much about how it works here, but we will see how to get the code up and running using Networkx . Applications From a Retail Perspective: Let us say, we have a lot of customers using a lot of accounts. One way in which we can use the Connected components algorithm is to find out distinct families in our dataset. We can assume edges(roads) between CustomerIDs based on same credit card usage, or same address or same mobile number, etc. Once we have those connections, we can then run the connected component algorithm on the same to create individual clusters to which we can then assign a family ID. We can then use these family IDs to provide personalized recommendations based on family needs. We can also use this family ID to fuel our classification algorithms by creating grouped features based on family. From a Finance Perspective: Another use case would be to capture fraud using these family IDs. If an account has done fraud in the past, it is highly probable that the connected accounts are also susceptible to fraud. The possibilities are only limited by your own imagination. Code We will be using the Networkx module in Python for creating and analyzing our graphs. Let us start with an example graph which we are using for our purpose. Contains cities and distance information between them. Graph with Some random distances We first start by creating a list of edges along with the distances which we will add as the weight of the edge: edgelist = [['Mannheim', 'Frankfurt', 85], ['Mannheim', 'Karlsruhe', 80], ['Erfurt', 'Wurzburg', 186], ['Munchen', 'Numberg', 167], ['Munchen', 'Augsburg', 84], ['Munchen', 'Kassel', 502], ['Numberg', 'Stuttgart', 183], ['Numberg', 'Wurzburg', 103], ['Numberg', 'Munchen', 167], ['Stuttgart', 'Numberg', 183], ['Augsburg', 'Munchen', 84], ['Augsburg', 'Karlsruhe', 250], ['Kassel', 'Munchen', 502], ['Kassel', 'Frankfurt', 173], ['Frankfurt', 'Mannheim', 85], ['Frankfurt', 'Wurzburg', 217], ['Frankfurt', 'Kassel', 173], ['Wurzburg', 'Numberg', 103], ['Wurzburg', 'Erfurt', 186], ['Wurzburg', 'Frankfurt', 217], ['Karlsruhe', 'Mannheim', 80], ['Karlsruhe', 'Augsburg', 250],["Mumbai", "Delhi",400],["Delhi", "Kolkata",500],["Kolkata", "Bangalore",600],["TX", "NY",1200],["ALB", "NY",800]] Let us create a graph using Networkx : g = nx.Graph() for edge in edgelist: g.add_edge(edge[0],edge[1], weight = edge[2]) Now we want to find out distinct continents and their cities from this graph. We can now do this using the connected components algorithm as: for i, x in enumerate(nx.connected_components(g)): print("cc"+str(i)+":",x) ------------------------------------------------------------ cc0: {'Frankfurt', 'Kassel', 'Munchen', 'Numberg', 'Erfurt', 'Stuttgart', 'Karlsruhe', 'Wurzburg', 'Mannheim', 'Augsburg'} cc1: {'Kolkata', 'Bangalore', 'Mumbai', 'Delhi'} cc2: {'ALB', 'NY', 'TX'} As you can see we are able to find distinct components in our data. Just by using Edges and Vertices. This algorithm could be run on different data to satisfy any use case that I presented above.
https://towardsdatascience.com/data-scientists-the-five-graph-algorithms-that-you-should-know-30f454fa5513
['Rahul Agarwal']
2020-09-11 11:58:49.065000+00:00
['Machine Learning', 'Artificial Intelligence', 'Visualization', 'Data Science', 'Programming']
Title Data Scientists 5 Graph Algorithms knowContent 1 Connected Components graph 3 connected component know clustering work think Connected Components layman’s term sort hard clustering algorithm find clustersislands relatedconnected data concrete example Say data road joining two city world need find continent world city contain achieve Come give thought connected component algorithm use based special case BFSDFS won’t talk much work see get code running using Networkx Applications Retail Perspective Let u say lot customer using lot account One way use Connected component algorithm find distinct family dataset assume edgesroads CustomerIDs based credit card usage address mobile number etc connection run connected component algorithm create individual cluster assign family ID use family IDs provide personalized recommendation based family need also use family ID fuel classification algorithm creating grouped feature based family Finance Perspective Another use case would capture fraud using family IDs account done fraud past highly probable connected account also susceptible fraud possibility limited imagination Code using Networkx module Python creating analyzing graph Let u start example graph using purpose Contains city distance information Graph random distance first start creating list edge along distance add weight edge edgelist Mannheim Frankfurt 85 Mannheim Karlsruhe 80 Erfurt Wurzburg 186 Munchen Numberg 167 Munchen Augsburg 84 Munchen Kassel 502 Numberg Stuttgart 183 Numberg Wurzburg 103 Numberg Munchen 167 Stuttgart Numberg 183 Augsburg Munchen 84 Augsburg Karlsruhe 250 Kassel Munchen 502 Kassel Frankfurt 173 Frankfurt Mannheim 85 Frankfurt Wurzburg 217 Frankfurt Kassel 173 Wurzburg Numberg 103 Wurzburg Erfurt 186 Wurzburg Frankfurt 217 Karlsruhe Mannheim 80 Karlsruhe Augsburg 250Mumbai Delhi400Delhi Kolkata500Kolkata Bangalore600TX NY1200ALB NY800 Let u create graph using Networkx g nxGraph edge edgelist gaddedgeedge0edge1 weight edge2 want find distinct continent city graph using connected component algorithm x enumeratenxconnectedcomponentsg printccstrix cc0 Frankfurt Kassel Munchen Numberg Erfurt Stuttgart Karlsruhe Wurzburg Mannheim Augsburg cc1 Kolkata Bangalore Mumbai Delhi cc2 ALB NY TX see able find distinct component data using Edges Vertices algorithm could run different data satisfy use case presented aboveTags Machine Learning Artificial Intelligence Visualization Data Science Programming
2,809
Increasing Personal Productivity During Distance Learning
Increasing Personal Productivity During Distance Learning 6 tips for getting your work done with kids at home Image of the author’s “office” provided by the author This was my year to finally hit some writing goals for myself. My youngest is going to full-day kindergarten and for the first time in 9 years I was going to have large portions of time to myself to knock things off my to-do list. Having my last baby go to school full-time was definitely bitter sweet. Last year, I began dreaming about how I was going to use this time. Other than the never ending chores and errands, I was going to dedicate days on my calendar for writing. If I could get away with it, I was going to dedicate a portion of everyday to my writing. But thanks to the pandemic, my kids are all distance learning from home and my husband has been working from his home office since March. Having five other people home means my house is never quiet. While each child has their own space for their school time, they all have different schedules so when one is on break, another is still in class. My makeshift office has always been the kitchen table. But since I was only able to dedicate 1–2 hours two days a week to my writing, it has never been an issue. Now, my “office” is at the end of the couch next to my kindergartener’s dedicated learning space. She’s fairly independent, but as she reminds me, she can’t read yet so I still have to help her navigate getting online for her class. I thought this set up was going to put a damper on my writing goals. Everyone else had a dedicated desk space, but me. But I have found that sitting next to her has actually made me more productive! How is that possible? Have you ever heard that adage from Lucille Ball: If you want to get something done, ask a busy person. I’ve always wondered if it’s true, but if you look at anyone who volunteers or those who are on several committees at work, it’s totally true. It also seems like it’s the same 5–7 people doing several different jobs. But they have learned to time manage effectively. When I became a stay at home mom there were months where I was busier and worked more than when I was working full time as a teacher. I was volunteering weekly at my children’s schools and their after school activities. My day started before theirs and often times ended well past a typical duty day if I was working a traditional 9–5 job. So here we are four weeks into the school year and in my makeshift office at the end of the couch I have cranked out more stories than I thought possible. I know that I only have x amount of minutes to get anything written before any of my four children are on a break. Even as I write this my teenager has just approached me talking to me about assignments and grades. Sometimes my children flit in and out of my peripheral vision to share something about their day and then move along before I can look up. So how do I do it? How do I write while juggling 4 children’s schedules and their various breaks? How is it possible to get anything one with someone always vying for my attention? Here’s what I do: I write in time chunks. I write for 15 minutes at a time and take a break if needed. If no one needs my attention right away I keep writing until someone asks for my attention. 15 minutes seems like a short amount of time, but it’s dedicated time. I’m not wandering aimlessly on the internet. I know it’s just a matter of time that I have to stop, so I write as much as I can in the time given to me. I take a lunch break when my children take their lunch/wellness break. It does force me to stop what I’m doing, clear the brain, and talk about something other than what I’ve been writing. When lunch is over and everyone is back at their desk, so am I. Surprisingly, it works. I know that I only have another small chunk of time before someone asks me for something. I dedicate time to work when my children are working. I could probably get other things done, but I’m treating this writing gig as a job despite the lack of a real office or office hours. So if they’re working, so am I. I put an imaginary do not disturb sign on my laptop and get my work done. I don’t answer superfluous texts, emails, or the rare phone call that do not pertain to the work I’m doing at that moment in time. I’ll spend an hour after my work day to do that. I don’t have time to waste. If I waste it on something other than my work, I don’t have time to go back to my writing until the kids are in bed or until the next day when they are back in school. Honestly, I am just too darn tired to go back to it at night. Once upon a time I was a night owl and I could be uber productive after dinner. But then kids happened and that time is spent with them or making sure everyone has underwear for the next day. So there’s that. When school is over for the day is when the laundry, housekeeping, cooking, and other chores get done. The nice thing about the pandemic is that we have no where to go. No after school sports or after school clubs. Self quarantining does have it’s been benefits. Not a lot, but I’ll take what I can get. Creating boundaries. Working at home and working in close proximity to my children at all times means I have to create boundaries. Because I’m not behind a close door, like my husband, doesn’t mean I’m immediately available. This has made my children more independent. If they see my fingers flying over the keyboards or if I put my finger up as they approach me with a question or comment, they’ll wait. I try to take up every second of that 15 minutes block to get down my thoughts. It has made them more patient and more independent. They have found that they don’t need me for every.blessed.thing and that’s okay. I don’t always finish my sentences. This is a tip I learned from Stephen King’s book On Writing. He suggests letting a sentence hang there and later when he gets back to it he has jumping off point to begin again. When my timer goes off and my children need me, I actually leave off my sentence and attend to them. When I come back to my piece, I reread and sometimes I find a new trajectory or a better ending for that sentence. I know that this isn’t possible for everyone and every situation, but for writing, give this one a try and see how it works for you. When I found that we were going into distance learning with the kids, I was mourning the loss of having time to myself to get things done. I honestly thought I would have to put off being productive in my writing for yet another year. My husband’s job isn’t flexible. When he’s in a meeting, he is in a meeting and no one can interrupt. I had no idea how many meetings that man could have in a day and now I do. I’m glad that it’s him and not me. Yes, the kids are in school, but I’m constantly called away to help them print something, access technology, follow up on an assignment, or answer a random question. While more independent day by day, my kindergartner wants me working next to her while she’s online for her class. That has more to do with anxiety and that some personal health issues that have cropped up for me so she’s in this phase of always wanting mommy around. But now that we’ve found our groove, I am more productive in the last 4 weeks than I have been in the last 8 months. I can still get my work done while attending to all the ups and downs of distance learning. It is possible without neglecting my children or my work. I’m not so arrogant to think that these tips will work for everyone due to job expectations and the ages of the children at home. Take these tips with a grain of salt. I know that this does not take into account families with younger children at home. That’s another ball of wax, but doable, and requires a lot more maneuvering of the day. It doesn’t take into account if you are needed in meetings many hours throughout the day, like my husband. And if you’re a teacher working from home while your children are also distance learning, thank you for your dedication. You are a true superhero. But for the rest of us, it is possible to check off your work to-do list amidst the chaos of distance learning.
https://medium.com/home-sweet-home/increasing-personal-productivity-during-distance-learning-f43939a73679
['Heather Jauquet']
2020-09-23 13:36:22.036000+00:00
['Work Life Balance', 'Life Lessons', 'Writing', 'Productivity', 'Parenting']
Title Increasing Personal Productivity Distance LearningContent Increasing Personal Productivity Distance Learning 6 tip getting work done kid home Image author’s “office” provided author year finally hit writing goal youngest going fullday kindergarten first time 9 year going large portion time knock thing todo list last baby go school fulltime definitely bitter sweet Last year began dreaming going use time never ending chore errand going dedicate day calendar writing could get away going dedicate portion everyday writing thanks pandemic kid distance learning home husband working home office since March five people home mean house never quiet child space school time different schedule one break another still class makeshift office always kitchen table since able dedicate 1–2 hour two day week writing never issue “office” end couch next kindergartener’s dedicated learning space She’s fairly independent reminds can’t read yet still help navigate getting online class thought set going put damper writing goal Everyone else dedicated desk space found sitting next actually made productive possible ever heard adage Lucille Ball want get something done ask busy person I’ve always wondered it’s true look anyone volunteer several committee work it’s totally true also seems like it’s 5–7 people several different job learned time manage effectively became stay home mom month busier worked working full time teacher volunteering weekly children’s school school activity day started often time ended well past typical duty day working traditional 9–5 job four week school year makeshift office end couch cranked story thought possible know x amount minute get anything written four child break Even write teenager approached talking assignment grade Sometimes child flit peripheral vision share something day move along look write juggling 4 children’s schedule various break possible get anything one someone always vying attention Here’s write time chunk write 15 minute time take break needed one need attention right away keep writing someone asks attention 15 minute seems like short amount time it’s dedicated time I’m wandering aimlessly internet know it’s matter time stop write much time given take lunch break child take lunchwellness break force stop I’m clear brain talk something I’ve writing lunch everyone back desk Surprisingly work know another small chunk time someone asks something dedicate time work child working could probably get thing done I’m treating writing gig job despite lack real office office hour they’re working put imaginary disturb sign laptop get work done don’t answer superfluous text email rare phone call pertain work I’m moment time I’ll spend hour work day don’t time waste waste something work don’t time go back writing kid bed next day back school Honestly darn tired go back night upon time night owl could uber productive dinner kid happened time spent making sure everyone underwear next day there’s school day laundry housekeeping cooking chore get done nice thing pandemic go school sport school club Self quarantining it’s benefit lot I’ll take get Creating boundary Working home working close proximity child time mean create boundary I’m behind close door like husband doesn’t mean I’m immediately available made child independent see finger flying keyboard put finger approach question comment they’ll wait try take every second 15 minute block get thought made patient independent found don’t need everyblessedthing that’s okay don’t always finish sentence tip learned Stephen King’s book Writing suggests letting sentence hang later get back jumping point begin timer go child need actually leave sentence attend come back piece reread sometimes find new trajectory better ending sentence know isn’t possible everyone every situation writing give one try see work found going distance learning kid mourning loss time get thing done honestly thought would put productive writing yet another year husband’s job isn’t flexible he’s meeting meeting one interrupt idea many meeting man could day I’m glad it’s Yes kid school I’m constantly called away help print something access technology follow assignment answer random question independent day day kindergartner want working next she’s online class anxiety personal health issue cropped she’s phase always wanting mommy around we’ve found groove productive last 4 week last 8 month still get work done attending ups down distance learning possible without neglecting child work I’m arrogant think tip work everyone due job expectation age child home Take tip grain salt know take account family younger child home That’s another ball wax doable requires lot maneuvering day doesn’t take account needed meeting many hour throughout day like husband you’re teacher working home child also distance learning thank dedication true superhero rest u possible check work todo list amidst chaos distance learningTags Work Life Balance Life Lessons Writing Productivity Parenting
2,810
Stumbling on the Happiness of Being Like Everyone Else
In some ways we realize we’re all very much alike. That’s why we can get behind big, bold statements like: “All men are created equal.” But research shows that regardless of IQ or education level, we are all susceptible to similar errors in our reasoning. As a result, most people believe they are the exceptions to the rule. Most overestimate their abilities and underestimate their weaknesses. Some researchers call this “illusory bias.” It reminds me of author William Saroyan’s statement: “Everyone has got to die, but I always thought an exception would be made in my case.” Daniel Gilbert’s, Stumbling on Happiness, brings to life the latest scientific research in psychology, cognitive neuroscience, philosophy, and behavioral economics. Gilbert reveals what scientists have discovered about the uniquely human ability to imagine the future, and about our capacity to predict how much we will like it when we get there. (Hint: we’re not very good.) He explains in detail the cognitive errors we make in trying to predict our future happiness. The greatest ability of the human brain is to imagine, to see the world as it has never been before. Our brains fall victim to biases that cause our predictions of the future, and our memories of the past, to be inaccurate. This leads to our fallibility and not being able to predict well what will make us happy. He also outlines one technique that has been effective in predicting future happiness, but then goes on to discuss the reason why the vast majority of humans won’t use it.
https://medium.com/big-self-society/stumbling-on-the-happiness-of-being-like-everyone-else-da087951fa08
['Chad Prevost']
2020-11-12 13:55:28.947000+00:00
['Authors', 'Books', 'Happiness', 'Psychology', 'Two Minute Takeaway']
Title Stumbling Happiness Like Everyone ElseContent way realize we’re much alike That’s get behind big bold statement like “All men created equal” research show regardless IQ education level susceptible similar error reasoning result people believe exception rule overestimate ability underestimate weakness researcher call “illusory bias” reminds author William Saroyan’s statement “Everyone got die always thought exception would made case” Daniel Gilbert’s Stumbling Happiness brings life latest scientific research psychology cognitive neuroscience philosophy behavioral economics Gilbert reveals scientist discovered uniquely human ability imagine future capacity predict much like get Hint we’re good explains detail cognitive error make trying predict future happiness greatest ability human brain imagine see world never brain fall victim bias cause prediction future memory past inaccurate lead fallibility able predict well make u happy also outline one technique effective predicting future happiness go discus reason vast majority human won’t use itTags Authors Books Happiness Psychology Two Minute Takeaway
2,811
How we can easily stop plastic waste now
Swimming in a sea of plastic (Source: Fabbaloo) Ok. So by now it’s pretty clear to most people that we have a plastic problem. Our oceans are literally swimming in plastic. The question is: what can we do about it? There is a fairly simple solution. But before we get to the solution, we need to understand the problem and how we got here. The problem Out of the 8.3 billion metric tons of plastic ever produced only 9% is recycled. More recently that figure is about 14% but the fact is that even when the intentions are good, we are terrible at recycling plastics still poses big challenges. For simplicity, we will focus on single-use plastic water bottles but many other plastics such as bags, cigarette buts, diapers, food packaging, other beverages, microbeads from clothes, etc. are equally important. A clear example: Bottled water The bottled water market globally keeps growing with an approximate 600 million households now consuming bottled water. In 2017 the bottled water market reached a volume of 391 billion litres after growing at an average of 6% per year during 2009–2016. At the current rate of growth, 90 million more homes will consume bottled water by 2022. Table: Bottled water consumption worldwide * Households with access to electricity and water (WHO) ** Estimates based on population and bottled water consumption. In some cases, it may include large bottles that are refilled. Assuming that each household consumes about 2 bottles per day on average this means 576 million x 365 = 210 billion bottles per year. This aligns pretty well with the estimate of a total of 480 billion plastic bottles consumed annually whereof 50% are water. Gobal annual bottled water consumption in millions of tons of plastic Why are so many people drinking bottled water? During the past 30 years, tap water quality in Europe and North America vastly improved both in terms of taste and quality. Despite this, bottled water consumption went from zero to the staggering numbers above. The main reasons cited by consumers are: Prefer the taste of bottled water Concerned about the quality and health impact of tap water Replacing sugary beverages Convenience of bottled water In addition to this, the bottled water industry has actively been promoting the health benefits of mineral and spring water for many years. Due to this almost half of the population believe bottled water is healthier than tap water. How can we solve this? There are many very challenging problems in the world such as climate change, inequality and terrorism that are extremely difficult to solve. Bottled water is not one of them. As a matter of fact, bottled water is completely unnecessary for most households. In North America and Europe more than 95% households have access to clean tap water. In many other areas of the world with access to tap water, it can easily be made safe with an affordable filter. Despite this too many homes choose bottled water due to taste preference or misinformed health concerns. Governments have a responsibility to educate people and provide guidelines on solutions for drinking water just like they do for recycling, water consumption, alcohol and general health. This includes informing people about the problems bottled water is causing in terms of transportation, waste and plastic pollution and provide alternatives. For low- income families it may even be advisable to subsidise solutions for clean drinking water. With education and water filters everyone can safely drink tap water What’s next? With the help of education and regulation Europe and North America could cut bottled water consumption by at least 75% in just a couple of years limiting most consumption to sparkling mineral water served on glass bottles. China, India, Mexico and Indonesia that are big consumers of bottled water can do the same, although the quality of local tap water requires more stringent regulation of water filters. The money saved by consumers will go to other consumption and thus creating new jobs replacing the bottled water industry. If we do the same thing for all the major groups of single-use plastics, then plastic waste can be vastly reduced as an issue. What are we waiting for? Let’s start lobbying family, friends and politicians now! Disclaimer: I’m Co-founder of TAPP Water with a mission to provide easy and affordable solutions for clean and environmentally friendly water. Sources: Ellen MacArthur Foundation — 2017 Study on plastic production and recycling National Geographics -Plastic Produced Recycling Waste Ocean Trash 2017 Forbes — 1 million bottles per minute and 91% not recycled
https://medium.com/hackernoon/how-we-can-easily-stop-plastic-waste-now-16107096a841
['Magnus Jern']
2018-10-01 10:51:11.871000+00:00
['Plastic Pollution', 'Sustainability', 'Recycling', 'Environment', 'Water']
Title easily stop plastic waste nowContent Swimming sea plastic Source Fabbaloo Ok it’s pretty clear people plastic problem ocean literally swimming plastic question fairly simple solution get solution need understand problem got problem 83 billion metric ton plastic ever produced 9 recycled recently figure 14 fact even intention good terrible recycling plastic still pose big challenge simplicity focus singleuse plastic water bottle many plastic bag cigarette buts diaper food packaging beverage microbeads clothes etc equally important clear example Bottled water bottled water market globally keep growing approximate 600 million household consuming bottled water 2017 bottled water market reached volume 391 billion litre growing average 6 per year 2009–2016 current rate growth 90 million home consume bottled water 2022 Table Bottled water consumption worldwide Households access electricity water Estimates based population bottled water consumption case may include large bottle refilled Assuming household consumes 2 bottle per day average mean 576 million x 365 210 billion bottle per year aligns pretty well estimate total 480 billion plastic bottle consumed annually whereof 50 water Gobal annual bottled water consumption million ton plastic many people drinking bottled water past 30 year tap water quality Europe North America vastly improved term taste quality Despite bottled water consumption went zero staggering number main reason cited consumer Prefer taste bottled water Concerned quality health impact tap water Replacing sugary beverage Convenience bottled water addition bottled water industry actively promoting health benefit mineral spring water many year Due almost half population believe bottled water healthier tap water solve many challenging problem world climate change inequality terrorism extremely difficult solve Bottled water one matter fact bottled water completely unnecessary household North America Europe 95 household access clean tap water many area world access tap water easily made safe affordable filter Despite many home choose bottled water due taste preference misinformed health concern Governments responsibility educate people provide guideline solution drinking water like recycling water consumption alcohol general health includes informing people problem bottled water causing term transportation waste plastic pollution provide alternative low income family may even advisable subsidise solution clean drinking water education water filter everyone safely drink tap water What’s next help education regulation Europe North America could cut bottled water consumption least 75 couple year limiting consumption sparkling mineral water served glass bottle China India Mexico Indonesia big consumer bottled water although quality local tap water requires stringent regulation water filter money saved consumer go consumption thus creating new job replacing bottled water industry thing major group singleuse plastic plastic waste vastly reduced issue waiting Let’s start lobbying family friend politician Disclaimer I’m Cofounder TAPP Water mission provide easy affordable solution clean environmentally friendly water Sources Ellen MacArthur Foundation — 2017 Study plastic production recycling National Geographics Plastic Produced Recycling Waste Ocean Trash 2017 Forbes — 1 million bottle per minute 91 recycledTags Plastic Pollution Sustainability Recycling Environment Water
2,812
Food Waste Economics
HOW FOOD IS WASTED People waste food at four levels: producer, distributor, seller, and consumer. At these levels, three types of food get discarded: food gone bad, food we think is bad, and food we know is still consumable, but we don’t want. 1. LOST IN TRANSIT When genuinely non-consumable food is thrown away, it is usually because problems in packaging, storage, and transportation at the production level and consumers and sellers stocking more than needed. For the average US household, approximately $2200 of food is tossed- roughly a fifth of goods in every consumer’s shopping cart. Surprisingly, actually bad food is the smallest margin of food wasted. On average, 90% of tossed food can still be safely eaten. 2. OVEREMPHASIZED EXPIRATION DATES AND APPEARANCES The largest category of food trash is food we think is bad, but could actually still be consumed. This comes down to aesthetics and expiration dates. First, aesthetically, producers and sellers are hesitant to deal with misshapen or bruised goods, even if they’re still eatable. At the retail level, there is an emphasis on all individual products looking homogeneous. So, when an item is perceived as a distorted, such as a two-bodied pear, it won’t make the market shelves. Tacked on to this, there is hesitation to consume food that looks slightly bruised or is past its sell-by date. However, when it comes to bruises on produce, damaged boxes, or passed sell-by dates, it often only indicates a decrease in quality- not in-edibility. Thus, the items are tossed. 3. LEFTOVERS Lastly, when we throw away food we know is still good, but we simply don’t want, it is often because the time, resources, and money needed to donate the food or transport it to someone who would eat the food outweighs what we believe the possible good to be. For sellers in particular, companies like Walmart recognize that it is more cost efficient to throw away the good than to spend money on a driver to transport the food to a homeless shelter.
https://christinagayton.medium.com/food-waste-economics-f3176cfaeb1a
['Christina Gayton']
2018-12-29 14:55:39.076000+00:00
['Economy', 'Economics', 'Sustainability', 'Environment', 'Food']
Title Food Waste EconomicsContent FOOD WASTED People waste food four level producer distributor seller consumer level three type food get discarded food gone bad food think bad food know still consumable don’t want 1 LOST TRANSIT genuinely nonconsumable food thrown away usually problem packaging storage transportation production level consumer seller stocking needed average US household approximately 2200 food tossed roughly fifth good every consumer’s shopping cart Surprisingly actually bad food smallest margin food wasted average 90 tossed food still safely eaten 2 OVEREMPHASIZED EXPIRATION DATES APPEARANCES largest category food trash food think bad could actually still consumed come aesthetic expiration date First aesthetically producer seller hesitant deal misshapen bruised good even they’re still eatable retail level emphasis individual product looking homogeneous item perceived distorted twobodied pear won’t make market shelf Tacked hesitation consume food look slightly bruised past sellby date However come bruise produce damaged box passed sellby date often indicates decrease quality inedibility Thus item tossed 3 LEFTOVERS Lastly throw away food know still good simply don’t want often time resource money needed donate food transport someone would eat food outweighs believe possible good seller particular company like Walmart recognize cost efficient throw away good spend money driver transport food homeless shelterTags Economy Economics Sustainability Environment Food
2,813
When Your Calling Seems Vague and Unclear, You’re on the Right Track
Lesson 2: Just Because It’s Hard Doesn’t Mean You Should Quit “We are what we repeatedly do. Excellence, then, is not an act, but a habit.” —Aristotle I’m wary of people who can name their dream immediately without having had any real experience with it. The flame that is fast to light is also the quickest to burn out. Although you occasionally encounter rare cases of people knowing what they were meant to do since childhood, most struggle with the clarity concept. But what if we at least temporarily disregarded it? Often, I hear people tell me they would gladly follow their passions in life, if they just knew what they were. Or they have too many interests in life and don’t know which one to focus on. So where do you start? Instead of following your passion, as Cal Newport says, maybe you should let your passion follow you. We all tend to enjoy activities we’re good at and shy away from the things we’re not. So if you don’t have something like that, don’t wait for passion. Just get so good that the enjoyment soon follows. And if it doesn’t, you can always pick something else. Naming and claiming a dream is a popular trend these days. What’s far less popular is the disciplined practice of a craft — spending thousands of thankless hours getting great at something before sharing it with the world. If you tell me, “I want to be an author” but have never written a word, I’m skeptical. If you say, “I was born to be a carpenter” but have never lifted a hammer, I’m doubtful. You may like the idea of being a writer or the image of being on a construction project, but you haven’t done any actual work. You don’t understand the cost of the dream, of putting yourself out there and risking failure. Therefore, it has no real value to you. You have to practice. But not all practice is equal. In fact, most people have no idea how to do something with excellence, which is little wonder why we drift from one meaningless job to the next. Maybe what we need is not less work and more four-hour work weeks, but instead the kind of practice that demands our total presence and most serious attitude. This is what Daniel Coyle, author of The Talent Code, calls “deep practice.” It is the kind of activity that requires all your strength and attention but also ends up being the most fulfilling thing you could possibly do. No, it isn’t always easy, but since when did your calling have to come easy? And if you choose to wait, to bide your time before beginning to figure out what you were meant to do with your life, well, that’s a form of practice, too.
https://medium.com/better-humans/when-your-calling-seems-vague-and-unclear-you-re-on-the-right-track-816cfddb2450
['Jeff Goins']
2019-12-10 01:46:34.378000+00:00
['Self Improvement', 'Work', 'Entrepreneurship', 'Careers', 'Productivity']
Title Calling Seems Vague Unclear You’re Right TrackContent Lesson 2 It’s Hard Doesn’t Mean Quit “We repeatedly Excellence act habit” —Aristotle I’m wary people name dream immediately without real experience flame fast light also quickest burn Although occasionally encounter rare case people knowing meant since childhood struggle clarity concept least temporarily disregarded Often hear people tell would gladly follow passion life knew many interest life don’t know one focus start Instead following passion Cal Newport say maybe let passion follow tend enjoy activity we’re good shy away thing we’re don’t something like don’t wait passion get good enjoyment soon follows doesn’t always pick something else Naming claiming dream popular trend day What’s far le popular disciplined practice craft — spending thousand thankless hour getting great something sharing world tell “I want author” never written word I’m skeptical say “I born carpenter” never lifted hammer I’m doubtful may like idea writer image construction project haven’t done actual work don’t understand cost dream putting risking failure Therefore real value practice practice equal fact people idea something excellence little wonder drift one meaningless job next Maybe need le work fourhour work week instead kind practice demand total presence serious attitude Daniel Coyle author Talent Code call “deep practice” kind activity requires strength attention also end fulfilling thing could possibly isn’t always easy since calling come easy choose wait bide time beginning figure meant life well that’s form practice tooTags Self Improvement Work Entrepreneurship Careers Productivity
2,814
Java + Python = Jython?
Java + Python = Jython? Yes, this is legit Photo by Tracy Adams on Unsplash The Story A couple of weeks ago, I was working on a Java application that creates directories and files based on the parameters given. Like with all of my applications, I want to know what’s going on while they are running. This got me thinking about my previous article that talked about a small logging module I wrote in Python. This module contains different levels for logging that get inserted into a database. The problem is that it was written in Python and that obviously doesn’t mix with Java. Or does it? It took less than five minutes of googling, to discover Jython. In a nutshell, Jython is an implementation of Python that runs on Java. For the most part, it is compatible with Python 2.7. Keep in mind that Python 2.7 is no longer receiving support, but the Jython team is working to get it compatible with Python 3. The Struggles Initially, I was hoping to leverage the Python logging class that I had already written. Essentially, this would require importing the module, creating a class object, and then calling one of the class functions (Depending on which level of logging I wanted to do). It would have looked like something similar to this: from my_logger import MyLogger myLogger = MyLogger("project_creator", "mysql://<USER>:<PASSWORD>@<HOST>/<DATABASE>") myLogger.LogInfo("This is some logging information.") Using Jython, this would loosely translate to: PythonInterpreter interp = new PythonInterpreter(); interp.exec("from my_logger import MyLogger"); PyInstance loggingObject = (PyInstance)interp.eval("MyLogging('project_creator', 'mysql://<USER>:<PASSWORD>@<HOST>/<DATABASE>')"); System.out.println(loggingObject.invoke("LogInfo()").__tojava__(String.class)); Writing the Java code seemed fairly quick and easy. With my hopes high, I started researching what needs to be done to get this project to build and run. It was after quite a lot of time and experimenting where I realized that my original plan wasn’t going to work. Before I realized this, I needed to get Jython installed first. Ubuntu has a package in its store called Jython that can be used. However, this package is for Jython 2.5. All of the modern documentation recommends downloading the Jython 2.7 installer which will give you the most recent version. Once downloaded, to run the installer: java -jar jython-installer-2.7.2.jar Selecting the second option which is the Standard edition will install the .jar file that you need along with demos and documentation. I tried the ninth option, which is supposed to install just the .jar file failed during installation every time I tried. While installing, you will be prompted to specify which directory you want the .jar file to install to. Once installed, I was able to run this command that, in theory, would build my Java application: javac -cp ~/jython/jython.jar jythontest/*.java Unfortunately, that was wishful thinking. It was here that I started seeing errors for missing Python modules. After more research, I learned that I need to install the missing modules for Jython using the .jar file that I installed. Normal Python uses “pip” to install packages. From the research, I’ve done, Jython did have something called “jip”, but documentation for that is scarce. It was a little bit of a pain, but I had to download the missing modules from PyPi and unzip them. The unzipped module directories contain a setup.py file Using a command similar to this, I was able to install them: java -jar ~/jython/jython.jar setup.py install All seemed well until I tried building the project for a second time. Again, it was another missing module (_mysql to be exact). This led to another round of research as to why my project wouldn’t build. As it turns out, the driver in the connection string I was using for SQLAlchemy was causing the issue. Since Jython was built using Java, it relies on the JDBC for connections to MySQL. In short, the JDBC (Java Database Connectivity)is an API (Application Programming Interface)that tells the client how it can connect to a database. JayDeBeApi and zxJDBC are a couple of modules that could be used to fix the problem, however, they don’t mix well with SQLAlchemy’s create_engine() function. By this, I mean when I tried using the recommended driver, “jdbc:mysql”, that the function fails to parse the URL. This is probably because these modules construct the connection in a different way than SQLAlchemy and are more designed for parameterized querying. The last hope that I had was in the documentation found here. Reading through, it was very detailed and well written. There is an SQLAlchemy example, but it’s connecting to an Oracle database using the module zxoracle. After another trip to Google to look for something similar, I came across the Github repo for zxoracle. Scanning through this code, I think it would be possible to modify this code to be used for MySQL. In the end, I decided that I needed to alter the course I was taking with this project. The Solution It wasn’t an easy decision by any means to change the implementation plan. Instead of importing the logging class and calling its functions, I decided to create an API for the logging class and create a client class that Jython will use. Since I already intended on making an API for logging, this wasn’t any extra work. Below is what the client class looked like and the Jython code in Java to call it: Looking at the client.py file, a very simple function was written that creates a POST request that gets sent to the logging API. A dictionary that contains the application name, log message, and log event type gets sent along with the request. The Jython code in jython.java admittedly looks a little weird. What it basically does is import the Python file, create a function object, and pass the necessary parameters to that function. Just like earlier, the command I had to run that builds the Java project was: javac -cp ~/jython/jython.jar jythontest/*.java At last, I was finally able to build without getting any errors. To run the project, this command was used. Note that because my project required command-line parameters, it was necessary to add it in (the part that says “python”). java -cp ~/jython/jython.jar:. jythontest.StartingPoint “python” Once the project had finished running, I checked the database to make sure my log event had been inserted. I think it was safe to say that at this point, I finally had a working project. Final Thoughts Reflecting on the events that occurred while trying to get the project to work, made me realize that maybe Jython isn’t the approach I’m looking for. On previous Java projects, I used the ProcessBuilder class to run all sorts of scripts. I am also very aware that Python has its own methods for calling APIs. I guess I was just hoping that Jython would save me a little more development time. In the end, I don’t regret the experience I obtained. If you happen to know what I did wrong while trying to get the SQLAlchemy driver to work, or notice any other mistakes I might have made, feel free to leave a comment. Happy coding and cheers!
https://medium.com/python-in-plain-english/java-python-jython-f887b356a92e
['Mike Wolfe']
2020-10-11 08:37:19.495000+00:00
['API', 'MySQL', 'Java', 'Python', 'Sql']
Title Java Python JythonContent Java Python Jython Yes legit Photo Tracy Adams Unsplash Story couple week ago working Java application creates directory file based parameter given Like application want know what’s going running got thinking previous article talked small logging module wrote Python module contains different level logging get inserted database problem written Python obviously doesn’t mix Java took le five minute googling discover Jython nutshell Jython implementation Python run Java part compatible Python 27 Keep mind Python 27 longer receiving support Jython team working get compatible Python 3 Struggles Initially hoping leverage Python logging class already written Essentially would require importing module creating class object calling one class function Depending level logging wanted would looked like something similar mylogger import MyLogger myLogger MyLoggerprojectcreator mysqlUSERPASSWORDHOSTDATABASE myLoggerLogInfoThis logging information Using Jython would loosely translate PythonInterpreter interp new PythonInterpreter interpexecfrom mylogger import MyLogger PyInstance loggingObject PyInstanceinterpevalMyLoggingprojectcreator mysqlUSERPASSWORDHOSTDATABASE SystemoutprintlnloggingObjectinvokeLogInfotojavaStringclass Writing Java code seemed fairly quick easy hope high started researching need done get project build run quite lot time experimenting realized original plan wasn’t going work realized needed get Jython installed first Ubuntu package store called Jython used However package Jython 25 modern documentation recommends downloading Jython 27 installer give recent version downloaded run installer java jar jythoninstaller272jar Selecting second option Standard edition install jar file need along demo documentation tried ninth option supposed install jar file failed installation every time tried installing prompted specify directory want jar file install installed able run command theory would build Java application javac cp jythonjythonjar jythontestjava Unfortunately wishful thinking started seeing error missing Python module research learned need install missing module Jython using jar file installed Normal Python us “pip” install package research I’ve done Jython something called “jip” documentation scarce little bit pain download missing module PyPi unzip unzipped module directory contain setuppy file Using command similar able install java jar jythonjythonjar setuppy install seemed well tried building project second time another missing module mysql exact led another round research project wouldn’t build turn driver connection string using SQLAlchemy causing issue Since Jython built using Java relies JDBC connection MySQL short JDBC Java Database Connectivityis API Application Programming Interfacethat tell client connect database JayDeBeApi zxJDBC couple module could used fix problem however don’t mix well SQLAlchemy’s createengine function mean tried using recommended driver “jdbcmysql” function fails parse URL probably module construct connection different way SQLAlchemy designed parameterized querying last hope documentation found Reading detailed well written SQLAlchemy example it’s connecting Oracle database using module zxoracle another trip Google look something similar came across Github repo zxoracle Scanning code think would possible modify code used MySQL end decided needed alter course taking project Solution wasn’t easy decision mean change implementation plan Instead importing logging class calling function decided create API logging class create client class Jython use Since already intended making API logging wasn’t extra work client class looked like Jython code Java call Looking clientpy file simple function written creates POST request get sent logging API dictionary contains application name log message log event type get sent along request Jython code jythonjava admittedly look little weird basically import Python file create function object pas necessary parameter function like earlier command run build Java project javac cp jythonjythonjar jythontestjava last finally able build without getting error run project command used Note project required commandline parameter necessary add part say “python” java cp jythonjythonjar jythontestStartingPoint “python” project finished running checked database make sure log event inserted think safe say point finally working project Final Thoughts Reflecting event occurred trying get project work made realize maybe Jython isn’t approach I’m looking previous Java project used ProcessBuilder class run sort script also aware Python method calling APIs guess hoping Jython would save little development time end don’t regret experience obtained happen know wrong trying get SQLAlchemy driver work notice mistake might made feel free leave comment Happy coding cheersTags API MySQL Java Python Sql
2,815
A World Without Climate Role Models — 5 Years After the Paris Agreement
In response to many commemorative and reflective discussions taking place to mark the 5th anniversary of the Paris Agreement, Greta Thunberg boldly accused national and international leaders of creating “distant hypothetical targets” and “new loopholes with empty words,” ultimately falling short of every uttered promise. With no intention of completely nullifying the attempts at the progress that has been made, I agree with her remarks. While electoral politics is inherently geared toward alleviating immediate concerns, governments have an obligation to anticipate future adversity, especially perils so clearcut as the ramifications of climate change. We stand in a situation now where these consequences are already perceptible and worsening. And yet, five years after the signing of the Paris Agreement, there are no global role models on climate change action. Only Morocco and the Gambia are on track for meeting the 1.5 degree Celsius limit set forth in this agreement meant to hold nations accountable for their actions. But the young activist was also correct to implore for our optimism and for a fervent, unbending commitment to making climate change mitigation and transitions toward a more sustainable global society our highest priority. All along, I have believed that the engagement of individuals and communities in the discussions concerning how to address the climate crisis will be imperative to ensure that appropriate action is actually taken in order to curb emissions and establish sustainable solutions moving forward. Without awareness of the current and imposing ramifications of global warming continually incurred with our inaction, and the daunting facts held secret for many years that human action is to blame, any number of other misfortunes, more paramount at the moment, will claim the position of highest salience. Rapid transitions without the will to adopt greener technology and more sustainable solutions will inevitably feel like some form of loss. But long, drawn-out problems — such as systemic racism, gender inequality, and, naturally, climate change — demand enduring commitments. Often we complain about an absence in political will when we ourselves remain confined to past traditions and resistant to change. Governments will move forward with climate action more aggressively when we push them to do so. So engage in discussion with your climate change-denying father and choose to eat plant-based even when it annoys your friends; speak as loudly as you can and listen to your Mother.
https://medium.com/climate-conscious/a-world-without-climate-role-models-5-years-after-the-paris-agreement-4a7de84ac1d6
['Amanda Hanemaayer']
2020-12-20 17:55:52.768000+00:00
['Environment', 'Climate Action', 'Sustainability', 'Awareness', 'Learning']
Title World Without Climate Role Models — 5 Years Paris AgreementContent response many commemorative reflective discussion taking place mark 5th anniversary Paris Agreement Greta Thunberg boldly accused national international leader creating “distant hypothetical targets” “new loophole empty words” ultimately falling short every uttered promise intention completely nullifying attempt progress made agree remark electoral politics inherently geared toward alleviating immediate concern government obligation anticipate future adversity especially peril clearcut ramification climate change stand situation consequence already perceptible worsening yet five year signing Paris Agreement global role model climate change action Morocco Gambia track meeting 15 degree Celsius limit set forth agreement meant hold nation accountable action young activist also correct implore optimism fervent unbending commitment making climate change mitigation transition toward sustainable global society highest priority along believed engagement individual community discussion concerning address climate crisis imperative ensure appropriate action actually taken order curb emission establish sustainable solution moving forward Without awareness current imposing ramification global warming continually incurred inaction daunting fact held secret many year human action blame number misfortune paramount moment claim position highest salience Rapid transition without adopt greener technology sustainable solution inevitably feel like form loss long drawnout problem — systemic racism gender inequality naturally climate change — demand enduring commitment Often complain absence political remain confined past tradition resistant change Governments move forward climate action aggressively push engage discussion climate changedenying father choose eat plantbased even annoys friend speak loudly listen MotherTags Environment Climate Action Sustainability Awareness Learning
2,816
Vegan for Keeps Submission Guidelines
Good work fueled by a Fair-Trade oat-milk dirty chai latte. Thanks for your interest in joining our community! What we are looking for: cultural criticism (particularly literary, extra-particularly #kidlit, which inspired the name of this publication), “white learning” and vegan-oriented social justice, reflections and experiments on personal growth and creativity through a vegan lens, interviews with vegan artists, veganized heirloom recipes, and plenty more that falls under the category of “we’ll love it when we see it.” cultural criticism (particularly literary, extra-particularly #kidlit, which inspired the name of this publication), “white learning” and vegan-oriented social justice, reflections and experiments on personal growth and creativity through a vegan lens, interviews with vegan artists, veganized heirloom recipes, and plenty more that falls under the category of “we’ll love it when we see it.” While we would be glad to publish your journey-to-veganism story, in order to write for us we ask that you be 100% committed to an ethical vegan lifestyle (meaning that you are all in for animal rights). If you’re “transitioning,” you can let us know when you’re actually vegan. If you’re “transitioning,” you can let us know when you’re actually vegan. We believe in excellent writers making an excellent livelihood, and that is why we suggest you pitch Tenderly first, since they are an official Medium publication (and as such can actually pay you beyond what you’ll make in the Medium Partner Program, which you should definitely sign up for before you start writing for us!) A further note on writers making more money: we’d be delighted to re-publish posts that originally appeared on your personal blog. Submissions should be free of grammatical and typographical errors. If we catch more than one, we’ll stop reading and ask you to revise and resubmit (ironic, yes, but like most editors these days, we do not have time to edit!) Do your utmost to write in accordance with Medium’s Curation Guidelines. To be added as a writer, simply leave a comment on this post to introduce yourself. Once added, you’ll be able to submit drafts for our consideration. We’ll be tweaking these guidelines over time, so do check back periodically. Feel free to comment or tweet to us with any questions you may have, and thanks again!
https://medium.com/vegan-for-keeps/vegan-for-keeps-submission-guidelines-138a4164a9c7
['Camille Deangelis']
2019-10-10 22:06:04.388000+00:00
['Animal Rights', 'Writing', 'Vegan', 'Veganism', 'Personal Growth']
Title Vegan Keeps Submission GuidelinesContent Good work fueled FairTrade oatmilk dirty chai latte Thanks interest joining community looking cultural criticism particularly literary extraparticularly kidlit inspired name publication “white learning” veganoriented social justice reflection experiment personal growth creativity vegan lens interview vegan artist veganized heirloom recipe plenty fall category “we’ll love see it” cultural criticism particularly literary extraparticularly kidlit inspired name publication “white learning” veganoriented social justice reflection experiment personal growth creativity vegan lens interview vegan artist veganized heirloom recipe plenty fall category “we’ll love see it” would glad publish journeytoveganism story order write u ask 100 committed ethical vegan lifestyle meaning animal right you’re “transitioning” let u know you’re actually vegan you’re “transitioning” let u know you’re actually vegan believe excellent writer making excellent livelihood suggest pitch Tenderly first since official Medium publication actually pay beyond you’ll make Medium Partner Program definitely sign start writing u note writer making money we’d delighted republish post originally appeared personal blog Submissions free grammatical typographical error catch one we’ll stop reading ask revise resubmit ironic yes like editor day time edit utmost write accordance Medium’s Curation Guidelines added writer simply leave comment post introduce added you’ll able submit draft consideration We’ll tweaking guideline time check back periodically Feel free comment tweet u question may thanks againTags Animal Rights Writing Vegan Veganism Personal Growth
2,817
How to feel like the King of the World
How to feel like the King of the World Top 5 Benefits of Cold Showers (and some tips to start) Photo from Xannah Xu on Unsplash There was a period in my life when I started doing challenges, one after another, constantly. Most of them just passed by, while some stayed. This one I never gave up on. Why? Because if you want to feel good and get out of your comfort zone cold showers could be the strongest practice you will ever find out there. I have been doing them daily for almost 3 months now: it is time I share with you the enormous benefits I got from it. You might be skeptical, I was, but you will never know until you will try, right? In the meantime, here are 5 benefits I got from cold showers. Hope you will reach the same results! 1. Cold showers make you feel like the king of the world The first benefit I noticed once I started taking cold showers was the amazing feeling I experienced once I finished. It is a mixture of joy and strength that I hardly could get from anywhere else: just amazing. The reason behind that feeling is a natural reaction of our body. As human beings we developed a strong resistance to cold temperature, hence overcoming that block will give you the impression you could defeat any obstacle on your way. Your decision to go under cold water is a conscious decision into stepping out of the comfort zone. By taking that step into the water, aware that it will hurt your comfort, you are taking a step into the unknown. Your body will never be prepared for what is coming. You will feel like you are taking part in a completely new fight, every time, winning it over and over again besides its harshnesses. This is exactly what will make you feel like the king of the world. Moreover, your decision will empower your resilience. How? Simple. Cold water will cause your body to produces eustress, which is the kind of stress that forces our mental health to get stronger. So, when you will get out of that shower, not only you will feel like the king of the world, but also your resilience will permanently improve. 2. Cold showers refill your energies and make you productive There are two types of energies you could get in your life: the one static and refreshing that comes from sleeping, and the one dynamic and explosive that you get from high impact activities, like jumping with a parachute. A cold shower is like jumping with a parachute in miniature, it is like bungee jumping with your eyes closed. You get a fast boost of that dynamic energy but staying in your bathroom, and you get it for free! One thing I experienced once I got out of the shower was exactly this enormous amount of rush power filling my body. Being under cold water for some minutes was recharging my brain and my muscles. Of course, it was less strong than jumping from a 20k feet height but still considerable. There is no other way you could get that adrenaline that simple. Moreover, that rush will make you feel the necessity of acting, the need of doing something, which might be very productive if you learn to use it properly. 3. Cold showers get you into a meditative state The first time I got under cold water I noticed how it built a block between me and the external world. My mind was completely erased, and all the thoughts that were draining me disappeared. I could not think about anything else but survival and, with a little effort, I could stop that too. Thus, the most important side benefit that you will get from cold showers is a deeper awareness of every inch of your body. At first, you will be able to distinguish between the parts of the skin exposed to the cold water and the relaxed ones. Then you will slowly become more conscious of your internal body by noticing how it fills up with air at every breath you take. This is exactly what you want to achieve with meditation: the mental clarity given by the absence of thoughts, and the mental embodiment given by a deeper comprehension of your body. 4. Cold showers make you reconnect to yourself When I first went under cold water I was so hyped by the benefits I did not think that much about how harsh could it be. The following repetitions were harder, but once you take that decision of going under you don’t come back. What happens next it’s the real challenge. Staying under the shower is a constant internal fight that makes you ultimately discover yourself on a deeper level. With time you will start to recognize which patterns your brain uses to get you out of danger, and which to keep you resistant. Being aware of the patterns that get you out of trouble is very important. First of all because you will recognize danger easier, and secondly you can stop your brain from overreacting in situations that are only apparently dangerous. 5. Cold showers improve your cold tolerance I remember when I moved out and I started living alone. I was economizing on the bills so the temperature in my house was very very low. I had to put always my sweater on and it was not that comfy. Then I started the cold shower challenge. After the first 30 days, I recognized how I was able to stay without any clothes on, at the same usual temperature, for around one hour, without feeling cold. Not only that, but also my general cold resistance improved, and I was able to remain in the house wearing just a simple T-shirt.
https://medium.com/get-better-togetter/cold-showers-how-to-feel-like-the-king-of-the-world-1c05f6cf2a23
['Cosmin Angheluta']
2020-05-16 15:10:17.798000+00:00
['Self-awareness', 'Self Improvement', 'Motivation', 'Cold Shower', 'Habit Building']
Title feel like King WorldContent feel like King World Top 5 Benefits Cold Showers tip start Photo Xannah Xu Unsplash period life started challenge one another constantly passed stayed one never gave want feel good get comfort zone cold shower could strongest practice ever find daily almost 3 month time share enormous benefit got might skeptical never know try right meantime 5 benefit got cold shower Hope reach result 1 Cold shower make feel like king world first benefit noticed started taking cold shower amazing feeling experienced finished mixture joy strength hardly could get anywhere else amazing reason behind feeling natural reaction body human being developed strong resistance cold temperature hence overcoming block give impression could defeat obstacle way decision go cold water conscious decision stepping comfort zone taking step water aware hurt comfort taking step unknown body never prepared coming feel like taking part completely new fight every time winning besides harshness exactly make feel like king world Moreover decision empower resilience Simple Cold water cause body produce eustress kind stress force mental health get stronger get shower feel like king world also resilience permanently improve 2 Cold shower refill energy make productive two type energy could get life one static refreshing come sleeping one dynamic explosive get high impact activity like jumping parachute cold shower like jumping parachute miniature like bungee jumping eye closed get fast boost dynamic energy staying bathroom get free One thing experienced got shower exactly enormous amount rush power filling body cold water minute recharging brain muscle course le strong jumping 20k foot height still considerable way could get adrenaline simple Moreover rush make feel necessity acting need something might productive learn use properly 3 Cold shower get meditative state first time got cold water noticed built block external world mind completely erased thought draining disappeared could think anything else survival little effort could stop Thus important side benefit get cold shower deeper awareness every inch body first able distinguish part skin exposed cold water relaxed one slowly become conscious internal body noticing fill air every breath take exactly want achieve meditation mental clarity given absence thought mental embodiment given deeper comprehension body 4 Cold shower make reconnect first went cold water hyped benefit think much harsh could following repetition harder take decision going don’t come back happens next it’s real challenge Staying shower constant internal fight make ultimately discover deeper level time start recognize pattern brain us get danger keep resistant aware pattern get trouble important First recognize danger easier secondly stop brain overreacting situation apparently dangerous 5 Cold shower improve cold tolerance remember moved started living alone economizing bill temperature house low put always sweater comfy started cold shower challenge first 30 day recognized able stay without clothes usual temperature around one hour without feeling cold also general cold resistance improved able remain house wearing simple TshirtTags Selfawareness Self Improvement Motivation Cold Shower Habit Building
2,818
Fixated on Taking Selfies? You Might Have these Psychological Issues
Fixated on Taking Selfies? You Might Have these Psychological Issues #2 needs to be fixed right now Photo by Cristina Zaragoza on Unsplash Is that the picture of a glass of milk? No, that’s a glass of black tea taken in my uber-cool new selfie camera!Apparently, the camera doesn’t like the ‘dark’ tone. I know that joke is a bit of a stretch, but selfie cameras and the Artificial Intelligence powering them, have come close to creating a near-perfect version of anything it captures. They remove the spots, patch the scars, pull the beauty filters, and do a million things you can’t imagine. Take a stroll down the mobile shop, see how the industry has raced to near saturation in selfie technology. The punch hole camera, the twin optics, the lens that magically appears from nowhere, all sorts of innovation within a tiny space at the top of your 6-inch device. We happily pay a premium for them. And we revel in posting selfies. But does taking selfies mean you have some psychological condition? After all, it’s a harmless means of fun that doesn’t poke into someone’s territory. Your face. Your camera. Your rules. But let me tell you that taking excessive selfies can be an indication of an underlying psychological problem. But here is the million-dollar question: What’s ‘excessive’? What is the limit one has to cross to be bothered about it? How much is too much? The American Psychiatric Association (APA), in a study, confirms three levels of disorders linked to an excessive affinity for selfies. The Borderline: Taking (atleast) three selfies a day, but not posting them on social media. The Acute: Taking (atleast) three selfies a day and posting them all on social media. Chronic: An uncontrollable urge to take selfies all day and post them (atleast) six times a day. The author calls such people with an excessive affinity for selfies as SELFITIS. So based on the above measure, are you a selfitis? Even if you are not one, I will encourage you to read further. I will tell you four reasons why people show a craving for taking selfies. No offence. #1 You Could be a narcissist! “The narcissist enjoys being looked at and not looking back.” — Mason Cooley A narcissist is a person who pursues gratification from vanity or egotistic admiration of one’s perfect self-image. From blowing his own trumpet to an outright exhibition of arrogance, a narcissist would seek to build his image, and no wonder selfies occur to him as a convenient tool. To maintain his own meticulous and perfect image, a narcissist has to post his flawless pictures. While letting someone handle the camera can go, either way, the ability to control his picture, with the perfect angle and the right looks, gives him the necessary control that allows him to have the image exactly as he wanted it. Besides, narcissists are also people who want them to be considered special. A selfie lets him be the lone subject of a photograph and feeds his craving to be the star. It allows them to set the exact public image they yearn for. A study published in The Open Psychology Journal, done by researchers from Swansea University and Milan University, confirms the link between selfie craving and narcissism. Out of the 74 test subjects in the study, those who used social media through excessive visual posting showed a 25% increase in narcissistic traits. #2 Do You have problems presenting your body? Low self esteem involves imagining the worst that other people can think about you. — Roger Ebert Many people are not impressed by the way they look, and much like a narcissist, they want to be in control of their images, albeit for a different reason. From being fat to having a slightly long nose, there is a myriad of details about themselves they would like to either hide or project. In my part of the world, fair skin is another illusion that’s coveted. And hence the cams that turn black coffee to milk! Selfie looms in the air as a rescue for all such people nursing a low self-image, for you can have the ‘perfect’ shot to your design. They adjust the angle, tweak the settings, put the filters, and use every big and small feature to ensure that what they don’t want is not captured and what they want is standing out and staring at the beholder. In a study published on Sciencedirect.com, done with a participation of 259 young women, it was found that social networking sites’ selfie activities are linked with body-related and eating concerns. However, such negative impressions of oneself can work the other way round too. For instance, if you have abysmal self-esteem, so much that you think your ‘poor looks’ cannot be fixed with any advanced effect of your smartphone, you might entirely withdraw from the act of taking selfies. #3 How is your social life going? A healthy social life is found only, when in the mirror of each soul the whole community finds its reflection, and when in the whole community the virtue of each one is living. — Rudolf Steiner If you take a lot of selfies and are alone in most of them, you better ask this question yourself. Ideally, a picture should be taken to cherish a special moment. But if most of your selfies are not encompassing such moments and instead show you in different backgrounds, it could be a strong indication that you are not entirely content with your social life. Perhaps you yearn to mix more but just cannot. Peerayuth Charoensukmongkol, who researched the connection between personal characteristics and selfie addiction, says that selfies are meant to improve self-disclosure and social communication on social media sites, and therefore, essential for those who experience loneliness. Posting pictures and getting feedback from social media websites can enhance their social communication. However, the approach can backfire as relationships erected through social media communications can often be shallow. This could further worsen your loneliness. Your loneliness can have several reasons behind it. It is possible that you recently broke up with your partner or that you have social anxiety issues. It makes sense for you to build a healthy social life or address the core issue, rather than seeking temporary relief in selfies. #4 Look at me! Seek respect, not attention. It lasts longer. Some people can’t get enough attention and approval. Taking your pictures and engaging them on social media is one of the easiest methods to draw eyeballs towards you. Besides, with all those filters and smiley faces, you can build a ‘my-life-is-cooler-than-yours’ aura around you. For such people, their mind perceives the ‘likes’ and ‘reactions’ they receive as a token of acceptance. Needless to say, if your self worth is invested in someone else’s opinion about you, you will end up living a life to impress. You will seldom listen to your inner calls. Besides, such attention-seeking behavior, in the long run, may adversely affect your self-confidence. For instance, if one of your pictures fails to draw the same successful results as your previous one did, suddenly, you may start doubting yourself. “Have people stopped loving me” “Don’t I look good in that photo” a million questions erupt. In an article published in psychologytoday.com, the author, Martin Graff Ph.D., says that attention-seeking may be one of the main reasons people take selfies and use social media. He adds that people would do so to feel more popular. Letting others’ opinion dictate your life is not the way to live. If you are posting more selfies to gain attention, you need to rethink your priorities. Final thoughts If you go through the image gallery of your smartphone, rest assured, you are going to find quite a few selfies. But that wouldn’t make you a sefitist or an addict. You have already read the parameters of becoming an addict. If you don’t fit that profile, you have nothing to worry about. However, if you are overly drawn to your front camera, with an irresistible temptation to post them on social media, there are things to ponder. You have to start introspecting now!
https://medium.com/indian-thoughts/fixated-on-taking-selfies-you-might-have-psychological-issues-a751927b4ed3
['Aravind Balakrishnan']
2020-12-11 14:59:27.530000+00:00
['Technology', 'Mental Health', 'Psychology', 'Culture', 'Social Media']
Title Fixated Taking Selfies Might Psychological IssuesContent Fixated Taking Selfies Might Psychological Issues 2 need fixed right Photo Cristina Zaragoza Unsplash picture glass milk that’s glass black tea taken ubercool new selfie cameraApparently camera doesn’t like ‘dark’ tone know joke bit stretch selfie camera Artificial Intelligence powering come close creating nearperfect version anything capture remove spot patch scar pull beauty filter million thing can’t imagine Take stroll mobile shop see industry raced near saturation selfie technology punch hole camera twin optic lens magically appears nowhere sort innovation within tiny space top 6inch device happily pay premium revel posting selfies taking selfies mean psychological condition it’s harmless mean fun doesn’t poke someone’s territory face camera rule let tell taking excessive selfies indication underlying psychological problem milliondollar question What’s ‘excessive’ limit one cross bothered much much American Psychiatric Association APA study confirms three level disorder linked excessive affinity selfies Borderline Taking atleast three selfies day posting social medium Acute Taking atleast three selfies day posting social medium Chronic uncontrollable urge take selfies day post atleast six time day author call people excessive affinity selfies SELFITIS based measure selfitis Even one encourage read tell four reason people show craving taking selfies offence 1 Could narcissist “The narcissist enjoys looked looking back” — Mason Cooley narcissist person pursues gratification vanity egotistic admiration one’s perfect selfimage blowing trumpet outright exhibition arrogance narcissist would seek build image wonder selfies occur convenient tool maintain meticulous perfect image narcissist post flawless picture letting someone handle camera go either way ability control picture perfect angle right look give necessary control allows image exactly wanted Besides narcissist also people want considered special selfie let lone subject photograph feed craving star allows set exact public image yearn study published Open Psychology Journal done researcher Swansea University Milan University confirms link selfie craving narcissism 74 test subject study used social medium excessive visual posting showed 25 increase narcissistic trait 2 problem presenting body Low self esteem involves imagining worst people think — Roger Ebert Many people impressed way look much like narcissist want control image albeit different reason fat slightly long nose myriad detail would like either hide project part world fair skin another illusion that’s coveted hence cam turn black coffee milk Selfie loom air rescue people nursing low selfimage ‘perfect’ shot design adjust angle tweak setting put filter use every big small feature ensure don’t want captured want standing staring beholder study published Sciencedirectcom done participation 259 young woman found social networking sites’ selfie activity linked bodyrelated eating concern However negative impression oneself work way round instance abysmal selfesteem much think ‘poor looks’ cannot fixed advanced effect smartphone might entirely withdraw act taking selfies 3 social life going healthy social life found mirror soul whole community find reflection whole community virtue one living — Rudolf Steiner take lot selfies alone better ask question Ideally picture taken cherish special moment selfies encompassing moment instead show different background could strong indication entirely content social life Perhaps yearn mix cannot Peerayuth Charoensukmongkol researched connection personal characteristic selfie addiction say selfies meant improve selfdisclosure social communication social medium site therefore essential experience loneliness Posting picture getting feedback social medium website enhance social communication However approach backfire relationship erected social medium communication often shallow could worsen loneliness loneliness several reason behind possible recently broke partner social anxiety issue make sense build healthy social life address core issue rather seeking temporary relief selfies 4 Look Seek respect attention last longer people can’t get enough attention approval Taking picture engaging social medium one easiest method draw eyeball towards Besides filter smiley face build ‘mylifeiscoolerthanyours’ aura around people mind perceives ‘likes’ ‘reactions’ receive token acceptance Needless say self worth invested someone else’s opinion end living life impress seldom listen inner call Besides attentionseeking behavior long run may adversely affect selfconfidence instance one picture fails draw successful result previous one suddenly may start doubting “Have people stopped loving me” “Don’t look good photo” million question erupt article published psychologytodaycom author Martin Graff PhD say attentionseeking may one main reason people take selfies use social medium add people would feel popular Letting others’ opinion dictate life way live posting selfies gain attention need rethink priority Final thought go image gallery smartphone rest assured going find quite selfies wouldn’t make sefitist addict already read parameter becoming addict don’t fit profile nothing worry However overly drawn front camera irresistible temptation post social medium thing ponder start introspecting nowTags Technology Mental Health Psychology Culture Social Media
2,819
Self-Care: You Need It Too
Self-Care: You Need It Too How caregivers can learn to care for themselves When you’re caught up in life, busy attending to bills, housework, pets, and maybe even a family member or two, it can be really easy to forget yourself. I don’t mean forgetting your personality outside of being a caregiver. I mean if you’re always busy caring for someone else, who is going to care for you? Photo by Keenan Constance from Pexels Rianne Grace made an excellent point in her story What My Self-Care Looks Like Today: Self-care is not always pretty, but it is necessary. My family has a long, long history of health issues, from cancer to diabetes to fibromyalgia. As one of the healthier members of the family (not to mention the youngest) I was left with a lot of the heavy lifting, so to speak. I was born a year or so before my mom was diagnosed with fibro. The intense lack of energy from the disease left her pretty well chair-bound for the better part of four years. She’s since learned to manage it better and can get around normally. However, this caused me to grow up with the caregiver mentality. What is the caregiver mentality, you ask? It’s where you’re so used to caring for another person, physically or emotionally, that it shapes your entire view of living. I was always the able-bodied young ’un who was obligated to help because I could. Because of that, I can’t stop myself from trying to help every single struggling person I come across. I became so focused on supporting my struggling family members, I forgot that I was struggling too. Now, I’m not saying it’s a bad thing to have this caregiver mentality. And I’m certainly not saying it was anyone’s fault; it’s a good thing to want to help people. What I’m trying to say is to be sure you’re taking care of yourself. I became so focused on supporting my struggling family members, I forgot that I was struggling too. Take it from me that once you’re focused on caring for someone else’s needs, it can be very easy to forget that you have needs as well.
https://medium.com/write-well-be-well/self-care-you-need-it-too-9873d5d42da0
['Pj Ryder']
2019-09-24 11:16:01.441000+00:00
['Self Care', 'Support', 'Mental Health', 'Psychology', 'Caregiving']
Title SelfCare Need TooContent SelfCare Need caregiver learn care you’re caught life busy attending bill housework pet maybe even family member two really easy forget don’t mean forgetting personality outside caregiver mean you’re always busy caring someone else going care Photo Keenan Constance Pexels Rianne Grace made excellent point story SelfCare Looks Like Today Selfcare always pretty necessary family long long history health issue cancer diabetes fibromyalgia one healthier member family mention youngest left lot heavy lifting speak born year mom diagnosed fibro intense lack energy disease left pretty well chairbound better part four year She’s since learned manage better get around normally However caused grow caregiver mentality caregiver mentality ask It’s you’re used caring another person physically emotionally shape entire view living always ablebodied young ’un obligated help could can’t stop trying help every single struggling person come across became focused supporting struggling family member forgot struggling I’m saying it’s bad thing caregiver mentality I’m certainly saying anyone’s fault it’s good thing want help people I’m trying say sure you’re taking care became focused supporting struggling family member forgot struggling Take you’re focused caring someone else’s need easy forget need wellTags Self Care Support Mental Health Psychology Caregiving
2,820
101,572 Words in 30 Days
by LaDonna Witmer Willems, with guest appearance by Chris Baty Artwork by Samuel Pasquier Every November, hundreds of thousands of writers around the world hunker down to write a 50,000-word novel in 30 days. (That’s 1,667 words per day.) It’s called National Novel Writing Month or, more colloquially, NaNoWriMo. These keyboard masochists gather in groups for write-ins, or sequester themselves in libraries, in cafés, in corners, or wherever they can find the space and time to write, unmolested by self-doubt, self-criticism, and other acts of self-bullying (as specified in NaNoWriMo’s Month-Long Novelist Agreement and Statement of Understanding.) To be able to write your way into a project, free of the gremlin of self-criticism, is no small thing. For many would-be writers (and full-time writers, too), getting started is the hardest part of the creative process. That’s because we often hold in our heads this utopian vision of what we want to make, but when we try — or even think about trying — to take it out and make it live in the visible world, it feels like it’s falling apart. Booking it For months, I had a writing project brewing in the back of my brain. It wasn’t a novel; more of a memoir-ish thing. I kept saying I was going to start, but had yet to ink a single word on paper. Luckily for me, I sit right next to Chris Baty in Writer’s Row at the Dropbox Brand Studio. Chris isn’t just a fine human person and Stanford professor of writing. He’s also the creator of NaNoWriMo. And he’s written a novel in 30 days, every year, for the last 20 years. So when he suggested I use the framework of NaNoWriMo to bang out a 50,000-word first draft of my not-novel, I signed up for the challenge. And it was, indeed, a challenge. To make that word count deadline, I wrote wherever and whenever I could. I wrote in airplanes and pickup trucks, in beds and bathrooms. I wrote on vacation, on Thanksgiving, and on my birthday. I even wrote during those first five minutes of work meetings when you’re sitting alone in a conference room waiting for everyone to gather. Some days I wrote well over 3,000 words. One day I wrote only 144. But every morning when I walked in to Dropbox, Chris would swivel his desk chair my way and say with a knowing twinkle, “How ya doin’ today? How’s your word count?” Between the two of us, a first-time NaNoWriMo-er and a 20-year veteran, we wrote 101,572 words in November. (I won’t tell you who wrote more, but 51,545 of those words were mine.) Here’s how it went: LaDonna and Chris discussing how two Dropbox writers each wrote a book in a month (and held down their day jobs) — Photo by Chris Behroozian The first-timer and the veteran: a debrief LaDonna: So, Chris, I want to know-in your 20th year writing a novel for NaNoWriMo, what’s different and what’s the same? Chris: I’d say there’s a lot more confidence. After the first time, when you realize you can do it, that’s the game-changer. That’s the Eureka moment. LaDonna: It’s mind-blowing, yeah! Chris: You’re like, “Whoa, there was a book in me I didn’t know was in there!” And then you start asking yourself, “What else is in there?” And it could be more books or it could be wanting to start a new business or learn a foreign language or get back to the viola lessons you gave up when you were nine. It’s that sense of discovering things inside you that you didn’t know were there, or you’d forgotten were there. And the other big wow is that it feels great to do it. I mean, it’s work and it hurts sometimes, but it’s also really fun. Especially when you start hitting that place where your imagination comes up with the connections and you see themes emerging. If you’re writing fiction, it happens when the characters start taking the story in different directions, and that feels incredible. I think a lot of people assume professional novelists or professional writers have a supercharged part of their brain, that their brain chemistry is different. But everybody who starts writing and keeps writing has that process of discovery and surprise and wonder. And once you’ve experienced it, the next times are not quite as miraculously eye-opening. In fact, the second time people do NaNoWriMo, it’s legendarily difficult. People will look at that first year and say, “I didn’t really plan and it turned out pretty well!” And then they plan four times as much and expect it to be four times as good or the output to be four times as refined, and instead it sucks four times worse because you’re suddenly putting all kinds of pressure and expectations on yourself. The first draft is always going to be terrible. Promising, but terrible. Once you start hoping that because you’re more experienced at this, you can write a second draft on your first try, that’s where things start to hurt a little bit more. LaDonna: So, after 20 times, do you think there’s going to be a year where you say, “Meh. I don’t need to NaNoWriMo this year.” Or will you just keep going until you’re too old to smack a keyboard? Chris: I do feel like there has not been a year so far when I thought, “I’m not going to do this.” I think it gets in your blood a little bit. Like the leaves start changing, and you get that autumn smell, and you’re like, “I NEED TO START WRITING! GET ME A COMPUTER!” Fall is such an interesting time. It feels like November is a month for cocooning and turning inward in general; it’s spitting rain outside, and everything is changing, and NaNoWriMo fits this notion so beautifully. There’s just something so appealing about starting with the seed of an idea and seeing that idea blossom and then wilt and then blossom some more. It’s pretty intoxicating in a way that few things are. So I can see myself continuing to do this. LaDonna: I was telling someone in October that I was going to do this, and she said, “November? That’s a terrible month! You’ve got Thanksgiving, and you’ve got all of this stuff. Why would anyone want to do all this writing in November?!” And my thought was just, “There is no good month!” Right? There’s never going be that perfect time to sit down and write a book! So besides fall and the magic of the leaves turning and whatnot, what made November the NaNoWriMo month? Chris: So we actually did it in July the first year. And it was great. It was a little challenging in that a lot of people went on vacation, so they were writing while they were supposed to be relaxing. But it was fun. The first year there were 21 people; it was such a small group. There were six of us who crossed that 50,000-word finish line, and we were the ones who would actually get together at night and write together. So when we were planning it again, we were going to do it in July the following year too, but then people were busy and everyone was like, “I can’t do July. How about August?” And it just kept getting pushed back until we landed on November as the time nobody had any plans or excuses. And then it just stuck in November. LaDonna: I like it. It feels like a nice roller coaster ride into the holidays. Chris: Yeah. You know, I think you’re right that there’s never going be a good time to write your book. February is the clear worst month because it’s just too short. A lot of people think January would be good because it’s like starting fresh, a lot of people have New Year’s resolutions around creativity. But this is something I’ve been telling everybody-any month can be National Novel Writing Month. If you can get at least one other person to agree on a set word-count goal and a time frame, you’re golden. The magic is that there are a couple hundred thousand people doing it at the same time which means there is a lot of encouragement in the air. I mean, you and I, just knowing that we were going to get to check in because we sit next to each other at work, that’s really powerful. LaDonna: It is. It is quite huge. On the day that I wrote only 144 words, I remember being glad it was a Saturday because I didn’t have to see you the next day. Because I knew you’d ask, “What’s your word count?!” and I’d go, [whispers] “One hundred and forty-four.” Chris: Yeah, and then I’d just spit on you and be like, “You’re a fraud. You’re a sham.” [laughter] LaDonna: Totally. And then we wouldn’t be friends anymore. [more laughter] Someone asked me after I had finished: “Where did you find the time?” And I said, “I didn’t. I stole it.” Five minutes here and an hour there. Deciding not to check social media and getting 15 minutes back. I know there are some writers who are like, “I’m getting up at 5:30 every morning, and I’m going to write for an hour.” And at this stage of life, for me, with a child, I can’t. Because she would for sure wake up at 5:35 and ruin the plan. Chris: Right, and she’d just want to hang out and talk about cereal. Yeah. So, LaDonna, you’re a professional writer, you’ve been part of this general rodeo most of your life. Was it surprising to you that you could get a book written in these pockets of time? Did you see yourself as someone who would need to block out two hours on a Sunday and write? LaDonna: Yeah, I did. I decided I wanted to write a book before you suggested jumping on NaNoWriMo. And I remember thinking, “Well, I guess maybe every Wednesday could be my book writing day.” And then, you know, a couple Wednesdays went by and book writing didn’t happen, because life. So it was a wonderful discovery to me that in even just five minutes, I can get down something worthwhile. I kind of knew that about poetry. But poetry is so much less intimidating to me, in part because I’ve done it for so long but also because it’s moments. It’s that skinny column of words, and you’re not writing an epic, usually. And so I knew I could bang out a poem in five minutes-it might suck-but it would be there, and I could fix it later. But the idea of writing a book in five-minute chunks had never occurred to me. Chris: Well, it’s not ideal. But we are forever going to live in a not-ideal world until we become independently wealthy, and then we can buy the castles that we deserve … LaDonna: … and hire ghostwriters. Chris: Exactly! Or literal ghosts from the castle can write our books! I think there’s something nice about discovering that there are these pockets of time. And this is where I think word count is actually quite helpful. Because books are magical, squishy, strange, mysterious creatures, so you feel like it wouldn’t work very well to pin it to this very linear sense of “How many words did you write?” or “Your total goal today is 1,667-where are you on that spectrum?” But in five minutes you can maybe write 100 words, and that’s a deposit in the word bank. And that starts to feel like you’ve achieved something. Whereas, if you write for five minutes and you don’t have that word count ticker in your head… you look at what you’ve made and you’re like, “Bleah.” But if you’re like “Bleah” plus 100 words, that’s a good bleah! There’s this writer, Rachael Herron, who I really love. She lives in the Bay Area and has done NaNoWriMo infinity times and has published most of her NaNoWriMo novels. She’s very prolific. And she says that the difference between the writing sessions she felt bad about-the ones that felt like pulling teeth, but she wrote through it anyway-and the sessions where she felt perfectly in flow, when she goes back and reads them both, she can’t tell the difference between the two. So even though one writing session during the creation process might feel better than the other, it doesn’t matter. Because, in fact, the thing you’re creating is your voice. LaDonna: One night during NaNoWriMo, I was writing at the dining room table and my husband’s making dinner, my daughter’s in and out, and I was getting increasingly annoyed with both of them. I thought it was because they were interrupting me-I don’t have a private place in my house where I can go and close the door and write-but then I realized, much later, that it was actually because what I was writing about was really dredging up some stuff. I was writing about my mom, and I got quite triggered by all of it. And I had to go back to both of them later and apologize and make sure they knew it wasn’t their fault. Do novels do that to you, too? Are they bleeding into your life? Chris: Oh, yeah. I mean, you’re writing these scenes with these people where big things are happening and somebody’s dying or a relationship is ending or something, and you really get pulled into it. In the NaNoWriMo forums, there’s a thread dedicated to weepy novelists. And there’s a badge dedicated to the moment when you’re writing your novel and you start crying. That happens to me every novel, you know? Especially if you’re listening to a good playlist that’s just punching you right in the feelings. And you’re writing a scene of great change or departures, and then real life comes knocking, and you’re like, “NOOOO! Something is happening here on this page and I’m with these people.” I mean, what a great thing, really. LaDonna: So you’ve got this momentum in November-you’ve written thousands and thousands of words, and you’ve built this daily habit and reached your 50,000-word count, and then you hit December. I wanted to let it marinate before I dove into editing, so I didn’t work on this project for a month or so. Do some people just keep going? Chris: I think it depends on what you want out of the experience. If it was to build the habit and now you want to keep going, that’s great. But 1,667 words a day is an unsustainable amount of words, in my opinion. I mean, some people can bash that out in, like, 20 minutes because they’re just great typists and their brain works well with it. But, to me, if you want to keep going, I would say drop it down to a much smaller word count-so you’re looking at 500 words a day, five days a week. Keeping some kind of schedule, I think, is good. I do think, though, that much like running a marathon, we’re exhausted now. This has been an exhausting endeavor. So I do think it’s important to go back and reconnect with your life while you let that thing you wrote rest. When we’re writing, we’re just so close to it, and that’s the right place to be. But when we’re revising, we need to start with some distance from it. Because there are going to be parts that we felt very connected to-and maybe they’re great writing-but they don’t fit in the book. And we’re going to have to say goodbye to those. We’re going to have to realize also that there are holes that are going to be pretty time-consuming to fill. When you have some distance from the writing process, you can make those decisions with a more clinical eye. And that’s exactly the right place to be, because you’re making hard decisions. But it’s also important to let it rest because you’re just tired! I mean, that was quite an experience. What were we all thinking? [laughter] So I have a question for you. There are a lot of NaNoWriMo haters out there or NaNoWriMo skeptics who say, “This is just encouraging crappy writing. It’s telling people they’ve done something that actually they haven’t. This isn’t a novel-it’s 50,000 words of a first draft!” I’m sure you heard that out in the world, so were you a NaNoWriMo skeptic at some point when you first heard about it, or did it always seem interesting to you? LaDonna: I was always wowed by the idea, but I stopped at the word “novel” because I have never aspired to write a novel. So when you suggested I use it to write a not-novel instead, lots of light bulbs started going off in my head. But, to me, it’s not the promise of “you will have a novel” at the end of November-it’s “you will have a beginning.” And I think that beginning, for many of us, is so difficult to achieve. For me, it was really super-helpful, not just to know that I wasn’t alone but to know that there were rules. And the rule was, you cannot go back and look at it and judge it.* I took that really seriously. When I do go back and look at it, I know I’m going to see parentheses that say, “UGH! THIS IS AWFUL!” Because whenever I had that thought, I would just write it down and keep going. Had I not had that framework, and those rules, I would have stopped myself 40,000 words ago, thrown up my hands, and said, “Who am I to think that I can do this? This is crazy, this is terrible, no one wants to read this! I should stop now.” But since I was purposely told that I was going to hear that voice and I should tell it to shut up and keep going, I did. So maybe there aren’t a lot of novels that have been created, but there are a lot of beginnings. There are beginnings that could become something. How many of yours have you gone back to? Chris: Five or six. LaDonna: Five or six out of 20 is pretty awesome. Chris: Yeah, and I think that’s the nice thing about the 30-day time frame, too. A lot of people end it feeling like, “I just don’t like that book that I was writing,” and they don’t go back to it. But that’s OK, because you learn so many things about how to build a book and where things can go wrong for you, and about your own approaches as a writer, and what inspires you. And it’s not so hard to let go of, because you were just writing for a month. LaDonna: I loved that, too! Because it was like, “You can do this” for 30 days. You can not eat carbs for 30 days. You can write 1,667 words each day for 30 days. Chris: You know, there’s this notion of the “writer’s retreat,” where you get put up in this beautiful house overlooking some ocean somewhere and get to write. I think the more powerful model is to have it happen in the middle of our busy, hectic lives and to learn how to carve out time. Because the writer’s retreat on the coast-sure, it may happen for you, but that’s not going to be a regular part of your life. But if you’ve learned how to create a writer’s retreat in the middle of everything else going on, that will be the ongoing, powerful, sustaining thing that helps you get this thing done. LaDonna: There’s not just the writer’s retreat but the sense that the “muse” will come, and it will be beautiful, and words will fill my head and fall right onto the page. I’ve learned by doing this for a living that, actually, nothing will happen unless you just start putting words down. Muse or no muse. I used to wait for a magical feeling and the right… whatever. The right desk. The right light. The right socks. And I don’t anymore. Chris: Yeah. You can write barefoot. It’s fine. Any month is Novel Writing Month If you’re feeling energized and inspired and itching for a blank page to make your mark on (and why wouldn’t you be?!), Chris’s book No Plot? No Problem! is a great place for getting-started ideas. Also, it’s important to remember that whatever you want to write is legit. You want to write start a novel in 30 days? Great. But you could also finish a novel. Or revise one. Or write a not-novel. A series of essays. A blog post every day. A poem a day! (I’m happy to tell you that April is, in fact, National Poetry Writing Month: NaPoWriMo.) So go-find yourself a comfy corner! Steal 15 minutes. Shut the door on that self-critiquing gremlin and put some words on a page. You might write your way straight into a book. Or at least a beginning.
https://medium.com/dropbox-design/101-572-words-in-30-days-c05a6c714a2d
['Ladonna Witmer Willems']
2020-03-02 18:30:31.241000+00:00
['Design Thinking', 'Design', 'Writing', 'NaNoWriMo', 'UX']
Title 101572 Words 30 DaysContent LaDonna Witmer Willems guest appearance Chris Baty Artwork Samuel Pasquier Every November hundred thousand writer around world hunker write 50000word novel 30 day That’s 1667 word per day It’s called National Novel Writing Month colloquially NaNoWriMo keyboard masochist gather group writeins sequester library cafés corner wherever find space time write unmolested selfdoubt selfcriticism act selfbullying specified NaNoWriMo’s MonthLong Novelist Agreement Statement Understanding able write way project free gremlin selfcriticism small thing many wouldbe writer fulltime writer getting started hardest part creative process That’s often hold head utopian vision want make try — even think trying — take make live visible world feel like it’s falling apart Booking month writing project brewing back brain wasn’t novel memoirish thing kept saying going start yet ink single word paper Luckily sit right next Chris Baty Writer’s Row Dropbox Brand Studio Chris isn’t fine human person Stanford professor writing He’s also creator NaNoWriMo he’s written novel 30 day every year last 20 year suggested use framework NaNoWriMo bang 50000word first draft notnovel signed challenge indeed challenge make word count deadline wrote wherever whenever could wrote airplane pickup truck bed bathroom wrote vacation Thanksgiving birthday even wrote first five minute work meeting you’re sitting alone conference room waiting everyone gather day wrote well 3000 word One day wrote 144 every morning walked Dropbox Chris would swivel desk chair way say knowing twinkle “How ya doin’ today How’s word count” two u firsttime NaNoWriMoer 20year veteran wrote 101572 word November won’t tell wrote 51545 word mine Here’s went LaDonna Chris discussing two Dropbox writer wrote book month held day job — Photo Chris Behroozian firsttimer veteran debrief LaDonna Chris want knowin 20th year writing novel NaNoWriMo what’s different what’s Chris I’d say there’s lot confidence first time realize that’s gamechanger That’s Eureka moment LaDonna It’s mindblowing yeah Chris You’re like “Whoa book didn’t know there” start asking “What else there” could book could wanting start new business learn foreign language get back viola lesson gave nine It’s sense discovering thing inside didn’t know you’d forgotten big wow feel great mean it’s work hurt sometimes it’s also really fun Especially start hitting place imagination come connection see theme emerging you’re writing fiction happens character start taking story different direction feel incredible think lot people assume professional novelist professional writer supercharged part brain brain chemistry different everybody start writing keep writing process discovery surprise wonder you’ve experienced next time quite miraculously eyeopening fact second time people NaNoWriMo it’s legendarily difficult People look first year say “I didn’t really plan turned pretty well” plan four time much expect four time good output four time refined instead suck four time worse you’re suddenly putting kind pressure expectation first draft always going terrible Promising terrible start hoping you’re experienced write second draft first try that’s thing start hurt little bit LaDonna 20 time think there’s going year say “Meh don’t need NaNoWriMo year” keep going you’re old smack keyboard Chris feel like year far thought “I’m going this” think get blood little bit Like leaf start changing get autumn smell you’re like “I NEED START WRITING GET COMPUTER” Fall interesting time feel like November month cocooning turning inward general it’s spitting rain outside everything changing NaNoWriMo fit notion beautifully There’s something appealing starting seed idea seeing idea blossom wilt blossom It’s pretty intoxicating way thing see continuing LaDonna telling someone October going said “November That’s terrible month You’ve got Thanksgiving you’ve got stuff would anyone want writing November” thought “There good month” Right There’s never going perfect time sit write book besides fall magic leaf turning whatnot made November NaNoWriMo month Chris actually July first year great little challenging lot people went vacation writing supposed relaxing fun first year 21 people small group six u crossed 50000word finish line one would actually get together night write together planning going July following year people busy everyone like “I can’t July August” kept getting pushed back landed November time nobody plan excuse stuck November LaDonna like feel like nice roller coaster ride holiday Chris Yeah know think you’re right there’s never going good time write book February clear worst month it’s short lot people think January would good it’s like starting fresh lot people New Year’s resolution around creativity something I’ve telling everybodyany month National Novel Writing Month get least one person agree set wordcount goal time frame you’re golden magic couple hundred thousand people time mean lot encouragement air mean knowing going get check sit next work that’s really powerful LaDonna quite huge day wrote 144 word remember glad Saturday didn’t see next day knew you’d ask “What’s word count” I’d go whisper “One hundred fortyfour” Chris Yeah I’d spit like “You’re fraud You’re sham” laughter LaDonna Totally wouldn’t friend anymore laughter Someone asked finished “Where find time” said “I didn’t stole it” Five minute hour Deciding check social medium getting 15 minute back know writer like “I’m getting 530 every morning I’m going write hour” stage life child can’t would sure wake 535 ruin plan Chris Right she’d want hang talk cereal Yeah LaDonna you’re professional writer you’ve part general rodeo life surprising could get book written pocket time see someone would need block two hour Sunday write LaDonna Yeah decided wanted write book suggested jumping NaNoWriMo remember thinking “Well guess maybe every Wednesday could book writing day” know couple Wednesdays went book writing didn’t happen life wonderful discovery even five minute get something worthwhile kind knew poetry poetry much le intimidating part I’ve done long also it’s moment It’s skinny column word you’re writing epic usually knew could bang poem five minutesit might suckbut would could fix later idea writing book fiveminute chunk never occurred Chris Well it’s ideal forever going live notideal world become independently wealthy buy castle deserve … LaDonna … hire ghostwriter Chris Exactly literal ghost castle write book think there’s something nice discovering pocket time think word count actually quite helpful book magical squishy strange mysterious creature feel like wouldn’t work well pin linear sense “How many word write” “Your total goal today 1667where spectrum” five minute maybe write 100 word that’s deposit word bank start feel like you’ve achieved something Whereas write five minute don’t word count ticker head… look you’ve made you’re like “Bleah” you’re like “Bleah” plus 100 word that’s good bleah There’s writer Rachael Herron really love life Bay Area done NaNoWriMo infinity time published NaNoWriMo novel She’s prolific say difference writing session felt bad aboutthe one felt like pulling teeth wrote anywayand session felt perfectly flow go back read can’t tell difference two even though one writing session creation process might feel better doesn’t matter fact thing you’re creating voice LaDonna One night NaNoWriMo writing dining room table husband’s making dinner daughter’s getting increasingly annoyed thought interrupting meI don’t private place house go close door writebut realized much later actually writing really dredging stuff writing mom got quite triggered go back later apologize make sure knew wasn’t fault novel bleeding life Chris Oh yeah mean you’re writing scene people big thing happening somebody’s dying relationship ending something really get pulled NaNoWriMo forum there’s thread dedicated weepy novelist there’s badge dedicated moment you’re writing novel start cry happens every novel know Especially you’re listening good playlist that’s punching right feeling you’re writing scene great change departure real life come knocking you’re like “NOOOO Something happening page I’m people” mean great thing really LaDonna you’ve got momentum Novemberyou’ve written thousand thousand word you’ve built daily habit reached 50000word count hit December wanted let marinate dove editing didn’t work project month people keep going Chris think depends want experience build habit want keep going that’s great 1667 word day unsustainable amount word opinion mean people bash like 20 minute they’re great typist brain work well want keep going would say drop much smaller word countso you’re looking 500 word day five day week Keeping kind schedule think good think though much like running marathon we’re exhausted exhausting endeavor think it’s important go back reconnect life let thing wrote rest we’re writing we’re close that’s right place we’re revising need start distance going part felt connected toand maybe they’re great writingbut don’t fit book we’re going say goodbye We’re going realize also hole going pretty timeconsuming fill distance writing process make decision clinical eye that’s exactly right place you’re making hard decision it’s also important let rest you’re tired mean quite experience thinking laughter question lot NaNoWriMo hater NaNoWriMo skeptic say “This encouraging crappy writing It’s telling people they’ve done something actually haven’t isn’t novelit’s 50000 word first draft” I’m sure heard world NaNoWriMo skeptic point first heard always seem interesting LaDonna always wowed idea stopped word “novel” never aspired write novel suggested use write notnovel instead lot light bulb started going head it’s promise “you novel” end Novemberit’s “you beginning” think beginning many u difficult achieve really superhelpful know wasn’t alone know rule rule cannot go back look judge took really seriously go back look know I’m going see parenthesis say “UGH AWFUL” whenever thought would write keep going framework rule would stopped 40000 word ago thrown hand said “Who think crazy terrible one want read stop now” since purposely told going hear voice tell shut keep going maybe aren’t lot novel created lot beginning beginning could become something many gone back Chris Five six LaDonna Five six 20 pretty awesome Chris Yeah think that’s nice thing 30day time frame lot people end feeling like “I don’t like book writing” don’t go back that’s OK learn many thing build book thing go wrong approach writer inspires it’s hard let go writing month LaDonna loved like “You this” 30 day eat carbs 30 day write 1667 word day 30 day Chris know there’s notion “writer’s retreat” get put beautiful house overlooking ocean somewhere get write think powerful model happen middle busy hectic life learn carve time writer’s retreat coastsure may happen that’s going regular part life you’ve learned create writer’s retreat middle everything else going ongoing powerful sustaining thing help get thing done LaDonna There’s writer’s retreat sense “muse” come beautiful word fill head fall right onto page I’ve learned living actually nothing happen unless start putting word Muse muse used wait magical feeling right… whatever right desk right light right sock don’t anymore Chris Yeah write barefoot It’s fine month Novel Writing Month you’re feeling energized inspired itching blank page make mark wouldn’t Chris’s book Plot Problem great place gettingstarted idea Also it’s important remember whatever want write legit want write start novel 30 day Great could also finish novel revise one write notnovel series essay blog post every day poem day I’m happy tell April fact National Poetry Writing Month NaPoWriMo gofind comfy corner Steal 15 minute Shut door selfcritiquing gremlin put word page might write way straight book least beginningTags Design Thinking Design Writing NaNoWriMo UX
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Aligning Sales And Marketing SaaS Teams
In the Digital Age, cohesion between departments is critical towards creating the seamless customer experience that consumers not only look for but expect, when considering new brands and businesses. A report by Forrester Research supports this by concluding that businesses with proper alignment see a 32% increase in revenue growth, while organizations with less alignment actually see a 7% decrease. Organizational alignment is particularly important between sales and marketing teams, as these two departments are so closely connected throughout the purchasing process. However, aligning sales and marketing and achieving this level of cohesion presents a lot of obstacles for companies. After all, sales and marketing have always been kept in separate containers. They still remain apart in many organizations. If your business still has this traditional structure, you should consider the powerful impact that aligning marketing and sales can have. Beyond meeting this new customer expectation, companies that have made this shift in their structure have seen 36% higher customer retention figures and 38% better success rates in sales opportunities. This discussion will focus on the steps that companies need to take into consideration as they push for alignment between marketing and sales teams. It Starts With Your Team Your first step is educating your organization, particularly your salespersons and marketers, about what alignment means and how this change will affect their duties and day-to-day work life. For some, this will be a hard adjustment because marketing and sales have for so long operated in their own bubbles. The key is showcasing how this change is going to affect the organization and promote a positive impact on revenue and growth. (Feel free to utilize some of the sales and marketing alignment statistics we’ve shared to justify the change to your staff). The truth that you need to get across to your organization is that times are changing — customers are changing. Adapting to these shifts is a matter of growth and survival. Most organizations will face some level of resistance from staff during this period of increased alignment, whether this is intentional or not. Some employees may be actively against merging sales and marketing teams together because it challenges everything that they’ve come to know and learn. Others will be on board with this new direction, but just lack the mindset that it takes. Unfortunately, you may have to make some tough personnel decisions. This means eliminating some staff and bringing in forward-thinking individuals that have experience working for an organization where marketing and sales work closely together, instead of apart. Assign Leadership To This Newly Aligned Team In the traditional, un-aligned model, sales and marketing departments each have their own leader (VP of sales, VP of marketing, etc.). As your company moves towards a more aligned organizational structure, this can create a lot of conflict. Do you allow both department heads to continue existing as part of a team? Do you let one leader go and appoint the other as the head of sales and marketing? Do you create a new leadership role, like chief revenue officer, to manage the alignment between these two teams? It’s best to have a single head to control both departments. While keeping both department heads may keep everyone happy in the short term, as no one has to be let go, if those individuals can’t effectively work as a cohesive, conflict-free team, alignment doesn’t occur. Review Your Revenue-Focused Strategy Alignment means treating sales and marketing as one entity. These once-separate departments now need to act with a singular, unified focus. The easiest way to achieve this is to focus your organization solely on driving revenue. This makes a defined path to guide both teams and ensure that everyone is marching in the same direction and with the same goals in mind. An aligned strategy has many critical components that your teams need to research and understand before proceeding: What’s the target market and what types of buyer personas exist in that audience? What messages, channels, and tactics do these buyers respond to most? What separates us from the competition? How do we utilize sales and marketing together to produce more revenue? Many of these questions your company has already answered, probably multiple times. However, readdressing them with your newly aligned teams ensures that everyone is indeed on the same page. Sometimes, poor alignment occurs because sales have a different understanding of the target audience than marketing, or they view the brand’s unique selling point differently. Create A Seamless Journey Customers just don’t follow the traditional paths to making a purchase that they used to. This is part of the reason that alignment is so crucial in the digital age. Thanks to the Internet, consumers, and brands sometimes interact on over 13 touch points before a purchase is made. Some of these are marketing-focused, while others are sales. Once you’ve created your cohesive strategy focused on producing revenue, you need to begin finding ways to utilize both sales and marketing touch points to facilitate a frictionless buying experience. Due to the sheer number of possible channels involved in a single customer’s purchasing journey, this is not an easy puzzle to solve. Not to mention, every touch point is unique in its own way, which requires lots of testing and learning to crack the code of each new platform. Eliminating friction in this customer journey involves effectively tracking their progress across all of these different touch points. As you monitor their activity, you learn about their unique preferences, needs and behaviors, which allows you to produce a smoother journey. When sales and marketing are misaligned, it can often create an experience where the customer feels that they are starting their journey over and over at each new touch point. Not only does this result in a clunky journey, but it also severely disinterests them in shopping with your business at all. Sharing Data-Born Insights And Business Intelligence Tools One of the keys to unlocking the puzzle of the customer journey is data. If sales and marketing were the apocalypses, data would be canned food. Because so much of the customer journey takes place online, there is a lot of data being created. Within all of this data is everything you need to learn about your customers. Extracting these customer insights from all this raw data, however, is a bit of a needle in a haystack conundrum. Two key obstacles get in the way: 1. The easy part: finding the right tools and solutions to help your organization collect, sort and analyze all of this unstructured data 2. The hard part: understanding which data points are most relevant and worthy of tracking to provide the answers to your company’s most pressing and revenue-producing questions Misalignment makes these obstacles even more difficult. You have two departments asking their own questions and sometimes using their own data tools. Once you bring these departments under the same roof, it becomes easier to realize the key metrics that are most valuable towards furthering your organization’s goals. Though, “easier,” in this sense, means removing only some of the hay from that pile with the needle. Communication, Communication… Communication The best tool that an organization can utilize to achieve seamless alignment of their sales and marketing is simple communication. These teams, which have operated autonomously of one another for so long, now need to work side by side. For example, marketing needs to create campaigns that aid sales’ strategies, while sales need to leverage marketing’s messages in their pitches. This produces that cohesive, frictionless purchase journey that organizations want to give their customers. There’s some simple, yet effective communication strategies that can bolster your organization’s alignment. For example: Team Meetings: No one likes large meetings, but in a properly aligned business, they are very essential. It’s a critical time to reiterate the latest goals, look at the current metrics and discuss new ways that sales can support marketing and vice versa. Feedback Loops: One of the more undervalued communication techniques is creating a feedback loop between marketers and salespersons. This creates an ongoing conversation about what’s working and what isn’t between these two, newly-connected teams. This feedback can quickly be applied and improve strategies in the immediate future. Open Office Layout: Changing the layout of your office to mix sales and marketing professionals together makes it much easier for natural communication to take place, whether it’s asking a simple question or collaborating on a new campaign. Conclusions Aligning your sales and marketing strategies is all about removing friction from the customer journey to generate increased revenue and more loyal clients. Ironically, achieving this alignment can add friction to your organization and even produce tension among your sales and marketing teams. By following the tips included in this discussion, you’ll successfully complete this transition with less turmoil. Any dramatic chance of this caliber is bound to create some disruption, but your staff will quickly realize that an aligned business performs and operates smoothly and to more significant effect, in terms of growth, revenue and overall success. https://upscri.be/hackernoon/
https://medium.com/hackernoon/aligning-sales-and-marketing-saas-teams-19ba70fcedc9
['Andrew Gazdecki']
2019-04-25 13:16:00.940000+00:00
['Marketing', 'Startup', 'Alignment', 'SaaS', 'Sales']
Title Aligning Sales Marketing SaaS TeamsContent Digital Age cohesion department critical towards creating seamless customer experience consumer look expect considering new brand business report Forrester Research support concluding business proper alignment see 32 increase revenue growth organization le alignment actually see 7 decrease Organizational alignment particularly important sale marketing team two department closely connected throughout purchasing process However aligning sale marketing achieving level cohesion present lot obstacle company sale marketing always kept separate container still remain apart many organization business still traditional structure consider powerful impact aligning marketing sale Beyond meeting new customer expectation company made shift structure seen 36 higher customer retention figure 38 better success rate sale opportunity discussion focus step company need take consideration push alignment marketing sale team Starts Team first step educating organization particularly salesperson marketer alignment mean change affect duty daytoday work life hard adjustment marketing sale long operated bubble key showcasing change going affect organization promote positive impact revenue growth Feel free utilize sale marketing alignment statistic we’ve shared justify change staff truth need get across organization time changing — customer changing Adapting shift matter growth survival organization face level resistance staff period increased alignment whether intentional employee may actively merging sale marketing team together challenge everything they’ve come know learn Others board new direction lack mindset take Unfortunately may make tough personnel decision mean eliminating staff bringing forwardthinking individual experience working organization marketing sale work closely together instead apart Assign Leadership Newly Aligned Team traditional unaligned model sale marketing department leader VP sale VP marketing etc company move towards aligned organizational structure create lot conflict allow department head continue existing part team let one leader go appoint head sale marketing create new leadership role like chief revenue officer manage alignment two team It’s best single head control department keeping department head may keep everyone happy short term one let go individual can’t effectively work cohesive conflictfree team alignment doesn’t occur Review RevenueFocused Strategy Alignment mean treating sale marketing one entity onceseparate department need act singular unified focus easiest way achieve focus organization solely driving revenue make defined path guide team ensure everyone marching direction goal mind aligned strategy many critical component team need research understand proceeding What’s target market type buyer persona exist audience message channel tactic buyer respond separate u competition utilize sale marketing together produce revenue Many question company already answered probably multiple time However readdressing newly aligned team ensures everyone indeed page Sometimes poor alignment occurs sale different understanding target audience marketing view brand’s unique selling point differently Create Seamless Journey Customers don’t follow traditional path making purchase used part reason alignment crucial digital age Thanks Internet consumer brand sometimes interact 13 touch point purchase made marketingfocused others sale you’ve created cohesive strategy focused producing revenue need begin finding way utilize sale marketing touch point facilitate frictionless buying experience Due sheer number possible channel involved single customer’s purchasing journey easy puzzle solve mention every touch point unique way requires lot testing learning crack code new platform Eliminating friction customer journey involves effectively tracking progress across different touch point monitor activity learn unique preference need behavior allows produce smoother journey sale marketing misaligned often create experience customer feel starting journey new touch point result clunky journey also severely disinterest shopping business Sharing DataBorn Insights Business Intelligence Tools One key unlocking puzzle customer journey data sale marketing apocalypse data would canned food much customer journey take place online lot data created Within data everything need learn customer Extracting customer insight raw data however bit needle haystack conundrum Two key obstacle get way 1 easy part finding right tool solution help organization collect sort analyze unstructured data 2 hard part understanding data point relevant worthy tracking provide answer company’s pressing revenueproducing question Misalignment make obstacle even difficult two department asking question sometimes using data tool bring department roof becomes easier realize key metric valuable towards furthering organization’s goal Though “easier” sense mean removing hay pile needle Communication Communication… Communication best tool organization utilize achieve seamless alignment sale marketing simple communication team operated autonomously one another long need work side side example marketing need create campaign aid sales’ strategy sale need leverage marketing’s message pitch produce cohesive frictionless purchase journey organization want give customer There’s simple yet effective communication strategy bolster organization’s alignment example Team Meetings one like large meeting properly aligned business essential It’s critical time reiterate latest goal look current metric discus new way sale support marketing vice versa Feedback Loops One undervalued communication technique creating feedback loop marketer salesperson creates ongoing conversation what’s working isn’t two newlyconnected team feedback quickly applied improve strategy immediate future Open Office Layout Changing layout office mix sale marketing professional together make much easier natural communication take place whether it’s asking simple question collaborating new campaign Conclusions Aligning sale marketing strategy removing friction customer journey generate increased revenue loyal client Ironically achieving alignment add friction organization even produce tension among sale marketing team following tip included discussion you’ll successfully complete transition le turmoil dramatic chance caliber bound create disruption staff quickly realize aligned business performs operates smoothly significant effect term growth revenue overall success httpsupscribehackernoonTags Marketing Startup Alignment SaaS Sales
2,822
Create a Running Docker Container With Gunicorn and Flask
Running With Local K8s via Minikube Assuming you already have Minikube running on your machine, follow the steps below. In order to use local Docker images, you need to run: eval $(minikube docker-env) Note that you should do that on each terminal you want to use. Next, build the image: docker build -t marounbassam/hello-flask:v1 . Run on kubectl and expose the deployment: $ kubectl run hello-flask --image=marounbassam/hello-flask:v1 --port=8003 --image-pull-policy=IfNotPresent $ kubectl expose deployment hello-flask --type=NodePort Now we can reach the endpoint of our application:
https://medium.com/better-programming/create-a-running-docker-container-with-gunicorn-and-flask-dcd98fddb8e0
['Maroun Maroun']
2020-11-04 16:37:54.771000+00:00
['Docker', 'Python', 'Gunicorn', 'Programming', 'Kubernetes']
Title Create Running Docker Container Gunicorn FlaskContent Running Local K8s via Minikube Assuming already Minikube running machine follow step order use local Docker image need run eval minikube dockerenv Note terminal want use Next build image docker build marounbassamhelloflaskv1 Run kubectl expose deployment kubectl run helloflask imagemarounbassamhelloflaskv1 port8003 imagepullpolicyIfNotPresent kubectl expose deployment helloflask typeNodePort reach endpoint applicationTags Docker Python Gunicorn Programming Kubernetes
2,823
Lowering Your Stress During the Holidays
Taking It Easy This Christmas holiday season, we get to sit down with the people we live with and share a feast where we acknowledge the things that happened to us, both the bad and the good. Without the bad, it can be hard to appreciate and enjoy the good. We savour the good because it is a luxury, and we lap it up. We deserve happiness, just as much as the next person, so there’s nothing wrong with a little enjoyment every now and then. Photo by Nabil Boukala on Unsplash — I liken happiness to honey and it’s okay to enjoy it sometimes. More often than not, a lot of us are plagued by ongoing stressors. Stress can impact a lot of areas in our lives, including our relationships and our perceptions of reality. As studies have shown, emotions can and will influence how we process neutral information. While it’s okay to be stressed sometimes, when your stress impacts your ability to make credible and reliable decisions, we sometimes need to take a step back and keep it easy. If we cannot control the outside forces that bother us, the only thing left to do is influence how we respond to those terrible situations. If that means doing a minimalist version of sought-after rituals and traditions, then that might be what you need. For example, let’s say you typically go all out in decorating your home to be that picturesque image for your neighbours to admire. This year, it’s more than okay to take a break, especially when we’re feeling more tired than usual. Plus, at the end of the day, we celebrate Christmas for the warmth and goodness it provides us, and not necessarily for the aesthetic luxury. Photo by Amy Humphries on Unsplash — Nothing like a little warmth and joy. There’s nothing wrong with working hard either, as long as you know how to pace yourself and take it easy. While we have a long year ahead of us, we need as much relaxation as we need, especially if we need to continue to fight our proverbial monsters. For now, we are readying our armour, ready to tackle and slay our demons, once and for all.
