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900 | Paige, AI in pathology and genomics | Paige, AI in pathology and genomics
Fundamentally transforming the diagnosis and treatment of cancer
Paige has raised $25M in total. We talked with Leo Grady, its CEO.
How would you describe Paige in a single tweet?
AI in pathology and genomics will fundamentally transform the diagnosis and treatment of cancer.
How did it all start and why?
Paige was founded out of Memorial Sloan Kettering to bring technology that was developed there to doctors and patients worldwide. For over a decade, Thomas Fuchs and his colleagues have developed a new, powerful technology for pathology. This technology can improve cancer diagnostics, driving better patient care at lower cost. Paige is building clinical products from this technology and extending the technology to the development of new biomarkers for the biopharma industry.
What have you achieved so far?
TEAM: In the past year and a half, Paige has built a team with members experienced in AI, entrepreneurship, design and commercialization of clinical software.
PRODUCT: We have achieved FDA breakthrough designation for the first product we plan to launch, a testament to the impact our technology will have in this market.
CUSTOMERS: None yet, as we are working on CE and FDA regulatory clearances. We are working with several biopharma companies.
What do you plan to achieve in the next 2–3 years?
Commercialization of multiple clinical products for pathologists, as well as the development of novel biomarkers that can help speed up and better inform the diagnosis and treatment selection for patients with cancer. | https://medium.com/petacrunch/paige-ai-in-pathology-and-genomics-c669a9dfee36 | ['Kevin Hart'] | 2019-11-15 16:53:56.115000+00:00 | ['Genomics', 'Startup', 'Technology', 'Cancer', 'AI'] | Title Paige AI pathology genomicsContent Paige AI pathology genomics Fundamentally transforming diagnosis treatment cancer Paige raised 25M total talked Leo Grady CEO would describe Paige single tweet AI pathology genomics fundamentally transform diagnosis treatment cancer start Paige founded Memorial Sloan Kettering bring technology developed doctor patient worldwide decade Thomas Fuchs colleague developed new powerful technology pathology technology improve cancer diagnostics driving better patient care lower cost Paige building clinical product technology extending technology development new biomarkers biopharma industry achieved far TEAM past year half Paige built team member experienced AI entrepreneurship design commercialization clinical software PRODUCT achieved FDA breakthrough designation first product plan launch testament impact technology market CUSTOMERS None yet working CE FDA regulatory clearance working several biopharma company plan achieve next 2–3 year Commercialization multiple clinical product pathologist well development novel biomarkers help speed better inform diagnosis treatment selection patient cancerTags Genomics Startup Technology Cancer AI |
901 | Lessons Learned from Creating a Custom Graph Visualization in React | By Horst Werner and Simon Fishel
Graphs are probably the most powerful and versatile of all data structures. Graph structures are everywhere: in social media, genealogy, supply and distribution chains, financial networks, security, and business processes, to name just a few.
Visualizations of graphs, in the form of circles connected by lines, have been used for centuries (see e.g. The Great Stemma, the “Tree of Knowledge”, or any Mind Map). Computers have enabled us to automatically create such visualizations from data and layout algorithm research has been done for decades. Open source libraries such as d3.js provide generic graph visualizations that can be used and adapted with minimal effort. One could assume that by today there is a perfect layout strategy for pretty much every common use case and probably some open source library implementing it.
So open source libraries were our first stop when we set out to build Splunk Business Flow, an application that provides business operations professionals with insights into their actual end-to-end business processes and customer experiences through interactive exploration and visualization. Oftentimes, the actual (“as-is”) business processes of our customers differ from the ideal (“to-be”) processes they have defined, and surfacing such discrepancies, bottlenecks and delays creates tremendous value.
Fig. 1: Simple process graph generated with Cytoscape + Dagre layout
We evaluated vis.js, some d3.js solutions, and Cytoscape, a Canvas-based visualization library that allows you to select from multiple layout algorithms, and provides the option to implement your own. The Dagre layout algorithm appeared to be the most advanced, but the graphs it creates don’t look quite like a business process (Fig. 1). Other generic algorithms, such as the force-directed graph layout, don’t produce much better results either (Fig. 2).
Fig. 2: Force-directed layout
This is due to the fact that generic layout algorithms can’t take the meaning of a graph into account, so while they can optimize for certain geometric properties (such as keeping the edges as short as possible, or minimizing the intersection of edges), they can’t produce a visual pattern reflecting the meaning. This insight led us to the decision to write a custom layout algorithm to visualize business processes.
We use React to develop our UI; unfortunately, the graph libraries we evaluated don’t properly support the rendering paradigm of React (e.g. in Cytoscape, the graph component is a Canvas, which is updated in a way that completely bypasses React’s virtual DOM optimizations). So we also developed a new, React-based rendering module, with an abstraction layer that allows us to switch between multiple layout implementations. Here is what we learned in the process:
Map the Meaning of the Data to an Intuitive Visual Structure
In our specific case, we expect the graph to represent a process flow, which has a clear direction. We decided that a vertical downward flow would be the most intuitive representation of this direction. Of course, there are lots of branches and loops blurring that ideal straightforward structure. Therefore, one of our core challenges was making the structure of the main process visible through the noise. We started with the following rules:
Wherever the process is linear (i.e. each step has exactly one successor), that segment of the graph should appear as a strictly vertical structure in the graph.
Where processes are branching and looping, keep the most frequent process flows close to the center, to get as close as possible to a central main flow and peripheral variants.
Establish a clear sequence of steps, so that loops become visible in the form of backward-pointing edges.
Needless to say, while these rules make sense for process flows, the rules for other types of graphs will be completely different.
Fig. 3 shows two of our layout iterations using these rules. | https://medium.com/splunk-engineering/lessons-learned-from-creating-a-custom-graph-visualization-in-react-9a667ba799d1 | ['Horst Werner'] | 2019-06-10 17:33:56.473000+00:00 | ['React', 'Graph', 'Splunk', 'Visualizations', 'Engineering'] | Title Lessons Learned Creating Custom Graph Visualization ReactContent Horst Werner Simon Fishel Graphs probably powerful versatile data structure Graph structure everywhere social medium genealogy supply distribution chain financial network security business process name Visualizations graph form circle connected line used century see eg Great Stemma “Tree Knowledge” Mind Map Computers enabled u automatically create visualization data layout algorithm research done decade Open source library d3js provide generic graph visualization used adapted minimal effort One could assume today perfect layout strategy pretty much every common use case probably open source library implementing open source library first stop set build Splunk Business Flow application provides business operation professional insight actual endtoend business process customer experience interactive exploration visualization Oftentimes actual “asis” business process customer differ ideal “tobe” process defined surfacing discrepancy bottleneck delay creates tremendous value Fig 1 Simple process graph generated Cytoscape Dagre layout evaluated visjs d3js solution Cytoscape Canvasbased visualization library allows select multiple layout algorithm provides option implement Dagre layout algorithm appeared advanced graph creates don’t look quite like business process Fig 1 generic algorithm forcedirected graph layout don’t produce much better result either Fig 2 Fig 2 Forcedirected layout due fact generic layout algorithm can’t take meaning graph account optimize certain geometric property keeping edge short possible minimizing intersection edge can’t produce visual pattern reflecting meaning insight led u decision write custom layout algorithm visualize business process use React develop UI unfortunately graph library evaluated don’t properly support rendering paradigm React eg Cytoscape graph component Canvas updated way completely bypass React’s virtual DOM optimization also developed new Reactbased rendering module abstraction layer allows u switch multiple layout implementation learned process Map Meaning Data Intuitive Visual Structure specific case expect graph represent process flow clear direction decided vertical downward flow would intuitive representation direction course lot branch loop blurring ideal straightforward structure Therefore one core challenge making structure main process visible noise started following rule Wherever process linear ie step exactly one successor segment graph appear strictly vertical structure graph process branching looping keep frequent process flow close center get close possible central main flow peripheral variant Establish clear sequence step loop become visible form backwardpointing edge Needless say rule make sense process flow rule type graph completely different Fig 3 show two layout iteration using rulesTags React Graph Splunk Visualizations Engineering |
902 | Hacking software sales by rethinking team structure | Introvert. Had zero friends. Was afraid of talking to strangers. Writing code since I was 11.
Then, I started building businesses and had to sell. I knew I was fucked.
But I soon learned. And I thought, the lessons I learned might help another introvert entrepreneur somewhere in the other corner of the world struggling with selling.
By the way, I am editor of a weekly newsletter, Unmade, which delivers one startup idea to your inboxes.
If startup, ditch the sales team altogether
I’ve had the opportunity to watch several sales teams in action over the years, and as much as I hate to see people lose their jobs, startups today are probably better off doing away with the dedicated sales role — or at least in the way it currently operates at most companies.
Whether your focus is acquisition or retention, your startup would be well advised to focus on perfecting its product and optimizing marketing efforts that drive self-service sales. A great product won’t “sell itself,” but with the right hooks built in and the right lead nurture automation in place, your app can go a long way without any outbound pitching to prospects.
There’s still a place for salespeople. But especially if you’re in the early stages of your company’s life cycle, the role should be more about high-end strategic business partnerships than anything else.
A great product is half the battle won.
Considering the way buyers evaluate their software options today, exploring product specs themselves online and asking trusted contacts for recommendations, your sales process can be structured without a sales team — at least in the traditional sense. And by traditional, I am referring to a group of sharks sitting on the phone all day, trying to persuade prospects, whose reactions hover between indifferent and hostile.
Here are a few ways to streamline your sales strategy without investing in an outdated sales department.
1. Build an amazing product and develop demand
The obvious first step in any marketing effort is to have a great product to market. Before you even attempt to get the word out, you need to have a stellar product that users will pine for.
Find a consumer pain point that can be addressed through products or technology. This way, you can easily create demand for it.
And besides, having a solid product helps you increase your credibility, which makes it easier for your marketing personnel to engage the audience with confidence.
Then, once you have found this niche and launched a credible product, you will need to define your marketing strategy to establish your startup as an authority in your chosen field. This involves hiring credible and capable people who will become storytellers for the business.
If you cannot hire these credible people (because of course, you are a tiny startup), become the credible one yourself.
Remember, storytelling is different from plain old marketing campaigns. It will need people who can take customers along for the journey and evoke that feeling of affinity and satisfaction in them, so they will treat your brand as their own.
Establish a blog as a go-to place for customers not just for company updates, but also for good productivity resources. Once you start engaging the audience with insightful advice, expect them to share the material throughout their own circles. Word-of-mouth marketing needs to start somewhere.
2. Most eggs in marketing’s basket
Early-stage startups with small teams should integrate sales as part of your lean marketing efforts. Your sales leads will come from many streams but are generally divided into paid and organic (including referral traffic). However, the source of the conversion should not matter.
Don’t fall into the trap of segmenting the sales lifecycle so granularly that relationships with contacts are handled by different people at every step. That’s not how list segmentation works.
Instead, the key to success is to ensure a consistent and positive customer experience throughout the entire lifecycle. Customers don’t like being tossed around across departments, and having one point person or team to handle them will ensure they get the right guidance and attention they deserve.
Marketing and sales teams’ roles have evolved past simply getting past the customer’s front door. Instead, the marketing, sales and customer service teams are combined, with customers often talking to a single point person all throughout.
If possible, get the developers themselves on the call with the customer. (Note: Proceed with caution.)
3. Let it drip
Instead of dividing your sales strategy and the consequent sales roles into acquisition and retention, you are better off with automated email campaigns that are sent out to the right leads at the right times.
Your audience likely consists of tech-savvy urbanites who prefer to use their mobile devices for anything but talking. Your best bet to reach them is a smart, personalized email.
Build out a premium downloadable resource, gate it behind a lead capture form and promote it across as many relevant marketing channels as you can viably manage.
If you do this well, you’ll generate plenty of qualified leads to nurture via timed and triggered email sequences. In some cases, cold email can be highly effective as well.
Drip campaigns are reliable and seldom fail. If you are concerned about the lack of human element, take a look at how your competitors handle their messaging. Plenty of companies can have their cake and eat it too, because personalization and automation can co-exist.
4. Hire a product marketing manager
Given the integrated approach, you’ll need a person who will be ultimately responsible for the product, including concept, execution, marketing and sales.
It makes no sense for someone head product development, only for someone else to be responsible for actually selling it. Your marketing product manager should know the ins and outs of the product, what clicks with customers and what exactly makes your brand stand out.
Large companies are often burdened by organizational inefficiencies across product, marketing and sales departments, not to mention after-sales support teams. Each team might have a different vision or approach to the product.
By giving operational oversight over all of these activities to one person, you can be more confident that there is cohesion among people with different responsibilities.
This can be even easier for startups with small or growing teams. This person can either be your CMO or a product manager, who must first have in-depth knowledge of your product and a good understanding of the industry. For the most part, such a person will need to have both the skills of a good engineer and a capable communicator.
5. Use the best marketing technology
You might encounter a few hurdles to managing the development, marketing and sales efforts jointly. However, many of these challenges can be overcome with technology, particularly through collaboration solutions that can help break down the silos in your workflow.
Marketing automation can streamline otherwise tedious and mind-numbing tasks, including cold outreach, sifting through customer communication and feedback, analyzing conversion funnels (including clickthroughs, purchases and most popular sources of conversion), and identifying top causes of churn.
Aside from adopting technologies to ease the marketing process, you should also apply analytics to virtually everything that involves customer retention.
Make sure you actually interpret the data that you collect about customers, and then translate it all into actionable insights, so that you can adjust your marketing efforts accordingly.
Without this level of business intelligence, you’ll have no idea whether something you’re doing has a positive effect or not.
6. Simplify acquisition and retention
Make the onboarding experience as easy as possible, and make it easy for users to sign on.
For example, implementing social login can simplify the entire authentication and signup process. It also makes it easier for you to collect information about customers without requiring them to repeatedly input their own data.
The point here is to ensure that your new signups don’t meet too many roadblocks along the way, making for a good customer experience.
From here onwards, you will need to consistently monitor the customer journey, to ensure satisfaction and to optimize the experience.
After all, the profitability of SaaS platforms relies heavily on recurring revenue rather than a single point-of-sale.
By cultivating your relationship with each customer, you can be assured of that customer’s continued subscription.