https://medium.com/preoccupy-negative-thoughts/lowering-your-stress-during-the-holidays-d2d21c8ce074
['Synthia Satkuna', 'Ma Candidate']
2020-12-24 19:30:57.178000+00:00
['Stress', 'Emotions', 'Mental Health', 'Validation', 'Psychology']
Title Lowering Stress HolidaysContent Taking Easy Christmas holiday season get sit people live share feast acknowledge thing happened u bad good Without bad hard appreciate enjoy good savour good luxury lap deserve happiness much next person there’s nothing wrong little enjoyment every Photo Nabil Boukala Unsplash — liken happiness honey it’s okay enjoy sometimes often lot u plagued ongoing stressor Stress impact lot area life including relationship perception reality study shown emotion influence process neutral information it’s okay stressed sometimes stress impact ability make credible reliable decision sometimes need take step back keep easy cannot control outside force bother u thing left influence respond terrible situation mean minimalist version soughtafter ritual tradition might need example let’s say typically go decorating home picturesque image neighbour admire year it’s okay take break especially we’re feeling tired usual Plus end day celebrate Christmas warmth goodness provides u necessarily aesthetic luxury Photo Amy Humphries Unsplash — Nothing like little warmth joy There’s nothing wrong working hard either long know pace take easy long year ahead u need much relaxation need especially need continue fight proverbial monster readying armour ready tackle slay demon allTags Stress Emotions Mental Health Validation Psychology
2,824
How startups are inverting the marketing funnel
Some weeks ago I was discussing my first months in Growth for CompareEuropeGroup, the largest financial comparison group in Europe, following the success of its sibling group in Asia. CEG has ventures in Denmark (Samlino.dk), Finland (VertaaEnsin.fi), Belgium (TopCompare.be), Portugal (ComparaJá.pt) and Norway (Samlino.no), all of them seeing considerable growth. Sat down in a nice coffeehouse in sunny Lisbon, an experienced digital marketer was inquiring me how is our approach to the customer conversion path, and what is the storytelling we use to attract the customer. My very early-stage experience forced me to think quickly to provide an answer: I haven’t outlined one. He was surprised. I later explained a bit more: In order to grow in a sustainable way (OK, as much as feasible…), I cannot think of the traditional marketing funnel to outline my digital strategy. I don’t have neither the budget nor sufficient insight to know what is the storyline I will tell to my customer. A bit surprised to hear this, he let me carry on. The approach we take is to use, optimise and exhaust the more intent-driven channels and then utilise the revenue growth to reinvest in more awareness channels. So you’re not telling a story to the customer, he replied. And with this sentence I realised that he was missing the point. More than wanting to create a storyline for the customer, I want to the customer to create it for me. This is the beauty of digital channels. The traditional strategy, planning and execution cycle that lasted several months is now shortened to days. Moreover, it is iterative more than ever. If I can have (almost) instant feedback, why not letting the customer tell me what works for him/her? The more interesting part is how this affects the marketing funnel. Looking at the traditional funnel (see below), traditional businesses rely on hypotheses to define the which story should they tell the users. “Let’s use this TV ad to create Awareness, then outdoors will bring Consideration, Conversion is done with a door-to-door”. Most of theses hypotheses come from our own assumptions of the product and the customer, but were they validated? Good marketers have done their job and ran some focus groups, but were these representative? We may have different answers to the questions, but the bottom line is that the digital world allows us to test these hypotheses in a very short period and take actions on the outcome. Credits to Travis Balinas, outboundengine.com Why am I being fussy about this so-called inversion? Sustainability. In order to grow these start-up businesses where cash is scarce (despite the usual hype around funding rounds, in which cash comes to allow marketing and operations to survive), the traditional marketing funnel is simply not available. TV is not an option, outdoors hardly. The actual only option is capture the customer that is ready to buy. For a B2C product, start-ups aim for search engines, whereas B2B typically requires more people interaction (marketing becomes sales). Andre Albuquerque (Uniplaces) was brilliant at explaining how channel utilisation is streamlined and put into cruise control, freeing up resources to explore other channels: After enough time of deepening the channel you get to cruise control (acquisition cost is maybe stable or improving at a reasonable % rate), so it’s time to restart testing more channels to grow your metrics (second red circle), and number of channels being tested increases again (third red circle), and the loop restarts. Overtime you stack up acquisition channels and your absolute metric values grows until you hit the holy grail trend of the hockey stick curve (orange line). Credits to Andre Albuquerque for such a nice chart :) Following what I said earlier, the first logical channel to explore are Action-related channels, such as Search, since it captures the customer with greater intent to buy/convert. E-mail marketing and Affiliate traffic can be also be included in this bucket, the former requiring a level of engagement with the user (or not, since several tools can stereotype your customer and provide you a “look-a-like” persona). The natural next step is to move on to Interest-based channels, such as Content (through your own blog for instance) and Referrals. Building on top of your persona (created through data gathered in the Action channels), you can now reach out to a greater audience, that still resembles in some aspects your current customers. Display and Social channels belong then to the Awareness layer of the marketing funnel, which are available to reach in a targeted and segmented way a greater, less-informed audience. These channels are then used when all the channels “below” have matured and been streamlined. Finally, TV and Outdoors can be used a later stage to “shout to the world” about your products’ existence. Most start-ups take their time to rely on these since targeting is much more inaccurate. Marketing funnel — adapted to the digital world. As mentioned above, the good performance of a channel at the bottom of the funnel will fund the development of the upper layer of channels, often at higher cost of acquisition (CPA). How can a start-up support a growing CPA? Scale, scale, scale. Cross-sell. Get more money from each transaction, or get more transactions. Whatever model the business is supported on. Summing up, you can construct your customer path by inverting the traditional marketing funnel. Start by the channels that offer an higher buying-intent customer, optimise, streamline, move up in the marketing funnel by selecting the next appropriate channel. Reinvest your earnings to climb up the ladder and reach a larger audience. The slippery funnel will be hard to climb, but the challenge is the exciting piece. This is my first Medium article, feel free to add your thoughts by commenting below.
https://medium.com/business-startup-development-and-more/how-startups-are-inverting-the-marketing-funnel-23b4067da960
['Ricardo Batista']
2017-01-19 10:51:07.625000+00:00
['Growth', 'Marketing', 'Startup', 'Digital', 'Digital Marketing']
Title startup inverting marketing funnelContent week ago discussing first month Growth CompareEuropeGroup largest financial comparison group Europe following success sibling group Asia CEG venture Denmark Samlinodk Finland VertaaEnsinfi Belgium TopComparebe Portugal ComparaJápt Norway Samlinono seeing considerable growth Sat nice coffeehouse sunny Lisbon experienced digital marketer inquiring approach customer conversion path storytelling use attract customer earlystage experience forced think quickly provide answer haven’t outlined one surprised later explained bit order grow sustainable way OK much feasible… cannot think traditional marketing funnel outline digital strategy don’t neither budget sufficient insight know storyline tell customer bit surprised hear let carry approach take use optimise exhaust intentdriven channel utilise revenue growth reinvest awareness channel you’re telling story customer replied sentence realised missing point wanting create storyline customer want customer create beauty digital channel traditional strategy planning execution cycle lasted several month shortened day Moreover iterative ever almost instant feedback letting customer tell work himher interesting part affect marketing funnel Looking traditional funnel see traditional business rely hypothesis define story tell user “Let’s use TV ad create Awareness outdoors bring Consideration Conversion done doortodoor” thesis hypothesis come assumption product customer validated Good marketer done job ran focus group representative may different answer question bottom line digital world allows u test hypothesis short period take action outcome Credits Travis Balinas outboundenginecom fussy socalled inversion Sustainability order grow startup business cash scarce despite usual hype around funding round cash come allow marketing operation survive traditional marketing funnel simply available TV option outdoors hardly actual option capture customer ready buy B2C product startup aim search engine whereas B2B typically requires people interaction marketing becomes sale Andre Albuquerque Uniplaces brilliant explaining channel utilisation streamlined put cruise control freeing resource explore channel enough time deepening channel get cruise control acquisition cost maybe stable improving reasonable rate it’s time restart testing channel grow metric second red circle number channel tested increase third red circle loop restarts Overtime stack acquisition channel absolute metric value grows hit holy grail trend hockey stick curve orange line Credits Andre Albuquerque nice chart Following said earlier first logical channel explore Actionrelated channel Search since capture customer greater intent buyconvert Email marketing Affiliate traffic also included bucket former requiring level engagement user since several tool stereotype customer provide “lookalike” persona natural next step move Interestbased channel Content blog instance Referrals Building top persona created data gathered Action channel reach greater audience still resembles aspect current customer Display Social channel belong Awareness layer marketing funnel available reach targeted segmented way greater lessinformed audience channel used channel “below” matured streamlined Finally TV Outdoors used later stage “shout world” products’ existence startup take time rely since targeting much inaccurate Marketing funnel — adapted digital world mentioned good performance channel bottom funnel fund development upper layer channel often higher cost acquisition CPA startup support growing CPA Scale scale scale Crosssell Get money transaction get transaction Whatever model business supported Summing construct customer path inverting traditional marketing funnel Start channel offer higher buyingintent customer optimise streamline move marketing funnel selecting next appropriate channel Reinvest earnings climb ladder reach larger audience slippery funnel hard climb challenge exciting piece first Medium article feel free add thought commenting belowTags Growth Marketing Startup Digital Digital Marketing
2,825
Why I’m not celebrating my birthday
And how a mindset shift can make every day feel like your birthday Oh, my birthday. In the past, I’d have been dropping hints and anticipating the big day for weeks. I would have been dreaming of it, thinking about it, and wishing for its arrival. I’ve always LOVED my birthday. But one year (in 2015, to be exact), I realized I hadn’t been very excited. It knew it wasn’t because I was bummed or having a bad birthday. And as I contemplated why, I realized that in the past, my birthday was just about the only time I gave myself permission to ask for and do what I wanted to do. But in 2015, in the months leading up to my birthday, everything had changed. A monumental, life-changing tragedy precipitated this change: the unexpected, unexplained, full-term stillbirth of my first child, Maeve Evalyn. After she died, I questioned everything in my life and made the changes I’m sharing here, but it doesn’t have to take a tragedy for YOU to do the same. As a result of losing her, and deciding to fully live for myself and for her, I’d stopped saying “someday” or “one day,” and instead I WENT FOR what I wanted. I decided I was no longer waiting for one day a year to give myself permission to do, get, and most importantly, BE, what I wanted. Since then, and to this day, I focus on these things EVERY day. I no longer spend every other day outside of my birthday feeling obligated to everyone and everything else in my life. And, while I was originally scared to be anything but a people-pleaser because I feared conflict above almost anything, ironically, that’s actually IMPROVED my relationships because I’m the authentic, genuine version of me, and that person is much happier and easier to love than the one who lived trying to be what I thought other people wanted or needed from me. In the months leading up to my birthday that fateful year when everything changed, I: Traveled to Europe for 2 weeks Moved into my dream house Tripled my monthly income Got over my lifelong fear of what others think Kicked the competitive habit and began surrounding myself with encouraging people Shared my story and started inspiring others Supported amazing high-achievers around the world in creating their dream lives I’m celebrating that change today and every day. I guess you could say I’ve started living every day like it’s my birthday! What about you? Don’t wait for your birthday; here’s how you can get closer to your dreams TODAY: 1. Be honest with yourself. What are the things you are pretending you don’t want in the name of “practicality?” Write them down. 2. Do something to make yourself smile today. Snap out of your daily rut. Exercise, meditate, go to your favorite coffee/tea shop and “treat yo’ self,” pick up a new book and get lost in it — even if you only have 5 minutes. 3. Just START. So often in my coaching and consulting, I see the theme of OVERTHOUGHT and UNDER ACTION in women who are struggling to make a change. The insightful book The Confidence Code: The Science and Art of Self-Assurance — What Women Should Know, reported that men will apply for a job when they feel 60% qualified, but women won’t apply unless they feel 100% qualified. Is this true for you, whether or not it relates to you going for a new job, starting or growing a business, or taking another risk you’ve been dreaming of? How does this relate to your life? Most importantly, action brings clarity (and relieves anxiety!), so where can you take action today? 4. Get support. Before 2015, I always told myself I could do it on my own because I prided myself on being independent and I honestly found many women to be catty or competitive. So I wasted years and years struggling in my business. Connecting with the right coach and a like-minded, supportive group of women were the two keys that helped me believe I COULD change, showed me what was possible, and catapulted me to the next level in visibility, income and living authentically, with passion, that I’d so long been dreaming of reaching. This change came for me years ago. It wasn’t just a temporary fad that eventually faded into the background of “real life” as the rawness of my grief subsided. I’ve had three more birthdays since then. And this is still how I’m embracing my life every day. This can be your reality, too. Will you embrace it? Let me know in the comments below! Next Steps Ready for more tips on how to get out of your own way and get visible with your business so that you can replace your income and quit or stay out of your 9–5? Learn the 7 simple steps to doing what you love & making 6 figures from anywhere in the first chapter of my #1 bestselling book, The Income Replacement Formula, for FREE by clicking here.
https://medium.com/thrive-global/why-im-not-celebrating-my-birthday-b6bdf661c133
['Christine Mcalister']
2019-01-22 22:18:39.627000+00:00
['Self Improvement', 'Mindset', 'Productivity', 'Entrepreneurship', 'Work Smarter']
Title I’m celebrating birthdayContent mindset shift make every day feel like birthday Oh birthday past I’d dropping hint anticipating big day week would dreaming thinking wishing arrival I’ve always LOVED birthday one year 2015 exact realized hadn’t excited knew wasn’t bummed bad birthday contemplated realized past birthday time gave permission ask wanted 2015 month leading birthday everything changed monumental lifechanging tragedy precipitated change unexpected unexplained fullterm stillbirth first child Maeve Evalyn died questioned everything life made change I’m sharing doesn’t take tragedy result losing deciding fully live I’d stopped saying “someday” “one day” instead WENT wanted decided longer waiting one day year give permission get importantly wanted Since day focus thing EVERY day longer spend every day outside birthday feeling obligated everyone everything else life originally scared anything peoplepleaser feared conflict almost anything ironically that’s actually IMPROVED relationship I’m authentic genuine version person much happier easier love one lived trying thought people wanted needed month leading birthday fateful year everything changed Traveled Europe 2 week Moved dream house Tripled monthly income Got lifelong fear others think Kicked competitive habit began surrounding encouraging people Shared story started inspiring others Supported amazing highachievers around world creating dream life I’m celebrating change today every day guess could say I’ve started living every day like it’s birthday Don’t wait birthday here’s get closer dream TODAY 1 honest thing pretending don’t want name “practicality” Write 2 something make smile today Snap daily rut Exercise meditate go favorite coffeetea shop “treat yo’ self” pick new book get lost — even 5 minute 3 START often coaching consulting see theme OVERTHOUGHT ACTION woman struggling make change insightful book Confidence Code Science Art SelfAssurance — Women Know reported men apply job feel 60 qualified woman won’t apply unless feel 100 qualified true whether relates going new job starting growing business taking another risk you’ve dreaming relate life importantly action brings clarity relief anxiety take action today 4 Get support 2015 always told could prided independent honestly found many woman catty competitive wasted year year struggling business Connecting right coach likeminded supportive group woman two key helped believe COULD change showed possible catapulted next level visibility income living authentically passion I’d long dreaming reaching change came year ago wasn’t temporary fad eventually faded background “real life” rawness grief subsided I’ve three birthday since still I’m embracing life every day reality embrace Let know comment Next Steps Ready tip get way get visible business replace income quit stay 9–5 Learn 7 simple step love making 6 figure anywhere first chapter 1 bestselling book Income Replacement Formula FREE clicking hereTags Self Improvement Mindset Productivity Entrepreneurship Work Smarter
2,826
How Negativity Can Always Stop Your Progress
Failure To Recognize Adverse Situations Will Halt Advancement… Image Courtesy of Unsplash A positive mindset is a great thing to have daily to uplift yourself and others. No one benefits from negativity or how it can subdue your progress in any situation. Looking deep into our lives, one must who is surrounding me that can bring more of a positive spin as opposed to negativity in one’s life? To be quite frank, negativity can be a mainstay in any life if you let it consume you and stop your progress to reaching more of your goals and achievements than you think. Lacking the proper mindset to move forward towards a desired result is something that takes effort. Surrounding yourself by awesome people that are like-minded can be a great thing to you and your mindset. When someone is being negative, oftentimes they’re doing it because of some reason that has nothing to do with you. Those are usually the people that you really don’t want to be around or have a meaningful relationship with. I will show how negativity can be a burden and get in the way of moving forward in life and your daily routine. Self Limited Beliefs Life provides us with many emotions and no matter how confident that you might be, self-limiting beliefs can be a negative thing. Everyone has doubts when throughout life especially when trying to get something accomplished. Image Courtesy of Unsplash Getting down on yourself no matter what the situation is can be a natural occurrence with anyone no matter who they are or what their persona might be. If you’re trying to accomplish a goal and you reach a roadblock doubting yourself, self-limiting beliefs could be the reason. We all have that little angel on one shoulder and the proverbial devil on the other shoulder giving us conflicting information about our next move. A positive mindset to the contrary can feed us great things and give encouragement to keep us going. The devil on the shoulder that’s putting in way more work than the angel on the other shoulder. The devil on one shoulder is telling you that it can’t be accomplished but at some point, you have to stop listening to it because of the negative energy that it creates. Fear of Learning or Furthering Education We all know the one person that doesn’t like to learn for one reason or another. The person that’s stuck in their ways and just can’t seem to get their feet out the quicksand to learn something new. It could be a common element that may or may not be true with you personally but you probably can relate because we all know someone like that. Sometimes learning something new can be a great thing and it can advance you in a lot of different ways whether it’s a relationship, new skill for a job or just something that could get you what you want in life. I had to do things to further my education too and I’m not just talking about school or college or anything like. I learned how to code, write tables and queries in a database better, build websites, etc. Image Courtesy of Unsplash I learned as much as possible because I knew the path that I wanted to take to be successful so I have to embrace learning new skills. Getting better daily using free tools such as YouTube, Google and iTunes and Stitcher for listening to audio podcasts can help you further your education for Free! The fear of furthering education or just learning any tactical thing can be a negative burden towards moving forward as well. Making Constant Excuses At some point, we’ve all made excuses in one form or another. It may help to come to grips and get it out of your system as soon as possible. Making continual excuses can add an abundance of negativity in your life. You can definitely stunt the growth of just about anything because making excuses is the easiest thing to do. Excuses are very easy to make and don’t require a lot of time but do sometimes require energy which is mainly wasted and unwanted. Think about how great things are when you don’t make steady explanations? Image Courtesy of Unsplash Some people are so caught up into making excuses that it’s the fabric of their existence. They don’t even realize the extent of what they’re doing and usually those same people really don’t care. Are you one of those people who make constant excuses that drain off negative energy? It’s not too late to make a change in the right direction. Stuck In Their Ways We are all stuck in our ways on something but the difference is some of us have the ability to recognize our faults. Generally, we can get out of situations but at the same time some of us just can’t because of stubbornness. I’ll give an example of being stuck in your ways: eating too many harmful foods. There has been so much research done on for health and wellness. And we know that one of the huge things that cause diseases is the food we consume. Image Courtesy of Unsplash In a lot of ways, it’s more harmful to eat a cheeseburger that it is to smoke cigarettes but it doesn’t stop us because we want that satisfaction of the food because it tastes so good. If this is something that’s in your daily or weekly diet and you just cannot remove it, then you might be stuck in your ways. Do you cherish your life or will you keep eating burgers every other day from one fast food restaurant to the next? Always Complaining Everyone complains about something whether it is intentional or apart of our fabric. There’s no way you can go through life without being dissatisfied with something whether it’s a product, your local salon or even customer service at your favorite restaurant. We can likely agree that everyone has a complaint somewhere along the line. But it’s the person that’s ALWAYS complaining that is extremely irritating. Image Courtesy of Unsplash The reality is that the “Complainer” sees it as an escape from other internal issues where he or she lacks and can’t recognize that the problem is them. The one thing that we find very hard to do in life is to look in the mirror embrace blame or better yet accountability. I truly believe that some people rather not face their inner fears and admit to being wrong about something. There’s a difference between a legitimate complaint and a constant one that shows negativity that keeps you from moving forward. Using Failure As The Reason To Quit Most people never reach their full potential, accomplish goals, and definitely halt their progress because they use failure as a reason to quit. If you look at failure as an opportunity to get back up to continue, then your chances of reaching a goal is a lot better. Image Courtesy of Unsplash Quitting is so easy to do, it requires zero effort and it’s very convenient. So many people fail because it can be a difficult task to believe in ourselves enough to think that we can actually accomplish something of value. Stop using failure as the reason to quit and keep moving in the direction of gratitude and positivity. You are much closer to a goal when you fall because of negativity and get back up than you were before. Are There Any Other Negative Ways To Stop You From Progressing? Leave A Comment, A Clap and/or A shout out on Twitter! If you liked this article, please check out the rest of my articles on Medium, Thrive Global, Good Men Project and for tips on Blogging.
https://medium.com/thrive-global/how-negativity-can-always-stop-your-progress-ee8a594bd337
['Andre L. Vaughn']
2019-03-01 01:44:28.093000+00:00
['Life Lessons', 'Productivity', 'Success', 'Entrepreneurship', 'Life']
Title Negativity Always Stop ProgressContent Failure Recognize Adverse Situations Halt Advancement… Image Courtesy Unsplash positive mindset great thing daily uplift others one benefit negativity subdue progress situation Looking deep life one must surrounding bring positive spin opposed negativity one’s life quite frank negativity mainstay life let consume stop progress reaching goal achievement think Lacking proper mindset move forward towards desired result something take effort Surrounding awesome people likeminded great thing mindset someone negative oftentimes they’re reason nothing usually people really don’t want around meaningful relationship show negativity burden get way moving forward life daily routine Self Limited Beliefs Life provides u many emotion matter confident might selflimiting belief negative thing Everyone doubt throughout life especially trying get something accomplished Image Courtesy Unsplash Getting matter situation natural occurrence anyone matter persona might you’re trying accomplish goal reach roadblock doubting selflimiting belief could reason little angel one shoulder proverbial devil shoulder giving u conflicting information next move positive mindset contrary feed u great thing give encouragement keep u going devil shoulder that’s putting way work angel shoulder devil one shoulder telling can’t accomplished point stop listening negative energy creates Fear Learning Furthering Education know one person doesn’t like learn one reason another person that’s stuck way can’t seem get foot quicksand learn something new could common element may may true personally probably relate know someone like Sometimes learning something new great thing advance lot different way whether it’s relationship new skill job something could get want life thing education I’m talking school college anything like learned code write table query database better build website etc Image Courtesy Unsplash learned much possible knew path wanted take successful embrace learning new skill Getting better daily using free tool YouTube Google iTunes Stitcher listening audio podcasts help education Free fear furthering education learning tactical thing negative burden towards moving forward well Making Constant Excuses point we’ve made excuse one form another may help come grip get system soon possible Making continual excuse add abundance negativity life definitely stunt growth anything making excuse easiest thing Excuses easy make don’t require lot time sometimes require energy mainly wasted unwanted Think great thing don’t make steady explanation Image Courtesy Unsplash people caught making excuse it’s fabric existence don’t even realize extent they’re usually people really don’t care one people make constant excuse drain negative energy It’s late make change right direction Stuck Ways stuck way something difference u ability recognize fault Generally get situation time u can’t stubbornness I’ll give example stuck way eating many harmful food much research done health wellness know one huge thing cause disease food consume Image Courtesy Unsplash lot way it’s harmful eat cheeseburger smoke cigarette doesn’t stop u want satisfaction food taste good something that’s daily weekly diet cannot remove might stuck way cherish life keep eating burger every day one fast food restaurant next Always Complaining Everyone complains something whether intentional apart fabric There’s way go life without dissatisfied something whether it’s product local salon even customer service favorite restaurant likely agree everyone complaint somewhere along line it’s person that’s ALWAYS complaining extremely irritating Image Courtesy Unsplash reality “Complainer” see escape internal issue lack can’t recognize problem one thing find hard life look mirror embrace blame better yet accountability truly believe people rather face inner fear admit wrong something There’s difference legitimate complaint constant one show negativity keep moving forward Using Failure Reason Quit people never reach full potential accomplish goal definitely halt progress use failure reason quit look failure opportunity get back continue chance reaching goal lot better Image Courtesy Unsplash Quitting easy requires zero effort it’s convenient many people fail difficult task believe enough think actually accomplish something value Stop using failure reason quit keep moving direction gratitude positivity much closer goal fall negativity get back Negative Ways Stop Progressing Leave Comment Clap andor shout Twitter liked article please check rest article Medium Thrive Global Good Men Project tip BloggingTags Life Lessons Productivity Success Entrepreneurship Life
2,827
Strategies for Learning New Skills Faster
Strategies for Learning New Skills Faster Like programming Learning any new skill has become easier than ever due to the internet. We are just a few clicks away from any information. Do you know that most people take an average of 25–30 days to complete a 30-hour course on Coursera/Udemy. Online MOOCs have a completion rate of less than 15%, which means that out of 1,000 people registered in a course, 850 of them never complete the course, and drop out. But why do people drop out in the middle of a course? What could be the reason? Is the course not good, or don’t we have enough motivation to continue? I conducted a survey of around 200 people, and here is what they say. Survey Response — 1 Survey Response — 2 Some key insights: More than 55% of people said they take more than one month of time. More than 70% of people have a course-completion rate of approximately 50% or less. Now, let’s see what the approaches are to learn any new skill faster.
https://medium.com/better-programming/how-to-learn-anything-faster-40b54235f0d6
['Deepak Kumar']
2020-12-05 07:12:42.348000+00:00
['Startup', 'Learning To Code', 'Learning', 'Entrepreneurship', 'Programming']
Title Strategies Learning New Skills FasterContent Strategies Learning New Skills Faster Like programming Learning new skill become easier ever due internet click away information know people take average 25–30 day complete 30hour course CourseraUdemy Online MOOCs completion rate le 15 mean 1000 people registered course 850 never complete course drop people drop middle course could reason course good don’t enough motivation continue conducted survey around 200 people say Survey Response — 1 Survey Response — 2 key insight 55 people said take one month time 70 people coursecompletion rate approximately 50 le let’s see approach learn new skill fasterTags Startup Learning Code Learning Entrepreneurship Programming
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A Conversational Design Primer
A Conversational Design Primer Looking to get started in voice or chatbot design? Learn the basic terminology and concepts to empower better design decisions. As we used to say at Amazon, the tech industry has passed through the threshold of a “one way door” with regard to conversational experiences. Our industry will never look back at the world of purely point-and-click websites as the end-all and be-all of customer experiences. My own path in the space of both voice UI and conversational design has been a long and winding road: from video games to CRM cloud services; from Cortana to Alexa. In 2017, I started a new chapter in that career, sharing the knowledge I’d gained along the way with others via workshops (Giving Voice to your Voice Designs) and talks (Blank Page to World Stage, The Future of Voice). Now that I’m focused on my work as Principal Designer and owner of Ideaplatz, I’d like to share with you the introductory primer to the key concepts in the conversational design space: the primer I wish I’d had when starting out on this modern wave of conversationally focused experiences. As it was passed on to me, I want to pass on to you the basic concepts you’ll need to start thinking about design for conversational user interfaces. Image licensed via Adobe Stock. Not sure whether voice or conversation is right for you? You may want to start with one of my introductory Medium posts: Voice User Interface Design: New Solutions to Old Problems. Let’s talk about the past Up until the advent of dedicated voice experiences on the iPhone, conversational interfaces fell into one of two categories: Dictation-based Products like Dragon Naturally Speaking, which required considerable training and were about transcription, not transactions. (This line has blurred in the ensuing decades.) These systems can transform the spoken word into digital text, but were not optimized for taking action on the spoken word. They also required quite a bit of user-specific training to get their accuracy to acceptable levels. Grammar-based Best for command-and-control scenarios, grammar-based systems know a fixed dictionary of terms and will match speech to the closest option within that dictionary. Many early voice-enabled toys and video games like Hey You, Pikachu and Disney Friends (disclaimer: I was the Lead Producer on Disney Friends) were grammar-based. The key shortcoming of grammar-based systems is that they are inherently unforgiving. If a customer changes the order of the words in their request in an unexpected way, or otherwise contravenes expectations, the system can’t adapt and will often take the wrong action as a result. In many ways, these shortcomings can be mapped to our own learning frameworks as children. When we are young, we only know a few words. Words that sound like words we know may be miscategorized because we don’t know how to adapt yet. Connectivity changes everything Once cloud services became a reality, everything changed. You see, to go beyond the dictionary approach, we needed to teach systems how to extract meaning from words. Not just to match sounds to letters, but to apply the semantic rules within a chosen language to understand the difference between similar words, and to understand that different phrasings sometimes mean the same thing. Consider this pair of examples: “Computer, turn on the lights in the play room.” “Computer, play ‘Turn it On Again’.” A system that was just looking for words that sound similar might get confused here. “Turn”, “on”, and “play” are all key words present in both phrases. Think about how we as humans distinguish between the two. It’s actually pretty complicated, isn’t it? Part of it is ordering, part of it is additional context (like the word “room” — which might not be present if I asked for lights in the basement), and part of it is those tricky linguistic connective tissues like “in” and “the”. This is the difference between early voice recognition systems and a natural language recognition system — the ability to go beyond sound and understand the underlying meaning in a customer’s request. It’s a complicated problem, which is why we needed artificial intelligence to solve it. The language behind natural language If you’re coming from a world of more traditional, visually-oriented design (and almost all of us do) — working on conversational designs will mean familiarizing yourself with the terms of the trade. You may encounter a new type of collaborator in linguists or speech scientists, who are the individuals tasked with teaching your artificial intelligence solution about the semantic meanings specific to your product, service, or feature. Utterance The utterance is the “ground truth” about a customer’s request; it is the specific way in which a request is posed to the system. For chatbots, this is typically a text string; for voice-based systems, it may be helpful to think of this as the actual recording of the request. This utterance may include typos, grammatical errors, ambient noise, or interruptions — whatever actually happened at the time of the request. Intent Conversational designers use the term “intent” to signify the customer’s goal when making a request. Many utterances may correspond to a single intent. For example, a thermostat may have an intent model to represent a customer’s desire to make it incrementally warmer in the room. The following utterances could all be mapped to Thermostat/Warmer: Make it warmer in here. I’m cold! It’s cold in here. Turn up the heat. Interaction designers and researchers are often responsible for examining potential customer intents and providing recommendations to speech scientists. During this process, the design team would also provide sample utterances like these for each intent to get things started. Slot A slot is essentially a conversational variable, for those of you with a programming background. For the rest of us, slots are parts of an utterance that we expect to vary from request to request. A common example is weather. Consider the following request: Computer, what’s the weather going to be in Orlando on January 9? In this example, most of the utterance is unlikely to vary much, though you might see discrepancies in ordering. But the bolded text indicates slots: places where we expect the content to vary almost every time. Intents often depend upon the content of a slot to complete the request. For a “Weather on specific day” intent, we would expect at minimum a date; and optionally a location we’re curious about. Entity This is where our industry terminology starts to feel a bit needlessly obtuse. Entities are a concept that almost everyone seems to understand, but no one can describe; maddening for those coming in from the outside. IBM’s developer documentation defines entities as “usually a classification of objects aimed to help alert the response to an intent.” Which is… not particularly helpful. Essentially, entities are a model of the concepts important to your product, and how those concepts relate to one another. You might start modeling your entities by drawing out a conceptual map of the terms your customers must deal with, and filling in the relationships and values. In most systems, you can define your own entity types. For example, when I was prototyping a Microsoft Azure onboarding chatbot during my latest stint at Microsoft, one entity I defined was an “operating system”, and that entity could have values of “Windows,” “Linux”, or “Mac OS”. But in many cases, the values in our slots correspond to very well-understood entities, like time or city name. In other cases, the value maps to a massive catalog of slot values, like musical artists. In those cases, designers don’t usually model the entities themselves. Slot Types (aka System Entities) This concept goes by several names in the industry, but in short a slot type is a hint to our natural language system to apply additional logic to the bit of utterance in that slot. For example, Alexa allows you to define a slot type of “Date”. Any utterance processed as AMAZON.Date is processed based on Amazon’s extensive experience. Slot types are often very forgiving: for the case of Date, it can handle a range of utterances like “January 9”, “January 9 2019”, “The 9th of January”, “January”, etc. Every system comes with its own system entities or slot types, so your mileage may vary; there is no universal set of concepts. Dates, times, cities, colors, and numbers are some of the most common slot types. For further examples, start with this Amazon Slot Type reference or Dialogflow System Entities. Prompt The text of a response to be delivered back to a customer conversationally on behalf of the system. “Prompt” sounds like it’s asking for something, but that’s not necessarily the case. Some systems use terms like “response” instead to avoid this issue. But note that we said text of a response. What if your response should be spoken? Text to Speech If you’re building a voice-enabled system, it’s a generally accepted best practice to ‘respond in kind’. That is, speak when you’re spoken to. But most prompts start out as text. 5 years ago, most spoken prompts required a recording session with a voice-over artist, resulting in MP3s that could be played back. That doesn’t scale to a huge problem space, like including all possible musicians and song titles. Alexa, Google Home and Cortana have all moved to using a text to speech system, or TTS. These used to sound very robotic, but proprietary advances in technology have allowed these systems to generate arbitrary audio prompts very convincingly in real time — as long as there’s a functional Internet connection to transmit the resulting audio file. Conversation or not? You’ll notice that I often specify “voice AND conversational” design, or differentiate between the two. This is because the two aren’t quite equivalent, at least as the industry sees them. Conversational design can apply to BOTH text-based chatbots AND voice user interfaces. can apply to BOTH text-based chatbots AND voice user interfaces. Voice user interface design refers ONLY to experiences where the input (and usually output) is audio-based, or spoken. An experience designed for voice can usually translate back to a traditional chat medium, but an experience built for chat is NOT necessarily going to succeed over voice. This is because these two modalities engage different parts of the human brain: visual memory and processing are fundamentally different from auditory memory and processing. A good foundation in cognitive psychology will go a long way for designers asked to straddle this divide. This distinction is a large part of what I cover in my workshop, “Giving Voice to your Voice Designs”. It’s also why the Twitter hashtag #VoiceFirst has gained such traction. The movement isn’t about ONLY interacting via voice, so much as it is starting from the most difficult and restrictive interaction model, and moving out from there. The systems behind conversational understanding As someone who’s worked for years in spaces considered by the outside world as “artificial intelligence”, I’m often asked about the robot revolution. When will SkyNet take over? I usually reply with the observation that I feel the singularity is overhyped at best. Most systems we perceive as a singular, unified intelligence (like Alexa and Cortana) are actually a series of disparate services on the Internet communicating in real time. If any link in this chain fails, our ability to understand and respond is limited, or completely removed. So what are these disparate systems? Let’s dive in. Automatic Speech Recognition (ASR) For voice controlled systems, automatic speech recognition is the first and most rudimentary step in the process — not so much artificial intelligence as a processing step. ASR systems take the spoken utterance from the customer (ie, the waveform itself) and chop it up into individual segments called phonemes. A phoneme is defined by Merriam-Webster as “any of the abstract units of the phonetic system of a language that correspond to a set of similar speech sounds.” ASR systems don’t understand sentence structure, but they do understand some basic fundamentals about their assigned language: for example, K and Z are unlikely to appear adjacent to each other in English text, so we can rule those guesses out. The output of the ASR step is a first guess at the customer’s utterance. Since we don’t have the full context, this guess might change. But it’s enough to move on to the natural language understanding system. Natural Language Understanding (NLU) Natural language understanding systems are the real artificial intelligence behind your favorite conversational systems. NLU engines take text as input — either directly from chat, or the output from an ASR system if speech is involved. From that starting point, a natural language understanding system attempts to map the utterance to an intent. Think of the NLU system as working to answer these three questions: What does the customer want to accomplish? (Intent) What’s unique about this request? (Slots) Is there anything in this request I need help understanding? (Entity Recognition) For voice recognition systems, sometimes the NLU system decides the ASR output doesn’t make sense… but it might be close. In these situations, NLU might send an utterance back to ASR with additional context to check a hypothesis. If you’ve ever used Siri and noticed that she erased her transcription of what you said and replaced it with something more accurate — this is what happened. Entity Recognition (ER) If our utterance contains a non-standard slot type, our utterance might be processed by a separate entity recognition engine. For finite sets, the entity recognition might be trivial, but usually still technically separate. In cases where our slot is expected to contain a reference to a giant catalog of possibilities, that piece of the utterance is often sent over to an entity recognition system. In some cases, these are run by different companies entirely. For example, Nuance Communications is a company that has helped many speech systems by providing an entity recognition service for musical requests. This is harder than it sounds, when you consider that the catalog of available music is literally getting larger day by day, and will continue to do so until the end of civilization. And don’t get speech scientists started on artist names like Ke$ha. Entity recognition engines often account for these sorts of challenges. Business logic This isn’t a formal system, per se, but I wanted to make the point that your system’s response to an intent is completely separate from the processing and identification of that intent. Most conversational services out there focus on intent processing, but the business logic to respond to an intent comes down to traditional programming, though often a serverless solution like Lambda or Azure Functions. For example, my Trainer Tips skill has two main components: the input processing, via Alexa’s Skill Kit; and the business logic, hosted on AWS Lambda, which generates the prompts for each intent and sends them to Alexa’s text-to-speech engine. Next steps on Medium With regard to conversational UI, I’m workshopping a few future pieces on the dangers of AI-powered experiences, conversational error patterns, and beyond. A great way to get started with conversational interfaces is to build your own chat app for fun, and see what you learn. I’m hoping to put together a chatbot tutorial for designer/developers, likely using LUIS.ai and Azure Bot Service. For those less experienced on the development side, Alexa skills have spawned a cottage industry of helper apps, tutorials, and templates to get you on your way. If you’re not yet ready to dive in headfirst but want more context, I have a written a wide variety of Medium articles exploring voice and conversational design, as well as some posts about more general product design topics. Peruse them all at my profile page, and follow me to get updates when new articles are available. Best of luck with wherever the conversation takes you. May the voice be with you.
https://medium.com/ideaplatz/a-conversational-design-primer-9914778559d5
['Cheryl Platz']
2019-04-20 19:33:00.441000+00:00
['Speech Recognition', 'Artificial Intelligence', 'Design', 'Alexa', 'Conversational UI']
Title Conversational Design PrimerContent Conversational Design Primer Looking get started voice chatbot design Learn basic terminology concept empower better design decision used say Amazon tech industry passed threshold “one way door” regard conversational experience industry never look back world purely pointandclick website endall beall customer experience path space voice UI conversational design long winding road video game CRM cloud service Cortana Alexa 2017 started new chapter career sharing knowledge I’d gained along way others via workshop Giving Voice Voice Designs talk Blank Page World Stage Future Voice I’m focused work Principal Designer owner Ideaplatz I’d like share introductory primer key concept conversational design space primer wish I’d starting modern wave conversationally focused experience passed want pas basic concept you’ll need start thinking design conversational user interface Image licensed via Adobe Stock sure whether voice conversation right may want start one introductory Medium post Voice User Interface Design New Solutions Old Problems Let’s talk past advent dedicated voice experience iPhone conversational interface fell one two category Dictationbased Products like Dragon Naturally Speaking required considerable training transcription transaction line blurred ensuing decade system transform spoken word digital text optimized taking action spoken word also required quite bit userspecific training get accuracy acceptable level Grammarbased Best commandandcontrol scenario grammarbased system know fixed dictionary term match speech closest option within dictionary Many early voiceenabled toy video game like Hey Pikachu Disney Friends disclaimer Lead Producer Disney Friends grammarbased key shortcoming grammarbased system inherently unforgiving customer change order word request unexpected way otherwise contravenes expectation system can’t adapt often take wrong action result many way shortcoming mapped learning framework child young know word Words sound like word know may miscategorized don’t know adapt yet Connectivity change everything cloud service became reality everything changed see go beyond dictionary approach needed teach system extract meaning word match sound letter apply semantic rule within chosen language understand difference similar word understand different phrasing sometimes mean thing Consider pair example “Computer turn light play room” “Computer play ‘Turn Again’” system looking word sound similar might get confused “Turn” “on” “play” key word present phrase Think human distinguish two It’s actually pretty complicated isn’t Part ordering part additional context like word “room” — might present asked light basement part tricky linguistic connective tissue like “in” “the” difference early voice recognition system natural language recognition system — ability go beyond sound understand underlying meaning customer’s request It’s complicated problem needed artificial intelligence solve language behind natural language you’re coming world traditional visuallyoriented design almost u — working conversational design mean familiarizing term trade may encounter new type collaborator linguist speech scientist individual tasked teaching artificial intelligence solution semantic meaning specific product service feature Utterance utterance “ground truth” customer’s request specific way request posed system chatbots typically text string voicebased system may helpful think actual recording request utterance may include typo grammatical error ambient noise interruption — whatever actually happened time request Intent Conversational designer use term “intent” signify customer’s goal making request Many utterance may correspond single intent example thermostat may intent model represent customer’s desire make incrementally warmer room following utterance could mapped ThermostatWarmer Make warmer I’m cold It’s cold Turn heat Interaction designer researcher often responsible examining potential customer intent providing recommendation speech scientist process design team would also provide sample utterance like intent get thing started Slot slot essentially conversational variable programming background rest u slot part utterance expect vary request request common example weather Consider following request Computer what’s weather going Orlando January 9 example utterance unlikely vary much though might see discrepancy ordering bolded text indicates slot place expect content vary almost every time Intents often depend upon content slot complete request “Weather specific day” intent would expect minimum date optionally location we’re curious Entity industry terminology start feel bit needlessly obtuse Entities concept almost everyone seems understand one describe maddening coming outside IBM’s developer documentation defines entity “usually classification object aimed help alert response intent” is… particularly helpful Essentially entity model concept important product concept relate one another might start modeling entity drawing conceptual map term customer must deal filling relationship value system define entity type example prototyping Microsoft Azure onboarding chatbot latest stint Microsoft one entity defined “operating system” entity could value “Windows” “Linux” “Mac OS” many case value slot correspond wellunderstood entity like time city name case value map massive catalog slot value like musical artist case designer don’t usually model entity Slot Types aka System Entities concept go several name industry short slot type hint natural language system apply additional logic bit utterance slot example Alexa allows define slot type “Date” utterance processed AMAZONDate processed based Amazon’s extensive experience Slot type often forgiving case Date handle range utterance like “January 9” “January 9 2019” “The 9th January” “January” etc Every system come system entity slot type mileage may vary universal set concept Dates time city color number common slot type example start Amazon Slot Type reference Dialogflow System Entities Prompt text response delivered back customer conversationally behalf system “Prompt” sound like it’s asking something that’s necessarily case system use term like “response” instead avoid issue note said text response response spoken Text Speech you’re building voiceenabled system it’s generally accepted best practice ‘respond kind’ speak you’re spoken prompt start text 5 year ago spoken prompt required recording session voiceover artist resulting MP3s could played back doesn’t scale huge problem space like including possible musician song title Alexa Google Home Cortana moved using text speech system TTS used sound robotic proprietary advance technology allowed system generate arbitrary audio prompt convincingly real time — long there’s functional Internet connection transmit resulting audio file Conversation You’ll notice often specify “voice conversational” design differentiate two two aren’t quite equivalent least industry see Conversational design apply textbased chatbots voice user interface apply textbased chatbots voice user interface Voice user interface design refers experience input usually output audiobased spoken experience designed voice usually translate back traditional chat medium experience built chat necessarily going succeed voice two modality engage different part human brain visual memory processing fundamentally different auditory memory processing good foundation cognitive psychology go long way designer asked straddle divide distinction large part cover workshop “Giving Voice Voice Designs” It’s also Twitter hashtag VoiceFirst gained traction movement isn’t interacting via voice much starting difficult restrictive interaction model moving system behind conversational understanding someone who’s worked year space considered outside world “artificial intelligence” I’m often asked robot revolution SkyNet take usually reply observation feel singularity overhyped best system perceive singular unified intelligence like Alexa Cortana actually series disparate service Internet communicating real time link chain fails ability understand respond limited completely removed disparate system Let’s dive Automatic Speech Recognition ASR voice controlled system automatic speech recognition first rudimentary step process — much artificial intelligence processing step ASR system take spoken utterance customer ie waveform chop individual segment called phoneme phoneme defined MerriamWebster “any abstract unit phonetic system language correspond set similar speech sounds” ASR system don’t understand sentence structure understand basic fundamental assigned language example K Z unlikely appear adjacent English text rule guess output ASR step first guess customer’s utterance Since don’t full context guess might change it’s enough move natural language understanding system Natural Language Understanding NLU Natural language understanding system real artificial intelligence behind favorite conversational system NLU engine take text input — either directly chat output ASR system speech involved starting point natural language understanding system attempt map utterance intent Think NLU system working answer three question customer want accomplish Intent What’s unique request Slots anything request need help understanding Entity Recognition voice recognition system sometimes NLU system decides ASR output doesn’t make sense… might close situation NLU might send utterance back ASR additional context check hypothesis you’ve ever used Siri noticed erased transcription said replaced something accurate — happened Entity Recognition ER utterance contains nonstandard slot type utterance might processed separate entity recognition engine finite set entity recognition might trivial usually still technically separate case slot expected contain reference giant catalog possibility piece utterance often sent entity recognition system case run different company entirely example Nuance Communications company helped many speech system providing entity recognition service musical request harder sound consider catalog available music literally getting larger day day continue end civilization don’t get speech scientist started artist name like Keha Entity recognition engine often account sort challenge Business logic isn’t formal system per se wanted make point system’s response intent completely separate processing identification intent conversational service focus intent processing business logic respond intent come traditional programming though often serverless solution like Lambda Azure Functions example Trainer Tips skill two main component input processing via Alexa’s Skill Kit business logic hosted AWS Lambda generates prompt intent sends Alexa’s texttospeech engine Next step Medium regard conversational UI I’m workshopping future piece danger AIpowered experience conversational error pattern beyond great way get started conversational interface build chat app fun see learn I’m hoping put together chatbot tutorial designerdevelopers likely using LUISai Azure Bot Service le experienced development side Alexa skill spawned cottage industry helper apps tutorial template get way you’re yet ready dive headfirst want context written wide variety Medium article exploring voice conversational design well post general product design topic Peruse profile page follow get update new article available Best luck wherever conversation take May voice youTags Speech Recognition Artificial Intelligence Design Alexa Conversational UI
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Pandas on Steroids: Dask- End to End Data Science with python code
Pandas on Steroids: Dask- End to End Data Science with python code End to End Parallelized Data Science from Reading Big Data to Data Manipulation to Visualisation to Machine Learning Dask- Familiar pandas with superpowers As the saying goes, a data scientist spends 90% of their time in cleaning data and 10% in complaining about the data. Their complaints may range from data size, faulty data distributions, Null values, data randomness, systematic errors in data capture, differences between train and test sets and the list just goes on and on. One common bottleneck theme is the enormity of data size where either the data doesn’t fit into memory or the processing time is so large(In order of multi-mins) that the inherent pattern analysis goes for a toss. Data scientists by nature are curious human beings who want to identify and interpret patterns normally hidden from cursory Drag-N-Drop glance. They need to wear multiple hats and make the data confess via repeated tortures(read iterations 😂 ) They wear multiple hats during exploratory data analysis and from a minimal dataset with 6 columns on New York Taxi Fare dataset( https://www.kaggle.com/c/new-york-city-taxi-fare-prediction) - ID, Fare, Time of Trip, Passengers and Location, their questions may range from: 1. How the fares have changed Year-Over-Year? 2. Has the number of trips increased across the years? 3. Do people prefer traveling alone or they have company? 4. Has the small distance rides increased as people have become lazier? 5. What time of the day and day of week do people want to travel? 6. Is there emergence of new hotspots in the city recently except the regular Air Port pickup and drop? 7. Are people taking more inter-city trips? 8. Has the traffic increased leading to more fares/time taken for the same distances? 9. Are there cluster of pick-up and Drop points or areas which see high traffic? 10. Are there outliers in data i.e 0 distance and fare of $100+ and so on? 11. Do the demand change during Holiday season and airport trips increase? 12. Is there any correlation of weather i.e rain or snow with the taxi demand? Even after answering these questions, multiple sub-threads can emerge i.e can we predict how the Covid affected New year is going to be, How the annual NY marathon shifts taxi demand, If a particular route if more prone to have multiple passengers(Party hub) vs Single Passengers( Airport to Suburbs). To quench these curiosities, time is of the essence and its criminal to keep the data scientists waiting for 5+ minutes to read a csv file(55 Mn rows) or do a column add followed by aggregation. Also, since the majority of Data Scientists are self-taught and they have been so much used to pandas data frame API that they wouldn’t want to start the learning process all over again with a different API like numba, Spark or datatable. I have tried juggling between DPLYR(R), Pandas(Python) and pyspark(Spark) and it is a bit unfulfilling/unproductive considering the need for a uniform pipeline and code syntax. However, for the curious folks, I have written a pyspark starter guide here: https://medium.com/@ravishankar_22148/billions-of-rows-milliseconds-of-time-pyspark-starter-guide-c1f984023bf2 In subsequent sections, I am trying to provide a hands on guide to Dask with minimal architectural change from our beloved Pandas: Data Read and Profiling Dask vs Pandas speed How is Dask able to process data ~90X faster i.e Sub 1 secs to 91 secs in pandas. What makes Dask so popular is the fact that it makes analytics scalable in Python and not necessarily need switching back and forth between SQL, Scala and Python.The magical feature is that this tool requires minimum code changes. It breaks down computation into pandas data frames and thus operates in parallel to enable fast calculations. 2. Data Aggregation: With absolutely 0 change from Pandas API, it is able to perform aggregation and sorting in milliseconds, Please note .compute() function at the end of lazy computation which brings the results of big data to memory in Pandas Data Frame. 3. Machine Learning: Code snippet below provides a working example of feature engineering and ML model building in Dask using XGBoost Feature Engineering and ML Model with Dask Conclusion: Dask is a powerful tool offering parallel computing, big data handling and creating end to end Data Science pipeline. It has a steep learning curve as the API is almost similar to pandas and it can handle Out Of Memory computations(~10X of RAM) like a breeze. Since it is a living blog, I will be writing subsequent parts in Dask series where we will be targeting Kaggle leaderboard using parallel processing. Let me know in comments if you are facing any issues in setting up Dask or unable to perform any Dask Operations or even for a general chit-chat. Happy Learning!!! Sources:
https://medium.com/analytics-vidhya/pandas-on-steroids-dask-end-to-end-data-science-with-python-code-1845d3722c8a
['Ravi Shankar']
2020-10-21 12:27:47.251000+00:00
['Machine Learning', 'Python', 'Dask', 'Parallel Processing', 'Big Data']
Title Pandas Steroids Dask End End Data Science python codeContent Pandas Steroids Dask End End Data Science python code End End Parallelized Data Science Reading Big Data Data Manipulation Visualisation Machine Learning Dask Familiar panda superpower saying go data scientist spends 90 time cleaning data 10 complaining data complaint may range data size faulty data distribution Null value data randomness systematic error data capture difference train test set list go One common bottleneck theme enormity data size either data doesn’t fit memory processing time largeIn order multimins inherent pattern analysis go toss Data scientist nature curious human being want identify interpret pattern normally hidden cursory DragNDrop glance need wear multiple hat make data confess via repeated torturesread iteration 😂 wear multiple hat exploratory data analysis minimal dataset 6 column New York Taxi Fare dataset httpswwwkagglecomcnewyorkcitytaxifareprediction ID Fare Time Trip Passengers Location question may range 1 fare changed YearOverYear 2 number trip increased across year 3 people prefer traveling alone company 4 small distance ride increased people become lazier 5 time day day week people want travel 6 emergence new hotspot city recently except regular Air Port pickup drop 7 people taking intercity trip 8 traffic increased leading farestime taken distance 9 cluster pickup Drop point area see high traffic 10 outlier data ie 0 distance fare 100 11 demand change Holiday season airport trip increase 12 correlation weather ie rain snow taxi demand Even answering question multiple subthreads emerge ie predict Covid affected New year going annual NY marathon shift taxi demand particular route prone multiple passengersParty hub v Single Passengers Airport Suburbs quench curiosity time essence criminal keep data scientist waiting 5 minute read csv file55 Mn row column add followed aggregation Also since majority Data Scientists selftaught much used panda data frame API wouldn’t want start learning process different API like numba Spark datatable tried juggling DPLYRR PandasPython pysparkSpark bit unfulfillingunproductive considering need uniform pipeline code syntax However curious folk written pyspark starter guide httpsmediumcomravishankar22148billionsofrowsmillisecondsoftimepysparkstarterguidec1f984023bf2 subsequent section trying provide hand guide Dask minimal architectural change beloved Pandas Data Read Profiling Dask v Pandas speed Dask able process data 90X faster ie Sub 1 sec 91 sec panda make Dask popular fact make analytics scalable Python necessarily need switching back forth SQL Scala PythonThe magical feature tool requires minimum code change break computation panda data frame thus operates parallel enable fast calculation 2 Data Aggregation absolutely 0 change Pandas API able perform aggregation sorting millisecond Please note compute function end lazy computation brings result big data memory Pandas Data Frame 3 Machine Learning Code snippet provides working example feature engineering ML model building Dask using XGBoost Feature Engineering ML Model Dask Conclusion Dask powerful tool offering parallel computing big data handling creating end end Data Science pipeline steep learning curve API almost similar panda handle Memory computations10X RAM like breeze Since living blog writing subsequent part Dask series targeting Kaggle leaderboard using parallel processing Let know comment facing issue setting Dask unable perform Dask Operations even general chitchat Happy Learning SourcesTags Machine Learning Python Dask Parallel Processing Big Data
2,830
The CRISPR Nobel Prize & Data Stored in DNA Gets Destroyed
NEWSLETTER The CRISPR Nobel Prize & Data Stored in DNA Gets Destroyed This Week in Synthetic Biology (Issue #11) Receive this newsletter every Friday morning! Sign up here: https://synbio.substack.com/ Data, Stored in DNA, Gets Destroyed (But In A Good Way) DNA is promising for data storage, mainly because a single gram of DNA can store 256 petabytes of information. But there’s a problem: DNA is, in some cases, too stable. To remove a user’s data from DNA on “nucleic acid hard drives” of the future, scientists first need to develop better ways to selectively target, and destroy, DNA. A new method, published in Nature Communications, could be a contender for wiping DNA hard drives in the year 2087 (assuming the human race survives that long). DNA sequences, each containing a “True” barcode and one, or several, “False” barcodes, are first mixed together. Then, “truth markers” — DNA sequences that selectively bind to the “True” sequences — are added to the mixture. If the mixture is then heated to 95 degrees Celsius, the “truth markers” fall off and information from the “True” bits is lost. It’s a simple technique, with promising results. The researchers showed that “8 separate bitmap images can be stably encoded and read after storage at 25 °C for 65 days with an average of over 99% correct information recall, which extrapolates to a half-life of over 15 years at 25 °C. Heating to 95 °C for 5 minutes, however, permanently erases the message.” An enzymatic pathway has been assembled on top of a Tobacco mosaic virus. Using peptide “linkers”, the scientists, based in Hong Kong, tethered “three terpene biosynthetic enzymes” to the outer particles of the virus, and grew them inside of E. coli cells. The goal was to explore how the proximity of enzymes impacts the bioproduction of a molecule (in this case, amorpha-4,11-diene). Since the Tobacco mosaic virus is 300nm long, metabolic engineers could presumably use it as a foundation to assemble any number of complex enzymatic pathways. This study was published in Bioconjugate Chemistry. Deep Learning to Design RNA “Switches” Two studies, published in Nature Communications, used deep learning to guide the engineering of RNA “toehold switches”. These RNA switches are, basically, synthetic RNA sequences that can be turned ON and OFF. In their OFF state, the toehold switches form a hairpin loop and cannot be read by the ribosomes — they do not produce a protein. The addition of an RNA “trigger”, however, can be used to turn a toehold switch ON; translation can proceed. Toehold switches are especially useful because a lot of them can be present in a cell at the same time, and triggers can be designed for each of them. This means that many genes can be precisely controlled for synthetic biology applications. Unfortunately, toehold switches are really difficult to design, and even a slight tweak to a sequence can impact their utility. In the first study, led by Nicolaas M. Angenent-Mari, over 90,000 toehold switches were synthesized and tested using clever experiments that enabled the activity of each toehold switch to be individually assessed. After testing each of the RNAs, data was fed into a deep learning model (which I won’t even pretend to understand). The output from that model looks promising: “[Deep Neural Networks] trained on nucleotide sequences outperform (R2 = 0.43–0.70) previous state-of-the-art thermodynamic and kinetic models (R2 = 0.04–0.15).” In the second study, led by Jacqueline Valeri, two “deep learning architectures” were introduced — called STORM and NuSpeak — to improve the performance of RNA toehold switches. Both studies are open access, and represent a paradigm shift in how quickly synthetic biologists will be able to design and engineer biological molecules that behave as expected. The vast majority of plants on earth are C3 plants; when it’s hot or dry, C3 plants close their stomas, oxygen builds up, and the efficiency of photosynthesis goes down. C4 plants, on the other hand, have figured out a way to avoid that pesky oxygen buildup. In C4 plants, fixation of entering carbon dioxide occurs in mesophyll cells, while the Calvin cycle instead occurs inside of bundle-sheath cells. This separation means that C4 cells can avoid oxygen buildup, and typically have a higher photosynthesis efficiency. A new study in Plant Biotechnology Journal has introduced five genes into a specific strain of rice, boosting its photosynthetic flux by…well, only about 2%. But these early results look promising. If scientists can get the balance of gene expression right, it may one day prove useful for boosting rice yields, a staple food for more than half of the planet’s population. Biological circuits, operating inside of cells, can be built from dozens of individual genetic parts. Even a tiny tweak to one of those parts — a promoter, ribosome binding site, or terminator — can impact the performance of the genetic circuit. A new study exhaustively characterized all 54 parts in a circuit, parametrized them, and then used the data to build a mathematical model that could “predict circuit performance, dynamics, and robustness.” They even used the computed parameters to calculate “the cellular power (RNAP and ribosome usage) required to maintain a circuit state.” This study, published in Nature Communications, is open access.
https://medium.com/bioeconomy-xyz/the-crispr-nobel-prize-data-stored-in-dna-gets-destroyed-df00c34c9111
['Niko Mccarty']
2020-10-09 09:06:46.420000+00:00
['Tech', 'Startup', 'Nobel Prize', 'Newsletter', 'Science']
Title CRISPR Nobel Prize Data Stored DNA Gets DestroyedContent NEWSLETTER CRISPR Nobel Prize Data Stored DNA Gets Destroyed Week Synthetic Biology Issue 11 Receive newsletter every Friday morning Sign httpssynbiosubstackcom Data Stored DNA Gets Destroyed Good Way DNA promising data storage mainly single gram DNA store 256 petabyte information there’s problem DNA case stable remove user’s data DNA “nucleic acid hard drives” future scientist first need develop better way selectively target destroy DNA new method published Nature Communications could contender wiping DNA hard drive year 2087 assuming human race survives long DNA sequence containing “True” barcode one several “False” barcodes first mixed together “truth markers” — DNA sequence selectively bind “True” sequence — added mixture mixture heated 95 degree Celsius “truth markers” fall information “True” bit lost It’s simple technique promising result researcher showed “8 separate bitmap image stably encoded read storage 25 °C 65 day average 99 correct information recall extrapolates halflife 15 year 25 °C Heating 95 °C 5 minute however permanently era message” enzymatic pathway assembled top Tobacco mosaic virus Using peptide “linkers” scientist based Hong Kong tethered “three terpene biosynthetic enzymes” outer particle virus grew inside E coli cell goal explore proximity enzyme impact bioproduction molecule case amorpha411diene Since Tobacco mosaic virus 300nm long metabolic engineer could presumably use foundation assemble number complex enzymatic pathway study published Bioconjugate Chemistry Deep Learning Design RNA “Switches” Two study published Nature Communications used deep learning guide engineering RNA “toehold switches” RNA switch basically synthetic RNA sequence turned state toehold switch form hairpin loop cannot read ribosome — produce protein addition RNA “trigger” however used turn toehold switch translation proceed Toehold switch especially useful lot present cell time trigger designed mean many gene precisely controlled synthetic biology application Unfortunately toehold switch really difficult design even slight tweak sequence impact utility first study led Nicolaas AngenentMari 90000 toehold switch synthesized tested using clever experiment enabled activity toehold switch individually assessed testing RNAs data fed deep learning model won’t even pretend understand output model look promising “Deep Neural Networks trained nucleotide sequence outperform R2 043–070 previous stateoftheart thermodynamic kinetic model R2 004–015” second study led Jacqueline Valeri two “deep learning architectures” introduced — called STORM NuSpeak — improve performance RNA toehold switch study open access represent paradigm shift quickly synthetic biologist able design engineer biological molecule behave expected vast majority plant earth C3 plant it’s hot dry C3 plant close stoma oxygen build efficiency photosynthesis go C4 plant hand figured way avoid pesky oxygen buildup C4 plant fixation entering carbon dioxide occurs mesophyll cell Calvin cycle instead occurs inside bundlesheath cell separation mean C4 cell avoid oxygen buildup typically higher photosynthesis efficiency new study Plant Biotechnology Journal introduced five gene specific strain rice boosting photosynthetic flux by…well 2 early result look promising scientist get balance gene expression right may one day prove useful boosting rice yield staple food half planet’s population Biological circuit operating inside cell built dozen individual genetic part Even tiny tweak one part — promoter ribosome binding site terminator — impact performance genetic circuit new study exhaustively characterized 54 part circuit parametrized used data build mathematical model could “predict circuit performance dynamic robustness” even used computed parameter calculate “the cellular power RNAP ribosome usage required maintain circuit state” study published Nature Communications open accessTags Tech Startup Nobel Prize Newsletter Science
2,831
The Origin of Machine Learning
Zoologists and psychologists study learning in animals and humans. There are several parallels between animal and machine learning. Certainly, many techniques in machine learning derived from the efforts of psychologists to make more precise their theories of animal and human learning through computational models. It seems likely also that the concepts and techniques being explored by researchers in machine learning may illuminate certain aspects of biological learning. As regards machines, we might say, very broadly, that a machine learns whenever it changes its structure, program, or data in such a manner that its expected future performance improves. Some of these changes, such as the addition of a record to a database, fall comfortably within the province of other disciplines and are not necessarily better understood for being called learning. Machine learning usually refers to the changes in systems that perform tasks associated with artificial intelligence. Such tasks involve recognition, diagnosis, planning, robot control, prediction, etc. Why should machines have to learn? Why not design machines to perform as desired in the first place? There are several reasons why machine learning is important. Of course, as I have already mentioned that the achievement of learning in machines might help us understand how animals and humans learn. But there are important engineering reasons as well. Some of these are: Some tasks cannot be defined well except by example; that is, we might be able to specify input/output pairs but not a concise relationship between inputs and desired outputs. We would like machines to be able to adjust their internal structure to produce correct outputs for a large number of sample inputs and thus suitably constrain their input/output function to approximate the relationship implicit in the examples. It is possible that hidden among large piles of data are important relationships and correlations. Machine learning methods can often be used to extract these relationships (data mining). Human designers often produce machines that do not work as well as desired in the environments in which they are used. In fact, certain characteristics of the working environment might not be completely known at design time. Machine learning methods can be used for the on-the-job improvement of existing machine designs. The amount of knowledge available about certain tasks might be too large for explicit encoding by humans. Machines that learn this knowledge gradually might be able to capture more of it than humans would want to write down. Environments change over time. Machines that can adapt to a changing environment would reduce the need for constant redesign. New knowledge about tasks is constantly being discovered by humans. Vocabulary changes. There is a constant stream of new events in the world. Continuing redesign of AI systems to conform to new knowledge is impractical, but machine learning methods might be able to track much of it. I hope you liked this article on the origin of Machine Learning. Feel free to ask your valuable questions in the comments section below. You can also connect with me from here, to learn every topic of Machine Learning.
https://medium.com/the-innovation/the-origin-of-machine-learning-c2a0893ee0c4
['Aman Kharwal']
2020-09-02 18:05:18.341000+00:00
['Programming', 'Artificial Intelligence', 'Python', 'Data Science', 'Machine Learning']
Title Origin Machine LearningContent Zoologists psychologist study learning animal human several parallel animal machine learning Certainly many technique machine learning derived effort psychologist make precise theory animal human learning computational model seems likely also concept technique explored researcher machine learning may illuminate certain aspect biological learning regard machine might say broadly machine learns whenever change structure program data manner expected future performance improves change addition record database fall comfortably within province discipline necessarily better understood called learning Machine learning usually refers change system perform task associated artificial intelligence task involve recognition diagnosis planning robot control prediction etc machine learn design machine perform desired first place several reason machine learning important course already mentioned achievement learning machine might help u understand animal human learn important engineering reason well task cannot defined well except example might able specify inputoutput pair concise relationship input desired output would like machine able adjust internal structure produce correct output large number sample input thus suitably constrain inputoutput function approximate relationship implicit example possible hidden among large pile data important relationship correlation Machine learning method often used extract relationship data mining Human designer often produce machine work well desired environment used fact certain characteristic working environment might completely known design time Machine learning method used onthejob improvement existing machine design amount knowledge available certain task might large explicit encoding human Machines learn knowledge gradually might able capture human would want write Environments change time Machines adapt changing environment would reduce need constant redesign New knowledge task constantly discovered human Vocabulary change constant stream new event world Continuing redesign AI system conform new knowledge impractical machine learning method might able track much hope liked article origin Machine Learning Feel free ask valuable question comment section also connect learn every topic Machine LearningTags Programming Artificial Intelligence Python Data Science Machine Learning
2,832
You’ve Settled in as an Engineer. Now What?
You’ve Settled in as an Engineer. Now What? How to avoid the plateau and continue to grow Photo by True Agency on Unsplash Congrats! You’ve settled in at your first job. You’ve made it past the initial wave of impostor syndrome and have some idea of what you’re doing and what you’re good at. You might’ve even received a promotion or two. You’re no longer wildly floundering every day and are able to at least flounder in the right direction. You might even be on your second or third job at this point. You actually feel like a real engineer now. Now what? It’s common to feel a sensation of plateauing after an initial few years of hypergrowth. This is only natural: Growth comes from new information, and the supply of novelty provided by a job quickly dries up as the years pass by. Up to this point, simply engaging with your job was enough to provide steady improvement; now, you must actively seek new information to keep growing. Before proceeding, I want to clarify one thing: being happy with where you are is perfectly fine. You might feel entirely comfortable with plateauing, and that doesn’t make you any less of a person. If you’re content and have job security, congrats — you’ve won. It’s not worth it to burn yourself out trying to level up if you’re not motivated to do so.
https://medium.com/better-programming/youve-settled-in-as-an-engineer-now-what-b7f12c277131
['Tim Hwang']
2020-12-27 23:59:34.334000+00:00
['Personal Development', 'Startup', 'Software Engineering', 'Learning To Code', 'Programming']
Title You’ve Settled Engineer WhatContent You’ve Settled Engineer avoid plateau continue grow Photo True Agency Unsplash Congrats You’ve settled first job You’ve made past initial wave impostor syndrome idea you’re you’re good might’ve even received promotion two You’re longer wildly floundering every day able least flounder right direction might even second third job point actually feel like real engineer It’s common feel sensation plateauing initial year hypergrowth natural Growth come new information supply novelty provided job quickly dry year pas point simply engaging job enough provide steady improvement must actively seek new information keep growing proceeding want clarify one thing happy perfectly fine might feel entirely comfortable plateauing doesn’t make le person you’re content job security congrats — you’ve It’s worth burn trying level you’re motivated soTags Personal Development Startup Software Engineering Learning Code Programming
2,833
I Wish Marketing Was Easy
.. but it’s not. Last week I was talking to a brilliant app developer. He launched his app few months ago and now he wants to “market it”. BTW this is very typical in the startup community. We build our apps / products and then start thinking about getting users. This is what I told him. If developing an app is hard, marketing it is 10x harder (ali) Why? There are 100s of apps that are launched daily. It’s hard to get people’s attention for your product. I read product hunt daily and I can’t even name 3 apps / products I saw there this morning. I saw a lot of cool stuff but, I can’t name any right now. I wish I was wrong but marketing is not easy. If you think of marketing as an after-thought, you will FAIL. Marketing != Selling Marketing = Educating Start educating your potential users as soon as possible. You can use content marketing as a medium. I know its a big word, but content marketing is not hard. It’s actually very simple. Here are some simple steps. 1 — Create a website (or landing page) for your app 2 — Install an email capture form on the home page 3 — Install Google Analytics 4 — Add a blog to your website 5 — Do some research and come up with 10 articles you can write. If this seems scary, just look at your competitor’s blog. What type of content they are producing. Steal some ideas from there. 6 — You can also use a tool like Buzzsumo to get some viral content ideas. 7 — Write and publish one article every week. 8 — If you suck at writing, it’s OK. That makes 2 of us. You can find ghost writers on Fiverr.com or Upwork.com 9 — You should also submit your startup to directories like Product Hunt, Beta list, and Startup list. 10 — Setup Google Alerts on your niche keywords and reach out to people who are writing about your industry or competitors. This is what I did to get my app featured in some news outlets. Here is the step by step process > Free press for an app Yes, marketing is HARD, but you can do it. Again, just think of marketing = educating. Your job is not to just to create beautiful apps. You have to tell your target audience about it. You kinda owe it to them. Start educating people about your idea the day you write your first if statement. (ali) Now over to you. Are you working on a startup? How are you educating your target audience about your product?
https://medium.com/social-media-growth-hacking-hub/i-wish-marketing-was-easy-5328b342a1ae
['Ali Mirza']
2016-05-03 07:09:21.363000+00:00
['Startup', 'Marketing', 'Growth']
Title Wish Marketing EasyContent it’s Last week talking brilliant app developer launched app month ago want “market it” BTW typical startup community build apps product start thinking getting user told developing app hard marketing 10x harder ali 100 apps launched daily It’s hard get people’s attention product read product hunt daily can’t even name 3 apps product saw morning saw lot cool stuff can’t name right wish wrong marketing easy think marketing afterthought FAIL Marketing Selling Marketing Educating Start educating potential user soon possible use content marketing medium know big word content marketing hard It’s actually simple simple step 1 — Create website landing page app 2 — Install email capture form home page 3 — Install Google Analytics 4 — Add blog website 5 — research come 10 article write seems scary look competitor’s blog type content producing Steal idea 6 — also use tool like Buzzsumo get viral content idea 7 — Write publish one article every week 8 — suck writing it’s OK make 2 u find ghost writer Fiverrcom Upworkcom 9 — also submit startup directory like Product Hunt Beta list Startup list 10 — Setup Google Alerts niche keywords reach people writing industry competitor get app featured news outlet step step process Free press app Yes marketing HARD think marketing educating job create beautiful apps tell target audience kinda owe Start educating people idea day write first statement ali working startup educating target audience productTags Startup Marketing Growth
2,834
Neurons in Spreadsheets
Neurons in Spreadsheets Your own neural network on the cheap In the previous post, we saw what a neural network is and how it works. Now comes the fun part. We’ll make one in a spreadsheet. It doesn’t matter which spreadsheet you use. You can visualise such neurons in Excel, or you can equally well use LibreOffice, Google Sheets or any other spreadsheet application. Image by the author In the top line, the two yellow cells are the input values. You can change these to simulate various inputs. The next line contains the two synaptic weights by which we will multiply the input values. Here we put them to 0.6 to simulate a logical and. Like above, if you change both synaptic weights to 1.1, you will make the neuron behave like a logical or, since the threshold is put at 1, and if either input is 1.1, and thus greater than the threshold value, the neuron will fire. In the next line, we see the activation value, which is just the sum of the two weighted inputs. The next line contains the threshold, which in all these examples is 1. But there is no reason not to change it to any other value if you want to experiment. Finally, in the last line, the blue cell contains the output of the neuron. This will be 1 if the neuron has fired or 0 if the neuron has not fired. You can also easily add additional neurons to your network and try to create more complex behaviours. The only special thing you need to do is to insert two formulas into the spreadsheet: Into cell C3 (the “activation” cell), we enter the formula for calculating the weighted sum of the two inputs: =(D1*D2)+(B1*B2). Into cell C5 (“output”), we enter a conditional statement: =if(C3>=C4, 1, 0). This is saying: if the sum of the inputs (cell C3) is greater than the threshold (cell C4), the neuron will fire (output=1); otherwise, it will stay silent (output=0). These formulas are written for Google Sheets, so if you use another spreadsheet application, you might need to change the syntax a bit. That’s it! Your first, very own artificial neuron. You can now play with it. You can change the synaptic weights and the activation thresholds, and observe how it works. You can also easily add additional neurons to your network and try to create more complex behaviours. Of course, this doesn’t yet learn. It is pre-programmed by the fixed synaptic weights to do one thing only. As an additional example, let’s look at how we would create a little network that can calculate the ‘exclusive or’, or xor, function in a spreadsheet. Here is the network we want to simulate (we discussed how this works in the previous post): Image by the author And here is the same neural network in a spreadsheet table. Again, the input is on top (yellow), and the output is at the bottom (blue). But now we have three neurons. The first layer (above) consists of two neurons (pink and green). Each of these neurons is connected to the two yellow inputs; this is why each has two synapses instead of one. Each of these neurons has its own (blue) output. Both intermediate outputs from the first layer feed into the orange neuron at the bottom. The orange neuron’s inputs are the outputs of the previous layer; this is why we don’t have yellow input cells for that neuron. The output of the whole network is the blue cell at the very bottom. This neuron will implement an xor function between its (yellow) inputs in the first row and the blue output cell at the very bottom: Image by the author What you can see from this, is how the behaviour of a neural network is all encoded in the synaptic weights, which, in this case, we entered by hand. In a later post will see how an artificial neural network can change these weights by itself, and in this way learn new behaviours. Make sure to follow this series, so you don’t miss the fun! Simulating neural networks in a spreadsheet is a great way to learn how they work and to get accustomed to the basic ideas and the structure of artificial neurons. I hope you enjoyed this and I hope to see you around here next time! Thanks for reading!
https://medium.com/the-innovation/neurons-in-spreadsheets-e917c5c77a22
['Moral Robots']
2020-10-10 17:38:20.374000+00:00
['Neural Networks', 'Artificial Intelligence', 'AI', 'Programming', 'Education Technology']
Title Neurons SpreadsheetsContent Neurons Spreadsheets neural network cheap previous post saw neural network work come fun part We’ll make one spreadsheet doesn’t matter spreadsheet use visualise neuron Excel equally well use LibreOffice Google Sheets spreadsheet application Image author top line two yellow cell input value change simulate various input next line contains two synaptic weight multiply input value put 06 simulate logical Like change synaptic weight 11 make neuron behave like logical since threshold put 1 either input 11 thus greater threshold value neuron fire next line see activation value sum two weighted input next line contains threshold example 1 reason change value want experiment Finally last line blue cell contains output neuron 1 neuron fired 0 neuron fired also easily add additional neuron network try create complex behaviour special thing need insert two formula spreadsheet cell C3 “activation” cell enter formula calculating weighted sum two input D1D2B1B2 cell C5 “output” enter conditional statement ifC3C4 1 0 saying sum input cell C3 greater threshold cell C4 neuron fire output1 otherwise stay silent output0 formula written Google Sheets use another spreadsheet application might need change syntax bit That’s first artificial neuron play change synaptic weight activation threshold observe work also easily add additional neuron network try create complex behaviour course doesn’t yet learn preprogrammed fixed synaptic weight one thing additional example let’s look would create little network calculate ‘exclusive or’ xor function spreadsheet network want simulate discussed work previous post Image author neural network spreadsheet table input top yellow output bottom blue three neuron first layer consists two neuron pink green neuron connected two yellow input two synapsis instead one neuron blue output intermediate output first layer feed orange neuron bottom orange neuron’s input output previous layer don’t yellow input cell neuron output whole network blue cell bottom neuron implement xor function yellow input first row blue output cell bottom Image author see behaviour neural network encoded synaptic weight case entered hand later post see artificial neural network change weight way learn new behaviour Make sure follow series don’t miss fun Simulating neural network spreadsheet great way learn work get accustomed basic idea structure artificial neuron hope enjoyed hope see around next time Thanks readingTags Neural Networks Artificial Intelligence AI Programming Education Technology
2,835
When is data science a house of cards?