Conclusion
The point in all of this is that you don’t have to beat your head against a wall by hiring an expensive sales team for something that you could accomplish with a great tech stack and a decent grasp of funnel optimization techniques. | https://medium.com/hackernoon/hacking-software-sales-by-rethinking-team-structure-3ef503d93609 | ['Mohit Mamoria'] | 2017-11-09 14:23:39.698000+00:00 | ['Inspiration', 'Marketing', 'Business', 'Ideas', 'Startup'] | Title Hacking software sale rethinking team structureContent Introvert zero friend afraid talking stranger Writing code since 11 started building business sell knew fucked soon learned thought lesson learned might help another introvert entrepreneur somewhere corner world struggling selling way editor weekly newsletter Unmade delivers one startup idea inboxes startup ditch sale team altogether I’ve opportunity watch several sale team action year much hate see people lose job startup today probably better away dedicated sale role — least way currently operates company Whether focus acquisition retention startup would well advised focus perfecting product optimizing marketing effort drive selfservice sale great product won’t “sell itself” right hook built right lead nurture automation place app go long way without outbound pitching prospect There’s still place salesperson especially you’re early stage company’s life cycle role highend strategic business partnership anything else great product half battle Considering way buyer evaluate software option today exploring product spec online asking trusted contact recommendation sale process structured without sale team — least traditional sense traditional referring group shark sitting phone day trying persuade prospect whose reaction hover indifferent hostile way streamline sale strategy without investing outdated sale department 1 Build amazing product develop demand obvious first step marketing effort great product market even attempt get word need stellar product user pine Find consumer pain point addressed product technology way easily create demand besides solid product help increase credibility make easier marketing personnel engage audience confidence found niche launched credible product need define marketing strategy establish startup authority chosen field involves hiring credible capable people become storyteller business cannot hire credible people course tiny startup become credible one Remember storytelling different plain old marketing campaign need people take customer along journey evoke feeling affinity satisfaction treat brand Establish blog goto place customer company update also good productivity resource start engaging audience insightful advice expect share material throughout circle Wordofmouth marketing need start somewhere 2 egg marketing’s basket Earlystage startup small team integrate sale part lean marketing effort sale lead come many stream generally divided paid organic including referral traffic However source conversion matter Don’t fall trap segmenting sale lifecycle granularly relationship contact handled different people every step That’s list segmentation work Instead key success ensure consistent positive customer experience throughout entire lifecycle Customers don’t like tossed around across department one point person team handle ensure get right guidance attention deserve Marketing sale teams’ role evolved past simply getting past customer’s front door Instead marketing sale customer service team combined customer often talking single point person throughout possible get developer call customer Note Proceed caution 3 Let drip Instead dividing sale strategy consequent sale role acquisition retention better automated email campaign sent right lead right time audience likely consists techsavvy urbanites prefer use mobile device anything talking best bet reach smart personalized email Build premium downloadable resource gate behind lead capture form promote across many relevant marketing channel viably manage well you’ll generate plenty qualified lead nurture via timed triggered email sequence case cold email highly effective well Drip campaign reliable seldom fail concerned lack human element take look competitor handle messaging Plenty company cake eat personalization automation coexist 4 Hire product marketing manager Given integrated approach you’ll need person ultimately responsible product including concept execution marketing sale make sense someone head product development someone else responsible actually selling marketing product manager know in out product click customer exactly make brand stand Large company often burdened organizational inefficiency across product marketing sale department mention aftersales support team team might different vision approach product giving operational oversight activity one person confident cohesion among people different responsibility even easier startup small growing team person either CMO product manager must first indepth knowledge product good understanding industry part person need skill good engineer capable communicator 5 Use best marketing technology might encounter hurdle managing development marketing sale effort jointly However many challenge overcome technology particularly collaboration solution help break silo workflow Marketing automation streamline otherwise tedious mindnumbing task including cold outreach sifting customer communication feedback analyzing conversion funnel including clickthroughs purchase popular source conversion identifying top cause churn Aside adopting technology ease marketing process also apply analytics virtually everything involves customer retention Make sure actually interpret data collect customer translate actionable insight adjust marketing effort accordingly Without level business intelligence you’ll idea whether something you’re positive effect 6 Simplify acquisition retention Make onboarding experience easy possible make easy user sign example implementing social login simplify entire authentication signup process also make easier collect information customer without requiring repeatedly input data point ensure new signups don’t meet many roadblock along way making good customer experience onwards need consistently monitor customer journey ensure satisfaction optimize experience profitability SaaS platform relies heavily recurring revenue rather single pointofsale cultivating relationship customer assured customer’s continued subscription Conclusion point don’t beat head wall hiring expensive sale team something could accomplish great tech stack decent grasp funnel optimization techniquesTags Inspiration Marketing Business Ideas Startup |
903 | Creating Waveforms Out of Spotify Tracks | One of the key features of my recent Future Islands project was pre-rendering waveforms so that we had a cool visual which would accompany audio playback. It’s a topic I haven’t thought about since I worked at SoundCloud many years ago. Since we didn’t stream the audio from Spotify on that project, I ended up extracting the waveform data using Meyda. (See the case study for more info.) However, when I finished up the project, I started to think about how I might actually be able to create waveform images from Spotify tracks. Spotify doesn’t really grant access to the full length audio files (for good reason) which would be required to extract this data. In addition, from what I can tell, their Web Playback SDK does not expose the audio in a way which you might be able to generate this in real-time using Web Audio.
I was ready to give up when I recalled that Spotify’s platform provided an Audio Analysis endpoint. This endpoint provides all sorts of interesting analysis on the track’s structure and musical content, including rhythm, pitch, and timbre. The object I was most interested in was Segments. These are sections of the track which contain roughly consistent sound. Each segment has many interesting properties, but I was most interested in three: the start point (in seconds,) the duration (in seconds,) and the max loudness (in decibels) of the segment. Using this data, I should be able to visualize the audio levels of the track. First, let’s download the data.
Calling the Endpoint
Since I’m going to be simplifying this data before I use it for visualizations, I like using Curl to download the data locally. This can be done very simply by passing the track id and a Spotify access token. You can generate a temporary access token using the Spotify Platform console. Once you do, just add --output track.json to the curl command to download the data to a file.
Now, we can simplify the data.
Preparing the Data
As I mentioned, the Audio Analysis endpoint provides all sorts of interesting data and this makes the returned data size pretty large to work with in practical applications. I downloaded Future Islands new track “Thrill” and the data amounted to 378kb. 😰 What I want to do is greatly simplify this data to only include an array of loudness levels from 0 to 1. I’ll then use this array of levels to generate a waveform using HTML5 canvas or SVG. I do this by writing a little node script.
First, we’ll include the node file system model and also our downloaded data.
const fs = require('fs')
const data = require('./track.json')
Next, we’ll create a variable for the track’s duration which is part of the data Spotify provides.
let duration = data.track.duration
Then, we’ll map the segments data to only include the start , duration , and loudness properties.
let segments = data.segments.map(segment => {
let loudness = segment.loudness_max
return {
start: segment.start / duration,
duration: segment.duration / duration,
loudness: 1 - (Math.min(Math.max(loudness, -35), 0) / -35)
}
})
If you look closely, you’ll see that I’m not mapping the properties directly as I want to create even further simplification. Instead of start or duration being a value in seconds, I want it to be a float between 0 and 1. We can get this by dividing each value by the duration we declared earlier.
Loudness is a bit more complicated because it is declared in decibels from 0 to -60. Similar to the two time properties, I want to turn this into a float from 0 to 1. In order to do this, I need to define a range of values. You might think that simply setting the range at 0 and -60 would yield a good result but how often do Spotify tracks hit those lower dB values? On Spotify’s Audio Features endpoint, they actually share a chart which shows the overall distribution of decibel data on the platform.
Using this chart, I decided to set my range between 0 and -35. Without this, the waveform would actually have a lot of dead space for all those decibels which don’t appear frequently. You can then use the Math min and max functions with a bit of division to create that 0 to 1 float we’re looking for.
Another way of deciding which range of decibels we should use is simply figuring out what the lowest and highest dB values exist on the track. Let’s actually establish those values now from our simplified segments data because they may come in handy.
let min = Math.min(...segments.map(segment => segment.loudness))
let max = Math.max(...segments.map(segment => segment.loudness))
If you look closely at the segment data, you’ll notice the reason for the start and duration properties is that the Spotify analyzer does not analyze tracks in a nice consistent manner like every second. Instead, these segments are organized into chunks of consistent sound. What we want to do is create a new array called levels and create 1000 new evenly spaced audio levels from the beginning to the end of a track.
Since we already turned both our start and duration properties into floats, we can achieve this by using a for loop to increment through 1000 values between 0 and 1. Within each loop iteration, we’ll find the segment in which the current duration iterator falls and add that loudness value to the array. However, we won’t add loudness directly and instead add one more level of simplification and divide the loudness value by the max value just in case the max value doesn’t actually reach 1. Oh, and we’ll also round the loudness value to two decimal places to. OK, enough simplification. 😅
let levels = [] for (let i = 0.000; i < 1; i += 0.001) {
let s = segments.find(segment => {
return i <= segment.start + segment.duration
}) let loudness = Math.round((s.loudness / max) * 100) / 100 levels.push(
loudness
)
}
The last thing to do is write the levels array to a JSON file so we use it for visualization. You can do this with the fs writeFile function.
fs.writeFile('levels.json', JSON.stringify(levels), (err) => {
console.log(err)
})
This is a rough solution I came to quickly and could certainly be cleaned up quite a bit. In the meantime, here’s the gist of it.
Generating the Waveform
Depending on where you plan on using your waveform, there are many ways of generating a visual of them from SVG to Canvas. Personally, I prefer generating my waveforms using Canvas so they can be both dynamic and responsive to screen sizes. Check out this CodePen which loads up our data and generates a responsive waveform. I’ll explain a bit about what’s happening.
First, I’m using axios to load the waveform data but you can use fetch if you’d like. I establish a Vue.js method called renderWaveform to do the actual rendering and make sure to call it anytime the window is resized.
let { data } = await axios.get('levels.json') this.waveform = data this.renderWaveform() window.onresize = () => this.renderWaveform()
We can finally move on to actually rendering this thing. I like to place my <canvas> element into a responsive parent div and simply resize the canvas size based on the parent’s size. Once you do that, establish the context for drawing.
let canvas = this.$refs.canvas let { height, width } = canvas.parentNode.getBoundingClientRect() canvas.width = width
canvas.height = height let context = canvas.getContext('2d')
We’ll then want to loop through each pixel of the width of our canvas and decide if and how we should be drawing a waveform line there. In this example, I’m going to draw a 4 pixel wide line every 8 pixels as I find this is aesthetically pleasing. I have also decided to mirror the waveform from a centered vertical location which is common in waveform visualization.
for (let x = 0; x < width; x++) {
if (x % 8 == 0) {
let i = Math.ceil(this.waveform.length * (x / width)) let h = Math.round(this.waveform[i] * height) / 2 context.fillRect(x, (height / 2) - h, 4, h)
context.fillRect(x, (height / 2), 4, h)
}
}
First, I check if the x value is divisible by 8. If so, we establish which value from the waveform data we should use for this line. We can define the height of this line by multiplying the selected waveform level with the height of the canvas. Since we’re mirroring the levels vertically, we’ll half this value. Finally, we’ll draw two lines using the fillRect method of HTML canvas. One which extends from the middle up and another which extends from the middle down.
Again, check out and fork this pen if you’re interested in this topic. | https://medium.com/swlh/creating-waveforms-out-of-spotify-tracks-b22030dd442b | ['Lee Martin'] | 2020-10-14 16:30:08.547000+00:00 | ['Marketing', 'Sound', 'SoundCloud', 'Programming', 'Music'] | Title Creating Waveforms Spotify TracksContent One key feature recent Future Islands project prerendering waveform cool visual would accompany audio playback It’s topic haven’t thought since worked SoundCloud many year ago Since didn’t stream audio Spotify project ended extracting waveform data using Meyda See case study info However finished project started think might actually able create waveform image Spotify track Spotify doesn’t really grant access full length audio file good reason would required extract data addition tell Web Playback SDK expose audio way might able generate realtime using Web Audio ready give recalled Spotify’s platform provided Audio Analysis endpoint endpoint provides sort interesting analysis track’s structure musical content including rhythm pitch timbre object interested Segments section track contain roughly consistent sound segment many interesting property interested three start point second duration second max loudness decibel segment Using data able visualize audio level track First let’s download data Calling Endpoint Since I’m going simplifying data use visualization like using Curl download data locally done simply passing track id Spotify access token generate temporary access token using Spotify Platform console add output trackjson curl command download data file simplify data Preparing Data mentioned Audio Analysis endpoint provides sort interesting data make returned data size pretty large work practical application downloaded Future Islands new track “Thrill” data amounted 378kb 😰 want greatly simplify data include array loudness level 0 1 I’ll use array level generate waveform using HTML5 canvas SVG writing little node script First we’ll include node file system model also downloaded data const f requirefs const data requiretrackjson Next we’ll create variable track’s duration part data Spotify provides let duration datatrackduration we’ll map segment data include start duration loudness property let segment datasegmentsmapsegment let loudness segmentloudnessmax return start segmentstart duration duration segmentduration duration loudness 1 MathminMathmaxloudness 35 0 35 look closely you’ll see I’m mapping property directly want create even simplification Instead start duration value second want float 0 1 get dividing value duration declared earlier Loudness bit complicated declared decibel 0 60 Similar two time property want turn float 0 1 order need define range value might think simply setting range 0 60 would yield good result often Spotify track hit lower dB value Spotify’s Audio Features endpoint actually share chart show overall distribution decibel data platform Using chart decided set range 0 35 Without waveform would actually lot dead space decibel don’t appear frequently use Math min max function bit division create 0 1 float we’re looking Another way deciding range decibel use simply figuring lowest highest dB value exist track Let’s actually establish value simplified segment data may come handy let min Mathminsegmentsmapsegment segmentloudness let max Mathmaxsegmentsmapsegment segmentloudness look closely segment data you’ll notice reason start duration property Spotify analyzer analyze track nice consistent manner like every second Instead segment organized chunk consistent sound want create new array called level create 1000 new evenly spaced audio level beginning end track Since already turned start duration property float achieve using loop increment 1000 value 0 1 Within loop iteration we’ll find segment current duration iterator fall add loudness value array However won’t add loudness directly instead add one level simplification divide loudness value max value case max value doesn’t actually reach 1 Oh we’ll also round loudness value two decimal place OK enough simplification 😅 let level let 0000 1 0001 let segmentsfindsegment return segmentstart segmentduration let loudness Mathroundsloudness max 100 100 levelspush loudness last thing write level array JSON file use visualization f writeFile function fswriteFilelevelsjson JSONstringifylevels err consolelogerr rough solution came quickly could certainly cleaned quite bit meantime here’s gist Generating Waveform Depending plan using waveform many way generating visual SVG Canvas Personally prefer generating waveform using Canvas dynamic responsive screen size Check CodePen load data generates responsive waveform I’ll explain bit what’s happening First I’m using axios load waveform data use fetch you’d like establish Vuejs method called renderWaveform actual rendering make sure call anytime window resized let data await axiosgetlevelsjson thiswaveform data thisrenderWaveform windowonresize thisrenderWaveform finally move actually rendering thing like place canvas element responsive parent div simply resize canvas size based parent’s size establish context drawing let canvas thisrefscanvas let height width canvasparentNodegetBoundingClientRect canvaswidth width canvasheight height let context canvasgetContext2d We’ll want loop pixel width canvas decide drawing waveform line example I’m going draw 4 pixel wide line every 8 pixel find aesthetically pleasing also decided mirror waveform centered vertical location common waveform visualization let x 0 x width x x 8 0 let Mathceilthiswaveformlength x width let h Mathroundthiswaveformi height 2 contextfillRectx height 2 h 4 h contextfillRectx height 2 4 h First check x value divisible 8 establish value waveform data use line define height line multiplying selected waveform level height canvas Since we’re mirroring level vertically we’ll half value Finally we’ll draw two line using fillRect method HTML canvas One extends middle another extends middle check fork pen you’re interested topicTags Marketing Sound SoundCloud Programming Music |
904 | Build a Natural Language Classifier With Bert and Tensorflow | The dataset is full of these duplicates, or phrase segments. We can remove these by typing:
Tokenization
We have our text data in the text column, which we now need to tokenize. We will use the BERT tokenizer, as we will be using a BERT transformer later.
Here we are first importing the transformers library and initializing a tokenizer for the bert-base-cased model used. A list of models can be found here. We then define a function tokenize that handles tokenization.
We use the encode_plus method of our BERT tokenizer to convert a sentence into input_ids and attention_mask tensors.
Xids and Xmask are our complete input_ids and attention_mask tensors respectively.
The input IDs are a list of integers that are uniquely tied to a specific word.
The attention mask is a list of 1s and 0s which correspond to the IDs in the input IDs array — BERT reads this and only applies attention to IDs that correspond to an attention mask value of 1. This allows us to avoid applying attention to padding tokens.
Our encode_plus arguments are:
Our sentence . This is simply a string representing one tweet.
. This is simply a string representing one tweet. The max_length of our encoded outputs. We use a value of 32 which means that every output tensor has a length of 32.
of our encoded outputs. We use a value of which means that every output tensor has a length of 32. We cut sequences that have a length of more than 32 tokens with truncation=True .
. For sequences that are shorter than 32 tokens, we pad them with zeros up to a length of 32 using padding='max_length' .
. BERT uses several special tokens, to mark the start/end of sequences, for padding, unknown words, and mask words. We add those using add_special_tokens=True .
. BERT also takes two inputs, the input_ids and attention_mask . We extract the attention mask with return_attention_mask=True .
and . We extract the attention mask with . By default, the tokenizer will return a token type IDs tensor — which we don’t need, so we use return_token_type_ids=False .