June Andrews | Pinterest engineer, Data Science As data scientists, when we reach an answer, we often communicate that answer and move on. But what happens when there are multiple data scientists with varying answers? The expense of replicating and testing the quality of work often leaves critical business challenges unstaffed. At Pinterest, we lowered the cost of replication to the point that could afford to run an experiment. So we did. We asked nine data scientists and machine learning engineers the same question, in the same setting, on the same day. We received nine different results. Reducing the costs of data science In order to efficiently replicate results nine times, we used a new method of iterative supervised clustering. It’s phenomenally easy to grok and comes with a three step Python notebook with pre-loaded data. It makes analysis fun again. The algorithm is an extension of Klaufman and Kleinberg’s KDD paper and is explained in the following diagrams. Stage 1: Use your favorite clustering algorithm to break up data into candidate clusters. Stage 2: Ask a domain expert to interact with visualizations of each cluster, select the most human interpretable description and define that cluster. A cluster definition includes a name, a description and a short Python function determining if a point belongs to that cluster. Stage 3: Now that we have a human interpretable cluster, we don’t need the machine to focus on data in that cluster, so remove the labeled data. Repeat from stage 1 and stop when the domain expert is no longer interested in the remaining data and labels remaining points as Unclassified. There we go! The power of human interpretable clustering is now in your hands. Digging into billions of data-rich Pins There was one particular question we wanted to put this to use for. As a catalog of ideas, Pinterest is built on an interest graph of +75 billion Pins saved by +100 million monthly active users onto +1 billion boards. Boards articulate how ideas can become reality. This is incredible data. There’s a tiny detail that works so well, you rarely notice it — behind each Pin is a link into the wild wild web. For the sources behind Pins, we wanted to know how do Pinners engage with link domains? Measuring Pin engagement To answer this question, we pulled a sample of 100K link domains and looked at how Pinners engaged with content during its first year on Pinterest. In particular, we pulled Pins created from the Pinterest Save button, both on and off Pinterest. The volume of new Pins reflects how a domain is performing on the web, and repins reflect how a domain is performing on Pinterest. The data was cleaned, normalized and loaded into a Python notebook. (We love our app aesthetic, and couldn’t help but have our notebooks follow suit.) Find additional clustering details in my talk at the from the O’Reilly Strata conference. You’ll find link domains fall into an interesting set of clusters. My favorite is “Pinterest Specials”, domains whose popularity or reachability has greatly diminished on the web, but whose content lives on and thrives within the Pinterest ecosystem. Here are our the monikers of Link Domain Types: Replicating data science We asked the question of how Pinners engage with link domains and found an interesting and insightful answer that helps us understand what types of products to build. Let’s ask that question again. This is where we asked nine data scientists and machine learning engineers the same question. Each is an industry veteran and has been at Pinterest for more than one year. They work with Pinterest content and are part of the team helping surface great content to Pinners through 1.5 trillion recommendations every year. With the above algorithm and handling of the data, each person completed a clustering of link domains within an hour. The only remaining step before sharing the cluster with colleagues was pulling domain examples from each cluster. Before we reveal the results, let us take a quick minute to review existing work touching on the replicability of analysis. Three incredible industry studies have surfaced in the last year. The first was a study on how skin tone affected the rate at which red cards attributed in soccer, published in Nature. Twenty-nine crowd-sourced researchers analyzed the same data and shared reviews of each other’s methods. While there’s a relatively consistent answer of yes, it makes a slight difference. Ten of the 29 teams have deviating results from the opposite conclusion to an astonishingly strong correlation. The replication crisis in medicine and science deserves at least one citation in this context. Last year, Begley and Ioannidis [Reproducibility in Science] pegged 75 percent to 90 percent of preclinical research as irreproducible. If you care about the effectiveness of cancer treatments, you’re in for a scary read. While some flaws have arisen from scandals of fabricated data such as with Diederik Stapel a majority of shortcomings have been attributed to the analysis of data and the human error under pressure to produce publishable results. In a recent test of asking the same question of the same data, The New York Times sent the same poll results to four other reputable pollsters. While the difference between Clinton at +3 and Clinton at +4 may seem negligible, one reputable pollster reported a conclusion of Trump winning Florida, which is an astronomically different outcome. For data science, is the diversity of our results on the level of Clinton within one point, or are data science results on polar ends of the spectrum? Going back to our test with nine data scientists and machine learning engineers, through the development of lightweight interactive algorithms and using Python notebooks with preloaded data, we lowered the cost of replicating data science work to the point we could ask everyone the same question: how do Pinners engage with link domains? Results We received nine different results that were so different, they may as well be as diverse as the previous studies in reproducibility. We found two reasons for the different results. The smaller influence was that some results contained bad answers. First, these answers were caused by two skills we can detect and level up people in: Preconceived notions of what the data entails before looking at the data. Cherry picking on a subset of features without understanding the larger picture. The second cause comes from a difference in perspective. Some data scientists were intent on the viral aspects of growth while others focused on the return on investment within the Pinterest ecosystem. For a sample of different universes of perspective on Pinterest content, here are the unique monikers of clusters in different results: House of cards We asked the same question nine times and received nine astronomically different answers. When have we built irreproducible analysis on top of irreproducible analysis to the point that data-driven decisions are no longer supported by data? If we want to advance in the future we must ask the hard question, we must speak Lord Voldemort’s name. When is data science a house of cards? There is an avalanche of supporting work I believe will enable data science as a field to answer this question in the near future. A key component is the infrastructural investment by many companies throughout Silicon Valley making experimental systems and fast access to data the standard. Another is that the industry-wide effort to recruit and train data scientists has taken data scientists from a scarce resource to within reach. The most recent key effort is that in reproducibility, a natural precursor to replicability is the ability to run the same analysis over the same data, with the same parameters, twice. Setting those parameters and designing models is still an expensive process, requiring a week or more for a broad question. With the development of faster Human-in-the-Loop algorithms, we’re lowering the cost of having multiple data scientists answer the same question. All of these components combined bring on the perfect storm to experiment and understand how different data science practices impact the business bottom line. It’s a hard question. But as a field, I believe we can take it on. To stay informed and be involved in future efforts, join us.
https://medium.com/pinterest-engineering/when-is-data-science-a-house-of-cards-86c9ab0a2c6f
['Pinterest Engineering']
2017-02-21 20:16:02.646000+00:00
['Data Science', 'Big Data', 'Engineering', 'A B Testing', 'Pinterest']
Title data science house cardsContent June Andrews Pinterest engineer Data Science data scientist reach answer often communicate answer move happens multiple data scientist varying answer expense replicating testing quality work often leaf critical business challenge unstaffed Pinterest lowered cost replication point could afford run experiment asked nine data scientist machine learning engineer question setting day received nine different result Reducing cost data science order efficiently replicate result nine time used new method iterative supervised clustering It’s phenomenally easy grok come three step Python notebook preloaded data make analysis fun algorithm extension Klaufman Kleinberg’s KDD paper explained following diagram Stage 1 Use favorite clustering algorithm break data candidate cluster Stage 2 Ask domain expert interact visualization cluster select human interpretable description define cluster cluster definition includes name description short Python function determining point belongs cluster Stage 3 human interpretable cluster don’t need machine focus data cluster remove labeled data Repeat stage 1 stop domain expert longer interested remaining data label remaining point Unclassified go power human interpretable clustering hand Digging billion datarich Pins one particular question wanted put use catalog idea Pinterest built interest graph 75 billion Pins saved 100 million monthly active user onto 1 billion board Boards articulate idea become reality incredible data There’s tiny detail work well rarely notice — behind Pin link wild wild web source behind Pins wanted know Pinners engage link domain Measuring Pin engagement answer question pulled sample 100K link domain looked Pinners engaged content first year Pinterest particular pulled Pins created Pinterest Save button Pinterest volume new Pins reflects domain performing web repins reflect domain performing Pinterest data cleaned normalized loaded Python notebook love app aesthetic couldn’t help notebook follow suit Find additional clustering detail talk O’Reilly Strata conference You’ll find link domain fall interesting set cluster favorite “Pinterest Specials” domain whose popularity reachability greatly diminished web whose content life thrives within Pinterest ecosystem moniker Link Domain Types Replicating data science asked question Pinners engage link domain found interesting insightful answer help u understand type product build Let’s ask question asked nine data scientist machine learning engineer question industry veteran Pinterest one year work Pinterest content part team helping surface great content Pinners 15 trillion recommendation every year algorithm handling data person completed clustering link domain within hour remaining step sharing cluster colleague pulling domain example cluster reveal result let u take quick minute review existing work touching replicability analysis Three incredible industry study surfaced last year first study skin tone affected rate red card attributed soccer published Nature Twentynine crowdsourced researcher analyzed data shared review other’s method there’s relatively consistent answer yes make slight difference Ten 29 team deviating result opposite conclusion astonishingly strong correlation replication crisis medicine science deserves least one citation context Last year Begley Ioannidis Reproducibility Science pegged 75 percent 90 percent preclinical research irreproducible care effectiveness cancer treatment you’re scary read flaw arisen scandal fabricated data Diederik Stapel majority shortcoming attributed analysis data human error pressure produce publishable result recent test asking question data New York Times sent poll result four reputable pollster difference Clinton 3 Clinton 4 may seem negligible one reputable pollster reported conclusion Trump winning Florida astronomically different outcome data science diversity result level Clinton within one point data science result polar end spectrum Going back test nine data scientist machine learning engineer development lightweight interactive algorithm using Python notebook preloaded data lowered cost replicating data science work point could ask everyone question Pinners engage link domain Results received nine different result different may well diverse previous study reproducibility found two reason different result smaller influence result contained bad answer First answer caused two skill detect level people Preconceived notion data entail looking data Cherry picking subset feature without understanding larger picture second cause come difference perspective data scientist intent viral aspect growth others focused return investment within Pinterest ecosystem sample different universe perspective Pinterest content unique moniker cluster different result House card asked question nine time received nine astronomically different answer built irreproducible analysis top irreproducible analysis point datadriven decision longer supported data want advance future must ask hard question must speak Lord Voldemort’s name data science house card avalanche supporting work believe enable data science field answer question near future key component infrastructural investment many company throughout Silicon Valley making experimental system fast access data standard Another industrywide effort recruit train data scientist taken data scientist scarce resource within reach recent key effort reproducibility natural precursor replicability ability run analysis data parameter twice Setting parameter designing model still expensive process requiring week broad question development faster HumanintheLoop algorithm we’re lowering cost multiple data scientist answer question component combined bring perfect storm experiment understand different data science practice impact business bottom line It’s hard question field believe take stay informed involved future effort join usTags Data Science Big Data Engineering B Testing Pinterest
2,836
The Future of Content Marketing is Already Here
Experienced marketers expect change. If you continue to use the same strategies and tactics today that worked 20 years ago, you will get buried. It has been quietly whispered in marketing circles for the past few years that Google has been suppressing organic reach. It has been more difficult to hit the magically shrinking first page of the world’s largest search engine. The experts at The Markup finally conducted an experiment that demonstrated what most marketers already suspected — Google shows you a lot of content to keep you on Google before showing you any organic results. While these practices may raise ethical and antitrust concerns, you have to deal with the reality on the ground. It’s time for businesses and marketers to think about what the true state of content marketing is. Cranking out dozens or hundreds of 500-word blog posts is not going to help your business. That doesn’t mean content marketing is dead. It means that you need to look at the purpose of content marketing is and understand how to use it beyond keywords and blog posts. Purpose of Content Marketing Content marketing is a way to build trust with your ideal prospects and move them into your sales funnel. Content marketing was not invented for the internet. It has existed for hundreds of years. Benjamin Franklin’s Poor Richard’s Almanac was a form of content marketing to show off his printing expertise. Brands as diverse as John Deere and Betty Crocker have made fortunes using content marketing long before the first microprocessor was ever fired up. We tend to associate content marketing with blog posts because that has been one of the cheapest tools in the marketing toolbox for the past 20 years. Only recently have businesses begun to embrace video and podcasts as content marketing tools. Many marketers have gotten complacent. They acted like Google would always be around to drive organic traffic to websites if they followed a few simple best practices. While those days are long gone, that doesn’t mean blogs or content marketing are dead. It means that you need to find new ways to get your content in front of your ideal customers. You need to be more creative and disciplined in how you showcase your authority and expertise. Google is Killing Traditional Business Blogging A blog used to be the best way to build almost any kind of online business. You could write high-quality posts and know that the search engine algorithms would eventually find your content. If you wanted to build an audience faster, you could just write more content. Blogs can still be a powerful way to build a business. But, it takes much longer to bear fruit. You also can’t put up a bunch of short blogs. Your content needs to be more detailed than ever before. You are not just competing with other blogs — you are competing with Google’s desire to drive traffic within its own ecosystem. The best performing blog content is now skyscraper posts or cornerstone posts that are 2,000-words to 10,000-words long. These are much more expensive to produce, but if used wisely, they provide a much higher return on investment than short blog posts that now seem disposable. You also need to do more legwork to drive traffic to your content. That means rethinking the way your sales funnels are constructed. The Old Model and the New Way The old content marketing model relied on organic traffic. You wrote content that people found on search engines. That content invited people to contact you or to join your mailing list. Once you had a prospect’s contact information, you could guide them through your sales funnel. Now, organic traffic is too slow and too small. If you have enough time, six months to three years, you can still rely primarily on organic traffic to power your business. Most entrepreneurs and marketers aren’t that patient. The new way requires you either invest in social media advertising to drive traffic to your content or to expand the channels you use to increase your organic reach. This often means branching out from blog posts and expanding into different types of media. Content marketing is a way for you to show your audience what you can do. It provides an entrance to your sales funnel. If your content is only generating likes, views, and shares, you are doing it wrong. Effective content marketing collects contact information, and it generates email list sign-ups. Is Email the New Blog? Email has always been an important part of a digital marketing strategy. If you have someone’s email, you have the key to their heart. You can reach them directly. Direct marketing is the best way to convert marketing dollars into revenues. It used to be that you created a massive amount of content to generate email list sign-ups. Now, you need to create fewer, better quality types of content to generate email sign-ups. Instead of pushing out blog posts to social media and the blogosphere, savvy businesses now save their best material for their email lists. Services like Substack are betting massive amounts of money that email newsletters will replace the blog as the primary form of long-term content marketing. It is much more cost-effective to invest money in high-value content as a lead magnet to build email lists of your ideal customers than to write a million blog posts. Once you have someone on your list, you can send them the same content you used to put on your blog in an email. Your emails nurture the relationship with your audience the way blog posts used to. But, with email, you have a much better sense of how effective something is. You also can drill down on the core needs of your audience. Best of all, Google isn’t scraping your email content and using it to keep people in their ecosystem. Email gives you a direct line to the people most likely to buy from you. Content Curation Another critical difference in modern content marketing is the role curation plays. The truth is none of your customers lack access to information. They don’t need you to tell them how or why to do something. They can just ask Siri or Alexa. What your audience needs is a way to filter all of the information out there. While every business still needs to create amazing content, they also need to focus on curating content for their customers. Curation means you put the best of the web together in a simple bundle for people to consume. You will want to include some of your best work too. Through curation, more people will come to trust you. They will also learn to enjoy your unique brand voice. If you love music, chances are you enjoy checking out the playlists your favorite artists make in Spotify. Those playlists are a form of curation. They are a type of content marketing. Curation scares some businesses because they are afraid of sending their customers away. They don’t trust their customers to come back. In March of 2020, Taylor Swift created a Spotify playlist for Women’s History Month that highlighted a bunch of other female artists. Was Swift worried that her fans would discover other artists and never listen to her music again? No, because that’s idiotic. That playlist was good for Swift’s career and it was a nice signal boost to other talented artists. Curation shows people that you are confident enough in your brand voice and business value to highlight the great work other businesses are doing. Reimagining Your Sales Funnel The future of content marketing will require you to create and curate content on many different channels. You may want to use Apple podcasts or TikTok or YouTube. But, no matter where you create content, you need a sales funnel. You need a strategy behind your content marketing. It used to be that you wanted to drive everyone to your website or blog. You still need your own website. But now you want to drive traffic to a specific lead magnet or landing page to join your mailing list. That lead magnet could be a bribe like a free PDF, or it could be a skyscraper blog post that anyone can access. You may find that curating content helps you build your email list faster than creating all of your own original content. However, you need to get people on your email list, and then you need a strategy to nurture those leads into becoming paying customers. If you think this sounds almost exactly like the old way of building a funnel, you are right. The only difference is in how you are using content to get people to join your email list. You don’t need a weekly blog anymore. You may get the results you want faster by changing the type of content you are using to attract your ideal customers. Content marketing and direct marketing are never going to die because they are based on human psychology. However, just like John Deere isn’t using the same content strategies in 2020 that it used in 1920, you shouldn’t be using the same content strategies today that you used in 2000, or even in 2016. The best content marketing is not dependent on Google or any other single platform to drive traffic and generate leads. The future of content marketing requires empathy, creativity, and adaptability. Instead of churning out another basic 500-word blog post today, spend time reimaging ways to show your ideal customers you can help them. That’s what successful marketers have always done and will continue to do.
https://medium.com/escape-motivation/the-future-of-content-marketing-is-already-here-546ab978708f
['Jason Mcbride']
2020-08-16 06:53:24.532000+00:00
['Marketing', 'Content Marketing', 'Email Marketing', 'Business', 'Writing']
Title Future Content Marketing Already HereContent Experienced marketer expect change continue use strategy tactic today worked 20 year ago get buried quietly whispered marketing circle past year Google suppressing organic reach difficult hit magically shrinking first page world’s largest search engine expert Markup finally conducted experiment demonstrated marketer already suspected — Google show lot content keep Google showing organic result practice may raise ethical antitrust concern deal reality ground It’s time business marketer think true state content marketing Cranking dozen hundred 500word blog post going help business doesn’t mean content marketing dead mean need look purpose content marketing understand use beyond keywords blog post Purpose Content Marketing Content marketing way build trust ideal prospect move sale funnel Content marketing invented internet existed hundred year Benjamin Franklin’s Poor Richard’s Almanac form content marketing show printing expertise Brands diverse John Deere Betty Crocker made fortune using content marketing long first microprocessor ever fired tend associate content marketing blog post one cheapest tool marketing toolbox past 20 year recently business begun embrace video podcasts content marketing tool Many marketer gotten complacent acted like Google would always around drive organic traffic website followed simple best practice day long gone doesn’t mean blog content marketing dead mean need find new way get content front ideal customer need creative disciplined showcase authority expertise Google Killing Traditional Business Blogging blog used best way build almost kind online business could write highquality post know search engine algorithm would eventually find content wanted build audience faster could write content Blogs still powerful way build business take much longer bear fruit also can’t put bunch short blog content need detailed ever competing blog — competing Google’s desire drive traffic within ecosystem best performing blog content skyscraper post cornerstone post 2000words 10000words long much expensive produce used wisely provide much higher return investment short blog post seem disposable also need legwork drive traffic content mean rethinking way sale funnel constructed Old Model New Way old content marketing model relied organic traffic wrote content people found search engine content invited people contact join mailing list prospect’s contact information could guide sale funnel organic traffic slow small enough time six month three year still rely primarily organic traffic power business entrepreneur marketer aren’t patient new way requires either invest social medium advertising drive traffic content expand channel use increase organic reach often mean branching blog post expanding different type medium Content marketing way show audience provides entrance sale funnel content generating like view share wrong Effective content marketing collect contact information generates email list signups Email New Blog Email always important part digital marketing strategy someone’s email key heart reach directly Direct marketing best way convert marketing dollar revenue used created massive amount content generate email list signups need create fewer better quality type content generate email signups Instead pushing blog post social medium blogosphere savvy business save best material email list Services like Substack betting massive amount money email newsletter replace blog primary form longterm content marketing much costeffective invest money highvalue content lead magnet build email list ideal customer write million blog post someone list send content used put blog email email nurture relationship audience way blog post used email much better sense effective something also drill core need audience Best Google isn’t scraping email content using keep people ecosystem Email give direct line people likely buy Content Curation Another critical difference modern content marketing role curation play truth none customer lack access information don’t need tell something ask Siri Alexa audience need way filter information every business still need create amazing content also need focus curating content customer Curation mean put best web together simple bundle people consume want include best work curation people come trust also learn enjoy unique brand voice love music chance enjoy checking playlist favorite artist make Spotify playlist form curation type content marketing Curation scare business afraid sending customer away don’t trust customer come back March 2020 Taylor Swift created Spotify playlist Women’s History Month highlighted bunch female artist Swift worried fan would discover artist never listen music that’s idiotic playlist good Swift’s career nice signal boost talented artist Curation show people confident enough brand voice business value highlight great work business Reimagining Sales Funnel future content marketing require create curate content many different channel may want use Apple podcasts TikTok YouTube matter create content need sale funnel need strategy behind content marketing used wanted drive everyone website blog still need website want drive traffic specific lead magnet landing page join mailing list lead magnet could bribe like free PDF could skyscraper blog post anyone access may find curating content help build email list faster creating original content However need get people email list need strategy nurture lead becoming paying customer think sound almost exactly like old way building funnel right difference using content get people join email list don’t need weekly blog anymore may get result want faster changing type content using attract ideal customer Content marketing direct marketing never going die based human psychology However like John Deere isn’t using content strategy 2020 used 1920 shouldn’t using content strategy today used 2000 even 2016 best content marketing dependent Google single platform drive traffic generate lead future content marketing requires empathy creativity adaptability Instead churning another basic 500word blog post today spend time reimaging way show ideal customer help That’s successful marketer always done continue doTags Marketing Content Marketing Email Marketing Business Writing
2,837
Objectron: Real-Time 3D Object Detection with Smartphone
DEEP LEARNING Objectron is a new SOTA dataset, recently presented by Google AI, which intended to improve 3D object recognition in videos. The dataset contains 15 thousand short video clips, each containing annotation of 3D boundaries of objects. The dataset contains both real clips and synthetic ones, that is, generated based on real ones. What is the problem The dataset is designed to facilitate the process of training models for 3D objects on 2D image and video data. While 2D prediction only provides 2D bounding boxes, by extending prediction to 3D, one can capture an object’s size, position, and orientation in the world, leading to a variety of applications in robotics, self-driving vehicles, image retrieval, and augmented reality. To do this, the researchers have collected a dataset that contains information about the structure of 3D objects and improves the accuracy of object detectors.
https://medium.com/deep-learning-digest/objectron-real-time-3d-object-detection-e5a689cc12f6
['Mikhail Raevskiy']
2020-11-25 10:57:46.995000+00:00
['Deep Learning', 'Data Science', 'Machine Learning', 'Artificial Intelligence', 'Computer Vision']
Title Objectron RealTime 3D Object Detection SmartphoneContent DEEP LEARNING Objectron new SOTA dataset recently presented Google AI intended improve 3D object recognition video dataset contains 15 thousand short video clip containing annotation 3D boundary object dataset contains real clip synthetic one generated based real one problem dataset designed facilitate process training model 3D object 2D image video data 2D prediction provides 2D bounding box extending prediction 3D one capture object’s size position orientation world leading variety application robotics selfdriving vehicle image retrieval augmented reality researcher collected dataset contains information structure 3D object improves accuracy object detectorsTags Deep Learning Data Science Machine Learning Artificial Intelligence Computer Vision
2,838
Latest Computer Vision Trends from CVPR 2019
Doing cool things with data! The 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) was held this year from June 16- June 20. CVPR is one of the world’s top three academic conferences in the field of computer vision (along with ICCV and ECCV). A total of 1300 papers were accepted this year from a record-high 5165 submissions (25.2 percent acceptance rate). CVPR brings in top minds in the field of computer vision and every year there are many papers that are very impressive. I have taken the accepted papers from CVPR and done analysis on them to understand the main areas of research and common keywords in Paper Titles. This can give an indication of where the research is moving. The underlying data and code is available on my Github. Feel free to pull this and add your own spin to it. CVPR assigns a primary subject area to each paper. The breakdown of accepted papers by subject area is below: Not surprisingly, most of the research is focused on Deep Learning (isn’t everything deep learning now!), Detection and Categorization and Face/Gesture/Pose. This breakdown is quite generic and doesn’t really give good insights. So next I extracted all the words from the accepted paper and used a counter to count their frequency. The top 25 most common keywords were below: Now this in more interesting. Most popular areas of research were detection, segmentation, 3D, and adversarial training. It also shows the growing research in unsupervised learning methods. Finally I also plotted the Word Cloud. You can use my Github to pull top papers by topic as shown below Papers with research on “face” I run a Machine Learning Consultancy. Check out our website here. I love to work on computer vision projects. Feel free to contact through the website or email at [email protected] if you have an idea that we can collaborate on. Next in the blog I chose 5 interesting papers from the key areas of research. Please note that I picked select papers that appealed the most to me. The human visual system has a remarkable ability to make sense of our 3D world from its 2D projection. Even in complex environments with multiple moving objects, people are able to maintain a feasible interpretation of the objects’ geometry and depth ordering. A lot of work has been done in depth estimation using camera images in the last few years but robust reconstruction remains difficult in many cases. A particularly challenging case occurs when both the camera and the objects in the scene are freely moving. This confuses traditional 3D reconstruction algorithms that are based on triangulation. To learn more about depth images and estimating depth of a scene please check out this blog. This paper solves this by building a deep learning model on a scene where both the camera and subject are freely moving. See gif below: Depth estimation on moving people To create such a model we need video sequences of natural scenes captured by moving camera along with accurate depth map for each image. Creating such a data set would be a challenge. To overcome this, the paper very innovatively uses an existing data set — YouTube videos in which people imitate mannequins by freezing in a wide variety of natural poses, while a hand-held camera tours the scene. Because the scene is stationary and only the camera is moving, accurate depth maps can be built using triangulation techniques. This paper is a very interesting read. It solves a complex problem and is very creative in creating a data set for it. The performance of the trained model on internet video clips with moving cameras and people is much better than any other previous research. See below: Model comparison through the paper You can read the full paper here. 2. BubbleNets: Learning to Select the Guidance Frame in Video Object Segmentation by Deep Sorting Frames I saw several papers on video object segmentation (VOS). This is the task of segmenting an object in a video provided a single annotation in first frame. This finds applications in video understanding and has seen a lot of research in the last one year. The location and appearance of objects in video can change significantly from frame-to-frame, and, the paper finds that using different frames for annotation changes performance dramatically, as shown below. Bubblenets video demo BubbleNets iteratively compares and swaps adjacent video frames until the frame with the greatest predicted performance is ranked highest, at which point, it is selected for the user to annotate and use for video object segmentation. BubbleNet first frame selection A video description of the model is shared on youtube and source code is open sourced on Github. BubbleNets model is used to predict relative performance difference between two frames. Relative performance is measured by a combination of region similarity and contour accuracy. It takes as input 2 frames to compare and 3 reference frames. It then passes these through ResNet50 and fully connected layers to output a single number f denoting the comparison of the 2 frames. To perform bubble sort, we start with the first 2 frames and compare them. If BubbleNet predicts that frame 1 has better performance than frame 2 then order of frames is swapped and the next frame is compared with the best frame so far. At the end of processing through the entire video sequence the best frame remains. The figure below shows BubbleNets architecture and process for bubble sort. Overall the authors show that changing the way the annotation frame is selected with no change to underlying segmentation algorithm results in an 11% increase in perform on the DAVIS benchmark data set. Bubblenets architecture 3. 3D Hand Shape and Pose Estimation from a Single RGB Image 3D hand shape and pose estimation has been a very active area of research lately. This has applications in VR and Robotics. This paper uses a monocular RGB image to create a 3D hand pose and 3D mesh around the hand as shown below. 3D hand mesh from single image The paper uses Graph CNNs to reconstruct a full 3D mesh of the hand. Here is a good introduction to the topic of Graph CNNs. To train the network, the authors created a large-scale synthetic dataset containing both ground truth 3D meshes and 3D poses. Manually annotating the ground truth 3D hand meshes on real-world RGB images is extremely laborious and time-consuming. However, models trained on the synthetic dataset usually produce unsatisfactory estimation results on real-world datasets due to the domain gap between them. To address this issue, the authors propose a novel weakly supervised method by leveraging depth map as a weak supervision for 3D mesh generation, since depth map can be easily captured by an RGB-D camera when collecting real world training data. The paper has rich details on data set, training process etc. Please read through it if this is an area that interests you. One interesting learning for me was the architecture of the Graph CNN used for mesh generation. The input to this network is a latent vector from the RGB image. It goes through 2 fully connected layers to output 80x64 features in a coarse graph. It then goes through layers of upsampling and Graph CNNs to output richer details resulting in a final output of 1280 vertices. 3D hand mesh model architecture 4. Reasoning-RCNN: Unifying Adaptive Global Reasoning into Large-scale Object Detection Reasoning RCNN output Object detection has gained a lot of popularity with many common computer vision applications. Faster RCNN is a popular object detection model that is frequently used. To learn more about object detection and Faster RCNN checkout this blog. However object detection is most successful when number of detection classes is small — less than 100. This paper addresses the large-scale object detection problem with thousands of categories, which poses severe challenges due to long-tail data distributions, heavy occlusions, and class ambiguities. Reasoning-RCNN does this by constructing a knowledge graph that encodes common human sense knowledge. What is Knowledge Graph? Knowledge graph encodes information between objects such as spatial relationship (on, near), subject-verb-object (ex. Drive, run) relationship as well as attribute similarities like color, size, material. As shown below categories with visual relationship to each other are closer to each other. Knowledge Graph In terms of architecture it stacks a Reasoning framework on top of a standard object detector like Faster RCNN. The weights of the previous classifier are collected to generate a global semantic pool over all categories, which is fed into an adaptive global reasoning module. The enhanced category contexts (i.e., output of the reasoning module) are mapped back to region proposals by a soft-mapping mechanism. Finally, each region’s enhanced features are used to improve the performance of both classification and localization in an end-to-end manner. The diagram below shows the model architecture. Please refer to the paper to get more detailed understanding of their architecture. The model is trained and evaluated on 3 main datasets — Visual Gnome (3000 categories), ADE (445 categories) and COCO (80 categories). The model is able to get 16% improvement on Visual Gnome, 37% on ADE and a 15% improvement in COCO on mAP scores. Training code will be open sourced at this link. Not available yet. 5. Deep Learning for Zero Shot Face Anti-Spoofing A lot of progress has been made on Facial Detection in the last few years and now facial detection and recognition systems are commonly used in many applications. In Fact it is possible to build a system that detects faces, recognizes them and understands their emotions in 8 lines of code. See blog here. However there is also continuous risk of face detection being spoofed to gain illegal access. Face anti-spoofing is designed to prevent face recognition systems from recognizing fake faces as the genuine users. While advanced face anti-spoofing methods are developed, new types of spoof attacks are also being created and becoming a threat to all existing systems. This paper introduces the concept of detecting unknown spoof attacks as s Zero-Shot Face Anti-spoofing (ZSFA). Previous ZSFA works only study 1- 2 types of spoof attacks, such as print/replay, which limits the insight of this problem. This work investigates the ZSFA problem in a wide range of 13 types of spoof attacks, including print, replay, 3D mask, and so on. The image below shows different types of spoof attacks. Face spoofing can include various forms like print (print a face photo), replaying a video, 3D mask, face photo with cutout for eyes, makeup, transparent mask etc. The paper proposes to use a deep tree network to learn semantic embeddings from spoof pictures in unsupervised fashion. Embeddings here could model things like human gaze. It creates a data set of spoof images to learn these embeddings. During the testing, the unknown attacks are projected to the embedding to find the closest attributes for spoof detection. Read the paper for more detail about the model architecture for deep tree network and process for training it. The paper is able to create embeddings that separate out live face (True Face) with various types of spoofs. See t-SNE plot below This paper was awesome. A promising research into tackling a practical problem. Conclusion It is fascinating to see all the latest research in Computer Vision. The 5 papers shared here are just the tip of the iceberg. I hope you will use my Github to sort through the papers and select the ones that interest you. I am extremely passionate about computer vision and deep learning in general. I have my own deep learning consultancy and love to work on interesting problems. I have helped many startups deploy innovative AI based solutions. Check us out at — http://deeplearninganalytics.org/. You can also see my other writings at: https://medium.com/@priya.dwivedi If you have a project that we can collaborate on, then please contact me through my website or at [email protected] References:
https://towardsdatascience.com/latest-computer-vision-trends-from-cvpr-2019-c07806dd570b
['Priya Dwivedi']
2019-08-09 17:45:03.421000+00:00
['Machine Learning', 'Artificial Intelligence', 'Trends', 'Computer Vision', 'Data Science']
Title Latest Computer Vision Trends CVPR 2019Content cool thing data 2019 IEEE Conference Computer Vision Pattern Recognition CVPR held year June 16 June 20 CVPR one world’s top three academic conference field computer vision along ICCV ECCV total 1300 paper accepted year recordhigh 5165 submission 252 percent acceptance rate CVPR brings top mind field computer vision every year many paper impressive taken accepted paper CVPR done analysis understand main area research common keywords Paper Titles give indication research moving underlying data code available Github Feel free pull add spin CVPR assigns primary subject area paper breakdown accepted paper subject area surprisingly research focused Deep Learning isn’t everything deep learning Detection Categorization FaceGesturePose breakdown quite generic doesn’t really give good insight next extracted word accepted paper used counter count frequency top 25 common keywords interesting popular area research detection segmentation 3D adversarial training also show growing research unsupervised learning method Finally also plotted Word Cloud use Github pull top paper topic shown Papers research “face” run Machine Learning Consultancy Check website love work computer vision project Feel free contact website email infodeeplearninganalyticsorg idea collaborate Next blog chose 5 interesting paper key area research Please note picked select paper appealed human visual system remarkable ability make sense 3D world 2D projection Even complex environment multiple moving object people able maintain feasible interpretation objects’ geometry depth ordering lot work done depth estimation using camera image last year robust reconstruction remains difficult many case particularly challenging case occurs camera object scene freely moving confuses traditional 3D reconstruction algorithm based triangulation learn depth image estimating depth scene please check blog paper solves building deep learning model scene camera subject freely moving See gif Depth estimation moving people create model need video sequence natural scene captured moving camera along accurate depth map image Creating data set would challenge overcome paper innovatively us existing data set — YouTube video people imitate mannequin freezing wide variety natural pose handheld camera tour scene scene stationary camera moving accurate depth map built using triangulation technique paper interesting read solves complex problem creative creating data set performance trained model internet video clip moving camera people much better previous research See Model comparison paper read full paper 2 BubbleNets Learning Select Guidance Frame Video Object Segmentation Deep Sorting Frames saw several paper video object segmentation VOS task segmenting object video provided single annotation first frame find application video understanding seen lot research last one year location appearance object video change significantly frametoframe paper find using different frame annotation change performance dramatically shown Bubblenets video demo BubbleNets iteratively compare swap adjacent video frame frame greatest predicted performance ranked highest point selected user annotate use video object segmentation BubbleNet first frame selection video description model shared youtube source code open sourced Github BubbleNets model used predict relative performance difference two frame Relative performance measured combination region similarity contour accuracy take input 2 frame compare 3 reference frame pass ResNet50 fully connected layer output single number f denoting comparison 2 frame perform bubble sort start first 2 frame compare BubbleNet predicts frame 1 better performance frame 2 order frame swapped next frame compared best frame far end processing entire video sequence best frame remains figure show BubbleNets architecture process bubble sort Overall author show changing way annotation frame selected change underlying segmentation algorithm result 11 increase perform DAVIS benchmark data set Bubblenets architecture 3 3D Hand Shape Pose Estimation Single RGB Image 3D hand shape pose estimation active area research lately application VR Robotics paper us monocular RGB image create 3D hand pose 3D mesh around hand shown 3D hand mesh single image paper us Graph CNNs reconstruct full 3D mesh hand good introduction topic Graph CNNs train network author created largescale synthetic dataset containing ground truth 3D mesh 3D pose Manually annotating ground truth 3D hand mesh realworld RGB image extremely laborious timeconsuming However model trained synthetic dataset usually produce unsatisfactory estimation result realworld datasets due domain gap address issue author propose novel weakly supervised method leveraging depth map weak supervision 3D mesh generation since depth map easily captured RGBD camera collecting real world training data paper rich detail data set training process etc Please read area interest One interesting learning architecture Graph CNN used mesh generation input network latent vector RGB image go 2 fully connected layer output 80x64 feature coarse graph go layer upsampling Graph CNNs output richer detail resulting final output 1280 vertex 3D hand mesh model architecture 4 ReasoningRCNN Unifying Adaptive Global Reasoning Largescale Object Detection Reasoning RCNN output Object detection gained lot popularity many common computer vision application Faster RCNN popular object detection model frequently used learn object detection Faster RCNN checkout blog However object detection successful number detection class small — le 100 paper address largescale object detection problem thousand category pose severe challenge due longtail data distribution heavy occlusion class ambiguity ReasoningRCNN constructing knowledge graph encodes common human sense knowledge Knowledge Graph Knowledge graph encodes information object spatial relationship near subjectverbobject ex Drive run relationship well attribute similarity like color size material shown category visual relationship closer Knowledge Graph term architecture stack Reasoning framework top standard object detector like Faster RCNN weight previous classifier collected generate global semantic pool category fed adaptive global reasoning module enhanced category context ie output reasoning module mapped back region proposal softmapping mechanism Finally region’s enhanced feature used improve performance classification localization endtoend manner diagram show model architecture Please refer paper get detailed understanding architecture model trained evaluated 3 main datasets — Visual Gnome 3000 category ADE 445 category COCO 80 category model able get 16 improvement Visual Gnome 37 ADE 15 improvement COCO mAP score Training code open sourced link available yet 5 Deep Learning Zero Shot Face AntiSpoofing lot progress made Facial Detection last year facial detection recognition system commonly used many application Fact possible build system detects face recognizes understands emotion 8 line code See blog However also continuous risk face detection spoofed gain illegal access Face antispoofing designed prevent face recognition system recognizing fake face genuine user advanced face antispoofing method developed new type spoof attack also created becoming threat existing system paper introduces concept detecting unknown spoof attack ZeroShot Face Antispoofing ZSFA Previous ZSFA work study 1 2 type spoof attack printreplay limit insight problem work investigates ZSFA problem wide range 13 type spoof attack including print replay 3D mask image show different type spoof attack Face spoofing include various form like print print face photo replaying video 3D mask face photo cutout eye makeup transparent mask etc paper proposes use deep tree network learn semantic embeddings spoof picture unsupervised fashion Embeddings could model thing like human gaze creates data set spoof image learn embeddings testing unknown attack projected embedding find closest attribute spoof detection Read paper detail model architecture deep tree network process training paper able create embeddings separate live face True Face various type spoof See tSNE plot paper awesome promising research tackling practical problem Conclusion fascinating see latest research Computer Vision 5 paper shared tip iceberg hope use Github sort paper select one interest extremely passionate computer vision deep learning general deep learning consultancy love work interesting problem helped many startup deploy innovative AI based solution Check u — httpdeeplearninganalyticsorg also see writing httpsmediumcompriyadwivedi project collaborate please contact website infodeeplearninganalyticsorg ReferencesTags Machine Learning Artificial Intelligence Trends Computer Vision Data Science
2,839
The Brain and Body Prioritize Adaptation, Not Balance
The Brain and Body Prioritize Adaptation, Not Balance ‘Allostasis’ is reshaping science’s understanding of disease and disorder In ancient Greece, the top medical minds believed that the function of the human brain and body was dependent on the proper ratio of four internal fluids which were known as the “humors.” Too much or too little of any one of the humors was thought to cause pain, dysfunction, and behavioral or emotional intemperance. This cocktail mixologist’s notion of human physiology continued to dominate medical theory until the 19th century, when doctors finally recognized that “humorism” was mostly bunk. But they couldn’t quite shake off the belief that a sick body is somehow a body out of balance. The next big idea that emerged — one that became “the dominant explanatory framework for physiological regulation” from the late 1800s all the way up to the present — is the concept of “homeostasis.” In a nutshell, homeostasis holds that the human body has certain baseline states or “set points” that it strives to maintain. Constancy is the goal, and disease and disorder are the result of deviations from these set points or the body’s unsuccessful attempts to get back to them. Like Leonardo da Vinci’s Vitruvian Man, homeostasis holds that a healthy body and mind are in all ways proportional. Type-1 diabetes is often cited as an example of homeostatic principles at work: An insulin insufficiency causes dangerous disruptions in the blood’s levels of glucose; introducing insulin via injection helps restore balance. But some experts have challenged the idea that the ultimate goal of the body’s inner workings is to maintain some predetermined set point or state of balance. “Homeostasis is all about staying the same, but most physiological systems are about change and adapting to it,” says Jay Schulkin, PhD, a behavioral neuroscientist at the University of Washington. Schulkin’s work has contributed to a newer concept of human health and functioning known as “allostasis,” which means “stability through change.” It argues that, rather than simply striving to preserve a steady state of internal balance, the human body and brain are designed to anticipate and make preparatory adjustments based on experience. For example, levels of digestive enzymes and energy-transporting hormones rise before a person eats a meal, and the specifics of these shifts depend in part on that person’s typical diet, eating schedule, and other past behaviors. If that person normally eats an unhealthy, sugar-rich diet, these pre-meal enzyme and hormone shifts — including ones that can contribute to poor energy metabolism and type-2 diabetes — will happen even if the person ends up dining on healthier fare. What the homeostasis model may regard as disorder or dysfunction, allostasis views as a logical response to external events or stimuli — even if that response has some unwelcome drawbacks. “Allostasis takes into account the environment and social contexts and how we adapt to them,” Schulkin says. For too long, he says that homeostatic theory has dominated medical science and its approach to research and treatment. Allostasis, by shifting the medical community’s notions of how the brain and body work, could inform more productive scholarship and better maybe especially when it comes to mental health conditions like anxiety and depression. “We need a concept like allostasis that takes into account how we manage to adjust, or don’t manage to adjust, to things in our life,” he says. Allostasis and mental health Anxiety disorders, depression, and other mental health challenges are often described as the result of chemical “imbalances” in the brain. This homeostasis-influenced view has been around for decades, and it serves as the foundation for contemporary pharmacotherapy. By correcting these supposed imbalances — for example, by increasing levels of the neurotransmitter serotonin — these drugs are intended to improve mood, cognition, or behavior. But some proponents of allostasis hold a different view. While mental health disorders are frequently associated with elevated or reduced levels of certain neurotransmitters, they say that there’s little evidence that these disorders are caused by neurotransmitter imbalances. “Drugs amount to a blind tweaking of circuits that are not even identified, let alone understood,” says Peter Sterling, PhD, a professor of neuroscience at the University of Pennsylvania and author of What Is Health? Allostasis and the Evolution of Human Design. While this kind of tweaking may in some cases help relieve a person’s symptoms, it doesn’t address the underlying causes of those symptoms, Sterling says. Adjusting the brain’s levels of neurochemicals can also interfere with other aspects of mood or cognition, and in some cases can induce bouts of paranoia, anger, or other negative side effects. “We need a concept like allostasis that takes into account how we manage to adjust, or don’t manage to adjust, to things in our life.” Sterling, along with the late UPenn biologist Joseph Eyer, coined the phrase “allostasis” and has been developing and refining its model for more than 30 years. He says that the big idea — the thing that really differentiates allostasis from homeostasis — is the recognition that the brain and body are constantly trying to predict and adapt through adjustments to a person’s physiology and behavior. “The most efficient way to run the body is for the brain to figure out ahead of time what will be needed,” he says. Allostasis concepts help explain why a person whose life is filled with stress may experience worry and its physical manifestations — such as elevated blood pressure, rapid heart rate, and GI discomfort — even during those times when no threat or source of stress is present. Rather than returning to a set point — which is the response that the homeostasis model predicts — the brain has adapted. In a 2014 paper in JAMA Psychiatry, Sterling explains how this allostatic understanding of the brain and body may inform mental health treatment. If practiced in the right contexts, mindfulness meditation, cognitive behavioral therapy, and other non-drug programs designed to encourage constructive thoughts, attitudes, and behaviors could engage the brain’s adaptation mechanisms in therapeutic ways. By changing the brain’s experience of life, people can remodel their own neural circuitry in ways that reduce the burden of mental health challenges, he says. A broad conceptual shake-up Not everyone buys into the idea of allostasis. Some experts have argued that it’s just a reorganization and rebranding of concepts already folded into homeostatic theory. Others see all the homeostasis-allostasis bickering as a semantical sideshow that doesn’t have much bearing on health and medicine. But plenty of experts agree that some new ways of thinking and talking about health are needed. Especially when it comes to mental health, a number of doctors have argued that the terms and theoretical frameworks we apply to some of these conditions need refurbishment. Peter Kinderman, PhD, a professor of clinical psychology at the University of Liverpool in the U.K., says that the current language around mental health pathologizes what are in a lot of instances predictable and logical responses to distressing life events, and that it might be better to refer to certain mental health conditions as experiences, rather than disorders. For example, depression and anxiety symptoms have increased in the U.S. during the coronavirus pandemic. SARS-CoV-2 poses a very real and deadly threat to oneself and one’s loved ones, and it has also contributed to economic, political, and social turmoil. Reacting to all this with feelings of sadness or anxiousness is not “a dysfunction in the biology of the brain,” Kinderman says. “There’s nothing pathological about that response.” Using more appropriate language to describe these experiences could in many cases help people move on from — rather than just manage — what they’re dealing with, he adds. These sorts of conceptual health debates aren’t going away anytime soon, and they’re of a piece with broader discussions about contemporary life and the way it may be driving historically high rates of metabolic disease and existential torment. “Homeostasis doesn’t explain why half of the population is obese or diabetic, or why we have such high rates of so-called ‘deaths of despair,’” Sterling says. “I think we’re overdriving the body and demanding too much of these mechanisms that aren’t really broken, they’re just mistreated.” Embracing an allostasis model of human functioning, he says, may help us better address these growing problems.
https://elemental.medium.com/the-brain-and-body-prioritize-adaptation-not-balance-c64aa6bb36be
['Markham Heid']
2020-09-24 05:32:39.106000+00:00
['Disease', 'Brain', 'The Nuance', 'Body', 'Science']
Title Brain Body Prioritize Adaptation BalanceContent Brain Body Prioritize Adaptation Balance ‘Allostasis’ reshaping science’s understanding disease disorder ancient Greece top medical mind believed function human brain body dependent proper ratio four internal fluid known “humors” much little one humor thought cause pain dysfunction behavioral emotional intemperance cocktail mixologist’s notion human physiology continued dominate medical theory 19th century doctor finally recognized “humorism” mostly bunk couldn’t quite shake belief sick body somehow body balance next big idea emerged — one became “the dominant explanatory framework physiological regulation” late 1800s way present — concept “homeostasis” nutshell homeostasis hold human body certain baseline state “set points” strives maintain Constancy goal disease disorder result deviation set point body’s unsuccessful attempt get back Like Leonardo da Vinci’s Vitruvian Man homeostasis hold healthy body mind way proportional Type1 diabetes often cited example homeostatic principle work insulin insufficiency cause dangerous disruption blood’s level glucose introducing insulin via injection help restore balance expert challenged idea ultimate goal body’s inner working maintain predetermined set point state balance “Homeostasis staying physiological system change adapting it” say Jay Schulkin PhD behavioral neuroscientist University Washington Schulkin’s work contributed newer concept human health functioning known “allostasis” mean “stability change” argues rather simply striving preserve steady state internal balance human body brain designed anticipate make preparatory adjustment based experience example level digestive enzyme energytransporting hormone rise person eats meal specific shift depend part person’s typical diet eating schedule past behavior person normally eats unhealthy sugarrich diet premeal enzyme hormone shift — including one contribute poor energy metabolism type2 diabetes — happen even person end dining healthier fare homeostasis model may regard disorder dysfunction allostasis view logical response external event stimulus — even response unwelcome drawback “Allostasis take account environment social context adapt them” Schulkin say long say homeostatic theory dominated medical science approach research treatment Allostasis shifting medical community’s notion brain body work could inform productive scholarship better maybe especially come mental health condition like anxiety depression “We need concept like allostasis take account manage adjust don’t manage adjust thing life” say Allostasis mental health Anxiety disorder depression mental health challenge often described result chemical “imbalances” brain homeostasisinfluenced view around decade serf foundation contemporary pharmacotherapy correcting supposed imbalance — example increasing level neurotransmitter serotonin — drug intended improve mood cognition behavior proponent allostasis hold different view mental health disorder frequently associated elevated reduced level certain neurotransmitter say there’s little evidence disorder caused neurotransmitter imbalance “Drugs amount blind tweaking circuit even identified let alone understood” say Peter Sterling PhD professor neuroscience University Pennsylvania author Health Allostasis Evolution Human Design kind tweaking may case help relieve person’s symptom doesn’t address underlying cause symptom Sterling say Adjusting brain’s level neurochemical also interfere aspect mood cognition case induce bout paranoia anger negative side effect “We need concept like allostasis take account manage adjust don’t manage adjust thing life” Sterling along late UPenn biologist Joseph Eyer coined phrase “allostasis” developing refining model 30 year say big idea — thing really differentiates allostasis homeostasis — recognition brain body constantly trying predict adapt adjustment person’s physiology behavior “The efficient way run body brain figure ahead time needed” say Allostasis concept help explain person whose life filled stress may experience worry physical manifestation — elevated blood pressure rapid heart rate GI discomfort — even time threat source stress present Rather returning set point — response homeostasis model predicts — brain adapted 2014 paper JAMA Psychiatry Sterling explains allostatic understanding brain body may inform mental health treatment practiced right context mindfulness meditation cognitive behavioral therapy nondrug program designed encourage constructive thought attitude behavior could engage brain’s adaptation mechanism therapeutic way changing brain’s experience life people remodel neural circuitry way reduce burden mental health challenge say broad conceptual shakeup everyone buy idea allostasis expert argued it’s reorganization rebranding concept already folded homeostatic theory Others see homeostasisallostasis bickering semantical sideshow doesn’t much bearing health medicine plenty expert agree new way thinking talking health needed Especially come mental health number doctor argued term theoretical framework apply condition need refurbishment Peter Kinderman PhD professor clinical psychology University Liverpool UK say current language around mental health pathologizes lot instance predictable logical response distressing life event might better refer certain mental health condition experience rather disorder example depression anxiety symptom increased US coronavirus pandemic SARSCoV2 pose real deadly threat oneself one’s loved one also contributed economic political social turmoil Reacting feeling sadness anxiousness “a dysfunction biology brain” Kinderman say “There’s nothing pathological response” Using appropriate language describe experience could many case help people move — rather manage — they’re dealing add sort conceptual health debate aren’t going away anytime soon they’re piece broader discussion contemporary life way may driving historically high rate metabolic disease existential torment “Homeostasis doesn’t explain half population obese diabetic high rate socalled ‘deaths despair’” Sterling say “I think we’re overdriving body demanding much mechanism aren’t really broken they’re mistreated” Embracing allostasis model human functioning say may help u better address growing problemsTags Disease Brain Nuance Body Science
2,840
We Design Reality With Words
Before a pandemic chewed through our livelihoods and collective mental health, summer used to be silly season. News slowed down to a crawl, trivia and oddities took their place, and life read a little easier for a while. But now? It’s been surreal season for so long constant overwhelm is the new normal. If words matter to you and you’re concerned about the political climate, you may have come to regard writing with suspicion and doubt. Is there no other way to earn a living with words than by oozing fear, greed, and anger in print or riding the coat tails of celebrities who behaved badly? Recycling the worst of the zeitgeist ad nauseam is no way to improve it, defunding dumb may be more effective. If there’s no financial incentive to produce garbage then the trash will eventually take itself out. Meanwhile, the internet is a dump, digital detritus abounds, and everyone is scavenging for meaning. We don’t have to be seagulls.
https://asingularstory.medium.com/we-design-reality-with-words-761e1e89bf77
['A Singular Story']
2020-08-28 09:24:20.258000+00:00
['Media', 'Social Media', 'Writing', 'Creativity', 'Philosophy']
Title Design Reality WordsContent pandemic chewed livelihood collective mental health summer used silly season News slowed crawl trivia oddity took place life read little easier It’s surreal season long constant overwhelm new normal word matter you’re concerned political climate may come regard writing suspicion doubt way earn living word oozing fear greed anger print riding coat tail celebrity behaved badly Recycling worst zeitgeist ad nauseam way improve defunding dumb may effective there’s financial incentive produce garbage trash eventually take Meanwhile internet dump digital detritus abounds everyone scavenging meaning don’t seagullsTags Media Social Media Writing Creativity Philosophy
2,841
How to Finetune mT5 to Create a Question Generator 🤔(for 100+ Languages)
Its been a month since Google released the massive multilingual model mT5. I was really excited to perform some crazy experiments using mT5. The special quirk about mT5 is its ability to perform any seq-2-seq task in more than 100 languages. I experimented with mT5 on mainly two tasks i.e. for language translations and secondly Question generation. I found the second use case much more interesting. So I created this blog as a tutorial on how to use mT5 for finetuning mT5 to build a question generator.🤩 What is exactly a question generator! Question generators generate questions. They can be used by teachers and students for generating a variety of questions from a giving text. They can be particularly helpful for comprehension type questions. Now that we know what is questions generator, let's build one. I will build question generator for Hindi language and you can replicate it on any 101 languages of your choice on which mT5 is trained on. (provided you have the dataset) You can check out supported language here. Task Let's define the task. For generating questions we need to input a text context to the mT5 model and expect a question in return. Here is an example in English: Context: Donald John Trump (born June 14, 1946) is the 45th and current president of the United States. Before entering politics, he was a businessman and television personality. Output: Who is Donald Trump? Since we are mainly focusing on the Hindi language we will have Hindi Context as input and Hindi Question as Output. Dataset Collection One another major issue in languages other than English is lack of quality Dataset for training and fine-tuning transformers models. Luckily for us, I found two similar datasets which just fulfil our dataset requirement in the Hindi language. First is Deepmind Xquad Dataset (Cross-lingual Question Answering Dataset)and Facebook MLQA (MultiLingual Question Answering). XQuAD (Cross-lingual Question Answering Dataset) is a benchmark dataset for evaluating cross-lingual question answering performance. The dataset consists of a subset of 240 paragraphs and 1190 question-answer pairs from the development set of SQuAD v1.1 (Rajpurkar et al., 2016) together with their professional translations into ten languages: Spanish, German, Greek, Russian, Turkish, Arabic, Vietnamese, Thai, Chinese, and Hindi. MLQA (MultiLingual Question Answering) is a benchmark dataset for evaluating cross-lingual question answering performance. MLQA consists of over 5K extractive QA instances (12K in English) in SQuAD format in seven languages — English, Arabic, German, Spanish, Hindi, Vietnamese and Simplified Chinese. MLQA is highly parallel, with QA instances parallel between 4 different languages on average. I collected 1190 context-question pairs from Deep Mind Xquad dataset. From Facebook MLQA I concatenated test and dev dataset which consist a total of 5425 context-question pairs. Since both datasets were originally present in JSON format for the ease of using I converted them CSV format. I divided the overall collected dataset into two sets: A training set with 6500 context-question pairs and testing set with 150 context-question pairs. The reason for keeping such low count testing set is unlike in classification problems, text generation problem doesn’t benefit much from a large testing dataset (since we do not have metric to evaluate generated questions or text generation in general). Above is the script I created to perform these operations. (Colab notebooks are less convenient than Kaggle as Kaggle provide P100 GPU while Colab has Tesla T4 thus much lesser time while finetuning on Kaggle). Finetuning mT5 using pytorch-lightning We’ll be using PyTorch-lightning library for finetuning. Most of the code below is adapted from here. The trainer is generic and can be used for any text-2-text task. You’ll just need to change the dataset. Rest of the code will stay unchanged for all the tasks. This is the most interesting and powerful thing about the text-2-text format. You can fine-tune the model on a variety of NLP tasks by just formulating the problem in the text-2-text setting. No need to change hyperparameters, learning rate, optimizer or loss function. I trained the ‘google/mt5-base’ for 10 epochs with a batch size of 8. Here is the link to the fine-tuning script. If you want to finetune mT5 on any of your tasks you need to take care of two things. Create your own dataset in CSV format and change the dataset path in the fine-tuning Kaggle notebook. (dataset must have two files train.csv and valid.csv) Secondly, change the QuestionDataset class in the above Kaggle notebook according to your use case. The input format I used while finetuning is Input = "Hindi Context: %s" % (input_text) # input_text is the given input to the model Inference for Question Generation Inferencing the model is the easiest part as we have done most of the heavy lifting. Let's check out the results. from transformers import MT5ForConditionalGeneration, AutoTokenizer model = MT5ForConditionalGeneration.from_pretrained("../input/mt5-hindi-question-generator") tokenizer = AutoTokenizer.from_pretrained("google/mt5-base") Input text (Any paragraph in the Hindi language) article = '''Hindi context:पूरे विश्व भर में भारत एक प्रसिद्ध देश है। भौगोलिक रुप से, हमारा देश एशिया महाद्वीप के दक्षिण में स्थित है। भारत एक अत्यधिक जनसंख्या वाला देश है साथ ही प्राकृतिक रुप से सभी दिशाओं से सुरक्षित है। पूरे विश्व भर में अपनी महान संस्कृति और पारंपरिक मूल्यों के लिये ये एक प्रसिद्ध देश है। इसके पास हिमालय नाम का एक पर्वत है जो विश्व में सबसे ऊँचा है। ये तीन तरफ से तीन महासागरों से घिरा हुआ है जैसे दक्षिण में भारतीय महासागर, पूरब में बंगाल की खाड़ी और पश्चिम में अरेबिक सागर से। भारत एक लोकतांत्रिक देश है जो जनसंख्या के लिहाज से दूसरे स्थान पर है। भारत में मुख्य रूप से हिंदी भाषा बोली जाती है परंतु यहां लगभग 22 भाषाओं को राष्ट्रीय रुप से मान्यता दी गयी है। ''' For decoding, we can either use greedy decoding with single question generation or top_kp decoding with multiple questions generation. Here are the results obtained start = time.time() encoding = tokenizer.encode_plus(article, return_tensors="pt") input_ids, attention_masks = encoding["input_ids"].to(device), encoding["attention_mask"].to(device) print(article) output = greedy_decoding(input_ids,attention_masks) print ("Greedy decoding:: ",output) end = time.time() print (" Time elapsed ", end-start) print (" ") Output : Hindi context:पूरे विश्व भर में भारत एक प्रसिद्ध देश है। भौगोलिक रुप से, हमारा देश एशिया महाद्वीप के दक्षिण में स्थित है। भारत एक अत्यधिक जनसंख्या वाला देश है साथ ही प्राकृतिक रुप से सभी दिशाओं से सुरक्षित है। पूरे विश्व भर में अपनी महान संस्कृति और पारंपरिक मूल्यों के लिये ये एक प्रसिद्ध देश है। इसके पास हिमालय नाम का एक पर्वत है जो विश्व में सबसे ऊँचा है। ये तीन तरफ से तीन महासागरों से घिरा हुआ है जैसे दक्षिण में भारतीय महासागर, पूरब में बंगाल की खाड़ी और पश्चिम में अरेबिक सागर से। भारत एक लोकतांत्रिक देश है जो जनसंख्या के लिहाज से दूसरे स्थान पर है। भारत में मुख्य रूप से हिंदी भाषा बोली जाती है परंतु यहां लगभग 22 भाषाओं को राष्ट्रीय रुप से मान्यता दी गयी है। Greedy decoding:: भारत में कितनी भाषाएं बोली जाती हैं? Time elapsed 1.0903606414794922 So the question generated seems pretty legit😇😇. Here is the top_kp output for multiple questions Hindi context:पूरे विश्व भर में भारत एक प्रसिद्ध देश है। भौगोलिक रुप से, हमारा देश एशिया महाद्वीप के दक्षिण में स्थित है। भारत एक अत्यधिक जनसंख्या वाला देश है साथ ही प्राकृतिक रुप से सभी दिशाओं से सुरक्षित है। पूरे विश्व भर में अपनी महान संस्कृति और पारंपरिक मूल्यों के लिये ये एक प्रसिद्ध देश है। इसके पास हिमालय नाम का एक पर्वत है जो विश्व में सबसे ऊँचा है। ये तीन तरफ से तीन महासागरों से घिरा हुआ है जैसे दक्षिण में भारतीय महासागर, पूरब में बंगाल की खाड़ी और पश्चिम में अरेबिक सागर से। भारत एक लोकतांत्रिक देश है जो जनसंख्या के लिहाज से दूसरे स्थान पर है। भारत में मुख्य रूप से हिंदी भाषा बोली जाती है परंतु यहां लगभग 22 भाषाओं को राष्ट्रीय रुप से मान्यता दी गयी है। Topkp decoding:: ['भारत कहाँ स्थित है?', 'भारत के पास कितनी भाषाएँ हैं?', 'भारत की मुख्य भाषा क्या है?', 'भारत में मुख्य रूप से कौन सी भाषाएं बोली जाती हैं?', 'भारत में कितनी भाषाएँ बोली जाती हैं?', 'भारत की दूसरी लोकतांत्रिक सरकार क्या है?', 'भारत का हिस्सा किस महाद्वीप के दक्षिण में है?', 'भारत में कौन सी भाषा बोली जाती है?', 'हिंदी भाषा की कौन सी संस्कृति सबसे अधिक लोकप्रिय है?', 'भारत की जनसंख्या क्या है?'] Time elapsed 1.3107168674468994 So as you can see few questions are grammatically incorrect but if we check the overall quality its good for basic uses. If you want to experiment more with my Hindi question generator check out my notebook on Kaggle. So I conclude my blog on the question generator using mT5. You can now finetune mT5 on the various task in various languages. All the Kaggle notebooks and dataset used is set to public (anyone can use). I have given references for so many notebooks which might be confusing so if you have any question you may ask in comments. So are you ready to experiment with mT5?🤔🤔🤔 References: Original Suraj Patil Colab on Finetuning T5
https://medium.com/swlh/how-to-finetune-mt5-to-create-a-question-generator-for-100-languages-4a3878e63118
['Parth Chokhra']
2020-12-04 12:51:59.441000+00:00
['Machine Learning', 'Artificial Intelligence', 'Google', 'Technology', 'Programming']
Title Finetune mT5 Create Question Generator 🤔for 100 LanguagesContent month since Google released massive multilingual model mT5 really excited perform crazy experiment using mT5 special quirk mT5 ability perform seq2seq task 100 language experimented mT5 mainly two task ie language translation secondly Question generation found second use case much interesting created blog tutorial use mT5 finetuning mT5 build question generator🤩 exactly question generator Question generator generate question used teacher student generating variety question giving text particularly helpful comprehension type question know question generator let build one build question generator Hindi language replicate 101 language choice mT5 trained provided dataset check supported language Task Lets define task generating question need input text context mT5 model expect question return example English Context Donald John Trump born June 14 1946 45th current president United States entering politics businessman television personality Output Donald Trump Since mainly focusing Hindi language Hindi Context input Hindi Question Output Dataset Collection One another major issue language English lack quality Dataset training finetuning transformer model Luckily u found two similar datasets fulfil dataset requirement Hindi language First Deepmind Xquad Dataset Crosslingual Question Answering Datasetand Facebook MLQA MultiLingual Question Answering XQuAD Crosslingual Question Answering Dataset benchmark dataset evaluating crosslingual question answering performance dataset consists subset 240 paragraph 1190 questionanswer pair development set SQuAD v11 Rajpurkar et al 2016 together professional translation ten language Spanish German Greek Russian Turkish Arabic Vietnamese Thai Chinese Hindi MLQA MultiLingual Question Answering benchmark dataset evaluating crosslingual question answering performance MLQA consists 5K extractive QA instance 12K English SQuAD format seven language — English Arabic German Spanish Hindi Vietnamese Simplified Chinese MLQA highly parallel QA instance parallel 4 different language average collected 1190 contextquestion pair Deep Mind Xquad dataset Facebook MLQA concatenated test dev dataset consist total 5425 contextquestion pair Since datasets originally present JSON format ease using converted CSV format divided overall collected dataset two set training set 6500 contextquestion pair testing set 150 contextquestion pair reason keeping low count testing set unlike classification problem text generation problem doesn’t benefit much large testing dataset since metric evaluate generated question text generation general script created perform operation Colab notebook le convenient Kaggle Kaggle provide P100 GPU Colab Tesla T4 thus much lesser time finetuning Kaggle Finetuning mT5 using pytorchlightning We’ll using PyTorchlightning library finetuning code adapted trainer generic used text2text task You’ll need change dataset Rest code stay unchanged task interesting powerful thing text2text format finetune model variety NLP task formulating problem text2text setting need change hyperparameters learning rate optimizer loss function trained ‘googlemt5base’ 10 epoch batch size 8 link finetuning script want finetune mT5 task need take care two thing Create dataset CSV format change dataset path finetuning Kaggle notebook dataset must two file traincsv validcsv Secondly change QuestionDataset class Kaggle notebook according use case input format used finetuning Input Hindi Context inputtext inputtext given input model Inference Question Generation Inferencing model easiest part done heavy lifting Lets check result transformer import MT5ForConditionalGeneration AutoTokenizer model MT5ForConditionalGenerationfrompretrainedinputmt5hindiquestiongenerator tokenizer AutoTokenizerfrompretrainedgooglemt5base Input text paragraph Hindi language article Hindi contextपूरे विश्व भर में भारत एक प्रसिद्ध देश है। भौगोलिक रुप से हमारा देश एशिया महाद्वीप के दक्षिण में स्थित है। भारत एक अत्यधिक जनसंख्या वाला देश है साथ ही प्राकृतिक रुप से सभी दिशाओं से सुरक्षित है। पूरे विश्व भर में अपनी महान संस्कृति और पारंपरिक मूल्यों के लिये ये एक प्रसिद्ध देश है। इसके पास हिमालय नाम का एक पर्वत है जो विश्व में सबसे ऊँचा है। ये तीन तरफ से तीन महासागरों से घिरा हुआ है जैसे दक्षिण में भारतीय महासागर पूरब में बंगाल की खाड़ी और पश्चिम में अरेबिक सागर से। भारत एक लोकतांत्रिक देश है जो जनसंख्या के लिहाज से दूसरे स्थान पर है। भारत में मुख्य रूप से हिंदी भाषा बोली जाती है परंतु यहां लगभग 22 भाषाओं को राष्ट्रीय रुप से मान्यता दी गयी है। decoding either use greedy decoding single question generation topkp decoding multiple question generation result obtained start timetime encoding tokenizerencodeplusarticle returntensorspt inputids attentionmasks encodinginputidstodevice encodingattentionmasktodevice printarticle output greedydecodinginputidsattentionmasks print Greedy decoding output end timetime print Time elapsed endstart print Output Hindi contextपूरे विश्व भर में भारत एक प्रसिद्ध देश है। भौगोलिक रुप से हमारा देश एशिया महाद्वीप के दक्षिण में स्थित है। भारत एक अत्यधिक जनसंख्या वाला देश है साथ ही प्राकृतिक रुप से सभी दिशाओं से सुरक्षित है। पूरे विश्व भर में अपनी महान संस्कृति और पारंपरिक मूल्यों के लिये ये एक प्रसिद्ध देश है। इसके पास हिमालय नाम का एक पर्वत है जो विश्व में सबसे ऊँचा है। ये तीन तरफ से तीन महासागरों से घिरा हुआ है जैसे दक्षिण में भारतीय महासागर पूरब में बंगाल की खाड़ी और पश्चिम में अरेबिक सागर से। भारत एक लोकतांत्रिक देश है जो जनसंख्या के लिहाज से दूसरे स्थान पर है। भारत में मुख्य रूप से हिंदी भाषा बोली जाती है परंतु यहां लगभग 22 भाषाओं को राष्ट्रीय रुप से मान्यता दी गयी है। Greedy decoding भारत में कितनी भाषाएं बोली जाती हैं Time elapsed 10903606414794922 question generated seems pretty legit😇😇 topkp output multiple question Hindi contextपूरे विश्व भर में भारत एक प्रसिद्ध देश है। भौगोलिक रुप से हमारा देश एशिया महाद्वीप के दक्षिण में स्थित है। भारत एक अत्यधिक जनसंख्या वाला देश है साथ ही प्राकृतिक रुप से सभी दिशाओं से सुरक्षित है। पूरे विश्व भर में अपनी महान संस्कृति और पारंपरिक मूल्यों के लिये ये एक प्रसिद्ध देश है। इसके पास हिमालय नाम का एक पर्वत है जो विश्व में सबसे ऊँचा है। ये तीन तरफ से तीन महासागरों से घिरा हुआ है जैसे दक्षिण में भारतीय महासागर पूरब में बंगाल की खाड़ी और पश्चिम में अरेबिक सागर से। भारत एक लोकतांत्रिक देश है जो जनसंख्या के लिहाज से दूसरे स्थान पर है। भारत में मुख्य रूप से हिंदी भाषा बोली जाती है परंतु यहां लगभग 22 भाषाओं को राष्ट्रीय रुप से मान्यता दी गयी है। Topkp decoding भारत कहाँ स्थित है भारत के पास कितनी भाषाएँ हैं भारत की मुख्य भाषा क्या है भारत में मुख्य रूप से कौन सी भाषाएं बोली जाती हैं भारत में कितनी भाषाएँ बोली जाती हैं भारत की दूसरी लोकतांत्रिक सरकार क्या है भारत का हिस्सा किस महाद्वीप के दक्षिण में है भारत में कौन सी भाषा बोली जाती है हिंदी भाषा की कौन सी संस्कृति सबसे अधिक लोकप्रिय है भारत की जनसंख्या क्या है Time elapsed 13107168674468994 see question grammatically incorrect check overall quality good basic us want experiment Hindi question generator check notebook Kaggle conclude blog question generator using mT5 finetune mT5 various task various language Kaggle notebook dataset used set public anyone use given reference many notebook might confusing question may ask comment ready experiment mT5🤔🤔🤔 References Original Suraj Patil Colab Finetuning T5Tags Machine Learning Artificial Intelligence Google Technology Programming
2,842
Human Ego and Aspirations Are the Driving Forces Behind Engineering Decisions
The Choice Let’s start with an example that might be 👀 inspired by a real situation. The team needs to make a technological choice by introducing a new event broker. There is none at the moment. The two contenders are Kafka and Pulsar. Developer A has significant experience with Kafka in real life situation. They mention the complexity of Kafka operations at scale and vouches for Pulsar. Developer B is a proponent of Kafka, as it became a standard in the industry and has strong support overall. They have little experience working with Kafka though. Both agree that we only have basic requirements with no change in workload for the foreseeable future and these two solutions would both fit the bill. The rest of the team is less opinionated. After hours of meetings and point-by-point comparisons against a technical criteria grid, Kafka is chosen. Everybody agrees it’s perfectly sound decision-making, the rationale behind the choice is documented, and the team proceeds with the implementation. But are the true motivations of this choice ever evoked?
https://medium.com/better-programming/human-ego-and-aspirations-are-the-driving-forces-behind-engineering-decisions-1519ecc076ff
['Emmanuel Sys']
2020-12-18 20:47:19.588000+00:00
['Programming', 'Startup', 'DevOps', 'Software Development', 'Software Engineering']
Title Human Ego Aspirations Driving Forces Behind Engineering DecisionsContent Choice Let’s start example might 👀 inspired real situation team need make technological choice introducing new event broker none moment two contender Kafka Pulsar Developer significant experience Kafka real life situation mention complexity Kafka operation scale vouches Pulsar Developer B proponent Kafka became standard industry strong support overall little experience working Kafka though agree basic requirement change workload foreseeable future two solution would fit bill rest team le opinionated hour meeting pointbypoint comparison technical criterion grid Kafka chosen Everybody agrees it’s perfectly sound decisionmaking rationale behind choice documented team proceeds implementation true motivation choice ever evokedTags Programming Startup DevOps Software Development Software Engineering
2,843
AWS CDK Continuous Integration and Delivery Using Travis CI
Open Pull Requests to Validate Your Deployment The best strategy I have found to deploy the code to AWS is to have one branch per stage ( dev , pre , pro ), so every time a new commit reaches one of these branches, we are deploying the actual stack. Yes, it looks like GitOps! But we don’t want to blindly deploy our CDK stack on an AWS account. So I have an automatic way of opening pull requests when something is merged to the main branch: Process of opening pull request Each time something is merged to the main branch, we have a specific job that runs cdk diff -c stage=<STAGE> and opens a pull request to the destination branch. For that, we use the script below. As you can see, it runs cdk diff and uses the results to open a pull request using the GitHub CLI: Now we have to call this script inside Travis, so our .travis.yaml file will look like this: As you can see, we are now using some env variables to specify our AWS Credentials in addition to our GitHub Token. Please make sure to encrypt them before committing them in your repo.
https://medium.com/better-programming/aws-cdk-continuous-integration-and-delivery-using-travis-ci-ee5dd7549434
['Thomas Poignant']
2020-12-09 16:42:41.710000+00:00
['Startup', 'AWS', 'Travis Ci', 'DevOps', 'Programming']
Title AWS CDK Continuous Integration Delivery Using Travis CIContent Open Pull Requests Validate Deployment best strategy found deploy code AWS one branch per stage dev pre pro every time new commit reach one branch deploying actual stack Yes look like GitOps don’t want blindly deploy CDK stack AWS account automatic way opening pull request something merged main branch Process opening pull request time something merged main branch specific job run cdk diff c stageSTAGE open pull request destination branch use script see run cdk diff us result open pull request using GitHub CLI call script inside Travis travisyaml file look like see using env variable specify AWS Credentials addition GitHub Token Please make sure encrypt committing repoTags Startup AWS Travis Ci DevOps Programming
2,844
Want To Increase Your Readership Today?
Want To Increase Your Readership Today? Come join us at The Narrative. As of today, The Narrative — an independent publication designed to house some of Medium’s most influential writers is now accepting submissions to become a contributor. With over 1300 followers up to date, we use a editor-based model that allows writers to self publish as they please — much like The Partnered Pen. As Medium’s userbase keeps growing, I understand that it may become increasingly difficult to get views on your articles. This is why I decided to re-brand the publication and use a model that has been working for a lot of active users. We currently have the following categories: Arts & Culture Life Lessons Career Growth World Travels Poetry Why self-publish? It’s easy for your article to get lost in a publication, especially with the amount of activity going on Medium these days. When you self-publish, other writers will instantly receive a notification for your article. This will not only help you gain a few new followers, but it will also provide more exposure for your writing too. Things to remember. As an editor of The Narrative, editing the posts of other authors without their permission will be frowned upon. Please be mindful of this when contributing to the publication. The Narrative does not promote any hate speech or plagiarism. If you violate these terms, we will immediately revoke your participation from the publication. Supporting other writers is highly encouraged. To keep the publication a positive space, we recommend you to read the work of others, highlight and comment as much as you can. Thank you for your interest in becoming a part of The Narrative. We look forward to hearing your stories.
https://medium.com/the-partnered-pen/want-to-increase-your-readership-today-c10e935fa222
['Katy Velvet']
2020-12-26 19:26:39.487000+00:00
['Writing', 'Medium', 'Business', 'Entrepreneurship', 'Work']
Title Want Increase Readership TodayContent Want Increase Readership Today Come join u Narrative today Narrative — independent publication designed house Medium’s influential writer accepting submission become contributor 1300 follower date use editorbased model allows writer self publish please — much like Partnered Pen Medium’s userbase keep growing understand may become increasingly difficult get view article decided rebrand publication use model working lot active user currently following category Arts Culture Life Lessons Career Growth World Travels Poetry selfpublish It’s easy article get lost publication especially amount activity going Medium day selfpublish writer instantly receive notification article help gain new follower also provide exposure writing Things remember editor Narrative editing post author without permission frowned upon Please mindful contributing publication Narrative promote hate speech plagiarism violate term immediately revoke participation publication Supporting writer highly encouraged keep publication positive space recommend read work others highlight comment much Thank interest becoming part Narrative look forward hearing storiesTags Writing Medium Business Entrepreneurship Work
2,845
Introducing Kaleido:
Introducing Kaleido ✨ Static image export for web-based visualization libraries with zero dependencies Background As simple as it sounds on the surface, programmatically generating static images (e.g. raster images like PNGs or vector images like SVGs) from web-based visualization libraries (e.g. Plotly.js) is a complex problem. It’s a problem that library developers have struggled with for years, and it has delayed the adoption of these libraries among scientific communities that rely on print-based publications for sharing their research. Today we introduce Kaleido: an easy to install Chromium-based library for static image export for web-based visualization libraries. The core difficulty is that web-based visualization libraries don’t actually render plots on their own. Instead, they delegate this work to web technologies like SVG, Canvas, WebGL, etc. Similar to how matplotlib relies on various backends to display figures, web-based visualization libraries rely on a web browser rendering engine to display figures. When a figure is displayed in a browser window, it’s relatively straight-forward for a visualization library to provide an export-image button because it has full access to the browser for rendering. The difficulty arises when trying to export an image programmatically (e.g. from Python) without displaying it in a browser and without user interaction. To accomplish this, the Python portion of the visualization library needs programmatic access to a web browser’s rendering engine. There are three main approaches that are currently in use among Python web-based visualization libraries (e.g. Plotly, Bokeh, Altair, ipyvolume, etc.): The Selenium or pyppeteer Python libraries can be used to control a full system web browser such as Firefox, Chrome, or Chromium to perform image rendering. A custom headless Electron application can be used to perform image rendering using the Chromium browser engine built in to Electron. This is the approach taken by Plotly’s current Orca image export library. When operating in the Jupyter notebook or JupyterLab, a Python library can use the Jupyter Comms protocol to communicate with a custom Jupyter extension running in the browser. This extension can perform the image export and then communicate the results back to the Python process using the Comms protocol. While approaches 1 and 2 can both be installed using conda , they still rely on all of the system dependencies of a complete web browser, even the parts that aren’t actually necessary for rendering a visualization. For example, on Linux both require the installation of system libraries related to audio ( libasound.so ), video ( libffmpeg.so ), GUI toolkit ( libgtk-3.so ), screensaver ( libXss.so ), and X11 ( libX11-xcb.so ) support. Many of these are not typically included in headless Linux installations like you find in JupyterHub, Binder, Colab, Azure Notebooks, SageMaker, etc. Also, conda is still not as universally available as the pip package manager and neither approach is installable using pip packages. Additionally, both 1 and 2 communicate between the Python process and the web browser process over a local network port. While not typically a problem, certain firewall and container configurations can interfere with this local network connection. The advantage of options 3 is that it introduces no additional system dependencies. The disadvantage is that it relies on running within a Jupyter notebook, so it can’t be used in standalone Python scripts. The end result is that all of these visualization libraries have in-depth documentation pages on how to get image export working, and how to troubleshoot the inevitable failures and edge cases that people run into. While this is a great improvement over the state of affairs just a couple of years ago, and a lot of excellent work has gone into making these approaches work as seamlessly as possible, the fundamental limitations detailed above still result in sub-optimal user experiences. This is especially true when comparing web-based plotting libraries to traditional plotting libraries like matplotlib and ggplot2 where there’s never a question of whether image export will work in a particular context. The goal of the Kaleido project is to make static image export of web-based visualization libraries as universally available and reliable as it is in matplotlib and ggplot2. The Kaleido Approach To accomplish this goal, Kaleido introduces a new approach. The core of Kaleido is a standalone C++ application that embeds the open-source Chromium browser as a library. This architecture allows Kaleido to communicate with the Chromium browser engine using the C++ API rather than requiring a local network connection. A thin Python wrapper runs the Kaleido C++ application as a subprocess and communicates with it by writing image export requests to standard-in and retrieving results by reading from standard-out. By compiling Chromium as a library, we have a degree of control over what is included in the Chromium build. In particular, on Linux we can build Chromium in headless mode which eliminates a large number of runtime dependencies, including the audio, video, GUI toolkit, screensaver, and X11 dependencies mentioned above. The remaining dependencies can then be bundled with the library, making it possible to run Kaleido in minimal Linux environments with no additional dependencies required. In this way, Kaleido can be distributed as a self-contained library that plays a similar role to a matplotlib backend. Improvements Compared to Orca, Kaleido brings a wide range of improvements to plotly.py users. pip installation support Pre-compiled wheels for 64-bit Linux, MacOS, and Windows are available on PyPI and can be installed using pip . As with Orca, Kaleido can also be installed using conda . Improved startup time and resource usage Kaleido starts up about twice as fast as Orca, and uses about half as much system memory. Docker compatibility Kaleido can operate inside docker containers based on Ubuntu 14.04+ or Centos 7+ (or most any other Linux distro released after ~2014) without the need to install additional dependencies using apt or yum , and without relying on Xvfb as a headless X11 Server. Hosted notebook service compatibility Kaleido can be used in just about any online notebook service that permits the use of pip to install the kaleido package. These include Colab, Sagemaker, Azure Notebooks, Databricks, Kaggle, etc. In addition, Kaleido is compatible with the default Docker image used by Binder. Security policy / Firewall compatibility There were occasionally situations where strict security policies and/or firewall services would block Orca’s ability to bind to a local port. Kaleido does not have this limitation since it does not use ports for communication. Try it out Kaleido can be installed using pip… $ pip install kaleido or conda. $ conda install -c plotly python-kaleido Out of the box, Kaleido supports converting Plotly figures to PNG, JPG, WebP, SVG, and PDF output formats. Support for the EPS format is available when the poppler library is installed. This can be done either using conda, or a system package manager. When Kaleido is installed, plotly.py 4.9.0+ will automatically use it for image export operations, falling back to Orca if Kaleido is not available. For example… import plotly.express as px df = px.data.iris() fig = px.scatter( df, x="sepal_width", y="sepal_length", color="species" ) fig.write_image("fig.png") This will produce a file named fig.png in the current working directory containing this image PNG image produced by Kaleido Beyond plotly.py: Kaleido Scopes While the development of Kaleido has been motivated by the needs of the plotly.py community, we know we’re not unique in facing these challenges. We’ve designed the C++ and Python portions of Kaleido using a basic plugin architecture (Kaleido plugins are called Scopes) with the goal of making it possible to support image export for other web-based visualization libraries. If you’re interested in adding support to Kaleido for another web-based visualization library, check out the Scope (Plugin) Architecture wiki page and let us know how we can help! Additionally, since the core of Kaleido is a standalone C++ application that receives export requests on standard-in and writes responses to standard-out, it is relatively straightforward to build wrappers for other languages besides Python. In fact, Kaleido support will be coming soon to the Plotly for Rust library. If you’re interested in writing a Kaleido wrapper for another language, check out the Language Wrapper Architecture wiki page and, again, let us know how we can help. Learn more
https://medium.com/plotly/introducing-kaleido-b03c4b7b1d81
['Jon Mease']
2020-07-16 13:33:51.723000+00:00
['Python', 'Plotly', 'Data Visualization']
Title Introducing KaleidoContent Introducing Kaleido ✨ Static image export webbased visualization library zero dependency Background simple sound surface programmatically generating static image eg raster image like PNGs vector image like SVGs webbased visualization library eg Plotlyjs complex problem It’s problem library developer struggled year delayed adoption library among scientific community rely printbased publication sharing research Today introduce Kaleido easy install Chromiumbased library static image export webbased visualization library core difficulty webbased visualization library don’t actually render plot Instead delegate work web technology like SVG Canvas WebGL etc Similar matplotlib relies various backends display figure webbased visualization library rely web browser rendering engine display figure figure displayed browser window it’s relatively straightforward visualization library provide exportimage button full access browser rendering difficulty arises trying export image programmatically eg Python without displaying browser without user interaction accomplish Python portion visualization library need programmatic access web browser’s rendering engine three main approach currently use among Python webbased visualization library eg Plotly Bokeh Altair ipyvolume etc Selenium pyppeteer Python library used control full system web browser Firefox Chrome Chromium perform image rendering custom headless Electron application used perform image rendering using Chromium browser engine built Electron approach taken Plotly’s current Orca image export library operating Jupyter notebook JupyterLab Python library use Jupyter Comms protocol communicate custom Jupyter extension running browser extension perform image export communicate result back Python process using Comms protocol approach 1 2 installed using conda still rely system dependency complete web browser even part aren’t actually necessary rendering visualization example Linux require installation system library related audio libasoundso video libffmpegso GUI toolkit libgtk3so screensaver libXssso X11 libX11xcbso support Many typically included headless Linux installation like find JupyterHub Binder Colab Azure Notebooks SageMaker etc Also conda still universally available pip package manager neither approach installable using pip package Additionally 1 2 communicate Python process web browser process local network port typically problem certain firewall container configuration interfere local network connection advantage option 3 introduces additional system dependency disadvantage relies running within Jupyter notebook can’t used standalone Python script end result visualization library indepth documentation page get image export working troubleshoot inevitable failure edge case people run great improvement state affair couple year ago lot excellent work gone making approach work seamlessly possible fundamental limitation detailed still result suboptimal user experience especially true comparing webbased plotting library traditional plotting library like matplotlib ggplot2 there’s never question whether image export work particular context goal Kaleido project make static image export webbased visualization library universally available reliable matplotlib ggplot2 Kaleido Approach accomplish goal Kaleido introduces new approach core Kaleido standalone C application embeds opensource Chromium browser library architecture allows Kaleido communicate Chromium browser engine using C API rather requiring local network connection thin Python wrapper run Kaleido C application subprocess communicates writing image export request standardin retrieving result reading standardout compiling Chromium library degree control included Chromium build particular Linux build Chromium headless mode eliminates large number runtime dependency including audio video GUI toolkit screensaver X11 dependency mentioned remaining dependency bundled library making possible run Kaleido minimal Linux environment additional dependency required way Kaleido distributed selfcontained library play similar role matplotlib backend Improvements Compared Orca Kaleido brings wide range improvement plotlypy user pip installation support Precompiled wheel 64bit Linux MacOS Windows available PyPI installed using pip Orca Kaleido also installed using conda Improved startup time resource usage Kaleido start twice fast Orca us half much system memory Docker compatibility Kaleido operate inside docker container based Ubuntu 1404 Centos 7 Linux distro released 2014 without need install additional dependency using apt yum without relying Xvfb headless X11 Server Hosted notebook service compatibility Kaleido used online notebook service permit use pip install kaleido package include Colab Sagemaker Azure Notebooks Databricks Kaggle etc addition Kaleido compatible default Docker image used Binder Security policy Firewall compatibility occasionally situation strict security policy andor firewall service would block Orca’s ability bind local port Kaleido limitation since use port communication Try Kaleido installed using pip… pip install kaleido conda conda install c plotly pythonkaleido box Kaleido support converting Plotly figure PNG JPG WebP SVG PDF output format Support EPS format available poppler library installed done either using conda system package manager Kaleido installed plotlypy 490 automatically use image export operation falling back Orca Kaleido available example… import plotlyexpress px df pxdatairis fig pxscatter df xsepalwidth ysepallength colorspecies figwriteimagefigpng produce file named figpng current working directory containing image PNG image produced Kaleido Beyond plotlypy Kaleido Scopes development Kaleido motivated need plotlypy community know we’re unique facing challenge We’ve designed C Python portion Kaleido using basic plugin architecture Kaleido plugins called Scopes goal making possible support image export webbased visualization library you’re interested adding support Kaleido another webbased visualization library check Scope Plugin Architecture wiki page let u know help Additionally since core Kaleido standalone C application receives export request standardin writes response standardout relatively straightforward build wrapper language besides Python fact Kaleido support coming soon Plotly Rust library you’re interested writing Kaleido wrapper another language check Language Wrapper Architecture wiki page let u know help Learn moreTags Python Plotly Data Visualization
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Coronavirus: Why You Must Act Now
If you stack up the orange bars until 1/22, you get 444 cases. Now add up all the grey bars. They add up to ~12,000 cases. So when Wuhan thought it had 444 cases, it had 27 times more. If France thinks it has 1,400 cases, it might well have tens of thousands The same math applies to Paris. With ~30 cases inside the city, the true number of cases is likely to be in the hundreds, maybe thousands. With 300 cases in the Ile-de-France region, the total cases in the region might already exceed tens of thousands. Spain and Madrid Spain has very similar numbers as France (1,200 cases vs. 1,400, and both have 30 deaths). That means the same rules are valid: Spain has probably upwards of 20k true cases already. In the Comunidad de Madrid region, with 600 official cases and 17 deaths, the true number of cases is likely between 10,000 and 60,000. If you read these data and tell yourself: “Impossible, this can’t be true”, just think this: With this number of cases, Wuhan was already in lockdown. With the number of cases we see today in countries like the US, Spain, France, Iran, Germany, Japan, Netherlands, Denmark, Sweden or Switzerland, Wuhan was already in lockdown. And if you’re telling yourself: “Well, Hubei is just one region”, let me remind you that it has nearly 60 million people, bigger than Spain and about the size of France. 2. What Will Happen When These Coronavirus Cases Materialize? So the coronavirus is already here. It’s hidden, and it’s growing exponentially. What will happen in our countries when it hits? It’s easy to know, because we already have several places where it’s happening. The best examples are Hubei and Italy. Fatality Rates The World Health Organization (WHO) quotes 3.4% as the fatality rate (% people who contract the coronavirus and then die). This number is out of context so let me explain it. It really depends on the country and the moment: between 0.6% in South Korea and 4.4% in Iran. So what is it? We can use a trick to figure it out. The two ways you can calculate the fatality rate is Deaths/Total Cases and Death/Closed Cases. The first one is likely to be an underestimate, because lots of open cases can still end up in death. The second is an overestimate, because it’s likely that deaths are closed quicker than recoveries. What I did was look at how both evolve over time. Both of these numbers will converge to the same result once all cases are closed, so if you project past trends to the future, you can make a guess on what the final fatality rate will be. This is what you see in the data. China’s fatality rate is now between 3.6% and 6.1%. If you project that in the future, it looks like it converges towards ~3.8%-4%. This is double the current estimate, and 30 times worse than the flu. It is made up of two completely different realities though: Hubei and the rest of China. Hubei’s fatality rate will probably converge towards 4.8%. Meanwhile, for the rest of China, it will likely converge to ~0.9%: I also charted the numbers for Iran, Italy and South Korea, the only countries with enough deaths to make this somewhat relevant. Iran’s and Italy’s Deaths / Total Cases are both converging towards the 3%-4% range. My guess is their numbers will end up around that figure too. South Korea is the most interesting example, because these 2 numbers are completely disconnected: deaths / total cases is only 0.6%, but deaths / closed cases is a whopping 48%. My take on it is that a few unique things are happening there. First, they’re testing everybody (with so many open cases, the death rate seems low), and leaving the cases open for longer (so they close cases quickly when the patient is dead). Second, they have a lot of hospital beds (see chart 17.b). There might also be other reasons we don’t know. What is relevant is that deaths/cases has hovered around 0.5% since the beginning, suggesting it will stay there, likely heavily influenced by the healthcare system and crisis management. The last relevant example is the Diamond Princess cruise: with 706 cases, 6 deaths and 100 recoveries, the fatality rate will be between 1% and 6.5%. Note that the age distribution in each country will also have an impact: Since mortality is much higher for older people, countries with an aging population like Japan will be harder hit on average than younger countries like Nigeria. There are also weather factors, especially humidity and temperature, but it’s still unclear how this will impact transmission and fatality rates. This is what you can conclude: Excluding these, countries that are prepared will see a fatality rate of ~0.5% (South Korea) to 0.9% (rest of China). Countries that are overwhelmed will have a fatality rate between ~3%-5% Put in another way: Countries that act fast can reduce the number of deaths by a factor of ten. And that’s just counting the fatality rate. Acting fast also drastically reduces the cases, making this even more of a no-brainer. Countries that act fast reduce the number of deaths at least by 10x. So what does a country need to be prepared? What Will Be the Pressure on the System Around 20% of cases require hospitalization, 5% of cases require the Intensive Care Unit (ICU), and around 2.5% require very intensive help, with items such as ventilators or ECMO (extra-corporeal oxygenation). The problem is that items such as ventilators and ECMO can’t be produced or bought easily. A few years ago, the US had a total of 250 ECMO machines, for example. So if you suddenly have 100,000 people infected, many of them will want to go get tested. Around 20,000 will require hospitalization, 5,000 will need the ICU, and 1,000 will need machines that we don’t have enough of today. And that’s just with 100,000 cases. That is without taking into account issues such as masks. A country like the US has only 1% of the masks it needs to cover the needs of its healthcare workers (12M N95, 30M surgical vs. 3.5B needed). If a lot of cases appear at once, there will be masks for only 2 weeks. Countries like Japan, South Korea, Hong Kong or Singapore, as well as Chinese regions outside of Hubei, have been prepared and given the care that patients need. But the rest of Western countries are rather going in the direction of Hubei and Italy. So what is happening there? What an Overwhelmed Healthcare System Looks Like The stories that happened in Hubei and those in Italy are starting to become eerily similar. Hubei built two hospitals in ten days, but even then, it was completely overwhelmed. Both complained that patients inundated their hospitals. They had to be taken care of anywhere: in hallways, in waiting rooms… I heavily recommend this short Twitter thread. It paints a pretty stark picture of Italy today Healthcare workers spend hours in a single piece of protective gear, because there’s not enough of them. As a result, they can’t leave the infected areas for hours. When they do, they crumble, dehydrated and exhausted. Shifts don’t exist anymore. People are driven back from retirement to cover needs. People who have no idea about nursing are trained overnight to fulfill critical roles. Everybody is on call, always. Francesca Mangiatordi, an Italian nurse that crumbled in the middle of the war with the Coronavirus That is, until they become sick. Which happens a lot, because they’re in constant exposure to the virus, without enough protective gear. When that happens, they need to be in quarantine for 14 days, during which they can’t help. Best case scenario, 2 weeks are lost. Worst case, they’re dead. The worst is in the ICUs, when patients need to share ventilators or ECMOs. These are in fact impossible to share, so the healthcare workers must determine what patient will use it. That really means, which one lives and which one dies. “After a few days, we have to choose. […] Not everyone can be intubated. We decide based on age and state of health.” —Christian Salaroli, Italian MD. Medical workers wear protective suits to attend to people sickened by the novel coronavirus, in the intensive care unit of a designated hospital in Wuhan, China, on Feb. 6. (China Daily/Reuters), via Washington Post All of this is what drives a system to have a fatality rate of ~4% instead of ~0.5%. If you want your city or your country to be part of the 4%, don’t do anything today. Satellite images show Behesht Masoumeh cemetery in the Iranian city of Qom. Photograph: ©2020 Maxar Technologies. Via The Guardian and the The New York Times. 3. What Should You Do? Flatten the Curve This is a pandemic now. It can’t be eliminated. But what we can do is reduce its impact. Some countries have been exemplary at this. The best one is Taiwan, which is extremely connected with China and yet still has as of today fewer than 50 cases. This recent paper explain all the measures they took early on, which were focused on containment. They have been able to contain it, but most countries lacked this expertise and didn’t. Now, they’re playing a different game: mitigation. They need to make this virus as inoffensive as possible. If we reduce the infections as much as possible, our healthcare system will be able to handle cases much better, driving the fatality rate down. And, if we spread this over time, we will reach a point where the rest of society can be vaccinated, eliminating the risk altogether. So our goal is not to eliminate coronavirus contagions. It’s to postpone them. The more we postpone cases, the better the healthcare system can function, the lower the mortality rate, and the higher the share of the population that will be vaccinated before it gets infected. How do we flatten the curve? Social Distancing There is one very simple thing that we can do and that works: social distancing. If you go back to the Wuhan graph, you will remember that as soon as there was a lockdown, cases went down. That’s because people didn’t interact with each other, and the virus didn’t spread. The current scientific consensus is that this virus can be spread within 2 meters (6 feet) if somebody coughs. Otherwise, the droplets fall to the ground and don’t infect you. The worst infection then becomes through surfaces: The virus survives for up to 9 days on different surfaces such as metal, ceramics and plastics. That means things like doorknobs, tables, or elevator buttons can be terrible infection vectors. The only way to truly reduce that is with social distancing: Keeping people home as much as possible, for as long as possible until this recedes. This has already been proven in the past. Namely, in the 1918 flu pandemic. Learnings from the 1918 Flu Pandemic You can see how Philadelphia didn’t act quickly, and had a massive peak in death rates. Compare that with St Louis, which did. Then look at Denver, which enacted measures and then loosened them. They had a double peak, with the 2nd one higher than the first. If you generalize, this is what you find: This chart shows, for the 1918 flu in the US, how many more deaths there were per city depending on how fast measures were taken. For example, a city like St Louis took measures 6 days before Pittsburgh, and had less than half the deaths per citizen. On average, taking measures 20 days earlier halved the death rate. Italy has finally figured this out. They first locked down Lombardy on Sunday, and one day later, on Monday, they realized their mistake and decided they had to lock down the entire country. Hopefully, we will see results in the coming days. However, it will take one to two weeks to see. Remember the Wuhan graph: there was a delay of 12 days between the moment when the lockdown was announced and the moment when official cases (orange) started going down. How Can Politicians Contribute to Social Distancing? The question politicians are asking themselves today is not whether they should do something, but rather what’s the appropriate action to take. There are several stages to control an epidemic, starting with anticipation and ending with eradication. But it’s too late for most options today. With this level of cases, the only options politicians have in front of them are containment, mitigation or suppression. Containment Containment is making sure all the cases are identified, controlled, and isolated. It’s what Singapore, South Korea or Taiwan are doing so well: They very quickly limit people coming in, identify the sick, immediately isolate them, use heavy protective gear to protect their health workers, track all their contacts, quarantine them… This works extremely well when you’re prepared and you do it early on, and don’t need to grind your economy to a halt to make it happen. I’ve already touted Taiwan’s approach. But China’s is good too. The lengths at which it went to contain the virus are mind-boggling. For example, they had up to 1,800 teams of 5 people each tracking every infected person, everybody they got interacted with, then everybody those people interacted with, and isolating the bunch. That’s how they were able to contain the virus across a billion-people country. This is not what Western countries have done. And now it’s too late. The recent US announcement that most travel from Europe was banned is a containment measure for a country that has, as of today, 3 times the cases that Hubei had when it shut down, growing exponentially. How can we know if it’s enough? It turns out, we can know by looking at the Wuhan travel ban.
https://tomaspueyo.medium.com/coronavirus-act-today-or-people-will-die-f4d3d9cd99ca
['Tomas Pueyo']
2020-05-28 07:57:30.905000+00:00
['Epidemia', 'Health', 'Healthcare', 'Coronavirus', 'Virality']
Title Coronavirus Must Act NowContent stack orange bar 122 get 444 case add grey bar add 12000 case Wuhan thought 444 case 27 time France think 1400 case might well ten thousand math applies Paris 30 case inside city true number case likely hundred maybe thousand 300 case IledeFrance region total case region might already exceed ten thousand Spain Madrid Spain similar number France 1200 case v 1400 30 death mean rule valid Spain probably upwards 20k true case already Comunidad de Madrid region 600 official case 17 death true number case likely 10000 60000 read data tell “Impossible can’t true” think number case Wuhan already lockdown number case see today country like US Spain France Iran Germany Japan Netherlands Denmark Sweden Switzerland Wuhan already lockdown you’re telling “Well Hubei one region” let remind nearly 60 million people bigger Spain size France 2 Happen Coronavirus Cases Materialize coronavirus already It’s hidden it’s growing exponentially happen country hit It’s easy know already several place it’s happening best example Hubei Italy Fatality Rates World Health Organization quote 34 fatality rate people contract coronavirus die number context let explain really depends country moment 06 South Korea 44 Iran use trick figure two way calculate fatality rate DeathsTotal Cases DeathClosed Cases first one likely underestimate lot open case still end death second overestimate it’s likely death closed quicker recovery look evolve time number converge result case closed project past trend future make guess final fatality rate see data China’s fatality rate 36 61 project future look like converges towards 384 double current estimate 30 time worse flu made two completely different reality though Hubei rest China Hubei’s fatality rate probably converge towards 48 Meanwhile rest China likely converge 09 also charted number Iran Italy South Korea country enough death make somewhat relevant Iran’s Italy’s Deaths Total Cases converging towards 34 range guess number end around figure South Korea interesting example 2 number completely disconnected death total case 06 death closed case whopping 48 take unique thing happening First they’re testing everybody many open case death rate seems low leaving case open longer close case quickly patient dead Second lot hospital bed see chart 17b might also reason don’t know relevant deathscases hovered around 05 since beginning suggesting stay likely heavily influenced healthcare system crisis management last relevant example Diamond Princess cruise 706 case 6 death 100 recovery fatality rate 1 65 Note age distribution country also impact Since mortality much higher older people country aging population like Japan harder hit average younger country like Nigeria also weather factor especially humidity temperature it’s still unclear impact transmission fatality rate conclude Excluding country prepared see fatality rate 05 South Korea 09 rest China Countries overwhelmed fatality rate 35 Put another way Countries act fast reduce number death factor ten that’s counting fatality rate Acting fast also drastically reduces case making even nobrainer Countries act fast reduce number death least 10x country need prepared Pressure System Around 20 case require hospitalization 5 case require Intensive Care Unit ICU around 25 require intensive help item ventilator ECMO extracorporeal oxygenation problem item ventilator ECMO can’t produced bought easily year ago US total 250 ECMO machine example suddenly 100000 people infected many want go get tested Around 20000 require hospitalization 5000 need ICU 1000 need machine don’t enough today that’s 100000 case without taking account issue mask country like US 1 mask need cover need healthcare worker 12M N95 30M surgical v 35B needed lot case appear mask 2 week Countries like Japan South Korea Hong Kong Singapore well Chinese region outside Hubei prepared given care patient need rest Western country rather going direction Hubei Italy happening Overwhelmed Healthcare System Looks Like story happened Hubei Italy starting become eerily similar Hubei built two hospital ten day even completely overwhelmed complained patient inundated hospital taken care anywhere hallway waiting rooms… heavily recommend short Twitter thread paint pretty stark picture Italy today Healthcare worker spend hour single piece protective gear there’s enough result can’t leave infected area hour crumble dehydrated exhausted Shifts don’t exist anymore People driven back retirement cover need People idea nursing trained overnight fulfill critical role Everybody call always Francesca Mangiatordi Italian nurse crumbled middle war Coronavirus become sick happens lot they’re constant exposure virus without enough protective gear happens need quarantine 14 day can’t help Best case scenario 2 week lost Worst case they’re dead worst ICUs patient need share ventilator ECMOs fact impossible share healthcare worker must determine patient use really mean one life one dy “After day choose … everyone intubated decide based age state health” —Christian Salaroli Italian MD Medical worker wear protective suit attend people sickened novel coronavirus intensive care unit designated hospital Wuhan China Feb 6 China DailyReuters via Washington Post drive system fatality rate 4 instead 05 want city country part 4 don’t anything today Satellite image show Behesht Masoumeh cemetery Iranian city Qom Photograph ©2020 Maxar Technologies Via Guardian New York Times 3 Flatten Curve pandemic can’t eliminated reduce impact country exemplary best one Taiwan extremely connected China yet still today fewer 50 case recent paper explain measure took early focused containment able contain country lacked expertise didn’t they’re playing different game mitigation need make virus inoffensive possible reduce infection much possible healthcare system able handle case much better driving fatality rate spread time reach point rest society vaccinated eliminating risk altogether goal eliminate coronavirus contagion It’s postpone postpone case better healthcare system function lower mortality rate higher share population vaccinated get infected flatten curve Social Distancing one simple thing work social distancing go back Wuhan graph remember soon lockdown case went That’s people didn’t interact virus didn’t spread current scientific consensus virus spread within 2 meter 6 foot somebody cough Otherwise droplet fall ground don’t infect worst infection becomes surface virus survives 9 day different surface metal ceramic plastic mean thing like doorknob table elevator button terrible infection vector way truly reduce social distancing Keeping people home much possible long possible recedes already proven past Namely 1918 flu pandemic Learnings 1918 Flu Pandemic see Philadelphia didn’t act quickly massive peak death rate Compare St Louis look Denver enacted measure loosened double peak 2nd one higher first generalize find chart show 1918 flu US many death per city depending fast measure taken example city like St Louis took measure 6 day Pittsburgh le half death per citizen average taking measure 20 day earlier halved death rate Italy finally figured first locked Lombardy Sunday one day later Monday realized mistake decided lock entire country Hopefully see result coming day However take one two week see Remember Wuhan graph delay 12 day moment lockdown announced moment official case orange started going Politicians Contribute Social Distancing question politician asking today whether something rather what’s appropriate action take several stage control epidemic starting anticipation ending eradication it’s late option today level case option politician front containment mitigation suppression Containment Containment making sure case identified controlled isolated It’s Singapore South Korea Taiwan well quickly limit people coming identify sick immediately isolate use heavy protective gear protect health worker track contact quarantine them… work extremely well you’re prepared early don’t need grind economy halt make happen I’ve already touted Taiwan’s approach China’s good length went contain virus mindboggling example 1800 team 5 people tracking every infected person everybody got interacted everybody people interacted isolating bunch That’s able contain virus across billionpeople country Western country done it’s late recent US announcement travel Europe banned containment measure country today 3 time case Hubei shut growing exponentially know it’s enough turn know looking Wuhan travel banTags Epidemia Health Healthcare Coronavirus Virality
2,847
Interesting AI/ML Articles On Medium This Week (Dec 12)
Some adults know Santa Claus isn’t real. But that doesn’t stop deep fake Santa Claus from making an appearance this Christmas. Thomas Smith explores an AI video generation tool that produces deep fake Santas. These synthetically generated Santas can utter words from provided scripts. Jair Ribeiro visualises a future where his daughters experience the comfort and efficiency of automated driving cars. Also, If you are a fan of Game Of Thrones, then Sajid Lhessani’s unique take on the association of programming languages and GOT characters is an article you have to read. These are just examples of the interesting articles I came across this week. Feel free to scroll through my compiled list of AI/ML/DS articles that are sure to provide some form of value to ML practitioners.