. Finally, we are using TensorFlow, so we return TensorFlow tensors using return_tensors='tf' . If using PyTorch, use return_tensors='pt' .
At the end of this, we return our two tensors. We initialize our two Xids and Xmask arrays beforehand and then populated them with our encoded tensors using a simple for-loop — applying tokenizer to each sentence of our dataset.
Data prep
We now need to prepare our data for training. For this, we will one-hot encode our target labels, creating a simple two-output vector for each sample where [1, 0] represents negative sentiment and [0, 1] positive.
One-hot encoding. Before (top) and after (bottom).
This whole process can take some time. I like to save the encoded arrays so that we can pick up from here if anything goes wrong or for future tests.
Now we have all of the encoded arrays, we load them into a TensorFlow dataset object. Using the dataset, we easily restructure, shuffle, and batch the data.
Train-validation split
The final step before training our model is to split our dataset into training, validation, and (optionally) test sets. We will stick with a simple 90–10 train-validation split here.
Model definition
Our data is now ready and we can define our model architecture. We will use BERT, followed by an LSTM layer, and some simple NN layers. Those final layers following BERT are our classifier.
Our classifier consumes the output hidden state tensors from BERT — using them to predict whether we’re seeing something with positive or negative sentiment.
Training
We can now train our model. First, we set up our optimizer (Adam), loss function, and accuracy metric. Then, we compile the model and train! | https://medium.com/better-programming/build-a-natural-language-classifier-with-bert-and-tensorflow-4770d4442d41 | ['James Briggs'] | 2020-12-23 15:26:40.891000+00:00 | ['Programming', 'Machine Learning', 'Python', 'Data Science', 'AI'] | Title Build Natural Language Classifier Bert TensorflowContent dataset full duplicate phrase segment remove typing Tokenization text data text column need tokenize use BERT tokenizer using BERT transformer later first importing transformer library initializing tokenizer bertbasecased model used list model found define function tokenize handle tokenization use encodeplus method BERT tokenizer convert sentence inputids attentionmask tensor Xids Xmask complete inputids attentionmask tensor respectively input IDs list integer uniquely tied specific word attention mask list 1 0 correspond IDs input IDs array — BERT read applies attention IDs correspond attention mask value 1 allows u avoid applying attention padding token encodeplus argument sentence simply string representing one tweet simply string representing one tweet maxlength encoded output use value 32 mean every output tensor length 32 encoded output use value mean every output tensor length 32 cut sequence length 32 token truncationTrue sequence shorter 32 token pad zero length 32 using paddingmaxlength BERT us several special token mark startend sequence padding unknown word mask word add using addspecialtokensTrue BERT also take two input inputids attentionmask extract attention mask returnattentionmaskTrue extract attention mask default tokenizer return token type IDs tensor — don’t need use returntokentypeidsFalse Finally using TensorFlow return TensorFlow tensor using returntensorstf using PyTorch use returntensorspt end return two tensor initialize two Xids Xmask array beforehand populated encoded tensor using simple forloop — applying tokenizer sentence dataset Data prep need prepare data training onehot encode target label creating simple twooutput vector sample 1 0 represents negative sentiment 0 1 positive Onehot encoding top bottom whole process take time like save encoded array pick anything go wrong future test encoded array load TensorFlow dataset object Using dataset easily restructure shuffle batch data Trainvalidation split final step training model split dataset training validation optionally test set stick simple 90–10 trainvalidation split Model definition data ready define model architecture use BERT followed LSTM layer simple NN layer final layer following BERT classifier classifier consumes output hidden state tensor BERT — using predict whether we’re seeing something positive negative sentiment Training train model First set optimizer Adam loss function accuracy metric compile model trainTags Programming Machine Learning Python Data Science AI |
905 | The Most Successful Marketing Campaign Has Toyed With People’s Emotions Since 1948 | Playing to the Human Condition
The human condition has remained the same for centuries. A few things that humans have always competed for, in no particular order:
Status.
Money.
Love.
This marketing strategy played perfectly to the fundamentals of our inherent and learned values. We want all the above and more.
Diamonds are now seen as a critical part of a successful and happy relationship. Men are told that the “larger and finer the diamond, the greater expression of love” (Farnam Street).
The price
How much should a diamond cost, or rather, how much is your dream girl worth to you?
About two months’ salary, or so this ad says.
And it started with an advertising campaign.
Original ad from De Beers (Source: Goodhousekeeping.com)
The ad goes on to say:
“You can’t look at Jane and tell me she’s not worth 2 months’ salary. I mean just look at her. So I wanted to get her a diamond engagement ring that said exactly that, ‘Just look.’ I’d found out that a good spending guideline today is about 2 months’ salary. That got me the biggest and best diamond I could afford, without breaking my budget. Now the only thing that other men ask her is, “When’s the wedding day?”
I mean look at her. Cutting your food bill in half until you’re able to save two months’ worth of salary is a small sacrifice compared to her hand in marriage.
Now, 63 years later, two months is still the written rule and still being followed, although I’ve heard three months is the norm now.
The competition
When I got engaged, the first thing people said to me was “Let’s see the ring.” When I respond by saying I don’t have one, their initial response is one of shock and disappointment. My cousin’s response when she saw my sister’s huge engagement ring was to yell her husband’s name.
People are curious and also competitive. Comparing ourselves to our neighbors is natural, especially when it comes to big shiny objects. When it comes to diamond rings, first comes love then comes size. | https://medium.com/better-marketing/the-most-successful-marketing-campaign-has-toyed-with-peoples-emotions-since-1948-580cde995137 | ['Alice Vuong'] | 2020-09-22 14:59:10.157000+00:00 | ['Marketing', 'Creativity', 'Life', 'Self', 'Advertising'] | Title Successful Marketing Campaign Toyed People’s Emotions Since 1948Content Playing Human Condition human condition remained century thing human always competed particular order Status Money Love marketing strategy played perfectly fundamental inherent learned value want Diamonds seen critical part successful happy relationship Men told “larger finer diamond greater expression love” Farnam Street price much diamond cost rather much dream girl worth two months’ salary ad say started advertising campaign Original ad De Beers Source Goodhousekeepingcom ad go say “You can’t look Jane tell she’s worth 2 months’ salary mean look wanted get diamond engagement ring said exactly ‘Just look’ I’d found good spending guideline today 2 months’ salary got biggest best diamond could afford without breaking budget thing men ask “When’s wedding day” mean look Cutting food bill half you’re able save two months’ worth salary small sacrifice compared hand marriage 63 year later two month still written rule still followed although I’ve heard three month norm competition got engaged first thing people said “Let’s see ring” respond saying don’t one initial response one shock disappointment cousin’s response saw sister’s huge engagement ring yell husband’s name People curious also competitive Comparing neighbor natural especially come big shiny object come diamond ring first come love come sizeTags Marketing Creativity Life Self Advertising |
906 | ART-ificial Intelligence in Gaming Part 3: Implications and Conclusion | This is part three of a miniseries, so please read parts one and two before continuing:
In the other parts of this miniseries, we talked about how GANs are used to generate new video game levels that adhere to all the rules and game physics. There are endless possibilities of how it can revolutionize modern gaming, including having more realistic graphics which can truly enhance the experience of virtual reality.
If you think about it, human intelligence is creativity. The “smartest” people you know are the ones who think outside the box; they think creatively and can make connections. Therefore, true artificial intelligence must have the capability of thinking independently and creatively.
GAN = creative?
Since GANs are used to generate completely new data that could plausibly be from the original dataset, it’s essentially “creative” AI. Let’s say we feed the model a diverse dataset of illustrations, from Picasso paintings to the digital art on TikTok and everything in between. Results would most likely be unique mixtures of the art styles — and isn’t that what we call “creative” or “original”?
Yep! Artists create their unique art styles by mimicking aspects of certain things they see. In the video game examples, the AI would mimic parts of existing levels. What other implications does creative AI have?
Benefits of Creative AI
Beyond helping game developers create more compelling video games, GANs could learn the rules of the real world much like how they learned the rules of Pac-Man. They could be used to program robots that would easily integrate into society, recognizing things such as social norms and laws through observation.
In general, having more creative — or more intelligent — AI benefits pretty much any field of interest you can think of. Some that I came up with:
more unique video game bots and terrains
more conversational or helpful chat-bots
cool, modern art and music made by AI
environment-adaptable robots
Of course, this comes with some major drawbacks :(
Drawbacks of Creative AI
The more we invest in researching how to create better AI algorithms, the more dangerous it becomes. Who knows what will happen when robots scheme to take over the world? Just kidding… Unless…?
Jokes aside, some people may be worried about creative robots stealing our jobs. But really, data privacy and security are the most pressing issues in developing AI because to have more effective algorithms, more data needs to be collected and fed into the system. This creates all sorts of problems when people don’t want their every move to be tracked and potentially be used against them.
Deepfakes are fake videos or images of people or events that seem real, created using GANs. Politicians are often victims of deepfakes because they are manipulated to appear to say something that they did not. If you’d like to learn more about deepfakes, I recommend checking out George Dvorsky’s article.
CONCLUSION
This is the end of my first miniseries and the last post for 2020! Throughout the miniseries, I talked about how AI is used in video game graphics, namely the generation of new stages or terrains. Then I went into how the AI is built (GANs), and finally concluded with implications beyond the virtual world. It’s up to you to decide if the benefits of advancing AI outweigh the drawbacks. I will be writing more about AI next year, so follow me on Medium (or don’t).
See you soon :) | https://medium.com/analytics-vidhya/art-ificial-intelligence-in-gaming-part-3-implications-and-conclusion-6282fa9240a5 | ['Danielle Trinh'] | 2020-12-21 12:27:51.758000+00:00 | ['Deep Learning', 'Machine Learning', 'Gaming', 'Artificial Intelligence', 'AI'] | Title ARTificial Intelligence Gaming Part 3 Implications ConclusionContent part three miniseries please read part one two continuing part miniseries talked GANs used generate new video game level adhere rule game physic endless possibility revolutionize modern gaming including realistic graphic truly enhance experience virtual reality think human intelligence creativity “smartest” people know one think outside box think creatively make connection Therefore true artificial intelligence must capability thinking independently creatively GAN creative Since GANs used generate completely new data could plausibly original dataset it’s essentially “creative” AI Let’s say feed model diverse dataset illustration Picasso painting digital art TikTok everything Results would likely unique mixture art style — isn’t call “creative” “original” Yep Artists create unique art style mimicking aspect certain thing see video game example AI would mimic part existing level implication creative AI Benefits Creative AI Beyond helping game developer create compelling video game GANs could learn rule real world much like learned rule PacMan could used program robot would easily integrate society recognizing thing social norm law observation general creative — intelligent — AI benefit pretty much field interest think came unique video game bot terrain conversational helpful chatbots cool modern art music made AI environmentadaptable robot course come major drawback Drawbacks Creative AI invest researching create better AI algorithm dangerous becomes know happen robot scheme take world kidding… Unless… Jokes aside people may worried creative robot stealing job really data privacy security pressing issue developing AI effective algorithm data need collected fed system creates sort problem people don’t want every move tracked potentially used Deepfakes fake video image people event seem real created using GANs Politicians often victim deepfakes manipulated appear say something you’d like learn deepfakes recommend checking George Dvorsky’s article CONCLUSION end first miniseries last post 2020 Throughout miniseries talked AI used video game graphic namely generation new stage terrain went AI built GANs finally concluded implication beyond virtual world It’s decide benefit advancing AI outweigh drawback writing AI next year follow Medium don’t See soon Tags Deep Learning Machine Learning Gaming Artificial Intelligence AI |
907 | Psychology of the Connected World | It’s true that the surrounding technologies are changing not our lives but also our behavior and attitudes. They or, rather, their creators learn not only to help us, but also to manipulate us in new ways. Our over-trust to technologies might be underneath the new notion of “post-truth” where nothing is ever provable.
The recently emerged era of the connected world has produced new concerns about our behavior and psychology in the new settings. The connectivity of the world around us is changing our lives at home and at work. It gives us more opportunities but also shapes our identities.
At Home
Privacy
Does it still exist? We leave hundreds of digital footprints everyday when we visit a webpage or pay with a credit card. In the connected world, where IoT devices will gain the ability to see and record all our moves, all of our notions of privacy will vanish. It is believed, that such constant surveillance violates the social and psychological foundation of humans, destroying our sense of privacy at every dimension.
We are told that this “ubiquitous surveillance” is emerging from our own voluntary choices because it is out choice to buy smart devices and accept cookies and privacy disclosure agreements on websites. Yet, for example, standard smartphone operating systems don’t permit you to choose safeguards to prevent being surveilled, so our choices are prompted by technology, not our free will.
How will this lack of privacy affect us in the long run? The Helsinki Privacy Experiment explored such long-term psychological consequences of surveillance at home when participants had to live with all their activities, both online and offline, tracked. At first, their responded to the constant intrusion of a camera by changing their behavior — sometimes stopping their activities entirely or hiding them. Yet, after several months, 10 out of 12 participants simply got used to it.
Privacy, it turns out, may not be so valuable after all.
Permanent connectivity
From the emergence of laptops, to the newest devices such as smart watches, the market offers a wide range of accessories that cement the idea of “always-on”. Once you had to look at your phone to stay in touch and up to date with everything, now it can be strapped around your wrist. We are so much attached to our “always-on/always-on-us” devices that we now live in two separate worlds: plugged and unplugged.
Availability
We believe that we live in a society where we expect to be able to reach everyone instantly. In this society there is no excuse not to be able to communicate at any time, because you are supposed to be constantly available. With wearable technology, it becomes even easier to do blurring of the lines between “real-life” and “virtual-life”. People stay connected to one another at any time through diverse microdata.
Digital fatigue
Constant connectivity can take a toll on physical and mental health. We can speak of addiction to smart devices, physical problems due to device-prompted positioning of our bodies, and constant stress. As a result of the blurred line between the online and offline life, many users feel the need to declare a “purge”, or a “holiday” from the connected world.
Changing habits
There exists a separate group of smart devices that are aimed at changing our habits and lifestyle, such as fitness bracelets that try to make us eat less and move more. Though giving valuable recommendations, such devices are still notoriously poor in terms of addressing the person’s motivation. When we use a smart device to have a healthier life, we should still enjoy it and not feel oppressed by the machines. Yet, some studies suggest that constant consulting with wearable devices can reduce our content with workouts.
Self-discovery
Smart devices collect all kinds of data about us to provide physical and psychological monitoring. At the same time, not all the information we get can be beneficial for us: with too much knowledge of ourselves and our vices we are forced to self-discovery which may lead to lower self-esteem and even self-rejection.
At Work
Impersonal workplace
With the IoT, teams can collaborate across very long distances saving corporate money and giving more independence and freedom to knowledge employees. Of course, many enterprises choose to reduce their office footprint in favor of “virtual teams.” At the same time, when team collaboration is mediated through software, it can be more difficult to understand the nuance behind communication and identify another’s intentions — potentially leading to disruptive misunderstandings and the sense of alienation
Really incessant work
“Always on” devices have led to an “always on” workplace, where people feel trapped to work on a 24-hour basis through their phones. Many people report discomfort when they do not check their work email at night or over the weekend. This reduces morale and makes off-time less restorative.
Working in a panopticon
The IoT provides immense capacity to track our movements throughout the workday. Potentially, this data can be useful — a good example is tracking trucks to ensure they are on time, but in practice it reduces autonomy and creates a sense of constant observation.