https://towardsdatascience.com/interesting-ai-ml-articles-on-medium-this-week-dec-12-59ffa32f1a5f
['Richmond Alake']
2020-12-12 01:04:01.633000+00:00
['Machine Learning', 'Artificial Intelligence', 'Technology', 'AI', 'Data Science']
Title Interesting AIML Articles Medium Week Dec 12Content adult know Santa Claus isn’t real doesn’t stop deep fake Santa Claus making appearance Christmas Thomas Smith explores AI video generation tool produce deep fake Santas synthetically generated Santas utter word provided script Jair Ribeiro visualises future daughter experience comfort efficiency automated driving car Also fan Game Thrones Sajid Lhessani’s unique take association programming language GOT character article read example interesting article came across week Feel free scroll compiled list AIMLDS article sure provide form value ML practitionersTags Machine Learning Artificial Intelligence Technology AI Data Science
2,848
‘Animal Kingdom,’ Prince’s Animal Rights Anthem
When regarding the late musician Prince, subjective statements find themselves turning objective. It is simply and undeniably factual that he was a guitar virtuoso, a musical visionary, fearless, pioneering, and massively influential. Also undeniable is how prolific Prince was, with an astonishing thirty-nine studio albums, to say nothing of compilations, live recordings, albums recorded with his bands, and posthumous releases. You might conclude that statistically anyone who creates thirty-nine albums worth of material would surely end up with a song about the plight of animals, because eventually, what else would there be to write about? Prince, of course, had no need for such a theorem: he was a proud animal rights activist and wrote about the subject very much on purpose, for example, in the song “Animal Kingdom” from his 1998 album The Truth — which was, for those counting, merely his twenty first studio album. “To eat a tomato and then replant it for your nutrition as opposed to killing a cow or a pig for your meal is reducing the amount of suffering in the world. Besides, pigs are too cute to die.” For the casual fan — which I admit, is me — it would be very easy to miss this song amongst Prince’s dizzying output. But it’s a highly rewarding discovery. According to interviews, Prince stopped eating red meat in the 1980s — “we don’t have to kill things to survive!” — and then continued to move towards a vegan lifestyle, although he has also claimed to be a vegetarian. “Compassion is an action word with no boundaries,” he said, “It is never wasted. To eat a tomato and then replant it for your nutrition as opposed to killing a cow or a pig for your meal is reducing the amount of suffering in the world. Besides, pigs are too cute to die.” This idea of compassion and living in harmony with the universe is explored in “Animal Kingdom,” a song that is edifying yet sexy at the same time, a curious but effective mix for getting his point across. His opinions are unambiguous, strident even, however the song is so languid and lushly produced that it’s a pleasure to receive the information. I saw a friend of mine today, in an ad sayin’ what would do my body good I told him he was wasting time I say If God wanted milk in me The breast I suck would have a line around the hood. The friend Prince is referring to is director Spike Lee, participating in the 90s celebrity-fronted Got Milk? campaign. This opening feels like pure brazen Prince, but the lyrics continue in an emotive, informative fashion. “No animal nurses past maturity,” he reminds us, and then, “I don’t eat red meat or white fish, don’t give me no blue cheese — we’re all members of the animal kingdom, leave your brothers and sisters in the sea.” I won’t lie, I don’t often consider the interiority of the clam, but such is the power of Prince’s profound words and delivery that I felt my eyes get a little misty when he sung this line: What about the clams on the shore? Souls in progress — here comes the fisherman — souls no more. This song was ahead of its time in many ways — not just in terms of the relevance of its message, as more people continue to reject eating animals. “Animal Kingdom” really sounds like it could have been released in the last year. There’s an airy quality to the production, his voice is extruded through a vocoder, every part of it is dreamy and unhurried — even the slinky guitar riff and bass line — and it’s interspersed with ambient ocean noises. It somehow sounds — and I mean this in a positive way — viral. It could sit side by side with say, “Old Town Road” or “Redbone,” those tracks that become songs of the summer, that become the background of your favourite TikToc videos, that you want to hear over and over again. It just feels so fresh. Further evidence of the power of Prince — way back in 1998 he knew how to not only preempt the ideas of the future, but also the sound of it.
https://medium.com/tenderlymag/animal-kingdom-prince-s-animal-rights-anthem-eea65d165db2
['Laura Vincent']
2020-01-10 17:31:01.950000+00:00
['Vegan', 'Equality', 'Prince', 'Animal Rights', 'Music']
Title ‘Animal Kingdom’ Prince’s Animal Rights AnthemContent regarding late musician Prince subjective statement find turning objective simply undeniably factual guitar virtuoso musical visionary fearless pioneering massively influential Also undeniable prolific Prince astonishing thirtynine studio album say nothing compilation live recording album recorded band posthumous release might conclude statistically anyone creates thirtynine album worth material would surely end song plight animal eventually else would write Prince course need theorem proud animal right activist wrote subject much purpose example song “Animal Kingdom” 1998 album Truth — counting merely twenty first studio album “To eat tomato replant nutrition opposed killing cow pig meal reducing amount suffering world Besides pig cute die” casual fan — admit — would easy miss song amongst Prince’s dizzying output it’s highly rewarding discovery According interview Prince stopped eating red meat 1980s — “we don’t kill thing survive” — continued move towards vegan lifestyle although also claimed vegetarian “Compassion action word boundaries” said “It never wasted eat tomato replant nutrition opposed killing cow pig meal reducing amount suffering world Besides pig cute die” idea compassion living harmony universe explored “Animal Kingdom” song edifying yet sexy time curious effective mix getting point across opinion unambiguous strident even however song languid lushly produced it’s pleasure receive information saw friend mine today ad sayin’ would body good told wasting time say God wanted milk breast suck would line around hood friend Prince referring director Spike Lee participating 90 celebrityfronted Got Milk campaign opening feel like pure brazen Prince lyric continue emotive informative fashion “No animal nurse past maturity” reminds u “I don’t eat red meat white fish don’t give blue cheese — we’re member animal kingdom leave brother sister sea” won’t lie don’t often consider interiority clam power Prince’s profound word delivery felt eye get little misty sung line clam shore Souls progress — come fisherman — soul song ahead time many way — term relevance message people continue reject eating animal “Animal Kingdom” really sound like could released last year There’s airy quality production voice extruded vocoder every part dreamy unhurried — even slinky guitar riff bass line — it’s interspersed ambient ocean noise somehow sound — mean positive way — viral could sit side side say “Old Town Road” “Redbone” track become song summer become background favourite TikToc video want hear feel fresh evidence power Prince — way back 1998 knew preempt idea future also sound itTags Vegan Equality Prince Animal Rights Music
2,849
5 Habits That Are Holding You Back From Being the Best Writer You Can Be
5. Complaining. Period. Photo by Priscilla Du Preez on Unsplash “This is unfair.” “How come I haven’t made that much yet?” “Why is everyone else doing better than me?” “How come she gets to do that?” “Why is this platform changing again?” It’s impossible for people not to complain. We’ve got a lot of crappy feelings inside that are slamming against the cage of our ribs, hoping to escape. But I do know that we can practice becoming aware of when we complain. We have the ability to stop ourselves from looking like further ungrateful bumbling idiots. (No offense. Also, I’m kidding. We’re not idiots. We’re human.) Complaining only accomplishes one thing: making you feel like crap. Other than that, it doesn’t benefit you. It doesn’t act like a slingshot and fling you closer to your goals. This journey is unfair. You might as well accept that now because once you do you can ask yourself this question: Am I going to keep complaining or am I going to do something about it? For example, let’s say a website made a change you don’t like. What can you do? Reach out to them about it. Take action. And if they don’t get back to you? Get over it. Seriously. What are you going to do? Keep complaining? No one cares. When I find myself feeling envious of someone’s success I tell myself one thing: “If you want those results, then start working as hard as them.” or “If you want to make that much money, stick around as long as them.” Keep working — that’ll get you the results you want. You can also acknowledge all the ways life is fair to you. You’re not making $1,000 yet, but you earned $100. You don’t have 50 comments, but you have five. You’re doing what you love. You’ve made friends. There’s a lot of greatness to acknowledge. Don’t let your self-pity, anger, or jealousy get in the way of it. Let that gray cloud move along so you can see the sun.
https://medium.com/the-brave-writer/5-habits-that-are-holding-you-back-from-being-the-best-writer-you-can-be-7d33b63142fe
['Itxy Lopez']
2020-11-19 17:01:08.290000+00:00
['Creativity', 'Writing Tips', '5 Tips', 'Habits', 'Writing']
Title 5 Habits Holding Back Best Writer BeContent 5 Complaining Period Photo Priscilla Du Preez Unsplash “This unfair” “How come haven’t made much yet” “Why everyone else better me” “How come get that” “Why platform changing again” It’s impossible people complain We’ve got lot crappy feeling inside slamming cage rib hoping escape know practice becoming aware complain ability stop looking like ungrateful bumbling idiot offense Also I’m kidding We’re idiot We’re human Complaining accomplishes one thing making feel like crap doesn’t benefit doesn’t act like slingshot fling closer goal journey unfair might well accept ask question going keep complaining going something example let’s say website made change don’t like Reach Take action don’t get back Get Seriously going Keep complaining one care find feeling envious someone’s success tell one thing “If want result start working hard them” “If want make much money stick around long them” Keep working — that’ll get result want also acknowledge way life fair You’re making 1000 yet earned 100 don’t 50 comment five You’re love You’ve made friend There’s lot greatness acknowledge Don’t let selfpity anger jealousy get way Let gray cloud move along see sunTags Creativity Writing Tips 5 Tips Habits Writing
2,850
A Major Instigator of Modern Conflict
When my daughter was in high school, she constantly questioned why it was so important to learn about history. Why did she have to study what happened hundreds or thousands of years ago, and when would she ever need to use any of that knowledge throughout her life? Although I often wondered the same, my automatic response would almost always be that it was important to know where we came from, and how the world got to be what it is today. And it’s true, we do! But what we choose to do with that information can be a little conflicting. How much weight should we allow past history to have on shaping the present and the future? I’m not arguing the fact that it’s important to know about our ancestors — what has shaped the world we live in today. However, we need to learn where to draw a very real line between knowing about it and re-living it. I’m going to start by saying that this is an opinion piece, and should only be taken as such. History vs. Heritage. There are many history buffs who feel it’s extremely important to know what happened before us. For example, did Christopher Colombus really discover America? History books say yes, but research tells us that he probably didn’t. I personally love learning and hearing about things that happened throughout history, not only in my own country and culture but in every country and culture. The good, the bad, and the ugly. And there’s a whole lot of ugly, from every point of view. Humans have a history of doing really horrific things to one another. That being said, I tend to question a lot of it and not just take everything at face value. History books were written and re-written, translated and updated. As we are mostly all writers here, I’m sure you can attest that most of what we write is tainted by our own often biassed opinions. How one person perceives an event might not be how the next person sees it. And just like rumours tend to evolve over time, we should probably expect that some of what was written as history may not be exactly as it happened. Just as we should expect that some of what happened may never have been written at all, or that some of what was written may have never happened. The only true experts on history are those who lived it. Why are so much time and energy spent (wasted?) on worrying about what has already happened? Heritage is one thing — but history is something entirely different, although it’s often mistaken for the same. Should we not be less concerned with a past that cannot be changed, and more with making sure we don’t repeat it? Should we not be focused more on how we can live our lives to the best of our abilities today, in order to create a beautiful tomorrow? We are currently writing the history books that will grace library shelves — or internet sites, or whatever technology will have overtaken the world — in another hundred years. What kind of legacy are we prepared to leave behind? What kind of ancestors do we want to portray? Our heritage tells us where we came from — what our customs were, the kind of lives our ancestors lived. Heritage is where family and cultural traditions come from, as a people. History, on the other hand, recounts events, both traumatic and memorable, such as wars, conflicts, and victories. Do not mistake the two. The Weight of History History, because we allow it, has the undeserved power to create chaos by reminding us of all the horrible things that have happened in the past. And let’s face it, the human race has recorded many more horrific events than we have good ones. Many more, I’m sure, have gone unspoken. Unwritten. And even most of those things that we consider to be ‘good’ have emerged out of conflict and war. Humans are a cruel, self-serving species. We’ve orchestrated horrifying events throughout the past centuries. We’ve gone to war more times than I can count, and continue to do so. We’ve enslaved or eradicated entire groups of people. We’ve traumatized, demoralized, dehumanized, and administered unspeakable torture. And instead of choosing to heal from these hurts, we hang on for dear life. We feel sorry for ourselves and pick at the wounds, we let it fester. We refuse to let go of the things that were done by our ancestors — and to our ancestor. We cling to it with fierce determination, hell-bent on retribution. Validation and revenge. We rant and scream about hate when we should encourage love. Who was right? Who was wrong? We endlessly debate this question with no right answer, instead of living in the present to create a peaceful future. Instead of making ‘now’ a good place to be, by our words and actions. We continue to revive and relive history, taking offence in the actions of our predecessors, and ultimately recreating them, taking vengeance on those who look the part. We bring history back to life and take our self-justified revenge on the people of this generation as if they were the ones who personally persecuted us. I ask you: should we let events that happened hundreds of years ago dictate how we live our lives today? People. We are not our ancestors. They were not us! Let us love, not hate! Do we make a child pay for the sins of his father? Or do we teach that child a better way instead? Live and Learn To live is to learn. To learn, to live. We can usually learn from our own mistakes, but we should also take notes and learn from the mistakes of those before us. Learn what to do. What not to do. We can see — both first and second hand — by being the product of what was, what needs to change in order for us to ensure a better outcome for what will be. This Woman’s [Unpopular] Opinion My thoughts on this may not be shared by many, but it’s my hope that they are at least shared by some. In my mind, the concept is quite simple. Or at least, should be simple. We are but one race: humankind. We have but one home: planet earth. A planet we did not create, therefore, do not own. We have ignorantly chosen, and continue to choose segregation. We have repeatedly chosen to divide. To conquer. To argue about who discovered what. To fight over land that we put our name on, to plant our flag in, but is not ours to fight over. We mistreat our home, and each other, with disregard, arrogance, hatred, and unspeakable violence. Where there should be unity, there is division. War, where there should be peace. We judge and hate those who appear different from us when we should accept, love, and embrace the undeniable beauty of diversity and individuality. History has proven time and again that there are no real winners in war. And yet we choose to continue down the same destructive paths paved by those who came before us. We choose to expand the divide. Real humanity knows no colour. Knows no language but love. It knows no judgement. Humanity is inclusive, completely. Regardless of whether you believe in one God, or many. Whether you are far left, or far right. Whether your skin is made of light or dark pigments, or no pigments at all. Whether you love men or women, or both, or neither. Where history has destroyed, humanity should rebuild. It is our duty as humans to go forth in unity, with love for all as our one guide. Because we all bleed red. And because when you turn out the lights, we all look the same.
https://medium.com/the-partnered-pen/a-major-instigator-of-modern-conflict-705086443f8a
['Edie Tuck']
2019-10-24 22:26:29.714000+00:00
['Society', 'Life', 'Conflict', 'History', 'Change']
Title Major Instigator Modern ConflictContent daughter high school constantly questioned important learn history study happened hundred thousand year ago would ever need use knowledge throughout life Although often wondered automatic response would almost always important know came world got today it’s true choose information little conflicting much weight allow past history shaping present future I’m arguing fact it’s important know ancestor — shaped world live today However need learn draw real line knowing reliving I’m going start saying opinion piece taken History v Heritage many history buff feel it’s extremely important know happened u example Christopher Colombus really discover America History book say yes research tell u probably didn’t personally love learning hearing thing happened throughout history country culture every country culture good bad ugly there’s whole lot ugly every point view Humans history really horrific thing one another said tend question lot take everything face value History book written rewritten translated updated mostly writer I’m sure attest write tainted often biassed opinion one person perceives event might next person see like rumour tend evolve time probably expect written history may exactly happened expect happened may never written written may never happened true expert history lived much time energy spent wasted worrying already happened Heritage one thing — history something entirely different although it’s often mistaken le concerned past cannot changed making sure don’t repeat focused live life best ability today order create beautiful tomorrow currently writing history book grace library shelf — internet site whatever technology overtaken world — another hundred year kind legacy prepared leave behind kind ancestor want portray heritage tell u came — custom kind life ancestor lived Heritage family cultural tradition come people History hand recount event traumatic memorable war conflict victory mistake two Weight History History allow undeserved power create chaos reminding u horrible thing happened past let’s face human race recorded many horrific event good one Many I’m sure gone unspoken Unwritten even thing consider ‘good’ emerged conflict war Humans cruel selfserving specie We’ve orchestrated horrifying event throughout past century We’ve gone war time count continue We’ve enslaved eradicated entire group people We’ve traumatized demoralized dehumanized administered unspeakable torture instead choosing heal hurt hang dear life feel sorry pick wound let fester refuse let go thing done ancestor — ancestor cling fierce determination hellbent retribution Validation revenge rant scream hate encourage love right wrong endlessly debate question right answer instead living present create peaceful future Instead making ‘now’ good place word action continue revive relive history taking offence action predecessor ultimately recreating taking vengeance look part bring history back life take selfjustified revenge people generation one personally persecuted u ask let event happened hundred year ago dictate live life today People ancestor u Let u love hate make child pay sin father teach child better way instead Live Learn live learn learn live usually learn mistake also take note learn mistake u Learn see — first second hand — product need change order u ensure better outcome Woman’s Unpopular Opinion thought may shared many it’s hope least shared mind concept quite simple least simple one race humankind one home planet earth planet create therefore ignorantly chosen continue choose segregation repeatedly chosen divide conquer argue discovered fight land put name plant flag fight mistreat home disregard arrogance hatred unspeakable violence unity division War peace judge hate appear different u accept love embrace undeniable beauty diversity individuality History proven time real winner war yet choose continue destructive path paved came u choose expand divide Real humanity know colour Knows language love know judgement Humanity inclusive completely Regardless whether believe one God many Whether far left far right Whether skin made light dark pigment pigment Whether love men woman neither history destroyed humanity rebuild duty human go forth unity love one guide bleed red turn light look sameTags Society Life Conflict History Change
2,851
Organizing as an Indie
Shaping an Idea I started off using a mind-mapping tool as everyone thinks of them. That starting bubble, just one or two words that sum up the app. It usually gets changed to the app name later, but for now, you need that title to identify this mind map. A few I’ve used for apps are Countdown, Timer, Shopping List, and Barcodes. Even though you don’t know what apps they became, you know a little of what they are for already. From that initial bubble, it’s easy to just start adding every random thought that comes into your head that you want to capture, which mind-mapping tools are designed to handle well. With that said, I do like to add a very minimal starting structure. I add three nodes immediately: Purpose, Technical, and Design. These will later be split into more nodes, but at this point, my mind is flitting between these aspects, so I need to group things very loosely. Purpose This is where the idea of the app is formed. They are either statements or multiple nodes in a question-and-answer format. That way, as I progress, I can add more answers. None are right — they are all options at this stage. I also chain nodes to back up a statement, which can often lead to questioning that statement later. Nodes here will often become technical items or user stories that you can either move from purpose or link to, depending on whether the idea is fully formed. Technical As you start defining the purpose of your app and sometimes the design, you’ll start running into things you’ve never done technically. Add them here. You’re building your research list for later and getting that worry about how hard something is out of your head. Design Like the technical node, this is a holding area to quickly get thoughts out of your head, allowing you to revisit them and probably iterate on your previous thoughts. Design, for me, covers everything on how I want to present the app. I always start with Name and Icon, which are usually the last things to get finalized, but as the app progresses, new ideas keep occurring. I’ll also start capturing thoughts on how I want the app to look, which is usually heavily influenced by the latest trends and anything I haven’t done before, so it will be nav bars, tab views, single screen. It inevitably won’t stick as the purpose and technical aspects evolve, but again, the idea is to stop dwelling on this irrelevant thought now and comforting yourself that it won’t be forgotten. The start of an idea After a few minutes, you’ll get a mind map you can start fleshing out with more and more detail until you are ready to create actionable items: Photo by the author. Every mind-mapping tool gives options to style things as much as you want, changing node shapes, colors, adding images. If it helps to add visual clues to where your thoughts are going, do so. I tend to stick to the default formatting applied. For some really big topics, I will add an icon to make it easy to identify later.
https://medium.com/better-programming/organizing-yourself-as-an-indie-developer-a7cabdcafd44
['Andrew Jackson']
2020-10-15 16:25:03.718000+00:00
['Software Development', 'Startup', 'Indy', 'Productivity', 'Programming']
Title Organizing IndieContent Shaping Idea started using mindmapping tool everyone think starting bubble one two word sum app usually get changed app name later need title identify mind map I’ve used apps Countdown Timer Shopping List Barcodes Even though don’t know apps became know little already initial bubble it’s easy start adding every random thought come head want capture mindmapping tool designed handle well said like add minimal starting structure add three node immediately Purpose Technical Design later split node point mind flitting aspect need group thing loosely Purpose idea app formed either statement multiple node questionandanswer format way progress add answer None right — option stage also chain node back statement often lead questioning statement later Nodes often become technical item user story either move purpose link depending whether idea fully formed Technical start defining purpose app sometimes design you’ll start running thing you’ve never done technically Add You’re building research list later getting worry hard something head Design Like technical node holding area quickly get thought head allowing revisit probably iterate previous thought Design cover everything want present app always start Name Icon usually last thing get finalized app progress new idea keep occurring I’ll also start capturing thought want app look usually heavily influenced latest trend anything haven’t done nav bar tab view single screen inevitably won’t stick purpose technical aspect evolve idea stop dwelling irrelevant thought comforting won’t forgotten start idea minute you’ll get mind map start fleshing detail ready create actionable item Photo author Every mindmapping tool give option style thing much want changing node shape color adding image help add visual clue thought going tend stick default formatting applied really big topic add icon make easy identify laterTags Software Development Startup Indy Productivity Programming
2,852
All you need is mobx-react-lite
What about bundle size? Using lightweight packages alternatives is a great way to reduce the final bundle size. And we can do that with many packages. Remember using Moment.js? I don’t recall using it for a while because it has a way bigger bundle size that the alternative Date-fns package. Even tho the Moment still has twice more downloads and stars. Mobx-react-lite is a lightweight binding to glue Mobx stores and functional React components. And the size of it is smaller, but maybe not as much as you would expect. Nevertheless — this is all we need. Let’s get started We will need a React project setup and two dependencies to get started: yarn add mobx mobx-react-lite OR npm install mobx mobx-react-lite For a simple example, we can create a Counter Store with some actions and values. I’m using Typescript with the feature enabled to support decorators syntax, but it does not matter if you are using decorators or functions for our case. In order to access the store from the component we will need to create the instance of the store and, of course, share it in some way with components. React Context is a quite good fit for this task and we can leverage it for our needs. Let’s create a stores.ts file with the store instances and Context wrapper. Good. Now we have a stores variable to which we can save instances of the Mobx stores. We freeze the object in order to avoid any unexpected changes in it. But, of course, this is an optional step. We created a React Context based on the store’s variables, and also created a Stores Provider component, we will use it shortly. Now, let’s update the root index.tsx file with a Context Provider wrapper. Follow this code snippet. Very well. At this point, we have a place, where we keep our stores. We also have a way to share the stores with the components, but not completely. To access that context we have to create two custom and quite handy hooks. One will return all stores, another — specific store of preference. Alright, now we have it. See that weird type definition for the useStore hook? It would give us proper types for the passed store key. <T extends keyof typeof stores> (store: T): typeof stores[T] We will only accept store variable type if it’s one of the keys of the stores object. So, in our case, it will only accept a counterStore string and will return the corresponding type of the given store. Nice, isn’t it? Ok, let’s finally access the store, its methods, and properties from the actual component. To do that we have to modify App.tsx file with the custom hooks and Mobx Observer wrapper. We access the counter store with it’s key and get the store in return. Also, we have to wrap the component into the observer function to allow the component to listen for the store changes. But still, we do not destruct stores. const counterStore = useStore("counterStore"); Counter App demo The app is working as expected, cool! Let’s see the TypeScript hints that we got from this setup and the ways it will cover our back from doing wrong things. The first thing to mention is the code completion feature. When we will add the useStore hook and start passing a string there as an argument — a key hint will be shown. We also will not be able to pass non-existing store keys. Nice! TypeScript hint TypeScript warning This also works for the case when we have multiple stores as well. We can access them with a separate useStore hook or with a useStores hook as well. Check this out. TypeScript hint for multiple options Testing Sure thing we need to test this. In this article, we won’t make tests for the store itself, since this is a topic of a different nature. I find it easy enough to use Jest alongside with React Testing Library. So, let’s add the necessary dependencies. yarn add @testing-library/react-hooks react-test-renderer -D OR npm install @testing-library/react-hooks react-test-renderer --save-dev Cool! Now we can start testing our hooks file. Nothing too fancy here, but still necessary. Hooks file tests results How about component tests? To do that we will need a few more dependencies. To test the components and to perform user events. yarn add @testing-library/react @testing-library/user-event -D OR npm install @testing -library/react @testing-library/user-event --save-dev Good! Let’s test the components now. We can mock the useStore hook to always return a specific store using Jest. And, we can be type-safe with a few extra lines of code. For every test we want the hook to return a new store. But, for one of the tests, we will change that slightly and replace the initial value of the counter. Check this code snippet. App file tests results Quite simple, isn’t it? Yep! And we got a green light as well! Summary Mobx-react-lite is actually all I need in my personal projects. Would this be your choice of favor as well? Let me know in the comments below 😉. The entire project is available on the GitHub link. Thanks for reading this topic!
https://medium.com/javascript-in-plain-english/all-you-need-is-mobx-react-lite-47ba0e95e9c8
['Bogdan Birdie']
2020-09-24 07:16:02.631000+00:00
['JavaScript', 'Mobx', 'Web Development', 'Typescript', 'React']
Title need mobxreactliteContent bundle size Using lightweight package alternative great way reduce final bundle size many package Remember using Momentjs don’t recall using way bigger bundle size alternative Datefns package Even tho Moment still twice downloads star Mobxreactlite lightweight binding glue Mobx store functional React component size smaller maybe much would expect Nevertheless — need Let’s get started need React project setup two dependency get started yarn add mobx mobxreactlite npm install mobx mobxreactlite simple example create Counter Store action value I’m using Typescript feature enabled support decorator syntax matter using decorator function case order access store component need create instance store course share way component React Context quite good fit task leverage need Let’s create storests file store instance Context wrapper Good store variable save instance Mobx store freeze object order avoid unexpected change course optional step created React Context based store’s variable also created Stores Provider component use shortly let’s update root indextsx file Context Provider wrapper Follow code snippet well point place keep store also way share store component completely access context create two custom quite handy hook One return store another — specific store preference Alright See weird type definition useStore hook would give u proper type passed store key extends keyof typeof store store typeof storesT accept store variable type it’s one key store object case accept counterStore string return corresponding type given store Nice isn’t Ok let’s finally access store method property actual component modify Apptsx file custom hook Mobx Observer wrapper access counter store it’s key get store return Also wrap component observer function allow component listen store change still destruct store const counterStore useStorecounterStore Counter App demo app working expected cool Let’s see TypeScript hint got setup way cover back wrong thing first thing mention code completion feature add useStore hook start passing string argument — key hint shown also able pas nonexisting store key Nice TypeScript hint TypeScript warning also work case multiple store well access separate useStore hook useStores hook well Check TypeScript hint multiple option Testing Sure thing need test article won’t make test store since topic different nature find easy enough use Jest alongside React Testing Library let’s add necessary dependency yarn add testinglibraryreacthooks reacttestrenderer npm install testinglibraryreacthooks reacttestrenderer savedev Cool start testing hook file Nothing fancy still necessary Hooks file test result component test need dependency test component perform user event yarn add testinglibraryreact testinglibraryuserevent npm install testing libraryreact testinglibraryuserevent savedev Good Let’s test component mock useStore hook always return specific store using Jest typesafe extra line code every test want hook return new store one test change slightly replace initial value counter Check code snippet App file test result Quite simple isn’t Yep got green light well Summary Mobxreactlite actually need personal project Would choice favor well Let know comment 😉 entire project available GitHub link Thanks reading topicTags JavaScript Mobx Web Development Typescript React
2,853
Why Risk Innovation is critical to the futures we aspire to
Why Risk Innovation is critical to the futures we aspire to If there’s one thing we cannot escape as we look to the future, it’s risk. An entrepreneur uses the risk innovation planner to navigate orphan risks Risk is inevitable in a universe where past “causes” connect in complex and often unpredictable ways with future “effects,” and every action we take leads to reactions that are detrimental to someone in some way. And just to make things harder, the sheer complexity, the interconnectedness, and the technological capabilities of today’s society, vastly amplify the uncertainty surrounding present-day actions and future consequences. As a result, if we’re to thrive in the future, we need to get a better handle on risk and how we think about it. The consequences of not doing so, ironically, are that our outmoded ideas about risk actually become a risk in themselves and threaten the future we aspire to. Thinking Differently About Risk This need to think differently about risk underpins the Risk Innovation Nexus at ASU — an initiative committed to connecting ethical and responsible innovation with value growth. The seeds of the ASU Risk Innovation Nexus were planted several years ago, while I was working with entrepreneurial students at the University of Michigan. Faced with a bewilderingly complex landscape around emerging and hard to grapple with risks — many of them social and political in nature — it was clear that entrepreneurially minded creators of the future needed a completely new risk toolkit if they were to not just succeed, but succeed in a way that that was a win-win for them and society more broadly. However, it wasn’t until 2016 that the ASU Idea Enterprise provided the opportunity to transform these seeds into a flourishing enterprise. With the encouragement of the Idea Enterprise and the support of Entrepreneurship + Innovation at ASU, we launched the Risk Innovation Accelerator in 2017 with the aim of providing time and resource-constrained entrepreneurs and others with a unique toolkit for navigating what we came to call ”orphan risks” — those hard to quantify and easy to ignore risks that nevertheless have a habit of coming back to bite. Orphan risks making up the Risk Innovation Nexus risk landscape Working at the Nexus of Entrepreneurship and Social Value Creation In 2019 we changed our name to the Risk Innovation Nexus, reflecting the evolving nature of our approaches that empower anyone working at the nexus of entrepreneurship and social value creation in a rapidly changing world. And with it, we began to see those initial seeds transformed into a powerful array of tools and resources that uniquely support entrepreneurial success. This phase of the Nexus is coming to an end as our initial seed funding wraps up. The good news though is that the tools and resources our fantastic team has produced will continue to be freely available to anyone looking to succeed in today’s complex world. Of course I may be a little biased here as the Nexus is near and dear to my heart, but working in the thick of technology innovation within an increasingly complex social, environmental and geopolitical landscape, I cannot emphasize enough how important these tools and resources are. One of the traits of complex, non-linear systems is that they look as if they are thriving, until seemingly-insignificant and often overlooked events lead catastrophic failures. And an important part of building resilience is having the ability to identify and navigate around risks that are hard to quantify, and because of this are often discounted, and yet can mean the difference between success and failure. Developing a Risk Innovation Mindset This is where a risk innovation mindset is critical–not just for entrepreneurs, but for anyone striving to build a better future. And it’s also why it’s central to the work of a college that is founded on opening up pathways to better futures. As we wrap up this phase of the Nexus, please do check out the resources below:
https://medium.com/edge-of-innovation/why-risk-innovation-is-critical-to-the-futures-we-aspire-to-a4ec96ef7516
['Andrew Maynard']
2020-11-05 15:39:47.498000+00:00
['Innovation', 'Entrepreneurship', 'Risk', 'Future', 'Responsible Innovation']
Title Risk Innovation critical future aspire toContent Risk Innovation critical future aspire there’s one thing cannot escape look future it’s risk entrepreneur us risk innovation planner navigate orphan risk Risk inevitable universe past “causes” connect complex often unpredictable way future “effects” every action take lead reaction detrimental someone way make thing harder sheer complexity interconnectedness technological capability today’s society vastly amplify uncertainty surrounding presentday action future consequence result we’re thrive future need get better handle risk think consequence ironically outmoded idea risk actually become risk threaten future aspire Thinking Differently Risk need think differently risk underpins Risk Innovation Nexus ASU — initiative committed connecting ethical responsible innovation value growth seed ASU Risk Innovation Nexus planted several year ago working entrepreneurial student University Michigan Faced bewilderingly complex landscape around emerging hard grapple risk — many social political nature — clear entrepreneurially minded creator future needed completely new risk toolkit succeed succeed way winwin society broadly However wasn’t 2016 ASU Idea Enterprise provided opportunity transform seed flourishing enterprise encouragement Idea Enterprise support Entrepreneurship Innovation ASU launched Risk Innovation Accelerator 2017 aim providing time resourceconstrained entrepreneur others unique toolkit navigating came call ”orphan risks” — hard quantify easy ignore risk nevertheless habit coming back bite Orphan risk making Risk Innovation Nexus risk landscape Working Nexus Entrepreneurship Social Value Creation 2019 changed name Risk Innovation Nexus reflecting evolving nature approach empower anyone working nexus entrepreneurship social value creation rapidly changing world began see initial seed transformed powerful array tool resource uniquely support entrepreneurial success phase Nexus coming end initial seed funding wrap good news though tool resource fantastic team produced continue freely available anyone looking succeed today’s complex world course may little biased Nexus near dear heart working thick technology innovation within increasingly complex social environmental geopolitical landscape cannot emphasize enough important tool resource One trait complex nonlinear system look thriving seeminglyinsignificant often overlooked event lead catastrophic failure important part building resilience ability identify navigate around risk hard quantify often discounted yet mean difference success failure Developing Risk Innovation Mindset risk innovation mindset critical–not entrepreneur anyone striving build better future it’s also it’s central work college founded opening pathway better future wrap phase Nexus please check resource belowTags Innovation Entrepreneurship Risk Future Responsible Innovation
2,854
A Better Note-Taking System for Your Scattered Brain
A Better Note-Taking System for Your Scattered Brain ‘Four Mind Banks’ can help you process information in a simple, engaging way Photo: David Travis via Unsplash I recently started a new job, and I’m in that phase where I’m constantly bombarded with new and unfamiliar concepts, from company vocabulary to industry know-how. The learning curve is steep. At every meeting, I take furious notes, trying to soak in as much information as possible. For a while, I tried the bullet journal system of note-taking, in which you use icons to label the nature of every single bullet point you write down. While it’s a creative way to mark your thoughts, I found that it becomes difficult to quickly label all the different patterns when you’re faced with heaps of new information. People talk fast. Slides move from one to the next at lightning speed. You don’t have time for labels — you’re simply trying to keep up. During meetings, I realized that four things were happening in my mind: I was gaining new information. I was coming across things I wanted to gain further clarity or dig deeper on. I was coming up with ideas and insights. I was having strong feelings about certain issues. And so I came up with a framework to capture these different notes and thoughts in a way that allows me to easily return to them later on. I call it the Four Mind Banks system. How it works: Create four “mind banks” in your notes. You can either divide a sheet of paper into four quadrants or divide your notebook into four sections. (If you go with the latter, it helps to add tabs to your notebook so you can swiftly switch from section to section.) Every note you take goes into one of the banks: 🤓 The minutes bank This is where you put important discussion points, new concepts, factual information, quotes, and key takeaways. ❓The question bank This is for the things you either don’t understand or want to learn more about. If there’s a Q&A portion of the meeting, you can refer to this bank. If not, you can dive deeper into the questions on your own time. 💡The idea bank This is for those lightbulb moments: Maybe you have an idea for a new project or a thought about how a certain process can be streamlined. It’s important that you don’t let these ideas escape you, no matter how small or raw they might be. 😳 The reaction bank This is for emotions and reactions. We are human beings, not robots that automatically absorb any information presented to us. Feeling is part of the processing. Our reactions and triggers help us to make sense of information, form opinions and convictions, and add value to the discussion. The notes we take aren’t just bits of new information. They’re breeding grounds for curiosity, creativity, and natural human responses. This system has helped me to process all the information I’m receiving in my meetings in a more effective and engaging way. My brain loves compartmentalizing things. You can use this system not just with meetings, but in any area of work or life. Try it for yourself. It’s like a filing cabinet for your brain — one that stores what you need for whenever you need it.
https://forge.medium.com/a-better-note-taking-system-for-your-scattered-brain-a65a398bd1f4
['Ria Tagulinao']
2020-10-14 15:26:57.483000+00:00
['Notes', 'Productivity', 'Brain', 'Work', 'Lifestyle']
Title Better NoteTaking System Scattered BrainContent Better NoteTaking System Scattered Brain ‘Four Mind Banks’ help process information simple engaging way Photo David Travis via Unsplash recently started new job I’m phase I’m constantly bombarded new unfamiliar concept company vocabulary industry knowhow learning curve steep every meeting take furious note trying soak much information possible tried bullet journal system notetaking use icon label nature every single bullet point write it’s creative way mark thought found becomes difficult quickly label different pattern you’re faced heap new information People talk fast Slides move one next lightning speed don’t time label — you’re simply trying keep meeting realized four thing happening mind gaining new information coming across thing wanted gain clarity dig deeper coming idea insight strong feeling certain issue came framework capture different note thought way allows easily return later call Four Mind Banks system work Create four “mind banks” note either divide sheet paper four quadrant divide notebook four section go latter help add tab notebook swiftly switch section section Every note take go one bank 🤓 minute bank put important discussion point new concept factual information quote key takeaway ❓The question bank thing either don’t understand want learn there’s QA portion meeting refer bank dive deeper question time 💡The idea bank lightbulb moment Maybe idea new project thought certain process streamlined It’s important don’t let idea escape matter small raw might 😳 reaction bank emotion reaction human being robot automatically absorb information presented u Feeling part processing reaction trigger help u make sense information form opinion conviction add value discussion note take aren’t bit new information They’re breeding ground curiosity creativity natural human response system helped process information I’m receiving meeting effective engaging way brain love compartmentalizing thing use system meeting area work life Try It’s like filing cabinet brain — one store need whenever need itTags Notes Productivity Brain Work Lifestyle
2,855
Your Code Should Read Like a Book
Your Code Should Read Like a Book It makes life easier for everyone involved Photo by Fabian Grohs on Unsplash There’s a pandemic among programmers. Long functions, broad and nondescriptive names for functions, classes, and variable names, overly commented code, disorganized structure, and a lack of overall streamlined flow. It’s much too often that I take a peek at someone else’s working code just to notice that I have to exert a strenuous amount of effort just to understand what it does in the first place. I have to try my best to reason about ambiguous variable names such as i, k, num, counter, etc. What type of num are we representing, and what is the purpose of the operations that surround it? What is the purpose of the counter? What is it tracking? Why is it there? I have to constantly jump all over the class to see how each function builds on top of the other functions around it, just to realize that the names of each function don’t really tell me anything about what the function does. I’d even have to sometimes read paragraphs of comments that explain the purpose of what a function might do, but still, I shouldn’t have to be reading an essay to simply understand what a function does. I should be able to reason about this simply by taking a quick glance at the function. Your code should read like a book. Just how a book is structured through paragraphs and chapters that follow a descriptive story that flows in a streamlined and progressive fashion, your code should be structured and designed in a way that I can enter into a class and be able to understand its purpose within moments of engagement. Please don’t make any developer, including yourself, who is looking at your code have to embody Sherlock Holmes in order to deduce the purpose and meaning behind what you wrote. What exactly should you do?
https://medium.com/better-programming/your-code-should-read-like-a-book-873b27f71fe5
['Zachary Minott']
2020-08-07 17:50:41.776000+00:00
['Programming', 'Software Development', 'Clean Code', 'Software Engineering', 'Startup']
Title Code Read Like BookContent Code Read Like Book make life easier everyone involved Photo Fabian Grohs Unsplash There’s pandemic among programmer Long function broad nondescriptive name function class variable name overly commented code disorganized structure lack overall streamlined flow It’s much often take peek someone else’s working code notice exert strenuous amount effort understand first place try best reason ambiguous variable name k num counter etc type num representing purpose operation surround purpose counter tracking constantly jump class see function build top function around realize name function don’t really tell anything function I’d even sometimes read paragraph comment explain purpose function might still shouldn’t reading essay simply understand function able reason simply taking quick glance function code read like book book structured paragraph chapter follow descriptive story flow streamlined progressive fashion code structured designed way enter class able understand purpose within moment engagement Please don’t make developer including looking code embody Sherlock Holmes order deduce purpose meaning behind wrote exactly doTags Programming Software Development Clean Code Software Engineering Startup
2,856
Where Did Tom, the Founder of Myspace, Bizarrely Vanish To?
Where Did Tom, the Founder of Myspace, Bizarrely Vanish To? This is what happens when the concept of money is removed from your life. Image Credit: Pedestrian/gettyimages “Myspace changed my life,” said no one. Well, it changed mine. I was an unknown musician looking for an audience. I set up a Myspace account. My first friend was this weird guy called Tom. Tom looked freaking happy and he was the co-founder of the site. He looked like someone that could actually be my friend. I was a Myspace prostitute. I made friends with everybody. Myspace was where I published the remixes I created and played in nightclubs as a DJ. Unfortunately, Myspace didn’t make me a successful musician. I didn’t go viral with my Fleetwood Mac remix while holding a bottle of cranberry juice. Myspace was fun though. It’s where I met one of my best friends. He randomly messaged me and asked to talk about my music. I met up with him, and his record label ended up publishing all of my electronic dance tracks to sites like Beatport. Without Myspace I would never have become a musician signed to two record labels. The experience on Myspace later became my foundation and apprenticeship for how to write on the internet. The online assistance from Myspace wasn’t enough. I didn’t know it at the time, but I was suffering from extreme mental illness. Practically speaking, this meant when I went to go on stage and play my set I’d feel physically sick. It took me hours to prepare for the nerve-racking battle that I faced every night. I loved playing to an audience. What made no sense was my body’s response to my hobby. After a while the stress of mental illness became too much. I gave up DJing and stopped using Myspace. It’s been years since my experience with Myspace, although my account is still very much alive (see here for a laugh). Screenshot by me (2020). From Hollywood celebs, to nightclubs, to mixtape cds, to strange long hair…haha The other day I thought to myself where the heck did Tom from Myspace end up? The answer surprised me, given he is now 50, which is hard to believe. You might be curious too and there’s an awesome lesson in it for you. The historical importance of Myspace Myspace was significant because it accidentally paved the way for creative people to release their work into the world without owning a website. Tom made this happen by mistake and it was a happy accident. Myspace created the social media category of apps. Without Myspace we may never of had Facebook, LinkedIn, Twitter or Instagram. Tom started Myspace in 2003 with Chris DeWolfe. Myspace got eaten for breakfast by Facebook in 2008. The company eventually pivoted to serving musicians solely. They lost their identity and their mojo. Nobody knew what Myspace was anymore. Now, only people who want to walk through a time warp (like me) visit the site. Myspace helped the internet unleash its creativity, and that’s historically important regardless of how things ended up. This is what Myspace Tom is doing now. Myspace was sold in 2005 for $580 million. Tom walked away from the experiment a rich human. He attempted to stay on for a few years at the company, but became frustrated with endless meetings and the inability for anybody to make a decision. He dabbled with a few adviser roles. Then, in 2009 he retired. Since then most people have no idea what happened to him. Here’s what he said about the concept of retirement: I’ll never say ‘never’ because, more than anything, I like the idea that anything can happen. I don’t know exactly where my life will lead. Adventure and the unknown has always been appealing to me. Tom was going to travel the world and do nothing. In 2011 Tom visited the Burning Man festival and became inspired by photography, thanks to his friend Troy Ratcliff. “I’m not necessarily trying to represent nature exactly. I’m trying to make something beautiful like a painter would,” says Tom. Now Tom travels the world as a photographer. He doesn’t make a dollar from his art and that’s intentional. All of his photographs can be found on Instagram. “I haven’t wanted to take commissions or sell my photos, or do anything commercial with it — that would just feel like work, which I don’t want to do.” Tom lives an odd life. It reminds me of the Humans of New York founder, Brandon Stanton. Brandon left behind a high-profile job in finance to take photos of everyday people in the street. He said in an interview “I’d go out some days and ten people in a row would make me feel like I’m some sort of freak. ‘No you can’t take my photo — get out of here!’ There were days when I couldn’t do it anymore and would go home and lay in bed.” Brandon burst into tears after sharing that experience. The rejection was overwhelming. What saved him was this: The act of doing his passion rather than thinking about it. Doing creative work for the sake of it is a deeply fulfilling and odd experience. It’s worth you experimenting with like Tom and Brandon have. What you can learn from Myspace Tom Okay, so you may not be retiring on hundreds of millions of dollars. What Tom can teach you about life through his experience is still powerful. Time is worth more than money. “I’ll pay a lot to not waste time. Time is the most important thing to me — how can you do all the things you want to do with such limited time. … I’m hoping the science of life extension makes progress.” The purpose of retirement is not to quit work. It’s to quit the type of work you have to do for money, so you can do whatever work you want and not need to stress about how much it pays. Retire from work you do for money as soon as you can. Buy back your time. Buying stuff forces you to work longer for money. Dumb meetings and indecision aren’t worth it. It forced Tom to walk away from corporate life. Tom likes to build stuff and explore his creative passions. It’s hard to make progress when you’ve got a corporate giant molding you for their exploitation and benefit. Real passion keeps you going. You might think having loads of money and retiring like Tom is a dream. The problem with retirement and loads of money is it gets boring. $580 million will make you happy for a few months, not a lifetime. Tom figured this out the hard way. He says his passion for photography keeps him traveling. I reckon that’s a lie. His passion for photography keeps him alive and away from doing enormous amounts of coke and gambling at casinos every day. When money is taken care of, work changes its meaning. If you’re not intentional about that meaning, then you’ll end up having a new meaning written for you which may not be consistent with living a good life.
https://medium.com/the-ascent/where-did-tom-the-founder-of-myspace-bizarrely-vanish-to-a4ddb3ef50d9
['Tim Denning']
2020-12-14 16:00:09.551000+00:00
['Creativity', 'Mental Health', 'Social Media', 'Money', 'Work']
Title Tom Founder Myspace Bizarrely Vanish ToContent Tom Founder Myspace Bizarrely Vanish happens concept money removed life Image Credit Pedestriangettyimages “Myspace changed life” said one Well changed mine unknown musician looking audience set Myspace account first friend weird guy called Tom Tom looked freaking happy cofounder site looked like someone could actually friend Myspace prostitute made friend everybody Myspace published remixes created played nightclub DJ Unfortunately Myspace didn’t make successful musician didn’t go viral Fleetwood Mac remix holding bottle cranberry juice Myspace fun though It’s met one best friend randomly messaged asked talk music met record label ended publishing electronic dance track site like Beatport Without Myspace would never become musician signed two record label experience Myspace later became foundation apprenticeship write internet online assistance Myspace wasn’t enough didn’t know time suffering extreme mental illness Practically speaking meant went go stage play set I’d feel physically sick took hour prepare nerveracking battle faced every night loved playing audience made sense body’s response hobby stress mental illness became much gave DJing stopped using Myspace It’s year since experience Myspace although account still much alive see laugh Screenshot 2020 Hollywood celebs nightclub mixtape cd strange long hair…haha day thought heck Tom Myspace end answer surprised given 50 hard believe might curious there’s awesome lesson historical importance Myspace Myspace significant accidentally paved way creative people release work world without owning website Tom made happen mistake happy accident Myspace created social medium category apps Without Myspace may never Facebook LinkedIn Twitter Instagram Tom started Myspace 2003 Chris DeWolfe Myspace got eaten breakfast Facebook 2008 company eventually pivoted serving musician solely lost identity mojo Nobody knew Myspace anymore people want walk time warp like visit site Myspace helped internet unleash creativity that’s historically important regardless thing ended Myspace Tom Myspace sold 2005 580 million Tom walked away experiment rich human attempted stay year company became frustrated endless meeting inability anybody make decision dabbled adviser role 2009 retired Since people idea happened Here’s said concept retirement I’ll never say ‘never’ anything like idea anything happen don’t know exactly life lead Adventure unknown always appealing Tom going travel world nothing 2011 Tom visited Burning Man festival became inspired photography thanks friend Troy Ratcliff “I’m necessarily trying represent nature exactly I’m trying make something beautiful like painter would” say Tom Tom travel world photographer doesn’t make dollar art that’s intentional photograph found Instagram “I haven’t wanted take commission sell photo anything commercial — would feel like work don’t want do” Tom life odd life reminds Humans New York founder Brandon Stanton Brandon left behind highprofile job finance take photo everyday people street said interview “I’d go day ten people row would make feel like I’m sort freak ‘No can’t take photo — get here’ day couldn’t anymore would go home lay bed” Brandon burst tear sharing experience rejection overwhelming saved act passion rather thinking creative work sake deeply fulfilling odd experience It’s worth experimenting like Tom Brandon learn Myspace Tom Okay may retiring hundred million dollar Tom teach life experience still powerful Time worth money “I’ll pay lot waste time Time important thing — thing want limited time … I’m hoping science life extension make progress” purpose retirement quit work It’s quit type work money whatever work want need stress much pay Retire work money soon Buy back time Buying stuff force work longer money Dumb meeting indecision aren’t worth forced Tom walk away corporate life Tom like build stuff explore creative passion It’s hard make progress you’ve got corporate giant molding exploitation benefit Real passion keep going might think load money retiring like Tom dream problem retirement load money get boring 580 million make happy month lifetime Tom figured hard way say passion photography keep traveling reckon that’s lie passion photography keep alive away enormous amount coke gambling casino every day money taken care work change meaning you’re intentional meaning you’ll end new meaning written may consistent living good lifeTags Creativity Mental Health Social Media Money Work
2,857
Whatever Happened to the Heroes? Punk, Trotsky, Che Chic and the consumption of revolutionary icons
Wandering down steaming ramen shopping alleys from Tokyo’s Koenji to Ueno in the mid-aughts, I was overcome by the ubiquity of Che Guevara’s image on t-shirts in cheap military gear and punk shops. In the suburbs of Saitama, his likeness also punctuated the crowded roads lined by Marui and Seibu department stores. The irony of Marxist iconography being commodified is well known, but I couldn’t help feel perplexed with Che’s presence in a culture more conformist than my ganga-infused, DIY, punk East Vancouver home city where Che shirts seemed a right of passage, once upon a time. This is not to say the image of Che belongs any more in Vancouver. In fact, the appropriateness of using his image to signify revolution at all should be called into question given his thirst for murder and his homophobia. But how does the imported icon of Che Guevara relate to the logo worship of Kitty-chan and brand fetishism of Louis Vuitton in Japan? Especially with emerging trend of uniformity of no logo in brands like Muji and Uniclo. In my hometown, I have always wondered why and how icons of revolution project the views of wearers. Is it earnest social consciousness with awareness of the history behind the image? Irony? Naive rebelliousness? Further, why do we need to import our heroes and do those heroes signify truly subversive revolution? The Stranglers song “No More Heroes” mourns the lack of sufficient revolutionary representatives by asking “whatever happened to Leon Trotsky…” a Marxist ledgend listed among several famous figures such as Lenin and Shakespeare. The 1977 punk song, as well as the punk movement, seemed to sense an absence of contemporary examples as it sought to cleave itself from the mainstream. Indeed, of cultural and ideological movements such as Literature, Trotsky argues continutiy of literary expression is dialectical and a series of reactions to and from which it is trying to break. The foundation of Punk was a break from the reliance on old, conservative forms that were less relevant to an increasingly restless urban culture. If one were to align punk with Trotsky’s idealized proletariat, the revolutionary individual is one who changes culture and history by seizing and modifying it. But wearing a mass-produced Che shirt feebly hints at the wearer’s rebelliousness. Even worn in sincerity, the ubiquity of the image alone has deadened the meaning. In most cases, the emergence of what Newsweek called “Che Chic” seems a non-revolutionary act of consumerism. “No More Hereos” cites other famous figures such as Elmyr de Hory, famous for forging great paintings and it seems ironic that the Stranglers exalt a copyist, but I believe it references de Hory’s ability to master the art of copying and undermine the legitimacy of the original paintings. Furthermore, the song “No More Heroes” itself became embattled in copyright litigation a few decades later against Elastica’s too-familiar sounding “Waking up” echoing the tenous legitimacy of original, revolutionary art. The key point of contention is whether or not the wearer of any pop or cult image is fully aware of the history of the signs they use. In the postmodern, capitalist exchange of icons and logos, the individual is too often worn by the logo. (I marvel, for instance at the prevalence of Disney paraphernalia and its cult of innocence in Japan, despite the company’s historical use of characters as Japanese stereotypes in anti-Japanese WWII propaganda). One can be a chameleon without much accountability to the idea from which the image or cultural use emerged. This is as potentially liberating, as it is a meaningless repetition of mass culture. The rift between images and their origins allows us to use them in a way that can potentially challenge long-stale stereotypes or challenge rigid meaning to make it dialectical. It is not a given that the image of Che is one we should revere, given the accounts of his less-celebrated brutality. My excursions to Tokyo’s goth Mecca, Harajuku as both spectator and spectacle confirms that repetition of subculture can turn into a completely different expression from some of the same inspiration. A subculture like Goth in Japan is multiply-removed from one of its iterations via late 70s punk in the UK, yet is uniquely expressive of youth culture in its colourful Japanese interpretation, which itself has now been (mis)appropriated by North American pop idols. But does Guevara, transfigured to a silk-screened face, long-since separated from the contested history of the “hero” himself, a hint of global consciousness? The rash of Che paraphernalia became popular in the 1960's and more recently spawned by the popular film The Motorcycle Diaries. Che Chic does not seem to capture the revolutionary spirit it had in the past because his image has been generally resurrected through consumerism and fashion, rather than ideological means. He has been donned by everyone from celebrities to left-wing college idealists. Is it possible to be aware of the irony, dismissing the claim that image never had authentic meaning? I am aware of my own hypocrisy here purchasing the 150th Anniversary Communist Manifesto from a huge, Canadian retailer Chapters, instead of my local, non-profit, socialist bookstore that had a cheeky sign at one point to liberate any books they did not have in stock at one of the bookstore giants. Yet, I have also delighted in buying American soda with Che’s image on the bottle and own a tin Lenin lunchbox (barcode and all) as a playful comment on the exchange between communist ideology and capitalist reality. How can one be ironic or visibly expressive as a means to counter the mass replication and homogeneity of culture? The last few decades has brough more playful incarnations of Che, allowing for the questioning of his image and legacy. Challenging monoculture and heternormativity, Comedian Margaret Cho modeled her likeness after Che in her one-woman show Revolution, using Guevara’s icon as a new means to express multiple cultural revolutions. Cho’s appropriation may be the most subversive because the parody of Cho wearing Che calls attention to the lack of representation of women and people of colour among revolutionary icons. The only female icon on t-shirts I can think of is Rosie the Riveter, who is not only fictional, but her edginess has been lost in a deluge of blasé, retro imagery on mugs and magnets aimed at women including “wine mom”. At least more humorous play with Che’s image recently includes drag, artisitc reinterpretations and commingling with other political heroes. For instance, Obama wearing a Che shirt wearing an Obama shirt hyperbolizes casual use of political iconography including Obama’s 2008 Hope poster in an endless play of signifiers. While a conscious play with Che’s symbolic meaning gives a glimmer of hope, I question how the image of revolution is being sold or misused as part of the mass culture of the individual. Revolution, transgression and anti-conformity can all be worn, but do they challenge or repeat? In a tacit responsibility for the individual to be a wearer and a thinker. We just may never know which it is until we open a dialogue about it.
https://jessicaleemcmillan.medium.com/whatever-happened-to-the-heroes-ebc3351584b3
['Jessica Lee Mcmillan']
2020-04-09 01:51:13.976000+00:00
['Tokyo', 'Nonfiction', 'Revolution', 'Che Guevara', 'Music']
Title Whatever Happened Heroes Punk Trotsky Che Chic consumption revolutionary iconsContent Wandering steaming ramen shopping alley Tokyo’s Koenji Ueno midaughts overcome ubiquity Che Guevara’s image tshirts cheap military gear punk shop suburb Saitama likeness also punctuated crowded road lined Marui Seibu department store irony Marxist iconography commodified well known couldn’t help feel perplexed Che’s presence culture conformist gangainfused DIY punk East Vancouver home city Che shirt seemed right passage upon time say image Che belongs Vancouver fact appropriateness using image signify revolution called question given thirst murder homophobia imported icon Che Guevara relate logo worship Kittychan brand fetishism Louis Vuitton Japan Especially emerging trend uniformity logo brand like Muji Uniclo hometown always wondered icon revolution project view wearer earnest social consciousness awareness history behind image Irony Naive rebelliousness need import hero hero signify truly subversive revolution Stranglers song “No Heroes” mourns lack sufficient revolutionary representative asking “whatever happened Leon Trotsky…” Marxist ledgend listed among several famous figure Lenin Shakespeare 1977 punk song well punk movement seemed sense absence contemporary example sought cleave mainstream Indeed cultural ideological movement Literature Trotsky argues continutiy literary expression dialectical series reaction trying break foundation Punk break reliance old conservative form le relevant increasingly restless urban culture one align punk Trotsky’s idealized proletariat revolutionary individual one change culture history seizing modifying wearing massproduced Che shirt feebly hint wearer’s rebelliousness Even worn sincerity ubiquity image alone deadened meaning case emergence Newsweek called “Che Chic” seems nonrevolutionary act consumerism “No Hereos” cite famous figure Elmyr de Hory famous forging great painting seems ironic Stranglers exalt copyist believe reference de Hory’s ability master art copying undermine legitimacy original painting Furthermore song “No Heroes” became embattled copyright litigation decade later Elastica’s toofamiliar sounding “Waking up” echoing tenous legitimacy original revolutionary art key point contention whether wearer pop cult image fully aware history sign use postmodern capitalist exchange icon logo individual often worn logo marvel instance prevalence Disney paraphernalia cult innocence Japan despite company’s historical use character Japanese stereotype antiJapanese WWII propaganda One chameleon without much accountability idea image cultural use emerged potentially liberating meaningless repetition mass culture rift image origin allows u use way potentially challenge longstale stereotype challenge rigid meaning make dialectical given image Che one revere given account lesscelebrated brutality excursion Tokyo’s goth Mecca Harajuku spectator spectacle confirms repetition subculture turn completely different expression inspiration subculture like Goth Japan multiplyremoved one iteration via late 70 punk UK yet uniquely expressive youth culture colourful Japanese interpretation misappropriated North American pop idol Guevara transfigured silkscreened face longsince separated contested history “hero” hint global consciousness rash Che paraphernalia became popular 1960s recently spawned popular film Motorcycle Diaries Che Chic seem capture revolutionary spirit past image generally resurrected consumerism fashion rather ideological mean donned everyone celebrity leftwing college idealist possible aware irony dismissing claim image never authentic meaning aware hypocrisy purchasing 150th Anniversary Communist Manifesto huge Canadian retailer Chapters instead local nonprofit socialist bookstore cheeky sign one point liberate book stock one bookstore giant Yet also delighted buying American soda Che’s image bottle tin Lenin lunchbox barcode playful comment exchange communist ideology capitalist reality one ironic visibly expressive mean counter mass replication homogeneity culture last decade brough playful incarnation Che allowing questioning image legacy Challenging monoculture heternormativity Comedian Margaret Cho modeled likeness Che onewoman show Revolution using Guevara’s icon new mean express multiple cultural revolution Cho’s appropriation may subversive parody Cho wearing Che call attention lack representation woman people colour among revolutionary icon female icon tshirts think Rosie Riveter fictional edginess lost deluge blasé retro imagery mug magnet aimed woman including “wine mom” least humorous play Che’s image recently includes drag artisitc reinterpretation commingling political hero instance Obama wearing Che shirt wearing Obama shirt hyperbolizes casual use political iconography including Obama’s 2008 Hope poster endless play signifier conscious play Che’s symbolic meaning give glimmer hope question image revolution sold misused part mass culture individual Revolution transgression anticonformity worn challenge repeat tacit responsibility individual wearer thinker may never know open dialogue itTags Tokyo Nonfiction Revolution Che Guevara Music
2,858
Blockchain and Artificial Intelligence
It is always exciting to keep an eye on the new and cutting edge technology that is shaping the world that we live in. What’s even better is when two of these emerging technologies are combined. Today we want to look at how blockchain technology is being combined with Artificial Intelligence. We will outline some of the projects leveraging these technologies in the crypto space. Let’s start by briefly defining these two technologies. What is Blockchain? We did an entire article recently explaining Blockchain technology. For the purpose of keeping it simple, Blockchain can be defined as follows: A blockchain is an incorruptible and decentralised digital ledger of transactions that can be programmed to record not just financial transactions but virtually anything of value. As mentioned above, Blockchain ledgers work through decentralisation. This means that there is no one central controller of the ledger. It is maintained and updated by the network. In the case of Bitcoin, the network is made up of thousands of devices all over the world. What is Artificial Intelligence? Artificial intelligence or AI , is an area of computing all around the creation of intelligent machines. Artificial Intelligence has actually been studied since the 1950’s when there was the emergence of neural networks. This was followed by machine learning techniques in the 1980’s. Today we see deep learning pushing a new boom in the Artificial Intelligence space. While there are many applications of AI for enterprise and business purposes, it is slowly engulfing much of the technology we use on a daily basis ourselves. Ride-sharing apps like Uber and Lyft utilise machine learning techniques to predict the price of your ride and minimise wait times. Your email service provider likely uses artificial intelligence to filter spam messages coming into your inbox. Google maps uses anonymised data from smartphones to update traffic statistics in real time. Plagiarism checkers use AI to scan for plagiarised content. Facebook, Snapchat and instagram all use AI for facial recognition and your favourite filters. So Artificial Intelligence is all around us. We are interacting with it on a daily basis, even though we may not even realise it. The AI Robots we see in the movies is but one form of AI we should concern ourselves with. The ways in which neural networks, machine learning and deep learning can be applied in our lives today can make our world much easier to manoeuvre. There are many projects in the cryptocurrency space trying to make this happen today. So what happens when Blockchain and AI are combined? There are some very ambitious projects in the cryptocurrency space seeking to make the best of these two technologies. Matrix AI Network Matrix AI network appears a very ambitious project on the surface. Videos on their website paint the picture of an Artificial Intelligence assistant helping us navigate nearly every facet of our daily lives. They describe themselves as an open source public intelligent Blockchain platform. They want to help bring old technology into the new world and propose to do this by utilising easily programmable smart contracts on their platform. The area where they seem to merge Artificial Intelligence into the project is through Deep Learning based code generation for smart contracts. They recognise that programming smart contracts on the likes of Ethereum requires having to read and write code. Matrix aims to leverage AI to generate smart contracts for users. Users will only need to insert basic information like input, output, and transaction conditions. Being able to write smart contracts without having a coding background will allow a much larger pool of people to use their platform. Also outlined in their white-paper is an interesting AI-enabled security and enhancement mechanism. Matrix’s built in compiler scans the smart contract code in order to try and find vulnerabilities and execution problems. It even carries out rule based checking and code revision. On top of all this they have a “deep learning based framework to discover the hidden intention of smart contracts and detect complex patterns of security vulnerabilities.” Matrix’s blockchain, coupled with the above implementations means their blockchain will learn and evolve over time. Using AI to constantly search for vulnerabilities means that it will be able to serve up better and more refined smart contract code for users over time. Potential Partners… There is also much speculation that Matrix is working closely with the Chinese government. The Chinese government are working on some huge initiatives. The resurrection of the Silk Road connecting China back across Asia to Europe is one example. Could Matrix AI have some partnerships lined up on some government ventures? It is all speculation for now. Nonetheless, Matrix AI network is a very interesting project and its implementation of AI seems very practical on the surface. If their machine learning algorithms can serve up easy to programme smart contracts this is sure to make Matrix AI network one to watch. DeepBrain Chain Deepbrain chain (DBC) is another initiative in the crypto space leveraging AI technology. They describe themselves as an Artificial Intelligence computing platform driven by Blockchain. In its whitepaper, DBC outlines a number of advantages of its platform. They focus on serving AI companies and already integrate deep learning frameworks such as TensorFlow (Google), Caffe (Facebook) and CNTK (Microsoft). While Matirix AI network runs on its own native blockchain, DeepBrain chain will release their DBC coin on NEO. They will also run the DBC Coin issuing algorithm on NEO’s smart contracts. It appears that DeepBrain Chain want to position themselves as the go to platform for AI companies. According to their whitepaper many of their benefits will stem from AI companies accessing DBC’s neural network computing power. By pooling together computing power from all over the world they say they can reduce the amount of money AI companies spend on computing power by up to 70%. They are not simply providing a decentralised supply of computing power though. DBC are also seeking to create an AI data trading platform, an AI algorithm trading platform, an AI model trading platform and much more. Where does this all lead? With the examples above, its clear that there could be some very interesting use cases for the merging of Blockchain and Artificial Intelligence. Both projects are creating initiatives that result in a form of decentralised intelligence. Leveraging elements of AI like machine learning and neural networks means that these blockchains can become more efficient and evolve over time. Add to this the ability for them to assist users in exploring and creating smart contracts and applications and it makes for a very interesting future. It is clear that AI can therefore aid us in not only creating a better user experience, but more efficient outputs in terms decision making and business performance.
https://medium.com/cryptosuss/blockchain-and-artificial-intelligence-232c4821885e
['Crypto Suss']
2018-09-17 17:30:43.910000+00:00
['Artificial Intelligence', 'Blockchain', 'Cryptocurrency', 'AI', 'Bitcoin']
Title Blockchain Artificial IntelligenceContent always exciting keep eye new cutting edge technology shaping world live What’s even better two emerging technology combined Today want look blockchain technology combined Artificial Intelligence outline project leveraging technology crypto space Let’s start briefly defining two technology Blockchain entire article recently explaining Blockchain technology purpose keeping simple Blockchain defined follows blockchain incorruptible decentralised digital ledger transaction programmed record financial transaction virtually anything value mentioned Blockchain ledger work decentralisation mean one central controller ledger maintained updated network case Bitcoin network made thousand device world Artificial Intelligence Artificial intelligence AI area computing around creation intelligent machine Artificial Intelligence actually studied since 1950’s emergence neural network followed machine learning technique 1980’s Today see deep learning pushing new boom Artificial Intelligence space many application AI enterprise business purpose slowly engulfing much technology use daily basis Ridesharing apps like Uber Lyft utilise machine learning technique predict price ride minimise wait time email service provider likely us artificial intelligence filter spam message coming inbox Google map us anonymised data smartphones update traffic statistic real time Plagiarism checker use AI scan plagiarised content Facebook Snapchat instagram use AI facial recognition favourite filter Artificial Intelligence around u interacting daily basis even though may even realise AI Robots see movie one form AI concern way neural network machine learning deep learning applied life today make world much easier manoeuvre many project cryptocurrency space trying make happen today happens Blockchain AI combined ambitious project cryptocurrency space seeking make best two technology Matrix AI Network Matrix AI network appears ambitious project surface Videos website paint picture Artificial Intelligence assistant helping u navigate nearly every facet daily life describe open source public intelligent Blockchain platform want help bring old technology new world propose utilising easily programmable smart contract platform area seem merge Artificial Intelligence project Deep Learning based code generation smart contract recognise programming smart contract like Ethereum requires read write code Matrix aim leverage AI generate smart contract user Users need insert basic information like input output transaction condition able write smart contract without coding background allow much larger pool people use platform Also outlined whitepaper interesting AIenabled security enhancement mechanism Matrix’s built compiler scan smart contract code order try find vulnerability execution problem even carry rule based checking code revision top “deep learning based framework discover hidden intention smart contract detect complex pattern security vulnerabilities” Matrix’s blockchain coupled implementation mean blockchain learn evolve time Using AI constantly search vulnerability mean able serve better refined smart contract code user time Potential Partners… also much speculation Matrix working closely Chinese government Chinese government working huge initiative resurrection Silk Road connecting China back across Asia Europe one example Could Matrix AI partnership lined government venture speculation Nonetheless Matrix AI network interesting project implementation AI seems practical surface machine learning algorithm serve easy programme smart contract sure make Matrix AI network one watch DeepBrain Chain Deepbrain chain DBC another initiative crypto space leveraging AI technology describe Artificial Intelligence computing platform driven Blockchain whitepaper DBC outline number advantage platform focus serving AI company already integrate deep learning framework TensorFlow Google Caffe Facebook CNTK Microsoft Matirix AI network run native blockchain DeepBrain chain release DBC coin NEO also run DBC Coin issuing algorithm NEO’s smart contract appears DeepBrain Chain want position go platform AI company According whitepaper many benefit stem AI company accessing DBC’s neural network computing power pooling together computing power world say reduce amount money AI company spend computing power 70 simply providing decentralised supply computing power though DBC also seeking create AI data trading platform AI algorithm trading platform AI model trading platform much lead example clear could interesting use case merging Blockchain Artificial Intelligence project creating initiative result form decentralised intelligence Leveraging element AI like machine learning neural network mean blockchains become efficient evolve time Add ability assist user exploring creating smart contract application make interesting future clear AI therefore aid u creating better user experience efficient output term decision making business performanceTags Artificial Intelligence Blockchain Cryptocurrency AI Bitcoin
2,859
Is Angular Still Alive?
Let the Stats Speak Stack Overflow Survey In this survey by Stack Overflow to find what the most loved, dreaded, and wanted web framework is, React and Vue placed first and second, respectively, in both the Loved and Wanted sections. Meanwhile, Angular placed third. As I remember it, Angular had a lead on React in those categories in 2018. NPM trends The NPM trends graph above shows us the number of downloads of each framework overs a period of time. The screenshot shows the stats over the past six months, and we can see that React clearly holds the lead with almost 9 million downloads. Vue and Angular are in a tight contest for second place. Another feature in NPM trends is that it shows the data from GitHub as well. In the screenshot below, you can see the number of forks, stars, and issues of each framework: These stats again emphasize Angular’s loss of users. Angular only has 67,000+ stars, while both Vue and React are well ahead with 158,000+ and 175,000+ stars in their GitHub repos. State of JavaScript The 2019 State of JavaScript includes another report generation platform on JavaScript, and you can find various kinds of comparisons there. The figure below shows the responses of the users, whether they will use it again or not, whether they have heard of the technology, etc. As we can see, the highest number of users are likely to use React and Vue again rather than Angular. Also, the number of users who voted “I’ve used it before, and would NOT use it again” is higher for Angular than the other two. This means Angular is losing its users rapidly.
https://medium.com/better-programming/is-angular-still-alive-4977515f4de1
['Chameera Dulanga']
2020-11-19 14:22:02.611000+00:00
['Programming', 'Angular', 'React', 'Vuejs', 'JavaScript']
Title Angular Still AliveContent Let Stats Speak Stack Overflow Survey survey Stack Overflow find loved dreaded wanted web framework React Vue placed first second respectively Loved Wanted section Meanwhile Angular placed third remember Angular lead React category 2018 NPM trend NPM trend graph show u number downloads framework over period time screenshot show stats past six month see React clearly hold lead almost 9 million downloads Vue Angular tight contest second place Another feature NPM trend show data GitHub well screenshot see number fork star issue framework stats emphasize Angular’s loss user Angular 67000 star Vue React well ahead 158000 175000 star GitHub repos State JavaScript 2019 State JavaScript includes another report generation platform JavaScript find various kind comparison figure show response user whether use whether heard technology etc see highest number user likely use React Vue rather Angular Also number user voted “I’ve used would use again” higher Angular two mean Angular losing user rapidlyTags Programming Angular React Vuejs JavaScript
2,860
Why (and when) you should use Kubernetes
Kubernetes is a powerful container management tool that automates the deployment and management of containers. Kubernetes (k8’s) is the next big wave in cloud computing and it’s easy to see why as businesses migrate their infrastructure and architecture to reflect a cloud-native, data-driven era. Getting started with Kubernetes? Try out the Practical Guide to Kubernetes and start running production grade clusters. Outlined in this post are some of the top reasons why you should use Kubernetes and when you should/shouldn’t use it. Container orchestration Containers are great. They provide you with an easy way to package and deploy services, allow for process isolation, immutability, efficient resource utilization, and are lightweight in creation. But when it comes to actually running containers in production, you can end up with dozens, even thousands of containers over time. These containers need to be deployed, managed, and connected and updated; if you were to do this manually, you’d need an entire team dedicated to this. It’s not enough to run containers; you need to be able to: Integrate and orchestrate these modular parts Scale up and scale down based on the demand Make them fault tolerant Provide communication across a cluster You might ask: aren’t containers supposed to do all that? The answer is that containers are only a low-level piece of the puzzle. The real benefits are obtained with tools that sit on top of containers — like Kubernetes. These tools are today known as container schedulers. Great for multi-cloud adoption With many of today’s businesses gearing towards microservice architecture, it’s no surprise that containers and the tools used to manage them have become so popular. Microservice architecture makes it easy to split your application into smaller components with containers that can then be run on different cloud environments, giving you the option to choose the best host for your needs. What’s great about Kubernetes is that it’s built to be used anywhere so you can deploy to public/private/hybrid clouds, enabling you to reach users where they’re at, with greater availability and security. You can see how Kubernetes can help you avoid potential hazards with “vendor lock-in”. Deploy and update applications at scale for faster time-to-market Kubernetes allows teams to keep pace with the requirements of modern software development. Without Kubernetes, large teams would have to manually script their own deployment workflows. Containers, combined with an orchestration tool, provide management of machines and services for you — improving the reliability of your application while reducing the amount of time and resources spent on DevOps. Kubernetes has some great features that allow you to deploy applications faster with scalability in mind: Horizontal infrastructure scaling: New servers can be added or removed easily. Auto-scaling: Automatically change the number of running containers, based on CPU utilization or other application-provided metrics. Manual scaling: Manually scale the number of running containers through a command or the interface. Replication controller: The replication controller makes sure your cluster has an equal amount of pods running. If there are too many pods, the replication controller terminates the extra pods. If there are too few, it starts more pods. Health checks and self-healing: Kubernetes can check the health of nodes and containers ensuring your application doesn’t run into any failures. Kubernetes also offers self-healing and auto-replacement so you don’t need to worry about if a container or pod fails. Traffic routing and load balancing: Traffic routing sends requests to the appropriate containers. Kubernetes also comes with built-in load balancers so you can balance resources in order to respond to outages or periods of high traffic. Automated rollouts and rollbacks: Kubernetes handles rollouts for new versions or updates without downtime while monitoring the containers’ health. In case the rollout doesn’t go well, it automatically rolls back. Canary Deployments: Canary deployments enable you to test the new deployment in production in parallel with the previous version. “Before Kubernetes, our infrastructure was so antiquated it was taking us more than six months to deploy a new microservice. Today, a new microservice takes less than five days to deploy. And we’re working on getting it to an hour.” — Box Better management of your applications Containers allow applications to be broken down into smaller parts which can then be managed through an orchestration tool like Kubernetes. This makes it easy to manage codebases and test specific inputs and outputs. As mentioned earlier, Kubernetes has built-in features like self-healing and automated rollouts/rollbacks, effectively managing the containers for you. To go even further, Kubernetes allows for declarative expressions of the desired state as opposed to an execution of a deployment script, meaning that a scheduler can monitor a cluster and perform actions whenever the actual state does not match the desired. You can think of schedulers as operators who are continually monitoring the system and fixing discrepancies between the desired and actual state. Overview/additional benefits You can use it to deploy your services, to roll out new releases without downtime, and to scale (or de-scale) those services. It is portable. It can run on a public or private cloud. It can run on-premise or in a hybrid environment. You can move a Kubernetes cluster from one hosting vendor to another without changing (almost) any of the deployment and management processes. Kubernetes can be easily extended to serve nearly any needs. You can choose which modules you’ll use, and you can develop additional features yourself and plug them in. Kubernetes will decide where to run something and how to maintain the state you specify. Kubernetes can place replicas of service on the most appropriate server, restart them when needed, replicate them, and scale them. Self-healing is a feature included in its design from the start. On the other hand, self-adaptation is coming soon as well. Zero-downtime deployments, fault tolerance, high availability, scaling, scheduling, and self-healing add significant value in Kubernetes. You can use it to mount volumes for stateful applications. It allows you to store confidential information as secrets. You can use it to validate the health of your services. It can load balance requests and monitor resources. It provides service discovery and easy access to logs. When you should use it If your application uses a microservice architecture If you have transitioned or are looking to transition to a microservice architecture then Kubernetes will suit you well because it’s likely you’re already using software like Docker to containerize your application. If you’re suffering from slow development and deployment If you’re unable to meet customer demands due to slow development time, then Kubernetes might help. Rather than a team of developers spending their time wrapping their heads around the development and deployment lifecycle, Kubernetes (along with Docker) can effectively manage it for you so the team can spend their time on more meaningful work that gets products out the door. “Our internal teams have less of a need to focus on manual capacity provisioning and more time to focus on delivering features for Spotify.”—Spotify Lower infrastructure costs Kubernetes uses an efficient resource management model at the container, pod, and cluster level, helping you lower cloud infrastructure costs by ensuring your clusters always have available resources for running applications. When you shouldn’t use it Simple, lightweight applications If your application makes use of a monolithic architecture it may be tough to see the real benefits of containers and a tool used to orchestrate them. That’s because the very nature of a monolithic architecture is to have every piece of the application intertwined — from IO to the data processing to rendering, whereas containers are used to separate your application into individual components. Culture doesn’t reflect the changes ahead Kubernetes notoriously has a steep learning curve, meaning you’ll be spending a good amount of time educating teams and addressing the challenges of a new solution, etc. If you don’t have a team that’s willing to experiment and take risks then it’s probably not the choice for you. What’s next? Overall, Kubernetes boasts some pretty great features that can have a positive impact on your developing/DevOps teams and for the business as a whole. If you’re looking to get started with Kubernetes, you can check out A Practical Guide to Kubernetes, written by Viktor Farcic, a Developer Advocate at CloudBees, a member of the Google Developer Experts and Docker Captains groups, and a published author.
https://medium.com/hackernoon/why-and-when-you-should-use-kubernetes-8b50915d97d8
['Fahim Ul Haq']
2019-07-12 17:23:22.307000+00:00
['Software Development', 'Use Kubernetes', 'Learn Kubernetes', 'Kubernetes', 'Cloud Computing']
Title use KubernetesContent Kubernetes powerful container management tool automates deployment management container Kubernetes k8’s next big wave cloud computing it’s easy see business migrate infrastructure architecture reflect cloudnative datadriven era Getting started Kubernetes Try Practical Guide Kubernetes start running production grade cluster Outlined post top reason use Kubernetes shouldshouldn’t use Container orchestration Containers great provide easy way package deploy service allow process isolation immutability efficient resource utilization lightweight creation come actually running container production end dozen even thousand container time container need deployed managed connected updated manually you’d need entire team dedicated It’s enough run container need able Integrate orchestrate modular part Scale scale based demand Make fault tolerant Provide communication across cluster might ask aren’t container supposed answer container lowlevel piece puzzle real benefit obtained tool sit top container — like Kubernetes tool today known container scheduler Great multicloud adoption many today’s business gearing towards microservice architecture it’s surprise container tool used manage become popular Microservice architecture make easy split application smaller component container run different cloud environment giving option choose best host need What’s great Kubernetes it’s built used anywhere deploy publicprivatehybrid cloud enabling reach user they’re greater availability security see Kubernetes help avoid potential hazard “vendor lockin” Deploy update application scale faster timetomarket Kubernetes allows team keep pace requirement modern software development Without Kubernetes large team would manually script deployment workflow Containers combined orchestration tool provide management machine service — improving reliability application reducing amount time resource spent DevOps Kubernetes great feature allow deploy application faster scalability mind Horizontal infrastructure scaling New server added removed easily Autoscaling Automatically change number running container based CPU utilization applicationprovided metric Manual scaling Manually scale number running container command interface Replication controller replication controller make sure cluster equal amount pod running many pod replication controller terminates extra pod start pod Health check selfhealing Kubernetes check health node container ensuring application doesn’t run failure Kubernetes also offer selfhealing autoreplacement don’t need worry container pod fails Traffic routing load balancing Traffic routing sends request appropriate container Kubernetes also come builtin load balancer balance resource order respond outage period high traffic Automated rollouts rollback Kubernetes handle rollouts new version update without downtime monitoring containers’ health case rollout doesn’t go well automatically roll back Canary Deployments Canary deployment enable test new deployment production parallel previous version “Before Kubernetes infrastructure antiquated taking u six month deploy new microservice Today new microservice take le five day deploy we’re working getting hour” — Box Better management application Containers allow application broken smaller part managed orchestration tool like Kubernetes make easy manage codebases test specific input output mentioned earlier Kubernetes builtin feature like selfhealing automated rolloutsrollbacks effectively managing container go even Kubernetes allows declarative expression desired state opposed execution deployment script meaning scheduler monitor cluster perform action whenever actual state match desired think scheduler operator continually monitoring system fixing discrepancy desired actual state Overviewadditional benefit use deploy service roll new release without downtime scale descale service portable run public private cloud run onpremise hybrid environment move Kubernetes cluster one hosting vendor another without changing almost deployment management process Kubernetes easily extended serve nearly need choose module you’ll use develop additional feature plug Kubernetes decide run something maintain state specify Kubernetes place replica service appropriate server restart needed replicate scale Selfhealing feature included design start hand selfadaptation coming soon well Zerodowntime deployment fault tolerance high availability scaling scheduling selfhealing add significant value Kubernetes use mount volume stateful application allows store confidential information secret use validate health service load balance request monitor resource provides service discovery easy access log use application us microservice architecture transitioned looking transition microservice architecture Kubernetes suit well it’s likely you’re already using software like Docker containerize application you’re suffering slow development deployment you’re unable meet customer demand due slow development time Kubernetes might help Rather team developer spending time wrapping head around development deployment lifecycle Kubernetes along Docker effectively manage team spend time meaningful work get product door “Our internal team le need focus manual capacity provisioning time focus delivering feature Spotify”—Spotify Lower infrastructure cost Kubernetes us efficient resource management model container pod cluster level helping lower cloud infrastructure cost ensuring cluster always available resource running application shouldn’t use Simple lightweight application application make use monolithic architecture may tough see real benefit container tool used orchestrate That’s nature monolithic architecture every piece application intertwined — IO data processing rendering whereas container used separate application individual component Culture doesn’t reflect change ahead Kubernetes notoriously steep learning curve meaning you’ll spending good amount time educating team addressing challenge new solution etc don’t team that’s willing experiment take risk it’s probably choice What’s next Overall Kubernetes boast pretty great feature positive impact developingDevOps team business whole you’re looking get started Kubernetes check Practical Guide Kubernetes written Viktor Farcic Developer Advocate CloudBees member Google Developer Experts Docker Captains group published authorTags Software Development Use Kubernetes Learn Kubernetes Kubernetes Cloud Computing
2,861
How To Decouple Data from UI in React
Approach A. Custom Hook Let’s create a custom hook — useSomeData — that returns the properties someData , loading , and error regardless of the data fetching/management logic. The following are 3 different implementations of useSomeData . With Fetch API and component state: With Redux: With Apollo GraphQL: The 3 implementations above are interchangeable without having to modify this UI component: But, as Julius Koronci correctly pointed out, while the data fetching/management logic is decoupled, the SomeComponent UI is still coupled to the useSomeData hook. In other words, even though we can reuse useSomeData without SomeComponent , we cannot reuse SomeComponent without useSomeData . Perhaps this is where Render Props and Higher Order Components do a better job at enforcing the separation of concerns (thanks again to Julius for highlighting this).
https://medium.com/javascript-in-plain-english/how-to-decouple-data-from-ui-in-react-d6b1516f4f0b
['Suhan']
2020-12-21 16:47:14.382000+00:00
['JavaScript', 'React', 'Technology', 'Software Engineering', 'Programming']
Title Decouple Data UI ReactContent Approach Custom Hook Let’s create custom hook — useSomeData — return property someData loading error regardless data fetchingmanagement logic following 3 different implementation useSomeData Fetch API component state Redux Apollo GraphQL 3 implementation interchangeable without modify UI component Julius Koronci correctly pointed data fetchingmanagement logic decoupled SomeComponent UI still coupled useSomeData hook word even though reuse useSomeData without SomeComponent cannot reuse SomeComponent without useSomeData Perhaps Render Props Higher Order Components better job enforcing separation concern thanks Julius highlighting thisTags JavaScript React Technology Software Engineering Programming
2,862
This is How Seth Godin Changed My Life For Good
This is How Seth Godin Changed My Life For Good Shattering the illusion of corporate security and picking myself Seth Godin and Rebecca Murauskas. Photo by Akimbo Staff. It’s 5:30 PM two days before Thanksgiving, and I step into an elevator with the COO of the Fortune 15 company that I work for. He and I have a good relationship and a shared interest in mountain climbing that we chat about periodically. I’ve also been working on a huge transformational project with him for a few months, and our camaraderie has expanded. As the ground floor nears, he turns to me and says, “Have you heard about the leadership summit we want to host?” “Yes,” I reply. I was privy to some vague chatter and had started to marinate on ideas. “Sounds great! How may I be helpful?” I add. “We want to gather our top leaders for a week and make a big impact.” I remember thinking, fantastic! We can make the event engaging and fun. Maybe release pieces of our transformational project? Plan it over a year and build up the hype. As the elevator doors open, he casually mentions, “I was thinking right after Easter would be a good time.” I froze. I can imagine the look on my face was sheer terror. This “important man,” who was my boss’s boss, wanted us to pull together 6,000 people from across the US to an unknown location for a week’s worth of a leadership summit with four months of planning time during the holidays while we still did our “regular jobs.” My internal first blush reaction was nothing short of four or five curse words. I may have mustered a fake smile as he turned to hop in his car. “Happy Thanksgiving,” he shouted.
https://medium.com/the-innovation/this-is-how-seth-godin-changed-my-life-for-good-a70f33652724
['Rebecca Murauskas']
2020-12-23 19:02:35.043000+00:00
['Self Improvement', 'Business', 'Mental Health', 'Writing', 'Life Lessons']
Title Seth Godin Changed Life GoodContent Seth Godin Changed Life Good Shattering illusion corporate security picking Seth Godin Rebecca Murauskas Photo Akimbo Staff It’s 530 PM two day Thanksgiving step elevator COO Fortune 15 company work good relationship shared interest mountain climbing chat periodically I’ve also working huge transformational project month camaraderie expanded ground floor nears turn say “Have heard leadership summit want host” “Yes” reply privy vague chatter started marinate idea “Sounds great may helpful” add “We want gather top leader week make big impact” remember thinking fantastic make event engaging fun Maybe release piece transformational project Plan year build hype elevator door open casually mention “I thinking right Easter would good time” froze imagine look face sheer terror “important man” boss’s bos wanted u pull together 6000 people across US unknown location week’s worth leadership summit four month planning time holiday still “regular jobs” internal first blush reaction nothing short four five curse word may mustered fake smile turned hop car “Happy Thanksgiving” shoutedTags Self Improvement Business Mental Health Writing Life Lessons
2,863
The Internet is Multilingual But You Need To Learn Mandarin
The Internet is Multilingual But You Need To Learn Mandarin Geopolitics and the global adoption of the internet are creating an East vs West language divide. Photo by Cherry Lin on Unsplash The internet is becoming the town square for the global village of tomorrow. — Bill Gates. The language of the internet has shifted from predominantly English to multilingual. But the internet seemingly reinforces a few main languages, putting the majority of others at risk of exclusion. Chinese Mandarin is quickly becoming one of the dominant languages of the internet at the expense of others. If as Bill Gates says, the internet is a town square, then you need to learn Mandarin in order to have a voice in the digital village of the future. The Internet’s Multilinguism is Contracting There are 8 billion people, 195 countries, and over 6,500 languages spoken on the planet. Of the 8 billion, nearly half the people on the planet don’t have regular internet access. And a significant portion of these individuals without access reside in the least developed countries. Given these stats, it’s fascinating to see the distribution of global languages on the internet. There are 10 languages that represent 75% of all web traffic. English and Mandarin are neck and neck as the most common languages with the most web traffic. Nearly 50% of global traffic. The primary English speaking nations (US and UK) have a combined population of about 400 million well below China’s 1.2 billion people. Of the Chinese population, 480 million are not online yet. Put plainly, populations that represent 15% of the global population see their local languages dominate 50% of web traffic. Based on these data points, it appears that the internet is leading to a contraction of the languages in use. Why The Internet’s Language Options are Contracting Why do English and Chinese dominate as the language of the internet when there are so many other languages? Because in the 20-year span of 2000 to 2020, the US, China and other more developed nations have experienced significant internet user growth. Unlike less developed locations, these languages have experienced a first-mover and early adoption advantage allowing them to dominate 75% of global web traffic. With this early advantage, a lot of useful content has been developed and added to the global network in these languages. As new and often poorly developed nations gain access to the internet, they are forced to choose between building useful content from scratch or opting for a dominant language with well-established content and network effects. Late adopters are left to adapt to pre-existing technology and their pre-established use cases. “The famous engine [Google] that recognises 30 European languages recognises only one African language and no indigenous American or Pacific languages.” Daniel Prado Wikipedia is just one site, but even this small pool suggests the universe of information on the internet looks very different from one language to the next. The Digital Language Divide Because language is often so intertwined with culture, the contracting of available languages online raises a question of equity on the internet. Ie: If languages are not represented equally on webpages does that mean that cultural representation on the web also contracts? This may indicate that its likely new users coming online have to choose an alternative language to navigate the web and subsequently assimilate into that global culture. Chinese Geopolitical Strategy Amplifies Language Contraction & Creates A Paradigm Shift China’s ongoing investments in Africa creates an interesting potential shift in the language makeup of the internet. Africa represents a significant number of the global populace without internet access. Nearly 70% of the Africans representing 800 million people don’t have access. As initiatives like Starlink and other infrastructure investments unfold, Africa will increasingly join the global internet network in the next decade. Whether they join because of Chinese or US investment, these new users are likely to use one of the 2 dominant languages because of the pre-established network effects. Research has suggested (pdf) that speakers of smaller languages online will often opt to use the internet in a larger language, even if they don’t speak it well. The Digital Language Divide But Starlink is an unproven technology and has a slow implementation process. The Chinese investment, on the other hand, is already underway on the African continent. And it also appears that as African’s join the internet their preference is for mobile access. Mobile internet is an area Chinese companies like Huawei have shown an ability to implement infrastructure quickly. As a consequence, it may be that pre-existing infrastructure investments create a scenario where many of the 800 million African’s default to Chinese web content. This would shift Mandarin to the most dominant language on the web. Image Created by Author The Divergent Internet of the East and the West The Chinese style of the internet is different from the Western style of the internet. The Chinese standard is a notoriously state-controlled economy, with authoritarian controls on media and other types of content. It’s a communally oriented internet, ie: the good of the state comes before the good of the individual. This is often contrary to the western ideals of individual freedoms, privacy-oriented regulations, and freedoms of expression. The divergent aspects of these respective networks have created different technologies and companies that support their respective network ideologies. Examples of Divergence: Like WeChat, an all in one P2P chat, social networking service, and payments platform. Many western individuals would balk at the privacy-related issues of having all their data wrapped into one app. In the west, there are privacy and security-oriented technologies like Bitcoin, Signal, and Facebook. China and the Mandarin language are more likely than English speaking countries to become the dominant force in the entire Asia region (with the exception of India). This makes it likely that Mandarin could become the dominant language of the web. Regardless of whether or not the language balance tips one way or the other, Mandarin oriented web content will still make up significant portions of the internet. The diverging policies and subsequent technologies that form from them will be interesting to follow. They represent an opportunity for aspiring digital workers to bridge the gap in diverging tech. Why You Need to Learn Mandarin Capital, like energy, is a dormant value. Bringing it to life requires us to go beyond looking at our assets as they are to actively thinking about them as they could be. It requires a process for fixing an asset’s economic potential into a form that can be used to initiate additional production. The Mystery of Capital In the digital age, information is capital and influence is power. The ability to create and curate unique digital information assets is like creating and accumulating potential power. As the languages of the internet contract to be dominated by a few, the cultural ideas reinforced by these dominant languages will be evangelized in developing communities. Influence is gained by leveraging the network effects of the internet to connect large groups of people. As more people join the network, it’s value grows and the internet converges on a few languages and the east/west divide. Moving forward, being a monolinguist will prove to be a significant opportunity cost as it represents a disadvantage in controlling the global ideological narrative. As China’s geopolitical strategy plays out over the coming decades the adoption of Mandarin can be expected to continuously grow in Africa and the developing world. Therefore, it makes sense for individuals that want to be relevant in an increasingly connected world to speak the 2 most dominant languages. Learning Mandarin will empower internet users to tap into a large and growing body of unique internet content. An amalgamation of divergent processes, unique thoughts, and ideologies. The future of the internet will be characteristic of a multilingual global society where the utility of polyglots becomes significant. By learning Mandarin, you open yourself up to a wider world of opportunities, positioning yourself to maximize the value of the internet's network effects.
https://medium.com/digital-diplomacy/the-internet-is-multilingual-but-you-need-to-learn-mandarin-558c15ab5158
['Doug Antin']
2020-07-26 16:18:02.794000+00:00
['Marketing', 'Technology', 'Future', 'Language', 'Internet']
Title Internet Multilingual Need Learn MandarinContent Internet Multilingual Need Learn Mandarin Geopolitics global adoption internet creating East v West language divide Photo Cherry Lin Unsplash internet becoming town square global village tomorrow — Bill Gates language internet shifted predominantly English multilingual internet seemingly reinforces main language putting majority others risk exclusion Chinese Mandarin quickly becoming one dominant language internet expense others Bill Gates say internet town square need learn Mandarin order voice digital village future Internet’s Multilinguism Contracting 8 billion people 195 country 6500 language spoken planet 8 billion nearly half people planet don’t regular internet access significant portion individual without access reside least developed country Given stats it’s fascinating see distribution global language internet 10 language represent 75 web traffic English Mandarin neck neck common language web traffic Nearly 50 global traffic primary English speaking nation US UK combined population 400 million well China’s 12 billion people Chinese population 480 million online yet Put plainly population represent 15 global population see local language dominate 50 web traffic Based data point appears internet leading contraction language use Internet’s Language Options Contracting English Chinese dominate language internet many language 20year span 2000 2020 US China developed nation experienced significant internet user growth Unlike le developed location language experienced firstmover early adoption advantage allowing dominate 75 global web traffic early advantage lot useful content developed added global network language new often poorly developed nation gain access internet forced choose building useful content scratch opting dominant language wellestablished content network effect Late adopter left adapt preexisting technology preestablished use case “The famous engine Google recognises 30 European language recognises one African language indigenous American Pacific languages” Daniel Prado Wikipedia one site even small pool suggests universe information internet look different one language next Digital Language Divide language often intertwined culture contracting available language online raise question equity internet Ie language represented equally webpage mean cultural representation web also contract may indicate likely new user coming online choose alternative language navigate web subsequently assimilate global culture Chinese Geopolitical Strategy Amplifies Language Contraction Creates Paradigm Shift China’s ongoing investment Africa creates interesting potential shift language makeup internet Africa represents significant number global populace without internet access Nearly 70 Africans representing 800 million people don’t access initiative like Starlink infrastructure investment unfold Africa increasingly join global internet network next decade Whether join Chinese US investment new user likely use one 2 dominant language preestablished network effect Research suggested pdf speaker smaller language online often opt use internet larger language even don’t speak well Digital Language Divide Starlink unproven technology slow implementation process Chinese investment hand already underway African continent also appears African’s join internet preference mobile access Mobile internet area Chinese company like Huawei shown ability implement infrastructure quickly consequence may preexisting infrastructure investment create scenario many 800 million African’s default Chinese web content would shift Mandarin dominant language web Image Created Author Divergent Internet East West Chinese style internet different Western style internet Chinese standard notoriously statecontrolled economy authoritarian control medium type content It’s communally oriented internet ie good state come good individual often contrary western ideal individual freedom privacyoriented regulation freedom expression divergent aspect respective network created different technology company support respective network ideology Examples Divergence Like WeChat one P2P chat social networking service payment platform Many western individual would balk privacyrelated issue data wrapped one app west privacy securityoriented technology like Bitcoin Signal Facebook China Mandarin language likely English speaking country become dominant force entire Asia region exception India make likely Mandarin could become dominant language web Regardless whether language balance tip one way Mandarin oriented web content still make significant portion internet diverging policy subsequent technology form interesting follow represent opportunity aspiring digital worker bridge gap diverging tech Need Learn Mandarin Capital like energy dormant value Bringing life requires u go beyond looking asset actively thinking could requires process fixing asset’s economic potential form used initiate additional production Mystery Capital digital age information capital influence power ability create curate unique digital information asset like creating accumulating potential power language internet contract dominated cultural idea reinforced dominant language evangelized developing community Influence gained leveraging network effect internet connect large group people people join network it’s value grows internet converges language eastwest divide Moving forward monolinguist prove significant opportunity cost represents disadvantage controlling global ideological narrative China’s geopolitical strategy play coming decade adoption Mandarin expected continuously grow Africa developing world Therefore make sense individual want relevant increasingly connected world speak 2 dominant language Learning Mandarin empower internet user tap large growing body unique internet content amalgamation divergent process unique thought ideology future internet characteristic multilingual global society utility polyglot becomes significant learning Mandarin open wider world opportunity positioning maximize value internet network effectsTags Marketing Technology Future Language Internet
2,864
What I Didn’t Learn at Wharton About Personal Finance
1. Establish The Basic Consumer Banking Accounts and Services Many people open a bank account after turning 18 or during college. However, a shocking amount of young adults don’t have basic bank accounts (and some are still sharing a custodial account with a parent or guardian). All young adults should open their own bank account. Ideally, both a checking and savings account, with no monthly fees. Not only is this good experience in and of itself, it’s important to learn more about the ancillary services your bank offers. Your bank account will likely come with checks and a debit card. Learn how to write a check! It may seem antiquated to some, but eventually, you will likely need to write one for a deposit, utility, or a landlord that does accept credit cards or direct deposit. If your bank offers safety deposit boxes, this can also be a good time to inquire about one. Many banks are reducing their physical footprint, and as a result, you may need to get on a waiting list. Why do you potentially need a safety deposit box? There are some documents and personal items that you want to keep the original version or protect it from fire or damage at home. Examples of this include: Social Security Card Passport Titles to vehicles or property Copies of important documents Physical photographs Extra keys Analog media that you haven’t taken the time to convert to digital format Family heirlooms Jewelry that is valuable/you don’t wear often 2. Develop A Plan to Maximize Your Credit Note: If you cannot control your spending, and will not be paying off your entire balance every month, do not get a credit card! Assuming you only use a credit card for purchases that you can easily pay off in full, getting a credit card is critical for most young adults, when building their credit. Their are many myths about credit cards: One of the worst myths is that you have to use a credit card on a regular basis or carry a balance to build credit. You do need to use credit products to build a good credit score, but you can use them very sparingly. That can be as simple as opening a credit card, charging a small amount with it 2–3 times per year, paying it off immediately every month, and otherwise keeping the card in your dresser drawer. If you feel comfortable using the card more regularly, you can compare different credit cards, and try to find a rewards structure that you like. Generally though, you should not be getting a credit card that has annual fees (unless you absolutely know you will be spending enough money to justify the credit card rewards/spending ratio). Even then, this can be a slippery slope into encouraging increased spending. So just stick with a card that has no annual fees. 3. Avoid Grad School Unless Absolutely Necessary For college graduates, there are generally three tracks that would lead you to pursue graduate education: Some professions require graduate school. In most cases, you cannot become a doctor, lawyer, university professor without a graduate degree. Assuming you are passionate about these professions, you can usually justify the cost. There is little choice in this scenario in getting the graduate degree, unless you reconsider the entire profession. However it get much more murky with the wide range of jobs, which may not require a graduate degree, but a graduate degree is something that may seem essential to succeed. For example, if you want to work in certain management level positions in business, you may realistically need an MBA depending upon how competitive a position is/company culture. You may also be able to get a lower level job, at the same company, demonstrate your value through work experience, and get promoted into such a role. It may even be the case that companies who otherwise require MBAs for external hires will waive these requirements for an internal candidate that they really want to retain. In this second case, you need to be careful. While graduate degrees are typically a clearly positive factor from a hiring perspective, many young adults fail to weigh this against the true cost of continuing with education. Debt, especially student loan debt, is very restrictive. While I can’t advise you one way or the another about whether you should go to graduate school without knowing the intricacies of your situation/life goals, I can say with certainty that the debt you will likely incur, will be something that you will likely have to adjust your life around for years if not decades. 3. Typically the third reason for considering graduate education is a career switch. This is similar to the second reason in that the debt you incur needs to be factored into the equation properly. 4. Emergency Fund Once you are working and able to save money, you should focus on building an emergency fund. An emergency fund is a readily available source of assets to help one navigate financial dilemmas such as the loss of a job, a debilitating illness, or a major repair to your home or car. The purpose of the fund is to improve financial security by creating a safety net of cash or other highly liquid assets that can be used to meet emergency expenses, as well as reduce the need to draw from high-interest debt options, such as credit cards or unsecured loans — or undermine your future security by tapping retirement funds. An emergency fund should contain enough money to cover between three and six months’ worth of expenses, according to most financial planners. Note that financial institutions do not carry accounts labeled as emergency funds. Rather, the onus falls on an individual to set up this type of account and earmark it as capital reserved for personal financial crises. I tend to agree that 3–6 months is a good amount for an emergency fund if you have a stable source of income. However, if you are a freelancer, entrepreneur, or are paid a large percentage of your salary as a bonus or work on commission, I would suggest saving a larger amount. 5. Dealing with Debt In general, you should be avoiding most consumer debt. But if you do have consumer debt (credit cards, auto, store debt), you should almost always prioritize paying down this debt before building your savings. This is because consumer debt (especially credit cards) tend to have very high interest rates. Credit card issuers can lure you in with a low introductory APR and gleaming credit line. But that introductory APR offer will eventually expire. When it does, you can find yourself staring at an overwhelming pile of debt if you didn’t manage your new credit card account the right way. The reason revolving debt can be so overwhelming is because credit card interest rates are typically really high. So, if you’re just making the minimum payment each month, it will take you a long time to pay off your balance — possibly decades. During that time, you’ll also pay a lot of interest. Let’s say you charge $8,000 on a credit card with 17% APR, and then put it in a drawer, never spending another cent. If you make only the minimum payment on that bill each month, it could take you almost 16 years to pay off your debt — and cost you nearly $7,000 extra in interest! 6. Develop Savings and Spending Patterns In our “treat yourself/YOLO” culture it is easy to forget to prioritize saving and developing good spending habits. Start with a spending log. Yes, you have heard this advice before. This exercise is eye-opening if you do it diligently. With online banking you will have access to a visual record of all your spending. This is a great way to begin to spot patterns and decide where you can cut back. Analyze your online account statement (four weeks is ideal) to help you determine where your money is going. Review your log without judgment. What you have done, in terms of your spending, does not matter — at least not yet. What does matter is that you get a firm hold on your expenses. For example, how much money do you spend on eating out each week? Next, write down all sources of income. With a list of your income and expenses in hand determine your priorities. Begin your budgeting process here. Obviously housing and other fixed costs will figure prominently on your priority list. Now, take a look at the conveniences that represent variable expenses. This is likely where you will find room to make changes. For example, if you buy coffee each day, can you bring it from home a time or two each week? Or would you be willing to purchase a smaller or otherwise less expensive cup? Can you clip coupons or eat out a little less? Remember, developing any new habit takes practice. In time you may even learn to love your new healthy spending habits. It is liberating to be in control of your finances. So take a serious look at your savings/spending. Create a budget and stick to your savings goal. 7. Developing Multiple Sources of Income This topic is a bit more advanced, but only because so few people are taught this. Developing multiple streams of income is essential to achieving financial independence. This could consist of someone creating a new source of active income. An example of this would be someone who works as an office manager during the week (their primary job) but begins driving for Uber on the weekend to make some extra money. This is also an additional income stream. This could also consist of someone creating new streams of passive income. I am a huge proponent of developing passive income streams. The basic difference between passive and active income is that active income requires the direct trading of time for money. Passive Income is generally defined as a stream of income earned with little or no ongoing effort needed from the individual receiving the passive income in order to grow the stream of income. Passive income is income that is not proportional to the time you physically put into acquiring it. I’ve written a fairly detailed article with a number of passive income ideas that I have tried: Regardless of whether its active or passive income, diversifying you sources of income will make you feel more secure and financially stable. 8. Investing Once you have a well stocked emergency fund, and your savings account begins to grow, it is time to start strategically investing that money. Many people are scared of investing. But luckily, the rise of index funds have made cost effective investing much easier than it was a generation ago. Index funds are a type of mutual fund where thousands of investors pool their cash to purchase shares in a fund that mimics a benchmark index, such as the S&P 500 (hence the name “index fund”). This simpler approach — known as passive investing — has proved more profitable for the average investor than active investing, for two reasons: Markets tend to rise over time, and index funds charge lower fees, allowing investors to keep more of their money in the market. As a result, many investors now flock to passive funds. All investments carry risk, and Vanguard index funds are no exception. For example, investors in Vanguard’s flagship S&P 500 Index Fund saw the fund’s value drop more than 4% year over year after the market tumult in 2018. But the fund’s 10-year average annual return was 14.3%, thanks to the second-longest bull market in history. Passively investing in index funds is so popular because most actively managed funds fail to consistently outperform the market. For example, from 2002 to 2017, only about 11% of actively managed stock funds beat their designated benchmark, according to Vanguard and Morningstar data. 9. Begin Retirement Account Contributions Even if you have never considered retirement, don’t feel like your ship has sailed. Every dollar you can save now will be much appreciated later. Strategically invest and you won’t be playing catch-up for long. Note: This topic is too big to cover in this section alone, but hopefully it will serve as a primer for the larger topic. The first place to start retirement planning is by saving and investing money through one or all of the available options offered through employment and personal investments. Many employers offer retirement planning options such as pension plans, 401(K) plans, or a combination of various plans. However, you do not have to rely solely on company-sponsored plans. You can choose to invest on your own with or without the help of financial planners. Employer-sponsored retirement plans Employer-sponsored retirement plans include benefit plans such as pensions; contribution plans such as 401(k), Roth 401(k), 403(b), 457(b); and Thrift Savings Plans. 401(k) can be one of the best tools for creating a secure retirement. It provides you with two important advantages. First, all contributions and earnings to your 401(k) are tax-deferred. You only pay taxes on contributions and earnings when the money is withdrawn. Second, many employers provide matching contributions to your 401(k) account. The combined result is a retirement savings plan you cannot afford to pass up. 403(b) plans are only available for employees of certain non-profit, tax-exempt organizations: 501c(3) Corps, including colleges, universities, schools, hospitals, etc. If you are an employee of one of these organizations, a 403(b) can be one of your best tools for creating a secure retirement. It provides you with two important advantages. First, all contributions and earnings to your 403(b) are tax-deferred. You only pay taxes on contributions and earnings when the money is withdrawn. Second, many employers provide matching contributions to your 403(b) account which can range from 0% to 100% of your contributions. The combined result is a retirement savings plan you cannot afford to pass up. Individual retirement plans Individual retirement plans include traditional IRAs, ROTH IRAs, spousal IRAs, myRAs, and rollover IRAs. Contributing to a traditional IRA can create a current tax deduction, plus it provides for tax-deferred growth. While long term savings in a Roth IRA may produce better after-tax returns, a Traditional IRA may be an excellent alternative if you qualify for the tax deduction. Always check with your tax advisor prior to making any investments. Retirement plans for self-employed and small business owners Retirement plans such as SEP, SIMPLE, and Payroll Deduction IRAs are for individuals or small business owners with employees.
https://medium.com/escaping-the-9-to-5/what-i-didnt-learn-at-wharton-about-personal-finance-8a1f2d79dee9
['Casey Botticello']
2020-05-06 02:27:01.226000+00:00
['Personal Finance', 'Business', 'Entrepreneurship', 'Productivity', 'Financial']
Title Didn’t Learn Wharton Personal FinanceContent 1 Establish Basic Consumer Banking Accounts Services Many people open bank account turning 18 college However shocking amount young adult don’t basic bank account still sharing custodial account parent guardian young adult open bank account Ideally checking saving account monthly fee good experience it’s important learn ancillary service bank offer bank account likely come check debit card Learn write check may seem antiquated eventually likely need write one deposit utility landlord accept credit card direct deposit bank offer safety deposit box also good time inquire one Many bank reducing physical footprint result may need get waiting list potentially need safety deposit box document personal item want keep original version protect fire damage home Examples include Social Security Card Passport Titles vehicle property Copies important document Physical photograph Extra key Analog medium haven’t taken time convert digital format Family heirloom Jewelry valuableyou don’t wear often 2 Develop Plan Maximize Credit Note cannot control spending paying entire balance every month get credit card Assuming use credit card purchase easily pay full getting credit card critical young adult building credit many myth credit card One worst myth use credit card regular basis carry balance build credit need use credit product build good credit score use sparingly simple opening credit card charging small amount 2–3 time per year paying immediately every month otherwise keeping card dresser drawer feel comfortable using card regularly compare different credit card try find reward structure like Generally though getting credit card annual fee unless absolutely know spending enough money justify credit card rewardsspending ratio Even slippery slope encouraging increased spending stick card annual fee 3 Avoid Grad School Unless Absolutely Necessary college graduate generally three track would lead pursue graduate education profession require graduate school case cannot become doctor lawyer university professor without graduate degree Assuming passionate profession usually justify cost little choice scenario getting graduate degree unless reconsider entire profession However get much murky wide range job may require graduate degree graduate degree something may seem essential succeed example want work certain management level position business may realistically need MBA depending upon competitive position iscompany culture may also able get lower level job company demonstrate value work experience get promoted role may even case company otherwise require MBAs external hire waive requirement internal candidate really want retain second case need careful graduate degree typically clearly positive factor hiring perspective many young adult fail weigh true cost continuing education Debt especially student loan debt restrictive can’t advise one way another whether go graduate school without knowing intricacy situationlife goal say certainty debt likely incur something likely adjust life around year decade 3 Typically third reason considering graduate education career switch similar second reason debt incur need factored equation properly 4 Emergency Fund working able save money focus building emergency fund emergency fund readily available source asset help one navigate financial dilemma loss job debilitating illness major repair home car purpose fund improve financial security creating safety net cash highly liquid asset used meet emergency expense well reduce need draw highinterest debt option credit card unsecured loan — undermine future security tapping retirement fund emergency fund contain enough money cover three six months’ worth expense according financial planner Note financial institution carry account labeled emergency fund Rather onus fall individual set type account earmark capital reserved personal financial crisis tend agree 3–6 month good amount emergency fund stable source income However freelancer entrepreneur paid large percentage salary bonus work commission would suggest saving larger amount 5 Dealing Debt general avoiding consumer debt consumer debt credit card auto store debt almost always prioritize paying debt building saving consumer debt especially credit card tend high interest rate Credit card issuer lure low introductory APR gleaming credit line introductory APR offer eventually expire find staring overwhelming pile debt didn’t manage new credit card account right way reason revolving debt overwhelming credit card interest rate typically really high you’re making minimum payment month take long time pay balance — possibly decade time you’ll also pay lot interest Let’s say charge 8000 credit card 17 APR put drawer never spending another cent make minimum payment bill month could take almost 16 year pay debt — cost nearly 7000 extra interest 6 Develop Savings Spending Patterns “treat yourselfYOLO” culture easy forget prioritize saving developing good spending habit Start spending log Yes heard advice exercise eyeopening diligently online banking access visual record spending great way begin spot pattern decide cut back Analyze online account statement four week ideal help determine money going Review log without judgment done term spending matter — least yet matter get firm hold expense example much money spend eating week Next write source income list income expense hand determine priority Begin budgeting process Obviously housing fixed cost figure prominently priority list take look convenience represent variable expense likely find room make change example buy coffee day bring home time two week would willing purchase smaller otherwise le expensive cup clip coupon eat little le Remember developing new habit take practice time may even learn love new healthy spending habit liberating control finance take serious look savingsspending Create budget stick saving goal 7 Developing Multiple Sources Income topic bit advanced people taught Developing multiple stream income essential achieving financial independence could consist someone creating new source active income example would someone work office manager week primary job begin driving Uber weekend make extra money also additional income stream could also consist someone creating new stream passive income huge proponent developing passive income stream basic difference passive active income active income requires direct trading time money Passive Income generally defined stream income earned little ongoing effort needed individual receiving passive income order grow stream income Passive income income proportional time physically put acquiring I’ve written fairly detailed article number passive income idea tried Regardless whether active passive income diversifying source income make feel secure financially stable 8 Investing well stocked emergency fund saving account begin grow time start strategically investing money Many people scared investing luckily rise index fund made cost effective investing much easier generation ago Index fund type mutual fund thousand investor pool cash purchase share fund mimic benchmark index SP 500 hence name “index fund” simpler approach — known passive investing — proved profitable average investor active investing two reason Markets tend rise time index fund charge lower fee allowing investor keep money market result many investor flock passive fund investment carry risk Vanguard index fund exception example investor Vanguard’s flagship SP 500 Index Fund saw fund’s value drop 4 year year market tumult 2018 fund’s 10year average annual return 143 thanks secondlongest bull market history Passively investing index fund popular actively managed fund fail consistently outperform market example 2002 2017 11 actively managed stock fund beat designated benchmark according Vanguard Morningstar data 9 Begin Retirement Account Contributions Even never considered retirement don’t feel like ship sailed Every dollar save much appreciated later Strategically invest won’t playing catchup long Note topic big cover section alone hopefully serve primer larger topic first place start retirement planning saving investing money one available option offered employment personal investment Many employer offer retirement planning option pension plan 401K plan combination various plan However rely solely companysponsored plan choose invest without help financial planner Employersponsored retirement plan Employersponsored retirement plan include benefit plan pension contribution plan 401k Roth 401k 403b 457b Thrift Savings Plans 401k one best tool creating secure retirement provides two important advantage First contribution earnings 401k taxdeferred pay tax contribution earnings money withdrawn Second many employer provide matching contribution 401k account combined result retirement saving plan cannot afford pas 403b plan available employee certain nonprofit taxexempt organization 501c3 Corps including college university school hospital etc employee one organization 403b one best tool creating secure retirement provides two important advantage First contribution earnings 403b taxdeferred pay tax contribution earnings money withdrawn Second many employer provide matching contribution 403b account range 0 100 contribution combined result retirement saving plan cannot afford pas Individual retirement plan Individual retirement plan include traditional IRAs ROTH IRAs spousal IRAs myRAs rollover IRAs Contributing traditional IRA create current tax deduction plus provides taxdeferred growth long term saving Roth IRA may produce better aftertax return Traditional IRA may excellent alternative qualify tax deduction Always check tax advisor prior making investment Retirement plan selfemployed small business owner Retirement plan SEP SIMPLE Payroll Deduction IRAs individual small business owner employeesTags Personal Finance Business Entrepreneurship Productivity Financial
2,865
10 rules for better dashboard design
One view to rule them all Dashboard design is a frequent request these days. Businesses dream about a simple view that presents all information, shows trends and risky areas, updates users on what happened — a view that will guide them into a bright financial future. For me, a dashboard — is an at a glance preview of the most crucial information for the user at the moment he is looking at it, and an easy way to navigate directly to various areas of the application that require users attention. The term “dashboard” is a metaphor for a car dashboard, sometimes also called the cockpit area, usually near the front of an aircraft or spacecraft, from which a pilot controls the aircraft. Working on enterprise projects for years, I have designed countless dashboards. And every new one is the next challenge for me. A good dashboard can be a daunting thing to design. Based on my experience, I put together a list of useful suggestions to help you in the future. Whether you just starting, or are seasoned designer, I’m sure you will find something interesting here. 1.Define the purpose of the dashboard. Like any other view in your product, the dashboard has a specific purpose that it’s undertaken to serve. Getting this wrong renders your further efforts meaningless. There are multiple popular ways to categorize dashboards based on their purpose(Analytical, Strategic, Operational, Tactical etc). To keep things simple I will divide them into 2 more general forms: Operational dashboard Operational dashboards aim to impart critical information quickly to users as they are engaged in time-sensitive tasks. The main goals of the operational dashboard are to present data deviations to the user quickly and clearly, show current resources, and display their status. It’s a digital control room designed to help users be quick, proactive, and efficient.
https://uxplanet.org/10-rules-for-better-dashboard-design-ef68189d734c
['Taras Bakusevych']
2019-10-05 17:11:28.891000+00:00
['Design', 'Dashboard', 'UX', 'Data Visualization', 'User Interface']
Title 10 rule better dashboard designContent One view rule Dashboard design frequent request day Businesses dream simple view present information show trend risky area update user happened — view guide bright financial future dashboard — glance preview crucial information user moment looking easy way navigate directly various area application require user attention term “dashboard” metaphor car dashboard sometimes also called cockpit area usually near front aircraft spacecraft pilot control aircraft Working enterprise project year designed countless dashboard every new one next challenge good dashboard daunting thing design Based experience put together list useful suggestion help future Whether starting seasoned designer I’m sure find something interesting 1Define purpose dashboard Like view product dashboard specific purpose it’s undertaken serve Getting wrong render effort meaningless multiple popular way categorize dashboard based purposeAnalytical Strategic Operational Tactical etc keep thing simple divide 2 general form Operational dashboard Operational dashboard aim impart critical information quickly user engaged timesensitive task main goal operational dashboard present data deviation user quickly clearly show current resource display status It’s digital control room designed help user quick proactive efficientTags Design Dashboard UX Data Visualization User Interface
2,866
Coronavirus: The Hammer and the Dance
As of today, there are 0 daily new cases of coronavirus in the entire 60 million-big region of Hubei. The diagnostics would keep going up for a couple of weeks, but then they would start going down. With fewer cases, the fatality rate starts dropping too. And the collateral damage is also reduced: fewer people would die from non-coronavirus-related causes because the healthcare system is simply overwhelmed. Suppression would get us: Fewer total cases of Coronavirus Immediate relief for the healthcare system and the humans who run it Reduction in fatality rate Reduction in collateral damage Ability for infected, isolated and quarantined healthcare workers to get better and back to work. In Italy, healthcare workers represent 8% of all contagions. Understand the True Problem: Testing and Tracing Right now, the UK and the US have no idea about their true cases. We don’t know how many there are. We just know the official number is not right, and the true one is in the tens of thousands of cases. This has happened because we’re not testing, and we’re not tracing. With a few more weeks, we could get our testing situation in order, and start testing everybody. With that information, we would finally know the true extent of the problem, where we need to be more aggressive, and what communities are safe to be released from a lockdown. New testing methods could speed up testing and drive costs down substantially. We could also set up a tracing operation like the ones they have in China or other East Asia countries, where they can identify all the people that every sick person met, and can put them in quarantine. This would give us a ton of intelligence to release later on our social distancing measures: if we know where the virus is, we can target these places only. This is not rocket science: it’s the basics of how East Asia Countries have been able to control this outbreak without the kind of draconian social distancing that is increasingly essential in other countries. The measures from this section (testing and tracing) single-handedly curbed the growth of the coronavirus in South Korea and got the epidemic under control, without a strong imposition of social distancing measures. Build Up Capacity The US (and presumably the UK) are about to go to war without armor. We have masks for just two weeks, few personal protective equipments (“PPE”), not enough ventilators, not enough ICU beds, not enough ECMOs (blood oxygenation machines)… This is why the fatality rate would be so high in a mitigation strategy. But if we buy ourselves some time, we can turn this around: We have more time to buy equipment we will need for a future wave We can quickly build up our production of masks, PPEs, ventilators, ECMOs, and any other critical device to reduce fatality rate. Put in another way: we don’t need years to get our armor, we need weeks. Let’s do everything we can to get our production humming now. Countries are mobilized. People are being inventive, such as using 3D printing for ventilator parts. We can do it. We just need more time. Would you wait a few weeks to get yourself some armor before facing a mortal enemy? This is not the only capacity we need. We will need health workers as soon as possible. Where will we get them? We need to train people to assist nurses, and we need to get medical workers out of retirement. Many countries have already started, but this takes time. We can do this in a few weeks, but not if everything collapses. Lower Public Contagiousness The public is scared. The coronavirus is new. There’s so much we don’t know how to do yet! People haven’t learned to stop hand-shaking. They still hug. They don’t open doors with their elbow. They don’t wash their hands after touching a door knob. They don’t disinfect tables before sitting. Once we have enough masks, we can use them outside of the healthcare system too. Right now, it’s better to keep them for healthcare workers. But if they weren’t scarce, people should wear them in their daily lives, making it less likely that they infect other people when sick, and with proper training also reducing the likelihood that the wearers get infected. (In the meantime, wearing something is better than nothing.) All of these are pretty cheap ways to reduce the transmission rate. The less this virus propagates, the fewer measures we’ll need in the future to contain it. But we need time to educate people on all these measures and equip them. Understand the Virus We know very very little about the virus. But every week, hundreds of new papers are coming. The world is finally united against a common enemy. Researchers around the globe are mobilizing to understand this virus better. How does the virus spread? How can contagion be slowed down? What is the share of asymptomatic carriers? Are they contagious? How much? What are good treatments? How long does it survive? On what surfaces? How do different social distancing measures impact the transmission rate? What’s their cost? What are tracing best practices? How reliable are our tests? Clear answers to these questions will help make our response as targeted as possible while minimizing collateral economic and social damage. And they will come in weeks, not years. Find Treatments Not only that, but what if we found a treatment in the next few weeks? Any day we buy gets us closer to that. Right now, there are already several candidates, such as Favipiravir, Chloroquine, or Chloroquine combined with Azithromycin. What if it turned out that in two months we discovered a treatment for the coronavirus? How stupid would we look if we already had millions of deaths following a mitigation strategy? Understand the Cost-Benefits All of the factors above can help us save millions of lives. That should be enough. Unfortunately, politicians can’t only think about the lives of the infected. They must think about all the population, and heavy social distancing measures have an impact on others. Right now we have no idea how different social distancing measures reduce transmission. We also have no clue what their economic and social costs are. Isn’t it a bit difficult to decide what measures we need for the long term if we don’t know their cost or benefit? A few weeks would give us enough time to start studying them, understand them, prioritize them, and decide which ones to follow. Fewer cases, more understanding of the problem, building up assets, understanding the virus, understanding the cost-benefit of different measures, educating the public… These are some core tools to fight the virus, and we just need a few weeks to develop many of them. Wouldn’t it be dumb to commit to a strategy that throws us instead, unprepared, into the jaws of our enemy? 4. The Hammer and the Dance Now we know that the Mitigation Strategy is probably a terrible choice, and that the Suppression Strategy has a massive short-term advantage. But people have rightful concerns about this strategy: How long will it actually last? How expensive will it be? Will there be a second peak as big as if we didn’t do anything? Here, we’re going to look at what a true Suppression Strategy would look like. We can call it the Hammer and the Dance. The Hammer First, you act quickly and aggressively. For all the reasons we mentioned above, given the value of time, we want to quench this thing as soon as possible. One of the most important questions is: How long will this last? The fear that everybody has is that we will be locked inside our homes for months at a time, with the ensuing economic disaster and mental breakdowns. This idea was unfortunately entertained in the famous Imperial College paper: Do you remember this chart? The light blue area that goes from end of March to end of August is the period that the paper recommends as the Hammer, the initial suppression that includes heavy social distancing. If you’re a politician and you see that one option is to let hundreds of thousands or millions of people die with a mitigation strategy and the other is to stop the economy for five months before going through the same peak of cases and deaths, these don’t sound like compelling options. But this doesn’t need to be so. This paper, driving policy today, has been brutally criticized for core flaws: They ignore contact tracing (at the core of policies in South Korea, China or Singapore among others) or travel restrictions (critical in China), ignore the impact of big crowds… The time needed for the Hammer is weeks, not months.
https://tomaspueyo.medium.com/coronavirus-the-hammer-and-the-dance-be9337092b56
['Tomas Pueyo']
2020-05-28 07:58:27.402000+00:00
['Health', 'Coronavirus', 'Politics', 'Healthcare']
Title Coronavirus Hammer DanceContent today 0 daily new case coronavirus entire 60 millionbig region Hubei diagnostics would keep going couple week would start going fewer case fatality rate start dropping collateral damage also reduced fewer people would die noncoronavirusrelated cause healthcare system simply overwhelmed Suppression would get u Fewer total case Coronavirus Immediate relief healthcare system human run Reduction fatality rate Reduction collateral damage Ability infected isolated quarantined healthcare worker get better back work Italy healthcare worker represent 8 contagion Understand True Problem Testing Tracing Right UK US idea true case don’t know many know official number right true one ten thousand case happened we’re testing we’re tracing week could get testing situation order start testing everybody information would finally know true extent problem need aggressive community safe released lockdown New testing method could speed testing drive cost substantially could also set tracing operation like one China East Asia country identify people every sick person met put quarantine would give u ton intelligence release later social distancing measure know virus target place rocket science it’s basic East Asia Countries able control outbreak without kind draconian social distancing increasingly essential country measure section testing tracing singlehandedly curbed growth coronavirus South Korea got epidemic control without strong imposition social distancing measure Build Capacity US presumably UK go war without armor mask two week personal protective equipment “PPE” enough ventilator enough ICU bed enough ECMOs blood oxygenation machines… fatality rate would high mitigation strategy buy time turn around time buy equipment need future wave quickly build production mask PPEs ventilator ECMOs critical device reduce fatality rate Put another way don’t need year get armor need week Let’s everything get production humming Countries mobilized People inventive using 3D printing ventilator part need time Would wait week get armor facing mortal enemy capacity need need health worker soon possible get need train people assist nurse need get medical worker retirement Many country already started take time week everything collapse Lower Public Contagiousness public scared coronavirus new There’s much don’t know yet People haven’t learned stop handshaking still hug don’t open door elbow don’t wash hand touching door knob don’t disinfect table sitting enough mask use outside healthcare system Right it’s better keep healthcare worker weren’t scarce people wear daily life making le likely infect people sick proper training also reducing likelihood wearer get infected meantime wearing something better nothing pretty cheap way reduce transmission rate le virus propagates fewer measure we’ll need future contain need time educate people measure equip Understand Virus know little virus every week hundred new paper coming world finally united common enemy Researchers around globe mobilizing understand virus better virus spread contagion slowed share asymptomatic carrier contagious much good treatment long survive surface different social distancing measure impact transmission rate What’s cost tracing best practice reliable test Clear answer question help make response targeted possible minimizing collateral economic social damage come week year Find Treatments found treatment next week day buy get u closer Right already several candidate Favipiravir Chloroquine Chloroquine combined Azithromycin turned two month discovered treatment coronavirus stupid would look already million death following mitigation strategy Understand CostBenefits factor help u save million life enough Unfortunately politician can’t think life infected must think population heavy social distancing measure impact others Right idea different social distancing measure reduce transmission also clue economic social cost Isn’t bit difficult decide measure need long term don’t know cost benefit week would give u enough time start studying understand prioritize decide one follow Fewer case understanding problem building asset understanding virus understanding costbenefit different measure educating public… core tool fight virus need week develop many Wouldn’t dumb commit strategy throw u instead unprepared jaw enemy 4 Hammer Dance know Mitigation Strategy probably terrible choice Suppression Strategy massive shortterm advantage people rightful concern strategy long actually last expensive second peak big didn’t anything we’re going look true Suppression Strategy would look like call Hammer Dance Hammer First act quickly aggressively reason mentioned given value time want quench thing soon possible One important question long last fear everybody locked inside home month time ensuing economic disaster mental breakdown idea unfortunately entertained famous Imperial College paper remember chart light blue area go end March end August period paper recommends Hammer initial suppression includes heavy social distancing you’re politician see one option let hundred thousand million people die mitigation strategy stop economy five month going peak case death don’t sound like compelling option doesn’t need paper driving policy today brutally criticized core flaw ignore contact tracing core policy South Korea China Singapore among others travel restriction critical China ignore impact big crowds… time needed Hammer week monthsTags Health Coronavirus Politics Healthcare
2,867
Life (and Sex) is Better Without Alcohol
I stopped drinking last year. I had been told to expect better sex. But it still surprised me when it happened. Photo of me 31 weeks pregnant, by Scott Schell. Growing up I remember my great-grandmother having her drink every day at 4 pm in a tall glass that I used for drinking milk — 3/4 red wine, 1/4 water. At her 88th birthday party, she was sitting on the grass in a wicker folding chair, and just as her drink was handed to her, the chair folded up. She fell to the ground and somehow managed to not break a bone or spill a drop of her drink. My uncle would tell this story with a drink in his hand and laugh so hard he needed to wipe his eyes. I heard this and understood that alcohol brings happiness and is worth sacrificing your body to protect. We inherit the experiences of at least three generations of our ancestors in our DNA, and all three of mine are Irish Catholic and drank too much. Alcohol isn’t a small thing to my body. It feels like the scaffolding of my nervous system has a lot of Budweiser, red wine, and Beefeater dry gin in it. I don’t remember my first drink, but I was probably five. I’m told they found me ‘asleep’ in the coat closet after I sneaked around my parents’ holiday party sampling adult refreshments. I was fourteen the first time I got drunk on purpose. My parents had a big party, and I took two beers every hour and hid them behind the furnace (it took me a few years to figure out that I could take all ten at once and no one would notice). The next weekend, after my parents had gone to bed, my best friend and I sat on the floor in the triangle between the couch, the coffee table, and the lazy boy and drank five beers each. I don’t remember what we talked about, but I do remember that we both cried and when I tried to stand up I fell over the lazy boy and threw up on the carpet. I continued drinking heavily until my early 30s when I started teaching yoga. I was living in Afghanistan and a friend asked me to fill in teaching her evening class on the UN compound. It wasn’t at a yoga studio and no one paid. It was just a group of people wanting some yoga. That’s how I justified drinking a gin and tonic before class. I almost fell over demonstrating a triangle pose and I laughed about that with my friends, but the hypocrisy I felt about myself was so excruciating that I started to drink less. Me and my grandmother. By the time I stopped drinking I was 42 and a lot like my great-grandmother, a dedicated one drink a day kind of gal. And what I can see looking back, is that whether I had one drink or five, the pattern was the same. I would spend a lot of time looking forward to it and a lot of energy trying to be cool about that. And then the glorious delight of it finally being time and my body softening at the first sip; my chest lighter and more open, and for a brief moment everything was going to be okay. With a few more sips a daydreamy, floaty mind would creep in and eventually linger into a sleepy, lonely, and slightly checked out feeling. As that wore off, there was only the worry that wouldn’t leave me alone — the part of me that knew my drinking was a problem. And the sad little pit in my stomach. The background hum of shame and melancholy was like the wallpaper in my parent’s bathroom. I didn’t like it, but I also didn’t think about it that much and it never occurred to me that I could change it. And then I got off that tragic little roller coaster that every cell of my being knew so well; and dropped a substance that had been organizing my emotions since long before I was even born. I have experienced every benefit purported in the quit lit: better sleep, better sex, more self-confidence, improved well-being. What I didn’t expect, was no longer needing a vibrator to have an orgasm during sex. My body only ever knew the predictable up and down of life disrupted and controlled by alcohol — and I was sort of free falling without it. And that is what changed my orgasm, the ability to release into the free fall of a life not controlled by a substance. The slow steady build-up of orgasm without a vibrator is terrifying — or it was because that build-up requires me to stay present with something I can’t control and don’t know where it’s going. I was probably thirteen the first time I used a vibrator. My mom was a math teacher and came home one day with a vibrating pen. I remember sneaking into her office with a tingle of excitement and shamefully putting it back exactly as I had found it not too long later. I never questioned the ‘sure-thing’ climax a vibrator provided me. Until all of a sudden, about six months after my last drink, I didn’t want to reach for the predictable outcome of the vibrator. I didn’t plan it or set out to do it. The vibrator just started to feel in the way. And I started being able to stay in my body, to feel my body, to feel safe enough to stay at the pace of my body — with my husband, and his body, and we started having orgasms at the same time. I had never done that before and always wanted to. The unconscious story playing out, “If I can’t control it then I’m not safe” — is true in an alcohol-addicted home. The story that, “I can’t trust myself” is also true with substance use. There is a good reason we shouldn’t use heavy machinery or send important work emails when drinking — we can’t be trusted. I didn’t even know these stories were there, or what they were holding me back from until I stopped using the substance that made them true. Pema Chodron describes addiction as anything we reach for to avoid a feeling we can’t tolerate. The intensity, even when it was exciting and felt good, scared me. And I only needed one drink to keep myself tethered to that deep groove in my nervous system. I grew up believing that hitting rock bottom, face first, was the only reason to stop drinking. That being forced to give up alcohol would be a tragic loss. That I would be bored and alone, white-knuckling my way through a sad little thirsty life. I believed there are alcoholics, who want to drink but can’t because there is something wrong with them; and normal people, who can drink as much as they want and never have a problem. Years ago, a family friend actually said, “I can drink as much as I want because I’m not an alcoholic.” Of course, that isn’t true. Alcohol is an addictive substance, and alcohol addiction is progressive. Just because we find ways to make our lives work around our drinking, doesn’t mean our drinking isn’t a problem or that it’s making us happy. For me, it took losing someone I love to an overdose to finally see alcohol for what it is, an imposter. A toxic and addictive depressant cleverly disguised as happiness. Alcohol wasn’t ruining my life, but it was diminishing it, and I was addicted. And every aspect of my life — including my orgasm — is more wild and free without it. Addiction is progressive and so is sobriety. Slowly, over time, and with repeated experiences we can and do re-pattern our nervous system. I stopped drinking a year ago, but I’ve been working on getting sober for at least a decade, and true sobriety means so much more than the absence of alcohol. It means coming closer to the nature of reality. It means I don’t need things to be more predictable than they are to feel safe. It means I can bake cookies with my kids and not lose my shit. When my four-year-old drops an egg and it feels like things are spiraling out of control and my one-year-old puts his hand in it and that familiar rush of fear and anxiety is so strong, and I feel panicked to make it stop — I can stay a few breaths longer. And sometimes, one year into being free from alcohol, I don’t lose my shit at all. Sometimes it’s genuinely fun. And that is the experience I want to share with three generations — the grounded freedom of true sobriety. If you have that voice that won’t let you alone, wondering if you’re drinking is a problem, I really want you to hear that sobriety is not the prison of boredom mainstream culture would have you believe. Freedom from alcohol means endless nights of deep dream-filled sleep, waking up bright-eyed, sturdy, without a hangover — and if you have them, ready to be more patient and enjoy your kids. You don’t need to be in a ditch bleeding out to decide it’s a good time to stop drinking. And it doesn’t have to be all or nothing. You can just drink a little less and see how it goes. And you don’t have to be addicted or have a family history of addiction for it to be a good idea. My husband stopped drinking before I did because he was training for a 150mile trail run. For him, he just feels better, and that’s enough. Like anything else, you will learn a lot about your relationship with alcohol when you leave it. So why not try and find out? You never know, you might just surprise yourself with a great orgasm.
https://medium.com/an-injustice/life-is-better-without-alcohol-dc5e7ec4ff13
['Meghann Mcniff']
2020-12-28 15:12:20.777000+00:00
['Women', 'Mental Health', 'Addiction', 'Sexuality', 'Health']
Title Life Sex Better Without AlcoholContent stopped drinking last year told expect better sex still surprised happened Photo 31 week pregnant Scott Schell Growing remember greatgrandmother drink every day 4 pm tall glass used drinking milk — 34 red wine 14 water 88th birthday party sitting grass wicker folding chair drink handed chair folded fell ground somehow managed break bone spill drop drink uncle would tell story drink hand laugh hard needed wipe eye heard understood alcohol brings happiness worth sacrificing body protect inherit experience least three generation ancestor DNA three mine Irish Catholic drank much Alcohol isn’t small thing body feel like scaffolding nervous system lot Budweiser red wine Beefeater dry gin don’t remember first drink probably five I’m told found ‘asleep’ coat closet sneaked around parents’ holiday party sampling adult refreshment fourteen first time got drunk purpose parent big party took two beer every hour hid behind furnace took year figure could take ten one would notice next weekend parent gone bed best friend sat floor triangle couch coffee table lazy boy drank five beer don’t remember talked remember cried tried stand fell lazy boy threw carpet continued drinking heavily early 30 started teaching yoga living Afghanistan friend asked fill teaching evening class UN compound wasn’t yoga studio one paid group people wanting yoga That’s justified drinking gin tonic class almost fell demonstrating triangle pose laughed friend hypocrisy felt excruciating started drink le grandmother time stopped drinking 42 lot like greatgrandmother dedicated one drink day kind gal see looking back whether one drink five pattern would spend lot time looking forward lot energy trying cool glorious delight finally time body softening first sip chest lighter open brief moment everything going okay sip daydreamy floaty mind would creep eventually linger sleepy lonely slightly checked feeling wore worry wouldn’t leave alone — part knew drinking problem sad little pit stomach background hum shame melancholy like wallpaper parent’s bathroom didn’t like also didn’t think much never occurred could change got tragic little roller coaster every cell knew well dropped substance organizing emotion since long even born experienced every benefit purported quit lit better sleep better sex selfconfidence improved wellbeing didn’t expect longer needing vibrator orgasm sex body ever knew predictable life disrupted controlled alcohol — sort free falling without changed orgasm ability release free fall life controlled substance slow steady buildup orgasm without vibrator terrifying — buildup requires stay present something can’t control don’t know it’s going probably thirteen first time used vibrator mom math teacher came home one day vibrating pen remember sneaking office tingle excitement shamefully putting back exactly found long later never questioned ‘surething’ climax vibrator provided sudden six month last drink didn’t want reach predictable outcome vibrator didn’t plan set vibrator started feel way started able stay body feel body feel safe enough stay pace body — husband body started orgasm time never done always wanted unconscious story playing “If can’t control I’m safe” — true alcoholaddicted home story “I can’t trust myself” also true substance use good reason shouldn’t use heavy machinery send important work email drinking — can’t trusted didn’t even know story holding back stopped using substance made true Pema Chodron describes addiction anything reach avoid feeling can’t tolerate intensity even exciting felt good scared needed one drink keep tethered deep groove nervous system grew believing hitting rock bottom face first reason stop drinking forced give alcohol would tragic loss would bored alone whiteknuckling way sad little thirsty life believed alcoholic want drink can’t something wrong normal people drink much want never problem Years ago family friend actually said “I drink much want I’m alcoholic” course isn’t true Alcohol addictive substance alcohol addiction progressive find way make life work around drinking doesn’t mean drinking isn’t problem it’s making u happy took losing someone love overdose finally see alcohol imposter toxic addictive depressant cleverly disguised happiness Alcohol wasn’t ruining life diminishing addicted every aspect life — including orgasm — wild free without Addiction progressive sobriety Slowly time repeated experience repattern nervous system stopped drinking year ago I’ve working getting sober least decade true sobriety mean much absence alcohol mean coming closer nature reality mean don’t need thing predictable feel safe mean bake cooky kid lose shit fouryearold drop egg feel like thing spiraling control oneyearold put hand familiar rush fear anxiety strong feel panicked make stop — stay breath longer sometimes one year free alcohol don’t lose shit Sometimes it’s genuinely fun experience want share three generation — grounded freedom true sobriety voice won’t let alone wondering you’re drinking problem really want hear sobriety prison boredom mainstream culture would believe Freedom alcohol mean endless night deep dreamfilled sleep waking brighteyed sturdy without hangover — ready patient enjoy kid don’t need ditch bleeding decide it’s good time stop drinking doesn’t nothing drink little le see go don’t addicted family history addiction good idea husband stopped drinking training 150mile trail run feel better that’s enough Like anything else learn lot relationship alcohol leave try find never know might surprise great orgasmTags Women Mental Health Addiction Sexuality Health
2,868
Trigger Warnings Help Me Deal With Trauma In My Own Time
Trigger Warnings Help Me Deal With Trauma In My Own Time How one website has helped me process traumatic incidents Photo by Colby Ray on Unsplash Trigger warnings have been much maligned as of late. They’ve been described as indicative of a “snowflake generation”, too scared to see anything mildly unpleasant, cocooned in cotton-wool by over-zealous parents. But trigger warnings have really helped me deal with the traumatic thing that happened to me. A trigger warning (often shortened to ‘TW’) is a kind of advance notice of a potentially traumatic image or phrase occurring in a film or literature. There are varied responses to the idea of a trigger warning. Urban Dictionary (arguably the encyclopedia of the youth) shows a polarization in views between people; the ‘top definition’ at the time of writing applauds trigger warnings, described them as ‘a warning before showing something that could cause a PTSD reaction. Commonly used as a joke, its meaning has unfortunately depreciated, drawing more stigma to mental illness.’ Another, however, takes a wholly negative view of the trigger warning — describing them as ‘a phrase posted at the beginning of various posts, articles, or blogs. Its purpose is to warn weak-minded people who are easily offended that they might find what is being posted offensive in some way due to its content, causing them to overreact […] trigger warnings are unnecessary 100% of the time due to the fact that people who are easily offended have no business randomly browsing the internet anyways. As a result of the phrases irrelevance, most opinions that start out with this phrase tend to be simplistic and dull since they were made by people ridiculous enough to think that the internet is supposed to cater to people who can’t take a joke.’ I don’t see it this way. Trigger warnings have really helped me. I use a site called DoesTheDogDie.com; a place where trigger warnings are given for material that could be sensitive to some eyes. The website scours various forms of media and assesses the content. It’s founded on the goodwill of users. I’ve found it to be a life-saver. I was in a psychiatric hospital a few years ago after everything with me, mental health-wise, reached a crisis. I had experienced a traumatic sexual assault when I was a teenager, and I had pushed the experience down deep inside me. I had barely thought about it. Then, a similar kind of thing happened again around consent — a male friend was very drunk, and I tried to push him away. He tried to kiss me because he thought I was his girlfriend. I completely broke. I remember crying after it happened, and someone stopping me in the street to ask if I was okay. I wasn’t. I ended up self-harming voraciously; daily burning myself or cutting the soles of my feet. I was binging and purging sometimes up to six times a day. I had to pour dishwashing liquid over the food I’d thrown out. It was intolerable. I ended up being sectioned under the UK’s Mental Health Act, and I was inside a psychiatric institution for a fortnight. While I was there, a healthcare assistant backed me up against the floor while she screamed at me. I was scrambling around on the floor like a dog. My parents traveled six hours north to visit me, where they would only stay for half-an-hour or so; they said they had to get back on the road, but I knew that they found it too upsetting. My father, a man who is normally very Stoic by nature, cried when he saw me in the hospital. I’d never seen him cry before, and I’ve never seen him cry since — and I’ll be twenty-five next year. My heart broke a little as I saw his eyes fill and a single, solitary tear trickle down his cheek. I didn’t magically get better upon leaving the hospital (as some people think), but that’s a story for another time. The important thing is that talking about mental illness became very distressing for me. Watching suicide attempts on screen left me squirming in my seat and sometimes in tears. I also found it hard to see images of psychiatric hospitals. It became incredibly tough to sit down and watch a movie with my family without worrying that there would be a scene that would make me feel distressed in it. I was already struggling with a Generalized Anxiety Disorder. I struggle with relaxing. When I’m thinking about self-care and what routines to implement in my daily life, there are often suggestions on the internet of ‘doing things to relax you’ — to which I think, “well how am I meant to do that?” So dealing with relaxation is something I really struggle with. I can’t deal with doing nothing; I start to feel guilty, I start to feel like I need to be doing something productive. Trying to relax and watch a film is stressful enough. But this is where DoesTheDogDie.com comes in; it offers warnings as to the potentially triggering material in over 7,000 movies, TV shows, books, and video games. The first question on every page is “Does the dog die?” Apparently, that used to be the only question. Creator John Whipple told Lifehacker that the site was originally his sister’s idea, “She found it frustrating to watch a movie with a dog in it because worrying over the survival of the dog made it impossible to enjoy the movie.” Now it’s expanded to cover a wide range of issues, like films with strobe effects, books where a parent dies, violence, self-harm, and torture, to TV shows where Santa is revealed to be a fictional character. Some questions aren’t covered, like “Is someone sexually assaulted?”, linking to the site Unconsenting Media, which meticulously tracks sexual violence in various media forms. But over 70 categories are covered, and that’s helped me deal with the awkwardness of an unsuspecting scene that could provoke a traumatic response in me and a general awkwardness with my family. Sure, things have got a little better since; I hardly use the site now, as I’m a lot less prone to traumatic responses. But I’m slowly tapering down from my medication, and so I’m aware that I can become triggered a little easier at the moment. I’ve found trigger warnings to be really helpful when I’m recovering from traumatic past incidents. I understand that some people can find trigger warnings unnecessary. But if that’s you, then — congratulations — you don’t need to use them. Scroll past that TW to your heart’s content. But for those of us who do need trigger warnings, it can save us an unnecessary amount of heartache. It’s not about completely avoiding everything that might upset me or trigger me. It’s about dealing with those trauma-inducing situations safely with a professional, like a therapist. I’m currently doing CBT-E, and I’m addressing some of the traumatic things that happened to be there. For people who really need them, trigger warnings are so important.
https://medium.com/invisible-illness/how-trigger-warnings-help-me-deal-with-my-trauma-1d0193ae7cec
['Lizzie Bestow']
2020-09-05 21:41:05.914000+00:00
['Health', 'Trauma', 'Life', 'Mental Health', 'Life Lessons']
Title Trigger Warnings Help Deal Trauma TimeContent Trigger Warnings Help Deal Trauma Time one website helped process traumatic incident Photo Colby Ray Unsplash Trigger warning much maligned late They’ve described indicative “snowflake generation” scared see anything mildly unpleasant cocooned cottonwool overzealous parent trigger warning really helped deal traumatic thing happened trigger warning often shortened ‘TW’ kind advance notice potentially traumatic image phrase occurring film literature varied response idea trigger warning Urban Dictionary arguably encyclopedia youth show polarization view people ‘top definition’ time writing applauds trigger warning described ‘a warning showing something could cause PTSD reaction Commonly used joke meaning unfortunately depreciated drawing stigma mental illness’ Another however take wholly negative view trigger warning — describing ‘a phrase posted beginning various post article blog purpose warn weakminded people easily offended might find posted offensive way due content causing overreact … trigger warning unnecessary 100 time due fact people easily offended business randomly browsing internet anyways result phrase irrelevance opinion start phrase tend simplistic dull since made people ridiculous enough think internet supposed cater people can’t take joke’ don’t see way Trigger warning really helped use site called DoesTheDogDiecom place trigger warning given material could sensitive eye website scour various form medium ass content It’s founded goodwill user I’ve found lifesaver psychiatric hospital year ago everything mental healthwise reached crisis experienced traumatic sexual assault teenager pushed experience deep inside barely thought similar kind thing happened around consent — male friend drunk tried push away tried kiss thought girlfriend completely broke remember cry happened someone stopping street ask okay wasn’t ended selfharming voraciously daily burning cutting sol foot binging purging sometimes six time day pour dishwashing liquid food I’d thrown intolerable ended sectioned UK’s Mental Health Act inside psychiatric institution fortnight healthcare assistant backed floor screamed scrambling around floor like dog parent traveled six hour north visit would stay halfanhour said get back road knew found upsetting father man normally Stoic nature cried saw hospital I’d never seen cry I’ve never seen cry since — I’ll twentyfive next year heart broke little saw eye fill single solitary tear trickle cheek didn’t magically get better upon leaving hospital people think that’s story another time important thing talking mental illness became distressing Watching suicide attempt screen left squirming seat sometimes tear also found hard see image psychiatric hospital became incredibly tough sit watch movie family without worrying would scene would make feel distressed already struggling Generalized Anxiety Disorder struggle relaxing I’m thinking selfcare routine implement daily life often suggestion internet ‘doing thing relax you’ — think “well meant that” dealing relaxation something really struggle can’t deal nothing start feel guilty start feel like need something productive Trying relax watch film stressful enough DoesTheDogDiecom come offer warning potentially triggering material 7000 movie TV show book video game first question every page “Does dog die” Apparently used question Creator John Whipple told Lifehacker site originally sister’s idea “She found frustrating watch movie dog worrying survival dog made impossible enjoy movie” it’s expanded cover wide range issue like film strobe effect book parent dy violence selfharm torture TV show Santa revealed fictional character question aren’t covered like “Is someone sexually assaulted” linking site Unconsenting Media meticulously track sexual violence various medium form 70 category covered that’s helped deal awkwardness unsuspecting scene could provoke traumatic response general awkwardness family Sure thing got little better since hardly use site I’m lot le prone traumatic response I’m slowly tapering medication I’m aware become triggered little easier moment I’ve found trigger warning really helpful I’m recovering traumatic past incident understand people find trigger warning unnecessary that’s — congratulation — don’t need use Scroll past TW heart’s content u need trigger warning save u unnecessary amount heartache It’s completely avoiding everything might upset trigger It’s dealing traumainducing situation safely professional like therapist I’m currently CBTE I’m addressing traumatic thing happened people really need trigger warning importantTags Health Trauma Life Mental Health Life Lessons
2,869
5 Untouched Writing Genres You Can Opt For
5 Untouched Writing Genres You Can Opt For Philosophy with fiction can be a good combination, learn how. Photo by Ella Jardim on Unsplash Writing genres are various categories in which your writing can fall. While some genres have grown with their writers and readers over time, others are probably not even heard of. Some of the prominent genres that have gained attention over time include: Poetry History Short story Narrative Biography Self-improvement Fiction including romance, Horror, sci-fi, crime, fantasy. But there are some equally fascinating genres that are like the roads less traveled by. Some of them were limited to a time period in history and have lost their imprints in today’s world. While others could not gain much traction due to other lesser-known reasons. In this article, I am going to talk about 5 such writing genres that could be added to your list. Even though they are chosen by relatively fewer people, this doesn't conclude that they are difficult to write in. So let's get started:
https://medium.com/the-brave-writer/5-untouched-writing-genres-you-can-opt-for-32f179168d69
['Niyati Jain']
2020-12-10 13:02:02.707000+00:00
['Creativity', 'Work', 'Self Improvement', 'Freelancing', 'Writing']
Title 5 Untouched Writing Genres Opt ForContent 5 Untouched Writing Genres Opt Philosophy fiction good combination learn Photo Ella Jardim Unsplash Writing genre various category writing fall genre grown writer reader time others probably even heard prominent genre gained attention time include Poetry History Short story Narrative Biography Selfimprovement Fiction including romance Horror scifi crime fantasy equally fascinating genre like road le traveled limited time period history lost imprint today’s world others could gain much traction due lesserknown reason article going talk 5 writing genre could added list Even though chosen relatively fewer people doesnt conclude difficult write let get startedTags Creativity Work Self Improvement Freelancing Writing
2,870
How To Use A Book To Build A Career Or Business
How To Use A Book To Build A Career Or Business A book will help you stand out Imagine meeting the person who can impact your career big time. Maybe it’s an angel investor for your start-up or a corporate executive who can get you some major consulting or public speaking projects. What can you give them, to effectively communicate that you’re worth listening to? A business card? A resume? Most people throw that stuff away as soon as you give it to them. They’ll move on and forget about you. Or let’s say you want to grow your business. Why would a stranger give you money for your products or services? Why would they trust you? No one likes to chase clients and get people for their business. This is where a book comes in. A book communicates that: You’re who had the idea and insight to write a book, Not everyone can start, finish, and publish a book — but you did; This means the book is proof you know what you’re talking about, plus you can execute. Everybody has a business card and a resume. And every business has a website. But compared to the masses, only a few people have a book. Of course, simply having a book won’t get you there. Your book has to actually deliver its message properly and persuasively; otherwise you’ll lose the credibility you’re trying to build. So how do you publish a book to build a career or business? Be Clear About Your Goals Every book has a purpose and a message. If your book has nothing to do with your professional field it won’t help your career at all. Imagine a sales trainer who would write about yoga. Nothing wrong with both topics, but there’s no match between your profession and your book in that case. So think of your goal first. Want to sell books and make money from book royalties? Or do you want to sell consulting, courses, apps, you name it? You have to be clear about the goal of your work, including the kind of people that you’re writing it for. This article is for people who want the latter. Remember that on average, nonfiction books sell less than 500 copies in a year. There are authors who couldn’t even reach the industry average, while best selling authors like the late Stephen Covery have sold millions of books. Price’s Law applies here too. Only a handful of people generate the majority of book sales. That’s why your book’s message and purpose has to be very clear from the start. To be honest, I’m definitely not part of the minority that generates the majority of the sales in the book business. And that’s totally fine. Accepting that will only make your career or business more successful. Write Something That Genuinely Helps A book’s main selling point is an effectively communicated idea. Consultants, public speakers and coaches are all there to help a specific niche of people. Keep this in mind when you’re writing your book: don’t write for everyone. Your personality, style of writing and solutions won’t work for everyone. Hitting too broad or too narrow will get you nowhere, so focus instead on giving a unique solution to a general problem. Remember the scenario when you give your book to a potential client/investor/business partner? Think of your book as an answer to your target audience’s perceived problems. This is why you should talk about the things you know best. It’s always about leveraging your strengths to solve other people’s problems. Your book serves as an initial impression of your skills and expertise. I believe this is the only way you can demonstrate your worth. No one cares about promises and what you want to do. Show it! This brings us to the next point. Establish Your Credibility There are plenty of experts in the world with shiny business cards and fancy websites. If you want to be a high-demand consultant, public speaker, or personal coach, your book helps you stand out from the crowd. There’s a reason why bloggers, interviewers, journalists want to talk to the “person who wrote the book” about a topic. A book not only shows that you have the concentration, dedication, and focus to get something done. It also establishes your status as an expert in your field. Nowadays, it’s almost an almost a necessity for panel experts or public speakers to have published at least a book or two, to be considered as a real specialist in the field. We’ve got to be honest about this. So remember to write your book well. Remember to be honest about what you say (you don’t want to have a reputation of being sleazy), keep your stories personal, clear and to the point, and research your facts right. Create and Attract Opportunities Here’s what I learned about the nonfiction book business: Don’t focus on book sales. Why? Because it’s all a matter of getting your book in front of the few people who can truly impact your business. My first book sold about 20–30 copies a month. The royalties were a few bucks a month. Most people will not be able to earn a good living from book royalties. But that book helped me to create many different opportunities as a trainer, earning six figures. Even now that I have a bigger audience, my book sales are good for about 7% of my revenue. You see, it’s not about book sales. With your book out there, you can reach the attention of people who are both consciously and unconsciously looking for what you have to say or the services that you offer. This is especially true for technical experts. You’re unlikely to reach busy executives or company heads using social media ads. So when you write your book, don’t think too much about book sales. Instead, focus on how your books will attract the right opportunities. Books Are Forever The great thing about writing a book is that often, your book can far outlast you. Peter Drucker passed away years ago (2005), yet his ideas are still being used in many progressive companies all over the world. How crazy is that? Think about the potential impact you can have with a book. This is the true power of books: They immortalize our ideas and stories, farther than our own lifespan can ever reach. It’s all about creating a lasting impact on people’s lives. So when you’re writing a book to build a business, always think about this: How can you change your reader’s life? Answer that, and you’ll book will take care of the rest. You just have to write it first.
https://medium.com/darius-foroux/how-to-use-a-book-to-build-a-career-or-business-194f200dd39a
['Darius Foroux']
2020-09-08 11:47:40.464000+00:00
['Business', 'Books', 'Careers', 'Writer', 'Writing']
Title Use Book Build Career BusinessContent Use Book Build Career Business book help stand Imagine meeting person impact career big time Maybe it’s angel investor startup corporate executive get major consulting public speaking project give effectively communicate you’re worth listening business card resume people throw stuff away soon give They’ll move forget let’s say want grow business would stranger give money product service would trust one like chase client get people business book come book communicates You’re idea insight write book everyone start finish publish book — mean book proof know you’re talking plus execute Everybody business card resume every business website compared mass people book course simply book won’t get book actually deliver message properly persuasively otherwise you’ll lose credibility you’re trying build publish book build career business Clear Goals Every book purpose message book nothing professional field won’t help career Imagine sale trainer would write yoga Nothing wrong topic there’s match profession book case think goal first Want sell book make money book royalty want sell consulting course apps name clear goal work including kind people you’re writing article people want latter Remember average nonfiction book sell le 500 copy year author couldn’t even reach industry average best selling author like late Stephen Covery sold million book Price’s Law applies handful people generate majority book sale That’s book’s message purpose clear start honest I’m definitely part minority generates majority sale book business that’s totally fine Accepting make career business successful Write Something Genuinely Helps book’s main selling point effectively communicated idea Consultants public speaker coach help specific niche people Keep mind you’re writing book don’t write everyone personality style writing solution won’t work everyone Hitting broad narrow get nowhere focus instead giving unique solution general problem Remember scenario give book potential clientinvestorbusiness partner Think book answer target audience’s perceived problem talk thing know best It’s always leveraging strength solve people’s problem book serf initial impression skill expertise believe way demonstrate worth one care promise want Show brings u next point Establish Credibility plenty expert world shiny business card fancy website want highdemand consultant public speaker personal coach book help stand crowd There’s reason blogger interviewer journalist want talk “person wrote book” topic book show concentration dedication focus get something done also establishes status expert field Nowadays it’s almost almost necessity panel expert public speaker published least book two considered real specialist field We’ve got honest remember write book well Remember honest say don’t want reputation sleazy keep story personal clear point research fact right Create Attract Opportunities Here’s learned nonfiction book business Don’t focus book sale it’s matter getting book front people truly impact business first book sold 20–30 copy month royalty buck month people able earn good living book royalty book helped create many different opportunity trainer earning six figure Even bigger audience book sale good 7 revenue see it’s book sale book reach attention people consciously unconsciously looking say service offer especially true technical expert You’re unlikely reach busy executive company head using social medium ad write book don’t think much book sale Instead focus book attract right opportunity Books Forever great thing writing book often book far outlast Peter Drucker passed away year ago 2005 yet idea still used many progressive company world crazy Think potential impact book true power book immortalize idea story farther lifespan ever reach It’s creating lasting impact people’s life you’re writing book build business always think change reader’s life Answer you’ll book take care rest write firstTags Business Books Careers Writer Writing
2,871
Plotly Express: the Good, the Bad, and the Ugly
Plotly Express: the Good, the Bad, and the Ugly It might be newer, but is it better? Creating effective data visualizations is a very important part of data science from the beginning to the end of the data science process. Using visualizations during your exploratory data analysis is a great way to get a good idea of what your data is about. Creating visualizations at the end of your project is a great way to communicate your findings in an easy-to-understand way. There are so many different tools for data visualization in Python, from cult favorites like Matplotlib and Seaborn, to the newly-released Plotly Express. All three are pretty simple to use, and don’t require a lot of in-depth programming knowledge, but how do you decide which one to use? What is Plotly Express? If you’ve ever used Plotly, or even just looked at code written to use Plotly, you know that it’s definitely not the simplest library to use for visualizations. That’s where Plotly Express comes in. Plotly Express is a high-level wrapper for Plotly, which essentially means it does a lot of the things that you can do it Plotly with a much simpler syntax. It is pretty easy to use, and doesn’t require connecting your file to Plotly or specifying that you want to work with Plotly offline. After Plotly Express is installed, a simple import plotly_express as px is all you need to start creating simple, interactive visualizations with Python. The Good There are several advantages to using Plotly Express to create visualizations. The entire visualization can be created with one line of code (kind of). px.scatter(df, x='ShareWomen', y = 'Median', color = 'Major_category', size = 'Total', size_max = 40, title = 'Median Salary vs Share of Women in a Major', color_discrete_sequence = px.colors.colorbrewer.Paired, hover_name = 'Major' While it technically took 6 lines to create this, it still only took a single command. In creating a Plotly Express visualization, everything can be done in the same command, from adjusting the size of the graphic, to the colors it uses, to the axes labels. In my opinion, Plotly Express is the easiest way to quickly create and modify a visualization. Also, the visualization is automatically interactive, which brings me to my next point. It’s interactive. A mouseover of a specific point will bring up a box that has any of the information that was used to create the graph, as well as any extra information you want to include. In this particular graph, including hover_name = 'Major' made the specific major the point was referring to the title of each box. This allows us to get a lot of information out of our graphic that we wouldn’t be able to get otherwise. Additionally, we can also see what the two largest majors are, which we were unable to do when creating a similar plot using Seaborn. You can isolate certain information. Clicking a category in the legend of the visualization twice will isolate that category so it is the only one we can see in the graphic. Clicking it once will remove that category, so we can see all of the categories with the exception of that one. If you want to zoom in on a certain area, all you have to do is click and drag to create a rectangle that encompasses the smaller are you want examine more closely. You can animate change. One of the coolest features available with Plotly Express is the ability to add an animation frame. By doing so, you allow yourself to view how something changes over a certain variable. Most often, the animation frame is based on year, so you can visualize how something changes over time. Not only is this cool to see as you’re creating visualizations for yourself, but being able to create an animated AND interactive visualization seriously make you look like you know what you’re doing. The Bad It doesn’t have ton of features. Don’t get me wrong, there is a LOT you can do with Plotly express. It just doesn’t have as many options when it comes to adjusting the appearance of your graph. In Seaborn, for example, you can change the why the points on your categorical scatterplot line up by changing things like jitter = False and kind = 'swarm' . To my knowledge, neither of these are possible using Plotly Express. This really isn’t the end of the world, especially considering that one of the main goals of Plotly Express was to allow users to quickly and easily create interactive visualizations while performing exploratory data analysis. I would guess that most people using it for this purpose don’t care too much about how their points are lined up on their scatter plot. You need to set the color every single time you create a new graph. # Seaborn sns.catplot(x = 'Major_category', y = 'Median', kind = 'box', data = df) plt.xticks(rotation = 90) plt.show() # Plotly Express px.box(df, x = "Major_category", y = 'Median', hover_name = 'Major') You would expect both of these to create very similar visualizations, and they do (for the most part).
https://towardsdatascience.com/plotly-express-the-good-the-bad-and-the-ugly-dc941649687c
['Reilly Meinert']
2019-06-14 22:37:59.678000+00:00
['Python', 'Data Science', 'Plotly', 'Data Visualization']
Title Plotly Express Good Bad UglyContent Plotly Express Good Bad Ugly might newer better Creating effective data visualization important part data science beginning end data science process Using visualization exploratory data analysis great way get good idea data Creating visualization end project great way communicate finding easytounderstand way many different tool data visualization Python cult favorite like Matplotlib Seaborn newlyreleased Plotly Express three pretty simple use don’t require lot indepth programming knowledge decide one use Plotly Express you’ve ever used Plotly even looked code written use Plotly know it’s definitely simplest library use visualization That’s Plotly Express come Plotly Express highlevel wrapper Plotly essentially mean lot thing Plotly much simpler syntax pretty easy use doesn’t require connecting file Plotly specifying want work Plotly offline Plotly Express installed simple import plotlyexpress px need start creating simple interactive visualization Python Good several advantage using Plotly Express create visualization entire visualization created one line code kind pxscatterdf xShareWomen Median color Majorcategory size Total sizemax 40 title Median Salary v Share Women Major colordiscretesequence pxcolorscolorbrewerPaired hovername Major technically took 6 line create still took single command creating Plotly Express visualization everything done command adjusting size graphic color us ax label opinion Plotly Express easiest way quickly create modify visualization Also visualization automatically interactive brings next point It’s interactive mouseover specific point bring box information used create graph well extra information want include particular graph including hovername Major made specific major point referring title box allows u get lot information graphic wouldn’t able get otherwise Additionally also see two largest major unable creating similar plot using Seaborn isolate certain information Clicking category legend visualization twice isolate category one see graphic Clicking remove category see category exception one want zoom certain area click drag create rectangle encompasses smaller want examine closely animate change One coolest feature available Plotly Express ability add animation frame allow view something change certain variable often animation frame based year visualize something change time cool see you’re creating visualization able create animated interactive visualization seriously make look like know you’re Bad doesn’t ton feature Don’t get wrong LOT Plotly express doesn’t many option come adjusting appearance graph Seaborn example change point categorical scatterplot line changing thing like jitter False kind swarm knowledge neither possible using Plotly Express really isn’t end world especially considering one main goal Plotly Express allow user quickly easily create interactive visualization performing exploratory data analysis would guess people using purpose don’t care much point lined scatter plot need set color every single time create new graph Seaborn snscatplotx Majorcategory Median kind box data df pltxticksrotation 90 pltshow Plotly Express pxboxdf x Majorcategory Median hovername Major would expect create similar visualization partTags Python Data Science Plotly Data Visualization
2,872
Inventing Enemies
It’s easy to imagine a regular season NBA game without fans; playoff seeding or the perceived slight of an opponent are usually all that elevate mid-season contests above glorified pickup basketball. But what about a game that matters? And what about home court advantage? If the NBA decides to finish out the season without real crowds, they should seriously consider ways to enhance the experience not just for the fans at home but for the players as well. “I play for the fans,” LeBron James said recently, before the severity of the situation became apparent around the league, “That’s what it’s all about. If I show up to an arena and there are no fans in there, I ain’t playing.” It’s not just home fans that matter for the players either. A huge part of the narrative of greatness in sports is tied to how one performs in enemy territory. If you look back to some of the most oft-cited “clutch” performances in NBA history, they often came on the road; Magic in Philadelphia in 1980, Jordan in Utah in 1998, Lebron in Boston in 2012, Klay Thompson in OKC in 2016. The list goes on. There needs to be real fan energy not just for aesthetics, but to push the stakes to another level. Clutch Performances Often Come on the Road My former colleagues at Populous have spent their entire careers designing venues that bring people together and I’m very interested to see what they do when challenged with the task of making the fan experience a long-distance relationship. It may not be a question of doing something new but rather absorbing innovations in interactive entertainment that have already been successful. There’s a lot to be learned from online video games, from the way platforms like Twitch engage their audiences to how games like Second Life allow players an open-ended virtual experience in which to interact with others they may not normally be able to reach. Online Games Provide a Template for Virtual Fans The NBA seeks out innovation, and as such they have been broadcasting games in Virtual Reality since 2016. During VR broadcasts you can connect with others watching the game and even customize an avatar. Still, the experience seems a work in progress and often utilizes vantages (courtside, directly behind the basket) out of alignment with the typical fan experience. Regarding socializing with others during the game it is not on the level of a Second Life, where anyone who is online is in a space with everyone else who has logged on. The NBA has Broadcast in VR since 2016 Perhaps the next step in this time of empty arenas is a VR camera in every seat. One could imagine a scenario similar to avatar based online meeting platforms where people can interact with each other in a digitized version of the concourse. To avoid hundreds of avatars running around obstructing the game, when someone enters the seating bowl they immediately find themselves in the seat they purchased a ticket for, next to other fans who purchased tickets for the specific seats next to them. They can watch the game in 360 degrees from their seat and also get the full experience of interacting with those around them in the crowd. Some might find it hard to believe people would pay not to be courtside, but there are a lot of people right now craving something familiar. If the cost tag of tens of thousands of VR cameras seems prohibitive there is no reason it couldn’t be done with a thousand or a few hundred seats, or only for playoff games that generate more revenue, with the individual VR seats sold at a cost that makes such an endeavor financially worthwhile. And if the idea of spending a higher amount of money for a better virtual seat seems crazy to you, just remember at one point Candy Crush was making $230 million a year solely off in-game upgrades. Virtual Meetings are Becoming More Prevalent; What About Virtual Fans? The in-game experience for the players could utilize the same digital interface in a completely different way. Think of something akin to an upside-down planetarium; a large projector sits a hundred feet above the court projecting on to perforated screens with speakers behind them. If you set up the interface so that the fans can use their actual voices like players live streaming on Twitch, and then calibrate the sound so that it correlates to where fans’ avatars are being projected on the screen, suddenly you have real fans surrounding the court making real noise. They would be free to heckle or cheer as much as they would at a real game, their only limitations being the same rules of conduct that they would be held to in person. A Planetarium Provides the Template No one is saying any of this would be ideal. But what is these days? The NBA is as creative and innovative as any league out there. They have consistently been at the forefront of not only VR but relaxing copyright restrictions so regular fans can post highlights on websites like YouTube, a policy which has been a huge asset in helping the league grow on social media platforms (people watch 30,000 hours of Steph Curry clips on YouTube every day). The league has already turned tragedy into innovation once this year, paying tribute to Kobe Bryant while experimenting with the “Elam Ending” at the 2020 All-Star game. Now, as the league tries to salvage the rest of the season, it’s not only possible for the NBA to do something significant with virtual fans, it might be more feasible than playing in front of real ones.
https://medium.com/paper-architecture/inventing-enemies-dc653f2b5d63
['Dan Edleson']
2020-03-18 20:54:32.743000+00:00
['Virtual Reality', 'NBA Playoffs', 'Design', 'NBA', 'Coronavirus']
Title Inventing EnemiesContent It’s easy imagine regular season NBA game without fan playoff seeding perceived slight opponent usually elevate midseason contest glorified pickup basketball game matter home court advantage NBA decides finish season without real crowd seriously consider way enhance experience fan home player well “I play fans” LeBron James said recently severity situation became apparent around league “That’s it’s show arena fan ain’t playing” It’s home fan matter player either huge part narrative greatness sport tied one performs enemy territory look back oftcited “clutch” performance NBA history often came road Magic Philadelphia 1980 Jordan Utah 1998 Lebron Boston 2012 Klay Thompson OKC 2016 list go need real fan energy aesthetic push stake another level Clutch Performances Often Come Road former colleague Populous spent entire career designing venue bring people together I’m interested see challenged task making fan experience longdistance relationship may question something new rather absorbing innovation interactive entertainment already successful There’s lot learned online video game way platform like Twitch engage audience game like Second Life allow player openended virtual experience interact others may normally able reach Online Games Provide Template Virtual Fans NBA seek innovation broadcasting game Virtual Reality since 2016 VR broadcast connect others watching game even customize avatar Still experience seems work progress often utilizes vantage courtside directly behind basket alignment typical fan experience Regarding socializing others game level Second Life anyone online space everyone else logged NBA Broadcast VR since 2016 Perhaps next step time empty arena VR camera every seat One could imagine scenario similar avatar based online meeting platform people interact digitized version concourse avoid hundred avatar running around obstructing game someone enters seating bowl immediately find seat purchased ticket next fan purchased ticket specific seat next watch game 360 degree seat also get full experience interacting around crowd might find hard believe people would pay courtside lot people right craving something familiar cost tag ten thousand VR camera seems prohibitive reason couldn’t done thousand hundred seat playoff game generate revenue individual VR seat sold cost make endeavor financially worthwhile idea spending higher amount money better virtual seat seems crazy remember one point Candy Crush making 230 million year solely ingame upgrade Virtual Meetings Becoming Prevalent Virtual Fans ingame experience player could utilize digital interface completely different way Think something akin upsidedown planetarium large projector sits hundred foot court projecting perforated screen speaker behind set interface fan use actual voice like player live streaming Twitch calibrate sound correlate fans’ avatar projected screen suddenly real fan surrounding court making real noise would free heckle cheer much would real game limitation rule conduct would held person Planetarium Provides Template one saying would ideal day NBA creative innovative league consistently forefront VR relaxing copyright restriction regular fan post highlight website like YouTube policy huge asset helping league grow social medium platform people watch 30000 hour Steph Curry clip YouTube every day league already turned tragedy innovation year paying tribute Kobe Bryant experimenting “Elam Ending” 2020 AllStar game league try salvage rest season it’s possible NBA something significant virtual fan might feasible playing front real onesTags Virtual Reality NBA Playoffs Design NBA Coronavirus
2,873
To Make Better Decisions
To Make Better Decisions Assign Rights, Describe Processes, Set Criteria, Experiment In Does Your Company Know How It Makes Decisions? I pointed out that most people have no idea how decisions get made within their own organizations, and as a consequence the organizations lack decision-making skills. While I claimed that there were better processes available than “consensus,” I didn’t specify what those might be, or how to design them to replace the ineffective, bureaucratic, political waste of energy that constitutes most organizational decision-making processes in American organizations. Now is a good time to correct this oversight. What is a decision? Although people probably make hundreds of decisions a day, few have thought about, or are able to describe, what constitutes a decision. Ask a dozen people in your company, and several of them are going to tell you something like, “A decision is when you make up your mind about something. It’s when you make a choice, from among several different alternatives.” But choices are prerequisites to a decision. They might provide some satisfaction of relieving uncertainty or anxiety, but they are not decisions. A decision is an irreversible commitment of resources. It’s not a decision when my niece makes a declaration at the family holiday picnic, “I’ve decided I’m moving to New York to pursue a new career as an actress!” Although her relatives might cheer her on and make encouraging noises, until she commits resources (time, energy, money) that create opportunity costs, her declaration is a fantasy, not a decision. To elevate her career aspirations from her imagination to reality, she must make commitments that will be difficult to undo. For example, she might sign a lease on an new apartment and pay a security deposit, strengthening her decision to move. She might audition for roles, committing time, energy, and putting herself at risk of rejection, to strengthen her decision to pursue a new vocation. Her problem is that making public declarations of intent is much more rewarding, with less effort, than an irreversible commitment of resources. Too many business managers are like my niece. They fantasize out loud about their aspirations, or make solemn declarations about change, but they never commit resources. They want the temporary satisfaction of a false resolve, so they announce public resolutions that reward their brains with the dope hit of false accomplishment, without incurring the expense, sacrifice, or risks of making commitments. It’s not a decision until you’ve made an irreversible commitment of resources. Who in your organization gets to make decisions? As organizations grow, they become further and further removed from the people who founded them. The problem is that the people who founded the organization have excellent judgment about what constitutes a good idea (or the organization would never have succeeded), and the people who join the organization as it grows do not. And how did these wise organizational Founders develop their excellent judgment? Typically, by making and learning from many mistakes. Then, once the organization figures out what’s working and it becomes profitable and growing, the patience for mistakes wears thin, and institutional controls creep in to reduce the possibility of errors. We call these controls “bureaucracy” and it is this system of policies and procedures that constitute and enforce these controls. Bureaucracies substitute rules for judgment. The problem with error-minimizing bureaucracies is that so few people in the organization are permitted to make the mistakes necessary to develop their own excellent judgment, as the entire organization becomes preoccupied learning and conforming to the rules. In bureaucratic organizations, their are few decision makers, because the policies, processes, and rules remove alternatives. For example, in No Rules Rules: Netflix and the Culture of Reinvention (Hastings & Meyer 2020) Netflix CEO Reed Hastings tells a story about an executive at one of Hasting’s earlier companies who was infuriated by a travel policy that refused to reimburse him for a $12 taxi fare. The travel expense refusal wasn’t a decision made by an individual at the company. It was a rule that absolved any travel account manager from the responsibility of exercising judgment. And there were no compensating rules that empowered anyone in the organizations to override it! Most bureaucracies do not allow decision making. They operate by approval, in which managers at upper levels review resource allocations to ensure that they comply with policies. Eventually, you get a corporate culture like the one satirized in the 1985 movie Head Office. To make better decisions, organizations must assign decision-making rights to the people in the organization and foster an environment that encourages them to experiment, make mistakes, receive feedback, and improve their judgment. Most organizations have no idea how to do this. For example, the first purchase I made right after I secured my very first National Science Foundation grant was an electric pencil sharpener. I wanted the sharpener so that I could take notes on the manuscripts and books I was reading for my dissertation. Because I wasn’t authorized to make such purchases, I put in a request that was subject to at least four different levels of organizational approval. These multiple levels of review are intended to avoid fraud and misappropriation of grant funds, which (upon rare occasions) has been a legitimate problem in the past. In fact, almost all purchases at my home University were treated like suspected fraud, no matter who initiated the purchase — because no one in any typical University organization is really authorized to commit $20 to the purchase of a pencil sharpener. We’re only authorized to initiate a series of reviews and approvals of proposed purchase commitments. By contrast, almost any idiot in a University can call a meeting. And meetings, when you consider the salaries paid to the employees who show up for them, are much more expensive than pencil sharpeners. To empower people in your organization to make decisions, you must communicate to them the resources they have the right to commit. And not all resource commitments will come with a receipt. What is your organizational decision process? After your organization learns to recognize what decisions are, and who within the organization has the right to make them, it’s important to give the people in your organization some guidance regarding how to make good decisions. For example, in Only the Paranoid Survive: Lessons from the CEO of Intel (Grove, 1988) Andy Grove describes the process by which production resources were allocated among different product lines at Intel Corporation. Production managers at individual production facilities were already empowered to commit resources to either memory chips or microprocessors. To guide their decision, they had information about sales prices, production costs, and gross margins. The managers were directed to make decisions that would increase production of the most profitable products, according to the data available for their factory. While almost everyone at Intel at the time thought of themselves as memory chip manufacturers first, and microprocessors as an accessory to the memory business, the production managers were getting data telling them that the microprocessors were more profitable. So they allocated additional resources to microprocessors, and fewer to memory, because their decision process was to gather data and reallocate production resources to the more profitable products. When Grove finally made a commitment to exit the memory business altogether, he discovered that his managers had already put Intel on that path, by shifting the company towards microprocessors. This sped Intel’s transition, and according to Grove, probably saved the company additional losses from the crippling competition in the low-cost memory market. In other words, Intel already understood that a decision is an irreversible commitment of production resources. They already assigned decision rights to the production managers. And they’d provided sufficient guidance to managers about the decision-making process that when the corporation was faced with what felt like an existential crisis, the managers had already been steering production towards a resolution. Nevertheless, the Intel example is an oversimplification. To create a more general process for a broader range of decisions, we must understand the two critical dimensions of decision-making: 1) speed, and 2) scale. The hundreds and thousands of decisions made every day in your company can be organized along two dimensions: 1) speed and 2) scale. Speed refers to pace of the decision. Some decisions happen fast and frequent, while others take longer. The processes that work well for fast, frequent decisions are different from those work for slower decisions. Scale refers to the number of people engaged in the decision-making process: individual, group, or larger society. Design processes that work well for individuals will differ form those that work well for large groups. The two scales relate to one another, as shown in the Figure above. The more people engaged in the decision-making process, the longer the decision typically takes. For example, in the Intel example, the production allocation decision resides in the middle of the figure, near the midpoint between fast and slow, because Intel established a data-driven process that was executed at the scale of small groups of plant managers. To improve organizational decisions, processes must be designed that apply to fast decisions made at the individual scale, as well as for slow decisions made at the collective scale. In the lower left-hand corner of the figure, where individuals make instantaneous decisions, processes rely on a sense of identity. For example, a vegetarian doesn’t have to think about whether they’re eating meat today. Because they identify as a vegetarian, they’re just not a meat person. This is why twelve-step addiction recovery programs begin with the identity statement: “I’m an alcoholic… and my life has become unmanageable.” The first part of Step 1 is a powerful rational for making the decision to stay sober, while the second part reminds the alcoholic that their current decision-making processes were not working for them and they need new processes that will support their new identity. Eventually, after weeks or months of practice, better decision making will become a habit. Because identity is so important to rapid decision making, organizational leaders must make a consistent effort to create a strong sense of identity for those in their organization. This is why we have job titles and descriptions, so that people understand who they are in relation to the organization, and what their role within it is. The stronger their sense of identity, the faster their identify-based individual decisions. Moving towards the middle of the figure, where policies and rules are found, decisions are made at a larger scale. This is the scale at which bureaucracy operates, and most readers have so much experience with bureaucracy that it’s of little further interest to us now. The key point to remember is that bureaucracy is an attempt to simplify the process of group decision making to make it less expensive and more reliable. That comes with consequences at slower speeds and larger scales, where bureaucracy no longer functions. What gets really interesting are judgment, analysis and the social process that couples them: deliberation. To the extent that judgment is about knowing when to break the rules, it stands in opposition to bureaucracy. And it provides room for creativity and innovation. While I can’t say what sort of creative, analytic-deliberative decision-making process will work for your organization, I can describe for you the processes that work at our little startup company called Morozko Forge. We manufacture the world’s first ice bath. (Our competitors are cold baths, because we’re the first and still the only that reaches freezing temperatures). Three co-Founders of the world’s first ice bath company: me, Adrienne Jezick and Jason Stauffer. (Photo by Patrick Nissen). The logo on my T-shirt is the Hydra monster, from Greek mythology. It symbolizes the antifragility of deliberate cold exposure, because cutting off one head of the Hydra will cause it to grow two more. It also symbolizes how we apply many brains in our decision-making processes. The Morozko decision-making process has two important stages. The first is to identify and formulate the problem you are trying to solve. The second is to share lots of ideas and speculate about the consequences in a process we call “What if?” What problem are you trying to solve (and why is it important)? When Steve Jobs launched the iphone over 10 years ago, he was explicit about the problem that the iphone solved for mobile phone users. Most people didn’t even know they had a problem… until Jobs showed them the Apple solution. And that’s the value with asking ‘What problem are you trying to solve?’ Most people are so pre-occupied with their own solutions that they forget what problem they’re trying to solve. They lose their focus. They dilute their efforts, and as a result they wind up with lots of great solutions for problems that don’t exist. I had an exchange with one subordinate who was two hours into an inventory solution without an understanding of the problem. Instead of asking, “What problem am I trying to solve?” this subordinate (and others) kept researching solutions to problems we didn’t have. As a start up company, our survival depends upon our ability to identify, formulate, and solve important problems. When we lose track of the problem we’re trying to solve at any particular moment, we’ve lost our path to profitability. In another exchange, a particularly clever and creative subordinate wanted to show me a new heat exchanger design he had just finished prototyping. He was beaming with his preliminary results, and he wanted to share them and improve the idea further. But I interrupted him and asked, “What problem are you trying to solve?” He said, “Oh, I don’t have a problem!” And I lost my temper, at least a little bit… because all of his creative energy could take us in the wrong direction if he wasn’t able to improve his capacity to identify, formulate, and articulate problems. I scolded him: Well, that sucks for me that YOU don’t have a problem, because our future as a startup depends on our ability to identify, formulate, and solve problems that make life better for our customers, and I have about 99 problems I’ve got to attend to, and here you are — one of our brightest and most clever companions — and you can’t find one single damn problem inside our company to be working on? He laughed. He understood right away that his enthusiasm for his new solution had caused him to lose sight of the problem he was working on, and that his response was a reflex instead of an explanation. When we use the prompt, “What problem are you trying to solve?” we sometimes activate an emotional, defensive response. As children, we learn that teachers, parents, bullies, and other authority figures will threaten us with the challenge: What’s your problem? Many of us learned to avoid conflict and confrontation by saying, “I don’t have a problem,” and that’s exactly what my subordinate found himself doing when he was trying to present his new prototype. In fact, this type of conflict-avoidant behavior is exactly why most organizations suffer from a failure to identify and formulate important problems. In this case, my clever engineer regained his composure, restarted his presentation with “The problem is that our units take too long to cool down in hot Phoenix summers, wearing out our compressors and disappointing our customers.” Now that’s a problem for which I have a lot of patience and creative energy! What if? After we understand the problem we’re trying to solve, it’s time to generate solutions. It’s OK if we start with crappy solutions, because each idea could lead to a better one. One of the things that is a comfort to me when brainstorming for new solutions is reminding myself: My first idea is rarely good enough. By asking, “What if… ?” we think through the consequences of of different alternatives. We’re simply speculating at this point. We’re creating thought experiments about what would change in the world if we implemented whatever idea it is that we’re asking about. For example, we had a leaky tub that defied our usual troubleshooting and repair protocols. So we ran a series of “What if … ?” thought experiments. It sounds like this: What if we threw the tub away and started with a new one? If we threw this tub away and started with a new one, we would save ourselves hours of head-scratching, we would finish producing the unit faster, we would increase our materials costs by about $110, and we would never learn about what was causing the problem and how to prevent it. What if we used Liquid Nails Fuze-it to seal all of the seams from the inside? If we used Liquid Nails Fuze-it to seal all the seams from the inside, it would take us an hour to apply the seal and retest the tub, and we might discover a reliable way of repairing leaky tubs and save ourselves from having to purchase a new $110 tub. (This experiment sounded good enough to try, but our brainstorming process doesn’t stop there. We often keep going, just to see if we could improve upon the idea). What if we used aluminum impregnated nitrile rubber to seal all the seams from the inside? If we used aluminum impregnated nitrile rubber sealant to seal all the seams from the inside, it might take several hours for the sealant to cure before we could retest the tub, and we might discovery a reliable way of repairing leaky tubs and save ourselves the expense of having to purchase a new $110 tub. (We decided to use both the Fuze-it and the nitrile rubber in separate experiments. The Fuze-it was faster, cheaper, and worked great!) The whole point to asking “What if… ?” is to generate enough solutions to ensure we might find one that is good enough. Only by describing the consequences of the solution, rather than judging it, can we come to understand what a world with that solution in it might look like to us. After a few years of implementing the “What if… ?” protocol, I’ve discovered that the most common mistake is short cutting the process by misinterpreting the question as a command. When your subordinates respond to your “What if… ?” by saying, “OK, I’ll do that,” they have removed themselves from the decision process. And that’s going to result in a lot of inferior decisions. By what criteria will you assess the quality of different solutions? Once you’ve described the consequences of different “solutions”, it’s important to understand which to experiment with first. To prioritize each, we must understand the criteria by which we assess our resources commitments. Thus, we ask ourselves a series of questions, in the following order: Will this experiment result in new knowledge? (I.e., what might we learn?) At this stage of our start up, knowledge is the single most important resource we have. It could be knowledge of technique, such as how to repair a tub. It could be knowledge of the market, such as customer preferences and values. It could even be knowledge of one another, and specific strengths each brings to our company. If the experiment will create new knowledge, it becomes a high resource priority. Will this experiment take care of our customers? The entire point of our health and wellness company is to help people take better care of themselves. Experimenting with solutions that come at the expense of our customers is antithetical to our mission, so that doens’twon’t work for us. No one is going value a health and wellness company that does not provide knowledge and equipment for taking care of health and wellness. That doesn’t mean we do everything for our customers, because caring for our customers means empowering them and we sometimes struggle to make the distinction between caring for and doing for. Nevertheless, this question prompts us to consider how our proposed solutions might impact our customers, because: “The purpose of business is to create customers. — Peter Drucker. Will this experiment take care of our companions? To enable our customers to better care for themselves, we must exemplify taking care of ourselves. Put another way, without caring for ourselves, we cannot expect to be able to care for our customers. Solutions that come at the health and wellness expense of our companions will undermine our capacity to provide the necessary knowledge and equipment to our customers, and undermine our credibility in the marketplace. Will this experiment conform to our vision of the future world in which we want to live? Responses to this question require clarity about the future vision of the company and the change we seek to make in the world. For us, that vision includes a world that is free from Type 2 diabetes, free from Alzheimer’s, free from obesity, and free from all the maladies of modern living. The mission of Morozko Forge is to provide the knowledge and equipment necessary to live a natural life in an unnatural world. Not every decision we make will be on direct path towards that vision, and that’s OK. We’re not asking for the shortest path, or the best path, or even the quickest path. When we ask whether an experiment conforms to our vision, we’re seeking to clarify our vision and the space within it for the experiment we’re contemplating. Sometimes, we won’t know the answer to this question until we run the experiment. And other times, asking this question makes it clear that the experiment will not take us closer to the future world we seek, in which case we discard the experiment. Might this experiment generate more resources than it consumes? In this final question, we’re finally getting to what MBA programs might call “return on investment” — but don’t think that means we’re reducing the answer to a financial spreadsheet. Although money is important to the health of our company, at this stage of our venture, our creative energy is even more important. So what we’re prompting in this question is a multi-dimensional examination of the resources we’re committing to a decisions in terms of energy, time, and money, relative to the return we will realize in all three of those resource categories. When we make resource commitments that generate more energy, more time, and more money, we accumulate the resources we need to grow our venture. Every decision is an experiment Although I’ve described a decision as an “irreversible commitment of resources,” that doesn’t mean we can’t make a different decision later. It only means that the resources we’ve committed to the previous decision can’t be recouped. A new decision might commit additional resources to undo the previous decision, and that’s OK — even if it gets expensive sometimes. Thinking of everything decision as an experiment gives us the freedom of being wrong without the anticipatory anxiety of regret. In Designing Your Life (2016) Stanford Professors Bill Burnett and Dave Evans encourage readers to think of commitments as experiments that allow trying new things, learning, and trying again. They argue for the application of what’s typically called “design thinking” to personal and career choices. The difficulty with this type of thinking is that you’re always going to be wrong. When you’re trying new things, you can hardly ever get it right the first time. For many, the imagined humiliation of being wrong is so painful that they’ll never do the experimenting that continue their learning. As a result, people get stuck in old patterns, old habits, and failed “solutions” that stopped working long ago — while their energy is midirected into defending themselves against the nagging suspicion that they might bear some responsibility for their own failures. The antidote is to stop worrying about being right, and to focus instead on what you have to do to be successful. At Morozko Forge, talking about every decision as an experiment releases us from the ego investment in being right. It helps dissolve the anticipatory anxiety of being proved wrong, and managing that anxiety is essential for the growth of our venture. When we think in terms of experiments, rather than in terms of answers, it refocuses our energy on our most important decision question, “Will this experiment result in new knowledge?” That’s how our organization makes decisions, by: Assigning decision rights, Describing decision processes, Setting criteria for evaluating alternatives, and Running experiments. I wonder if your organization might benefit from adopting some of the same practices?