Greater safety and security
Especially in manufacturing and resource extraction, the Internet of Things can mitigate risks that were once believed to be intractable by integrating safety systems into a true network. Whilst the current model relies on the individual vigilance, in future workers will be able to think less actively about their safety and feel more at ease without a constant anticipation of life-threatening events. | https://medium.com/sciforce/psychology-of-the-connected-world-1c2190b0bf29 | [] | 2019-07-25 12:14:01.026000+00:00 | ['Health', 'Technology', 'Internet of Things', 'Psychology', 'Work Life Balance'] | Title Psychology Connected WorldContent It’s true surrounding technology changing life also behavior attitude rather creator learn help u also manipulate u new way overtrust technology might underneath new notion “posttruth” nothing ever provable recently emerged era connected world produced new concern behavior psychology new setting connectivity world around u changing life home work give u opportunity also shape identity Home Privacy still exist leave hundred digital footprint everyday visit webpage pay credit card connected world IoT device gain ability see record move notion privacy vanish believed constant surveillance violates social psychological foundation human destroying sense privacy every dimension told “ubiquitous surveillance” emerging voluntary choice choice buy smart device accept cooky privacy disclosure agreement website Yet example standard smartphone operating system don’t permit choose safeguard prevent surveilled choice prompted technology free lack privacy affect u long run Helsinki Privacy Experiment explored longterm psychological consequence surveillance home participant live activity online offline tracked first responded constant intrusion camera changing behavior — sometimes stopping activity entirely hiding Yet several month 10 12 participant simply got used Privacy turn may valuable Permanent connectivity emergence laptop newest device smart watch market offer wide range accessory cement idea “alwayson” look phone stay touch date everything strapped around wrist much attached “alwaysonalwaysonus” device live two separate world plugged unplugged Availability believe live society expect able reach everyone instantly society excuse able communicate time supposed constantly available wearable technology becomes even easier blurring line “reallife” “virtuallife” People stay connected one another time diverse microdata Digital fatigue Constant connectivity take toll physical mental health speak addiction smart device physical problem due deviceprompted positioning body constant stress result blurred line online offline life many user feel need declare “purge” “holiday” connected world Changing habit exists separate group smart device aimed changing habit lifestyle fitness bracelet try make u eat le move Though giving valuable recommendation device still notoriously poor term addressing person’s motivation use smart device healthier life still enjoy feel oppressed machine Yet study suggest constant consulting wearable device reduce content workout Selfdiscovery Smart device collect kind data u provide physical psychological monitoring time information get beneficial u much knowledge vice forced selfdiscovery may lead lower selfesteem even selfrejection Work Impersonal workplace IoT team collaborate across long distance saving corporate money giving independence freedom knowledge employee course many enterprise choose reduce office footprint favor “virtual teams” time team collaboration mediated software difficult understand nuance behind communication identify another’s intention — potentially leading disruptive misunderstanding sense alienation Really incessant work “Always on” device led “always on” workplace people feel trapped work 24hour basis phone Many people report discomfort check work email night weekend reduces morale make offtime le restorative Working panopticon IoT provides immense capacity track movement throughout workday Potentially data useful — good example tracking truck ensure time practice reduces autonomy creates sense constant observation Greater safety security Especially manufacturing resource extraction Internet Things mitigate risk believed intractable integrating safety system true network Whilst current model relies individual vigilance future worker able think le actively safety feel ease without constant anticipation lifethreatening eventsTags Health Technology Internet Things Psychology Work Life Balance |
908 | April Update: Product Releases Focused on Customers | As we move into the middle of the year, our focus at Quadrant continues to be on building the products our customers need to meet their business goals. Last month we released our AI Models layer, and this month we’ve continued to develop our platform so that it provides the best solutions in the industry. We are preparing the launch of our Data Quality Dashboard, another microservice layer intended to boost the capabilities and user-friendliness of the Quadrant Platform, and we are building toward additional announcements in the middle of the year. As always, our team was active in the community, speaking at events around Singapore.
Here are a few highlights:
Quadrant team active at industry events
Quadrant hosted its monthly community event, focused on luxury travel, on Thursday, 25th April 2019. Luxury travel is one of the biggest sources of revenue for the tourism industry, and some of the fastest growth is seen coming from countries in the Asia-Pacific.
Quadrant decided to study the patterns exhibited by these affluent travellers with mobile location data to uncover insights into their behaviour and preferences. The findings and insights were shared at the event by members of our team.
The event was well attended and feedback from the audience has been very positive. You can read a summary of the event here, and find the full presentation materials here.
Sneak peak: Data Quality Dashboard
Quadrant’s Data Quality Dashboard, scheduled to release next month, is the second piece of the microservices layer we launched with our AI Models. It is designed to help location data evaluators gain more insights into the data feeds prior to executing expensive evaluation job batches. The first version of the dashboard consists of data quality control metrics as follows:
Global DAU and MAU
Data Completeness
Events per Device per Day
Horizontal Accuracy
Days Seen Per Month
Hours Seen Per Day
The Data Quality Dashboard will help save data buyers time and reduce data processing costs by eliminating non-qualifying data for ingestion. It will be a big step toward eliminating bad data from business processes, and we’re proud that Quadrant is the first to offer it. Stay tuned for the official launch announcement in the coming weeks.
Major announcements coming soon
We are proud of the progress we have made thus far in 2019 and the progress we have made in less than a year. But our team is working hard to deliver even bigger achievements in the coming months. These will come on both the product and the business side, so stay tuned to our blog for the latest updates.
As always, we are grateful to our customers and the members of our community for your continued support. We have already achieved a great deal, and have strong momentum toward our longer-term organisational goals. The support of the community is an integral part of this success.
Best Regards,
The Quadrant Team | https://medium.com/quadrantprotocol/april-update-product-releases-focused-on-customers-610cc3c6810a | ['Nikos', 'Quadrant Protocol'] | 2019-05-16 10:58:38.249000+00:00 | ['Big Data', 'Blockchain', 'Cryptocurrency', 'Startup Lessons', 'AI'] | Title April Update Product Releases Focused CustomersContent move middle year focus Quadrant continues building product customer need meet business goal Last month released AI Models layer month we’ve continued develop platform provides best solution industry preparing launch Data Quality Dashboard another microservice layer intended boost capability userfriendliness Quadrant Platform building toward additional announcement middle year always team active community speaking event around Singapore highlight Quadrant team active industry event Quadrant hosted monthly community event focused luxury travel Thursday 25th April 2019 Luxury travel one biggest source revenue tourism industry fastest growth seen coming country AsiaPacific Quadrant decided study pattern exhibited affluent traveller mobile location data uncover insight behaviour preference finding insight shared event member team event well attended feedback audience positive read summary event find full presentation material Sneak peak Data Quality Dashboard Quadrant’s Data Quality Dashboard scheduled release next month second piece microservices layer launched AI Models designed help location data evaluator gain insight data feed prior executing expensive evaluation job batch first version dashboard consists data quality control metric follows Global DAU MAU Data Completeness Events per Device per Day Horizontal Accuracy Days Seen Per Month Hours Seen Per Day Data Quality Dashboard help save data buyer time reduce data processing cost eliminating nonqualifying data ingestion big step toward eliminating bad data business process we’re proud Quadrant first offer Stay tuned official launch announcement coming week Major announcement coming soon proud progress made thus far 2019 progress made le year team working hard deliver even bigger achievement coming month come product business side stay tuned blog latest update always grateful customer member community continued support already achieved great deal strong momentum toward longerterm organisational goal support community integral part success Best Regards Quadrant TeamTags Big Data Blockchain Cryptocurrency Startup Lessons AI |
909 | Apple Is Crushing Deep Links That Were Used As Ad-Tracking Devices | Apple Is Crushing Deep Links That Were Used As Ad-Tracking Devices
iOS 14’s new opt-in ad tracking feature is about to debilitate deep links and cut advertisement revenue streams
Photo by Denis Cherkashin on Unsplash
The fact that Apple has been cracking down on privacy in recent years is no mystery.
With iOS 13, the tech giant gave users more transparency about their location use.
Subsequently, with iOS 14, Apple doubled down with the new approximate location permission. This caused distress among advertisement agencies.
But, still, the loss of revenue wasn’t significant until Apple unveiled a new opt-in ad tracking feature with iOS 14.
For those who are new, iOS 14 has plans to roll out a pop-up that lets the user choose whether they’d want ads to track them across apps and websites or not. If the user decides against ad tracking, the app cannot collect the IDFA, ad identifier.
As digital agencies heavily rely on personalized to determine user trends and ultimately monetize them, this single dialog had upheaved the entire mobile advertising ecosystem during the WWDC 2020.
Unsurprisingly, Facebook cried foul play, and Apple obliged by postponing the feature to give developers and businesses time to cope up with the changes.
Now that the controversial privacy feature is finally rolling out at the start of 2021, Deep Links that were used in the app ads are about to go obsolete. | https://medium.com/big-tech/apple-is-crushing-deep-links-that-were-used-as-ad-tracking-devices-807d3b889061 | ['Anupam Chugh'] | 2020-11-26 08:45:47.894000+00:00 | ['Marketing', 'Business', 'Technology', 'Privacy', 'Apple'] | Title Apple Crushing Deep Links Used AdTracking DevicesContent Apple Crushing Deep Links Used AdTracking Devices iOS 14’s new optin ad tracking feature debilitate deep link cut advertisement revenue stream Photo Denis Cherkashin Unsplash fact Apple cracking privacy recent year mystery iOS 13 tech giant gave user transparency location use Subsequently iOS 14 Apple doubled new approximate location permission caused distress among advertisement agency still loss revenue wasn’t significant Apple unveiled new optin ad tracking feature iOS 14 new iOS 14 plan roll popup let user choose whether they’d want ad track across apps website user decides ad tracking app cannot collect IDFA ad identifier digital agency heavily rely personalized determine user trend ultimately monetize single dialog upheaved entire mobile advertising ecosystem WWDC 2020 Unsurprisingly Facebook cried foul play Apple obliged postponing feature give developer business time cope change controversial privacy feature finally rolling start 2021 Deep Links used app ad go obsoleteTags Marketing Business Technology Privacy Apple |
910 | Will Autonomous Devices Become our Benevolent Overlords? | Can we manage autonomous devices for the benefit of humanity? For the answer to be yes, we need systems that ensure autonomous smart devices will only act to enhance human quality of life.
Threats to Humanity Posed by Autonomous Machines
The fields of artificial intelligence and robotics have grown explosively over the past few decades. Computers are now able to achieve human-level performance in highly complex perceptual tasks. In the near future, robotic doctors will be able to diagnose and treat patients. Self-driving cars will communicate with nearby cars to minimize crashes.
While the robot revolution has the potential to greatly improve the human condition, it also has a dark side. With the development of autonomous robotics, human are creating machines that can interact with one another without our involvement. Some of these machines are autonomous weapon systems. How do we prevent them from undertaking actions that are harmful to humanity? Who is to be held responsible if they do undertake such actions? The fictional robotic superintelligence system in the movie The Terminator is a representation of the worst case scenario.
Is Skynet a Solution?
A new project called Skynet (ironically the same name as the robotic intelligence system in The Terminator) argues concerns over the future of autonomous machine development are warranted. The team believes the development of automated machines created today will eventually culminate in superintelligence systems with power over human affairs. The challenge is to make sure such systems function to benefit humanity. This is what Skynet intends to help do. As described in the whitepaper, it is creating “an end-to-end protocol combining a neural processing blockchain core to create the new benevolent overlord.”
In a nutshell, Skynet will link Internet of Things (IoT) devices worldwide with a connection to a blockchain network using the first blockchain chip in the world (using RISC V architecture). The plan is to embed Skynet chips in small IoT edge nodes or servers. The chips will be globally connected and communicate with each other intelligently.
Skynet protocol has two components: Skynet Open Network (SON), a scalable machine learning IoT blockchain platform and Skynet Core, a license-free neural processing blockchain core. Skynet Core provides the security and intelligence that IoT needs. SON provides the applications necessary for these cores to securely communicate and transact over. I describe both in more detail below.
What is Skynet Core?
Skynet Core will be a real-world infrastructure that blockchain tech can utilize. One of its key features is an embedded crypto wallet that lets devices such as wearables, smartphones, soft robots, connected cameras, and even self-driving cars have crypto storage capabilities. Skynet Core will give billions of these devices instant access to IoT blockchain networks. The infrastructure will use a Ledger Nano S hardware wallet, which has RSA encryption, secure memory, and CC EAL6+. With this combination, Skynet Core devices can run blockchain networks with high throughput while providing secure protection from theft.
What Is Skynet Open Network?
Skynet Core will layer over the Skynet Open Network, which will serve as a distributed “hive mind” infrastructure that will give devices the capacity to self-organize, learn, and transfer information between one another. Data and pre-trained algorithms are distributed across the network through the Core chip, and neural processing will let devices learn to respond to new situations. SON will enable IoT devices to become intelligent and autonomous. They will be able to form a self-learning economy and improve on current cloud systems and standard machine learning datasets.
The billions of Skynet Cores deployed to devices worldwide will also all include the native cryptocurrency of SON. In theory, this will allow the Skynet Open Network to become the most adopted blockchain network instantly.
What Makes Skynet a “Benevolent” Overlord?
First, SON will provide ways (via audit trails) for humans to manage their devices when they are not functioning properly. SON will also provide the ability to add permissions to the data devices share and the amount of identifiable information provided in the network (note: this doesn’t necessarily eliminate all privacy problems, as some are related to the immutability of blockchain technology itself).
Second, no centralized control is possible with blockchain technology. The collective knowledge of all devices is distributed, which means no central system can influence all the others. Devices collaborate directly without going through a controller like HPEnterprise or Microsoft Azure. They can exchange data and value in milliseconds, without Visa or Paypal. Blockchain enables autonomous machines to directly interact without a human middleman. At the same time, it ensures these devices don’t take control over human affairs and form a centralized intelligence against us.
Conclusion
Skynet is one of the most ambitious projects I have come across in a while. There is a lot of technical detail in its whitepaper that I am still parsing through, but the premise of linking blockchain technology and Internet of Things with the overarching purpose of advancing the social good is significant for me. The team behind it has the academic credentials and practical experience to know what they are talking about, both about the technology and about the urgency of paying attention to how autonomous robotics will shape our future. I am slightly terrified of the future they anticipate and hope they (and others) succeed in making sure our new overlords are benevolent.
Disclosure: I do not own SON tokens and I have not participated in the SON ICO. This article is not intended as investment advice. You should always do your own research. | https://medium.com/hackernoon/will-autonomous-devices-become-our-benevolent-overlord-14963b901c83 | ['Mina Down'] | 2018-09-03 10:48:11.494000+00:00 | ['AI', 'Artificial Intelligence', 'Blockchain', 'Robotics', 'Bitcoin'] | Title Autonomous Devices Become Benevolent OverlordsContent manage autonomous device benefit humanity answer yes need system ensure autonomous smart device act enhance human quality life Threats Humanity Posed Autonomous Machines field artificial intelligence robotics grown explosively past decade Computers able achieve humanlevel performance highly complex perceptual task near future robotic doctor able diagnose treat patient Selfdriving car communicate nearby car minimize crash robot revolution potential greatly improve human condition also dark side development autonomous robotics human creating machine interact one another without involvement machine autonomous weapon system prevent undertaking action harmful humanity held responsible undertake action fictional robotic superintelligence system movie Terminator representation worst case scenario Skynet Solution new project called Skynet ironically name robotic intelligence system Terminator argues concern future autonomous machine development warranted team belief development automated machine created today eventually culminate superintelligence system power human affair challenge make sure system function benefit humanity Skynet intends help described whitepaper creating “an endtoend protocol combining neural processing blockchain core create new benevolent overlord” nutshell Skynet link Internet Things IoT device worldwide connection blockchain network using first blockchain chip world using RISC V architecture plan embed Skynet chip small IoT edge node server chip globally connected communicate intelligently Skynet protocol two component Skynet Open Network SON scalable machine learning IoT blockchain platform Skynet Core licensefree neural processing blockchain core Skynet Core provides security intelligence IoT need SON provides application necessary core securely communicate transact describe detail Skynet Core Skynet Core realworld infrastructure blockchain tech utilize One key feature embedded crypto wallet let device wearable smartphones soft robot connected camera even selfdriving car crypto storage capability Skynet Core give billion device instant access IoT blockchain network infrastructure use Ledger Nano hardware wallet RSA encryption secure memory CC EAL6 combination Skynet Core device run blockchain network high throughput providing secure protection theft Skynet Open Network Skynet Core layer Skynet Open Network serve distributed “hive mind” infrastructure give device capacity selforganize learn transfer information one another Data pretrained algorithm distributed across network Core chip neural processing let device learn respond new situation SON enable IoT device become intelligent autonomous able form selflearning economy improve current cloud system standard machine learning datasets billion Skynet Cores deployed device worldwide also include native cryptocurrency SON theory allow Skynet Open Network become adopted blockchain network instantly Makes Skynet “Benevolent” Overlord First SON provide way via audit trail human manage device functioning properly SON also provide ability add permission data device share amount identifiable information provided network note doesn’t necessarily eliminate privacy problem related immutability blockchain technology Second centralized control possible blockchain technology collective knowledge device distributed mean central system influence others Devices collaborate directly without going controller like HPEnterprise Microsoft Azure exchange data value millisecond without Visa Paypal Blockchain enables autonomous machine directly interact without human middleman time ensures device don’t take control human affair form centralized intelligence u Conclusion Skynet one ambitious project come across lot technical detail whitepaper still parsing premise linking blockchain technology Internet Things overarching purpose advancing social good significant team behind academic credential practical experience know talking technology urgency paying attention autonomous robotics shape future slightly terrified future anticipate hope others succeed making sure new overlord benevolent Disclosure SON token participated SON ICO article intended investment advice always researchTags AI Artificial Intelligence Blockchain Robotics Bitcoin |
911 | The Shape of a Song | “The diagrams in The Shape of Song display musical form as a sequence of translucent arches. Each arch connects two repeated, identical passages of a composition. By using repeated passages as signposts, the diagram illustrates the deep structure of the composition.”
The Shape of a Song visualisiert die Musik z.B. von Aphex Twin, AC/DC, Bach, Chopin, oder Madonnas Musik mittels eines Algorithmus der auf den repetitiven Prinzip der Musik setzt.
[Via Anselm.Peischl.] | https://medium.com/fifth-music/the-shape-of-a-song-724349b51426 | ['Matthias Hacksteiner'] | 2017-01-12 17:56:28.329000+00:00 | ['Music', 'Design'] | Title Shape SongContent “The diagram Shape Song display musical form sequence translucent arch arch connects two repeated identical passage composition using repeated passage signpost diagram illustrates deep structure composition” Shape Song visualisiert die Musik zB von Aphex Twin ACDC Bach Chopin oder Madonnas Musik mittels eines Algorithmus der auf den repetitiven Prinzip der Musik setzt Via AnselmPeischlTags Music Design |
912 | Optimizing Health Equity through AI — Defying racial bias that plagues medical appointment scheduling. | Optimizing Health Equity through AI — Defying racial bias that plagues medical appointment scheduling. Dalton Chasser Follow Sep 23 · 5 min read
In almost every realm - from who gets to work from home to how families are coping with distance learning - the COVID-19 pandemic has laid bare the deep inequalities in our society. In health, the hardest hit have been traditionally marginalized people - in particular Black, Brown and Indigenous communities, where health inequities were already present. On Wednesday, September 9, scholars from Santa Clara Leavey School of Business discussed the racial health equity problems caused by algorithms - and how to solve them - in the realm of appointment booking drawing from their research and paper under review: Overbooked and Overlooked: Racial Bias in Medical Appointment Scheduling. The talk was hosted by Professor of Law, Colleen Chien, co-curator of the Artificial Intelligence for Social Impact and Equity Series currently ongoing through the High Tech Law Institute at Santa Clara. My personal interest in this topic stems from my previous work experience as a biomedical engineer and regular clinic patient. I found the authors' work here to be inspiring, and I hope you do too.
MEDICAL APPOINTMENT SCHEDULING.
All access to healthcare (or at least most) starts with an appointment. Some people get 8 A.M. appointments, and some get 4 P.M. appointments. But how does that actually work for clinics that employ schedule optimization technologies?
At some clinics, many patients do not show up for scheduled appointments. In fact, the ‘show rate’ for patients at the clinic observed in the study was only about 74%. So why do we wait so long when we go in for checkups?
A LOOK AT THE SCHEDULING PROBLEM.
The problem stems from various solutions. Providers can charge non-showing patients, but this is often unavailable for some (e.g. non-profit clinics) and still does not fix the problem. Providers could also send reminder calls and texts, but that is how we arrived at the 74% figure. The most commonly used practice relies on a ‘double-book’ approach — that is, to overbook patients in one appointment slot. This allows the provider to have a full day, optimizing the revenue of the clinic, but of course, means that sometimes we have to wait a long time.
According to Dr. Samorani, AI appointment scheduling systems work by employing two steps, (1) machine learning, and (2) schedule optimization. The first step is to predict the “show” probability of each patient. Each machine learning show prediction can be based on a variety of factors including (a) patient demographics (which could include race), (b) previous no-show data, and (c) other information (e.g. how long ago the appointment was scheduled).
After predictions are made for each patient, a schedule optimization component slots the patients based on their overall predicted no show probabilities throughout the day in an attempt to achieve a “desired result.” This is known as an objective function.
The method, used widely in clinics and the industry today, is called the Traditional Objective Function (TOF). The ‘desired result’ of the TOF is to minimize patients’ wait times while equally reducing providers’ overtime, thereby reducing costs. The TOF accomplishes this task very well. However, the TOF results in significantly longer waiting time for the patients at the highest risk of no-show, which are usually minority groups.
RACIAL BIAS IN SCHEDULING.
As it turns out, among the groups investigated, Black patients end up waiting the longest because they are predicted to have the highest no-show rate. In computational experiments based on the data from the clinic under study, Black patients ended up waiting 33% longer (on average) than non-Black patients. This is a significant problem because longer wait times exacerbate existing issues of inferior access to healthcare, poor health care quality, and worsen healthcare outcomes for certain populations. Over the past few months, the authors have worked to tackle this problem.
The authors’ research considers the issue from multiple angles. As Dr. Samorani elaborated, there are likewise two intervention points at which one can attack the problem. The first is at the machine learning point (reduce disparity) to make the show probabilities correlate less with race. The second is at the schedule optimization point (change the TOF to have a desired result of fairness).
Intervention points 1 and 2 (black arrows).
METHODS & RESULTS.
In the first method, the authors try to mitigate some of the factors that are correlated to race or otherwise remove them completely:
- But even after reducing all demographic factors correlating with race, we only get a middle-of-the-road solution — schedule quality decreases and racial disparity is still present. Dr. Samorani shares how these are the two fundamental problems with this approach.
In the second method, the authors change the TOF so that the desired result is to reduce the waiting time of the racial group expecting to wait the longest. The authors refer to this method as the “race-aware” approach:
- Using this method, the authors achieved a schedule quality equivalent to [not statistically different from] the state-of-the-art scheduling method AND nearly 0 racial disparity.
Considering this approach, the authors acknowledge how some might argue that their “race-aware” approach is inappropriate because it takes race explicitly into account. Even though they (and we) believe using race-aware policies is morally warranted, the authors have developed an alternative version of the TOF using the second method which they call “race-unaware.” In this TOF variant, the ‘desired result’ is to reduce the waiting time of the patient expecting to wait the longest:
- Using this alternative, the authors achieved a middle-of-the-road schedule quality with less racial disparity.
In summary, alternative power or weight can be given not only through machine learning or optimization to fix current problems in healthcare, but also in other areas.
MOVING FORWARD.
It is important now, more than ever, to combat these disparities and implement countermeasures to our existing systems and before our technologies are developed. The authors here highlight some concrete ways that we can approach problems in medical appointment scheduling, and we are excited to keep learning and looking for more solutions in other areas.
We are thankful for the opportunity to have spoken with some of the authors. I hope that our exploration, albeit a light one, on the topic has shed some light on a problem in healthcare not generally known, and is useful for others when thinking about the day-to-day and greater scheme of health equity.
If you would like to read more on the work here please see the under review paper here.
Other work that Santa Clara Law’s High Tech Law Institute has done can be found here. As a Santa Clara Law Student, you can find the class (The Business, Law, Technology, and Policy of Artificial Intelligence) where this blog's work was initiated here.
About the author of this post:
Dalton Chasser is a 2L focusing on Health and Intellectual Property Law at Santa Clara University School of Law. | https://medium.com/artificial-intelligence-ai-for-social-impact/optimizing-health-equity-through-ai-defying-racial-bias-that-plagues-medical-appointment-bd149069b22f | ['Dalton Chasser'] | 2020-09-23 00:35:53.275000+00:00 | ['AI', 'Artificial Intelligence', 'Health Equity', 'Scheduling', 'Healthcare'] | Title Optimizing Health Equity AI — Defying racial bias plague medical appointment schedulingContent Optimizing Health Equity AI — Defying racial bias plague medical appointment scheduling Dalton Chasser Follow Sep 23 · 5 min read almost every realm get work home family coping distance learning COVID19 pandemic laid bare deep inequality society health hardest hit traditionally marginalized people particular Black Brown Indigenous community health inequity already present Wednesday September 9 scholar Santa Clara Leavey School Business discussed racial health equity problem caused algorithm solve realm appointment booking drawing research paper review Overbooked Overlooked Racial Bias Medical Appointment Scheduling talk hosted Professor Law Colleen Chien cocurator Artificial Intelligence Social Impact Equity Series currently ongoing High Tech Law Institute Santa Clara personal interest topic stem previous work experience biomedical engineer regular clinic patient found author work inspiring hope MEDICAL APPOINTMENT SCHEDULING access healthcare least start appointment people get 8 appointment get 4 PM appointment actually work clinic employ schedule optimization technology clinic many patient show scheduled appointment fact ‘show rate’ patient clinic observed study 74 wait long go checkup LOOK SCHEDULING PROBLEM problem stem various solution Providers charge nonshowing patient often unavailable eg nonprofit clinic still fix problem Providers could also send reminder call text arrived 74 figure commonly used practice relies ‘doublebook’ approach — overbook patient one appointment slot allows provider full day optimizing revenue clinic course mean sometimes wait long time According Dr Samorani AI appointment scheduling system work employing two step 1 machine learning 2 schedule optimization first step predict “show” probability patient machine learning show prediction based variety factor including patient demographic could include race b previous noshow data c information eg long ago appointment scheduled prediction made patient schedule optimization component slot patient based overall predicted show probability throughout day attempt achieve “desired result” known objective function method used widely clinic industry today called Traditional Objective Function TOF ‘desired result’ TOF minimize patients’ wait time equally reducing providers’ overtime thereby reducing cost TOF accomplishes task well However TOF result significantly longer waiting time patient highest risk noshow usually minority group RACIAL BIAS SCHEDULING turn among group investigated Black patient end waiting longest predicted highest noshow rate computational experiment based data clinic study Black patient ended waiting 33 longer average nonBlack patient significant problem longer wait time exacerbate existing issue inferior access healthcare poor health care quality worsen healthcare outcome certain population past month author worked tackle problem authors’ research considers issue multiple angle Dr Samorani elaborated likewise two intervention point one attack problem first machine learning point reduce disparity make show probability correlate le race second schedule optimization point change TOF desired result fairness Intervention point 1 2 black arrow METHODS RESULTS first method author try mitigate factor correlated race otherwise remove completely even reducing demographic factor correlating race get middleoftheroad solution — schedule quality decrease racial disparity still present Dr Samorani share two fundamental problem approach second method author change TOF desired result reduce waiting time racial group expecting wait longest author refer method “raceaware” approach Using method author achieved schedule quality equivalent statistically different stateoftheart scheduling method nearly 0 racial disparity Considering approach author acknowledge might argue “raceaware” approach inappropriate take race explicitly account Even though believe using raceaware policy morally warranted author developed alternative version TOF using second method call “raceunaware” TOF variant ‘desired result’ reduce waiting time patient expecting wait longest Using alternative author achieved middleoftheroad schedule quality le racial disparity summary alternative power weight given machine learning optimization fix current problem healthcare also area MOVING FORWARD important ever combat disparity implement countermeasure existing system technology developed author highlight concrete way approach problem medical appointment scheduling excited keep learning looking solution area thankful opportunity spoken author hope exploration albeit light one topic shed light problem healthcare generally known useful others thinking daytoday greater scheme health equity would like read work please see review paper work Santa Clara Law’s High Tech Law Institute done found Santa Clara Law Student find class Business Law Technology Policy Artificial Intelligence blog work initiated author post Dalton Chasser 2L focusing Health Intellectual Property Law Santa Clara University School LawTags AI Artificial Intelligence Health Equity Scheduling Healthcare |
913 | What’s new in Java 15 | JDK 15 is the open-source reference implementation of version 15 of the Java SE Platform, as specified by JSR 390 in the Java Community Process.
JDK 15 reached General Availability on 15 September 2020. Production-ready binaries under the GPL are available from Oracle; binaries from other vendors will follow shortly.
The features and schedule of this release were proposed and tracked via the JEP Process, as amended by the JEP 2.0 proposal. The release was produced using the JDK Release Process (JEP 3).
Removals
Solaris and SPARC Ports
The source code and build support for the Solaris/SPARC, Solaris/x64, and Linux/SPARC ports were removed. These ports were deprecated for removal in JDK 14 with the express intent to remove them in a future release.
Nashorn Javascript Engine
The Nashorn JavaScript script engine and APIs, and the jjs tool were removed. The engine, the APIs, and the tool were deprecated for removal in Java 11 with the express intent to remove them in a future release.
Deprecations
RMI Activation
RMI Activation mechanism is deprecated. RMI Activation is an obsolete part of RMI that has been optional since Java 8. No other part of RMI will be deprecated.
What's new
Helpful NullPointerExceptions
Usability of NullPointerException has been improved. Messages generated by the JVM are describing precisely which variable was null .
Before Java 15
In Java 15
Text Blocks
A text block is a multi-line string literal that avoids the need for most escape sequences, automatically formats the string in a predictable way, and gives the developer control over the format when desired.
Before Java 15
In Java 15
JVM Improvements
ZGC Garbage Collector
The Z Garbage Collector (ZGC) is a scalable low latency garbage collector. ZGC performs all expensive work concurrently, without stopping the execution of application threads for more than 10ms, which makes it suitable for applications that require low latency and/or use a very large heap (multi-terabytes).
At a glance, ZGC is:
Concurrent
Region-based
Compacting
NUMA-aware
Using colored pointers
Using load barriers
At its core, ZGC is a concurrent garbage collector, meaning all heavy lifting work is done while Java threads continue to execute. This greatly limits the impact garbage collection will have on your application’s response time.
Beginning from a Java 15 it is a production-ready GC.
Hidden Classes
Classes that cannot be used directly by the bytecode of other classes. Hidden classes are intended for use by frameworks that generate classes at run time and use them indirectly, via reflection. A hidden class may be defined as a member of an access control nest and may be unloaded independently of other classes.
EdDSA
EdDSA is a modern elliptic curve signature scheme that has several advantages over the existing signature schemes in the JDK.
DatagramSocket API
Replacement for the underlying implementations of the java.net.DatagramSocket and java.net.MulticastSocket APIs with simpler and more modern implementations that are easy to maintain and debug. The new implementations are easy to adapt to work with virtual threads, currently being explored in Project Loom.
Preview Features
A preview feature is a new feature whose design, specification, and implementation are complete, but which is not permanent, which means that the feature may exist in a different form or not at all in future JDK releases.
Pattern Matching
Pattern matching involves testing whether an object has a particular structure, then extracting data from that object if there’s a match. You can already do this with Java; however, pattern matching introduces new language enhancements that enable you to conditionally extract data from objects with code that’s more concise and robust.
More specifically, JDK 15 extends the instanceof operator: you can specify a binding variable; if the result of the instanceof operator is true , then the object being tested is assigned to the binding variable.
Records
Introduced as a preview feature in Java SE 14, record classes help to model plain data aggregates with less ceremony than normal classes. Java SE 15 extends the preview feature with additional capabilities such as local record classes.
A record class declares a sequence of fields, and then the appropriate accessors, constructors, equals , hashCode , and toString methods are created automatically. The fields are final because the class is intended to serve as a simple "data carrier". It means that records are Immutable.