https://medium.com/morozko-method/to-make-better-decisions-40bbf57fe46
['Thomas P Seager']
2020-11-14 00:18:46.173000+00:00
['Creativity', 'Decision Making', 'Innovation', 'Entrepreneurship', 'Small Business']
Title Make Better DecisionsContent Make Better Decisions Assign Rights Describe Processes Set Criteria Experiment Company Know Makes Decisions pointed people idea decision get made within organization consequence organization lack decisionmaking skill claimed better process available “consensus” didn’t specify might design replace ineffective bureaucratic political waste energy constitutes organizational decisionmaking process American organization good time correct oversight decision Although people probably make hundred decision day thought able describe constitutes decision Ask dozen people company several going tell something like “A decision make mind something It’s make choice among several different alternatives” choice prerequisite decision might provide satisfaction relieving uncertainty anxiety decision decision irreversible commitment resource It’s decision niece make declaration family holiday picnic “I’ve decided I’m moving New York pursue new career actress” Although relative might cheer make encouraging noise commits resource time energy money create opportunity cost declaration fantasy decision elevate career aspiration imagination reality must make commitment difficult undo example might sign lease new apartment pay security deposit strengthening decision move might audition role committing time energy putting risk rejection strengthen decision pursue new vocation problem making public declaration intent much rewarding le effort irreversible commitment resource many business manager like niece fantasize loud aspiration make solemn declaration change never commit resource want temporary satisfaction false resolve announce public resolution reward brain dope hit false accomplishment without incurring expense sacrifice risk making commitment It’s decision you’ve made irreversible commitment resource organization get make decision organization grow become removed people founded problem people founded organization excellent judgment constitutes good idea organization would never succeeded people join organization grows wise organizational Founders develop excellent judgment Typically making learning many mistake organization figure what’s working becomes profitable growing patience mistake wear thin institutional control creep reduce possibility error call control “bureaucracy” system policy procedure constitute enforce control Bureaucracies substitute rule judgment problem errorminimizing bureaucracy people organization permitted make mistake necessary develop excellent judgment entire organization becomes preoccupied learning conforming rule bureaucratic organization decision maker policy process rule remove alternative example Rules Rules Netflix Culture Reinvention Hastings Meyer 2020 Netflix CEO Reed Hastings tell story executive one Hasting’s earlier company infuriated travel policy refused reimburse 12 taxi fare travel expense refusal wasn’t decision made individual company rule absolved travel account manager responsibility exercising judgment compensating rule empowered anyone organization override bureaucracy allow decision making operate approval manager upper level review resource allocation ensure comply policy Eventually get corporate culture like one satirized 1985 movie Head Office make better decision organization must assign decisionmaking right people organization foster environment encourages experiment make mistake receive feedback improve judgment organization idea example first purchase made right secured first National Science Foundation grant electric pencil sharpener wanted sharpener could take note manuscript book reading dissertation wasn’t authorized make purchase put request subject least four different level organizational approval multiple level review intended avoid fraud misappropriation grant fund upon rare occasion legitimate problem past fact almost purchase home University treated like suspected fraud matter initiated purchase — one typical University organization really authorized commit 20 purchase pencil sharpener We’re authorized initiate series review approval proposed purchase commitment contrast almost idiot University call meeting meeting consider salary paid employee show much expensive pencil sharpener empower people organization make decision must communicate resource right commit resource commitment come receipt organizational decision process organization learns recognize decision within organization right make it’s important give people organization guidance regarding make good decision example Paranoid Survive Lessons CEO Intel Grove 1988 Andy Grove describes process production resource allocated among different product line Intel Corporation Production manager individual production facility already empowered commit resource either memory chip microprocessor guide decision information sale price production cost gross margin manager directed make decision would increase production profitable product according data available factory almost everyone Intel time thought memory chip manufacturer first microprocessor accessory memory business production manager getting data telling microprocessor profitable allocated additional resource microprocessor fewer memory decision process gather data reallocate production resource profitable product Grove finally made commitment exit memory business altogether discovered manager already put Intel path shifting company towards microprocessor sped Intel’s transition according Grove probably saved company additional loss crippling competition lowcost memory market word Intel already understood decision irreversible commitment production resource already assigned decision right production manager they’d provided sufficient guidance manager decisionmaking process corporation faced felt like existential crisis manager already steering production towards resolution Nevertheless Intel example oversimplification create general process broader range decision must understand two critical dimension decisionmaking 1 speed 2 scale hundred thousand decision made every day company organized along two dimension 1 speed 2 scale Speed refers pace decision decision happen fast frequent others take longer process work well fast frequent decision different work slower decision Scale refers number people engaged decisionmaking process individual group larger society Design process work well individual differ form work well large group two scale relate one another shown Figure people engaged decisionmaking process longer decision typically take example Intel example production allocation decision resides middle figure near midpoint fast slow Intel established datadriven process executed scale small group plant manager improve organizational decision process must designed apply fast decision made individual scale well slow decision made collective scale lower lefthand corner figure individual make instantaneous decision process rely sense identity example vegetarian doesn’t think whether they’re eating meat today identify vegetarian they’re meat person twelvestep addiction recovery program begin identity statement “I’m alcoholic… life become unmanageable” first part Step 1 powerful rational making decision stay sober second part reminds alcoholic current decisionmaking process working need new process support new identity Eventually week month practice better decision making become habit identity important rapid decision making organizational leader must make consistent effort create strong sense identity organization job title description people understand relation organization role within stronger sense identity faster identifybased individual decision Moving towards middle figure policy rule found decision made larger scale scale bureaucracy operates reader much experience bureaucracy it’s little interest u key point remember bureaucracy attempt simplify process group decision making make le expensive reliable come consequence slower speed larger scale bureaucracy longer function get really interesting judgment analysis social process couple deliberation extent judgment knowing break rule stand opposition bureaucracy provides room creativity innovation can’t say sort creative analyticdeliberative decisionmaking process work organization describe process work little startup company called Morozko Forge manufacture world’s first ice bath competitor cold bath we’re first still reach freezing temperature Three coFounders world’s first ice bath company Adrienne Jezick Jason Stauffer Photo Patrick Nissen logo Tshirt Hydra monster Greek mythology symbolizes antifragility deliberate cold exposure cutting one head Hydra cause grow two also symbolizes apply many brain decisionmaking process Morozko decisionmaking process two important stage first identify formulate problem trying solve second share lot idea speculate consequence process call “What if” problem trying solve important Steve Jobs launched iphone 10 year ago explicit problem iphone solved mobile phone user people didn’t even know problem… Jobs showed Apple solution that’s value asking ‘What problem trying solve’ people preoccupied solution forget problem they’re trying solve lose focus dilute effort result wind lot great solution problem don’t exist exchange one subordinate two hour inventory solution without understanding problem Instead asking “What problem trying solve” subordinate others kept researching solution problem didn’t start company survival depends upon ability identify formulate solve important problem lose track problem we’re trying solve particular moment we’ve lost path profitability another exchange particularly clever creative subordinate wanted show new heat exchanger design finished prototyping beaming preliminary result wanted share improve idea interrupted asked “What problem trying solve” said “Oh don’t problem” lost temper least little bit… creative energy could take u wrong direction wasn’t able improve capacity identify formulate articulate problem scolded Well suck don’t problem future startup depends ability identify formulate solve problem make life better customer 99 problem I’ve got attend — one brightest clever companion — can’t find one single damn problem inside company working laughed understood right away enthusiasm new solution caused lose sight problem working response reflex instead explanation use prompt “What problem trying solve” sometimes activate emotional defensive response child learn teacher parent bully authority figure threaten u challenge What’s problem Many u learned avoid conflict confrontation saying “I don’t problem” that’s exactly subordinate found trying present new prototype fact type conflictavoidant behavior exactly organization suffer failure identify formulate important problem case clever engineer regained composure restarted presentation “The problem unit take long cool hot Phoenix summer wearing compressor disappointing customers” that’s problem lot patience creative energy understand problem we’re trying solve it’s time generate solution It’s OK start crappy solution idea could lead better one One thing comfort brainstorming new solution reminding first idea rarely good enough asking “What if… ” think consequence different alternative We’re simply speculating point We’re creating thought experiment would change world implemented whatever idea we’re asking example leaky tub defied usual troubleshooting repair protocol ran series “What … ” thought experiment sound like threw tub away started new one threw tub away started new one would save hour headscratching would finish producing unit faster would increase material cost 110 would never learn causing problem prevent used Liquid Nails Fuzeit seal seam inside used Liquid Nails Fuzeit seal seam inside would take u hour apply seal retest tub might discover reliable way repairing leaky tub save purchase new 110 tub experiment sounded good enough try brainstorming process doesn’t stop often keep going see could improve upon idea used aluminum impregnated nitrile rubber seal seam inside used aluminum impregnated nitrile rubber sealant seal seam inside might take several hour sealant cure could retest tub might discovery reliable way repairing leaky tub save expense purchase new 110 tub decided use Fuzeit nitrile rubber separate experiment Fuzeit faster cheaper worked great whole point asking “What if… ” generate enough solution ensure might find one good enough describing consequence solution rather judging come understand world solution might look like u year implementing “What if… ” protocol I’ve discovered common mistake short cutting process misinterpreting question command subordinate respond “What if… ” saying “OK I’ll that” removed decision process that’s going result lot inferior decision criterion ass quality different solution you’ve described consequence different “solutions” it’s important understand experiment first prioritize must understand criterion ass resource commitment Thus ask series question following order experiment result new knowledge Ie might learn stage start knowledge single important resource could knowledge technique repair tub could knowledge market customer preference value could even knowledge one another specific strength brings company experiment create new knowledge becomes high resource priority experiment take care customer entire point health wellness company help people take better care Experimenting solution come expense customer antithetical mission doens’twon’t work u one going value health wellness company provide knowledge equipment taking care health wellness doesn’t mean everything customer caring customer mean empowering sometimes struggle make distinction caring Nevertheless question prompt u consider proposed solution might impact customer “The purpose business create customer — Peter Drucker experiment take care companion enable customer better care must exemplify taking care Put another way without caring cannot expect able care customer Solutions come health wellness expense companion undermine capacity provide necessary knowledge equipment customer undermine credibility marketplace experiment conform vision future world want live Responses question require clarity future vision company change seek make world u vision includes world free Type 2 diabetes free Alzheimer’s free obesity free malady modern living mission Morozko Forge provide knowledge equipment necessary live natural life unnatural world every decision make direct path towards vision that’s OK We’re asking shortest path best path even quickest path ask whether experiment conforms vision we’re seeking clarify vision space within experiment we’re contemplating Sometimes won’t know answer question run experiment time asking question make clear experiment take u closer future world seek case discard experiment Might experiment generate resource consumes final question we’re finally getting MBA program might call “return investment” — don’t think mean we’re reducing answer financial spreadsheet Although money important health company stage venture creative energy even important we’re prompting question multidimensional examination resource we’re committing decision term energy time money relative return realize three resource category make resource commitment generate energy time money accumulate resource need grow venture Every decision experiment Although I’ve described decision “irreversible commitment resources” doesn’t mean can’t make different decision later mean resource we’ve committed previous decision can’t recouped new decision might commit additional resource undo previous decision that’s OK — even get expensive sometimes Thinking everything decision experiment give u freedom wrong without anticipatory anxiety regret Designing Life 2016 Stanford Professors Bill Burnett Dave Evans encourage reader think commitment experiment allow trying new thing learning trying argue application what’s typically called “design thinking” personal career choice difficulty type thinking you’re always going wrong you’re trying new thing hardly ever get right first time many imagined humiliation wrong painful they’ll never experimenting continue learning result people get stuck old pattern old habit failed “solutions” stopped working long ago — energy midirected defending nagging suspicion might bear responsibility failure antidote stop worrying right focus instead successful Morozko Forge talking every decision experiment release u ego investment right help dissolve anticipatory anxiety proved wrong managing anxiety essential growth venture think term experiment rather term answer refocuses energy important decision question “Will experiment result new knowledge” That’s organization make decision Assigning decision right Describing decision process Setting criterion evaluating alternative Running experiment wonder organization might benefit adopting practicesTags Creativity Decision Making Innovation Entrepreneurship Small Business
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What To Look For In A Graph
A Machine Learning Engineer who needs to figure out distributions of features to create better models, or a Platform Engineer who needs to monitor the platform for metrics like requests per minute, needs to draw and understand graphs. Knowing what graph works in which situation can make it easier to depict stories through graphs. Today there are so many graphs out there, selecting one can become an overwhelming task. The goal of this article is to understand how based on specific type of data we can choose a specific type of graph and what information we can infer from that graph. This enables the reader to quickly infer vital information from a graph and to know which graph to use just based on the type of variables. This article is written keeping in mind what information a machine learning engineer or data scientist will try to infer from some give data. Even though it is useful for anyone who want to know what graphs to draw in which scenario or how to understand the basic graphs. Contents Types of Variable (Categorical, Quantitative) Scale of Measurement (Nominal, Ordinal, Interval, Ratio) Examining Distributions (Pie Chart, Bar Graph, Histogram, Box Plot) Examining Relationships (Side-By-Side Box Plot, Scatter Plot, Two Ways Table, HeatMap) Conclusion Types of Variable Categorical Variables: According to Wikipedia A categorical (qualitative) variable is a variable that can take on one of a limited, and usually fixed, number of possible values , assigning each individual or other unit of observation to a particular group. For example Smoking is a categorical variable which can categorize a person into two groups one that smokes and other one that doesn’t smoke. Gender and Race are also categorical as a person can belong to one of a given set of values. Zip code is a categorical variable as it categorizes geographic location. According to Wikipedia A categorical (qualitative) variable is a variable that can take on , assigning each individual or other unit of observation to a particular group. For example is a categorical variable which can categorize a person into two groups one that smokes and other one that doesn’t smoke. and are also categorical as a person can belong to one of a given set of values. is a categorical variable as it categorizes geographic location. Quantitative Variables: Are the variables that represent some kind of measurement and take numerical value. Example can be Age, Weight and Height of a person. An easier way to recognize if a variable is quantitative is to see if it represents some form of measurement while having numeric values, which is not the case with categorical variables. Otherwise there is no restriction on categorical variables to not to have numerical values or have a small set of possible values as is the case with Zip code. Even though it’s numerical and hence can be added, subtracted or sorted it doesn’t represents any ordinal behavior but just the locality to which a person belongs. Scale of Measurement Nominal: is a qualitative (categorical) measure that uses discrete categories to describe a characteristic. For example: citizenship, religious affiliation, and marital status . Even though these can be represented by using numbers these don’t have and way to be ranked or ordered. is a qualitative (categorical) measure that uses discrete categories to describe a characteristic. For example: . Even though these can be represented by using numbers these don’t have and way to be ranked or ordered. Ordinal: ranks or orders participants on some scale or attribute, but the difference doesn’t convey fixed or equal differences. For example condition of a car . It can be Very Good, Good, Okay, Bad. ranks or orders participants on some scale or attribute, but the difference doesn’t convey fixed or equal differences. For example . It can be Very Good, Good, Okay, Bad. Interval: takes numerical form and the distance between pairs of consecutive number is equal. For example temperature . takes numerical form and the distance between pairs of consecutive number is equal. For example . Ratio: is similar to interval scale, the major difference is how we interpret a value of zero. For ratio measures the zero is meaningful and tell us that the attribute is absent in the participant. For example number of people having polio in India. Examining Distribution Examining distribution has two components What values the variable takes How often the variable takes those values Categorical Variable In case the data we have contains categorical variable, for example the data in the below image, which show a snippet of data of car and brand to which car belongs to, In some vintage car store. Categorical car brands data In such a dataset what we look for is the frequency distributions of the categorical variable. As that answers the category imbalance that we might have in our data. In this case the graph we go for are the following: Frequency Distribution of Cars A Pie chart is useful in describing the frequency distribution. The area covered by one color shows the dominance of that category in the dataset. Additional information like Name and percentage of the category can be useful to show. Looking at the above graph we see that The parking lot has 53% cars with brand Mercedes. Frequency Distribution of Cars In a bar graph x-axis usually represents the categorical labels and y axis will represent the numerical term associated with it. Which is the frequency in this case. The bars that are higher will show the dominant category in the dataset. Quantitative Variable In case the variable is quantitative, we usually have values over a large range and it’s not possible to create frequency distribution for each individual value. So we create bins for it and then those bins represent categorical variables for which the histogram can be drawn. An example of quantitative variable is shown in the following graph. Example of Quantitative Dataset We can define a set of intervals to represent a grade for those marks which will look like: Bins for Student Marks Histogram of Student Grades Histogram even though is just a bar chart, is different as we didn’t represent the values we were given on the X-axis but created bins and then represented the frequency distribution of those bins. In some places it might be clear on how many bins make sense or the bins can be predefined. But in some places this can be experimented with or let alone for the plotting libraries to decide based on some mathematical formulation. To checkout variations in histogram/distplots checkout histogram and distplot. The information we can infer from a histogram is the following: Shape Shape of a histogram has two things to look for: Skewness: If the distribution is left skewed, right skewed or symmetric. Symmetric Symmetric distribution in real word can be seen when measuring heights of students in a class. Where majority of students will exist within some specific range with some exceptions on either side. Left Skewed Left skewed distribution will have most of the data towards the right end. A real world example of this kind of distribution is the age of death from natural causes. Most such deaths happen at older ages. Right Skewed In skewed right distribution the most of the data is at the left end. A real world example of this is salaries of people. Most people earn in lower ranges while a few have very high salaries. By knowing the skew we can decide from which side we want to remove the outliers for a given set of data. If we remove data from both sides of a distribution when the distribution is skewed we might end up removing useful data and as a consequence the models trained might not generalize well. Modality: the number of peaks the distribution has. Bimodal Graph (2 peaks) Any graph with more than 2 modes is known as multimodal The graph above has two peaks and in real world can come up while looking at distribution of money spent by people at an e-commerce website. The use of this information is to create various segments of users which can be targeted using different ranged recommendations in term of prices. Outliers Outliers are the observations that fall outside the overall pattern. Outliers Center Center is the midpoint of the distribution. Center is expected to divide the distribution into approximately two equal parts. Mode, Mean and Median are the three measures of center. The point to remember is that Mean is highly sensitive to outliers but median is almost unaffected. Spread Spread of the distribution is described by the approximate range covered by the data. Measures of Spread include Range, Inter-quartile range (IQR) and Standard deviation. Let’s see what Inter-quartile range is, as its the measure we will need for understanding the upcoming graph. The IQR is the first quartile subtracted from the third quartile. And what first quartile represents is the point on the x-axis which has 25% of data on the left side and 75% of the data on the right side. The third quartile represents the point on x-axis which has 75% of the data on the left side and 25% of the data on the right side of it. So IQR represents the range in which 50% of the data around the median lies. IQR And Range of Dataset IQR can help us detect outliers. A general rule of thumb know as 1.5(IQR) Criterion is that: An observation is considered a suspected outlier if it is: Below Q1–1.5(IQR) or Above Q3 + 1.5(IQR) In the above image (Min, Q1, Median, Q3, Max) gives us a quick numerical description of both center and spread of the distribution which brings us to the next graph which can show that. Box Plot for Distribution of Sepal Width The information in the above graph is based on the data which looks like: Histogram of Sepal Width We will revisit box plots later explaining how it is even more useful while examining relationships. Examining Relationship Examining distribution is based on a single variable, whereas relationship is between two variables. We will explore three cases which are One variable is Categorical and other is Quantitative Both variables are Quantitative Both variables are Categorical Categorical-Quantitative The following image shows a snippet of Iris dataset which represents three categories of Iris flower and also their sepal and petal dimensions. Iris Dataset Let’s try to find the relationship between sepal_width and species. Side by Side Box Plots: Side by Side Box Plots Once we know what a box plot represents we can use the box plots side by side to let us see how distribution of sepal_width varies in the three varieties of flower. Based on the above graph one can see some patterns, like setosa on average have much larger sepal widths as compared to others. Quantitative-Quantitative When both variables are quantitative for example the sepal_width and sepal_height in the above Iris dataset, we can use scatter plot. Scatter Plot petal_width vs sepal_width Scatter plot shows a relationship between sepal_width and petal_width. Based on this one can create regression line to see a potential trend in the two variables which shows that as sepal_width increases the petal_width also shows increase. Scatter plot in the most basic form has become a thing of past. Usually it is accompanied with regression lines showing possible trends, with boxplots showing the distributions of the variables plotted along axis. With labeled points(Usually colors are used to label different points on the graph) The graph below shows an advance version of scatter plot. Hybrid Scatter Plot Categorical-Categorical In case both variables are categorical. The hypothetical example below shows an example of that: Flower Gender and its Species Two Way Table In a two way table each cell contains the value for the intersection of two categorical attributes. for example there are 21 Male Versicolor type Iris flowers in our dataset. If both variables are categorical, their counts/percentage can shown in a two way table to clearly show the relationship between those. Heat Map If the number of categories is large it might take a lot of time to read through the numbers, in those cases a heat map can be used which displays this information using colors of cells making it easy to find ranges of interest or unusual patterns. Like in this figure Male-Setosa flowers are the least represented category in our dataset. The color map on the right shows the number associated with a specific shade of color. Conclusion Above I’ve shown a way to infer based on types of variables how one can decide the type of graph one might want and what insights one can find in those graphs. This set represents only a basic set of graphs that are available out there. Those graphs are mostly some form of modification of the above described basic graphs which are used to show some extra information. One should be careful while using those graphs as having too many insights within the same graph instead of summarizing the point might just confuse people. It is better to use multiple graphs which visualize some insights at a time and then try to conclude the entire set of insights using some hybrid version of graphs. Using basic graphs also has a benefit that most people will know how to read those and hence it’s easier to propagate information without having to attach some long documentation that just represents the same information that we wanted the graph to depict in words, completely deferring the point of having a graph. If the graph isn’t self explanatory, then it’s pointless to have it.
https://medium.com/ai-in-plain-english/what-to-look-for-in-a-graph-5c2cf85c7446
['Kartikeya Sharma']
2020-12-28 16:40:40.399000+00:00
['Machine Learning', 'Python', 'Artificial Intelligence', 'Data Science', 'Data Visualization']
Title Look GraphContent Machine Learning Engineer need figure distribution feature create better model Platform Engineer need monitor platform metric like request per minute need draw understand graph Knowing graph work situation make easier depict story graph Today many graph selecting one become overwhelming task goal article understand based specific type data choose specific type graph information infer graph enables reader quickly infer vital information graph know graph use based type variable article written keeping mind information machine learning engineer data scientist try infer give data Even though useful anyone want know graph draw scenario understand basic graph Contents Types Variable Categorical Quantitative Scale Measurement Nominal Ordinal Interval Ratio Examining Distributions Pie Chart Bar Graph Histogram Box Plot Examining Relationships SideBySide Box Plot Scatter Plot Two Ways Table HeatMap Conclusion Types Variable Categorical Variables According Wikipedia categorical qualitative variable variable take one limited usually fixed number possible value assigning individual unit observation particular group example Smoking categorical variable categorize person two group one smoke one doesn’t smoke Gender Race also categorical person belong one given set value Zip code categorical variable categorizes geographic location According Wikipedia categorical qualitative variable variable take assigning individual unit observation particular group example categorical variable categorize person two group one smoke one doesn’t smoke also categorical person belong one given set value categorical variable categorizes geographic location Quantitative Variables variable represent kind measurement take numerical value Example Age Weight Height person easier way recognize variable quantitative see represents form measurement numeric value case categorical variable Otherwise restriction categorical variable numerical value small set possible value case Zip code Even though it’s numerical hence added subtracted sorted doesn’t represents ordinal behavior locality person belongs Scale Measurement Nominal qualitative categorical measure us discrete category describe characteristic example citizenship religious affiliation marital status Even though represented using number don’t way ranked ordered qualitative categorical measure us discrete category describe characteristic example Even though represented using number don’t way ranked ordered Ordinal rank order participant scale attribute difference doesn’t convey fixed equal difference example condition car Good Good Okay Bad rank order participant scale attribute difference doesn’t convey fixed equal difference example Good Good Okay Bad Interval take numerical form distance pair consecutive number equal example temperature take numerical form distance pair consecutive number equal example Ratio similar interval scale major difference interpret value zero ratio measure zero meaningful tell u attribute absent participant example number people polio India Examining Distribution Examining distribution two component value variable take often variable take value Categorical Variable case data contains categorical variable example data image show snippet data car brand car belongs vintage car store Categorical car brand data dataset look frequency distribution categorical variable answer category imbalance might data case graph go following Frequency Distribution Cars Pie chart useful describing frequency distribution area covered one color show dominance category dataset Additional information like Name percentage category useful show Looking graph see parking lot 53 car brand Mercedes Frequency Distribution Cars bar graph xaxis usually represents categorical label axis represent numerical term associated frequency case bar higher show dominant category dataset Quantitative Variable case variable quantitative usually value large range it’s possible create frequency distribution individual value create bin bin represent categorical variable histogram drawn example quantitative variable shown following graph Example Quantitative Dataset define set interval represent grade mark look like Bins Student Marks Histogram Student Grades Histogram even though bar chart different didn’t represent value given Xaxis created bin represented frequency distribution bin place might clear many bin make sense bin predefined place experimented let alone plotting library decide based mathematical formulation checkout variation histogramdistplots checkout histogram distplot information infer histogram following Shape Shape histogram two thing look Skewness distribution left skewed right skewed symmetric Symmetric Symmetric distribution real word seen measuring height student class majority student exist within specific range exception either side Left Skewed Left skewed distribution data towards right end real world example kind distribution age death natural cause death happen older age Right Skewed skewed right distribution data left end real world example salary people people earn lower range high salary knowing skew decide side want remove outlier given set data remove data side distribution distribution skewed might end removing useful data consequence model trained might generalize well Modality number peak distribution Bimodal Graph 2 peak graph 2 mode known multimodal graph two peak real world come looking distribution money spent people ecommerce website use information create various segment user targeted using different ranged recommendation term price Outliers Outliers observation fall outside overall pattern Outliers Center Center midpoint distribution Center expected divide distribution approximately two equal part Mode Mean Median three measure center point remember Mean highly sensitive outlier median almost unaffected Spread Spread distribution described approximate range covered data Measures Spread include Range Interquartile range IQR Standard deviation Let’s see Interquartile range measure need understanding upcoming graph IQR first quartile subtracted third quartile first quartile represents point xaxis 25 data left side 75 data right side third quartile represents point xaxis 75 data left side 25 data right side IQR represents range 50 data around median lie IQR Range Dataset IQR help u detect outlier general rule thumb know 15IQR Criterion observation considered suspected outlier Q1–15IQR Q3 15IQR image Min Q1 Median Q3 Max give u quick numerical description center spread distribution brings u next graph show Box Plot Distribution Sepal Width information graph based data look like Histogram Sepal Width revisit box plot later explaining even useful examining relationship Examining Relationship Examining distribution based single variable whereas relationship two variable explore three case One variable Categorical Quantitative variable Quantitative variable Categorical CategoricalQuantitative following image show snippet Iris dataset represents three category Iris flower also sepal petal dimension Iris Dataset Let’s try find relationship sepalwidth specie Side Side Box Plots Side Side Box Plots know box plot represents use box plot side side let u see distribution sepalwidth varies three variety flower Based graph one see pattern like setosa average much larger sepal width compared others QuantitativeQuantitative variable quantitative example sepalwidth sepalheight Iris dataset use scatter plot Scatter Plot petalwidth v sepalwidth Scatter plot show relationship sepalwidth petalwidth Based one create regression line see potential trend two variable show sepalwidth increase petalwidth also show increase Scatter plot basic form become thing past Usually accompanied regression line showing possible trend boxplots showing distribution variable plotted along axis labeled pointsUsually color used label different point graph graph show advance version scatter plot Hybrid Scatter Plot CategoricalCategorical case variable categorical hypothetical example show example Flower Gender Species Two Way Table two way table cell contains value intersection two categorical attribute example 21 Male Versicolor type Iris flower dataset variable categorical countspercentage shown two way table clearly show relationship Heat Map number category large might take lot time read number case heat map used display information using color cell making easy find range interest unusual pattern Like figure MaleSetosa flower least represented category dataset color map right show number associated specific shade color Conclusion I’ve shown way infer based type variable one decide type graph one might want insight one find graph set represents basic set graph available graph mostly form modification described basic graph used show extra information One careful using graph many insight within graph instead summarizing point might confuse people better use multiple graph visualize insight time try conclude entire set insight using hybrid version graph Using basic graph also benefit people know read hence it’s easier propagate information without attach long documentation represents information wanted graph depict word completely deferring point graph graph isn’t self explanatory it’s pointless itTags Machine Learning Python Artificial Intelligence Data Science Data Visualization
2,875
How Amazon Plans to Take Down SpaceX
Space Is the Only Way to Go On several occasions Bezos has expressed the view that mankind must inevitably move into the heavens. His vision — outlined in a speech in 2019 — paints a future of mass industrialisation of space. Instead of polluting and destroying our fragile world, he wants factories placed in giant orbiting hubs. Bezos imagines humanity will leave the Earth as well. But unlike others, who picture colonies on Mars or on the Moon, he believes we will construct gigantic habitats in space. These structures, first imagined by physicist Gerard O’Neill, could be perfectly adapted to human life. Unlike planets, which by nature are limited in size, an almost endless supply of habitats could be built. In this vision of the future, the pressure we currently place on the Earth would slowly be lifted. As manufacturing moved off-world, pollution would fall. As people migrate to new habitats in the heavens, wildlife could reclaim our planet. Eventually the Earth would become a massive park, and humanity would become truly space-borne. What Bezos imagines is vast in scale, a revolution comparable to the dawn of agriculture thousands of years ago. Even with huge wealth and the vast resources of Amazon, Bezos will not be able to do it alone. His aim, at least for now, is to the take the first few steps down the road towards that future. The launch of New Shepard in 2015 was the first, small, step along the road. Now he has bigger steps planned. Take Blue Origin first. Since 2015 the company has continued work on New Shepard. They have now made a dozen sub-orbital flights, and hope to soon demonstrate that the capsule can carry paying passengers to the edge of space. The real prize, of course, is building an orbital rocket — and with New Glenn, a new design, Blue Origin believe they have that. Building an orbital rocket is hard. Only one private company — SpaceX — has ever managed to do so. Despite at least eight years of development work Blue Origin still have not flown New Glenn, though they claim to be close to a launch, perhaps as soon as 2021. Like SpaceX, Blue Origin hope to one day carry astronauts onboard, taking them to orbit, and even beyond. To that end Blue Origin have announced another secretive project: New Armstrong. Though little is known about the project, it would appear to be a lunar rocket of some kind. That guess is backed up by Bezos’ publicly stated ambitions to reach the Moon. In 2019 he unveiled a planned lunar lander named Blue Moon, now under consideration by NASA for use in any American return to the Moon. Blue Moon: a vision of how Jeff Bezos may one day send deliveries, and astronauts, to the Moon. Image by Blue Origin The Second Path to Space: Amazon Blue Origin is a separate company to Amazon. It sells no products, and makes no profit. The company is funded privately by Jeff Bezos, reportedly costing him more than a billion dollars every year. And though it has had some success in reaching space, it has not achieved as much as Elon Musk has with SpaceX. Through Amazon, though, Bezos has a second lever to push his goals in space. And though the company has so far revealed little about its intentions, it has made several interesting announcements. Most notably the company has announced plans, named Project Kuiper, to launch a constellation of satellites. Officially the aim is to expand Internet access, especially among the poor. But this is probably not the only reason Amazon is suddenly interested in the heavens. The business case for large satellite constellations remains unproven. Previous attempts at building such constellations — by Iridium, Teledesic and Globalstar — failed miserably when faced with the high costs of putting thousands of satellites into orbit. Several recent attempts have stumbled at the same hurdle. OneWeb recently suffered bankruptcy, and others like LeoSat have long since faded away. Jeff Bezos does not seem to be afraid of the huge capital investment, or even of running a satellite internet service at a loss. If instead the constellation serves as a means to drive data and customers towards Amazon’s computing platform, it may be worth the costs. If it can serve his other ambitions in space, and perhaps provide Blue Origin with a dedicated customer, even better. Both Amazon and Microsoft are already building ground stations near their data centres. They aim to transfer data from orbit to their computing clouds as fast as possible. It is clear both companies think large amounts of data will soon be flowing through satellite networks, and they each want to capture as much of this market as they can. Much like computer infrastructure, satellites don’t directly earn revenue for their owners. Their value lies in the data they collect or transfer, and especially in processing that data. One clue that Amazon is thinking in this direction comes from Earth, a set of tools provided through Amazon Web Services that handles processing of Earth observation data. Satellites can capture vast amounts of data. The hard part is getting it back to Earth. Photo by NASA on Unsplash To Know the Future, Watch the Data The idea is simple. Amazon, or rivals, can provide powerful data processing tools through their cloud platforms. Satellite networks, together with strategically located ground stations, help them rapidly collect and transfer data into the cloud. Stop thinking about satellite broadband as a way of connecting the world, then, and start thinking of it as a massive new way of gathering data. More speculatively, Amazon could even treat its satellites as a service. Instead of needing to launch a constellation of satellites to collect datasets, could you just rent sensor time on an Amazon satellite? If Amazon is regularly launching satellites, could you just pay them a nominal fee to carry your device to orbit? If this succeeds, if the cost of getting an instrument into orbit falls to almost nothing, then we may see huge volumes of data following back to Earth. Everything from weather monitoring to movements of ships, aircraft and cargo containers could potentially be watched, recorded and processed through Amazon offerings. This is, so far, just speculation. Amazon has revealed very little publicly about its plans for satellite constellations, though senior figures at Amazon hint they are thinking in this direction. Regardless, as more and more satellites go up, and constellations grow ever larger, it’s hard not to imagine something similar happening. The elephant in the room is, of course, SpaceX. By all appearances they are far ahead of Amazon and Jeff Bezos. SpaceX have already launched astronauts to the International Space Station, and placed hundreds of satellites into orbit. Amazon, by contrast, seem to have hardly moved off the drawing board. Can they really compete? Amazon has two big advantages over SpaceX. They have more money, with annual revenues that dwarf anything SpaceX can claim. They also have more existing infrastructure. If Amazon can make space all about data, their existing platforms will make them the clear winner, even if they are slow to get started. Jeff Bezos though, is undoubtedly thinking bigger. New Shepard, Blue Origin, Blue Moon, Project Kuiper. All are just the first steps along a path towards revolutionising our way of life. That revolution may not happen for decades, or even centuries. But Bezos is determined to give humanity the push it needs to get moving.
https://medium.com/discourse/the-new-space-race-is-all-about-data-5e1b757e04a7
['Alastair Isaacs']
2020-12-18 03:08:45.096000+00:00
['Space', 'Technology', 'Amazon', 'Data Science', 'Future']
Title Amazon Plans Take SpaceXContent Space Way Go several occasion Bezos expressed view mankind must inevitably move heaven vision — outlined speech 2019 — paint future mass industrialisation space Instead polluting destroying fragile world want factory placed giant orbiting hub Bezos imago humanity leave Earth well unlike others picture colony Mars Moon belief construct gigantic habitat space structure first imagined physicist Gerard O’Neill could perfectly adapted human life Unlike planet nature limited size almost endless supply habitat could built vision future pressure currently place Earth would slowly lifted manufacturing moved offworld pollution would fall people migrate new habitat heaven wildlife could reclaim planet Eventually Earth would become massive park humanity would become truly spaceborne Bezos imago vast scale revolution comparable dawn agriculture thousand year ago Even huge wealth vast resource Amazon Bezos able alone aim least take first step road towards future launch New Shepard 2015 first small step along road bigger step planned Take Blue Origin first Since 2015 company continued work New Shepard made dozen suborbital flight hope soon demonstrate capsule carry paying passenger edge space real prize course building orbital rocket — New Glenn new design Blue Origin believe Building orbital rocket hard one private company — SpaceX — ever managed Despite least eight year development work Blue Origin still flown New Glenn though claim close launch perhaps soon 2021 Like SpaceX Blue Origin hope one day carry astronaut onboard taking orbit even beyond end Blue Origin announced another secretive project New Armstrong Though little known project would appear lunar rocket kind guess backed Bezos’ publicly stated ambition reach Moon 2019 unveiled planned lunar lander named Blue Moon consideration NASA use American return Moon Blue Moon vision Jeff Bezos may one day send delivery astronaut Moon Image Blue Origin Second Path Space Amazon Blue Origin separate company Amazon sell product make profit company funded privately Jeff Bezos reportedly costing billion dollar every year though success reaching space achieved much Elon Musk SpaceX Amazon though Bezos second lever push goal space though company far revealed little intention made several interesting announcement notably company announced plan named Project Kuiper launch constellation satellite Officially aim expand Internet access especially among poor probably reason Amazon suddenly interested heaven business case large satellite constellation remains unproven Previous attempt building constellation — Iridium Teledesic Globalstar — failed miserably faced high cost putting thousand satellite orbit Several recent attempt stumbled hurdle OneWeb recently suffered bankruptcy others like LeoSat long since faded away Jeff Bezos seem afraid huge capital investment even running satellite internet service loss instead constellation serf mean drive data customer towards Amazon’s computing platform may worth cost serve ambition space perhaps provide Blue Origin dedicated customer even better Amazon Microsoft already building ground station near data centre aim transfer data orbit computing cloud fast possible clear company think large amount data soon flowing satellite network want capture much market Much like computer infrastructure satellite don’t directly earn revenue owner value lie data collect transfer especially processing data One clue Amazon thinking direction come Earth set tool provided Amazon Web Services handle processing Earth observation data Satellites capture vast amount data hard part getting back Earth Photo NASA Unsplash Know Future Watch Data idea simple Amazon rival provide powerful data processing tool cloud platform Satellite network together strategically located ground station help rapidly collect transfer data cloud Stop thinking satellite broadband way connecting world start thinking massive new way gathering data speculatively Amazon could even treat satellite service Instead needing launch constellation satellite collect datasets could rent sensor time Amazon satellite Amazon regularly launching satellite could pay nominal fee carry device orbit succeeds cost getting instrument orbit fall almost nothing may see huge volume data following back Earth Everything weather monitoring movement ship aircraft cargo container could potentially watched recorded processed Amazon offering far speculation Amazon revealed little publicly plan satellite constellation though senior figure Amazon hint thinking direction Regardless satellite go constellation grow ever larger it’s hard imagine something similar happening elephant room course SpaceX appearance far ahead Amazon Jeff Bezos SpaceX already launched astronaut International Space Station placed hundred satellite orbit Amazon contrast seem hardly moved drawing board really compete Amazon two big advantage SpaceX money annual revenue dwarf anything SpaceX claim also existing infrastructure Amazon make space data existing platform make clear winner even slow get started Jeff Bezos though undoubtedly thinking bigger New Shepard Blue Origin Blue Moon Project Kuiper first step along path towards revolutionising way life revolution may happen decade even century Bezos determined give humanity push need get movingTags Space Technology Amazon Data Science Future
2,876
Monitoring with JMX: How to Integrate Tableau Server with InfluxDB
Concurrent VizQL Sessions from JMX in InfluxDB/Grafana Telegraf is a great tool to collect information from thousands of different sources, but sometimes you need to complete it with other tools due to source limitations. One of these cases when we want to get monitoring and/or performance information from applications using Java Management Extensions API — an API exclusive for Java VMs — where the client must be written in Java too. This the second part of the Grafana/InfluxDB monitoring series, focusing on collecting JMX metrics from 3rd party applications like Tableau Server. The previous post can be found here. We have two options: use Telegraf’s Jolokia2 plugin, or use a standalone JMX agent: jmxtrans. Jolokia2 (a JMX-to-REST-API gateway) is a great solution in case we need to monitor local processes, however, to use it for remote monitoring it has to be deployed in a web container (like OSGi, Tomcat, Jboss). For these scenarios using jmxtrans is more straightforward: it can monitor multiple JMX/RMI endpoints and feed the results to time series databases such as InfluxDB. Monitoring Tableau Server using its JMX API Tableau Server containers and most parts of their application are written in Java, thus it was a natural decision from the Tableau engineering teams to make their internal, performance metrics available in JMX/RMI. You can get information about current active sessions in each service, cache/hit ratio in the VizQL servers among many other metrics. Enable JMX in Tableau Server To enable JMX ports in Tableau Server, use the following tsm commands: $ tsm configuration set -k service.jmx_enabled -v true $ tsm pending-changes apply After the configuration is deployed, you can check the JMX ports for each service: tsm topology list-ports | grep jmx[^\.] These ports are dynamically allocated, so it is advised to set them manually to a fixed port as described here. Now our Server is ready to serve us with JMX metrics. Understand our Server JMX Domains, MBeans, Attributes and values Before we set up jmxtrans to collect JMX metrics, we need to understand what are the available attributes in each service. Some people like to use jconsole for this purpose, I personally favor command-line tools like jmxterm . Let’s pick one of the vizqlserver JMX ports from list-ports ‘s output and connect to it: wget https://github.com/jiaqi/jmxterm/releases/download/v1.0.2/jmxterm-1.0.2-uber.jar $ java -jar jmxterm-1.0.2-uber.jar Welcome to JMX terminal. Type "help" for available commands. $>open localhost:8789 #Connection to localhost:8789 is opened Welcome to JMX terminal. Type "help" for available commands.$>#Connection to localhost:8789 is opened We are connected to our vizqlserver JMX service, how exciting it is. The first thing we can do is to list all domains using domains command: $>domains #following domains are available Catalina JMImplementation Users com.sun.management com.tableausoftware.instrumentation java.lang java.nio java.util.logging org.apache.commons.pool2 tableau.health.jmx Catalina domain contains tomcat related information, we have a few JVM related domains too, but tableau.health.jmx is the one what we are looking for. Let’s have a closer look, what beans do we have in it: $>beans -d tableau.health.jmx #domain = tableau.health.jmx: tableau.health.jmx:name=searchservice tableau.health.jmx:name=vizqlservice We have two beans in the service, one for searchservice and one for vizqlservice. To see what attributes we have inside vizqlservice bean, use the info command: $>info -b tableau.health.jmx:name=vizqlservice -t a #mbean = tableau.health.jmx:name=vizqlservice #class name = com.tableausoftware.health.performancecounter.jmx.JMXMonitoringView # attributes %0 - PerformanceMetrics (javax.management.openmbean.CompositeData, r) It has one attribute called PerformanceMetrics . We are getting close, the last step is to get the actual values from this bean attribute: $>get -b tableau.health.jmx:name=vizqlservice PerformanceMetrics #mbean = tableau.health.jmx:name=vizqlservice: PerformanceMetrics = { ActiveSessions = 0; Bootstraps = 0; BootstrapsDeferred = 0; BootstrapsDeferredThenPerformed = 0; DataserverInserters = 0; DataserverLockedSessions = 0; [...] VisualModelCacheHits = 0; VisualModelCacheMisses = 0; VisualModelCachePartialHits = 0; WorkbookAttributesParseCacheHits = 0; WorkbookAttributesParseCacheMisses = 0; }; These metrics are extremely important in case we want to understand how our Server performs. Since these metrics are stored in these processes’ memory, we do not have to go into the Postgres repository and collect these data with costly SQL queries — everything is a matter of milliseconds. Now we just have to collect some of the important metrics and store them in our InfluxDB. Sending metrics to InfluxDB with jmxtrans You can use rpm to install jmxtrans on Centos, otherwise, you can follow the install instruction on the page. sudo rpm -Uvh https://repo1.maven.org/maven2/org/jmxtrans/jmxtrans/271/jmxtrans-271.rpm Configuration files are stored under /var/lib/jmxtrans folder. Let’s create a new file called /var/lib/jmxtrans/tableau.json with the following contents (sample config for one vizqlserver and one backgrounder processes): If all set, we can start our JMX service: sudo service jmxtrans start Results in Grafana If we log in to our grafana instance (the one what we configured in my previous blog post), we can start consuming the results: We have tons of vizqlservice metrics available for our dashboards In the next parts, we will build an execd based input plugin for telegraf to collect additional, non-standard metrics (using TSM API in our case), then put everything together in a nice monitoring dashboard. Questions? Comments? Did this help? Or something is not quite right? Or you need help to set it up on your end? Just drop a comment below.
https://medium.com/starschema-blog/monitoring-with-jmx-how-to-integrate-tableau-server-with-influxdb-d99e87119750
['Tamas Foldi']
2020-12-15 12:26:05.765000+00:00
['Data Engineering', 'Jmx', 'Influxdb', 'Tableau Server', 'Dataviz']
Title Monitoring JMX Integrate Tableau Server InfluxDBContent Concurrent VizQL Sessions JMX InfluxDBGrafana Telegraf great tool collect information thousand different source sometimes need complete tool due source limitation One case want get monitoring andor performance information application using Java Management Extensions API — API exclusive Java VMs — client must written Java second part GrafanaInfluxDB monitoring series focusing collecting JMX metric 3rd party application like Tableau Server previous post found two option use Telegraf’s Jolokia2 plugin use standalone JMX agent jmxtrans Jolokia2 JMXtoRESTAPI gateway great solution case need monitor local process however use remote monitoring deployed web container like OSGi Tomcat Jboss scenario using jmxtrans straightforward monitor multiple JMXRMI endpoint feed result time series database InfluxDB Monitoring Tableau Server using JMX API Tableau Server container part application written Java thus natural decision Tableau engineering team make internal performance metric available JMXRMI get information current active session service cachehit ratio VizQL server among many metric Enable JMX Tableau Server enable JMX port Tableau Server use following tsm command tsm configuration set k servicejmxenabled v true tsm pendingchanges apply configuration deployed check JMX port service tsm topology listports grep jmx port dynamically allocated advised set manually fixed port described Server ready serve u JMX metric Understand Server JMX Domains MBeans Attributes value set jmxtrans collect JMX metric need understand available attribute service people like use jconsole purpose personally favor commandline tool like jmxterm Let’s pick one vizqlserver JMX port listports ‘s output connect wget httpsgithubcomjiaqijmxtermreleasesdownloadv102jmxterm102uberjar java jar jmxterm102uberjar Welcome JMX terminal Type help available command open localhost8789 Connection localhost8789 opened Welcome JMX terminal Type help available commandsConnection localhost8789 opened connected vizqlserver JMX service exciting first thing list domain using domain command domain following domain available Catalina JMImplementation Users comsunmanagement comtableausoftwareinstrumentation javalang javanio javautillogging orgapachecommonspool2 tableauhealthjmx Catalina domain contains tomcat related information JVM related domain tableauhealthjmx one looking Let’s closer look bean bean tableauhealthjmx domain tableauhealthjmx tableauhealthjmxnamesearchservice tableauhealthjmxnamevizqlservice two bean service one searchservice one vizqlservice see attribute inside vizqlservice bean use info command info b tableauhealthjmxnamevizqlservice mbean tableauhealthjmxnamevizqlservice class name comtableausoftwarehealthperformancecounterjmxJMXMonitoringView attribute 0 PerformanceMetrics javaxmanagementopenmbeanCompositeData r one attribute called PerformanceMetrics getting close last step get actual value bean attribute get b tableauhealthjmxnamevizqlservice PerformanceMetrics mbean tableauhealthjmxnamevizqlservice PerformanceMetrics ActiveSessions 0 Bootstraps 0 BootstrapsDeferred 0 BootstrapsDeferredThenPerformed 0 DataserverInserters 0 DataserverLockedSessions 0 VisualModelCacheHits 0 VisualModelCacheMisses 0 VisualModelCachePartialHits 0 WorkbookAttributesParseCacheHits 0 WorkbookAttributesParseCacheMisses 0 metric extremely important case want understand Server performs Since metric stored processes’ memory go Postgres repository collect data costly SQL query — everything matter millisecond collect important metric store InfluxDB Sending metric InfluxDB jmxtrans use rpm install jmxtrans Centos otherwise follow install instruction page sudo rpm Uvh httpsrepo1mavenorgmaven2orgjmxtransjmxtrans271jmxtrans271rpm Configuration file stored varlibjmxtrans folder Let’s create new file called varlibjmxtranstableaujson following content sample config one vizqlserver one backgrounder process set start JMX service sudo service jmxtrans start Results Grafana log grafana instance one configured previous blog post start consuming result ton vizqlservice metric available dashboard next part build execd based input plugin telegraf collect additional nonstandard metric using TSM API case put everything together nice monitoring dashboard Questions Comments help something quite right need help set end drop comment belowTags Data Engineering Jmx Influxdb Tableau Server Dataviz
2,877
Meet the Mormon Transhumanists Seeking Salvation in the Singularity
Michaelann Bradley was living the good Mormon life. A faithful member of the Church of Jesus Christ of Latter-day Saints, Bradley had moved from Texas to Provo, Utah, the fervent epicenter of Mormon culture, to attend Brigham Young University. At church, she played the organ, taught Sunday school, and often served in leadership roles in her congregation. Bradley was “living by the Spirit” — a practice she learned as a young girl and refined during her time as a missionary in Switzerland. In everyday situations, she would pause and reflect, trying to intuit what God would want her to do: Did he want her to take the long way home from campus? Who should she assign to look after a member with unique needs in her congregation? She felt guided. Until she didn’t. The crisis came during her senior year of college when she felt the spirit pushing her to marry someone she sensed was a bad fit. He was abusive, and she knew that if she married him, it wouldn’t end well. “I had to make a decision between what I knew was best for me and what I thought God expected of me,” she said. The disconnect pained her, but she told God no. “I remember praying, telling God, ‘It’s my eternity, not yours,’” she said. The decision drove a wedge between her and God — and between her and other Mormons, who she felt didn’t understand her doubts. So she quietly wrestled with God alone for years. “I used to have this magical view of God, and then those views were shattered,” Michaelann Bradley said. “Then Mormon Transhumanism came along, and has been an anchor for me. We don’t know if heaven exists, but we can make it.” In 2013, Bradley met her future husband, Don, at an academic scripture study group. He was a thoughtful historian 18 years her senior whose own faith in the LDS Church had been shaken years before. Many of their early dates were to “Mormon-adjacent gatherings,” Bradley said, so she hardly batted an eye when Don invited her to a meeting of the Mormon Transhumanist Association. He billed it as a group of thoughtful folks tackling slightly different ideas about Mormonism. “I thought he meant ‘transcendentalist,’” Bradley told me. “I came prepared to talk about Thoreau.” The meeting was as far from Walden as the moon or a terraformed Mars. Held in a local tech entrepreneur’s basement, it was a philosophical free-for-all of ideas that were closer to science fiction than scripture. The 10 other attendees — all male, all white, all in their 20s and 30s, and mostly with backgrounds in computer science or the tech world — batted around theories that reframed deeply held Mormon beliefs, like the notion that “As man now is, God once was; as God now is, man may become,” in terms of cryonics and the singularity. They quoted futurists in the same breath as Latter-day Saint Apostles and Carl Sagan. They asked whether we could become like God through technology — could we live forever now and not just after we die? Scratch the surface, and you’ll find that Mormon transhumanists believe the coming leaps in science and technology will help us realize the Mormon promise of achieving perfect, immortal bodies and becoming Gods. With nearly 1,000 members, the Mormon Transhumanist Association, or MTA, is a growing offshoot of the broad transhumanist movement, which believes that the human race can evolve beyond its current mental and physical state through the use of science and technology in order to achieve breakthrough outcomes in the near future. Think: uploading your brain to the cloud or freezing your body in order to resuscitate in an era of immortality. Championed by innovators like Google’s head of engineering, Ray Kurzweil, and Elon Musk, the idea has taken hold with a generation of techno-libertarians and others looking for solutions to — or just an escape hatch out of — a failing world. Mormon transhumanism takes those theories and molds them onto a religious framework, where technology and science are tools to further the work of Jesus Christ. There are straightforward applications, like using cybernetic limbs to help injured and disabled people to walk or laser cataract procedures to help people with low vision to see. But scratch the surface, and you’ll find that Mormon transhumanists believe that science can bring about the “realization of diverse prophetic visions of transfiguration, immortality, resurrection, renewal of this world, and the discovery and creation of worlds without end.” They believe the coming leaps in science and technology will help us realize the Mormon promise of achieving perfect, immortal bodies and becoming Gods. Bradley left her first meeting of the MTA buzzing. For the first time in a long time, she felt at home with her doubts. Here was a group of people “thinking really hard about what it means to have faith and what it means to believe in science and logic,” she said. No idea was taboo. Skepticism and doubt were part of the discourse. “It was invigorating,” she said.
https://gen.medium.com/meet-the-mormon-transhumanists-seeking-salvation-in-the-singularity-a7e3784d6c04
['Erin Clare Brown']
2019-09-27 00:48:26.490000+00:00
['Mormon', 'Reasonable Doubt', 'Transhumanism', 'Future', 'Religion']
Title Meet Mormon Transhumanists Seeking Salvation SingularityContent Michaelann Bradley living good Mormon life faithful member Church Jesus Christ Latterday Saints Bradley moved Texas Provo Utah fervent epicenter Mormon culture attend Brigham Young University church played organ taught Sunday school often served leadership role congregation Bradley “living Spirit” — practice learned young girl refined time missionary Switzerland everyday situation would pause reflect trying intuit God would want want take long way home campus assign look member unique need congregation felt guided didn’t crisis came senior year college felt spirit pushing marry someone sensed bad fit abusive knew married wouldn’t end well “I make decision knew best thought God expected me” said disconnect pained told God “I remember praying telling God ‘It’s eternity yours’” said decision drove wedge God — Mormons felt didn’t understand doubt quietly wrestled God alone year “I used magical view God view shattered” Michaelann Bradley said “Then Mormon Transhumanism came along anchor don’t know heaven exists make it” 2013 Bradley met future husband academic scripture study group thoughtful historian 18 year senior whose faith LDS Church shaken year Many early date “Mormonadjacent gatherings” Bradley said hardly batted eye invited meeting Mormon Transhumanist Association billed group thoughtful folk tackling slightly different idea Mormonism “I thought meant ‘transcendentalist’” Bradley told “I came prepared talk Thoreau” meeting far Walden moon terraformed Mars Held local tech entrepreneur’s basement philosophical freeforall idea closer science fiction scripture 10 attendee — male white 20 30 mostly background computer science tech world — batted around theory reframed deeply held Mormon belief like notion “As man God God man may become” term cryonics singularity quoted futurist breath Latterday Saint Apostles Carl Sagan asked whether could become like God technology — could live forever die Scratch surface you’ll find Mormon transhumanists believe coming leap science technology help u realize Mormon promise achieving perfect immortal body becoming Gods nearly 1000 member Mormon Transhumanist Association MTA growing offshoot broad transhumanist movement belief human race evolve beyond current mental physical state use science technology order achieve breakthrough outcome near future Think uploading brain cloud freezing body order resuscitate era immortality Championed innovator like Google’s head engineering Ray Kurzweil Elon Musk idea taken hold generation technolibertarians others looking solution — escape hatch — failing world Mormon transhumanism take theory mold onto religious framework technology science tool work Jesus Christ straightforward application like using cybernetic limb help injured disabled people walk laser cataract procedure help people low vision see scratch surface you’ll find Mormon transhumanists believe science bring “realization diverse prophetic vision transfiguration immortality resurrection renewal world discovery creation world without end” believe coming leap science technology help u realize Mormon promise achieving perfect immortal body becoming Gods Bradley left first meeting MTA buzzing first time long time felt home doubt group people “thinking really hard mean faith mean believe science logic” said idea taboo Skepticism doubt part discourse “It invigorating” saidTags Mormon Reasonable Doubt Transhumanism Future Religion
2,878
7 Quotes by Albert Einstein That Will Change How You Think
Albert Einstein is considered one of the smartest people in history. So smart that after his death, the pathologist who inspected his body stole his brain. Thomas Harvey took Einstein’s brain even though the genius clearly stated that he didn’t want his brain or body to be studied after his death. And even though it turned out that Einstein’s brain was really different from the majority, his genius wasn’t always obvious. When he was young, Einstein’s parents even thought that he was disabled because he was slow to learn and didn't talk until he was four years old. Yet he became obsessed with science at the age of five when his father showed him a compass for the first time. In the following decades, he didn’t only develop the theory of relativity and several other inventions that changed the way we see and experience the world but also left us with wisdom on how to live better lives.
https://medium.com/age-of-awareness/7-quotes-by-albert-einstein-that-will-change-how-you-think-6b898c3af6ee
['Sinem Günel']
2020-10-21 14:58:33.837000+00:00
['Creativity', 'Education', 'Psychology', 'Advice', 'Inspiration']
Title 7 Quotes Albert Einstein Change ThinkContent Albert Einstein considered one smartest people history smart death pathologist inspected body stole brain Thomas Harvey took Einstein’s brain even though genius clearly stated didn’t want brain body studied death even though turned Einstein’s brain really different majority genius wasn’t always obvious young Einstein’s parent even thought disabled slow learn didnt talk four year old Yet became obsessed science age five father showed compass first time following decade didn’t develop theory relativity several invention changed way see experience world also left u wisdom live better livesTags Creativity Education Psychology Advice Inspiration
2,879
The Hidden Connection Between Habits and Learning
Learning and habits seem like to separate facts about our psychology. Learning is about knowledge, information and skills. Habits are about routines, behaviors and actions. However, I think the two actually work on mostly the same principles of the brain, and recognizing this connection can help you both learn better and form better habits. Learning = Habits To see the connection, let’s start by asking what a habit is. A habit is a semi-automatic behavioral response, given a certain set of cues in the environment. In other words, when you say you have a habit you mean something of the form “Whenever X happens, I do Y.” Examples: I go to the gym every day = “Every day after work, I go to the gym.” I don’t eat meat = “Whenever there’s meat in something, I don’t eat it.” I have a reading habit = “Whenever I have free time, I tend to read (as opposed to something else)” Informally, habits can be more complicated than a 1:1 association. A regular exercise “habit” may, in fact, be multiple such associations of varying complexity, for instance: “When I plan my day, I always put in exercise.” “If the day is nearly over, and I haven’t exercised yet, I exercise.” “I go after work, except if I have other activities, in which case I go in the morning.” Although some habits are actually just a simple cue and response, most are complex, dealing with specific sub-cases and having rules for certain situations that get embedded so they work most of the time. A habit doesn’t need to be 100% coupled to count, either. A voracious reader may not have a habit that says “whenever X happens, I must read,” but simply a tendency to read more when there’s spare time. Learning, it turns out, is almost exactly like this. To learn something means you produce some kind of response (mentally or physically) when given a set of cues. Examples: I know the capital cities of every state = “When state X is mentioned, in context of asking for the capital city, I produce the correct city, Y.” I can speak Chinese = “When someone speaks to me in Chinese, I produce an appropriate response.” I can ski downhill = “When I’m falling down on my skis, my body automatically produces the motor actions that will get me to the bottom safely.” This may sound hand-wavey, because these examples are so much more complicated and nuanced than simple habits. But as I mentioned before, habits are also often quite complicated, with varying responses for different situations and sometimes only probabilistically so, rather than a completely automated response to a situation. Conscious Control Versus Automatic Action One seeming difference between learning and habits may be that applying what you’ve learned is a more conscious process, whereas a habit is thought to be mostly automatic. An expert painter, for instance, doesn’t just splatter paint on autopilot. Every stroke is a deliberate effort to achieve a particular result. This deliberateness seems the complete opposite of habits, which are defined by their level of automaticity. While this seems to be the case, I’m also inclined to believe it’s more a superficial difference than it first appears. Even in simple habits, there’s often a great deal of flexibility about how to execute it. Take something like exercising every day: should you go in the morning or afternoon? Run or lift weights? Push yourself or take it easy? Of course, a habitual action tends to have a strong default (otherwise it wouldn’t be a habit), but this too is similar to learning. When you encounter a familiar problem, the overriding tendency is to apply the techniques you’ve learned before. To solve a problem in an original way takes effort the same way that breaking out of a habitual groove does. The Neuroscience of Learning and Habits There’s a lot we don’t understand yet about both learning and habit-formation in the brain. But a common principle to both seems to be selectively strengthening the connections between neuronal circuits that lead to the desired output, and weakening incorrect or spurious connections. A habit forms when a sequence of neurons fire forms a strong connection with downstream synapses and thus when the earlier ones fire, the later ones fire with a high probability. Think of this like a river carving a valley into the ground, so the water flowing downhill will be exceedingly likely to follow a certain path. Learning happens when associations of one long-term memory become tightly coupled with another. This can be as simple as a cue-response: “Q: What is the capital of France? A: Paris.” or it can be as complicated as solving a differential equation by having the forms of the differential equation automatically flow to the mental actions that begin to solve it. While there is likely quite a bit of nuance in each of these broad categories, my suspicion is that they overlap considerably, rather than being largely separate domains. Some forms of learning are encoded as motor sequences (such as learning to drive a car), some habits are encoded as associations between higher-level abstractions (such as remembering to write down to-do items when actions are discussed in an office meeting). How to Use this to Learn Better (and Make Better Habits) By seeing learning as similar to habit formation, you can start to view learning not as the process of storing information, but of preparing actions in particular contexts. So learning a language isn’t just storing vocabulary words, but learning to activate certain knowledge, in response to particular situations. Once you see learning as cue-driven and context-based, as well as something that is trained like a habit (through repetition of the pattern of cue-response), then you’ll be much more likely to practice in a way that will eventually be useful. You’ll be able to spot inefficient learning designs when you recognize that the habit you’re creating isn’t the habit you actually need. While it is true that you can’t anticipate every detail of a situation, it’s easy to recognize, for instance that a fundamental habit of mind which is useful when speaking a language is being able to think of an idea/concept and come up with the associate word in the language, but that picking that word out of a wordbox isn’t probably the habit you need (like in apps such as DuoLingo). Similarly, you can improve your habit-formation by seeing it more like an act of learning. Rather than see your habits as being simple units, you can see that you’re trying to create flexible responses to a whole host of situations, all of which need to be conditioned separately. An exercise habit isn’t just going to the gym every day, but finding the appropriate response for all sorts of varied conditions (the gym is closed, you’re feeling sick, you forgot your running shoes, etc.) By seeing habits-as-learning, you recognize that what you’re doing is not simply a matter of self-discipline, but also of exploration, experimentation and trying to create patterns of behavior that produce useful responses in situations you can’t quite predict. This takes time and practice, rather than simply being an act of will to execute. Above all, by seeing the connection between learning and habits, you can see how much of your life is made up of similar patterns. Your thoughts, emotions, relationships and identity also operate on similarly practiced loops of cue and response. See the patterns, and you can start to change them.
https://medium.com/datadriveninvestor/the-hidden-connection-between-habits-and-learning-4ed4ec1f11b6
['Scott H. Young']
2020-12-15 05:12:47.044000+00:00
['Neuroscience', 'Self', 'Productivity', 'Habits', 'Learning']
Title Hidden Connection Habits LearningContent Learning habit seem like separate fact psychology Learning knowledge information skill Habits routine behavior action However think two actually work mostly principle brain recognizing connection help learn better form better habit Learning Habits see connection let’s start asking habit habit semiautomatic behavioral response given certain set cue environment word say habit mean something form “Whenever X happens Y” Examples go gym every day “Every day work go gym” don’t eat meat “Whenever there’s meat something don’t eat it” reading habit “Whenever free time tend read opposed something else” Informally habit complicated 11 association regular exercise “habit” may fact multiple association varying complexity instance “When plan day always put exercise” “If day nearly haven’t exercised yet exercise” “I go work except activity case go morning” Although habit actually simple cue response complex dealing specific subcases rule certain situation get embedded work time habit doesn’t need 100 coupled count either voracious reader may habit say “whenever X happens must read” simply tendency read there’s spare time Learning turn almost exactly like learn something mean produce kind response mentally physically given set cue Examples know capital city every state “When state X mentioned context asking capital city produce correct city Y” speak Chinese “When someone speaks Chinese produce appropriate response” ski downhill “When I’m falling ski body automatically produce motor action get bottom safely” may sound handwavey example much complicated nuanced simple habit mentioned habit also often quite complicated varying response different situation sometimes probabilistically rather completely automated response situation Conscious Control Versus Automatic Action One seeming difference learning habit may applying you’ve learned conscious process whereas habit thought mostly automatic expert painter instance doesn’t splatter paint autopilot Every stroke deliberate effort achieve particular result deliberateness seems complete opposite habit defined level automaticity seems case I’m also inclined believe it’s superficial difference first appears Even simple habit there’s often great deal flexibility execute Take something like exercising every day go morning afternoon Run lift weight Push take easy course habitual action tends strong default otherwise wouldn’t habit similar learning encounter familiar problem overriding tendency apply technique you’ve learned solve problem original way take effort way breaking habitual groove Neuroscience Learning Habits There’s lot don’t understand yet learning habitformation brain common principle seems selectively strengthening connection neuronal circuit lead desired output weakening incorrect spurious connection habit form sequence neuron fire form strong connection downstream synapsis thus earlier one fire later one fire high probability Think like river carving valley ground water flowing downhill exceedingly likely follow certain path Learning happens association one longterm memory become tightly coupled another simple cueresponse “Q capital France Paris” complicated solving differential equation form differential equation automatically flow mental action begin solve likely quite bit nuance broad category suspicion overlap considerably rather largely separate domain form learning encoded motor sequence learning drive car habit encoded association higherlevel abstraction remembering write todo item action discussed office meeting Use Learn Better Make Better Habits seeing learning similar habit formation start view learning process storing information preparing action particular context learning language isn’t storing vocabulary word learning activate certain knowledge response particular situation see learning cuedriven contextbased well something trained like habit repetition pattern cueresponse you’ll much likely practice way eventually useful You’ll able spot inefficient learning design recognize habit you’re creating isn’t habit actually need true can’t anticipate every detail situation it’s easy recognize instance fundamental habit mind useful speaking language able think ideaconcept come associate word language picking word wordbox isn’t probably habit need like apps DuoLingo Similarly improve habitformation seeing like act learning Rather see habit simple unit see you’re trying create flexible response whole host situation need conditioned separately exercise habit isn’t going gym every day finding appropriate response sort varied condition gym closed you’re feeling sick forgot running shoe etc seeing habitsaslearning recognize you’re simply matter selfdiscipline also exploration experimentation trying create pattern behavior produce useful response situation can’t quite predict take time practice rather simply act execute seeing connection learning habit see much life made similar pattern thought emotion relationship identity also operate similarly practiced loop cue response See pattern start change themTags Neuroscience Self Productivity Habits Learning
2,880
Efficient Biomedical Segmentation When Only a Few Label Images Are Available @MICCAI2020
Computer Vision Efficient Biomedical Segmentation When Only a Few Label Images Are Available @MICCAI2020 A Proposal for State-of-the-Art Unsupervised Segmentation Using Contrastive Learning MICCAI 2020 Photo by National Cancer Institute on Unsplash In this story, Label-Efficient Multi-Task Segmentation using Contrastive Learning, by the University of Tokyo and Preferred Networks, is presented. This is published as a technical paper of the MICCAI BrainLes 2020 workshop. In this paper, a multi-task segmentation model is proposed for a precision medical image task where only a small amount of labeled data is available, and contrast learning is used to train the segmentation model. We show experimentally for the first time the effectiveness of contrastive predictive coding [Oord et al., 2018 and H´enaff et al., 2019] as a regularization task for image segmentation using both labeled and unlabeled images, and The results provide a new direction for label-efficient segmentation. The results show that it outperforms other multi-tasking methods, including state-of-the-art fully supervised models, when the amount of annotated data is limited. Experiments suggest that the use of unlabeled data can provide state-of-the-art performance when the amount of annotated data is limited. Let’s see how they achieved that. I will explain only the essence of ssCPCseg, so If you are interested in reading my blog, please click on ssCPCseg paper and Github.
https://medium.com/towards-artificial-intelligence/efficient-biomedical-segmentation-when-only-a-few-label-images-are-available-2e0b2513703d
['Makoto Takamatsu']
2020-12-19 14:21:21.971000+00:00
['Machine Learning', 'Artificial Intelligence', 'Deep Learning', 'Medical Imaging', 'Computer Vision']
Title Efficient Biomedical Segmentation Label Images Available MICCAI2020Content Computer Vision Efficient Biomedical Segmentation Label Images Available MICCAI2020 Proposal StateoftheArt Unsupervised Segmentation Using Contrastive Learning MICCAI 2020 Photo National Cancer Institute Unsplash story LabelEfficient MultiTask Segmentation using Contrastive Learning University Tokyo Preferred Networks presented published technical paper MICCAI BrainLes 2020 workshop paper multitask segmentation model proposed precision medical image task small amount labeled data available contrast learning used train segmentation model show experimentally first time effectiveness contrastive predictive coding Oord et al 2018 H´enaff et al 2019 regularization task image segmentation using labeled unlabeled image result provide new direction labelefficient segmentation result show outperforms multitasking method including stateoftheart fully supervised model amount annotated data limited Experiments suggest use unlabeled data provide stateoftheart performance amount annotated data limited Let’s see achieved explain essence ssCPCseg interested reading blog please click ssCPCseg paper GithubTags Machine Learning Artificial Intelligence Deep Learning Medical Imaging Computer Vision
2,881
Song lyrics generation with Artificial Intelligence (RNN)
1. The theory (a brief overview) Note: If you know enough about Machine Learning and Recurrent Neural Networks (and you are just interested in the code), please skip this part. Let’s try to give a brief (non technical) overview of the theory that is behind this project. Saying Artificial Intelligence is saying so many things, and it collapses into saying almost nothing. With this term we mean generally the entire set of techniques that are used to build some form of ability that we can in some way define “intelligent” (it is unclear, right?). Let’s try to be more precise. In this particular application of this vague term that is Artificial Intelligence, I’ve used Recurrent Neural Networks. What are these beasts? Let’s take a step-back. Neural Networks are Machine Learning algorithms that learn stuff in a layered way, in a similar way of the human learning (from simple concepts to more complex ones). Recurrent Neural Networks is a specific kind of Neural Networks that process the data that are meant to be look in their entire sequence. Let’s say you want to predict the highest temperature you will get tomorrow. A way to do that is to use the Recurrent Neural Networks. This example may seems trivial, but it is actually the same thing we want to do here: From a given sequence as an input, predict the next word, then the next word, then the next word… Let’s play. :) GIF from The Kennedy Center 2. The Dataset The dataset I’ve used is a courtesy of Manva Pradhan and you can find it here Yes, I’ve picked Taylor Swift choruses to train my data. And it is not (just) because she melts my hearts every time she sings. GIF from Giphy These methods work extremely well if you use a lot of data to train your model (you may have encountered the term “Big Data”). The drawback is that you require a lot of computational power to have a decent result out of a lot of data. So I’ve used a single singer and base my model on that. But why did I use Taylor Swift? I’ve done that because she is actually “easy to get” when it is about choruses. She doesn’t use solemn terms and she doesn’t use over-sophisticated metrics. And that’s about it. You could use Ed Sheeran, or Justin Bieber, or someone else (the best thing would be actually to use them all together to create a powerful model). 3. Data pre-processing Let’s give a look at the dataset: So you have the entire lyrics with this line_number for each songs. But we want to write the new choruses, so we’re eventually have to take the choruses only (we will do that, keep calm). In all the datasets I’ve worked, I’ve always found something strange that messes your model up. Unfortunately, this is not an exception. The same album appears multiple times, but with different names, and it is actually a problem. Fixing this with this few lines: Ok, we’re cool. Now, if you look at the starting point of each verse, chorus, or bridge you could find this notation : [Verse], [Chorus], [Bridge] (actually you find it every where, it is like super-basic). So let’s have another column that select the lines that contains that ‘[‘ stuff (1/0). Awesome, now we just have to pick the Choruses. We move in these ‘[‘ values that are specifically the ones of the Choruses (remember that you have stored those in that IND list), and we stop when we find another ‘]’. Again, let’s clean some mess here: Here: And here: With this line: And the die is cast. This is an example: GIF from Ash vs Evil Dead 4. Song-writing RNN These models are complex to build, and unless you are a researcher, you’ll never build a Neural Network from scratch. Here’ s the Recurrent Neural Network I’ve used . The first thing you do is not immediate to comprehend, as it is pretty technical. It regards a series of techniques that are used in order to make strings “readable” as numbers. It is not so interesting to deepen it here, but here’s the TensorFlow commented code: Then you have the interesting part. Words are seen as vectors that needs to be computed in the best way as possible to capture the meaning of the word itself (this method is called embedding). Then, you use the Gated Recurrent Units, that are cells that are able to “remember” a certain number of previous words in a clever way. Finally, you use a dense layer with the logit that gives you an information about the most probable word you expect. Isn’t that awesome? Graph developed by Tensorflow Of course, these methods are “magical but not magic”. So they need to be trained, for a pretty long period of time. Specifically, they are trained to minimize a certain loss you have to attach to your optimizer: Trained model right here: And this is the last step: So the input is: The trained model The start string (remember: the model is “recurrent”) The temperature. This last input is actually amazing. In fact if you use low temperature, you will get predictable results, if you increase the temperature, your lyrics will become more “creative”. You don’t believe me, right? You will. :) 5. Results You would probably be thinking: “Hey man, this is enough. Give me your lyrics”. You’re right bad boy/ girl. Here’s three example, with different values of temperature and different inputs: As I’ve told you, if you increase the temperature you risk to have nonsense lyrics like “Say a mind of my friends are saying”. On the other hand, low temperature takes you to existing lyrics, so you have to be careful and adapt the temperature and the start string. If you want to be more technical, you could use LSTM cell instead of GRU, or use a more powerful machine, or change the data pre processing part. 6. Thinking out loud We are skeptical about “AI writing songs”, and there is a reason why we are. We like to think that Music, Art, Poetry, Cinema doesn’t regards numbers, equation, computers, but belongs to a different part of ourselves, that is the creative and passionate one. As a musician and data scientist, I’m really confused. I would like to think that when I listen to my favourite album and I get goosebumps it is because there is something more about the music that is not just a good mix of sounds and words that are accurately predicted by a logit function. But isn’t it Artificial Intelligence a form of art by itself? Does this “art” actually exist? Does these feelings actually exist? Well, I do have feelings for Taylor Swift though. Ok, I’ve got way too far. As always, please hit me at [email protected] if you have anything you would like to share with me about this project (literally, anything). Thank you :)
https://towardsdatascience.com/song-lyrics-generation-with-artificial-intelligence-rnn-cdba26738530
['Piero Paialunga']
2020-12-29 00:47:11.546000+00:00
['Machine Learning', 'Artificial Intelligence', 'Taylor Swift', 'Lyrics', 'Music']
Title Song lyric generation Artificial Intelligence RNNContent 1 theory brief overview Note know enough Machine Learning Recurrent Neural Networks interested code please skip part Let’s try give brief non technical overview theory behind project Saying Artificial Intelligence saying many thing collapse saying almost nothing term mean generally entire set technique used build form ability way define “intelligent” unclear right Let’s try precise particular application vague term Artificial Intelligence I’ve used Recurrent Neural Networks beast Let’s take stepback Neural Networks Machine Learning algorithm learn stuff layered way similar way human learning simple concept complex one Recurrent Neural Networks specific kind Neural Networks process data meant look entire sequence Let’s say want predict highest temperature get tomorrow way use Recurrent Neural Networks example may seems trivial actually thing want given sequence input predict next word next word next word… Let’s play GIF Kennedy Center 2 Dataset dataset I’ve used courtesy Manva Pradhan find Yes I’ve picked Taylor Swift chorus train data melt heart every time sings GIF Giphy method work extremely well use lot data train model may encountered term “Big Data” drawback require lot computational power decent result lot data I’ve used single singer base model use Taylor Swift I’ve done actually “easy get” chorus doesn’t use solemn term doesn’t use oversophisticated metric that’s could use Ed Sheeran Justin Bieber someone else best thing would actually use together create powerful model 3 Data preprocessing Let’s give look dataset entire lyric linenumber song want write new chorus we’re eventually take chorus keep calm datasets I’ve worked I’ve always found something strange mess model Unfortunately exception album appears multiple time different name actually problem Fixing line Ok we’re cool look starting point verse chorus bridge could find notation Verse Chorus Bridge actually find every like superbasic let’s another column select line contains ‘‘ stuff 10 Awesome pick Choruses move ‘‘ value specifically one Choruses remember stored IND list stop find another ‘’ let’s clean mess line die cast example GIF Ash v Evil Dead 4 Songwriting RNN model complex build unless researcher you’ll never build Neural Network scratch Here’ Recurrent Neural Network I’ve used first thing immediate comprehend pretty technical regard series technique used order make string “readable” number interesting deepen here’s TensorFlow commented code interesting part Words seen vector need computed best way possible capture meaning word method called embedding use Gated Recurrent Units cell able “remember” certain number previous word clever way Finally use dense layer logit give information probable word expect Isn’t awesome Graph developed Tensorflow course method “magical magic” need trained pretty long period time Specifically trained minimize certain loss attach optimizer Trained model right last step input trained model start string remember model “recurrent” temperature last input actually amazing fact use low temperature get predictable result increase temperature lyric become “creative” don’t believe right 5 Results would probably thinking “Hey man enough Give lyrics” You’re right bad boy girl Here’s three example different value temperature different input I’ve told increase temperature risk nonsense lyric like “Say mind friend saying” hand low temperature take existing lyric careful adapt temperature start string want technical could use LSTM cell instead GRU use powerful machine change data pre processing part 6 Thinking loud skeptical “AI writing songs” reason like think Music Art Poetry Cinema doesn’t regard number equation computer belongs different part creative passionate one musician data scientist I’m really confused would like think listen favourite album get goosebump something music good mix sound word accurately predicted logit function isn’t Artificial Intelligence form art “art” actually exist feeling actually exist Well feeling Taylor Swift though Ok I’ve got way far always please hit pieropaialungahotmailcom anything would like share project literally anything Thank Tags Machine Learning Artificial Intelligence Taylor Swift Lyrics Music
2,882
How to Create a Custom Request Model in React Using RxJs, TypeScript, and Fetch
How to Create a Custom Request Model in React Using RxJs, TypeScript, and Fetch Make your API requests easier Image source: Author Shifting from Angular to React wasn’t an easy transition. That was not due to the difference in difficulty between frameworks, but because I knew how much I’d miss the seamless TypeScript integration, along with Services and Pipes, but most of all potentially having to abandon RxJs. That is, until I did some research and realized I wouldn’t have to. So in this article, we’ll be looking at how to implement a base model for using the Fetch API already provided by JavaScript, along with TypeScript and RxJs for some flavor. To get things started, let’s begin by creating a fresh React project with TypeScript support off the bat using the command: npx create-react-app rxjs-react --template typescript If you’d like to add TypeScript support to a current React project, please refer to this link: https://create-react-app.dev/docs/adding-typescript/ After that has been set up, switch to the root directory of your project and run this command to install RxJs: npm i rxjs Upon installation we’re good to go. You can now open the project in your preferred code editor and begin coding. Below is the structure we’ll be following for our files within our project. Please note that these will have to go under our src folder. -services |-api.service.ts |-index.ts -utils |-types.ts |-base-request-model.ts We’ll start off with creating our types.ts . Here we’ll be declaring the allowed types we’ll be using when performing our fetch requests. Next, we’ll be creating our base-request-model.ts . This is the model we’ll be using to make any request coming from our app. We then import these types into our BaseRequestModel like so: import { Method, _Headers, Body } from "./types"; For this example, we’ll be using http://dummy.restapiexample.com/api/v1 as our baseUrl and setting our default method to GET in our constructor. We’ll also be implementing our own interface for the properties. The model will have the following: const baseUrl = 'http://dummy.restapiexample.com/api/v1'; interface Props { url: string; method?: Method; headers: _Headers, body?: Body } We’re making the body optional in the event that we’re making a get request and we don’t supply a body. We then implement the interface by using the keyword “implements” followed by the interface name after our class name. We then create a method that returns an observable, but before that, we’ll have to import the observable interface into our file in order to use it. import {Observable} from 'rxjs' Then we initialize our properties in the BaseModel contructor. A constructor is basically a special method that is used to initialize objects and is called as an object of a class is instantiated. Then we implement the request method. Inside this method is where we’ll be using the built-in Fetch API: https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API We’ll be returning the resolved promise wrapped in a new observable where we pass our values using the next() method provided by the observable and closing the stream using complete() . We can also throw errors using the error() method, similar to how promises use resolve() and reject() . And that’s it for the BaseRequestModel . Below is the complete implementation. Next, we’ll be creating our api.service.ts . Here we’ll be declaring our own fetch methods and returning an observable, as well as creating any custom headers we might need to pass. For now, we’ll be focusing only on post and get , but feel free to add your own methods and develop further if need be. First, we’ll import our BaseRequestModel previously created and the Body interface declared in our types.ts . import BaseRequestModel from '../utils/base-request-model'; import { Body } from '../utils/types'; Then we implement our get method wrapped in an object so we can easily access them, like so: const ApiService = { get: (route: string): Observable<any> => { const headers = { 'Access-Control-Allow-Origin': '*' }; const newBase = new BaseRequestModel(route, 'GET', headers); return newBase.request(); }, } What we’re basically doing here is creating a new instance of our BaseRequestModel . We’re passing the route, the method, and the headers defined by our constructor and then returning the request() method property, which is an observable stream we can subscribe to later to access the values of the request we made. We repeat this for our post method, with the exception of a form parameter, which will be of type Body that we imported from our types and content type of application/json in our headers. We then pass the form into our new BaseRequestModel (this is why we made the body optional). To conclude this part, we’ll export these methods with our index.ts , which we’ll be creating at the root of our services folder. We just need to add the export keyword to our ApiService variable. Below is the complete implementation. Finally, we can test this by simply importing ApiService from our services into any component we’d like to make any fetch methods from. import { ApiService } from "./services"; For now, we’ll be using this in our App.tsx . We’ll start by creating an interface for our employee. interface Employee { id: string; employee_name: string; employee_salary: string; employee_age: string; profile_image?: string; } The Elvis operator “?” indicates that the profile_image property will be optional, and we don’t have to assign a value to it. We’ll start with the get request. You can place this in a function and call it when need be, but for now, we’ll be using this in our useEffect() . Note that on mount, we’re assigning our subscription to a value so we can easily unsubscribe from our observable on cleanup as our component unmounts. We’re also using the take() operator imported from ‘rxjs/operators’ and passing (1) so that we only get the first result of the stream, as well as the map() operator to manipulate any data received before assigning it to any value within the component. In this case, I only want the res.data being returned from the response. We then map the results on our template and add some styling to each div note to declare the style object outside the scope of your component. This will be the result: We then include a button to test adding of an employee, along with the appropriate style declared outside the scope of the component. We then define our addEmployee function. We’ll be passing an object with the id, age, salary, and name of the employee to our post method from our ApiService and then pushing this object to the front of our employee array upon successful subscription or a successful post request. Save, and then click the Add Employee button to see the new employee prepended to our list of employees. Ben Solo has joined the list Below is the complete implementation.
https://medium.com/better-programming/creating-a-fetch-model-for-react-using-rxjs-typescript-e2aecf113023
['Rogelio Monteagudo']
2020-11-11 03:38:39.322000+00:00
['JavaScript', 'Typescript', 'React', 'Reactjs', 'Programming']
Title Create Custom Request Model React Using RxJs TypeScript FetchContent Create Custom Request Model React Using RxJs TypeScript Fetch Make API request easier Image source Author Shifting Angular React wasn’t easy transition due difference difficulty framework knew much I’d miss seamless TypeScript integration along Services Pipes potentially abandon RxJs research realized wouldn’t article we’ll looking implement base model using Fetch API already provided JavaScript along TypeScript RxJs flavor get thing started let’s begin creating fresh React project TypeScript support bat using command npx createreactapp rxjsreact template typescript you’d like add TypeScript support current React project please refer link httpscreatereactappdevdocsaddingtypescript set switch root directory project run command install RxJs npm rxjs Upon installation we’re good go open project preferred code editor begin coding structure we’ll following file within project Please note go src folder service apiservicets indexts utils typests baserequestmodelts We’ll start creating typests we’ll declaring allowed type we’ll using performing fetch request Next we’ll creating baserequestmodelts model we’ll using make request coming app import type BaseRequestModel like import Method Headers Body type example we’ll using httpdummyrestapiexamplecomapiv1 baseUrl setting default method GET constructor We’ll also implementing interface property model following const baseUrl httpdummyrestapiexamplecomapiv1 interface Props url string method Method header Headers body Body We’re making body optional event we’re making get request don’t supply body implement interface using keyword “implements” followed interface name class name create method return observable we’ll import observable interface file order use import Observable rxjs initialize property BaseModel contructor constructor basically special method used initialize object called object class instantiated implement request method Inside method we’ll using builtin Fetch API httpsdevelopermozillaorgenUSdocsWebAPIFetchAPI We’ll returning resolved promise wrapped new observable pas value using next method provided observable closing stream using complete also throw error using error method similar promise use resolve reject that’s BaseRequestModel complete implementation Next we’ll creating apiservicets we’ll declaring fetch method returning observable well creating custom header might need pas we’ll focusing post get feel free add method develop need First we’ll import BaseRequestModel previously created Body interface declared typests import BaseRequestModel utilsbaserequestmodel import Body utilstypes implement get method wrapped object easily access like const ApiService get route string Observableany const header AccessControlAllowOrigin const newBase new BaseRequestModelroute GET header return newBaserequest we’re basically creating new instance BaseRequestModel We’re passing route method header defined constructor returning request method property observable stream subscribe later access value request made repeat post method exception form parameter type Body imported type content type applicationjson header pas form new BaseRequestModel made body optional conclude part we’ll export method indexts we’ll creating root service folder need add export keyword ApiService variable complete implementation Finally test simply importing ApiService service component we’d like make fetch method import ApiService service we’ll using Apptsx We’ll start creating interface employee interface Employee id string employeename string employeesalary string employeeage string profileimage string Elvis operator “” indicates profileimage property optional don’t assign value We’ll start get request place function call need we’ll using useEffect Note mount we’re assigning subscription value easily unsubscribe observable cleanup component unmounts We’re also using take operator imported ‘rxjsoperators’ passing 1 get first result stream well map operator manipulate data received assigning value within component case want resdata returned response map result template add styling div note declare style object outside scope component result include button test adding employee along appropriate style declared outside scope component define addEmployee function We’ll passing object id age salary name employee post method ApiService pushing object front employee array upon successful subscription successful post request Save click Add Employee button see new employee prepended list employee Ben Solo joined list complete implementationTags JavaScript Typescript React Reactjs Programming
2,883
A Founder’s Story: Julian Mazzitelli, CIO of BioBox Analytics (3/3)
When I began my undergraduate degree at the University of Toronto, I knew exactly what I was going to study. It started in a high school civics class, when our teacher handed out some university program fliers to help us figure out our career paths. One of these fliers was for a Bioinformatics program. I learned that a specialization in Bioinformatics combined two of my strongest passions — Biology & Computer Science. From that point on, I would go on to pursue those passions relentlessly throughout undergrad, and now at BioBox. An exemplary instance of combining my passions is the real-scale 3D mitochondria I built for a project course. Outside of classes I kept these passions alive by participating in a Google Summer of Code project under the Open Bioinformatics Foundation, leading the iGEM dry lab team and joining the Center for Computational Medicine as a co-op student, where I would end up staying beyond my co-op term as summer research student on the CANDIG project. At CCM I worked on full stack web development, cloud computing infrastructure, and would participate in the bioinformatician team meetings. These skills in concert, unknowingly to me at the time, had prepared me for what would be the most exciting opportunity yet… The powerhouse of the cell One fateful evening, my co-founder Chris and I were having 🐟 sushi 🍣 at a favourite UofT spot on Baldwin. Chris had wrote a simple web application for biologists to configure plots to their data and was surprised at how well it was received. This first prototypal app exposed two pain points from both sides of the biology research fence: Biologists want independence and autonomy when investigating data and Bioinformaticians want to spend more time on challenging problems rather than manually making modifications to plotting parameters. Shortly thereafter, I was introduced to my second co-founder, Hamza, and the trio was formed. I started BioBox with my two co-founders because we all have strong convictions to fix the problems that we ourselves had experienced. As a biologist (Chris), a bioinformatician (Hamza), and an infrastructure developer (Yours Truly), we each had a different perspective on the same problems. We bonded over our shared optimism that these problems could in fact be tackled, and imagined the possibilities of such a software. Confidence in my co-founders is the ultimate reason I chose to join BioBox. When not directly developing code for the product, I act as our DevOps ambassador by ensuring that our developers and team at large have a productive work environment. In the same way BioBox streamlines the research process between bioinformaticians and biologists, I am excited to apply DevOps methodologies and tools to our company’s internal assembly line to foster efficiencies. We have built the continuous integration and continuous deployment capabilities from the beginning with these goals in mind. My personal mandate to utilize DevOps practices doesn’t stop at our company. Last fall I gave a conference talk on GitOps-based continuous delivery with Kubernetes as well as a meetup talk on leveraging GitOps for developer environments! I believe that a strong DevOps culture is key to a company’s success and am passionate about sharing it with the greater DevOps community. GDG DevFest 2019 in Montreal While DevOps has improved our internal processes, no amount of perfect sprint planning or developer tooling will scratch the itch my co-founders and I initially bonded over. The real meat and potatoes of BioBox is delivering a web application to enable the autonomy of biologists to explore their data while simultaneously streamlining the collaboration process for bioinformaticians. I am beyond excited to continue to build this company alongside my colleagues, to influence our internal processes and culture, and to leverage my skills to help make our product the best it can possibly be.
https://medium.com/bioboxanalytics/a-founders-story-julian-mazzitelli-cio-of-biobox-analytics-3-3-d2ebd7ac6bc4
['Julian Mazzitelli']
2020-12-10 13:49:03.491000+00:00
['Software Development', 'Founder Stories', 'Startup', 'Kubernetes', 'DevOps']
Title Founder’s Story Julian Mazzitelli CIO BioBox Analytics 33Content began undergraduate degree University Toronto knew exactly going study started high school civics class teacher handed university program flier help u figure career path One flier Bioinformatics program learned specialization Bioinformatics combined two strongest passion — Biology Computer Science point would go pursue passion relentlessly throughout undergrad BioBox exemplary instance combining passion realscale 3D mitochondrion built project course Outside class kept passion alive participating Google Summer Code project Open Bioinformatics Foundation leading iGEM dry lab team joining Center Computational Medicine coop student would end staying beyond coop term summer research student CANDIG project CCM worked full stack web development cloud computing infrastructure would participate bioinformatician team meeting skill concert unknowingly time prepared would exciting opportunity yet… powerhouse cell One fateful evening cofounder Chris 🐟 sushi 🍣 favourite UofT spot Baldwin Chris wrote simple web application biologist configure plot data surprised well received first prototypal app exposed two pain point side biology research fence Biologists want independence autonomy investigating data Bioinformaticians want spend time challenging problem rather manually making modification plotting parameter Shortly thereafter introduced second cofounder Hamza trio formed started BioBox two cofounder strong conviction fix problem experienced biologist Chris bioinformatician Hamza infrastructure developer Truly different perspective problem bonded shared optimism problem could fact tackled imagined possibility software Confidence cofounder ultimate reason chose join BioBox directly developing code product act DevOps ambassador ensuring developer team large productive work environment way BioBox streamlines research process bioinformaticians biologist excited apply DevOps methodology tool company’s internal assembly line foster efficiency built continuous integration continuous deployment capability beginning goal mind personal mandate utilize DevOps practice doesn’t stop company Last fall gave conference talk GitOpsbased continuous delivery Kubernetes well meetup talk leveraging GitOps developer environment believe strong DevOps culture key company’s success passionate sharing greater DevOps community GDG DevFest 2019 Montreal DevOps improved internal process amount perfect sprint planning developer tooling scratch itch cofounder initially bonded real meat potato BioBox delivering web application enable autonomy biologist explore data simultaneously streamlining collaboration process bioinformaticians beyond excited continue build company alongside colleague influence internal process culture leverage skill help make product best possibly beTags Software Development Founder Stories Startup Kubernetes DevOps
2,884
The Cone of Silence: Speech Separation by Localization
The model produces an audio track with the speaker’s speech and predicts the speaker’s position in relation to the microphones. The neural network handles audio recordings where speakers speak simultaneously and interrupt each other. The neural network isolates sound sources for a particular corner. By decreasing the angle exponentially, the model localizes and separates sound sources in logarithmic time. The algorithm works on audio recordings with any number of moving speakers. Based on the results of the experiments, the model produces state-of-the-art results both on the problem of localizing the source of noise and on the problem of separating speakers.
https://medium.com/deep-learning-digest/the-cone-of-silence-speech-separation-by-localization-91fd7eb9c3c5
['Mikhail Raevskiy']
2020-11-12 11:57:13.707000+00:00
['Machine Learning', 'Artificial Intelligence', 'Deep Learning', 'AI', 'Data Science']
Title Cone Silence Speech Separation LocalizationContent model produce audio track speaker’s speech predicts speaker’s position relation microphone neural network handle audio recording speaker speak simultaneously interrupt neural network isolates sound source particular corner decreasing angle exponentially model localizes separate sound source logarithmic time algorithm work audio recording number moving speaker Based result experiment model produce stateoftheart result problem localizing source noise problem separating speakersTags Machine Learning Artificial Intelligence Deep Learning AI Data Science
2,885
15 virtual AI assistants for digital marketers
15 virtual AI assistants for digital marketers A quick look at AI digital assistants to carry out marketing tasks (track metrics, detect anomalies, analyze ads, create and publish content, suggest how to optimize campaigns, generate reports) Inspired by Seth Louey I decided to share this list of virtual AI assistants for digital marketers. Hope you will find some useful assistants to carry out your marketing tasks. To create and publish content #1 Yala — a chatbot that uses machine learning to find the best time to schedule social media posts. Channels: Facebook, Twitter, LinkedIn. Platforms: Facebook Messenger, Slack. #2 Martin — content curation bot powered by A.I. Martin learns what you post to your Page and finds new content for you. Channels: Facebook. Platforms: Facebook Messenger. #3 Rocco — will suggest fresh content that your followers are likely to engage with. Spend less time coming up with content strategies and crafting social-media posts. Platforms: Slack. To track metrics and get reports #4 Statsbot — monitors your application’s metrics by integrating with tools like Google Analytics, Salesforce and Mixpanel. Platforms: Slack. #5 Hunch — the fastest way to check on all PPC campaigns across Facebook and Adwords at once. Channels: Facebook, Adwords, Twitter. Platforms: Slack. #6 Revere — get critical alerts in Slack for AdWords campaigns and Optimizely experiments. Channels: Adwords, Optimizely. Platforms: Slack. #7 Maisie — AI-powered marketing analyst. Maisie’s goal is to help you be more effective with your marketing so you can successfully grow your business. Integrated with Google analytics. Platforms: Slack. #8 Reveal — your personal marketing assistant who warns you when you lose money on ads. Channels: Facebook, Instagram, Adwords, Youtube. Platforms: Slack. To make decisions and optimize ad campaigns #9 Leadza — a personal advertising assistant for Facebook marketers that sends daily optimizations tips which saves you ad spend and improve campaign performance. Channels: Facebook, Instagram. Platforms: Facebook Messanger. #10 Aiden — AI powered virtual colleague for marketers that helps you spend your marketing budget efficiently. Integrated with Google analytics. Platforms: Facebook Messenger, Slack, Skype, SMS. #11 Crystal — turn data into clear answers with the latest technologies in order to help modern-day marketers and companies make better decisions to reach their targets. Channels: Facebook, Google, Twitter, Youtube, Instagram, LinkedIn. Platforms: Mobile Website, iOS, Android. #12 IBM Watson Marketing Assistant — is intended to simplify the analysis and decisions made by marketers trying to understand the effects of different components on their campaigns. Powered by voice. To create and run simple marketing campaigns #13 Kit — helps drive sales by doing everything from creating Facebook ads, to sending thank you emails, to handling the other apps that you use with your Shopify store. Channels: Email, Facebook, Instagram, MMS, Bold aps, Yotpo. Platforms: Facebook Messуnger, SMS, Telegram. #14 Joy — is an AI powered virtual assistant to run personalized 1v1 marketing campaigns on social media and messaging channels. Channels: Facebook, Instagram, Twitter. Platforms: Mobile Website. To get marketing advice #15 GrowthBot — gives you useful information in a fast, friendly chat interface. It’s built for marketing, sales and others working on driving growth for companies. Uses Google analytics and Hubspot data. Platforms: Facebook Messenger, Slack, Twitter. This list does not pretend to be complete. It would be great if you will help to add new solutions for marketers that you already use and like. Your comments and suggestions are welcome!