Sealed Classes
Sealed classes and interfaces restrict which other classes or interfaces may extend or implement them.
One of the primary purposes of inheritance is code reuse: When you want to create a new class and there is already a class that includes some of the code that you want, you can derive your new class from the existing class. In doing this, you can reuse the fields and methods of the existing class without having to write (and debug) them yourself.
Before Sealed Classes
With Sealed Classes
Conclusion
In this article, we have checked what was added and removed in Java 15. And how all the changes that were delivered with a Java 15 can improve your existing projects. | https://medium.com/javarevisited/whats-new-in-java-15-70335926cc42 | ['Dmytro Timchenko'] | 2020-11-21 06:19:25.188000+00:00 | ['Technology', 'Software Engineering', 'Programming', 'Software Development', 'Java'] | Title What’s new Java 15Content JDK 15 opensource reference implementation version 15 Java SE Platform specified JSR 390 Java Community Process JDK 15 reached General Availability 15 September 2020 Productionready binary GPL available Oracle binary vendor follow shortly feature schedule release proposed tracked via JEP Process amended JEP 20 proposal release produced using JDK Release Process JEP 3 Removals Solaris SPARC Ports source code build support SolarisSPARC Solarisx64 LinuxSPARC port removed port deprecated removal JDK 14 express intent remove future release Nashorn Javascript Engine Nashorn JavaScript script engine APIs jjs tool removed engine APIs tool deprecated removal Java 11 express intent remove future release Deprecations RMI Activation RMI Activation mechanism deprecated RMI Activation obsolete part RMI optional since Java 8 part RMI deprecated Whats new Helpful NullPointerExceptions Usability NullPointerException improved Messages generated JVM describing precisely variable null Java 15 Java 15 Text Blocks text block multiline string literal avoids need escape sequence automatically format string predictable way give developer control format desired Java 15 Java 15 JVM Improvements ZGC Garbage Collector Z Garbage Collector ZGC scalable low latency garbage collector ZGC performs expensive work concurrently without stopping execution application thread 10ms make suitable application require low latency andor use large heap multiterabytes glance ZGC Concurrent Regionbased Compacting NUMAaware Using colored pointer Using load barrier core ZGC concurrent garbage collector meaning heavy lifting work done Java thread continue execute greatly limit impact garbage collection application’s response time Beginning Java 15 productionready GC Hidden Classes Classes cannot used directly bytecode class Hidden class intended use framework generate class run time use indirectly via reflection hidden class may defined member access control nest may unloaded independently class EdDSA EdDSA modern elliptic curve signature scheme several advantage existing signature scheme JDK DatagramSocket API Replacement underlying implementation javanetDatagramSocket javanetMulticastSocket APIs simpler modern implementation easy maintain debug new implementation easy adapt work virtual thread currently explored Project Loom Preview Features preview feature new feature whose design specification implementation complete permanent mean feature may exist different form future JDK release Pattern Matching Pattern matching involves testing whether object particular structure extracting data object there’s match already Java however pattern matching introduces new language enhancement enable conditionally extract data object code that’s concise robust specifically JDK 15 extends instanceof operator specify binding variable result instanceof operator true object tested assigned binding variable Records Introduced preview feature Java SE 14 record class help model plain data aggregate le ceremony normal class Java SE 15 extends preview feature additional capability local record class record class declares sequence field appropriate accessors constructor equal hashCode toString method created automatically field final class intended serve simple data carrier mean record Immutable Sealed Classes Sealed class interface restrict class interface may extend implement One primary purpose inheritance code reuse want create new class already class includes code want derive new class existing class reuse field method existing class without write debug Sealed Classes Sealed Classes Conclusion article checked added removed Java 15 change delivered Java 15 improve existing projectsTags Technology Software Engineering Programming Software Development Java |
914 | This Is How Medium Writers Get Paid | This Is How Medium Writers Get Paid
Or: yes, your claps matter.
Two Sundays ago, I posted a story about how the behavior of some Medium users makes me extremely confused sometimes. The story was very well-received, and it generated a good number of comments from Medium users who admit that they are still confused about how the platform works.
The fact that so many people still don’t understand how the platform works might be a sign that Medium should work on clarifying things a bit better.
Meanwhile, I’m glad that so many have taken to the response section of my story to ask for clarification on details they’re still unsure about.
A big source of confusion is how Medium pays writers through the Partner Program. In other words, not all readers know that a writer’s payment depends on user engagement measured through claps — and only through claps.
To clarify, the number of views a story gets does not translate into payment for writers.
Responses do not translate into payment for writers.
Highlights do no translate into payment for writers.
Only claps by paying members do.
Medium takes every member’s $5 monthly membership fee and distributes it to writers according to how each member clapped throughout the month.
So, if you like the story you just read and want to reward the writer, make sure to clap at the end, otherwise no part of your membership fee will ever reach that writer.
If you’re not a paying member, your claps still matter.
Just think about it this way: claps are the approval units of Medium, it’s how we as writers measure if our writing has any impact on readers. We can’t rely on views alone, because views don’t tell us if our story resonated or not — and few people are compelled to leave a response at the end.
Another common concern of readers is if there’s a right or wrong way to clap, and the answer is that there isn’t.
You can come up with whatever clapping system you want. I find that sticking to the basics is the most helpful tactic: if you like a story, make sure to clap, however many times you want — you can clap up to 50 times for a single story.
If anyone would like a reference point, this is my personal system:
If I like the story, and haven’t found anything in the text that I fundamentally disagree with on a moral level, 5 claps.
If I think the story has above average quality, 10 claps.
If the story is particularly well-written, and if I deeply relate to it on an emotional level, 15–20 claps.
If the story blows my mind, 50 claps.
You can clap however you like, as long as you keep in mind these two things:
Clapping signifies to the writer that she’s doing a good job more than any other metric;
Claps by paying members are the only thing that guarantees the writer will get some money for that story.
Regardless of how you choose to clap, know this: your claps matter.
Happy reading. | https://medium.com/sunday-morning-talks/this-is-how-medium-writers-get-paid-83d803fddee4 | ['Tesia Blake'] | 2019-08-11 13:46:22.870000+00:00 | ['Writing', 'Self', 'Writing Tips', 'Creativity', 'Medium'] | Title Medium Writers Get PaidContent Medium Writers Get Paid yes clap matter Two Sundays ago posted story behavior Medium user make extremely confused sometimes story wellreceived generated good number comment Medium user admit still confused platform work fact many people still don’t understand platform work might sign Medium work clarifying thing bit better Meanwhile I’m glad many taken response section story ask clarification detail they’re still unsure big source confusion Medium pay writer Partner Program word reader know writer’s payment depends user engagement measured clap — clap clarify number view story get translate payment writer Responses translate payment writer Highlights translate payment writer clap paying member Medium take every member’s 5 monthly membership fee distributes writer according member clapped throughout month like story read want reward writer make sure clap end otherwise part membership fee ever reach writer you’re paying member clap still matter think way clap approval unit Medium it’s writer measure writing impact reader can’t rely view alone view don’t tell u story resonated — people compelled leave response end Another common concern reader there’s right wrong way clap answer isn’t come whatever clapping system want find sticking basic helpful tactic like story make sure clap however many time want — clap 50 time single story anyone would like reference point personal system like story haven’t found anything text fundamentally disagree moral level 5 clap think story average quality 10 clap story particularly wellwritten deeply relate emotional level 15–20 clap story blow mind 50 clap clap however like long keep mind two thing Clapping signifies writer she’s good job metric Claps paying member thing guarantee writer get money story Regardless choose clap know clap matter Happy readingTags Writing Self Writing Tips Creativity Medium |
915 | I Learned Writing Through Love Letters | Image: Author
After many long years I re-read her first letter, and remembered, as if it were my first reading, its fine musical intervention into my life, carrying its own breath, long lines, short ones, setting lost images. It was the first of many beautiful letters I received from my wife during our marriage.
There had been many such letters, just not recently, and all written with the sound of the sea close by. Waiting still, years on from that first letter, I busy myself with household chores, each year touching up the paint around the house, green and yellow, her favorite scheme, and walk out every day.
Other letters talked of places visited, Rome, Amsterdam, Ruth and Knud’s bar; words that recalled a child’s smile, given from the window of a passing bus, that left her in tears for its beauty. But the letters I loved most were those that spoke of her love for our home, the times she spent in the garden with snow on her ground, the creaks and sighs the house made during winter’s nor’easters, sitting close to the fire with the comfort of my arms around her.
She writes, …these sleepless nights, I wait for a sign, a sound, a whisper… echoing the words I have loved and known so well. I trust in your compass to find me, turning you inland to step on snow, knowing tomorrow my footprints will be gone, but never from your heart.
I place the letter down on the table, under the blue and white Anemones, and stare out the window across a shoreline shrouded in mist. Out of sight, the waves bring a mingling of her auburn hair, while tricky tides fondle her breasts. It is absurd to feel grief and let so much joy be undone. Turning from the window, collecting the letter into my hands again, I read on…
And this time, my darling man, long after the doldrums of you being away, you come home to replenish my love’s energy, make my sentences spiral like blue delphiniums, ever higher, reaching out, impervious to a bland day happening beyond this window. You are my home, I feel centered, powerful, happy in the wholeness of your love, its dignity and security captured by your light and shadow.
We were childhood sweethearts. If I could turn back a day, or a thousand, and find a single line that summed it up, it would say: all for you, everything I have made from my life and with my life: here it is — what I have done down forty years from crying over our first child in the cradle, to sobbing in the spotlight of your absence, every laugh and long sigh in between was but preparation for just now.
I earned my toys, my tinsel, and my time with her. I kiss the paper on which her words still shine.
What we had in common was a love of the written word. It seemed we also have an appreciation for the part of the world we lived in. Though we found Glasgow a little too tough, preferring Paris, arm in arm, in and out of the beautiful fashion shops.
Today, I miss going into shops. Choosing La Perla underwear from the lingerie section. I believe in that stuff. Most of my life has been lived out near the sea, which shows itself in my work more than any other subject. But I knew lingerie through loving.
I never wanted to be a man in a woman’s imagination. I am not anything more or less than I say. If there is beauty, let it not alone be responsible; for beauty is made up of two things, what you give out and what is returned.
As a writer, being taught by love letters, and not teachers, taught me that writers are always reaching out in some way. | https://medium.com/literally-literary/i-learned-writing-through-love-letters-e1f806e1b7f2 | ['Harry Hogg'] | 2019-08-14 03:15:56.548000+00:00 | ['Romance', 'Relationships', 'Creativity', 'Love', 'Writing'] | Title Learned Writing Love LettersContent Image Author many long year reread first letter remembered first reading fine musical intervention life carrying breath long line short one setting lost image first many beautiful letter received wife marriage many letter recently written sound sea close Waiting still year first letter busy household chore year touching paint around house green yellow favorite scheme walk every day letter talked place visited Rome Amsterdam Ruth Knud’s bar word recalled child’s smile given window passing bus left tear beauty letter loved spoke love home time spent garden snow ground creak sigh house made winter’s nor’easters sitting close fire comfort arm around writes …these sleepless night wait sign sound whisper… echoing word loved known well trust compass find turning inland step snow knowing tomorrow footprint gone never heart place letter table blue white Anemones stare window across shoreline shrouded mist sight wave bring mingling auburn hair tricky tide fondle breast absurd feel grief let much joy undone Turning window collecting letter hand read on… time darling man long doldrums away come home replenish love’s energy make sentence spiral like blue delphinium ever higher reaching impervious bland day happening beyond window home feel centered powerful happy wholeness love dignity security captured light shadow childhood sweetheart could turn back day thousand find single line summed would say everything made life life — done forty year cry first child cradle sobbing spotlight absence every laugh long sigh preparation earned toy tinsel time kiss paper word still shine common love written word seemed also appreciation part world lived Though found Glasgow little tough preferring Paris arm arm beautiful fashion shop Today miss going shop Choosing La Perla underwear lingerie section believe stuff life lived near sea show work subject knew lingerie loving never wanted man woman’s imagination anything le say beauty let alone responsible beauty made two thing give returned writer taught love letter teacher taught writer always reaching wayTags Romance Relationships Creativity Love Writing |
916 | Things We Don't Say When We Talk About Weight Loss | For the past few months, my body has been too heavy to measure. Well, too heavy to weigh on my home scale. It has a 400-pound weight limit.
When I first began my own writing career last spring, my weight was ranging anywhere from 340 to 375 pounds, but swinging upwards. At some point, I gave up completely and saw my weight reach 400 pounds last fall.
Obviously, that's a huge number. I know, some of you are laughing or rolling your eyes. Some of you want to vomit. Meanwhile, I have intense, conflicted emotions about all of it. About typing it out or even talking about it. Because nobody else really knows what it's like for me in my body. They can guess, assume, or argue, but both this life and this body are mine alone and not theirs.
Obesity is not simply a lack of knowledge on the part of fat folks.
Sometimes, people want to give me advice about how to lose weight. Honestly? I roll my eyes every damn time because I have a long history of triple-digit weight loss and weight gain, so I'm much more knowledgeable about nutrition than most people might think. And weight loss isn't only about knowledge, of course. But we don't often talk about that.
The truth is that I haven't been in a mindset to lose weight for a very long time. I'm talking about years of making a meal and exercise plan, but not following through on it for more than a day or two. If even.
Months ago, I wrote about going on a gastric bypass diet. I actually said I was going to eat like a gastric bypass patient, and why. But then I didn’t do it. Eight more months of my life squandered in self-loathing, occasional starving, and all-too-often binge eating. Why? It's not because I don't know how calories work, or that I have never been on a diet.
It's because we don't talk about the mental health or virtually any other health condition behind obesity. We don't talk about the loneliness, trauma, or pain.
If I wasn't the single mom of a young child, I’d have tried to put myself into an inpatient program for eating disorders because I just simply don’t know how to have a healthy relationship with food. Lock me away and teach me, please. Help cure me of my unhealthy fixations.
But within the medical community, and well, pretty much everywhere else, fatness and binge eating, or fatness and any other kind of disordered eating aren't taken as seriously “legit” eating disorders like anorexia or bulimia.
Sadly, most physicians will nonchalantly advise their obese patients right into an eating disorder — as long as it might translate into weight loss. Of course, most doctors don’t realize how much damage they are actually doing or have already done.
I have lipedema and PCOS. Two diseases which occur before obesity, but typically aren't diagnosed until after. So I know firsthand how hard it is to find physicians who don’t encourage drastic methods of weight loss for obese patients. It’s hard enough to find doctors who don’t blame your every illness on your weight. Regardless of how many other illnesses came first.
"Dieting" is... complicated.
Maybe "diet" is more of a dirty word in 2019. But the reality is that doctors do still prescribe diets to the morbidly obese, obviously. When they prescribe pills or exercise, there’s a diet. And even when they cut, staple, or bind stomachs, there's still a diet nearby. It’s the fat person's prescription for life.
And yet, everybody knows that diets don’t work, right? Even when they surgically cut and reroute our insides, weight loss surgery is simply a tool to help a person stick to a lifelong diet.
That doesn’t mean they’ll do it. That doesn’t mean the diet won’t fail.
For years, I have resisted bariatric surgery for myself, not only because it's so costly. But also because I know I have other issues at play. And I've seen patients get gastric bypass but still regain the weight. Frankly, I worry that I would be one of them.
I keep telling myself that I can figure this out without gastric bypass surgery. Not because surgery is an easy way out--but because I know it isn't. I still want to believe that I can develop a healthier relationship with food right now. If I did have the surgery, I'd still have to develop a healthier relationship with food.
But since my relationship with food has been so broken, I tend to push myself to extremes.
For a long time, I have had it in my head that I've got to go on a restrictive diet. So I keep telling myself to just eat as if I've had bariatric surgery. Like it's so simple. But I never do make it more than a day. Since becoming a mom, my ability to stick to a restrictive diet is (apparently) lost. I feel irritated trying to stick to protein shakes. And I feel guilty about things like sucralose and eating a ton of food that isn't really... food.
There are no one-size-fits-all diets.
People keep telling me about the benefits of ketogenic diets without realizing that I've done my research on them and even tried several variations for more than five years. I tried keto long before it became the biggest fad, back when it was mostly my fellow Scandinavians espousing the benefits of a low carb high fat (lchf) diet.
While I wished that keto or even low carb would work for me, the pounds kept piling up. What's been a miracle diet for some did very little for me. But it shouldn't be a revolutionary thing. There's no one-size-fits-all diet.
Even people who go on to have weight loss surgery end up doing different things with their diets. Surgeons often recommend a 900-1,000 calorie diet for life. But experts vary if that lifelong diet should be low carb, low fat, whole foods or what.
Oh well, right? Keto hasn't worked for me (despite actually sticking to it). Time to move on.
Weight loss is almost exclusively linked to failure.
I haven't had a wellness related win for a long time. With the holiday season, I mostly gave up (again) once I outgrew my scale. So I'm not sure how far beyond 400 pounds my weight has gone since my scale stops there. If I step on it while weighing more than 400 pounds, I get an error message.
And I'd been getting that error message for months.
Of course, when January came, I wanted to lose weight for the new year. It doesn't matter that it's a cliche. I'm unhappy with my weight, so I'd like to do something about it. And I kept telling myself that I just gotta to suck it up and restrict my caloric intake down to a 500 or 800 maximum. I've done it before.
Except that's the problem. I've done it before.
I have lost over 100 pounds twice in my life. I've lost count of how many times I have lost less than 50. See, weight loss has always been exclusively linked to failure for me. Because I have never lost all of the weight, and I have never loved my body. I have yet to feel comfortable in my own skin.
To be fair, I have no idea what my body could look like if I wasn't fat, because I have lipedema. That means I carry plenty of fat (particularly in my legs) that cannot be dieted or exercised away. That's not how lipedema fat works. It grows without regard to your efforts.
It's hard then, for me to consider weight loss without also feeling the failure of never being slim enough. And I suspect I'm not the only obese person to struggle with that.
I want to lose weight AND enjoy eating... right now.
Like right now. See, plenty of obese people with eating disorders gravitate toward restrictive plans to lose 20 pounds (or more) in one week because we so desperately need a win. I don't know how else to explain it.
I have been struggling with food addiction and disordered eating more than ever since my daughter was born in 2014. Like I just can't get my act together. I've been needing a win for a damn long time.
But what would happen if I gave myself permission to eat and enjoy my food rather than loathing myself for daring to do something so mundane? Can I eat happily and quit the painful binges? And lose weight?
I've written about wanting to drop the guilt before. And clearly, I've been largely unsuccessful. In case you missed it, it's pretty damn tough to build boundaries around healthy eating when you have... none.
I've read books on practically every diet (or non-diet) known to the human race, yet I still flounder when it comes to enjoying my food with healthy boundaries and no guilt.
Weight loss is painfully public.
Whatever I do when it comes to my weight, someone is going to notice. Hundreds of pounds cannot easily hide. I might as well write about it honestly, though of course, that means you'll be prithee to my failure too.
Over the past nine months, there's been a ton of failure in terms of my eating habits, body image, and weight. It doesn't help knowing that anywhere I go, people may easily judge me for my weight without ever understanding how much of a battle it is every day.
That's why I've been sitting on this story for a few days. Trying to figure out exactly what to say. Trying to figure out how to talk about a wellness win. God knows I've needed one.
Well, guess what? Strangely enough, I've got three. Three little wellness wins I'm hoping to build upon.
I haven't had a binge eating episode in a week. I've been enjoying my food... without counting calories. I can weigh myself again.
Finally, I am under my scale's weight limit of 400 pounds. I am eating mostly "healthy food," with a few "less healthy" treats here and there. And I think I'm finally in the mindset to lose weight. It's just a very different mindset, because I'm giving myself permission to eat more than 1200 calories a day. In fact, I'm not even counting calories at all now. And for a superfat girl with a long history of regain?
It's scary as hell. | https://medium.com/awkwardly-honest/things-we-dont-say-when-we-talk-about-weight-loss-f119946d4ade | ['Shannon Ashley'] | 2019-01-30 21:58:44.988000+00:00 | ['Weight Loss', 'Life Lessons', 'Life', 'Mental Health', 'Health'] | Title Things Dont Say Talk Weight LossContent past month body heavy measure Well heavy weigh home scale 400pound weight limit first began writing career last spring weight ranging anywhere 340 375 pound swinging upwards point gave completely saw weight reach 400 pound last fall Obviously thats huge number know laughing rolling eye want vomit Meanwhile intense conflicted emotion typing even talking nobody else really know like body guess assume argue life body mine alone Obesity simply lack knowledge part fat folk Sometimes people want give advice lose weight Honestly roll eye every damn time long history tripledigit weight loss weight gain Im much knowledgeable nutrition people might think weight loss isnt knowledge course dont often talk truth havent mindset lose weight long time Im talking year making meal exercise plan following day two even Months ago wrote going gastric bypass diet actually said going eat like gastric bypass patient didn’t Eight month life squandered selfloathing occasional starving alltoooften binge eating dont know calorie work never diet dont talk mental health virtually health condition behind obesity dont talk loneliness trauma pain wasnt single mom young child I’d tried put inpatient program eating disorder simply don’t know healthy relationship food Lock away teach please Help cure unhealthy fixation within medical community well pretty much everywhere else fatness binge eating fatness kind disordered eating arent taken seriously “legit” eating disorder like anorexia bulimia Sadly physician nonchalantly advise obese patient right eating disorder — long might translate weight loss course doctor don’t realize much damage actually already done lipedema PCOS Two disease occur obesity typically arent diagnosed know firsthand hard find physician don’t encourage drastic method weight loss obese patient It’s hard enough find doctor don’t blame every illness weight Regardless many illness came first Dieting complicated Maybe diet dirty word 2019 reality doctor still prescribe diet morbidly obese obviously prescribe pill exercise there’s diet even cut staple bind stomach there still diet nearby It’s fat person prescription life yet everybody know diet don’t work right Even surgically cut reroute inside weight loss surgery simply tool help person stick lifelong diet doesn’t mean they’ll doesn’t mean diet won’t fail year resisted bariatric surgery costly also know issue play Ive seen patient get gastric bypass still regain weight Frankly worry would one keep telling figure without gastric bypass surgery surgery easy way outbut know isnt still want believe develop healthier relationship food right surgery Id still develop healthier relationship food since relationship food broken tend push extreme long time head Ive got go restrictive diet keep telling eat Ive bariatric surgery Like simple never make day Since becoming mom ability stick restrictive diet apparently lost feel irritated trying stick protein shake feel guilty thing like sucralose eating ton food isnt really food onesizefitsall diet People keep telling benefit ketogenic diet without realizing Ive done research even tried several variation five year tried keto long became biggest fad back mostly fellow Scandinavians espousing benefit low carb high fat lchf diet wished keto even low carb would work pound kept piling Whats miracle diet little shouldnt revolutionary thing Theres onesizefitsall diet Even people go weight loss surgery end different thing diet Surgeons often recommend 9001000 calorie diet life expert vary lifelong diet low carb low fat whole food Oh well right Keto hasnt worked despite actually sticking Time move Weight loss almost exclusively linked failure havent wellness related win long time holiday season mostly gave outgrew scale Im sure far beyond 400 pound weight gone since scale stop step weighing 400 pound get error message Id getting error message month course January came wanted lose weight new year doesnt matter cliche Im unhappy weight Id like something kept telling gotta suck restrict caloric intake 500 800 maximum Ive done Except thats problem Ive done lost 100 pound twice life Ive lost count many time lost le 50 See weight loss always exclusively linked failure never lost weight never loved body yet feel comfortable skin fair idea body could look like wasnt fat lipedema mean carry plenty fat particularly leg cannot dieted exercised away Thats lipedema fat work grows without regard effort hard consider weight loss without also feeling failure never slim enough suspect Im obese person struggle want lose weight enjoy eating right Like right See plenty obese people eating disorder gravitate toward restrictive plan lose 20 pound one week desperately need win dont know else explain struggling food addiction disordered eating ever since daughter born 2014 Like cant get act together Ive needing win damn long time would happen gave permission eat enjoy food rather loathing daring something mundane eat happily quit painful binge lose weight Ive written wanting drop guilt clearly Ive largely unsuccessful case missed pretty damn tough build boundary around healthy eating none Ive read book practically every diet nondiet known human race yet still flounder come enjoying food healthy boundary guilt Weight loss painfully public Whatever come weight someone going notice Hundreds pound cannot easily hide might well write honestly though course mean youll prithee failure past nine month there ton failure term eating habit body image weight doesnt help knowing anywhere go people may easily judge weight without ever understanding much battle every day Thats Ive sitting story day Trying figure exactly say Trying figure talk wellness win God know Ive needed one Well guess Strangely enough Ive got three Three little wellness win Im hoping build upon havent binge eating episode week Ive enjoying food without counting calorie weigh Finally scale weight limit 400 pound eating mostly healthy food le healthy treat think Im finally mindset lose weight different mindset Im giving permission eat 1200 calorie day fact Im even counting calorie superfat girl long history regain scary hellTags Weight Loss Life Lessons Life Mental Health Health |
917 | Back to basics — company law 101 for startups | Starting a business is a risky endeavor and requires courage. It is also an opportunity. Whether this opportunity will materialize depends on how well the aspiring entrepreneur is prepared and how adaptable the startup is. Equally important is the policy and legal framework that can mitigate the risk and increase chances of success.
What legal form to operate in is one of first decision points for startups. This decision has important implications on fundamental issues such as personal liability, taxation, financing of activities, innovation. A strong companies law can help entrepreneurs navigate this process and makes starting a business more predictable. However, the companies law often falls short. Many countries are still missing the basics, including the context needed to form an entity that will give the entrepreneur proper legal protection.
Without a strong companies’ law, navigating company legislation is not straightforward. As a consequence, entrepreneurs face significant uncertainty and do not have the basic elements to decide which legal form is appropriate for their needs.
Some common issues we observe are:
Excessive and discretionary government controls of business entry and business activities .
Uncertainty as to how long and when an entrepreneur can enjoy limited liability.
Corporate governance provisions that are too complex and costly for small companies but insufficient for public shareholding companies. Simple company forms such as LLC’s are required to have complex governance structures such as general meetings, board of directors, company secretaries. On the other hand, public shareholding companies are not required to comply with good corporate governance principles such as disclosure, division of power between executive and non-executive board members.
Insufficient or missing provisions on the relationship between the company and its stakeholders and shareholders.
This influences the entrepreneur’s decisions and can significantly impair the ability of a startup to operate grow, innovate, recruit and retain talent. In short, without a proper company law framework that governs the formation, operation and corporate governance of companies in a country, there can be no entrepreneurship.
The World Bank group is currently working with many client countries to put in place a sound company law framework. Amendments to the Companies Law in Egypt introduced for the first time the possibility to have a single member limited liability company. A comprehensive review of the Companies Act in Zambia improved disclosure and protection of minority shareholders and reduced discretionary powers in business entry and operation.
From a development perspective, the private sector can indeed play a much bigger role in filling the $2.5 trillion gap required annually to meet the sustainable development goals. But in order to encourage the investment necessary, a lot has to change in terms of the business environment. A sound framework for company laws can go a long way towards facilitating entrepreneurship.
Read more World Bank blogs. | https://medium.com/world-of-opportunity/back-to-basics-company-law-101-for-startups-322aa4e048f8 | ['World Bank'] | 2018-12-04 17:28:08.993000+00:00 | ['Startup', 'Entrepreneurship', 'Business', 'Innovation'] | Title Back basic — company law 101 startupsContent Starting business risky endeavor requires courage also opportunity Whether opportunity materialize depends well aspiring entrepreneur prepared adaptable startup Equally important policy legal framework mitigate risk increase chance success legal form operate one first decision point startup decision important implication fundamental issue personal liability taxation financing activity innovation strong company law help entrepreneur navigate process make starting business predictable However company law often fall short Many country still missing basic including context needed form entity give entrepreneur proper legal protection Without strong companies’ law navigating company legislation straightforward consequence entrepreneur face significant uncertainty basic element decide legal form appropriate need common issue observe Excessive discretionary government control business entry business activity Uncertainty long entrepreneur enjoy limited liability Corporate governance provision complex costly small company insufficient public shareholding company Simple company form LLC’s required complex governance structure general meeting board director company secretary hand public shareholding company required comply good corporate governance principle disclosure division power executive nonexecutive board member Insufficient missing provision relationship company stakeholder shareholder influence entrepreneur’s decision significantly impair ability startup operate grow innovate recruit retain talent short without proper company law framework governs formation operation corporate governance company country entrepreneurship World Bank group currently working many client country put place sound company law framework Amendments Companies Law Egypt introduced first time possibility single member limited liability company comprehensive review Companies Act Zambia improved disclosure protection minority shareholder reduced discretionary power business entry operation development perspective private sector indeed play much bigger role filling 25 trillion gap required annually meet sustainable development goal order encourage investment necessary lot change term business environment sound framework company law go long way towards facilitating entrepreneurship Read World Bank blogsTags Startup Entrepreneurship Business Innovation |
918 | Make Your Snapshots Into Lead Story Photos With This Quickstart Guide | Composition
One of the most important aspects when shooting photos is composition. Amateurs have a tendency to frame an object dead center and not care about the surroundings. We find it esthetically pleasing when we use the golden ratio.
I’m not saying you should never center a subject, but you have to do it because it is an active choice.
The golden ratio
In short, the golden ratio is: math, math, oh my goodness, nature is crazy, math → 0.618. This means that if you place your subject 62% to the left or right in the frame, it will look more pleasing to the eye.
If you enjoy reading about the wonders of our nature, I suggest you read more about the golden ratio here (Wikipedia).
I did an experiment when teaching composition in 3d many moons ago and I asked the students to draw a line.
Then I asked them to add another line where it felt right. 80–90% of the students added that line smack in the golden ratio.
If you don’t consider this while shooting, have it in the back of your head when you edit the photo.
How would this shot look if the church tower was in the middle of the frame?
Tip: If you found this topic interesting, you can bump it up a notch by researching Fibonacci’s Ratio.
The “Rule of thirds”
Another well-known rule (which is meant to be broken as any other rule) is the rule of thirds. On most pocket cameras or phones, you can turn this grid on and get an overlay in your viewfinder.
The rule of thirds represented with vertical- and horizontal lines. Notice where they intersect as well. Graphics by author
The iPhone rule of third grids turned on. A nice, non-intrusive overlay. Screenshot by author
If you place your subject in the cross-section or along with one of these lines, the photo will subconsciously be more pleasant to look at. You can use several of them at the same time.
Try placing your human subject in the bottom left point while placing the distant mountain in the top right point. It will look good, I promise
Focus and depth of field
Focus is simply about what subject in the photo you give attention to. You can think about focus in two ways — what you are aiming at and how blurred out the rest of the image is. This is called depth of field, or DOF for short.
You have probably seen photos where the subject is crystal clear but the background is blurred out. You have also probably seen photos where the foreground is blurred out and the mid- or background is clear. You can use DOF to frame the action of your photo.
Focus on the book. Blurred out background. Photo by author
Subject and landscape all in focus. Photo by author
A high aperture (for example f1.8) will blur out the background. A low aperture (for example f16) will keep more of the image in focus. More about that in the technical part of this story.
Lighting
Without lighting, you have no photo. It is all about how you let light into the camera.
There is a lot of nice natural light out there. You don’t have to buy light equipment unless you want to experiment.
Remember that backlit tends to darken the subject, so unless it is a style you are going for, you might want to avoid that.
Don’t have the light hit your subject from the front. Have it hit a bit on the side. This way you will shape the subject instead of flooding it. If you need some bounce light from the other side, you can set up a reflector. This can be a piece of styrofoam.
Light from the side, additional help from the other side if needed. Graphics by author
When the sun is low you can get some amazing colors. When you have figured out what you want to shoot, you can do it in the early morning or night for the warm, golden feel.