https://medium.com/leadza/15-virtual-ai-assistants-for-digital-marketers-d84265dce79e
['Victoria Fast']
2017-10-27 04:56:14.233000+00:00
['AI', 'Digital Marketing', 'Virtual Assistant', 'Artificial Intelligence']
Title 15 virtual AI assistant digital marketersContent 15 virtual AI assistant digital marketer quick look AI digital assistant carry marketing task track metric detect anomaly analyze ad create publish content suggest optimize campaign generate report Inspired Seth Louey decided share list virtual AI assistant digital marketer Hope find useful assistant carry marketing task create publish content 1 Yala — chatbot us machine learning find best time schedule social medium post Channels Facebook Twitter LinkedIn Platforms Facebook Messenger Slack 2 Martin — content curation bot powered AI Martin learns post Page find new content Channels Facebook Platforms Facebook Messenger 3 Rocco — suggest fresh content follower likely engage Spend le time coming content strategy crafting socialmedia post Platforms Slack track metric get report 4 Statsbot — monitor application’s metric integrating tool like Google Analytics Salesforce Mixpanel Platforms Slack 5 Hunch — fastest way check PPC campaign across Facebook Adwords Channels Facebook Adwords Twitter Platforms Slack 6 Revere — get critical alert Slack AdWords campaign Optimizely experiment Channels Adwords Optimizely Platforms Slack 7 Maisie — AIpowered marketing analyst Maisie’s goal help effective marketing successfully grow business Integrated Google analytics Platforms Slack 8 Reveal — personal marketing assistant warns lose money ad Channels Facebook Instagram Adwords Youtube Platforms Slack make decision optimize ad campaign 9 Leadza — personal advertising assistant Facebook marketer sends daily optimization tip save ad spend improve campaign performance Channels Facebook Instagram Platforms Facebook Messanger 10 Aiden — AI powered virtual colleague marketer help spend marketing budget efficiently Integrated Google analytics Platforms Facebook Messenger Slack Skype SMS 11 Crystal — turn data clear answer latest technology order help modernday marketer company make better decision reach target Channels Facebook Google Twitter Youtube Instagram LinkedIn Platforms Mobile Website iOS Android 12 IBM Watson Marketing Assistant — intended simplify analysis decision made marketer trying understand effect different component campaign Powered voice create run simple marketing campaign 13 Kit — help drive sale everything creating Facebook ad sending thank email handling apps use Shopify store Channels Email Facebook Instagram MMS Bold aps Yotpo Platforms Facebook Messуnger SMS Telegram 14 Joy — AI powered virtual assistant run personalized 1v1 marketing campaign social medium messaging channel Channels Facebook Instagram Twitter Platforms Mobile Website get marketing advice 15 GrowthBot — give useful information fast friendly chat interface It’s built marketing sale others working driving growth company Uses Google analytics Hubspot data Platforms Facebook Messenger Slack Twitter list pretend complete would great help add new solution marketer already use like comment suggestion welcomeTags AI Digital Marketing Virtual Assistant Artificial Intelligence
2,886
“ProGuard”-A Safe and Unique Platform for Sharing Confidential Files Using AWS
Privacy is the main concern in today’s world. There are many threats to the integrity of data and can be more harmful if the data is highly confidential. Encrypting the data and adding security layers is a must when dealing with highly confidential information. And for this purpose, using Advanced Encryption Standard (AES) encryption-decryption algorithm becomes most important as the AES algorithm is very difficult to crack. What is Advanced Encryption Standard (AES)? The Advanced Encryption Standard (AES) is a symmetric block cipher used to protect classified information.There are three block ciphers in AES: AES-128, AES-192 and AES-256. AES-128 uses a 128-bit key length to encrypt-decrypt a block of messages, while AES-192 uses a 192-bit key length and AES-256 uses a 256-bit key length to encrypt-decrypt messages. Each cipher encrypts and decrypts data in blocks of 128 bits using cryptographic keys of 128, 192 and 256 bits. Symmetric, also known as secret key, ciphers use the same key for encrypting and decrypting, so the sender and the receiver must both know and use the same secret key. There are 10 rounds for 128-bit keys, 12 rounds for 192-bit keys and 14 rounds for 256-bit keys. A round consists of several processing steps that include substitution, transposition and mixing of the input plain-text to transform it into the final output of cipher-text. It uses higher length key sizes such as 128, 192 and 256 bits for encryption. Hence it makes AES algorithm more robust against hacking. What is ProGuard and how it works? ProGuard is a safe platform for transferring confidential files by encrypting the files and sending them to receiver using AWS instance which is slightly different approach than the current platforms. Here there are two applications: 1) Stand-alone Application and 2) Web Application. The stand-alone application works on local machine for encryption-decryption and securing the files. The web application runs on cloud for the purpose of sending the encoded file and key to the receiver which he can later download the file and key to decode it through stand-alone application. Pre-requisites Necessary dependencies for this project: Flask Pycrypto Reportlib Secretsharing PyPDF2 Below is the step-by-step process for implementing the program to share the files securely: 1. Stand-alone Application Step 1: Download the project folder from my Github page and install all the necessary dependencies for this project. You can also find all the libraries listed above in the site-packages folder within the ProGuard folder. Step 2: Create one text file and write your data which you intend to encrypt and share with others. Step 3: Go to ProGuard/source/stand-alone-application and run the main.py file. Here one dialog box will appear in which you have to select the text file which you want to encrypt and share. After browsing the file location, you have to enter the pass-key and secret-key which can also be called as public key of receiver and private key of sender. These keys will be further used for generating keys for AES algorithm. Step 4: After entering the details, press the Encrypt button to generate the encoded file on the destination folder. Note that the original file gets replaced with the encoded file. So currently you will not have your original data file on the machine but only the encoded file. Now you will see the file name EncodedFile.txt on your destination place in local machine. Step 5: Now click the Make PDF button on the stand-alone application to generate the PDF of the keys used for encryption. Here you have to enter the pass-key and secret-key which you entered in the application and also the name of the PDF. Step 6: Now press the Create PDF button. It will create a new PDF of the information that you entered above and will be present in your stand-alone-application folder. Step 7: Now press the Secure PDF button. Another dialog box will appear after this. Here you have to choose the PDF file location and also the pass-key. Note that this pass-key is not the same as discussed above. This pass-key will be the password for accessing the PDF, so the pass-key should be known to both the party. For example, pass-key can be the last four digits of the contact number of receiver which is pre-decided by both the parties. After securing, you will find one new PDF file created named ENCRYPTED_KEY.pdf in the folder. After entering the correct password, the keys in the PDF are accessible. Step 8: Now comes the decryption part. Go to the dialog box in Step 3, and select the file location which you want to decrypt. Enter the pass-key and secret-key and lastly press the Decrypt button. You will find the same original data file with name DecodedFile.txt in the destination that you provided in the application. First part of the process is completed with stand-alone application. Now comes the second portion of the process i.e. file sharing through web application using AWS.
https://medium.com/swlh/proguard-a-safe-and-unique-platform-for-sharing-confidential-files-using-aws-f2694d0247e5
['Kirtan Pathak']
2020-10-15 21:02:54.797000+00:00
['Python', 'Security', 'AWS', 'Privacy', 'Cryptography']
Title “ProGuard”A Safe Unique Platform Sharing Confidential Files Using AWSContent Privacy main concern today’s world many threat integrity data harmful data highly confidential Encrypting data adding security layer must dealing highly confidential information purpose using Advanced Encryption Standard AES encryptiondecryption algorithm becomes important AES algorithm difficult crack Advanced Encryption Standard AES Advanced Encryption Standard AES symmetric block cipher used protect classified informationThere three block cipher AES AES128 AES192 AES256 AES128 us 128bit key length encryptdecrypt block message AES192 us 192bit key length AES256 us 256bit key length encryptdecrypt message cipher encrypts decrypts data block 128 bit using cryptographic key 128 192 256 bit Symmetric also known secret key cipher use key encrypting decrypting sender receiver must know use secret key 10 round 128bit key 12 round 192bit key 14 round 256bit key round consists several processing step include substitution transposition mixing input plaintext transform final output ciphertext us higher length key size 128 192 256 bit encryption Hence make AES algorithm robust hacking ProGuard work ProGuard safe platform transferring confidential file encrypting file sending receiver using AWS instance slightly different approach current platform two application 1 Standalone Application 2 Web Application standalone application work local machine encryptiondecryption securing file web application run cloud purpose sending encoded file key receiver later download file key decode standalone application Prerequisites Necessary dependency project Flask Pycrypto Reportlib Secretsharing PyPDF2 stepbystep process implementing program share file securely 1 Standalone Application Step 1 Download project folder Github page install necessary dependency project also find library listed sitepackages folder within ProGuard folder Step 2 Create one text file write data intend encrypt share others Step 3 Go ProGuardsourcestandaloneapplication run mainpy file one dialog box appear select text file want encrypt share browsing file location enter passkey secretkey also called public key receiver private key sender key used generating key AES algorithm Step 4 entering detail press Encrypt button generate encoded file destination folder Note original file get replaced encoded file currently original data file machine encoded file see file name EncodedFiletxt destination place local machine Step 5 click Make PDF button standalone application generate PDF key used encryption enter passkey secretkey entered application also name PDF Step 6 press Create PDF button create new PDF information entered present standaloneapplication folder Step 7 press Secure PDF button Another dialog box appear choose PDF file location also passkey Note passkey discussed passkey password accessing PDF passkey known party example passkey last four digit contact number receiver predecided party securing find one new PDF file created named ENCRYPTEDKEYpdf folder entering correct password key PDF accessible Step 8 come decryption part Go dialog box Step 3 select file location want decrypt Enter passkey secretkey lastly press Decrypt button find original data file name DecodedFiletxt destination provided application First part process completed standalone application come second portion process ie file sharing web application using AWSTags Python Security AWS Privacy Cryptography
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Scalable & Highly Available Web & Mobile App Architecture
This is a quick overview of how to architect a web+mobile application in a way it is scalable and highly available. We will use AWS cloud technologies to implement the architecutre to achieve these targets. What is High Availability? A highly available application is one that can function properly when one or more of its components fail. It does not have a single point of failure, that is, when one component fails, the application can still deliver correct results. What is scalability? Scalability is the ability of an application to fulfill its functions properly when its execution rate becomes higher. For example, in the case of a HTTP API, it concretely means the ability of the API to respond correctly and in a reasonable time to all requests when the number of requests per second goes higher. Typical Application Architecture Modern applications typically consist of one or more frontend clients used by customers (one or more native mobile apps + a javascript app), talking to one back-end through HTTP API. The back-end stores data in a database and responds to requests coming from front-end clients. Design for High Availability Single points of failure The first step is to identify where a failure can compromise the availability of the application. All the following are single points of failure : The locations where the front-end clients are stored for distribution. If a location becomes unavailable, one of the clients cannot be accessed and used by customers, and thus cannot use the application. The HTTP API back-end component. If this component fails, requests sent by front-end clients will not be fullfilled. The database. If the database fails, the back-end will not be able to extract stored data or write data in response to API requests sent by clients. HA for front-end clients distribution locations The locations where the front-end clients are stored for distribution depend of the target platform. In case of Android and IOS clients, these locations are typically Google Play Store and Apple App Store. Or mobile app stores in general. High availability of these locations are handled by Google, Apple and app stores owners and we can’t do much about it. For web client, we can store it in AWS S3 and distribute it with AWS Cloudfront, which makes it not only highly available but also scalable as we will see later. Using this setup is so common today. Here is a step by step tutorial about how to achieve that. HA for Back-end The back-end API component needs to be up and running to respond to any request sent by front-end clients. The basic setup consists in running one instance of Nodejs express server that fullfills HTTP requests. But if that instance goes down for whatever reason, the application is not available anymore. One approach is to launch multiple EC2 instances hosting your servers on multiple Availability Zones / Regions. Then use Amazon Elastic Load Balancer to distribute the incoming requests to the healthy instances. Amazon ELB does the health check automatically so that if it finds that an instance is not responding, it does not forward future requests to it. Using Amazon ELB has another advantage, it can do the SSL/HTTPS connection management for us so that our servers receive plain HTTP traffic. This is a big advantage, given the high cost of SSL connection management computing. And since usage of SSL is increasingly being enforced by web browsers and platforms, this comes really handy. HA for Database The typical way to ensure high availability of a database is to have replicas in different availability zones that are the mirror of the master database. When the master becomes unavailable, one of the replicas takes the role of the master. Replication can be done either the old way, setting up multiple EC2 instances each hosting a database replica, and you manage the replication and failover by yourself. Or you can use Amazon RDS which manages the database server for you and takes care of maintenance, upgrades, replications and failover. Note that Amazon RDS is for relational database servers. There are also offerings for NoSql databases. Design for Scalability Now we know how to make our application highly available. But what about scalability? How to make sure our application can cope with traffic peaks and still functions properly under heavy load? Front-end clients distribution For front-end clients distribution, mobile app stores and Amazon cloudfront are designed to be highly scalable so no need to worry about that point. Backend API For the back-end part, Amazon EC2 Auto Scaling can be leveraged to automatically scale your Nodejs servers when required. Amazon Elastic Load Balancer works well with EC2 Auto Scaling. Here is a tutorial about how to achieve it. Another way to achieve scalability is to use Amazon API Gateway in combination with AWS Lambda. The first lets you define endpoints for your API. The second lets you execute functions without managing any server. This is called Serverless Computing. Express application servers can easily be updated to run as lambda function using serverless-http npm module. It will be triggered when front-end clients fire HTTPS requests to your defined APIs. Amazon API Gateway is highly available and scalable and you can use your own domains and subdomains to trigger it. Amazon API Gateway + AWS Lambda can be used as a replacement for Amazon Elastic Load Balancer + Amazon EC2 Auto Scaling + EC2 with less administration overhead. It should also cost less. It costs nothing when you have no or low traffic. Database Coming to database, it is not as easy to scale as computing since most databases can support a limited number of open connections, depending on the database server and the underlying machine available memory. The first step scaling database layer is to use some pooling mechanism that can recycle connections and manage them in an efficient way. Amazon RDS Proxy achieves this pooling mechanism for serverless applications that use AWS lambda. But even if it improves and optimizes connection management to your RDS instance, the proxy is not sufficient in case of heavy load. Once the pool is saturated due to high number of concurrent requests, the remaining requests will be delayed and will probably time out. The second step, is to use a memory cache like Redis or the equivalent AWS offer called Amazon ElasticCache. Memory caches are incredibly fast and have a very low latency. They also have much lighter connection management mechanisms and support a much higher number of simultanous connections. So you will need to implement your data access methods in your application in a way that they look for data in the cache first, and only if it is not available or is outdated, retrieve it from database. Obviously, this is rather applicable to the read operations. Write operations should be done on the database for consistency. One way to scale write operations is to handle them asynchronically. An example implementation would be to send write commands to an Amazon SQS queue and have them executed by another lambda function. This way, write operations and database connections are made in a predictable manner. Please note as well that to have a highly available memory cache setup you need either use multiple instances of Redis with sentinels or use Amazon ElasticCache with replicas. Client Side Caching Implementing caching on front-end client side can be benefical for two aspects : It allows to reduce the load on the back-end by serving data that does not change frequently from local cache. It provides a better overall user experience, allowing users to still use some parts of your application when your back-end is not reachable. This typically happens when a mobile user has no internet connection. Users appreciate when they can still use applications offline. A simple cache can be implemented as a key,value,ttl array with 3 simple methods : set(key,value[,ttl]) : store or update an object in the cache indexed by key with optional time to live get(key) : get the object indexed by key if it exists and is not expired getCacheEntry(key) : get the object indexed by key even if it has expired. The result could be something like {object : …, expired: true|false} SharedPreferences could be used to store cache data in Android if it is relatively small. On Web application side, LocalStorage can be leveraged to achieve the same. One more convenient way is to use LocalForage which abstracts the underlying storage APIs and use the optimal ones when available. Conclusion I hope this article was a helpful overview. There is no step by step tutorial or code snippets but this is intended to be a quick overview about making your application scalable and highly available. I used most of these concepts to architect couponfog the coupons app.
https://medium.com/swlh/scalable-highly-available-web-mobile-app-architecture-d803b8ba56e
['Ahmed Mahouachi']
2020-11-10 08:56:17.856000+00:00
['AWS Lambda', 'High Availability', 'React', 'AWS', 'Scalability']
Title Scalable Highly Available Web Mobile App ArchitectureContent quick overview architect webmobile application way scalable highly available use AWS cloud technology implement architecutre achieve target High Availability highly available application one function properly one component fail single point failure one component fails application still deliver correct result scalability Scalability ability application fulfill function properly execution rate becomes higher example case HTTP API concretely mean ability API respond correctly reasonable time request number request per second go higher Typical Application Architecture Modern application typically consist one frontend client used customer one native mobile apps javascript app talking one backend HTTP API backend store data database responds request coming frontend client Design High Availability Single point failure first step identify failure compromise availability application following single point failure location frontend client stored distribution location becomes unavailable one client cannot accessed used customer thus cannot use application HTTP API backend component component fails request sent frontend client fullfilled database database fails backend able extract stored data write data response API request sent client HA frontend client distribution location location frontend client stored distribution depend target platform case Android IOS client location typically Google Play Store Apple App Store mobile app store general High availability location handled Google Apple app store owner can’t much web client store AWS S3 distribute AWS Cloudfront make highly available also scalable see later Using setup common today step step tutorial achieve HA Backend backend API component need running respond request sent frontend client basic setup consists running one instance Nodejs express server fullfills HTTP request instance go whatever reason application available anymore One approach launch multiple EC2 instance hosting server multiple Availability Zones Regions use Amazon Elastic Load Balancer distribute incoming request healthy instance Amazon ELB health check automatically find instance responding forward future request Using Amazon ELB another advantage SSLHTTPS connection management u server receive plain HTTP traffic big advantage given high cost SSL connection management computing since usage SSL increasingly enforced web browser platform come really handy HA Database typical way ensure high availability database replica different availability zone mirror master database master becomes unavailable one replica take role master Replication done either old way setting multiple EC2 instance hosting database replica manage replication failover use Amazon RDS manages database server take care maintenance upgrade replication failover Note Amazon RDS relational database server also offering NoSql database Design Scalability know make application highly available scalability make sure application cope traffic peak still function properly heavy load Frontend client distribution frontend client distribution mobile app store Amazon cloudfront designed highly scalable need worry point Backend API backend part Amazon EC2 Auto Scaling leveraged automatically scale Nodejs server required Amazon Elastic Load Balancer work well EC2 Auto Scaling tutorial achieve Another way achieve scalability use Amazon API Gateway combination AWS Lambda first let define endpoint API second let execute function without managing server called Serverless Computing Express application server easily updated run lambda function using serverlesshttp npm module triggered frontend client fire HTTPS request defined APIs Amazon API Gateway highly available scalable use domain subdomains trigger Amazon API Gateway AWS Lambda used replacement Amazon Elastic Load Balancer Amazon EC2 Auto Scaling EC2 le administration overhead also cost le cost nothing low traffic Database Coming database easy scale computing since database support limited number open connection depending database server underlying machine available memory first step scaling database layer use pooling mechanism recycle connection manage efficient way Amazon RDS Proxy achieves pooling mechanism serverless application use AWS lambda even improves optimizes connection management RDS instance proxy sufficient case heavy load pool saturated due high number concurrent request remaining request delayed probably time second step use memory cache like Redis equivalent AWS offer called Amazon ElasticCache Memory cache incredibly fast low latency also much lighter connection management mechanism support much higher number simultanous connection need implement data access method application way look data cache first available outdated retrieve database Obviously rather applicable read operation Write operation done database consistency One way scale write operation handle asynchronically example implementation would send write command Amazon SQS queue executed another lambda function way write operation database connection made predictable manner Please note well highly available memory cache setup need either use multiple instance Redis sentinel use Amazon ElasticCache replica Client Side Caching Implementing caching frontend client side benefical two aspect allows reduce load backend serving data change frequently local cache provides better overall user experience allowing user still use part application backend reachable typically happens mobile user internet connection Users appreciate still use application offline simple cache implemented keyvaluettl array 3 simple method setkeyvaluettl store update object cache indexed key optional time live getkey get object indexed key exists expired getCacheEntrykey get object indexed key even expired result could something like object … expired truefalse SharedPreferences could used store cache data Android relatively small Web application side LocalStorage leveraged achieve One convenient way use LocalForage abstract underlying storage APIs use optimal one available Conclusion hope article helpful overview step step tutorial code snippet intended quick overview making application scalable highly available used concept architect couponfog coupon appTags AWS Lambda High Availability React AWS Scalability
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Disaster Recovery: Backing Up your Oracle Database with Oracle Database Cloud Backup Service, RMAN, and Object Storage
Disaster Recovery: Backing Up your Oracle Database with Oracle Database Cloud Backup Service, RMAN, and Object Storage how to back up your Oracle Cloud Database Photo by Kevin Ku on Unsplash How can we prepare for disaster? If a server crashes, a technician unplugs a machine, or a meteor hits a datacenter, how can the business recover crucial data? In this tutorial we demonstrate how to backup the Oracle Cloud Database with Oracle Database Cloud Backup Service, RMAN (Recovery Manager), and Object Storage. Here, Oracle Database Cloud Backup Service enables connection and communication with Oracle Cloud Infrastructure (OCI) while RMAN executes backups of your Oracle Cloud Database to OCI Object Storage. Note: there are many different ways to backup an Oracle Cloud Database, this is meant to represent one option. Note: given the diversity of customer environments and the ever-changing landscape of Oracle Cloud Infrastructure, please take the commands and their explanations listed below with a grain of salt. Outline: Pre-Requisites for Using Oracle Database Cloud Backup Service Full List of Commands for installing Oracle Database Cloud Backup Service Pre-Requisites for Installing Oracle Cloud Backup Database Service Installing RMAN Configure RMAN and Backup Database Database Table Access through SQL Plus Conclusion Pre-Requisites for Using Oracle Database Cloud Backup Service Before we get started, here is a link to all the pre-requisites needed to use the Oracle Cloud Backup Service. I will try to provide as much context to each pre-requisite and provide helpful links and examples. Check and make sure you are running the right database version and operating system. In this module I am using Enterprise Extreme Performance Edition version 19c. Setup Object Storage in OCI (Oracle Cloud Infrastructure). I recommend simply using the console, accessing object storage, and creating a bucket. In the virtual machine which hosts the database, generate keys to access OCI. Here is, in essence, how it will look. (The scripts below assume you are already in the VM instance which hosts the database.) This is how you will upload the key to OCI such that your virtual machine can communicate/connect with OCI. Check that you have a JDK 1.7 or later. You can check which version you have by typing “java -version” in your linux terminal. You should get an output similar to the following: java version “1.8.0_191” Java(TM) SE Runtime Environment (build 1.8.0_191-b12) Java HotSpot(TM) 64-Bit Server VM (build 25.191-b12, mixed mode) Finally, you want to download the latest version of the Oracle Cloud Backup service. This is the link to download the backup service. This should download a zip file called opc_installer. When unzipped, you should two folders, opc_installer and oci_installer. These are the two ways to install the Cloud Backup Service. In this tutorial, I will be using the oci_installer for OCI (not OCI classic). Note: If you have downloaded the Oracle Cloud Backup Service on a different machine than the one which hosts your database, you can use this command to copy your key from your local machine to your database host instance: #generic command cp -i <file/path/to/your/private_key> oci_install.jar opc@<vm_db_ip>:~”. cp -i /Users/abibi/.ssh/id_rsa oci_install.jar #examplecp -i /Users/abibi/.ssh/id_rsa oci_install.jar [email protected] :~ Note: To SSH to the virtual machine which hosts your database: Full List of Commands for installing Oracle Database Cloud Backup Service I am doing this a bit backwards and providing a list of commands for installing the oci_install.jar file before detailing the pre-requisites for the command. I am doing this because I wanted to provide a nice flow of commands. If you like more detail about the commands or are running into issues, simply reference the pre-reqs listed in the next section. Note: If you have executed some the commands listed above, no need to repeat them. #copy the newly downloaded oci_install.jar file to your database instance, assumes that the oci_install file in your current directory scp -i <private_key> oci_install.jar opc@<db_ip>:~ #SSH into the instance ssh -i <private_key> opc@<db_ip> #maybe log into your Oracle user--see note below #sudo su - oracle #create directories for installing jar file mkdir ~/lib mkdir ~/wallet #directory for oci credentials mkdir .oci #generating key for OCI openssl genrsa -out ~/.oci/oci_api_key.pem 2048 openssl rsa -pubout -in ~/.oci/oci_api_key.pem -out ~/.oci/oci_api_key_public.pem #change directory to oci folder cd .oci #note: to see hidden files, enter "ls -a" #output the key, copy and paste into user ssh key cat oci_api_key_public.pem #cd into folder containing oci_install.jar file, should be in opc folder #I assume the opc directory is where the jar file is located cd opc #generic command to install backup service java -jar oci_install.jar -host <object storage endpoint> -pvtKeyFile ~/.oci/oci_api_key.pem -pubFingerprint <fingerprint> -tOCID <tOCID> -cOCID <cOCID> -uOCID <uOCID> -walletDir ~/wallet -libDir ~/lib -bucket <bucketname> N ote: depending on the version of the database you are installing, you may need to copy files from one directory to another within the database instance. To do this, I recommend accessing the root user, copying files, and changing permissions for a file: #becoming root user sudo su #example of copying wallet credentials from opc to oracle user cp /home/opc/wallet/cwallet.sso /u01/app/oracle #changing permission access for a particular file such that other users can access the file chmod 775 /home/opc/wallet/cwallet.sso Note: another option is to log in as the instance’s Oracle user and run the commands above. To do this you can enter the following command after you have SSH’d into the instance: sudo su - oracle Pre-Requisites for Installing Oracle Cloud Backup Database Service To execute the jar file that will install the Oracle Cloud Backup Database Service, we need to gather some information from our Oracle Cloud Tenancy: Host: our object storage endpoint indicating the region where we created a bucket. Here is a list of valid value. pvtKeyFile: the location to the oci_api_key which we generated earlier in our database virtual machine. pubFingerprint: the fingerprint corresponding to the oci_api_key. tOCID: our tenancy OCID cOCID: the compartment OCID which holds object storage and our database instance. uOCID: our user’s OCID. Note: OCID is a unique value which identifies specific components of OCI like user, compartments, tenancy, and services. Learn more about OCIDs, here. walletDir: location for newly created wallet. Note: simply type the following if you want to create a folder in your current working directory: mkdir ~/wallet libDir: location for newly created library. Note: simply type the following if you want to create a folder in your current working directory. mkdir ~/lib Here is the GENERIC command that installs the Oracle Cloud Backup Database Service: Here is an EXAMPLE command: Note: I’ve spaced out the commands so that it is easier to understand, but when executing these commands in linux, they should all be in one line separated by a space. Note: if you are getting errors, here is some documentation that helps diagnose some common issues. We can validate successfully installing the jar file by checking if wallet and lib folders were created and if we see a “config” file which contains the OPC_HOST, OPC_WALLET, OPC_CONTAINER, OPC_COMPARTMENT, and OPC_AUTH_SCHEME values. Note: To open and read linux files, I recommend installing nano by typing the following (assuming you are in a directory with access to the config file): yum install nano nano config Installing RMAN Now that we have successfully installed Oracle Database Cloud Backup Service and established a connection to OCI, let’s setup RMAN (Oracle Recovery Manager) to manage our database backup to object storage. Pre-requisite: Oracle DB Password, the password entered when provisioning the Oracle Cloud Database instance. RMAN binaries location for installation #to find the rman binaries find / -iname rman Note: if there is a permission error, please enter the command to become a root user #example output should look something like this: /opt/oracle/dcs/log/ary/rman /tmp/dcsserver/rman /u01/app/19.0.0.0/grid/bin/rman /u01/app/oracle/product/19.0.0.0/dbhome_1/bin/rman Add RMAN binary location to current path #generic example of path export PATH=/u01/app/oracle/product/<insert DB version number>/dbhome_1/bin Set environment variables, ORACLE_HOME and ORACLE_SID #not really sure how important this, but points to database path export ORACLE_HOME=/u01/app/oracle/product/19.0.0.0/dbhome_1 #a unique identifier for your database, can find this in the console where you database is provisioned export ORACLE_SID=DB1111 #outputs all environment variables to confirm env #outputs config info for the database srvctl config database -d <database unique identifier> Configure RMAN and Backup Database Now we are ready to configure RMAN for backing up the Oracle Cloud Database to object storage. Simply enter this command to set/authorize RMAN connection to the database: #generic, TARGET is the command, SYS is the user, oracle is the password, and trgt2 is the database unique identifier rman TARGET SYS/oracle@trgt2 #example rman TARGET SYS/mypassword@DB111_asc3fp By this point, you should see a lingering “RMAN” at the bottom of the terminal and a message above stating that you have successfully connected to the database. Note: Here is some additional documentation and another source that is helpful for logging into the database using RMAN. Next, we need to configure some RMAN parameters before backing up the database: CONFIGURE CHANNEL DEVICE TYPE 'SBT_TAPE' PARMS 'SBT_LIBRARY=/path/to/libopc.so, SBT_PARMS=(OPC_PFILE=/path/to/config)'; Some additional commands: CONFIGURE CONTROLFILE AUTOBACKUP ON; CONFIGURE DEFAULT DEVICE TYPE TO SBT_TAPE; CONFIGURE BACKUP OPTIMIZATION ON; CONFIGURE CONTROLFILE AUTOBACKUP FORMAT FOR DEVICE TYPE SBT_TAPE TO '%F'; CONFIGURE ENCRYPTION FOR DATABASE ON; SET ENCRYPTION IDENTIFIED BY "password" ONLY; Note: details about the commands listed above and other options can be found here. Finally: BACKUP DATABASE; At this point, the command should result in the database being backed up into the object storage defined earlier. To confirm the backup is successful simply check object storage for database content and metadata files along with other related objects. Database Table Access through SQL Plus As an aside, to connect to the database tables, here is a link to some documentation. More information about connecting to a database. Below is a command that accesses the database tables through SQL Plus. #generic script to access database tables as system user sqlplus system/@(DESCRIPTION=(CONNECT_TIMEOUT=5)(TRANSPORT_CONNECT_TIMEOUT=3)(RETRY_COUNT=3)(ADDRESS_LIST=(LOAD_BALANCE=on)(ADDRESS=(PROTOCOL=TCP)(HOST=10.0.0.3)(PORT=1521)))(CONNECT_DATA=(SERVICE_NAME=<unique service name defined in database console under database connection>))) #example script to access database tables as system user sqlplus system/@meee.subnet.vcn.oraclevcn.com:1521/DB1111_asb3bs.subnet.vcn.oraclevcn.com Conclusion There are other ways of backing up an Oracle Cloud Database, why choose this option? I believe this provides find-grained control and the ability to set a cron job for scheduling the backup. With object storage involved, the database can be backed up to another region where the database is not running to provide high availability during a disaster. Nevertheless, there are automatic backups available in the console, the Oracle OCI Python SDK, and a number of other options to backup your database. I recommend considering the use case, RPO, RTO, and other factors before choosing this backup solution as it is tedious and time consuming to implement.
https://medium.com/oracledevs/disaster-recovery-backing-up-your-oracle-database-with-oracle-database-cloud-backup-service-rman-e28b86876ad2
['Ary Sharifian']
2020-08-10 05:43:47.156000+00:00
['Oracle Database', 'Disaster Recovery', 'Data Engineering', 'Cloud Computing', 'Iaas']
Title Disaster Recovery Backing Oracle Database Oracle Database Cloud Backup Service RMAN Object StorageContent Disaster Recovery Backing Oracle Database Oracle Database Cloud Backup Service RMAN Object Storage back Oracle Cloud Database Photo Kevin Ku Unsplash prepare disaster server crash technician unplugs machine meteor hit datacenter business recover crucial data tutorial demonstrate backup Oracle Cloud Database Oracle Database Cloud Backup Service RMAN Recovery Manager Object Storage Oracle Database Cloud Backup Service enables connection communication Oracle Cloud Infrastructure OCI RMAN executes backup Oracle Cloud Database OCI Object Storage Note many different way backup Oracle Cloud Database meant represent one option Note given diversity customer environment everchanging landscape Oracle Cloud Infrastructure please take command explanation listed grain salt Outline PreRequisites Using Oracle Database Cloud Backup Service Full List Commands installing Oracle Database Cloud Backup Service PreRequisites Installing Oracle Cloud Backup Database Service Installing RMAN Configure RMAN Backup Database Database Table Access SQL Plus Conclusion PreRequisites Using Oracle Database Cloud Backup Service get started link prerequisite needed use Oracle Cloud Backup Service try provide much context prerequisite provide helpful link example Check make sure running right database version operating system module using Enterprise Extreme Performance Edition version 19c Setup Object Storage OCI Oracle Cloud Infrastructure recommend simply using console accessing object storage creating bucket virtual machine host database generate key access OCI essence look script assume already VM instance host database upload key OCI virtual machine communicateconnect OCI Check JDK 17 later check version typing “java version” linux terminal get output similar following java version “180191” JavaTM SE Runtime Environment build 180191b12 Java HotSpotTM 64Bit Server VM build 25191b12 mixed mode Finally want download latest version Oracle Cloud Backup service link download backup service download zip file called opcinstaller unzipped two folder opcinstaller ociinstaller two way install Cloud Backup Service tutorial using ociinstaller OCI OCI classic Note downloaded Oracle Cloud Backup Service different machine one host database use command copy key local machine database host instance generic command cp filepathtoyourprivatekey ociinstalljar opcvmdbip” cp Usersabibisshidrsa ociinstalljar examplecp Usersabibisshidrsa ociinstalljar opc1301472683 Note SSH virtual machine host database Full List Commands installing Oracle Database Cloud Backup Service bit backwards providing list command installing ociinstalljar file detailing prerequisite command wanted provide nice flow command like detail command running issue simply reference prereqs listed next section Note executed command listed need repeat copy newly downloaded ociinstalljar file database instance assumes ociinstall file current directory scp privatekey ociinstalljar opcdbip SSH instance ssh privatekey opcdbip maybe log Oracle usersee note sudo su oracle create directory installing jar file mkdir lib mkdir wallet directory oci credential mkdir oci generating key OCI openssl genrsa ociociapikeypem 2048 openssl rsa pubout ociociapikeypem ociociapikeypublicpem change directory oci folder cd oci note see hidden file enter l output key copy paste user ssh key cat ociapikeypublicpem cd folder containing ociinstalljar file opc folder assume opc directory jar file located cd opc generic command install backup service java jar ociinstalljar host object storage endpoint pvtKeyFile ociociapikeypem pubFingerprint fingerprint tOCID tOCID cOCID cOCID uOCID uOCID walletDir wallet libDir lib bucket bucketname N ote depending version database installing may need copy file one directory another within database instance recommend accessing root user copying file changing permission file becoming root user sudo su example copying wallet credential opc oracle user cp homeopcwalletcwalletsso u01apporacle changing permission access particular file user access file chmod 775 homeopcwalletcwalletsso Note another option log instance’s Oracle user run command enter following command SSH’d instance sudo su oracle PreRequisites Installing Oracle Cloud Backup Database Service execute jar file install Oracle Cloud Backup Database Service need gather information Oracle Cloud Tenancy Host object storage endpoint indicating region created bucket list valid value pvtKeyFile location ociapikey generated earlier database virtual machine pubFingerprint fingerprint corresponding ociapikey tOCID tenancy OCID cOCID compartment OCID hold object storage database instance uOCID user’s OCID Note OCID unique value identifies specific component OCI like user compartment tenancy service Learn OCIDs walletDir location newly created wallet Note simply type following want create folder current working directory mkdir wallet libDir location newly created library Note simply type following want create folder current working directory mkdir lib GENERIC command installs Oracle Cloud Backup Database Service EXAMPLE command Note I’ve spaced command easier understand executing command linux one line separated space Note getting error documentation help diagnose common issue validate successfully installing jar file checking wallet lib folder created see “config” file contains OPCHOST OPCWALLET OPCCONTAINER OPCCOMPARTMENT OPCAUTHSCHEME value Note open read linux file recommend installing nano typing following assuming directory access config file yum install nano nano config Installing RMAN successfully installed Oracle Database Cloud Backup Service established connection OCI let’s setup RMAN Oracle Recovery Manager manage database backup object storage Prerequisite Oracle DB Password password entered provisioning Oracle Cloud Database instance RMAN binary location installation find rman binary find iname rman Note permission error please enter command become root user example output look something like optoracledcslogaryrman tmpdcsserverrman u01app19000gridbinrman u01apporacleproduct19000dbhome1binrman Add RMAN binary location current path generic example path export PATHu01apporacleproductinsert DB version numberdbhome1bin Set environment variable ORACLEHOME ORACLESID really sure important point database path export ORACLEHOMEu01apporacleproduct19000dbhome1 unique identifier database find console database provisioned export ORACLESIDDB1111 output environment variable confirm env output config info database srvctl config database database unique identifier Configure RMAN Backup Database ready configure RMAN backing Oracle Cloud Database object storage Simply enter command setauthorize RMAN connection database generic TARGET command SYS user oracle password trgt2 database unique identifier rman TARGET SYSoracletrgt2 example rman TARGET SYSmypasswordDB111asc3fp point see lingering “RMAN” bottom terminal message stating successfully connected database Note additional documentation another source helpful logging database using RMAN Next need configure RMAN parameter backing database CONFIGURE CHANNEL DEVICE TYPE SBTTAPE PARMS SBTLIBRARYpathtolibopcso SBTPARMSOPCPFILEpathtoconfig additional command CONFIGURE CONTROLFILE AUTOBACKUP CONFIGURE DEFAULT DEVICE TYPE SBTTAPE CONFIGURE BACKUP OPTIMIZATION CONFIGURE CONTROLFILE AUTOBACKUP FORMAT DEVICE TYPE SBTTAPE F CONFIGURE ENCRYPTION DATABASE SET ENCRYPTION IDENTIFIED password Note detail command listed option found Finally BACKUP DATABASE point command result database backed object storage defined earlier confirm backup successful simply check object storage database content metadata file along related object Database Table Access SQL Plus aside connect database table link documentation information connecting database command access database table SQL Plus generic script access database table system user sqlplus systemDESCRIPTIONCONNECTTIMEOUT5TRANSPORTCONNECTTIMEOUT3RETRYCOUNT3ADDRESSLISTLOADBALANCEonADDRESSPROTOCOLTCPHOST10003PORT1521CONNECTDATASERVICENAMEunique service name defined database console database connection example script access database table system user sqlplus systemmeeesubnetvcnoraclevcncom1521DB1111asb3bssubnetvcnoraclevcncom Conclusion way backing Oracle Cloud Database choose option believe provides findgrained control ability set cron job scheduling backup object storage involved database backed another region database running provide high availability disaster Nevertheless automatic backup available console Oracle OCI Python SDK number option backup database recommend considering use case RPO RTO factor choosing backup solution tedious time consuming implementTags Oracle Database Disaster Recovery Data Engineering Cloud Computing Iaas
2,889
I Thought I Was Some Bigshot Writer, Then I Submitted to Real Publications
WRITING I Thought I Was Some Bigshot Writer, Then I Submitted to Real Publications Like ‘America’s Got Talent,’ but awkwarder Photo: Francisco Osorio on Flickr / CC-2.0 “Sorry, sir, your card is declined.” A declined credit card only happened a few times in my life, and my heart sinks every time. It feels like I did something wrong, even though it’s always been a machine error. Did I overspend? Did someone hack my bank account? Am I overdrawn? The questions spin around my mind — all from a declined card. Now, I’m getting used to that feeling. I used to think I was special. I used to believe I could write. Then I started submitting to publications, and boy is it a wake-up. When I wrote my first articles, I was like one of those singers on America’s Got Talent. I wanted to get them published. Give me the microphone already! In my imagination, I could already hear the audience screaming in adoration. Then I sang and — oh no — It’s not that the audience started laughing. It was more of an awkward, silent grimace. You know those people who annoy you because they clearly think they’re somebody? They think they’ve got it, even though it’s obvious they don’t. I’m sorry to say it, but I was that guy. I believed I wrote incredible articles that no-one would decline. It’s easy to believe that when you don’t write anything. Life’s so much easier when you avoid stepping out, avoid creating, keep it all inside, where it’s pristine and perfect. You can admire that beautiful blank canvas, and nobody will ever judge. I stopped being pristine. I started submitting. The beautiful articles that I spent so many hours crafting. “Thank you for your submission; we’re going to pass on this article.” Simon Cowell, how could you? If you want a wake-up call, start submitting to publications. It’s a ride like no other. And nope, I’m not ready to stop submitting yet. No matter how many times I get declined, here’s to one more try.
https://medium.com/2-minute-madness/i-thought-i-was-some-bigshot-writer-then-i-submitted-to-real-publications-1b1aa66c3b3e
['David Majister']
2020-12-10 16:22:45.268000+00:00
['Writing', 'Creativity', 'Writing Tips', 'Rejection', 'Humor']
Title Thought Bigshot Writer Submitted Real PublicationsContent WRITING Thought Bigshot Writer Submitted Real Publications Like ‘America’s Got Talent’ awkwarder Photo Francisco Osorio Flickr CC20 “Sorry sir card declined” declined credit card happened time life heart sink every time feel like something wrong even though it’s always machine error overspend someone hack bank account overdrawn question spin around mind — declined card I’m getting used feeling used think special used believe could write started submitting publication boy wakeup wrote first article like one singer America’s Got Talent wanted get published Give microphone already imagination could already hear audience screaming adoration sang — oh — It’s audience started laughing awkward silent grimace know people annoy clearly think they’re somebody think they’ve got even though it’s obvious don’t I’m sorry say guy believed wrote incredible article noone would decline It’s easy believe don’t write anything Life’s much easier avoid stepping avoid creating keep inside it’s pristine perfect admire beautiful blank canvas nobody ever judge stopped pristine started submitting beautiful article spent many hour crafting “Thank submission we’re going pas article” Simon Cowell could want wakeup call start submitting publication It’s ride like nope I’m ready stop submitting yet matter many time get declined here’s one tryTags Writing Creativity Writing Tips Rejection Humor
2,890
Mico Yuk on the Importance of Community and the Paradigm Shift in Business Intelligence
Mico Yuk is the CEO and Co-Founder of BI Brainz. Her company uses their data storytelling methodology to help companies take their data and make sense of it in a fun, visual way. “I am heading into a conference with 25K tech women which is partly why I’m high octane right now!!!” That’s the message I received from the CEO and Co-Founder of BI Brainz, Mico Yuk. I had reached out to her to be a part of my ongoing series talking to thought leaders such as Ben Jones, Nick Caldwell and Matt David to get her insights on the future of BI. After years of being a sought-after consultant, Mico formed BI Brainz to “help companies take their data and make sense of it in a fun, visual way” using their data storytelling methodology and templates. In addition to running her own analytics consultancy, she’s an author, speaker and host of her own podcast, Analytics on Fire! Mico was about to enter the Grace Hopper Celebration (GHC) when she responded to my request for an interview. She was pumped up to attend THE largest gathering of women technologists in the United States. GHC is an event run by women for women in the tech space to network, mentor and find their tribe. Mico shares her highlights of GHC as well as the future of business intelligence. Mico hanging out with GHC President Brenda Wilkerson. Ms Wilkerson personally invited Mico to the GHC festivities! Mico describes her experience there as a career dream come true. Allen Hillery: Hi Mico! Thanks so much for chatting with me! I know we were exchanging messages from the Grace Hopper Celebration. Please tell us what the energy was like and what it means to you to be a part of such a monumental event? Mico Yuk: “I finally know what heaven looks like. Women, from all over the world, talking about technology, making hiring decisions and in leadership.” That is how I described #GHC19 to both the CEO of Anita.borg, Brenda Wilkerson, who inspires me and personally invited me to #GHC19, and our CMO of BI Brainz, Soo Tang Yuk on day one. I literally stood up in the middle of the exhibition center watching companies I only dreamed to worked for 5–10 years ago, with hundreds of women lined up, résumé in hand waiting for an interview. I pinched myself and realized it was not a dream. I stood in awe, as I went from booth to booth being celebrated for being a woman, greeted with girlie colors like pink, pastel green and purples. Every sticker, wall, and pen had an empowering message for women. My heart is racing again just thinking about it! It was A-M-A-Z-I-N-G!! AH: What particular moment, event or speaker at GHC has most inspired you ? MY:There were so many sessions but if I had to pick one event, it would have to be the closing ceremony. I felt like I was at a rock concert, but we, the women in tech, were on stage — crazy right? AH: Tell us about it. MY: The closing ceremony on the last day was a collection of final announcements such as the Abie Award winner, scholarships recipients and winners of the #pitcher event. At the #pitcher segment, I was so excited to see Backstage Capital Founder, Arland Hamilton on stage, stating that she hit her goal of investing in 100 under represented companies two years early! Mico Yuk (left) with Stephanie Lampkin, CEO of Blendoor, a recruiting tool that removes unconscious bias from hiring by leaving only the applicant credentials visible to employers. Even more amazing, was running into my engineering classmate Sanna Gaspard after 15 years. She won first place in the #pitcher contest, going home with $40,000 to accelerate her biotech startup Rubitection, an early detection tool. I was delighted to run into old friends like Stephanie Lampkin, Founder of Blendoor, a recruiting tool that removes unconscious bias from hiring by hiding everything but applicant credentials. Her Tedtalk is prolific. It was nuts! AH: That sounds like an awesome reunion! Can you share more about how that sense of community has been helpful in your career overall? MY: Community is SO important! It’s honestly how we built BI Brainz from the ground up. Being a woman in tech can be very mentally and emotionally taxing at times. People make assumptions because you’re a woman. You have to work harder because you’re a woman. My outlet has always been and will continue to be the community and knowing that what I do makes a difference in people’s lives. I have also met so many amazing females who are on the same path. We support each other and pay it forward to the next generation of intelligent ladies. I’d tell anyone getting into tech as a woman… find your community and hold unto it, tightly. “Knowing someone else has been discriminated against, overlooked, and not even invited to the table is sometimes what you need to push forward and realize it’s not just you!” -Mico Yuk on the importance of community AH: BI and Data Viz are both male dominated fields. What do you think is missing when these fields don’t accurately represent society at large? Mico discussed how women in tech can be very mentally and emotionally taxing at times but she credits her community of amazing females for helping her push forward and continuing to break boundaries! MY: The first thing that comes to mind is a keynote I heard at an MIT event I spoke at by Peter Schwartz, author of The Art of the Long View where he described what led IBM to decide not to invest in then unknown startup Microsoft, as they projected that PCs were for girls and the fad would die by the 1980’s. He concluded that companies like IBM who made such ‘now unthinkable’ decisions had one thing in common. A lack of diversity in ideas, a lack of diversity in thought and a lack of diversity in the room (in gender and race). Business intelligence has been like this for a long time. The last 20 years has been focused on the dark hole aka the data warehouse. Thank God we are now focused on getting insights and wisdom out of data. The creative nature of data visualization also attracts more females to the field, so we will continue to see more diversity in the coming years. “Business intelligence has been like this for a long time. The last 20 years has been focused on the dark hole aka the data warehouse. Thank God we are now focused on getting insights and wisdom out of data.” — Mico Yuk on the historical lack of diversity of BI AH: What made you want to get started in data viz and how did you end up where you are now? Growing up in the Caribbean, I’ve always loved art. I was the president of our Art Honor Society in high school, which was no. 1 throughout the Caribbean. I also had a secret hobby at home, which was playing on my over-sized HP desktop I begged my parents to buy in the ninth grade. Fast-forward to age 15 — I graduated from high school and went to college to study computer engineering (dropping out twice before graduating). AH: Did you see computer engineering as your pathway to data visualization? MY: Data viz kind of found me. I spent six months programming in mainframe SaaS as a data scientist, and then a year later I saw a job on Craigslist for a data viz expert, who would could help Ryder Logistics role out their Lean Six Sigma program to all their customers. I applied (running away from writing C++ code at AT&T all day, ugh), got the offer two days later and I took it. That job changed my life. My obsession with user design, user experience and user adoption, helped to make Ryder’s Lean Six Sigma visual program successful, then taking me to New York to work with Pfizer, and then onto work with other large enterprises such as AllState, Bank of America, Shell, and many more. Now I run my own analytics consulting firm, BI Brainz, which is now co-owned by a company called EPI-USE, whose core competency is developing HR solutions. With access to 2,200 consultants globally in 67 countries there is no limit to our future! It’s not easy, but I love what we do. AH: How much has your love for art impacted your career in data viz? Do you feel someone with a liberal arts background can contribute to data visualization or even business intelligence? MY: I LOVE art. So when I realized that I could combine my programming skills with my passion for user design and user experience, creating data visualizations was a no-brainer for me. I was honestly dreading doing hard core programming or even graphic design! I think anyone who wants to learn (regardless of degree), enjoys solving complex problems and is willing to put on a critical thinking hat can do BI. It’s a field that requires passion, customer service, and THEN technical know how. “I think anyone who wants to learn (regardless of degree), enjoys solving complex problems and is willing to put on a critical thinking hat can do BI. It’s a field that requires passion, customer service, and THEN technical know how.” — Mico Yuk on the importance of liberal arts majors entering BI AH: In addition to a consultancy you also host a podcast, Analytics on Fire. What have you learned from that experience? How has it impacted you and your work? Do you have a favorite episode of all time? Let’s just say AoF was a $50,000 failure in 2016. I took a break from podcasting for two and a half years (never planning to return, I’m embarrassed to admit that) but after 500-plus “please bring it back” messages from around the globe, I finally caved in and brought back Analytics on Fire in May of 2019. To my surprise we were greeted with 10,000+ monthly downloads and continue to grow! In terms of lessons learned from hosting a podcast, there are so many hard lessons, but here a few key ones. 1) It’s a different audience. People who listen to podcasts don’t necessarily read blogs and vice versa. You must cater to both learning styles. 2) Be yourself. It’s challenging sometimes talking into a microphone, knowing that thousands of people are going to listen to it word for word. Very early on I decided to just be Mico. 3) Just go with it. I used to be a perfectionist, editing out any and everything that did not go as planned. Today I edit out nothing. Authenticity can be heard, not just seen. The great thing about hosting a podcast with the biggest data influencers, our largest customers and some of our most successful students is getting a free PhD with each interview. It’s HARD to pick a favorite podcast. Seriously … this may affect me getting future guests lol. But, If I had to pick one, it would have to be Episode 33, with Andrew Mackay. I met Andrew back in 2014, while he was working in Saudi Arabia. He had just registered for our online BI Dashboard methodology course, and wanted to differentiate himself in the analytics field in the Middle East. Fast forward to 2019, where he sold his company to PWC and now the Director or Digital Transformation! “It’s special to me, because I recall our discussion. I had no idea it would change his life. Those little things keep me motivated and going.” — Mico Yuk on hosting BI podcast ‘Analytics on Fire’ AH: I would like to go back to something you said earlier. You mentioned people who listen to podcasts don’t necessarily read blogs and vice versa. Can you elaborate on that for us in the content game? How do the learning styles differ? MY: OMG … wow. This was such a freaking learning curve for us. After spending years writing a blog , we made a HUGE assumption (ass — out — of — you — and — me) that our thousands of loyal blog readers would automatically listen to our new Analytics on Fire podcast. Boy were we wrong! We quickly learned from our audience that they listen to our podcasts during their commutes, at the gym and even in the shower (like me). When done, most do not go to the podcast page to get the show notes and downloads, they just move on to the next podcast! So we are super careful how we use the limited notes we can post with each of our podcasts in iTunes, Spotify and other platforms, of course including a link to the full podcast page, but also including the podcast highlights, podcast artwork, and any special offers directly in the notes. Don’t get me wrong, there is some overlap, but we opened up to an entirely new audience which is amazing! AH: What accomplishment are you most proud of this year? MY: Disclaimer: I’m not good at talking about myself! I’m never really proud, just grateful. If I had to point out one thing, I never thought I would keynote events at Google, Facebook, and MIT to name a few. I’m now eyeballing a Ted Talk! I feel sooo blessed to have a platform where I can teach and inspire so many. It’s a responsibility I take very seriously. I look at what I do as more than a business, it’s a cause and one that changes people’s lives. I feel humbled and blessed that God chose me. AH: What has you excited as we go into 2020? There are rumors that you will be chatting with Alberto Cairo very soon! MY: Many things! This year we re-launched our Analytics on Fire podcast, kicked off our first three-day public BI Data Storytelling workshop (which sold out in six weeks), doubled our team size, expanded our technology focus to Microsoft Power BI and Power Apps. We also started our private BI Data Storytelling Mastery Facebook group which has over 1,500 enthusiast storytellers like me. In 2020 we not only plan to expand on all of the above, but I’m may be writing a book (hint hint) if I find the right publisher and finally relaunching our flagship online course, the BI Dashboard Formula. Needless to say, it’s going to be lit! AH: I believe there is a difference between data visualization & data storytelling. I would love to hear your opinion on this to share with our readers. MY: Of course there is — however, most of the big BI vendors (no name called) milk the definition to their benefit. It’s a constant uphill battle for us, as we see storytelling as the art of engaging your users with what you say, write and draw. We view data visualization as one of many means to engage users through drawing. It is just one small component of the data storytelling, but because it is the most visible it gets most of the attention. The reality is this — If you engage just the visual sense of your users, you won’t get long term adoption and buy in for your solution, whether it is a data visualization, dashboard or a reporting tool. You first have to engage your users on an emotion level. There was a study done a while back by neuroscientist named Antonio Damasio, who concluded that human beings make decisions with their emotions, and then justify those decisions with logic aka data, not the other way around. Data visualization is great, but without engaging and really understanding the user’s story it’s useless IMO. “Long story short, you need data storytelling to make data visualization useful and that is exactly what we teach at BI Brainz in our BI Data Storytelling Accelerator workshops.” — Mico Yuk on the importance of data storytelling AH: Between running Analytics on Fire and being co-Founder of BI Brainz, how would you define your leadership style? MY: Everyday I’m honored that people are willing to work for me and follow my dream. You have no idea. I get up before 5 a.m. everyday, and the first thing I do is thank God that by 9 a.m. my team is ready to go and our customers are excited to work with us. I depend on my amazing team at BI Brainz for EVERYTHING. People often see you on the top but they don’t realize it’s virtually impossible without insane support. I expect a lot from our team, and they over deliver. I want everyone to work to their strengths, but as a perfectionist I am always pushing them to do more, sometimes over the edge. Comfort zones bore me. My motto is, when you stop having fun, it’s time to change. AH: When reading your website a few messages pop out like timeliness, quick turnaround times and visual presentation. Would you describe this as the secret sauce of your business?
https://medium.com/nightingale/mico-yuk-on-the-importance-of-community-and-the-paradigm-shift-in-business-intelligence-a297515204f5
['Allen Hillery']
2020-01-08 12:01:01.413000+00:00
['Analytics', 'Startup', 'Business Intelligence', 'Data Visualization', 'Women In Tech']
Title Mico Yuk Importance Community Paradigm Shift Business IntelligenceContent Mico Yuk CEO CoFounder BI Brainz company us data storytelling methodology help company take data make sense fun visual way “I heading conference 25K tech woman partly I’m high octane right now” That’s message received CEO CoFounder BI Brainz Mico Yuk reached part ongoing series talking thought leader Ben Jones Nick Caldwell Matt David get insight future BI year soughtafter consultant Mico formed BI Brainz “help company take data make sense fun visual way” using data storytelling methodology template addition running analytics consultancy she’s author speaker host podcast Analytics Fire Mico enter Grace Hopper Celebration GHC responded request interview pumped attend largest gathering woman technologist United States GHC event run woman woman tech space network mentor find tribe Mico share highlight GHC well future business intelligence Mico hanging GHC President Brenda Wilkerson Ms Wilkerson personally invited Mico GHC festivity Mico describes experience career dream come true Allen Hillery Hi Mico Thanks much chatting know exchanging message Grace Hopper Celebration Please tell u energy like mean part monumental event Mico Yuk “I finally know heaven look like Women world talking technology making hiring decision leadership” described GHC19 CEO Anitaborg Brenda Wilkerson inspires personally invited GHC19 CMO BI Brainz Soo Tang Yuk day one literally stood middle exhibition center watching company dreamed worked 5–10 year ago hundred woman lined résumé hand waiting interview pinched realized dream stood awe went booth booth celebrated woman greeted girlie color like pink pastel green purple Every sticker wall pen empowering message woman heart racing thinking AMAZING AH particular moment event speaker GHC inspired MYThere many session pick one event would closing ceremony felt like rock concert woman tech stage — crazy right AH Tell u closing ceremony last day collection final announcement Abie Award winner scholarship recipient winner pitcher event pitcher segment excited see Backstage Capital Founder Arland Hamilton stage stating hit goal investing 100 represented company two year early Mico Yuk left Stephanie Lampkin CEO Blendoor recruiting tool remove unconscious bias hiring leaving applicant credential visible employer Even amazing running engineering classmate Sanna Gaspard 15 year first place pitcher contest going home 40000 accelerate biotech startup Rubitection early detection tool delighted run old friend like Stephanie Lampkin Founder Blendoor recruiting tool remove unconscious bias hiring hiding everything applicant credential Tedtalk prolific nut AH sound like awesome reunion share sense community helpful career overall Community important It’s honestly built BI Brainz ground woman tech mentally emotionally taxing time People make assumption you’re woman work harder you’re woman outlet always continue community knowing make difference people’s life also met many amazing female path support pay forward next generation intelligent lady I’d tell anyone getting tech woman… find community hold unto tightly “Knowing someone else discriminated overlooked even invited table sometimes need push forward realize it’s you” Mico Yuk importance community AH BI Data Viz male dominated field think missing field don’t accurately represent society large Mico discussed woman tech mentally emotionally taxing time credit community amazing female helping push forward continuing break boundary first thing come mind keynote heard MIT event spoke Peter Schwartz author Art Long View described led IBM decide invest unknown startup Microsoft projected PCs girl fad would die 1980’s concluded company like IBM made ‘now unthinkable’ decision one thing common lack diversity idea lack diversity thought lack diversity room gender race Business intelligence like long time last 20 year focused dark hole aka data warehouse Thank God focused getting insight wisdom data creative nature data visualization also attracts female field continue see diversity coming year “Business intelligence like long time last 20 year focused dark hole aka data warehouse Thank God focused getting insight wisdom data” — Mico Yuk historical lack diversity BI AH made want get started data viz end Growing Caribbean I’ve always loved art president Art Honor Society high school 1 throughout Caribbean also secret hobby home playing oversized HP desktop begged parent buy ninth grade Fastforward age 15 — graduated high school went college study computer engineering dropping twice graduating AH see computer engineering pathway data visualization Data viz kind found spent six month programming mainframe SaaS data scientist year later saw job Craigslist data viz expert would could help Ryder Logistics role Lean Six Sigma program customer applied running away writing C code ATT day ugh got offer two day later took job changed life obsession user design user experience user adoption helped make Ryder’s Lean Six Sigma visual program successful taking New York work Pfizer onto work large enterprise AllState Bank America Shell many run analytics consulting firm BI Brainz coowned company called EPIUSE whose core competency developing HR solution access 2200 consultant globally 67 country limit future It’s easy love AH much love art impacted career data viz feel someone liberal art background contribute data visualization even business intelligence LOVE art realized could combine programming skill passion user design user experience creating data visualization nobrainer honestly dreading hard core programming even graphic design think anyone want learn regardless degree enjoys solving complex problem willing put critical thinking hat BI It’s field requires passion customer service technical know “I think anyone want learn regardless degree enjoys solving complex problem willing put critical thinking hat BI It’s field requires passion customer service technical know how” — Mico Yuk importance liberal art major entering BI AH addition consultancy also host podcast Analytics Fire learned experience impacted work favorite episode time Let’s say AoF 50000 failure 2016 took break podcasting two half year never planning return I’m embarrassed admit 500plus “please bring back” message around globe finally caved brought back Analytics Fire May 2019 surprise greeted 10000 monthly downloads continue grow term lesson learned hosting podcast many hard lesson key one 1 It’s different audience People listen podcasts don’t necessarily read blog vice versa must cater learning style 2 It’s challenging sometimes talking microphone knowing thousand people going listen word word early decided Mico 3 go used perfectionist editing everything go planned Today edit nothing Authenticity heard seen great thing hosting podcast biggest data influencers largest customer successful student getting free PhD interview It’s HARD pick favorite podcast Seriously … may affect getting future guest lol pick one would Episode 33 Andrew Mackay met Andrew back 2014 working Saudi Arabia registered online BI Dashboard methodology course wanted differentiate analytics field Middle East Fast forward 2019 sold company PWC Director Digital Transformation “It’s special recall discussion idea would change life little thing keep motivated going” — Mico Yuk hosting BI podcast ‘Analytics Fire’ AH would like go back something said earlier mentioned people listen podcasts don’t necessarily read blog vice versa elaborate u content game learning style differ OMG … wow freaking learning curve u spending year writing blog made HUGE assumption as — — — — — thousand loyal blog reader would automatically listen new Analytics Fire podcast Boy wrong quickly learned audience listen podcasts commute gym even shower like done go podcast page get show note downloads move next podcast super careful use limited note post podcasts iTunes Spotify platform course including link full podcast page also including podcast highlight podcast artwork special offer directly note Don’t get wrong overlap opened entirely new audience amazing AH accomplishment proud year Disclaimer I’m good talking I’m never really proud grateful point one thing never thought would keynote event Google Facebook MIT name I’m eyeballing Ted Talk feel sooo blessed platform teach inspire many It’s responsibility take seriously look business it’s cause one change people’s life feel humbled blessed God chose AH excited go 2020 rumor chatting Alberto Cairo soon Many thing year relaunched Analytics Fire podcast kicked first threeday public BI Data Storytelling workshop sold six week doubled team size expanded technology focus Microsoft Power BI Power Apps also started private BI Data Storytelling Mastery Facebook group 1500 enthusiast storyteller like 2020 plan expand I’m may writing book hint hint find right publisher finally relaunching flagship online course BI Dashboard Formula Needless say it’s going lit AH believe difference data visualization data storytelling would love hear opinion share reader course — however big BI vendor name called milk definition benefit It’s constant uphill battle u see storytelling art engaging user say write draw view data visualization one many mean engage user drawing one small component data storytelling visible get attention reality — engage visual sense user won’t get long term adoption buy solution whether data visualization dashboard reporting tool first engage user emotion level study done back neuroscientist named Antonio Damasio concluded human being make decision emotion justify decision logic aka data way around Data visualization great without engaging really understanding user’s story it’s useless IMO “Long story short need data storytelling make data visualization useful exactly teach BI Brainz BI Data Storytelling Accelerator workshops” — Mico Yuk importance data storytelling AH running Analytics Fire coFounder BI Brainz would define leadership style Everyday I’m honored people willing work follow dream idea get 5 everyday first thing thank God 9 team ready go customer excited work u depend amazing team BI Brainz EVERYTHING People often see top don’t realize it’s virtually impossible without insane support expect lot team deliver want everyone work strength perfectionist always pushing sometimes edge Comfort zone bore motto stop fun it’s time change AH reading website message pop like timeliness quick turnaround time visual presentation Would describe secret sauce businessTags Analytics Startup Business Intelligence Data Visualization Women Tech
2,891
Fragranced Products Could Hurt Your Health
Fragranced Products Could Hurt Your Health Americans are cleaning more than ever — and all those scented products are worrying consumer-health researchers Even before the pandemic, Americans were among the world’s most enthusiastic users of scented home-cleaning products. Market research from the industry-tracking firm Statista shows that the United States ranks first in the world in spending on household cleaners; the U.S. spends more on these products than the next three countries on the list, combined. The emergence of SARS-CoV-2 has only intensified the country’s zeal for scented wipes, sprays, detergents, soaps, and sanitizers. According to a recent study in Air Quality, Atmosphere & Health, the pandemic has initiated a “sweeping and surging use” of such products both in the U.S. and abroad. While there’s certainly a heightened need for regular and thorough hand-washing, and probably also for frequent disinfection of door handles and other oft-touched surfaces, it’s not at all clear that Americans can scrub and spray the novel coronavirus into lavender-scented submission — especially if they’re doing so at home. In August, an expert comment appearing in The Lancet reviewed some of the best research to date on surface-contact transmission. It concluded that the risks of a person catching the virus by touching an infected surface are “exaggerated.” Likewise, the U.S. Centers for Disease Control and Prevention now says that while surface-contact transmission is probably possible, it “is not thought to be a common way that COVID-19 spreads.” (Most experts now agree that close-range exposure to an infected individual — especially indoors — is the primary mode of transmission.) Even if surface-contact transmission is a thing, hand-washing and masks would foil most of the virus’s opportunities to move from a surface into a person’s body. “A primary source of indoor air pollutants is fragranced consumer products, such as air fresheners and cleaning supplies.” It would be one thing if commercial cleaners or disinfectants came with no downsides. And this seems to be the operating assumption that governs a lot of people’s approach to their use. But experts say that many of the chemicals in these products — and, notably, the chemicals that lend these products pleasing scents, which contribute nothing to their germ-clearing effectiveness — are linked to health harms ranging from headaches and skin rashes to asthma, immune system dysfunction, and heart trouble. They may even contribute to some Covid-19-related risks. The hazards of fragrance chemicals Chemicals that give a product fragrance — whether that product is an all-purpose cleaner, a scented candle, an air freshener, or hair spray — have lately been worrying some consumer-health researchers. A 2020 review in Air Quality, Atmosphere & Health summarized some of the latest findings. “As background, most of our exposure to pollutants occurs indoors,” writes Anne Steinemann, PhD, author of that review and a professor at the University of Melbourne in Australia. “A primary source of indoor air pollutants is fragranced consumer products, such as air fresheners and cleaning supplies.” Steinemann is an expert in product emissions and environmental health, and has authored or co-authored dozens of studies on these topics. Her review catalogs a long list of health harms associated with fragrance chemicals, among which migraine headaches, breathing problems, and skin reactions are most common. While a product’s list of ingredients may include a single word like “fragrance” or “parfum,” these or similar words often refer to a proprietary blend of several or even dozens of chemicals. The chemicals used in this blend do not have to be publicly disclosed, and may lawfully contain any one (or more) of the thousands of chemicals that are now approved for use in consumer products. This list includes volatile organic compounds (VOCs) and also endocrine-disrupting chemicals, so named because they may interfere in some way with the activity of the body’s hormones. And that list of allowed fragrance chemicals is growing. “Even 10 years ago, the list included just one phthalate,” says Robin Dodson, PhD, an environmental exposure scientist at the nonprofit Silent Spring Institute in Massachusetts. Phthalates are a type of chemical that research has linked to elevated risks for breast cancer, reduced fertility, and asthma. “Now there are several phthalates on the list,” she says. Dodson sometimes gives talks on the risks of consumer chemicals. She says that even health-conscious, in-the-know consumers are often unaware of how the U.S. chemical industry is regulated — or, in many cases, not regulated. “Something people are always surprised to learn is that only a minority of the chemicals in our products are thoroughly tested for toxicity,” she says. “Companies are allowed to put chemicals into products that have not been fully evaluated for safety, and often these chemicals are only flagged as harmful after evaluation by independent scientists.” She highlights research findings that have linked phthalates and other fragrance chemicals to a heightened risk for asthma, suppressed immune function, and diabetes. All of these are on the CDC’s list of conditions associated with severe Covid-19 disease. “I don’t think it’s overboard to say that exposure to the chemicals could make you more susceptible to something like Covid-19,” she says. More chemical concerns Fragrance chemicals aren’t the only ones in consumer products that are associated with health problems. Far from it. “Unfortunately, with Covid, we’re seeing a resurgence in the use of antimicrobials and other disinfectants that wipe out the virus but can be toxic or endocrine-disrupting in humans,” says Heather Patisaul, PhD, an expert in environmental chemicals and health at North Carolina State University. Patisaul highlights a category of disinfectant chemicals called quaternary ammonium compounds (QACs or “quats”), which are found in products that were once mainly used in medical or commercial food-service settings but have since migrated into the home. According to a report from Mount Sinai and New York University, QACs now turn up in everything from disinfectant sprays and wipes to dish soaps, all-purpose cleaners, and baby products. Products labeled “antimicrobial” or “disinfectant” are most likely to contain QACs, which can be hard to avoid unless you memorize their names and look for them on the list of active ingredients. “We’re exposed to a whole soup of these on a daily basis, and it’s that soup that most concerns me.” “Although they are marketed as household disinfectants, they are actually certified by the EPA as pesticides, and they are overkill for cleaning at home,” Patisaul says. QAC’s are lung and skin irritants, “which is not great if you’re worried about Covid,” she says. They’re also “teratogenic,” meaning they have been shown to interfere with fetal development. They can also disrupt the actions of hormones in ways that may promote the development of cancer or immune dysfunction, though those specific harms are still theoretical. And that’s just one category of chemical among the hundreds found in household cleaning and personal care products. Patisaul is part of a community of researchers and public health advocates who for years have worked to raise awareness of the dangers of consumer chemicals — both to people and to the environment. The emergence of Covid-19 — and the persistent misconception that a “clean” person, place, or thing is one bathed in some kind of scented product — threaten to undo much of their good work. The Silent Spring Institute’s Dodson says that U.S. health authorities, unlike oversight bodies in some other countries, tend to apply an “innocent until proven guilty” standard to consumer chemicals. And especially when it comes to cancer, immune dysfunction, and other slow-to-emerge, multifactorial health conditions, establishing “proof” of harm is next to impossible. “We’re ubiquitously exposed to these chemicals — they’re everywhere — and so there’s really no way to compare people who’ve been exposed to those who have not been exposed to see what might happen 30 years later,” Dodson says. Even if you could do that type of experiment, it wouldn’t reveal how the combination of hundreds of these chemicals might interact with an individual’s unique biology in ways that could create disease or damage. “We’re exposed to a whole soup of these on a daily basis, and it’s that soup that most concerns me,” she adds. How to avoid the risks Ditching fragranced products is a good first step, Dodson says. Even if you’re unwilling to part with a favorite cologne or perfume — and yes, those products also contain potentially harmful chemicals — she points out that most American households contain a panoply of scented cosmetics, lotions, detergents, air fresheners, candles, and cleaning products. “None of us needs fragranced trash bags,” she says. “We can all skip those.” Unfortunately, avoiding fragrance chemicals may be easier said than done. While products labeled “fragrance free” are often good options, those labeled “unscented” may actually contain additional chemicals used to mask a product’s unpleasant odor, Dodson says. Searching out products labeled “green” or “organic” also isn’t much use; research has found that those products often emit some of the same harmful pollutants as regular products. On the other hand, simply buying and using fewer cosmetics and cleaning products is one good way to cut back exposure. And if ditching a product isn’t possible, the nonprofit Environmental Working Group provides helpful resources for finding safer options for cleaning and personal care. The Silent Spring Institute’s Detox Me app is also a useful tool. “None of us needs fragranced trash bags. We can all skip those.” When it comes to safely ridding your home, car, or other areas — not your hands or body — of SARS-CoV-2, simple and old-school cleaning solutions may be the safest options. “Hydrogen peroxide, citric acid, or octanoic acid are safe and effective,” says NCSU’s Patisaul. Each of these is on the Environmental Protection Agency’s list of products that can effectively inactivate SARS-CoV-2 on surfaces. They’re all inexpensive and easy to find. Just make sure you’re not mixing them with vinegar or other cleaners, which Patisaul says can create a toxic cocktail. (According to resources from the University of North Carolina, mixing one part over-the-counter hydrogen peroxide with one part water creates a solution that will inactive the coronavirus on surfaces.) To clean your hands and body, the CDC says that plain old soap and water is the best and safest way to go. If you can’t wash, hand sanitizers are a next-best option; fragrance-free, alcohol-based products that contain at least 60% alcohol are effective, per the CDC, and need not contain any other chemicals to effectively neutralize the virus. Looking beyond the pandemic, Dodson says that in order to meaningfully reduce the public’s exposure to harmful consumer chemicals, regulators will need to implement more robust safety standards. Today, even if a person is diligent about avoiding harmful chemicals, that person may still be exposed to harmful levels at work, at school, or elsewhere. “We really need better safeguards in place,” she says.
https://elemental.medium.com/fragranced-products-could-hurt-your-health-f746b7680f71
['Markham Heid']
2020-10-22 05:33:29.367000+00:00
['Health', 'Lifestyle', 'The Nuance', 'Cleaning', 'Science']
Title Fragranced Products Could Hurt HealthContent Fragranced Products Could Hurt Health Americans cleaning ever — scented product worrying consumerhealth researcher Even pandemic Americans among world’s enthusiastic user scented homecleaning product Market research industrytracking firm Statista show United States rank first world spending household cleaner US spends product next three country list combined emergence SARSCoV2 intensified country’s zeal scented wipe spray detergent soap sanitizers According recent study Air Quality Atmosphere Health pandemic initiated “sweeping surging use” product US abroad there’s certainly heightened need regular thorough handwashing probably also frequent disinfection door handle ofttouched surface it’s clear Americans scrub spray novel coronavirus lavenderscented submission — especially they’re home August expert comment appearing Lancet reviewed best research date surfacecontact transmission concluded risk person catching virus touching infected surface “exaggerated” Likewise US Centers Disease Control Prevention say surfacecontact transmission probably possible “is thought common way COVID19 spreads” expert agree closerange exposure infected individual — especially indoors — primary mode transmission Even surfacecontact transmission thing handwashing mask would foil virus’s opportunity move surface person’s body “A primary source indoor air pollutant fragranced consumer product air freshener cleaning supplies” would one thing commercial cleaner disinfectant came downside seems operating assumption governs lot people’s approach use expert say many chemical product — notably chemical lend product pleasing scent contribute nothing germclearing effectiveness — linked health harm ranging headache skin rash asthma immune system dysfunction heart trouble may even contribute Covid19related risk hazard fragrance chemical Chemicals give product fragrance — whether product allpurpose cleaner scented candle air freshener hair spray — lately worrying consumerhealth researcher 2020 review Air Quality Atmosphere Health summarized latest finding “As background exposure pollutant occurs indoors” writes Anne Steinemann PhD author review professor University Melbourne Australia “A primary source indoor air pollutant fragranced consumer product air freshener cleaning supplies” Steinemann expert product emission environmental health authored coauthored dozen study topic review catalog long list health harm associated fragrance chemical among migraine headache breathing problem skin reaction common product’s list ingredient may include single word like “fragrance” “parfum” similar word often refer proprietary blend several even dozen chemical chemical used blend publicly disclosed may lawfully contain one thousand chemical approved use consumer product list includes volatile organic compound VOCs also endocrinedisrupting chemical named may interfere way activity body’s hormone list allowed fragrance chemical growing “Even 10 year ago list included one phthalate” say Robin Dodson PhD environmental exposure scientist nonprofit Silent Spring Institute Massachusetts Phthalates type chemical research linked elevated risk breast cancer reduced fertility asthma “Now several phthalates list” say Dodson sometimes give talk risk consumer chemical say even healthconscious intheknow consumer often unaware US chemical industry regulated — many case regulated “Something people always surprised learn minority chemical product thoroughly tested toxicity” say “Companies allowed put chemical product fully evaluated safety often chemical flagged harmful evaluation independent scientists” highlight research finding linked phthalates fragrance chemical heightened risk asthma suppressed immune function diabetes CDC’s list condition associated severe Covid19 disease “I don’t think it’s overboard say exposure chemical could make susceptible something like Covid19” say chemical concern Fragrance chemical aren’t one consumer product associated health problem Far “Unfortunately Covid we’re seeing resurgence use antimicrobial disinfectant wipe virus toxic endocrinedisrupting humans” say Heather Patisaul PhD expert environmental chemical health North Carolina State University Patisaul highlight category disinfectant chemical called quaternary ammonium compound QACs “quats” found product mainly used medical commercial foodservice setting since migrated home According report Mount Sinai New York University QACs turn everything disinfectant spray wipe dish soap allpurpose cleaner baby product Products labeled “antimicrobial” “disinfectant” likely contain QACs hard avoid unless memorize name look list active ingredient “We’re exposed whole soup daily basis it’s soup concern me” “Although marketed household disinfectant actually certified EPA pesticide overkill cleaning home” Patisaul say QAC’s lung skin irritant “which great you’re worried Covid” say They’re also “teratogenic” meaning shown interfere fetal development also disrupt action hormone way may promote development cancer immune dysfunction though specific harm still theoretical that’s one category chemical among hundred found household cleaning personal care product Patisaul part community researcher public health advocate year worked raise awareness danger consumer chemical — people environment emergence Covid19 — persistent misconception “clean” person place thing one bathed kind scented product — threaten undo much good work Silent Spring Institute’s Dodson say US health authority unlike oversight body country tend apply “innocent proven guilty” standard consumer chemical especially come cancer immune dysfunction slowtoemerge multifactorial health condition establishing “proof” harm next impossible “We’re ubiquitously exposed chemical — they’re everywhere — there’s really way compare people who’ve exposed exposed see might happen 30 year later” Dodson say Even could type experiment wouldn’t reveal combination hundred chemical might interact individual’s unique biology way could create disease damage “We’re exposed whole soup daily basis it’s soup concern me” add avoid risk Ditching fragranced product good first step Dodson say Even you’re unwilling part favorite cologne perfume — yes product also contain potentially harmful chemical — point American household contain panoply scented cosmetic lotion detergent air freshener candle cleaning product “None u need fragranced trash bags” say “We skip those” Unfortunately avoiding fragrance chemical may easier said done product labeled “fragrance free” often good option labeled “unscented” may actually contain additional chemical used mask product’s unpleasant odor Dodson say Searching product labeled “green” “organic” also isn’t much use research found product often emit harmful pollutant regular product hand simply buying using fewer cosmetic cleaning product one good way cut back exposure ditching product isn’t possible nonprofit Environmental Working Group provides helpful resource finding safer option cleaning personal care Silent Spring Institute’s Detox app also useful tool “None u need fragranced trash bag skip those” come safely ridding home car area — hand body — SARSCoV2 simple oldschool cleaning solution may safest option “Hydrogen peroxide citric acid octanoic acid safe effective” say NCSU’s Patisaul Environmental Protection Agency’s list product effectively inactivate SARSCoV2 surface They’re inexpensive easy find make sure you’re mixing vinegar cleaner Patisaul say create toxic cocktail According resource University North Carolina mixing one part overthecounter hydrogen peroxide one part water creates solution inactive coronavirus surface clean hand body CDC say plain old soap water best safest way go can’t wash hand sanitizers nextbest option fragrancefree alcoholbased product contain least 60 alcohol effective per CDC need contain chemical effectively neutralize virus Looking beyond pandemic Dodson say order meaningfully reduce public’s exposure harmful consumer chemical regulator need implement robust safety standard Today even person diligent avoiding harmful chemical person may still exposed harmful level work school elsewhere “We really need better safeguard place” saysTags Health Lifestyle Nuance Cleaning Science
2,892
The Volunteers who Challenge the Virus: Controlled Human Infections
The Volunteers who Challenge the Virus: Controlled Human Infections Would you be a volunteer who challenges the virus? Photo by Obi Onyeador on Unsplash In a time where everybody tries to protect themselves from COVID-19 — by wearing masks, respecting social distancing, or avoiding shared surfaces — some are facing the virus head-on! Yes, thousands of people have expressed interest in participating in Controlled Human Infection (CHI) studies with SARS-CoV-2, the causative agent of COVID-19. CHI studies aim to speed up the development of a vaccine for COVID-19. According to 1daysooner.org, a website that encourages people to volunteer to participate in human challenge trials or to advocate on their behalf, almost 30000 people from 140 countries have already applied to deliberately expose themselves to SARS-CoV-2. This is surprising, given that COVID-19 is like the “perfect” pandemic, it killed almost 500000 people worldwide and no specific treatments are available. Why do these volunteers want to take on a life-threatening risk? There are multiple reasons: some have strong motivations to help others, some people are motivated by the money while other volunteers are curious of the experience. The perspective of one 41-year-old volunteer is very interesting, as the owner of a business that has him visiting warehouses and flying regularly, he figures he’ll inevitably get infected anyways, so he declared on CNN: “I feel if I did it under a controlled environment, and I had an adverse reaction, my chances are much better”. On one hand, Dr. Lipsitch, a Harvard epidemiologist, confirmed that “as a part of being in the trial they [partecipants] would be guaranteed excellent care if they needed it”. On the other hand, controlled human infection studies continue to generate controversy within the scientific community especially from an ethical point of view. It may seem impermissible to ask people to take on the risk of severe illness or death, even for an important collective gain. To better understand the scientific doubts on this matter let’s start by defining controlled human infection studies. In CHI studies, a small number of healthy participants are deliberately exposed to a known dose of a pathogen in a controlled setting, to study infection and gather preliminary efficacy data on experimental vaccines or treatments. CHI studies, by allowing preliminary efficacy testing in 10–100 participants, are cheaper than phase 2 and 3 clinical trials that often require sample sizes ranging from hundreds to hundreds of thousands of participants. Thus, they help to identify inferior vaccine candidates or treatments before initiating large safety and efficacy trials, allowing valuable resources to be focused on those candidates that have the greatest potential for success. CHI studies have emerged as powerful tools to select promising new vaccines or drugs on the increasingly complex and expensive path towards licensure. In this decade more than 120 controlled human infection studies have been published, primarily for influenza, rhinovirus, typhoid and malaria. A malaria CHI study provided critical information for the development of the malaria vaccine RTS,S. Malaria CHI studies were performed to first evaluate the efficacy of this vaccine and to then further refine the formulation and dosing regimen before initiating Phase 3 efficacy evaluations in Africa. A dengue CHI study was used to determine which formulation of a live-attenuated tetravalent dengue vaccine should be chosen to move forward in a Phase 3 efficacy trial in Brazil.
https://medium.com/beingwell/the-volunteers-who-challenge-the-virus-controlled-human-infections-321e5d2fb887
['Valentina Colapicchioni']
2020-06-25 11:10:30.016000+00:00
['Vaccines', 'Health', 'Research', 'Science', 'Clinical Trials']
Title Volunteers Challenge Virus Controlled Human InfectionsContent Volunteers Challenge Virus Controlled Human Infections Would volunteer challenge virus Photo Obi Onyeador Unsplash time everybody try protect COVID19 — wearing mask respecting social distancing avoiding shared surface — facing virus headon Yes thousand people expressed interest participating Controlled Human Infection CHI study SARSCoV2 causative agent COVID19 CHI study aim speed development vaccine COVID19 According 1daysoonerorg website encourages people volunteer participate human challenge trial advocate behalf almost 30000 people 140 country already applied deliberately expose SARSCoV2 surprising given COVID19 like “perfect” pandemic killed almost 500000 people worldwide specific treatment available volunteer want take lifethreatening risk multiple reason strong motivation help others people motivated money volunteer curious experience perspective one 41yearold volunteer interesting owner business visiting warehouse flying regularly figure he’ll inevitably get infected anyways declared CNN “I feel controlled environment adverse reaction chance much better” one hand Dr Lipsitch Harvard epidemiologist confirmed “as part trial partecipants would guaranteed excellent care needed it” hand controlled human infection study continue generate controversy within scientific community especially ethical point view may seem impermissible ask people take risk severe illness death even important collective gain better understand scientific doubt matter let’s start defining controlled human infection study CHI study small number healthy participant deliberately exposed known dose pathogen controlled setting study infection gather preliminary efficacy data experimental vaccine treatment CHI study allowing preliminary efficacy testing 10–100 participant cheaper phase 2 3 clinical trial often require sample size ranging hundred hundred thousand participant Thus help identify inferior vaccine candidate treatment initiating large safety efficacy trial allowing valuable resource focused candidate greatest potential success CHI study emerged powerful tool select promising new vaccine drug increasingly complex expensive path towards licensure decade 120 controlled human infection study published primarily influenza rhinovirus typhoid malaria malaria CHI study provided critical information development malaria vaccine RTSS Malaria CHI study performed first evaluate efficacy vaccine refine formulation dosing regimen initiating Phase 3 efficacy evaluation Africa dengue CHI study used determine formulation liveattenuated tetravalent dengue vaccine chosen move forward Phase 3 efficacy trial BrazilTags Vaccines Health Research Science Clinical Trials
2,893
Deploy a Production Django App With Elastic Beanstalk (Part 2)
Setting up S3 — Static and Media Storage Up to this point, we have a working Django app deployed on Elastic Beanstalk Amazon Linux 2. Congratulations! However, we still need to set up S3 so the site shows styles and we can upload images — which would be nice, considering it’s an image of the day app! Create a group and user First things first: We need to create an IAM user with programmatic access so our application can access the S3 bucket we’re creating next. Best practice here is to create a group with the appropriate policies attached and add a new user to the group. Note: I highly recommend creating a new user for the application’s S3 access. Using an admin user opens all kinds of security risks. In the AWS services search bar, look for IAM. Navigate to IAM → Groups → Create New Group. Set the group name to something like “S3FullAccess” and go to the next step. Here, search for “S3” and select AmazonS3FullAccess . Click on the next step and create the group. Now, we’ll navigate to “Users” and add a new user. Name the user whatever you want, I’ll go with “iotd-s3-access” and select “Programmatic Access.” Click to permissions and add this user to the group we created. Click through and create the user. After the user is created, you will get a success notification and be able to save the Access key ID and Secret access key. Important: if you don’t save these credentials here, you will not be able to see them again. You will have to delete this user and create a new one to get credentials again. Download the .csv file with the credentials in it and head back over to the iotd project settings file. Add two new settings at the end of iotd/settings.py — we’re not going to add the keys, but instead references to them: if 'AWS_ACCESS_KEY_ID' in os.environ: AWS_ACCESS_KEY_ID = os.environ['AWS_ACCESS_KEY_ID'] AWS_SECRET_ACCESS_KEY = os.environ['AWS_SECRET_ACCESS_KEY'] Committing the actual keys in your settings file is a dangerous idea. It poses a security vulnerability if anyone were to gain access to your project’s code (GitHub or otherwise). Instead of keeping them in the settings file, we’re going to add them as environment variables and pull them into the settings file securely. Docs here. Create a bucket Before we get into environment variables, navigate to S3, and create a new bucket. Make sure to turn off the block public access. We’ll need the images stored here to be public to show them in the API and have access to them later on. Name your bucket whatever you want. I usually recommend enabling versioning, but this is optional. Click “Create Bucket” and we’re all set.
https://medium.com/better-programming/production-django-elastic-beanstalk-part2-4501caf7d8fb
['Zack Petersen']
2020-12-15 16:49:55.854000+00:00
['Python', 'Database', 'AWS', 'Django', 'Programming']
Title Deploy Production Django App Elastic Beanstalk Part 2Content Setting S3 — Static Media Storage point working Django app deployed Elastic Beanstalk Amazon Linux 2 Congratulations However still need set S3 site show style upload image — would nice considering it’s image day app Create group user First thing first need create IAM user programmatic access application access S3 bucket we’re creating next Best practice create group appropriate policy attached add new user group Note highly recommend creating new user application’s S3 access Using admin user open kind security risk AWS service search bar look IAM Navigate IAM → Groups → Create New Group Set group name something like “S3FullAccess” go next step search “S3” select AmazonS3FullAccess Click next step create group we’ll navigate “Users” add new user Name user whatever want I’ll go “iotds3access” select “Programmatic Access” Click permission add user group created Click create user user created get success notification able save Access key ID Secret access key Important don’t save credential able see delete user create new one get credential Download csv file credential head back iotd project setting file Add two new setting end iotdsettingspy — we’re going add key instead reference AWSACCESSKEYID osenviron AWSACCESSKEYID osenvironAWSACCESSKEYID AWSSECRETACCESSKEY osenvironAWSSECRETACCESSKEY Committing actual key setting file dangerous idea pose security vulnerability anyone gain access project’s code GitHub otherwise Instead keeping setting file we’re going add environment variable pull setting file securely Docs Create bucket get environment variable navigate S3 create new bucket Make sure turn block public access We’ll need image stored public show API access later Name bucket whatever want usually recommend enabling versioning optional Click “Create Bucket” we’re setTags Python Database AWS Django Programming
2,894
Tools for Machine Learning and Artificial Intelligence in Analytics
Photo by Mitchell Luo on Unsplash By tools for analytics, the reference are to apps that allow for environments to create solutions, language, libraries, and even graphical user interface to manipulate data for insights from information. There are many tools for data analytics. What is available? Tools Anaconda provides environment for Python and R including machine learning for mac/linux/windows. After downloading the app and installing, the environment can be customized to include variety of data science tools with libraries. Anaconda is used desktop but also exists as a cloud version. JetBrains is an organization with a lot of apps for specific goals. There is PyCharm for Python, DataGrip for Databases, RubyMine for Ruby, and more. For analytics, the tool set and ability to integrate across their tools is unique. The positive is creating full apps that have artificial intelligent components or subcomponents and code for other pieces of the app in languages like PHP that can work together in a JetBrains solution. Google has a few analytics tools, most notably, Looker and Google Cloud Platform. Microsoft Access, Azure, Excel, and Power BI all provide analytics and data service. IBM has SPSS and Watson tools there are cloud and local versions of each platform. SPSS provides analytics and smart menus in a graphical user interface. Watson is famous for its performance on “Jeopardy” January 14, 2011 where it was tasked with competing against humans in trivia. Now, it is a service that can be tasked with data challenges. Salesforce has Tableau which is a business oriented analytics service. Snowflake is a data warehouse and analytics provider providing data services. Photo by Patrick Fore on Unsplash I have experience in cloud and local tools. Cloud is trending, easy, and has great benefits. Artificial Intelligence is highly integrated into tool platforms with a range of how much control the developer or user has in method and performance. The introduction of smart menus and graphical user interfaces for analytics has changed the way many approach data analytics and data science. It is more friendly and requires more knowledge of how processes work to gain results with meaning and coherence. Conclusion There are different ways and tools to develop a solution for knowledge from data. Analytics done in code is more control and provides specific results. Using a toolset that has blocks is less control and provides results that are based on subunits creating a tradeoff on control, how a process works. Last, using an app and selecting by forms and menus is little control over process, easy, and will process according to parameters with little seen of the computation. Choice is there for tools specifically with machine learning and artificial intelligence, however best fit for the situation and conditions is important.
https://medium.com/ai-in-plain-english/tools-for-machine-learning-and-artificial-intelligence-in-analytics-5313c2ba05e
['Sarah Mason']
2020-12-28 08:04:44.217000+00:00
['Machine Learning', 'Analytics Platforms', 'Artificial Intelligence', 'Analytic Applications', 'AI']
Title Tools Machine Learning Artificial Intelligence AnalyticsContent Photo Mitchell Luo Unsplash tool analytics reference apps allow environment create solution language library even graphical user interface manipulate data insight information many tool data analytics available Tools Anaconda provides environment Python R including machine learning maclinuxwindows downloading app installing environment customized include variety data science tool library Anaconda used desktop also exists cloud version JetBrains organization lot apps specific goal PyCharm Python DataGrip Databases RubyMine Ruby analytics tool set ability integrate across tool unique positive creating full apps artificial intelligent component subcomponents code piece app language like PHP work together JetBrains solution Google analytics tool notably Looker Google Cloud Platform Microsoft Access Azure Excel Power BI provide analytics data service IBM SPSS Watson tool cloud local version platform SPSS provides analytics smart menu graphical user interface Watson famous performance “Jeopardy” January 14 2011 tasked competing human trivia service tasked data challenge Salesforce Tableau business oriented analytics service Snowflake data warehouse analytics provider providing data service Photo Patrick Fore Unsplash experience cloud local tool Cloud trending easy great benefit Artificial Intelligence highly integrated tool platform range much control developer user method performance introduction smart menu graphical user interface analytics changed way many approach data analytics data science friendly requires knowledge process work gain result meaning coherence Conclusion different way tool develop solution knowledge data Analytics done code control provides specific result Using toolset block le control provides result based subunit creating tradeoff control process work Last using app selecting form menu little control process easy process according parameter little seen computation Choice tool specifically machine learning artificial intelligence however best fit situation condition importantTags Machine Learning Analytics Platforms Artificial Intelligence Analytic Applications AI
2,895
How to Learn Coding: From Theory to Practice
source: Unsplash Software development is one of the most popular professions today with an average salary of $59,568 a year. As the demand for promising coding professionals is not going anywhere, many people strive to master new skills to join the ranks of developers. But, even if you don’t plan to become a full-time developer, obtaining experience in coding will open up more opportunities and greatly benefit your future career. In this post, I will help you start your journey in the world of coding — you will figure out the best ways to make the learning process efficient. Following these tips will put you on the right track. Top Recommendations on How to Learn Coding There is no single correct algorithm to follow to become a first-class developer. However, I have a few encouraging pieces of advice for everyone who wants to learn to code independently but has no idea where to start. Let’s get right to the point. Start with a Brainstorm Every single process requires thorough preparation. Coding is no exception. Before starting to learn any programming language, it is quite important to decide on the real reasons you want that. Answering the following questions will let you figure that out. What reasons are there to become a dev? Am I going to learn just for fun? Do I want to get a promotion or change my career? Do I have an idea for my own app and need appropriate skills for it? What kind of software developer do I want to become? Do I plan to work in a company? Do I want to work individually? Is freelance a better option for me? What industries am I interested in? Web development? Server-side projects? Game development? Big Data, or others? Additionally, do some research among different industries, be it fintech or AI, enquire about what kind of programmers they are looking for, and learn job specifics and salaries to decide where you want to work. Of course, if you already have a preferred industry in your mind, you’re a step ahead. Answering the given questions will also help you determine the programming language to master. E.g., creating a well-performing OS or alternatives to prominent photo editors may only require studying formal computer science. The latter will give you a clear understanding of C++ language, data structure, memory allocation, and algorithms. Although, if you want to make a mid-career change to a tech job, it is reasonable to apply for an intensive website development program rather than spend a fortune on obtaining the second degree. Choosing the Right Programming Language Now you know the reason for learning to code, so choosing the right language will be way easier. In a few words, mobile apps flawlessly perform if they are based on Java, Swift or Kotlin. Javascript, in its turn, is suitable for front-end development, while PHP and Python will benefit back-end devs. To create video games, developers prefer C++. Choosing the programming language requires considering its popularity on the market. Let’s take a quick look at the TIOBE Index. Java has never left the top three most popular coding languages. Two other languages commonly used in many areas of software development include C and Python, which are unlikely to lose their popularity in the coming years. For a better idea on the most commonly used programming languages, I will give you a quick overview of them. Java Java is an easy-to-manage object-oriented multithreaded programming language with a good level of security. It is an independent platform that follows the clue “Write once, Run anywhere”, which means you can transfer the already written app between different platforms. Java also ensures backward compatibility and is easier to keep up with compared to C++ and any other programming languages. Main uses: Server-side enterprise applications Desktop enterprise Android apps (including games) Big Data Embed Scientific Applications Systems Finances and Trading Software Tools Sometimes — Big Games (such as Minecraft) Python Python is another high-level, server-side interpreted scripting language. It can be used as an independent language or as a part of another framework. With its constructs and object-oriented approach, it allows developers to write readable code for small and large projects. Main uses: Desktop GUIs Software AI and ML Data science and visualization Web scraping apps and more C Language C language is a machine-independent, general-purpose programming language frequently used in various applications, including low-level ones. There is an opinion that it is a base for programming, so if you’ve mastered C language, you can easily master the others. Main uses: Embedded systems System and desktop apps Browsers and their extensions Databases Operating systems Javascript JavaScript, abbreviated as JS, determines a high-level and multi-paradigm programming language used for client-side page behavior. JS is also known as one of the key technologies enabling interactive web pages and playing a significant role in building web apps. Main uses: Front-end web development Non-browser applications Games and APIs Web-based slide decks Smartwatch apps, etc PHP PHP refers to an open-source scripting language used to generate dynamic page content that supports a wide range of databases. PHP runs on various platforms and is compatible with almost all commonly used servers, including Apache, IIS, and others. PHP files can support text, HTML, CSS, JavaScript, and PHP code. Main uses: Web development (backend) LAMP platform used by Facebook and Yahoo CMS platforms Form data collection Encrypted data Cookies SQL SQL stands for Structured Query Language used to work with databases. MySQL, an open-source version of SQL, is the most common way to interact with databases. Main uses: Relational database management systems Data query language Database transaction management Manual analysis Procedures, user-defined functions, triggers, indexes, etc. Swift Swift is a six-year-old product by Apple Inc. built using a modern approach to safety, performance, and software design patterns. This general-purpose coding language makes writing and maintaining programs easier for developers. Main uses: Mobile and desktop apps for iOS and OS X Cloud services A new class of modern server applications Event-driven network application framework Server-oriented tools and technologies, comprising metrics and database drivers, etc. C# C# language (pronounced “see sharp”) is more or less like Java, but made by Microsoft. It is a type-safe object-oriented language used to build secure and robust apps that run in the .NET ecosystem. Main uses: Backend services Microsoft .NET-connected apps Windows apps Server-side web applications Games with the Unity game engine, etc. Give Online Courses a Try If you don’t feel comfortable about an in-person coding-intensive program, there are multiple courses on the web to choose from. Since many of them teach the same coding language in different ways and picking up the right course may be challenging, I’ve put together a few working solutions. Practical Training I’ve recently had a talk with fellow developers about what advice they would give to newbies. They all answered that the more practice, the better. So, I’ve decided to put practical training in the first place. Other than theory, coding needs practice that allows for developing problem-solving skills. For this, you need to choose the right platform. For instance, you can go for coding platforms based on practice, such as: CodeGym. This online course is directly aimed at studying Java programming and consists of 80% practice. Despite the theory, it offers 1200 small practical tasks of increasing complexity. To get experience and land a job, you need to write tons of code. FreeCodeCamp with a whole lot of project-based tasks. Also, they have a great News and Forum section. You could get a certification in Python, JavaScript, HTML, CSS, etc. Code4Startup with an ability to write your first line of code for an existing business. Codewars addictive assignments that let you test your skills while competing with your fellow developers. Code Avengers with a bulk of engaging quizzes on different programming languages, etc. Theoretical Training Regardless of what you are learning, the educational process is not complete without the theory. I would say you should try Udacity. It is a MOOC-based platform, so everyone who wants to start learning to code can sign up and get an online learning experience right away. I like the range of courses this website offers. They are in micro-credential form, also known as Nanodegrees. The micro-credentials that are sometimes released for free come with video courses and projects. So, you can choose one to your liking, sorting them by language and level. If to say about other resources used for theoretical training, I would also highlight books as an additional source of learning. Every learning process requires starting with the details, hence involves familiarization with the theory in one way or another. It is likely to give you a good idea of coding. So, if you are looking for helpful books, I would recommend considering the next three. Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. “Uncle Bob” Martin The Pragmatic Programmer: From Journeyman to Master by Andrew Hunt and Dave Thomas Code Complete: A Practical Handbook of Software Construction by Steve McConnell Put Interactive Tutorials and Coding Games on the List What makes interactive coding tutorials good is that they bring into action the so-called abstract concepts you would read about in a book, so you won’t get bored while obtaining the programming experience. For instance, the CodeGym platform offers different coding gamified projects in the Games section. The whole course has an exciting plot, vivid characters, and a tricky concept explained through real-life examples, you will keep training without getting bored. For example, there are four cool quests with a robot named Amigo. Every single quest contains ten levels with 12 to 13 lessons and guides through different subjects from Java Core to Java Multithreading. So, students can’t jump to the next level or more fun stuff until they debug the code while learning, which is very useful, as if you want to become a programmer, you need to code. The other courses I’ve previously mentioned also offer interactive tutorials, quizzes, and other engaging tasks, such as: Project Caesar Cipher on Ruby programming at the Odin Project Mastering different languages on kata at Codewars Different gamified courses at Code Avengers, etc. Consider Watching Videos When Learning to Code People perceive information differently: one prefers reading books or taking courses, while the other chooses to watch videos on platforms like YouTube. Learning to code by watching videos is cost-saving and allows for moving at your own pace — you can either spend more time on the video or skip ahead if things seem easy to you. YouTube is home to numerous educational videos dedicated to software development. Here you can find coding marathons and solutions that show how to troubleshoot issues within any programming language you can imagine. So, if you are the one searching for decent content, my top-ten list of YouTube channels for coding is at your disposal. Google the Error Let’s face it: everyone who learns to code experiences errors that break their code. You are not alone in your problem — there are many users before you who have made the same mistakes and already found solutions. So, if you are struggling to understand why your code is broken and can’t find the explanation, try to google the error. This is a simple yet effective trick that is more likely to give answers to your concerns. Otherwise, you can leave your question on Q&A or discussion websites, such as Stack Overflow, Reddit, or GitHub. Unpack Someone Else’s Code As soon as you get a clear idea of how to code, it’s time to move further and strengthen your knowledge of the programming language. Here we come to the unpacking of someone else’s code. Browse GitHub to find the code file, open it in your code editor, and start working through. Feel free to apply your changes if you see they can improve the outcome. When done, save the edited code and share it back with the community to get feedback from your peers. Communicate with Other Programmers Teaching yourself to code and spending hours at the computer can put you out of reality. Even though figuring things out on your own may be the best way to learn coding, sometimes outside help is necessary to get to the solution faster. Communicate with other developers, visit tech talks of all kinds, hackathons, startups, and other tech events to make useful contacts. Or the simplest way is through online forums. Here they are: Github is a community where people learn, share, and work together to build software. It allows for managing your open-source projects, contributing to others, showcasing your work, attracting recruiters, and more. StackOverflow is a Q&A website for both newbies and experienced programmers. It lets you find answers to the toughest coding questions, share knowledge, and even find your dream job. HackerNews is a highly trusted cybersecurity news platform attracting IT professionals, hackers, technologists, and others. It features the latest security news and builds a bridge between communities like security researchers, business grads, and thousands of security professionals. Reddit is a social news aggregation and discussion website. It puts together thousands of communities and lets users share the things they care about. All you have to do is find the right subreddits about programming. Come Up with Your Own Project and Implement It Building your own project, like a little app or so, is a good idea if you want to stay motivated about teaching yourself to code. Your own project forces you to move forward, keep practicing, and overcome grief and blockages. So, to start: Set a goal to create a project. Make sure you and other people need it in real life. Use the skills you already have. Work to improve and extend your project’s scope of application. Plan future features and consider the skills you would need for their implementation. Extra Tips to Stay Motivated Coding is not easy — like many other beginners, you may sometimes fail, become frustrated, stop all attempts to cope with lines of code, and give up. That is why you need to create a friendly atmosphere around you while learning to code. Try to avoid becoming a strict parent or primary school teacher who scolds you for mistakes. Be a friend to yourself and remember a few things. Never compare yourself to other developers. Although the advice has a cliché, it is one to remember. Everyone starts somewhere — those who are on chapter 20 today have started from chapter 1, where you are now, and once wrote their first line of code, just like you. You’re making much more progress than you think. Have you ever thought you are not progressing? Sure, you have. Everyone who starts learning something passes that. You start thinking you’re not making enough effort, nothing changes, and you are still on the same stage you started with. However, the fact is that every time you study or code, you are growing — just accept it and look back to see how much you’ve already done. Everyone struggles in the beginning. The learning process is always challenging, but that doesn’t mean you are going to be a bad coder. Feeling frustrated is normal, especially if you’ve just started training and everything seems vague to you. Let’s Wrap It Up How long does it take to learn coding? There is no single correct answer, as everyone starts with their own level of training and at their own pace. However, if you follow the given advice, you can get to your first line of code a little bit faster. For this, start with small things, like choosing the appropriate programming language and taking online courses. Then move on to bigger ones, like completing tasks on different platforms, unpacking someone else’s code, and building your own project. The learning process is not a piece of cake, so make sure to create a friendly environment and support yourself, especially when you want to give up. The understanding that you are in the same boat with other developers who take the same steps during this path to coding will help you stay motivated about teaching yourself to code.
https://medium.com/quick-code/how-to-learn-coding-from-theory-to-practice-265e5ea68bf1
['John Selawsky']
2020-08-08 04:04:02.021000+00:00
['Python', 'C Sharp Programming', 'Learn Coding', 'Java', 'Programming Languages']
Title Learn Coding Theory PracticeContent source Unsplash Software development one popular profession today average salary 59568 year demand promising coding professional going anywhere many people strive master new skill join rank developer even don’t plan become fulltime developer obtaining experience coding open opportunity greatly benefit future career post help start journey world coding — figure best way make learning process efficient Following tip put right track Top Recommendations Learn Coding single correct algorithm follow become firstclass developer However encouraging piece advice everyone want learn code independently idea start Let’s get right point Start Brainstorm Every single process requires thorough preparation Coding exception starting learn programming language quite important decide real reason want Answering following question let figure reason become dev going learn fun want get promotion change career idea app need appropriate skill kind software developer want become plan work company want work individually freelance better option industry interested Web development Serverside project Game development Big Data others Additionally research among different industry fintech AI enquire kind programmer looking learn job specific salary decide want work course already preferred industry mind you’re step ahead Answering given question also help determine programming language master Eg creating wellperforming OS alternative prominent photo editor may require studying formal computer science latter give clear understanding C language data structure memory allocation algorithm Although want make midcareer change tech job reasonable apply intensive website development program rather spend fortune obtaining second degree Choosing Right Programming Language know reason learning code choosing right language way easier word mobile apps flawlessly perform based Java Swift Kotlin Javascript turn suitable frontend development PHP Python benefit backend devs create video game developer prefer C Choosing programming language requires considering popularity market Let’s take quick look TIOBE Index Java never left top three popular coding language Two language commonly used many area software development include C Python unlikely lose popularity coming year better idea commonly used programming language give quick overview Java Java easytomanage objectoriented multithreaded programming language good level security independent platform follows clue “Write Run anywhere” mean transfer already written app different platform Java also ensures backward compatibility easier keep compared C programming language Main us Serverside enterprise application Desktop enterprise Android apps including game Big Data Embed Scientific Applications Systems Finances Trading Software Tools Sometimes — Big Games Minecraft Python Python another highlevel serverside interpreted scripting language used independent language part another framework construct objectoriented approach allows developer write readable code small large project Main us Desktop GUIs Software AI ML Data science visualization Web scraping apps C Language C language machineindependent generalpurpose programming language frequently used various application including lowlevel one opinion base programming you’ve mastered C language easily master others Main us Embedded system System desktop apps Browsers extension Databases Operating system Javascript JavaScript abbreviated JS determines highlevel multiparadigm programming language used clientside page behavior JS also known one key technology enabling interactive web page playing significant role building web apps Main us Frontend web development Nonbrowser application Games APIs Webbased slide deck Smartwatch apps etc PHP PHP refers opensource scripting language used generate dynamic page content support wide range database PHP run various platform compatible almost commonly used server including Apache IIS others PHP file support text HTML CSS JavaScript PHP code Main us Web development backend LAMP platform used Facebook Yahoo CMS platform Form data collection Encrypted data Cookies SQL SQL stand Structured Query Language used work database MySQL opensource version SQL common way interact database Main us Relational database management system Data query language Database transaction management Manual analysis Procedures userdefined function trigger index etc Swift Swift sixyearold product Apple Inc built using modern approach safety performance software design pattern generalpurpose coding language make writing maintaining program easier developer Main us Mobile desktop apps iOS OS X Cloud service new class modern server application Eventdriven network application framework Serveroriented tool technology comprising metric database driver etc C C language pronounced “see sharp” le like Java made Microsoft typesafe objectoriented language used build secure robust apps run NET ecosystem Main us Backend service Microsoft NETconnected apps Windows apps Serverside web application Games Unity game engine etc Give Online Courses Try don’t feel comfortable inperson codingintensive program multiple course web choose Since many teach coding language different way picking right course may challenging I’ve put together working solution Practical Training I’ve recently talk fellow developer advice would give newbie answered practice better I’ve decided put practical training first place theory coding need practice allows developing problemsolving skill need choose right platform instance go coding platform based practice CodeGym online course directly aimed studying Java programming consists 80 practice Despite theory offer 1200 small practical task increasing complexity get experience land job need write ton code FreeCodeCamp whole lot projectbased task Also great News Forum section could get certification Python JavaScript HTML CSS etc Code4Startup ability write first line code existing business Codewars addictive assignment let test skill competing fellow developer Code Avengers bulk engaging quiz different programming language etc Theoretical Training Regardless learning educational process complete without theory would say try Udacity MOOCbased platform everyone want start learning code sign get online learning experience right away like range course website offer microcredential form also known Nanodegrees microcredentials sometimes released free come video course project choose one liking sorting language level say resource used theoretical training would also highlight book additional source learning Every learning process requires starting detail hence involves familiarization theory one way another likely give good idea coding looking helpful book would recommend considering next three Clean Code Handbook Agile Software Craftsmanship Robert C “Uncle Bob” Martin Pragmatic Programmer Journeyman Master Andrew Hunt Dave Thomas Code Complete Practical Handbook Software Construction Steve McConnell Put Interactive Tutorials Coding Games List make interactive coding tutorial good bring action socalled abstract concept would read book won’t get bored obtaining programming experience instance CodeGym platform offer different coding gamified project Games section whole course exciting plot vivid character tricky concept explained reallife example keep training without getting bored example four cool quest robot named Amigo Every single quest contains ten level 12 13 lesson guide different subject Java Core Java Multithreading student can’t jump next level fun stuff debug code learning useful want become programmer need code course I’ve previously mentioned also offer interactive tutorial quiz engaging task Project Caesar Cipher Ruby programming Odin Project Mastering different language kata Codewars Different gamified course Code Avengers etc Consider Watching Videos Learning Code People perceive information differently one prefers reading book taking course chooses watch video platform like YouTube Learning code watching video costsaving allows moving pace — either spend time video skip ahead thing seem easy YouTube home numerous educational video dedicated software development find coding marathon solution show troubleshoot issue within programming language imagine one searching decent content topten list YouTube channel coding disposal Google Error Let’s face everyone learns code experience error break code alone problem — many user made mistake already found solution struggling understand code broken can’t find explanation try google error simple yet effective trick likely give answer concern Otherwise leave question QA discussion website Stack Overflow Reddit GitHub Unpack Someone Else’s Code soon get clear idea code it’s time move strengthen knowledge programming language come unpacking someone else’s code Browse GitHub find code file open code editor start working Feel free apply change see improve outcome done save edited code share back community get feedback peer Communicate Programmers Teaching code spending hour computer put reality Even though figuring thing may best way learn coding sometimes outside help necessary get solution faster Communicate developer visit tech talk kind hackathons startup tech event make useful contact simplest way online forum Github community people learn share work together build software allows managing opensource project contributing others showcasing work attracting recruiter StackOverflow QA website newbie experienced programmer let find answer toughest coding question share knowledge even find dream job HackerNews highly trusted cybersecurity news platform attracting professional hacker technologist others feature latest security news build bridge community like security researcher business grad thousand security professional Reddit social news aggregation discussion website put together thousand community let user share thing care find right subreddits programming Come Project Implement Building project like little app good idea want stay motivated teaching code project force move forward keep practicing overcome grief blockage start Set goal create project Make sure people need real life Use skill already Work improve extend project’s scope application Plan future feature consider skill would need implementation Extra Tips Stay Motivated Coding easy — like many beginner may sometimes fail become frustrated stop attempt cope line code give need create friendly atmosphere around learning code Try avoid becoming strict parent primary school teacher scold mistake friend remember thing Never compare developer Although advice cliché one remember Everyone start somewhere — chapter 20 today started chapter 1 wrote first line code like You’re making much progress think ever thought progressing Sure Everyone start learning something pass start thinking you’re making enough effort nothing change still stage started However fact every time study code growing — accept look back see much you’ve already done Everyone struggle beginning learning process always challenging doesn’t mean going bad coder Feeling frustrated normal especially you’ve started training everything seems vague Let’s Wrap long take learn coding single correct answer everyone start level training pace However follow given advice get first line code little bit faster start small thing like choosing appropriate programming language taking online course move bigger one like completing task different platform unpacking someone else’s code building project learning process piece cake make sure create friendly environment support especially want give understanding boat developer take step path coding help stay motivated teaching codeTags Python C Sharp Programming Learn Coding Java Programming Languages
2,896
Tell the World About It, Even if the World Doesn’t Care
I migrated my blog last weekend. Over ten years worth of articles! (though I should say that I haven’t blogged regularly since 2013) Goodbye self-hosted static site with CSS from 2009. Hello Medium. It’s possible that I’m a little late to this party. In the end, I didn’t end up importing everything. Because Medium appears to lack the ability to auto-import articles from Jekyll (preposterous! who would have thought?!), I had to manually migrate — or at least extensively edit — most of the content. Only the top 50 or so articles that were receiving significant traffic from Google Analytics made the cut. So I had an excuse to cheat a bit and discard a lot of the chaff. Looking back on the rants and raves of 20-something me (the way that soon 40-something me will look back on 30-something me), even the best of those posts can still seem rather embarrassing. Misplaced enthusiasm for absurd tools, often impractical NIH-ism, and terrible grammar are among the many crimes of my youth. It’s also readily apparent that the tech industry as a whole has evolved a lot; 2007’s developer best practices were not what we would today consider practices at all, let alone preferential practices. Such is progress. Reading through those old posts was also inspiring. It reminded me that at one time a regular writing schedule served a super important developmental function for me. It’s widely documented that there are a bunch of pretty great benefits that one gets from writing on the regular. It helps you organize and reframe your thoughts, it can be therapeutic during hard times, and improves memory recall. If nothing else, it’s a fantastically cheap type of external memory. Writing something down means you never have to ask “what exactly did I do yesterday, anyway?” or “how long did that crazy project take me and what did I actually learn from it?” (anyone who doesn’t manage their life through daily TODO lists is definitely missing out on an awesome party). The most important benefit for me was that writing in public was a way of committing myself to certain things, on a certain schedule, at a time when my life was pretty much completely unscheduled. Knowing that I had to publish an article every week, or every month, or on any schedule really, ensured that I was continuously learning things that were worth talking about, and later, building things that had enough value to share… even if I was sometimes inventing those things just so I could share them. And even if no one was listening (which was frequently the case). Not everyone needs this sort of framework for self-discipline. But it sure helped me when I needed it most.
https://medium.com/zerosum-dot-org/tell-the-world-about-it-even-if-the-world-doesnt-care-48130678a333
['Nick Plante']
2017-12-08 00:49:14.192000+00:00
['Software Development', 'Productivity', 'Blogging', 'Life Hacking', 'Writing']
Title Tell World Even World Doesn’t CareContent migrated blog last weekend ten year worth article though say haven’t blogged regularly since 2013 Goodbye selfhosted static site CSS 2009 Hello Medium It’s possible I’m little late party end didn’t end importing everything Medium appears lack ability autoimport article Jekyll preposterous would thought manually migrate — least extensively edit — content top 50 article receiving significant traffic Google Analytics made cut excuse cheat bit discard lot chaff Looking back rant raf 20something way soon 40something look back 30something even best post still seem rather embarrassing Misplaced enthusiasm absurd tool often impractical NIHism terrible grammar among many crime youth It’s also readily apparent tech industry whole evolved lot 2007’s developer best practice would today consider practice let alone preferential practice progress Reading old post also inspiring reminded one time regular writing schedule served super important developmental function It’s widely documented bunch pretty great benefit one get writing regular help organize reframe thought therapeutic hard time improves memory recall nothing else it’s fantastically cheap type external memory Writing something mean never ask “what exactly yesterday anyway” “how long crazy project take actually learn it” anyone doesn’t manage life daily TODO list definitely missing awesome party important benefit writing public way committing certain thing certain schedule time life pretty much completely unscheduled Knowing publish article every week every month schedule really ensured continuously learning thing worth talking later building thing enough value share… even sometimes inventing thing could share even one listening frequently case everyone need sort framework selfdiscipline sure helped needed mostTags Software Development Productivity Blogging Life Hacking Writing
2,897
How it optimize the disk usage in the Prometheus database?
How it optimize the disk usage in the Prometheus database? Learn some tricks to analyze and optimize the usage that you are doing of the TSDB and save money on your cloud deployment. Photo by Markus Spiske on Unsplash In previous posts, we discussed how the storage layer worked for Prometheus and how effective it was. But in the current times, we are of cloud computing we know that each technical optimization is also a cost optimization as well and that is why we need to be very diligent about any option that we use regarding optimization. We know that usually when we monitor using Prometheus we have so many exporters available at our disposal and also that each of them exposes a lot of very relevant metrics that we need to track everything we need to. But also, we should be aware that there are also metrics that we don’t need at this moment or we don’t plan to use it. So, if we are not planning to use, why do we want to waste disk space storing them? So, let’s start taking a look at one of the exporters we have in our system. In my case, I would like to use a BusinessWorks Container Application that exposes metrics about its utilization. If you check their metrics endpoint you could see something like this: # HELP jvm_info JVM version info # TYPE jvm_info gauge jvm_info{version="1.8.0_221-b27",vendor="Oracle Corporation",runtime="Java(TM) SE Runtime Environment",} 1.0 # HELP jvm_memory_bytes_used Used bytes of a given JVM memory area. # TYPE jvm_memory_bytes_used gauge jvm_memory_bytes_used{area="heap",} 1.0318492E8 jvm_memory_bytes_used{area="nonheap",} 1.52094712E8 # HELP jvm_memory_bytes_committed Committed (bytes) of a given JVM memory area. # TYPE jvm_memory_bytes_committed gauge jvm_memory_bytes_committed{area="heap",} 1.35266304E8 jvm_memory_bytes_committed{area="nonheap",} 1.71302912E8 # HELP jvm_memory_bytes_max Max (bytes) of a given JVM memory area. # TYPE jvm_memory_bytes_max gauge jvm_memory_bytes_max{area="heap",} 1.073741824E9 jvm_memory_bytes_max{area="nonheap",} -1.0 # HELP jvm_memory_bytes_init Initial bytes of a given JVM memory area. # TYPE jvm_memory_bytes_init gauge jvm_memory_bytes_init{area="heap",} 1.34217728E8 jvm_memory_bytes_init{area="nonheap",} 2555904.0 # HELP jvm_memory_pool_bytes_used Used bytes of a given JVM memory pool. # TYPE jvm_memory_pool_bytes_used gauge jvm_memory_pool_bytes_used{pool="Code Cache",} 3.3337536E7 jvm_memory_pool_bytes_used{pool="Metaspace",} 1.04914136E8 jvm_memory_pool_bytes_used{pool="Compressed Class Space",} 1.384304E7 jvm_memory_pool_bytes_used{pool="G1 Eden Space",} 3.3554432E7 jvm_memory_pool_bytes_used{pool="G1 Survivor Space",} 1048576.0 jvm_memory_pool_bytes_used{pool="G1 Old Gen",} 6.8581912E7 # HELP jvm_memory_pool_bytes_committed Committed bytes of a given JVM memory pool. # TYPE jvm_memory_pool_bytes_committed gauge jvm_memory_pool_bytes_committed{pool="Code Cache",} 3.3619968E7 jvm_memory_pool_bytes_committed{pool="Metaspace",} 1.19697408E8 jvm_memory_pool_bytes_committed{pool="Compressed Class Space",} 1.7985536E7 jvm_memory_pool_bytes_committed{pool="G1 Eden Space",} 4.6137344E7 jvm_memory_pool_bytes_committed{pool="G1 Survivor Space",} 1048576.0 jvm_memory_pool_bytes_committed{pool="G1 Old Gen",} 8.8080384E7 # HELP jvm_memory_pool_bytes_max Max bytes of a given JVM memory pool. # TYPE jvm_memory_pool_bytes_max gauge jvm_memory_pool_bytes_max{pool="Code Cache",} 2.5165824E8 jvm_memory_pool_bytes_max{pool="Metaspace",} -1.0 jvm_memory_pool_bytes_max{pool="Compressed Class Space",} 1.073741824E9 jvm_memory_pool_bytes_max{pool="G1 Eden Space",} -1.0 jvm_memory_pool_bytes_max{pool="G1 Survivor Space",} -1.0 jvm_memory_pool_bytes_max{pool="G1 Old Gen",} 1.073741824E9 # HELP jvm_memory_pool_bytes_init Initial bytes of a given JVM memory pool. # TYPE jvm_memory_pool_bytes_init gauge jvm_memory_pool_bytes_init{pool="Code Cache",} 2555904.0 jvm_memory_pool_bytes_init{pool="Metaspace",} 0.0 jvm_memory_pool_bytes_init{pool="Compressed Class Space",} 0.0 jvm_memory_pool_bytes_init{pool="G1 Eden Space",} 7340032.0 jvm_memory_pool_bytes_init{pool="G1 Survivor Space",} 0.0 jvm_memory_pool_bytes_init{pool="G1 Old Gen",} 1.26877696E8 # HELP jvm_buffer_pool_used_bytes Used bytes of a given JVM buffer pool. # TYPE jvm_buffer_pool_used_bytes gauge jvm_buffer_pool_used_bytes{pool="direct",} 148590.0 jvm_buffer_pool_used_bytes{pool="mapped",} 0.0 # HELP jvm_buffer_pool_capacity_bytes Bytes capacity of a given JVM buffer pool. # TYPE jvm_buffer_pool_capacity_bytes gauge jvm_buffer_pool_capacity_bytes{pool="direct",} 148590.0 jvm_buffer_pool_capacity_bytes{pool="mapped",} 0.0 # HELP jvm_buffer_pool_used_buffers Used buffers of a given JVM buffer pool. # TYPE jvm_buffer_pool_used_buffers gauge jvm_buffer_pool_used_buffers{pool="direct",} 19.0 jvm_buffer_pool_used_buffers{pool="mapped",} 0.0 # HELP jvm_classes_loaded The number of classes that are currently loaded in the JVM # TYPE jvm_classes_loaded gauge jvm_classes_loaded 16993.0 # HELP jvm_classes_loaded_total The total number of classes that have been loaded since the JVM has started execution # TYPE jvm_classes_loaded_total counter jvm_classes_loaded_total 17041.0 # HELP jvm_classes_unloaded_total The total number of classes that have been unloaded since the JVM has started execution # TYPE jvm_classes_unloaded_total counter jvm_classes_unloaded_total 48.0 # HELP bwce_activity_stats_list BWCE Activity Statictics list # TYPE bwce_activity_stats_list gauge # HELP bwce_activity_counter_list BWCE Activity related Counters list # TYPE bwce_activity_counter_list gauge # HELP all_activity_events_count BWCE All Activity Events count by State # TYPE all_activity_events_count counter all_activity_events_count{StateName="CANCELLED",} 0.0 all_activity_events_count{StateName="COMPLETED",} 0.0 all_activity_events_count{StateName="STARTED",} 0.0 all_activity_events_count{StateName="FAULTED",} 0.0 # HELP activity_events_count BWCE All Activity Events count by Process, Activity State # TYPE activity_events_count counter # HELP activity_total_evaltime_count BWCE Activity EvalTime by Process and Activity # TYPE activity_total_evaltime_count counter # HELP activity_total_duration_count BWCE Activity DurationTime by Process and Activity # TYPE activity_total_duration_count counter # HELP bwpartner_instance:total_request Total Request for the partner invocation which mapped from the activities # TYPE bwpartner_instance:total_request counter # HELP bwpartner_instance:total_duration_ms Total Duration for the partner invocation which mapped from the activities (execution or latency) # TYPE bwpartner_instance:total_duration_ms counter # HELP bwce_process_stats BWCE Process Statistics list # TYPE bwce_process_stats gauge # HELP bwce_process_counter_list BWCE Process related Counters list # TYPE bwce_process_counter_list gauge # HELP all_process_events_count BWCE All Process Events count by State # TYPE all_process_events_count counter all_process_events_count{StateName="CANCELLED",} 0.0 all_process_events_count{StateName="COMPLETED",} 0.0 all_process_events_count{StateName="STARTED",} 0.0 all_process_events_count{StateName="FAULTED",} 0.0 # HELP process_events_count BWCE Process Events count by Operation # TYPE process_events_count counter # HELP process_duration_seconds_total BWCE Process Events duration by Operation in seconds # TYPE process_duration_seconds_total counter # HELP process_duration_milliseconds_total BWCE Process Events duration by Operation in milliseconds # TYPE process_duration_milliseconds_total counter # HELP bwdefinitions:partner BWCE Process Events count by Operation # TYPE bwdefinitions:partner counter bwdefinitions:partner{ProcessName="t1.module.item.getTransactionData",ActivityName="FTLPublisher",ServiceName="GetCustomer360",OperationName="GetDataOperation",PartnerService="TransactionService",PartnerOperation="GetTransactionsOperation",Location="internal",PartnerMiddleware="MW",} 1.0 bwdefinitions:partner{ProcessName=" t1.module.item.auditProcess",ActivityName="KafkaSendMessage",ServiceName="GetCustomer360",OperationName="GetDataOperation",PartnerService="AuditService",PartnerOperation="AuditOperation",Location="internal",PartnerMiddleware="MW",} 1.0 bwdefinitions:partner{ProcessName="t1.module.item.getCustomerData",ActivityName="JMSRequestReply",ServiceName="GetCustomer360",OperationName="GetDataOperation",PartnerService="CustomerService",PartnerOperation="GetCustomerDetailsOperation",Location="internal",PartnerMiddleware="MW",} 1.0 # HELP bwdefinitions:binding BW Design Time Repository - binding/transport definition # TYPE bwdefinitions:binding counter bwdefinitions:binding{ServiceName="GetCustomer360",OperationName="GetDataOperation",ServiceInterface="GetCustomer360:GetDataOperation",Binding="/customer",Transport="HTTP",} 1.0 # HELP bwdefinitions:service BW Design Time Repository - Service definition # TYPE bwdefinitions:service counter bwdefinitions:service{ProcessName="t1.module.sub.item.getCustomerData",ServiceName="GetCustomer360",OperationName="GetDataOperation",ServiceInstance="GetCustomer360:GetDataOperation",} 1.0 bwdefinitions:service{ProcessName="t1.module.sub.item.auditProcess",ServiceName="GetCustomer360",OperationName="GetDataOperation",ServiceInstance="GetCustomer360:GetDataOperation",} 1.0 bwdefinitions:service{ProcessName="t1.module.sub.orchestratorSubFlow",ServiceName="GetCustomer360",OperationName="GetDataOperation",ServiceInstance="GetCustomer360:GetDataOperation",} 1.0 bwdefinitions:service{ProcessName="t1.module.Process",ServiceName="GetCustomer360",OperationName="GetDataOperation",ServiceInstance="GetCustomer360:GetDataOperation",} 1.0 # HELP bwdefinitions:gateway BW Design Time Repository - Gateway definition # TYPE bwdefinitions:gateway counter bwdefinitions:gateway{ServiceName="GetCustomer360",OperationName="GetDataOperation",ServiceInstance="GetCustomer360:GetDataOperation",Endpoint="bwce-demo-mon-orchestrator-bwce",InteractionType="ISTIO",} 1.0 # HELP process_cpu_seconds_total Total user and system CPU time spent in seconds. # TYPE process_cpu_seconds_total counter process_cpu_seconds_total 1956.86 # HELP process_start_time_seconds Start time of the process since unix epoch in seconds. # TYPE process_start_time_seconds gauge process_start_time_seconds 1.604712447107E9 # HELP process_open_fds Number of open file descriptors. # TYPE process_open_fds gauge process_open_fds 763.0 # HELP process_max_fds Maximum number of open file descriptors. # TYPE process_max_fds gauge process_max_fds 1048576.0 # HELP process_virtual_memory_bytes Virtual memory size in bytes. # TYPE process_virtual_memory_bytes gauge process_virtual_memory_bytes 3.046207488E9 # HELP process_resident_memory_bytes Resident memory size in bytes. # TYPE process_resident_memory_bytes gauge process_resident_memory_bytes 4.2151936E8 # HELP jvm_gc_collection_seconds Time spent in a given JVM garbage collector in seconds. # TYPE jvm_gc_collection_seconds summary jvm_gc_collection_seconds_count{gc="G1 Young Generation",} 540.0 jvm_gc_collection_seconds_sum{gc="G1 Young Generation",} 4.754 jvm_gc_collection_seconds_count{gc="G1 Old Generation",} 2.0 jvm_gc_collection_seconds_sum{gc="G1 Old Generation",} 0.563 # HELP jvm_threads_current Current thread count of a JVM # TYPE jvm_threads_current gauge jvm_threads_current 98.0 # HELP jvm_threads_daemon Daemon thread count of a JVM # TYPE jvm_threads_daemon gauge jvm_threads_daemon 43.0 # HELP jvm_threads_peak Peak thread count of a JVM # TYPE jvm_threads_peak gauge jvm_threads_peak 98.0 # HELP jvm_threads_started_total Started thread count of a JVM # TYPE jvm_threads_started_total counter jvm_threads_started_total 109.0 # HELP jvm_threads_deadlocked Cycles of JVM-threads that are in deadlock waiting to acquire object monitors or ownable synchronizers # TYPE jvm_threads_deadlocked gauge jvm_threads_deadlocked 0.0 # HELP jvm_threads_deadlocked_monitor Cycles of JVM-threads that are in deadlock waiting to acquire object monitors # TYPE jvm_threads_deadlocked_monitor gauge jvm_threads_deadlocked_monitor 0.0 As you can see a lot of metrics but I have to be honest I am not using most of them in my dashboards and to generate my alerts. I can use the metrics regarding the application performance for each of the BusinessWorks process and its activities, also the JVM memory performance and number of threads but things like how the JVM GC is working for each of the layers of the JVM (G1 Young Generation, G1 Old Generation) I’m not using them at all. So, If I show the same metric endpoint highlighting the things that I am not using it would be something like this: # HELP jvm_info JVM version info # TYPE jvm_info gauge jvm_info{version="1.8.0_221-b27",vendor="Oracle Corporation",runtime="Java(TM) SE Runtime Environment",} 1.0 # HELP jvm_memory_bytes_used Used bytes of a given JVM memory area. # TYPE jvm_memory_bytes_used gauge jvm_memory_bytes_used{area="heap",} 1.0318492E8 jvm_memory_bytes_used{area="nonheap",} 1.52094712E8 # HELP jvm_memory_bytes_committed Committed (bytes) of a given JVM memory area. # TYPE jvm_memory_bytes_committed gauge jvm_memory_bytes_committed{area="heap",} 1.35266304E8 jvm_memory_bytes_committed{area="nonheap",} 1.71302912E8 # HELP jvm_memory_bytes_max Max (bytes) of a given JVM memory area. # TYPE jvm_memory_bytes_max gauge jvm_memory_bytes_max{area="heap",} 1.073741824E9 jvm_memory_bytes_max{area="nonheap",} -1.0 # HELP jvm_memory_bytes_init Initial bytes of a given JVM memory area. # TYPE jvm_memory_bytes_init gauge jvm_memory_bytes_init{area="heap",} 1.34217728E8 jvm_memory_bytes_init{area="nonheap",} 2555904.0 # HELP jvm_memory_pool_bytes_used Used bytes of a given JVM memory pool. # TYPE jvm_memory_pool_bytes_used gauge jvm_memory_pool_bytes_used{pool="Code Cache",} 3.3337536E7 jvm_memory_pool_bytes_used{pool="Metaspace",} 1.04914136E8 jvm_memory_pool_bytes_used{pool="Compressed Class Space",} 1.384304E7 jvm_memory_pool_bytes_used{pool="G1 Eden Space",} 3.3554432E7 jvm_memory_pool_bytes_used{pool="G1 Survivor Space",} 1048576.0 jvm_memory_pool_bytes_used{pool="G1 Old Gen",} 6.8581912E7 # HELP jvm_memory_pool_bytes_committed Committed bytes of a given JVM memory pool. # TYPE jvm_memory_pool_bytes_committed gauge jvm_memory_pool_bytes_committed{pool="Code Cache",} 3.3619968E7 jvm_memory_pool_bytes_committed{pool="Metaspace",} 1.19697408E8 jvm_memory_pool_bytes_committed{pool="Compressed Class Space",} 1.7985536E7 jvm_memory_pool_bytes_committed{pool="G1 Eden Space",} 4.6137344E7 jvm_memory_pool_bytes_committed{pool="G1 Survivor Space",} 1048576.0 jvm_memory_pool_bytes_committed{pool="G1 Old Gen",} 8.8080384E7 # HELP jvm_memory_pool_bytes_max Max bytes of a given JVM memory pool. # TYPE jvm_memory_pool_bytes_max gauge jvm_memory_pool_bytes_max{pool="Code Cache",} 2.5165824E8 jvm_memory_pool_bytes_max{pool="Metaspace",} -1.0 jvm_memory_pool_bytes_max{pool="Compressed Class Space",} 1.073741824E9 jvm_memory_pool_bytes_max{pool="G1 Eden Space",} -1.0 jvm_memory_pool_bytes_max{pool="G1 Survivor Space",} -1.0 jvm_memory_pool_bytes_max{pool="G1 Old Gen",} 1.073741824E9 # HELP jvm_memory_pool_bytes_init Initial bytes of a given JVM memory pool. # TYPE jvm_memory_pool_bytes_init gauge jvm_memory_pool_bytes_init{pool="Code Cache",} 2555904.0 jvm_memory_pool_bytes_init{pool="Metaspace",} 0.0 jvm_memory_pool_bytes_init{pool="Compressed Class Space",} 0.0 jvm_memory_pool_bytes_init{pool="G1 Eden Space",} 7340032.0 jvm_memory_pool_bytes_init{pool="G1 Survivor Space",} 0.0 jvm_memory_pool_bytes_init{pool="G1 Old Gen",} 1.26877696E8 # HELP jvm_buffer_pool_used_bytes Used bytes of a given JVM buffer pool. # TYPE jvm_buffer_pool_used_bytes gauge jvm_buffer_pool_used_bytes{pool="direct",} 148590.0 jvm_buffer_pool_used_bytes{pool="mapped",} 0.0 # HELP jvm_buffer_pool_capacity_bytes Bytes capacity of a given JVM buffer pool. # TYPE jvm_buffer_pool_capacity_bytes gauge jvm_buffer_pool_capacity_bytes{pool="direct",} 148590.0 jvm_buffer_pool_capacity_bytes{pool="mapped",} 0.0 # HELP jvm_buffer_pool_used_buffers Used buffers of a given JVM buffer pool. # TYPE jvm_buffer_pool_used_buffers gauge jvm_buffer_pool_used_buffers{pool="direct",} 19.0 jvm_buffer_pool_used_buffers{pool="mapped",} 0.0 # HELP jvm_classes_loaded The number of classes that are currently loaded in the JVM # TYPE jvm_classes_loaded gauge jvm_classes_loaded 16993.0 # HELP jvm_classes_loaded_total The total number of classes that have been loaded since the JVM has started execution # TYPE jvm_classes_loaded_total counter jvm_classes_loaded_total 17041.0 # HELP jvm_classes_unloaded_total The total number of classes that have been unloaded since the JVM has started execution # TYPE jvm_classes_unloaded_total counter jvm_classes_unloaded_total 48.0 # HELP bwce_activity_stats_list BWCE Activity Statictics list # TYPE bwce_activity_stats_list gauge # HELP bwce_activity_counter_list BWCE Activity related Counters list # TYPE bwce_activity_counter_list gauge # HELP all_activity_events_count BWCE All Activity Events count by State # TYPE all_activity_events_count counter all_activity_events_count{StateName="CANCELLED",} 0.0 all_activity_events_count{StateName="COMPLETED",} 0.0 all_activity_events_count{StateName="STARTED",} 0.0 all_activity_events_count{StateName="FAULTED",} 0.0 # HELP activity_events_count BWCE All Activity Events count by Process, Activity State # TYPE activity_events_count counter # HELP activity_total_evaltime_count BWCE Activity EvalTime by Process and Activity # TYPE activity_total_evaltime_count counter # HELP activity_total_duration_count BWCE Activity DurationTime by Process and Activity # TYPE activity_total_duration_count counter # HELP bwpartner_instance:total_request Total Request for the partner invocation which mapped from the activities # TYPE bwpartner_instance:total_request counter # HELP bwpartner_instance:total_duration_ms Total Duration for the partner invocation which mapped from the activities (execution or latency) # TYPE bwpartner_instance:total_duration_ms counter # HELP bwce_process_stats BWCE Process Statistics list # TYPE bwce_process_stats gauge # HELP bwce_process_counter_list BWCE Process related Counters list # TYPE bwce_process_counter_list gauge # HELP all_process_events_count BWCE All Process Events count by State # TYPE all_process_events_count counter all_process_events_count{StateName="CANCELLED",} 0.0 all_process_events_count{StateName="COMPLETED",} 0.0 all_process_events_count{StateName="STARTED",} 0.0 all_process_events_count{StateName="FAULTED",} 0.0 # HELP process_events_count BWCE Process Events count by Operation # TYPE process_events_count counter # HELP process_duration_seconds_total BWCE Process Events duration by Operation in seconds # TYPE process_duration_seconds_total counter # HELP process_duration_milliseconds_total BWCE Process Events duration by Operation in milliseconds # TYPE process_duration_milliseconds_total counter # HELP bwdefinitions:partner BWCE Process Events count by Operation # TYPE bwdefinitions:partner counter bwdefinitions:partner{ProcessName="t1.module.item.getTransactionData",ActivityName="FTLPublisher",ServiceName="GetCustomer360",OperationName="GetDataOperation",PartnerService="TransactionService",PartnerOperation="GetTransactionsOperation",Location="internal",PartnerMiddleware="MW",} 1.0 bwdefinitions:partner{ProcessName=" t1.module.item.auditProcess",ActivityName="KafkaSendMessage",ServiceName="GetCustomer360",OperationName="GetDataOperation",PartnerService="AuditService",PartnerOperation="AuditOperation",Location="internal",PartnerMiddleware="MW",} 1.0 bwdefinitions:partner{ProcessName="t1.module.item.getCustomerData",ActivityName="JMSRequestReply",ServiceName="GetCustomer360",OperationName="GetDataOperation",PartnerService="CustomerService",PartnerOperation="GetCustomerDetailsOperation",Location="internal",PartnerMiddleware="MW",} 1.0 # HELP bwdefinitions:binding BW Design Time Repository - binding/transport definition # TYPE bwdefinitions:binding counter bwdefinitions:binding{ServiceName="GetCustomer360",OperationName="GetDataOperation",ServiceInterface="GetCustomer360:GetDataOperation",Binding="/customer",Transport="HTTP",} 1.0 # HELP bwdefinitions:service BW Design Time Repository - Service definition # TYPE bwdefinitions:service counter bwdefinitions:service{ProcessName="t1.module.sub.item.getCustomerData",ServiceName="GetCustomer360",OperationName="GetDataOperation",ServiceInstance="GetCustomer360:GetDataOperation",} 1.0 bwdefinitions:service{ProcessName="t1.module.sub.item.auditProcess",ServiceName="GetCustomer360",OperationName="GetDataOperation",ServiceInstance="GetCustomer360:GetDataOperation",} 1.0 bwdefinitions:service{ProcessName="t1.module.sub.orchestratorSubFlow",ServiceName="GetCustomer360",OperationName="GetDataOperation",ServiceInstance="GetCustomer360:GetDataOperation",} 1.0 bwdefinitions:service{ProcessName="t1.module.Process",ServiceName="GetCustomer360",OperationName="GetDataOperation",ServiceInstance="GetCustomer360:GetDataOperation",} 1.0 # HELP bwdefinitions:gateway BW Design Time Repository - Gateway definition # TYPE bwdefinitions:gateway counter bwdefinitions:gateway{ServiceName="GetCustomer360",OperationName="GetDataOperation",ServiceInstance="GetCustomer360:GetDataOperation",Endpoint="bwce-demo-mon-orchestrator-bwce",InteractionType="ISTIO",} 1.0 # HELP process_cpu_seconds_total Total user and system CPU time spent in seconds. # TYPE process_cpu_seconds_total counter process_cpu_seconds_total 1956.86 # HELP process_start_time_seconds Start time of the process since unix epoch in seconds. # TYPE process_start_time_seconds gauge process_start_time_seconds 1.604712447107E9 # HELP process_open_fds Number of open file descriptors. # TYPE process_open_fds gauge process_open_fds 763.0 # HELP process_max_fds Maximum number of open file descriptors. # TYPE process_max_fds gauge process_max_fds 1048576.0 # HELP process_virtual_memory_bytes Virtual memory size in bytes. # TYPE process_virtual_memory_bytes gauge process_virtual_memory_bytes 3.046207488E9 # HELP process_resident_memory_bytes Resident memory size in bytes. # TYPE process_resident_memory_bytes gauge process_resident_memory_bytes 4.2151936E8 # HELP jvm_gc_collection_seconds Time spent in a given JVM garbage collector in seconds. # TYPE jvm_gc_collection_seconds summary jvm_gc_collection_seconds_count{gc="G1 Young Generation",} 540.0 jvm_gc_collection_seconds_sum{gc="G1 Young Generation",} 4.754 jvm_gc_collection_seconds_count{gc="G1 Old Generation",} 2.0 jvm_gc_collection_seconds_sum{gc="G1 Old Generation",} 0.563 # HELP jvm_threads_current Current thread count of a JVM # TYPE jvm_threads_current gauge jvm_threads_current 98.0 # HELP jvm_threads_daemon Daemon thread count of a JVM # TYPE jvm_threads_daemon gauge jvm_threads_daemon 43.0 # HELP jvm_threads_peak Peak thread count of a JVM # TYPE jvm_threads_peak gauge jvm_threads_peak 98.0 # HELP jvm_threads_started_total Started thread count of a JVM # TYPE jvm_threads_started_total counter jvm_threads_started_total 109.0 # HELP jvm_threads_deadlocked Cycles of JVM-threads that are in deadlock waiting to acquire object monitors or ownable synchronizers # TYPE jvm_threads_deadlocked gauge jvm_threads_deadlocked 0.0 # HELP jvm_threads_deadlocked_monitor Cycles of JVM-threads that are in deadlock waiting to acquire object monitors # TYPE jvm_threads_deadlocked_monitor gauge jvm_threads_deadlocked_monitor 0.0 So, it can be a 50% of the metric endpoint response the part that I’m not using, so, why I am using disk space that I am paying for to storing it? And this is just for a “critical exporter”, one that I try to use as much information as possible, but think about how many exporters do you have and how much information you use for each of them. Ok, so now the purpose and the motivation of this post are clear, but what we can do about it? Discovering the REST API Prometheus has an awesome REST API to expose all the information that you can wish about. If you have ever use the Graphical Interface for Prometheus (shown below) you are using the REST API because this is why is behind it. Target view of the Prometheus Graphical Interface We have all the documentation regarding the REST API in the Prometheus official documentation: But what is this API providing us in terms of the time-series database TSDB that Prometheus is using? TSDB Admin APIs We have a specific API to manage the performance of the TSDB database but in order to be able to use it, we need to enable the Admin API. And that is done by providing the following flag where we are launching the Prometheus server --web.enable-admin-api. If we are using the Prometheus Operator Helm Chart to deploy this we need to use the following item in our values.yaml ## EnableAdminAPI enables Prometheus the administrative HTTP API which includes functionality such as deleting time series. ## This is disabled by default. ## ref: https://prometheus.io/docs/prometheus/latest/querying/api/#tsdb-admin-apis ## enableAdminAPI: true We have a lot of options enable when we enable this administrative API but today we are going to focus on a single REST operation that is the “stats”. This is the only method related to TSDB that it doesn’t require to enable the Admin API. This operation, as we can read in the Prometheus documentation, returns the following items: headStats: This provides the following data about the head block of the TSDB: numSeries : The number of series. : The number of series. chunkCount : The number of chunks. : The number of chunks. minTime : The current minimum timestamp in milliseconds. : The current minimum timestamp in milliseconds. maxTime: The current maximum timestamp in milliseconds. seriesCountByMetricName: This will provide a list of metrics names and their series count. labelValueCountByLabelName: This will provide a list of the label names and their value count. memoryInBytesByLabelName This will provide a list of the label names and memory used in bytes. Memory usage is calculated by adding the length of all values for a given label name. seriesCountByLabelPair This will provide a list of label value pairs and their series count. To access to that API we need to hit the following endpoint: GET /api/v1/status/tsdb So, when I am doing that in my Prometheus deployment I get something similar to this: { "status":"success", "data":{ "seriesCountByMetricName":[ { "name":"apiserver_request_duration_seconds_bucket", "value":34884 }, { "name":"apiserver_request_latencies_bucket", "value":7344 }, { "name":"etcd_request_duration_seconds_bucket", "value":6000 }, { "name":"apiserver_response_sizes_bucket", "value":3888 }, { "name":"apiserver_request_latencies_summary", "value":2754 }, { "name":"etcd_request_latencies_summary", "value":1500 }, { "name":"apiserver_request_count", "value":1216 }, { "name":"apiserver_request_total", "value":1216 }, { "name":"container_tasks_state", "value":1140 }, { "name":"apiserver_request_latencies_count", "value":918 } ], "labelValueCountByLabelName":[ { "name":"__name__", "value":2374 }, { "name":"id", "value":210 }, { "name":"mountpoint", "value":208 }, { "name":"le", "value":195 }, { "name":"type", "value":185 }, { "name":"name", "value":181 }, { "name":"resource", "value":170 }, { "name":"secret", "value":168 }, { "name":"image", "value":107 }, { "name":"container_id", "value":97 } ], "memoryInBytesByLabelName":[ { "name":"__name__", "value":97729 }, { "name":"id", "value":21450 }, { "name":"mountpoint", "value":18123 }, { "name":"name", "value":13831 }, { "name":"image", "value":8005 }, { "name":"container_id", "value":7081 }, { "name":"image_id", "value":6872 }, { "name":"secret", "value":5054 }, { "name":"type", "value":4613 }, { "name":"resource", "value":3459 } ], "seriesCountByLabelValuePair":[ { "name":"namespace=default", "value":72064 }, { "name":"service=kubernetes", "value":70921 }, { "name":"endpoint=https", "value":70917 }, { "name":"job=apiserver", "value":70917 }, { "name":"component=apiserver", "value":57992 }, { "name":"instance=192.168.185.199:443", "value":40343 }, { "name":"__name__=apiserver_request_duration_seconds_bucket", "value":34884 }, { "name":"version=v1", "value":31152 }, { "name":"instance=192.168.112.31:443", "value":30574 }, { "name":"scope=cluster", "value":29713 } ] } } We can also check the same information if we use the new and experimental React User Interface on the following endpoint: /new/tsdb-status Graphical Visualization of top 10 series count by metric name in the new Prometheus UI So, with that, you will get the Top 10 series and labels that are inside your time-series database, so in case, some of them are not useful you can just get rid of them using the normal approaches to drop a series or a label. This is great, but what if all the ones shown here are relevant, what can we do about it? Mmmm, maybe we can use PromQL to monitor this (dogfodding approach). So if we would like to extract the same information but using PromQL we can do it with the following query: topk(10, count by (__name__)({__name__=~".+"})) Top 10 of metric series generated and stored in the time series database And now we have all the power at my hands. For example, let’s take a look not at the 10 more relevant but the 100 more relevants or any other filter that we need to apply. For example, let’s see the metrics regarding with the JVM that we discussed at the beginning. And we will do that with the following PromQL query: topk(100, count by (__name__)({__name__=~"jvm.+"})) Top 100 of metric series regarding to JVM metrics So we can see that we have at least 150 series regarding to metrics that I am not using at all. But let’s do it even better, let’s take a look at the same but group by job names: topk(10, count by (job,__name__)({__name__=~".+"}))
https://medium.com/dev-genius/how-it-optimize-the-disk-usage-in-the-prometheus-database-ef8151d201db
['Alex Vazquez']
2020-11-17 17:49:56.776000+00:00
['Software Development', 'Technology', 'Kubernetes', 'Cloud Computing', 'Programming']
Title optimize disk usage Prometheus databaseContent optimize disk usage Prometheus database Learn trick analyze optimize usage TSDB save money cloud deployment Photo Markus Spiske Unsplash previous post discussed storage layer worked Prometheus effective current time cloud computing know technical optimization also cost optimization well need diligent option use regarding optimization know usually monitor using Prometheus many exporter available disposal also expose lot relevant metric need track everything need also aware also metric don’t need moment don’t plan use planning use want waste disk space storing let’s start taking look one exporter system case would like use BusinessWorks Container Application expose metric utilization check metric endpoint could see something like HELP jvminfo JVM version info TYPE jvminfo gauge jvminfoversion180221b27vendorOracle CorporationruntimeJavaTM SE Runtime Environment 10 HELP jvmmemorybytesused Used byte given JVM memory area TYPE jvmmemorybytesused gauge jvmmemorybytesusedareaheap 10318492E8 jvmmemorybytesusedareanonheap 152094712E8 HELP jvmmemorybytescommitted Committed byte given JVM memory area TYPE jvmmemorybytescommitted gauge jvmmemorybytescommittedareaheap 135266304E8 jvmmemorybytescommittedareanonheap 171302912E8 HELP jvmmemorybytesmax Max byte given JVM memory area TYPE jvmmemorybytesmax gauge jvmmemorybytesmaxareaheap 1073741824E9 jvmmemorybytesmaxareanonheap 10 HELP jvmmemorybytesinit Initial byte given JVM memory area TYPE jvmmemorybytesinit gauge jvmmemorybytesinitareaheap 134217728E8 jvmmemorybytesinitareanonheap 25559040 HELP jvmmemorypoolbytesused Used byte given JVM memory pool TYPE jvmmemorypoolbytesused gauge jvmmemorypoolbytesusedpoolCode Cache 33337536E7 jvmmemorypoolbytesusedpoolMetaspace 104914136E8 jvmmemorypoolbytesusedpoolCompressed Class Space 1384304E7 jvmmemorypoolbytesusedpoolG1 Eden Space 33554432E7 jvmmemorypoolbytesusedpoolG1 Survivor Space 10485760 jvmmemorypoolbytesusedpoolG1 Old Gen 68581912E7 HELP jvmmemorypoolbytescommitted Committed byte given JVM memory pool TYPE jvmmemorypoolbytescommitted gauge jvmmemorypoolbytescommittedpoolCode Cache 33619968E7 jvmmemorypoolbytescommittedpoolMetaspace 119697408E8 jvmmemorypoolbytescommittedpoolCompressed Class Space 17985536E7 jvmmemorypoolbytescommittedpoolG1 Eden Space 46137344E7 jvmmemorypoolbytescommittedpoolG1 Survivor Space 10485760 jvmmemorypoolbytescommittedpoolG1 Old Gen 88080384E7 HELP jvmmemorypoolbytesmax Max byte given JVM memory pool TYPE jvmmemorypoolbytesmax gauge jvmmemorypoolbytesmaxpoolCode Cache 25165824E8 jvmmemorypoolbytesmaxpoolMetaspace 10 jvmmemorypoolbytesmaxpoolCompressed Class Space 1073741824E9 jvmmemorypoolbytesmaxpoolG1 Eden Space 10 jvmmemorypoolbytesmaxpoolG1 Survivor Space 10 jvmmemorypoolbytesmaxpoolG1 Old Gen 1073741824E9 HELP jvmmemorypoolbytesinit Initial byte given JVM memory pool TYPE jvmmemorypoolbytesinit gauge jvmmemorypoolbytesinitpoolCode Cache 25559040 jvmmemorypoolbytesinitpoolMetaspace 00 jvmmemorypoolbytesinitpoolCompressed Class Space 00 jvmmemorypoolbytesinitpoolG1 Eden Space 73400320 jvmmemorypoolbytesinitpoolG1 Survivor Space 00 jvmmemorypoolbytesinitpoolG1 Old Gen 126877696E8 HELP jvmbufferpoolusedbytes Used byte given JVM buffer pool TYPE jvmbufferpoolusedbytes gauge jvmbufferpoolusedbytespooldirect 1485900 jvmbufferpoolusedbytespoolmapped 00 HELP jvmbufferpoolcapacitybytes Bytes capacity given JVM buffer pool TYPE jvmbufferpoolcapacitybytes gauge jvmbufferpoolcapacitybytespooldirect 1485900 jvmbufferpoolcapacitybytespoolmapped 00 HELP jvmbufferpoolusedbuffers Used buffer given JVM buffer pool TYPE jvmbufferpoolusedbuffers gauge jvmbufferpoolusedbufferspooldirect 190 jvmbufferpoolusedbufferspoolmapped 00 HELP jvmclassesloaded number class currently loaded JVM TYPE jvmclassesloaded gauge jvmclassesloaded 169930 HELP jvmclassesloadedtotal total number class loaded since JVM started execution TYPE jvmclassesloadedtotal counter jvmclassesloadedtotal 170410 HELP jvmclassesunloadedtotal total number class unloaded since JVM started execution TYPE jvmclassesunloadedtotal counter jvmclassesunloadedtotal 480 HELP bwceactivitystatslist BWCE Activity Statictics list TYPE bwceactivitystatslist gauge HELP bwceactivitycounterlist BWCE Activity related Counters list TYPE bwceactivitycounterlist gauge HELP allactivityeventscount BWCE Activity Events count State TYPE allactivityeventscount counter allactivityeventscountStateNameCANCELLED 00 allactivityeventscountStateNameCOMPLETED 00 allactivityeventscountStateNameSTARTED 00 allactivityeventscountStateNameFAULTED 00 HELP activityeventscount BWCE Activity Events count Process Activity State TYPE activityeventscount counter HELP activitytotalevaltimecount BWCE Activity EvalTime Process Activity TYPE activitytotalevaltimecount counter HELP activitytotaldurationcount BWCE Activity DurationTime Process Activity TYPE activitytotaldurationcount counter HELP bwpartnerinstancetotalrequest Total Request partner invocation mapped activity TYPE bwpartnerinstancetotalrequest counter HELP bwpartnerinstancetotaldurationms Total Duration partner invocation mapped activity execution latency TYPE bwpartnerinstancetotaldurationms counter HELP bwceprocessstats BWCE Process Statistics list TYPE bwceprocessstats gauge HELP bwceprocesscounterlist BWCE Process related Counters list TYPE bwceprocesscounterlist gauge HELP allprocesseventscount BWCE Process Events count State TYPE allprocesseventscount counter allprocesseventscountStateNameCANCELLED 00 allprocesseventscountStateNameCOMPLETED 00 allprocesseventscountStateNameSTARTED 00 allprocesseventscountStateNameFAULTED 00 HELP processeventscount BWCE Process Events count Operation TYPE processeventscount counter HELP processdurationsecondstotal BWCE Process Events duration Operation second TYPE processdurationsecondstotal counter HELP processdurationmillisecondstotal BWCE Process Events duration Operation millisecond TYPE processdurationmillisecondstotal counter HELP bwdefinitionspartner BWCE Process Events count Operation TYPE bwdefinitionspartner counter bwdefinitionspartnerProcessNamet1moduleitemgetTransactionDataActivityNameFTLPublisherServiceNameGetCustomer360OperationNameGetDataOperationPartnerServiceTransactionServicePartnerOperationGetTransactionsOperationLocationinternalPartnerMiddlewareMW 10 bwdefinitionspartnerProcessName t1moduleitemauditProcessActivityNameKafkaSendMessageServiceNameGetCustomer360OperationNameGetDataOperationPartnerServiceAuditServicePartnerOperationAuditOperationLocationinternalPartnerMiddlewareMW 10 bwdefinitionspartnerProcessNamet1moduleitemgetCustomerDataActivityNameJMSRequestReplyServiceNameGetCustomer360OperationNameGetDataOperationPartnerServiceCustomerServicePartnerOperationGetCustomerDetailsOperationLocationinternalPartnerMiddlewareMW 10 HELP bwdefinitionsbinding BW Design Time Repository bindingtransport definition TYPE bwdefinitionsbinding counter bwdefinitionsbindingServiceNameGetCustomer360OperationNameGetDataOperationServiceInterfaceGetCustomer360GetDataOperationBindingcustomerTransportHTTP 10 HELP bwdefinitionsservice BW Design Time Repository Service definition TYPE bwdefinitionsservice counter bwdefinitionsserviceProcessNamet1modulesubitemgetCustomerDataServiceNameGetCustomer360OperationNameGetDataOperationServiceInstanceGetCustomer360GetDataOperation 10 bwdefinitionsserviceProcessNamet1modulesubitemauditProcessServiceNameGetCustomer360OperationNameGetDataOperationServiceInstanceGetCustomer360GetDataOperation 10 bwdefinitionsserviceProcessNamet1modulesuborchestratorSubFlowServiceNameGetCustomer360OperationNameGetDataOperationServiceInstanceGetCustomer360GetDataOperation 10 bwdefinitionsserviceProcessNamet1moduleProcessServiceNameGetCustomer360OperationNameGetDataOperationServiceInstanceGetCustomer360GetDataOperation 10 HELP bwdefinitionsgateway BW Design Time Repository Gateway definition TYPE bwdefinitionsgateway counter bwdefinitionsgatewayServiceNameGetCustomer360OperationNameGetDataOperationServiceInstanceGetCustomer360GetDataOperationEndpointbwcedemomonorchestratorbwceInteractionTypeISTIO 10 HELP processcpusecondstotal Total user system CPU time spent second TYPE processcpusecondstotal counter processcpusecondstotal 195686 HELP processstarttimeseconds Start time process since unix epoch second TYPE processstarttimeseconds gauge processstarttimeseconds 1604712447107E9 HELP processopenfds Number open file descriptor TYPE processopenfds gauge processopenfds 7630 HELP processmaxfds Maximum number open file descriptor TYPE processmaxfds gauge processmaxfds 10485760 HELP processvirtualmemorybytes Virtual memory size byte TYPE processvirtualmemorybytes gauge processvirtualmemorybytes 3046207488E9 HELP processresidentmemorybytes Resident memory size byte TYPE processresidentmemorybytes gauge processresidentmemorybytes 42151936E8 HELP jvmgccollectionseconds Time spent given JVM garbage collector second TYPE jvmgccollectionseconds summary jvmgccollectionsecondscountgcG1 Young Generation 5400 jvmgccollectionsecondssumgcG1 Young Generation 4754 jvmgccollectionsecondscountgcG1 Old Generation 20 jvmgccollectionsecondssumgcG1 Old Generation 0563 HELP jvmthreadscurrent Current thread count JVM TYPE jvmthreadscurrent gauge jvmthreadscurrent 980 HELP jvmthreadsdaemon Daemon thread count JVM TYPE jvmthreadsdaemon gauge jvmthreadsdaemon 430 HELP jvmthreadspeak Peak thread count JVM TYPE jvmthreadspeak gauge jvmthreadspeak 980 HELP jvmthreadsstartedtotal Started thread count JVM TYPE jvmthreadsstartedtotal counter jvmthreadsstartedtotal 1090 HELP jvmthreadsdeadlocked Cycles JVMthreads deadlock waiting acquire object monitor ownable synchronizer TYPE jvmthreadsdeadlocked gauge jvmthreadsdeadlocked 00 HELP jvmthreadsdeadlockedmonitor Cycles JVMthreads deadlock waiting acquire object monitor TYPE jvmthreadsdeadlockedmonitor gauge jvmthreadsdeadlockedmonitor 00 see lot metric honest using dashboard generate alert use metric regarding application performance BusinessWorks process activity also JVM memory performance number thread thing like JVM GC working layer JVM G1 Young Generation G1 Old Generation I’m using show metric endpoint highlighting thing using would something like HELP jvminfo JVM version info TYPE jvminfo gauge jvminfoversion180221b27vendorOracle CorporationruntimeJavaTM SE Runtime Environment 10 HELP jvmmemorybytesused Used byte given JVM memory area TYPE jvmmemorybytesused gauge jvmmemorybytesusedareaheap 10318492E8 jvmmemorybytesusedareanonheap 152094712E8 HELP jvmmemorybytescommitted Committed byte given JVM memory area TYPE jvmmemorybytescommitted gauge jvmmemorybytescommittedareaheap 135266304E8 jvmmemorybytescommittedareanonheap 171302912E8 HELP jvmmemorybytesmax Max byte given JVM memory area TYPE jvmmemorybytesmax gauge jvmmemorybytesmaxareaheap 1073741824E9 jvmmemorybytesmaxareanonheap 10 HELP jvmmemorybytesinit Initial byte given JVM memory area TYPE jvmmemorybytesinit gauge jvmmemorybytesinitareaheap 134217728E8 jvmmemorybytesinitareanonheap 25559040 HELP jvmmemorypoolbytesused Used byte given JVM memory pool TYPE jvmmemorypoolbytesused gauge jvmmemorypoolbytesusedpoolCode Cache 33337536E7 jvmmemorypoolbytesusedpoolMetaspace 104914136E8 jvmmemorypoolbytesusedpoolCompressed Class Space 1384304E7 jvmmemorypoolbytesusedpoolG1 Eden Space 33554432E7 jvmmemorypoolbytesusedpoolG1 Survivor Space 10485760 jvmmemorypoolbytesusedpoolG1 Old Gen 68581912E7 HELP jvmmemorypoolbytescommitted Committed byte given JVM memory pool TYPE jvmmemorypoolbytescommitted gauge jvmmemorypoolbytescommittedpoolCode Cache 33619968E7 jvmmemorypoolbytescommittedpoolMetaspace 119697408E8 jvmmemorypoolbytescommittedpoolCompressed Class Space 17985536E7 jvmmemorypoolbytescommittedpoolG1 Eden Space 46137344E7 jvmmemorypoolbytescommittedpoolG1 Survivor Space 10485760 jvmmemorypoolbytescommittedpoolG1 Old Gen 88080384E7 HELP jvmmemorypoolbytesmax Max byte given JVM memory pool TYPE jvmmemorypoolbytesmax gauge jvmmemorypoolbytesmaxpoolCode Cache 25165824E8 jvmmemorypoolbytesmaxpoolMetaspace 10 jvmmemorypoolbytesmaxpoolCompressed Class Space 1073741824E9 jvmmemorypoolbytesmaxpoolG1 Eden Space 10 jvmmemorypoolbytesmaxpoolG1 Survivor Space 10 jvmmemorypoolbytesmaxpoolG1 Old Gen 1073741824E9 HELP jvmmemorypoolbytesinit Initial byte given JVM memory pool TYPE jvmmemorypoolbytesinit gauge jvmmemorypoolbytesinitpoolCode Cache 25559040 jvmmemorypoolbytesinitpoolMetaspace 00 jvmmemorypoolbytesinitpoolCompressed Class Space 00 jvmmemorypoolbytesinitpoolG1 Eden Space 73400320 jvmmemorypoolbytesinitpoolG1 Survivor Space 00 jvmmemorypoolbytesinitpoolG1 Old Gen 126877696E8 HELP jvmbufferpoolusedbytes Used byte given JVM buffer pool TYPE jvmbufferpoolusedbytes gauge jvmbufferpoolusedbytespooldirect 1485900 jvmbufferpoolusedbytespoolmapped 00 HELP jvmbufferpoolcapacitybytes Bytes capacity given JVM buffer pool TYPE jvmbufferpoolcapacitybytes gauge jvmbufferpoolcapacitybytespooldirect 1485900 jvmbufferpoolcapacitybytespoolmapped 00 HELP jvmbufferpoolusedbuffers Used buffer given JVM buffer pool TYPE jvmbufferpoolusedbuffers gauge jvmbufferpoolusedbufferspooldirect 190 jvmbufferpoolusedbufferspoolmapped 00 HELP jvmclassesloaded number class currently loaded JVM TYPE jvmclassesloaded gauge jvmclassesloaded 169930 HELP jvmclassesloadedtotal total number class loaded since JVM started execution TYPE jvmclassesloadedtotal counter jvmclassesloadedtotal 170410 HELP jvmclassesunloadedtotal total number class unloaded since JVM started execution TYPE jvmclassesunloadedtotal counter jvmclassesunloadedtotal 480 HELP bwceactivitystatslist BWCE Activity Statictics list TYPE bwceactivitystatslist gauge HELP bwceactivitycounterlist BWCE Activity related Counters list TYPE bwceactivitycounterlist gauge HELP allactivityeventscount BWCE Activity Events count State TYPE allactivityeventscount counter allactivityeventscountStateNameCANCELLED 00 allactivityeventscountStateNameCOMPLETED 00 allactivityeventscountStateNameSTARTED 00 allactivityeventscountStateNameFAULTED 00 HELP activityeventscount BWCE Activity Events count Process Activity State TYPE activityeventscount counter HELP activitytotalevaltimecount BWCE Activity EvalTime Process Activity TYPE activitytotalevaltimecount counter HELP activitytotaldurationcount BWCE Activity DurationTime Process Activity TYPE activitytotaldurationcount counter HELP bwpartnerinstancetotalrequest Total Request partner invocation mapped activity TYPE bwpartnerinstancetotalrequest counter HELP bwpartnerinstancetotaldurationms Total Duration partner invocation mapped activity execution latency TYPE bwpartnerinstancetotaldurationms counter HELP bwceprocessstats BWCE Process Statistics list TYPE bwceprocessstats gauge HELP bwceprocesscounterlist BWCE Process related Counters list TYPE bwceprocesscounterlist gauge HELP allprocesseventscount BWCE Process Events count State TYPE allprocesseventscount counter allprocesseventscountStateNameCANCELLED 00 allprocesseventscountStateNameCOMPLETED 00 allprocesseventscountStateNameSTARTED 00 allprocesseventscountStateNameFAULTED 00 HELP processeventscount BWCE Process Events count Operation TYPE processeventscount counter HELP processdurationsecondstotal BWCE Process Events duration Operation second TYPE processdurationsecondstotal counter HELP processdurationmillisecondstotal BWCE Process Events duration Operation millisecond TYPE processdurationmillisecondstotal counter HELP bwdefinitionspartner BWCE Process Events count Operation TYPE bwdefinitionspartner counter bwdefinitionspartnerProcessNamet1moduleitemgetTransactionDataActivityNameFTLPublisherServiceNameGetCustomer360OperationNameGetDataOperationPartnerServiceTransactionServicePartnerOperationGetTransactionsOperationLocationinternalPartnerMiddlewareMW 10 bwdefinitionspartnerProcessName t1moduleitemauditProcessActivityNameKafkaSendMessageServiceNameGetCustomer360OperationNameGetDataOperationPartnerServiceAuditServicePartnerOperationAuditOperationLocationinternalPartnerMiddlewareMW 10 bwdefinitionspartnerProcessNamet1moduleitemgetCustomerDataActivityNameJMSRequestReplyServiceNameGetCustomer360OperationNameGetDataOperationPartnerServiceCustomerServicePartnerOperationGetCustomerDetailsOperationLocationinternalPartnerMiddlewareMW 10 HELP bwdefinitionsbinding BW Design Time Repository bindingtransport definition TYPE bwdefinitionsbinding counter bwdefinitionsbindingServiceNameGetCustomer360OperationNameGetDataOperationServiceInterfaceGetCustomer360GetDataOperationBindingcustomerTransportHTTP 10 HELP bwdefinitionsservice BW Design Time Repository Service definition TYPE bwdefinitionsservice counter bwdefinitionsserviceProcessNamet1modulesubitemgetCustomerDataServiceNameGetCustomer360OperationNameGetDataOperationServiceInstanceGetCustomer360GetDataOperation 10 bwdefinitionsserviceProcessNamet1modulesubitemauditProcessServiceNameGetCustomer360OperationNameGetDataOperationServiceInstanceGetCustomer360GetDataOperation 10 bwdefinitionsserviceProcessNamet1modulesuborchestratorSubFlowServiceNameGetCustomer360OperationNameGetDataOperationServiceInstanceGetCustomer360GetDataOperation 10 bwdefinitionsserviceProcessNamet1moduleProcessServiceNameGetCustomer360OperationNameGetDataOperationServiceInstanceGetCustomer360GetDataOperation 10 HELP bwdefinitionsgateway BW Design Time Repository Gateway definition TYPE bwdefinitionsgateway counter bwdefinitionsgatewayServiceNameGetCustomer360OperationNameGetDataOperationServiceInstanceGetCustomer360GetDataOperationEndpointbwcedemomonorchestratorbwceInteractionTypeISTIO 10 HELP processcpusecondstotal Total user system CPU time spent second TYPE processcpusecondstotal counter processcpusecondstotal 195686 HELP processstarttimeseconds Start time process since unix epoch second TYPE processstarttimeseconds gauge processstarttimeseconds 1604712447107E9 HELP processopenfds Number open file descriptor TYPE processopenfds gauge processopenfds 7630 HELP processmaxfds Maximum number open file descriptor TYPE processmaxfds gauge processmaxfds 10485760 HELP processvirtualmemorybytes Virtual memory size byte TYPE processvirtualmemorybytes gauge processvirtualmemorybytes 3046207488E9 HELP processresidentmemorybytes Resident memory size byte TYPE processresidentmemorybytes gauge processresidentmemorybytes 42151936E8 HELP jvmgccollectionseconds Time spent given JVM garbage collector second TYPE jvmgccollectionseconds summary jvmgccollectionsecondscountgcG1 Young Generation 5400 jvmgccollectionsecondssumgcG1 Young Generation 4754 jvmgccollectionsecondscountgcG1 Old Generation 20 jvmgccollectionsecondssumgcG1 Old Generation 0563 HELP jvmthreadscurrent Current thread count JVM TYPE jvmthreadscurrent gauge jvmthreadscurrent 980 HELP jvmthreadsdaemon Daemon thread count JVM TYPE jvmthreadsdaemon gauge jvmthreadsdaemon 430 HELP jvmthreadspeak Peak thread count JVM TYPE jvmthreadspeak gauge jvmthreadspeak 980 HELP jvmthreadsstartedtotal Started thread count JVM TYPE jvmthreadsstartedtotal counter jvmthreadsstartedtotal 1090 HELP jvmthreadsdeadlocked Cycles JVMthreads deadlock waiting acquire object monitor ownable synchronizer TYPE jvmthreadsdeadlocked gauge jvmthreadsdeadlocked 00 HELP jvmthreadsdeadlockedmonitor Cycles JVMthreads deadlock waiting acquire object monitor TYPE jvmthreadsdeadlockedmonitor gauge jvmthreadsdeadlockedmonitor 00 50 metric endpoint response part I’m using using disk space paying storing “critical exporter” one try use much information possible think many exporter much information use Ok purpose motivation post clear Discovering REST API Prometheus awesome REST API expose information wish ever use Graphical Interface Prometheus shown using REST API behind Target view Prometheus Graphical Interface documentation regarding REST API Prometheus official documentation API providing u term timeseries database TSDB Prometheus using TSDB Admin APIs specific API manage performance TSDB database order able use need enable Admin API done providing following flag launching Prometheus server webenableadminapi using Prometheus Operator Helm Chart deploy need use following item valuesyaml EnableAdminAPI enables Prometheus administrative HTTP API includes functionality deleting time series disabled default ref httpsprometheusiodocsprometheuslatestqueryingapitsdbadminapis enableAdminAPI true lot option enable enable administrative API today going focus single REST operation “stats” method related TSDB doesn’t require enable Admin API operation read Prometheus documentation return following item headStats provides following data head block TSDB numSeries number series number series chunkCount number chunk number chunk minTime current minimum timestamp millisecond current minimum timestamp millisecond maxTime current maximum timestamp millisecond seriesCountByMetricName provide list metric name series count labelValueCountByLabelName provide list label name value count memoryInBytesByLabelName provide list label name memory used byte Memory usage calculated adding length value given label name seriesCountByLabelPair provide list label value pair series count access API need hit following endpoint GET apiv1statustsdb Prometheus deployment get something similar statussuccess data seriesCountByMetricName nameapiserverrequestdurationsecondsbucket value34884 nameapiserverrequestlatenciesbucket value7344 nameetcdrequestdurationsecondsbucket value6000 nameapiserverresponsesizesbucket value3888 nameapiserverrequestlatenciessummary value2754 nameetcdrequestlatenciessummary value1500 nameapiserverrequestcount value1216 nameapiserverrequesttotal value1216 namecontainertasksstate value1140 nameapiserverrequestlatenciescount value918 labelValueCountByLabelName namename value2374 nameid value210 namemountpoint value208 namele value195 nametype value185 namename value181 nameresource value170 namesecret value168 nameimage value107 namecontainerid value97 memoryInBytesByLabelName namename value97729 nameid value21450 namemountpoint value18123 namename value13831 nameimage value8005 namecontainerid value7081 nameimageid value6872 namesecret value5054 nametype value4613 nameresource value3459 seriesCountByLabelValuePair namenamespacedefault value72064 nameservicekubernetes value70921 nameendpointhttps value70917 namejobapiserver value70917 namecomponentapiserver value57992 nameinstance192168185199443 value40343 namenameapiserverrequestdurationsecondsbucket value34884 nameversionv1 value31152 nameinstance19216811231443 value30574 namescopecluster value29713 also check information use new experimental React User Interface following endpoint newtsdbstatus Graphical Visualization top 10 series count metric name new Prometheus UI get Top 10 series label inside timeseries database case useful get rid using normal approach drop series label great one shown relevant Mmmm maybe use PromQL monitor dogfodding approach would like extract information using PromQL following query topk10 count namename Top 10 metric series generated stored time series database power hand example let’s take look 10 relevant 100 relevants filter need apply example let’s see metric regarding JVM discussed beginning following PromQL query topk100 count namenamejvm Top 100 metric series regarding JVM metric see least 150 series regarding metric using let’s even better let’s take look group job name topk10 count jobnamenameTags Software Development Technology Kubernetes Cloud Computing Programming
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Quit the Growth Hacks & Algorithm Games
You’ve seen the countless articles about gaming elusive algorithms and hacking your way to cash money millions. I plan to gouge out my eyes with an acetylene torch if I read one more hack preaching about beating the system. People, you are dealing with humans. One person’s random success on Instagram, TikTok, or Medium does not a blueprint make. Sometimes, success boils down to luck, timing, and privilege. If I were born a generation later, who knows? Maybe I would’ve been an influencer preening on Instagram. (Probably not because I don’t preen and I’m allergic to social media.) But I digress. Today, my online friend Bianca Bass wrote the article about Medium I’ve always wanted to write, but she’s done it better. You’re don’t care about the platform? Hold onto your pants, this isn’t a story about Medium. This is relevant for everyone, especially if you’re in a service-based business. Let me preface what I’m about to say with the fact that I know what it’s like to live on ramen and oatmeal for months at a time. I’m in year three of five in Chapter 13 bankruptcy, shelling out four-figure payments per month. I’m not doling out advice from my gilded throne. If your sole objective in anything is to make money, you will not make money. [Counting down 3,2,1 to the bros in the comments who will tell me otherwise. Please don’t.] One more time for the people in the cheap seats: If your sole objective in anything is to make money, you will not make money. Your work will reflect your thirst. Your obsession will make you myopic. You’ll build yourself a growth hack box, rarely jumping out in fear of not following the advice of the herd. Writing your ten vague, common sense ways to live a good life, etc. Your #1 objective should be to deliver value. Let’s get neurological for a hot minute. We’re wired to feel first, think second (fight or flight). Couple that with the fact that people consume content and read stories for selfish reasons, mirror neurons are key in understanding how people form bonds with other people, and yes, with brands. Let’s say you’re on the highway and you see a horrific four-car pileup. Part of what your brain does to process the information is to re-enact the situation from your POV so you can empathize and comprehend the severity of what you’ve just witnessed. Neural coupling occurs when an event or story activates parts in the brain that allow the listener to turn the story into their own experience. With mirroring, listeners will not only experience similar activity to each other, but also to the storyteller. Our brains are wired to empathize for, and make connections with, others and the stories they tell. Our reactions are primarily emotional until the rational, more pragmatic side of our brain kicks in, which means, stories have the power to draw people in immediately. What does this have to do with making some sweet coin? WELL, FRIEND. LET ME TELL YOU. People scan aisles and websites to determine if what they’re being sold is right for them. Is this speaking to me? Does this product or person understand me? Are they echoing back what I’m thinking, feeling, doing? Are they mirroring my wants and needs but solving them in some way? People make instantaneous decisions about who to read and what to buy based on value. Value could be in the form of utility, reciprocity, education, entertainment, or saving/making $$$. People want their needs met and problems solved. They’re busy and have a proliferation of choice and they want to make sure that you won’t waste their time. If you show up consistently at work — whether it’s in a traditional office setting or at home in your platypus pajamas — and deliver real, tangible value, the money and accolades will come. What does that mean practically? Let’s say you’re an email marketing consultant. Here are a few ways to bring value to your prospective clients: Publish “teardowns” : Val Geisler is genius at this. She takes emails from the kinds of companies she wants to attract and analyzes them in detail — the good, bad, and ugly. Offering constructive feedback on how they can improve their communication. Not only does this get the attention of a prospect, but it positions her as an industry expert. I have no doubt she’s won adjacent clients because of the teardowns she’s published online. : Val Geisler is genius at this. She takes emails from the kinds of companies she wants to attract and analyzes them in detail — the good, bad, and ugly. Offering constructive feedback on how they can improve their communication. Not only does this get the attention of a prospect, but it positions her as an industry expert. I have no doubt she’s won adjacent clients because of the teardowns she’s published online. Don’t cast vague bait : Go into your area of expertise and burrow deep. Be specific and comprehensive in writing articles and tutorials. Cite reputable research and sources. Back up the information with case studies or industry examples that illustrate your point. Broaden the scope of your work beyond you but at the same time go deep. Don’t slap up a post that took you five minutes because some guru told you to publish every day even if it’s garbage. Everything you put out into the world makes an impression. And do you want to waste someone’s time? : Go into your area of expertise and burrow deep. Be specific and comprehensive in writing articles and tutorials. Cite reputable research and sources. Back up the information with case studies or industry examples that illustrate your point. Broaden the scope of your work beyond you but at the same time go deep. Don’t slap up a post that took you five minutes because some guru told you to publish every day even if it’s garbage. Everything you put out into the world makes an impression. And do you want to waste someone’s time? Don’t gate everything behind an email sign-up, FFS : Give them true value before they sign up and keep the goods going after you have their email. Share the checklists, worksheets, and tutorials online. Let them wonder, “Hey! If I’m getting valuable content without giving you anything, what would you give me if I actually gave you my email or paid you?” It’s a question for the ages, mis compadres y comadres. : Give them true value before they sign up and keep the goods going after you have their email. Share the checklists, worksheets, and tutorials online. Let them wonder, “Hey! If I’m getting valuable content without giving you anything, what would you give me if I actually gave you my email or paid you?” It’s a question for the ages, mis compadres y comadres. Give real-life examples : I can go on about how many articles I’ve read from people who are not marketers giving marketing advice. They might have done their research, but they don’t have the track record. They haven’t endured the agita of a campaign gone wrong and what one learned as a result. You can’t teach what you haven’t done — I’ll fight you on this. Share case studies (blotting out client names and material information if you’re under NDA) and what you’ve learned from the campaigns — the good, bad, and violently ugly. This communicates to prospects that you’ve done the work before, successfully, so they’re more inclined to show up in your inbox. : I can go on about how many articles I’ve read from people who are not marketers giving marketing advice. They might have done their research, but they don’t have the track record. They haven’t endured the agita of a campaign gone wrong and what one learned as a result. You can’t teach what you haven’t done — I’ll fight you on this. Share case studies (blotting out client names and material information if you’re under NDA) and what you’ve learned from the campaigns — the good, bad, and violently ugly. This communicates to prospects that you’ve done the work before, successfully, so they’re more inclined to show up in your inbox. Make the complex simple: People want to know that you can solve problems. Every industry has its jargon, methodologies, best practices — all that jazz. Explain hard concepts simply, in a voice that’s wholly you’re own. Prospective clients won’t feel intimidated or feel the need to pull out a dictionary every time they get on the phone with you. You’ve excited them because they learned something from you, something that’s not in their area of expertise, in a way that made sense to them. If you’re a creative writer, are you improving on your craft? Or are you merely getting better at sending more people to mediocre work? Are you a ravenous reader, a student of the word? Do you study other writers and dissect their work? Many people are blinded by their ego and don’t want to admit that they have to do the work to make their work better. Sometimes, your work might not be good enough and your ego is holding you back. But sure, complain, it’s easier. You’re not entitled to readers because you’ve spent six months writing on the internet. You’re not entitled to clients simply because you exist. Stop getting high on your own supply. You have to play the long game. Put in the time and work. Consistency breeds legitimacy. Consistency breeds trust. Consistency bonds clients and readers to you. Gaming a fucking algorithm does nothing for you over the long haul. Who cares if the fast-money, shiny object-shakers are cashing in right now? Who knows where they’ll be in a year or five or ten? Don’t aim to be anyone other than yourself. People are buying and reading you — not the cheap knockoff of an industry titan. I got my MFA from Columbia (biggest regret going) and I learned this — you can teach the mechanics of plot, character, dialogue, structure, point-of-view, and all the things. You can coach a writer into finding their voice and honing their style. But you can’t teach magic. You can’t write books for them. It’s up to them to take the tools and apply them. Same with your revered “gurus” online. Take the tools, but make your own magic. Tell standout stories. Give the kind of value that puts a client’s heart on pause. But it’s hard to see past the glare in a world where people are impatient. It’s been six months and I’m not making $10,000/month! It’s been three months — where is my first million in sales? Failing to realize what they consider long is, in fact, a minute. Here’s a fact. 85% of my clients in 2019 came as a result of the articles I published on Medium. Six figures earned off the platform. Five figures earned on. I’m not saying this to brag because bragging is gauche, rather, I’m sharing this because I’ve been writing articles, comprehensive tutorials, and how-tos for three years. I’ve been on Medium since 2013. Look at me, the tortoise. Shimmying her way to the finish line. How did I build a thriving consultancy? I showed up consistently for my specific audience and delivered value. I didn’t write SEO-drenched articles that were vague photocopies of bland Inc. originals. I didn’t dangle a carrot and snatch it away if you didn’t sign up for my email list or purchase my course for the low, low price of $997. I don’t have a course. Instead, I rolled up with tutorials, case studies, detailed strategies, and tactics. I poured out my brain onto a computer screen and spoke plain English when all the kids are gasping over “synergistic innovations.” I shared methodologies and frameworks in detail. My “How to Build a Brand” series is a 250-page book spread over eight articles. Friends, I’m not playing around. People noticed, and then they hired me. This week, I’m signing a five-figure, two-month engagement with a client because the founders found my brand development articles valuable. I’m giving a two-day, four-figure brand intensive workshop for a start-up in New York because their VC, who vouched for me, was impressed with my work online. We spoke for all of 2019 — a year — before he gave me my first project. I didn’t complain about the fact that this VC didn’t move faster. That the gigs didn’t start rolling in as soon as I hit publish. I was being a farmer, playing the long game. It’s easy to whine. It’s easy to read hacks and optimize titles for search. It’s easy to copy what others have done because it’s safe and that one article went viral or that one campaign blew up like nitro on Instagram. It’s easy to focus on tactics without considering the big picture. But it’s hard to show up. It’s hard to bring your A-game consistently. It’s hard to identify who your audience is, figure out what they want, and deliver on that want in a way that knocks the little bootie socks off their feet. Quit complaining. Create.
https://medium.com/falling-into-freelancing/quit-the-growth-hacks-algorithm-games-14f28b09a8fb
['Felicia C. Sullivan']
2020-01-23 14:11:22.892000+00:00
['Marketing', 'Medium', 'Business', 'Freelancing', 'Writing']
Title Quit Growth Hacks Algorithm GamesContent You’ve seen countless article gaming elusive algorithm hacking way cash money million plan gouge eye acetylene torch read one hack preaching beating system People dealing human One person’s random success Instagram TikTok Medium blueprint make Sometimes success boil luck timing privilege born generation later know Maybe would’ve influencer preening Instagram Probably don’t preen I’m allergic social medium digress Today online friend Bianca Bass wrote article Medium I’ve always wanted write she’s done better You’re don’t care platform Hold onto pant isn’t story Medium relevant everyone especially you’re servicebased business Let preface I’m say fact know it’s like live ramen oatmeal month time I’m year three five Chapter 13 bankruptcy shelling fourfigure payment per month I’m doling advice gilded throne sole objective anything make money make money Counting 321 bros comment tell otherwise Please don’t One time people cheap seat sole objective anything make money make money work reflect thirst obsession make myopic You’ll build growth hack box rarely jumping fear following advice herd Writing ten vague common sense way live good life etc 1 objective deliver value Let’s get neurological hot minute We’re wired feel first think second fight flight Couple fact people consume content read story selfish reason mirror neuron key understanding people form bond people yes brand Let’s say you’re highway see horrific fourcar pileup Part brain process information reenact situation POV empathize comprehend severity you’ve witnessed Neural coupling occurs event story activates part brain allow listener turn story experience mirroring listener experience similar activity also storyteller brain wired empathize make connection others story tell reaction primarily emotional rational pragmatic side brain kick mean story power draw people immediately making sweet coin WELL FRIEND LET TELL People scan aisle website determine they’re sold right speaking product person understand echoing back I’m thinking feeling mirroring want need solving way People make instantaneous decision read buy based value Value could form utility reciprocity education entertainment savingmaking People want need met problem solved They’re busy proliferation choice want make sure won’t waste time show consistently work — whether it’s traditional office setting home platypus pajama — deliver real tangible value money accolade come mean practically Let’s say you’re email marketing consultant way bring value prospective client Publish “teardowns” Val Geisler genius take email kind company want attract analyzes detail — good bad ugly Offering constructive feedback improve communication get attention prospect position industry expert doubt she’s adjacent client teardowns she’s published online Val Geisler genius take email kind company want attract analyzes detail — good bad ugly Offering constructive feedback improve communication get attention prospect position industry expert doubt she’s adjacent client teardowns she’s published online Don’t cast vague bait Go area expertise burrow deep specific comprehensive writing article tutorial Cite reputable research source Back information case study industry example illustrate point Broaden scope work beyond time go deep Don’t slap post took five minute guru told publish every day even it’s garbage Everything put world make impression want waste someone’s time Go area expertise burrow deep specific comprehensive writing article tutorial Cite reputable research source Back information case study industry example illustrate point Broaden scope work beyond time go deep Don’t slap post took five minute guru told publish every day even it’s garbage Everything put world make impression want waste someone’s time Don’t gate everything behind email signup FFS Give true value sign keep good going email Share checklist worksheet tutorial online Let wonder “Hey I’m getting valuable content without giving anything would give actually gave email paid you” It’s question age mi compadres comadres Give true value sign keep good going email Share checklist worksheet tutorial online Let wonder “Hey I’m getting valuable content without giving anything would give actually gave email paid you” It’s question age mi compadres comadres Give reallife example go many article I’ve read people marketer giving marketing advice might done research don’t track record haven’t endured agita campaign gone wrong one learned result can’t teach haven’t done — I’ll fight Share case study blotting client name material information you’re NDA you’ve learned campaign — good bad violently ugly communicates prospect you’ve done work successfully they’re inclined show inbox go many article I’ve read people marketer giving marketing advice might done research don’t track record haven’t endured agita campaign gone wrong one learned result can’t teach haven’t done — I’ll fight Share case study blotting client name material information you’re NDA you’ve learned campaign — good bad violently ugly communicates prospect you’ve done work successfully they’re inclined show inbox Make complex simple People want know solve problem Every industry jargon methodology best practice — jazz Explain hard concept simply voice that’s wholly you’re Prospective client won’t feel intimidated feel need pull dictionary every time get phone You’ve excited learned something something that’s area expertise way made sense you’re creative writer improving craft merely getting better sending people mediocre work ravenous reader student word study writer dissect work Many people blinded ego don’t want admit work make work better Sometimes work might good enough ego holding back sure complain it’s easier You’re entitled reader you’ve spent six month writing internet You’re entitled client simply exist Stop getting high supply play long game Put time work Consistency breed legitimacy Consistency breed trust Consistency bond client reader Gaming fucking algorithm nothing long haul care fastmoney shiny objectshakers cashing right know they’ll year five ten Don’t aim anyone People buying reading — cheap knockoff industry titan got MFA Columbia biggest regret going learned — teach mechanic plot character dialogue structure pointofview thing coach writer finding voice honing style can’t teach magic can’t write book It’s take tool apply revered “gurus” online Take tool make magic Tell standout story Give kind value put client’s heart pause it’s hard see past glare world people impatient It’s six month I’m making 10000month It’s three month — first million sale Failing realize consider long fact minute Here’s fact 85 client 2019 came result article published Medium Six figure earned platform Five figure earned I’m saying brag bragging gauche rather I’m sharing I’ve writing article comprehensive tutorial howtos three year I’ve Medium since 2013 Look tortoise Shimmying way finish line build thriving consultancy showed consistently specific audience delivered value didn’t write SEOdrenched article vague photocopy bland Inc original didn’t dangle carrot snatch away didn’t sign email list purchase course low low price 997 don’t course Instead rolled tutorial case study detailed strategy tactic poured brain onto computer screen spoke plain English kid gasping “synergistic innovations” shared methodology framework detail “How Build Brand” series 250page book spread eight article Friends I’m playing around People noticed hired week I’m signing fivefigure twomonth engagement client founder found brand development article valuable I’m giving twoday fourfigure brand intensive workshop startup New York VC vouched impressed work online spoke 2019 — year — gave first project didn’t complain fact VC didn’t move faster gig didn’t start rolling soon hit publish farmer playing long game It’s easy whine It’s easy read hack optimize title search It’s easy copy others done it’s safe one article went viral one campaign blew like nitro Instagram It’s easy focus tactic without considering big picture it’s hard show It’s hard bring Agame consistently It’s hard identify audience figure want deliver want way knock little bootie sock foot Quit complaining CreateTags Marketing Medium Business Freelancing Writing
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How Publishing My Work Makes Me A More Powerful Writer
When I just started my writing journey, I used to be really scared to hit publish. I would sit on my articles and stories for days and when I worked up the courage to actually publish the damn thing, my heart would be racing and I would get butterflies in the pit of my stomach. I’m not a courageous person. I wish I could be a little bit braver especially when it comes to putting my work out there. But since I’ve started my writing journey, I’ve published over 150 articles. Whether you’re a seasoned writer who’s published over 1,000 or a new writer trying to will up the courage to publish your first story, there is power in hitting publish and sending your work out into the world. You gain a little more confidence each time I had very little confidence as a writer and I still do. I go through dips and peaks as a writer. But since I’ve started publishing my stories, the dips don’t last as long and I can make my way up that hill a lot faster than I used to. Even though I’m not making a full-time income (or even a part-time income) off my writing, I don’t doubt myself as a writer anymore. Publishing my stories have given me the confidence and courage I needed to keep writing. Writing takes confidence and bravery. It’s risky to put your work out there and share personal moments and thoughts with the world but in doing so, you cultivate your confidence in your ability to change the world through your writing with every published piece. It allows you to move forward in your writing journey I can write my heart out and have a hundred drafts (actually I probably do) but until I hit publish on one of my creations, I don’t feel accomplished. And until I feel like I’ve accomplished one task, I can’t move on to the next. Publishing our work allows us to move on. Having unfinished or even complete works of art sitting in our space holds us back in our creative endeavors because we keep coming back to those pieces. An unpublished story is the equivalent of unfinished business in that we can’t put it out of our minds and let it go. Hitting publish allows you to let go. You stop caring what others think If you write long enough and publish your work often enough, you will quickly learn that people are not afraid to share their opinions about you through the guise of the Internet. You will also quickly learn that the opinion of others doesn’t matter as much as you think. Most of the responses I get on my stories are very encouraging but there will always be haters and trolls who feel the need to voice their dislike for my perspective on my personal experiences or my take on the world. Unless they offer some sort of constructive criticism (which most trolls don’t), their negativity used to bother and anger me. Since I’ve started publishing my stories, my need to appease others have diminished and I’ve stopped caring (to an extent) about what people think about me or my writing. There’s true power and freedom in not caring about the opinion of others, as a writer and as a human being. Publishing forces you to give up your perfectionist tendencies Perfectionism is the killer of dreams. We often see perfectionism as a strength rather than a weakness but perfectionism is simply a mask to hide the fear and doubts we have as writers. If I waited and tried to make my stories perfect before publishing them, they would all still be sitting in my drafts folder. Our writing can never be perfect because perfection is subjective. The idea of a perfect story rests in the reader’s mind. One person’s “perfect” is another person’s “not good enough”. Publishing my stories over and over has taught me that my writing will never be perfect. And I’m okay with that. After all, I’m human and humans will never be perfect. Since I am the creator of my stories, I shouldn’t expect my writing to be perfect either. Your realize the world doesn’t end if nobody likes your work The world doesn’t end if nobody reads my work or if they read it and hate it. I am still here, writing away. We have such angst and fear over making our stories available for the world to read. We cannot guarantee that our writing will change other people’s lives but it will change our own. You become a little braver, a tiny bit more courageous and confident, more authentic. And that’s what we need in this world — something that can make us more of those things. That’s the true power of publishing.
https://medium.com/beyond-fear/how-publishing-my-work-made-me-a-more-powerful-writer-edeb72389331
['Alice Vuong']
2020-04-08 19:04:29.110000+00:00
['Creativity', 'Personal Development', 'Self', 'Inspiration', 'Writing']
Title Publishing Work Makes Powerful WriterContent started writing journey used really scared hit publish would sit article story day worked courage actually publish damn thing heart would racing would get butterfly pit stomach I’m courageous person wish could little bit braver especially come putting work since I’ve started writing journey I’ve published 150 article Whether you’re seasoned writer who’s published 1000 new writer trying courage publish first story power hitting publish sending work world gain little confidence time little confidence writer still go dip peak writer since I’ve started publishing story dip don’t last long make way hill lot faster used Even though I’m making fulltime income even parttime income writing don’t doubt writer anymore Publishing story given confidence courage needed keep writing Writing take confidence bravery It’s risky put work share personal moment thought world cultivate confidence ability change world writing every published piece allows move forward writing journey write heart hundred draft actually probably hit publish one creation don’t feel accomplished feel like I’ve accomplished one task can’t move next Publishing work allows u move unfinished even complete work art sitting space hold u back creative endeavor keep coming back piece unpublished story equivalent unfinished business can’t put mind let go Hitting publish allows let go stop caring others think write long enough publish work often enough quickly learn people afraid share opinion guise Internet also quickly learn opinion others doesn’t matter much think response get story encouraging always hater troll feel need voice dislike perspective personal experience take world Unless offer sort constructive criticism troll don’t negativity used bother anger Since I’ve started publishing story need appease others diminished I’ve stopped caring extent people think writing There’s true power freedom caring opinion others writer human Publishing force give perfectionist tendency Perfectionism killer dream often see perfectionism strength rather weakness perfectionism simply mask hide fear doubt writer waited tried make story perfect publishing would still sitting draft folder writing never perfect perfection subjective idea perfect story rest reader’s mind One person’s “perfect” another person’s “not good enough” Publishing story taught writing never perfect I’m okay I’m human human never perfect Since creator story shouldn’t expect writing perfect either realize world doesn’t end nobody like work world doesn’t end nobody read work read hate still writing away angst fear making story available world read cannot guarantee writing change people’s life change become little braver tiny bit courageous confident authentic that’s need world — something make u thing That’s true power publishingTags Creativity Personal Development Self Inspiration Writing