Dawn over Oslo. Photo by author
Color
You might not be used to care about color. If you take a photo of a subject, it is easy to forget about the total feeling of the photo. You might find yourself focusing too much on the subject and not the colors in the photo.
Colors, like teal and orange, complement each other. This means that they go well together. All colors have complimentary colors and there are many websites out there that will help you find the right colors for you.
Screenshot from colors.adobe.com by author
If you have the main color established, maybe you can find another color to help the photo shine.
Here are a few resources:
There are tons of resources on color, so browse around until you find the one you like best.
It’s not just about finding matching colors. It’s also about making photos pop with strong saturated colors.
Without the yellow wall, this shot would not have popped as much. Photo by author
Make it interesting
How many times have you seen people take photos of their kids from above? Get down to their level and the photo will look better.
What is your subject and why is it interesting? If it’s not interesting to begin with, make the whole setting interesting.
A classic mistake is to shoot the main photos to reveal all the relevant information to the viewer. This makes sense. You’re trying to show the viewer everything you can. It is the most boring way to shoot a photo though.
Consider the following presentation:
Lots of info. So boring that I want to hide under the carpet in disgust. Photo by author
Absolutely not… Maybe you need this view in your article or in a graphical presentation. Do that, but as your header, you want to be more creative.
This shot does not give the user all the info — only a taste. It is clearly about travel and is probably part of user research.
Which would you click?
A much more interesting view. Photo by author
Here are a few similar examples. | https://medium.com/curious/make-your-snapshots-into-lead-story-photos-with-this-quickstart-guide-884860d4bf31 | ['Martin Andersson Aaberge'] | 2020-10-27 15:36:18.364000+00:00 | ['Marketing', 'Branding', 'Writing Tips', 'Creativity', 'Photography'] | Title Make Snapshots Lead Story Photos Quickstart GuideContent Composition One important aspect shooting photo composition Amateurs tendency frame object dead center care surroundings find esthetically pleasing use golden ratio I’m saying never center subject active choice golden ratio short golden ratio math math oh goodness nature crazy math → 0618 mean place subject 62 left right frame look pleasing eye enjoy reading wonder nature suggest read golden ratio Wikipedia experiment teaching composition 3d many moon ago asked student draw line asked add another line felt right 80–90 student added line smack golden ratio don’t consider shooting back head edit photo would shot look church tower middle frame Tip found topic interesting bump notch researching Fibonacci’s Ratio “Rule thirds” Another wellknown rule meant broken rule rule third pocket camera phone turn grid get overlay viewfinder rule third represented vertical horizontal line Notice intersect well Graphics author iPhone rule third grid turned nice nonintrusive overlay Screenshot author place subject crosssection along one line photo subconsciously pleasant look use several time Try placing human subject bottom left point placing distant mountain top right point look good promise Focus depth field Focus simply subject photo give attention think focus two way — aiming blurred rest image called depth field DOF short probably seen photo subject crystal clear background blurred also probably seen photo foreground blurred mid background clear use DOF frame action photo Focus book Blurred background Photo author Subject landscape focus Photo author high aperture example f18 blur background low aperture example f16 keep image focus technical part story Lighting Without lighting photo let light camera lot nice natural light don’t buy light equipment unless want experiment Remember backlit tends darken subject unless style going might want avoid Don’t light hit subject front hit bit side way shape subject instead flooding need bounce light side set reflector piece styrofoam Light side additional help side needed Graphics author sun low get amazing color figured want shoot early morning night warm golden feel Dawn Oslo Photo author Color might used care color take photo subject easy forget total feeling photo might find focusing much subject color photo Colors like teal orange complement mean go well together color complimentary color many website help find right color Screenshot colorsadobecom author main color established maybe find another color help photo shine resource ton resource color browse around find one like best It’s finding matching color It’s also making photo pop strong saturated color Without yellow wall shot would popped much Photo author Make interesting many time seen people take photo kid Get level photo look better subject interesting it’s interesting begin make whole setting interesting classic mistake shoot main photo reveal relevant information viewer make sense You’re trying show viewer everything boring way shoot photo though Consider following presentation Lots info boring want hide carpet disgust Photo author Absolutely not… Maybe need view article graphical presentation header want creative shot give user info — taste clearly travel probably part user research would click much interesting view Photo author similar examplesTags Marketing Branding Writing Tips Creativity Photography |
919 | Oh, The Places You’ll Go Once You Set Up Your Patient Portal! | Oh, The Places You’ll Go Once You Set Up Your Patient Portal!
A Seussian journey through the medical-industrial complex.
Image by brgfx on Freepik
Congratulations!
Today is your day.
Convenient access to personal health records
Is just a one-star app away.
You have brains in your head.
You have teeth in your mouth.
Set up automatic refills
Before your insulin runs out!
Schedule an X-ray, CT scan, ultrasound, or MRI —
Here’s a confirmation code to log into our site.
Lost it already?
We can’t say we’re shocked.
Our fifteen-factor verification
Should get it unlocked.
Now the portal is active!
Strap in for the ride
As the time-space continuum tears open wide…
OH! THE PLACES YOU’LL GO!
You’ll scream, “Please God, no!
I knew I should have ignored
That green stuff on my toe!
I should have solved it with crystals!
Natural oils! Meditation!
Is that…could it be…
A missed payment notification?”
We’re sorry to say so,
But sadly, it’s true.
You owe us a lot
For the crusty green goo.
Sure, all we did was prescribe you a cream
That over the counter is $8.98
When its name-brand equal, mysteriously,
Costs ten times the amount
That it cost them to make.
But just play along! Don’t worry! Don’t let
Those Big Pharma profit margins get you upset.
What’s the harm in a little more credit card debt?
You’ll realize you’re starting
To feel a bit sweaty
When a pop-up declares:
Your MyLab™ test results are ready!
Is 1.9ng/dL good? Is 1.9ng/dL bad??
“??????!!!!!!!” you’ll type in the secure patient chat.
Should I search WebMD while I wait to hear back?
Yes, you’ll decide,
There’s no harm in trying
To crowdsource the question:
“Do you think that I’m dying?”
You’ll have settled on typhus
When a message arrives!
From your doctor, it seems —
But to your surprise,
Your session’s timed out! And your login’s all wrong!
You’ve tried too many times.
We’re not sure you belong.
So…
Be your username Bixby or Bottom or Brauer,
Be your security question, “What underlying conditions make you a liability to your insurance provider?”
Get on your way! The portal’s sealed over.
Try again in 48–72 hours. | https://medium.com/slackjaw/oh-the-places-youll-go-once-you-set-up-your-patient-portal-1470ce597a5c | ['Jenna Nobs'] | 2020-12-29 13:07:51.800000+00:00 | ['Humor', 'Dr Seuss', 'Health', 'Wellness', 'Satire'] | Title Oh Places You’ll Go Set Patient PortalContent Oh Places You’ll Go Set Patient Portal Seussian journey medicalindustrial complex Image brgfx Freepik Congratulations Today day Convenient access personal health record onestar app away brain head teeth mouth Set automatic refill insulin run Schedule Xray CT scan ultrasound MRI — Here’s confirmation code log site Lost already can’t say we’re shocked fifteenfactor verification get unlocked portal active Strap ride timespace continuum tear open wide… OH PLACES YOU’LL GO You’ll scream “Please God knew ignored green stuff toe solved crystal Natural oil Meditation that…could be… missed payment notification” We’re sorry say sadly it’s true owe u lot crusty green goo Sure prescribe cream counter 898 namebrand equal mysteriously Costs ten time amount cost make play along Don’t worry Don’t let Big Pharma profit margin get upset What’s harm little credit card debt You’ll realize you’re starting feel bit sweaty popup declares MyLab™ test result ready 19ngdL good 19ngdL bad “” you’ll type secure patient chat search WebMD wait hear back Yes you’ll decide There’s harm trying crowdsource question “Do think I’m dying” You’ll settled typhus message arrives doctor seems — surprise session’s timed login’s wrong You’ve tried many time We’re sure belong So… username Bixby Bottom Brauer security question “What underlying condition make liability insurance provider” Get way portal’s sealed Try 48–72 hoursTags Humor Dr Seuss Health Wellness Satire |
920 | Can We Talk About Erectile Dysfunction? | ED, or erectile dysfunction, is medically defined as the inability to achieve or sustain an erection long enough for sexual intercourse. It is said that virtually all men experience some erection failures at certain points in their lives. The major culprits would be stress, depression, or other mental health issues in some cases. In other cases, it is due to physical factors, such as obesity, heart conditions, high cholesterol, inefficient blood flow, undiagnosed diabetes. It can be a one-off occasion, or for some, the problem can become a chronic condition.
Contrary to popular belief, it’s important for both men and women to realise that ED is not at all uncommon affecting 50% of men in the U.S. who experience some form of sexual dysfunction at some point in their lives. ED is one of the most common male sexual problems, affecting an estimated 30 million men in the U.S. and approximately 140 million men worldwide.
And while it seems to be a man’s problem, this is far from the truth. The moment it occurs within a relationship, it affects two lives and it has detrimental effects not only on the man but on his partner and on the relationship.
Photo by Charles 🇵🇭 on Unsplash
ED is more a relationship problem than a male sexual problem.
Women usually internalise things. They tend to look for a reason and they tend to find it in themselves, blaming themselves, thinking it’s because they have done something wrong, or that they are no longer attractive to their partner. Or hinting that there is an affair in the background that can cause a lack of interest. It can result in anger, hurt, distrust and in extreme cases the falling out of the relationship.
Often a line of questioning results in both parties being offended and hurt, the lack of initiation becomes more common — to avoid the possible rejection or failure.
The solution for it highly depends on how the couple is willing to acknowledge it as a problem and how they chose to tackle it. There are the overcomers, with a strong desire to find a solution together, and there are the resigners, who admit to the problem but choose to ignore it without doing anything about actively, waiting for it to magically resolve on its own.
When the issue derives more from mental blocks than actual chronic physical issues there are quite a few everyday solutions that can improve the problem.
Seek professional help
Sometimes the solution is easier than it seems. It can take the form of discovering a long-hidden depression or anxiety that causes ED as a side effect, in which case it’s not ED that needs to be treated but with solving the root problem it resolves on its own with time. Other times adjusting the diet, consuming better-quality food, taking vitamin D supplement can already help. Physical exercise can also be a solution in mild cases, just as testosterone supplement can be.
Take the stress out of the equation
Stress is detrimental in every aspect of life, of course, it can affect a man’s manhood too. Being frustrated, stressed, tired and drowning in work can result in ED. Go on a vacation, take a day off, try to decrease the causes of stress — popping a pill here won’t help. Getting stressed didn’t happen overnight, it is a longer process. Winding down from it and eliminating stress-factors won’t happen overnight either, but it’s a good start.
Communication
If the woman is experiencing a pullback from the man it confirms her initial belief that she indeed has done something wrong, so she retreats further. This can increase the levels of anxiety and depression that will only worsen the physical symptoms for the man. The ned result can be them stopping to communicate altogether, that will only make problems worse. If the woman withdraws that is the perfect relationship disaster. It ends up being a tragic dance and before you know it, it leaves unforgettable marks on the relationship.
Being able to talk about it is the first step. To open a line of communication is paramount in resolving ED. It is not an easy topic to talk about. It requires a lot of trust, maturity and understanding. But not talking about it can significantly affect first the sex life, and eventually even the whole of the relationship.
Loosen up and do not try harder
If it is not spelt out that the ED is not the result of losing interest, some women might feel the urge to seduce their partners, to prove their own worth and attractiveness. And while in any other case showing some skin and get down to sexy texts is a fun and helpful way to improve the relationship — it can be very frustrating and downright counterproductive in this case. Wearing sexy clothes or stroking him harder will not cut it, as the problem is not in getting aroused, it is about not being able to maintain an erection satisfyingly long enough.
Take the focus off penetration
Incredible but true, that not only penetrative sex can bring mutual satisfaction to a couple. From a woman’s perspective, it is more commonly understood that oral or manual stimulation can get her there. It is less understood that for a male orgasm an erection is not a precondition either. It is important to keep the intimacy, the cuddles, and probably to shift the focus to her pleasure. Sometimes the most frustrating feeling about ED is the feeling of failure as in not being able to satisfy the woman. Which is not true, as most women only experience or just prefer clitoral orgasms to penetrative ones. This time can be taken as a great experience in different sexual experimenting, giving way to various solutions, other than PiV.
And most importantly, shift the mindset. It is not a man’s problem. It is a relationship problem. Erectile dysfunction, in general, is not about the woman. And while women don’t need to take responsibility for their partner’s ED many women can and do play a critical role in supporting men to seek and find treatment. | https://zitafontaine.medium.com/can-we-talk-about-erectile-dysfunction-8d0f47e591c2 | ['Zita Fontaine'] | 2019-06-29 16:45:25.727000+00:00 | ['Relationships', 'Health', 'Mental Health', 'Sexuality', 'Sex'] | Title Talk Erectile DysfunctionContent ED erectile dysfunction medically defined inability achieve sustain erection long enough sexual intercourse said virtually men experience erection failure certain point life major culprit would stress depression mental health issue case case due physical factor obesity heart condition high cholesterol inefficient blood flow undiagnosed diabetes oneoff occasion problem become chronic condition Contrary popular belief it’s important men woman realise ED uncommon affecting 50 men US experience form sexual dysfunction point life ED one common male sexual problem affecting estimated 30 million men US approximately 140 million men worldwide seems man’s problem far truth moment occurs within relationship affect two life detrimental effect man partner relationship Photo Charles 🇵🇭 Unsplash ED relationship problem male sexual problem Women usually internalise thing tend look reason tend find blaming thinking it’s done something wrong longer attractive partner hinting affair background cause lack interest result anger hurt distrust extreme case falling relationship Often line questioning result party offended hurt lack initiation becomes common — avoid possible rejection failure solution highly depends couple willing acknowledge problem chose tackle overcomer strong desire find solution together resigners admit problem choose ignore without anything actively waiting magically resolve issue derives mental block actual chronic physical issue quite everyday solution improve problem Seek professional help Sometimes solution easier seems take form discovering longhidden depression anxiety cause ED side effect case it’s ED need treated solving root problem resolve time time adjusting diet consuming betterquality food taking vitamin supplement already help Physical exercise also solution mild case testosterone supplement Take stress equation Stress detrimental every aspect life course affect man’s manhood frustrated stressed tired drowning work result ED Go vacation take day try decrease cause stress — popping pill won’t help Getting stressed didn’t happen overnight longer process Winding eliminating stressfactors won’t happen overnight either it’s good start Communication woman experiencing pullback man confirms initial belief indeed done something wrong retreat increase level anxiety depression worsen physical symptom man ned result stopping communicate altogether make problem worse woman withdraws perfect relationship disaster end tragic dance know leaf unforgettable mark relationship able talk first step open line communication paramount resolving ED easy topic talk requires lot trust maturity understanding talking significantly affect first sex life eventually even whole relationship Loosen try harder spelt ED result losing interest woman might feel urge seduce partner prove worth attractiveness case showing skin get sexy text fun helpful way improve relationship — frustrating downright counterproductive case Wearing sexy clothes stroking harder cut problem getting aroused able maintain erection satisfyingly long enough Take focus penetration Incredible true penetrative sex bring mutual satisfaction couple woman’s perspective commonly understood oral manual stimulation get le understood male orgasm erection precondition either important keep intimacy cuddle probably shift focus pleasure Sometimes frustrating feeling ED feeling failure able satisfy woman true woman experience prefer clitoral orgasm penetrative one time taken great experience different sexual experimenting giving way various solution PiV importantly shift mindset man’s problem relationship problem Erectile dysfunction general woman woman don’t need take responsibility partner’s ED many woman play critical role supporting men seek find treatmentTags Relationships Health Mental Health Sexuality Sex |
921 | Estimate Probabilities of Card Games | Estimate Probabilities of Card Games
A practical example of how you can calculate Card Probabilities with Monte Carlo Simulation and Numerically
Photo by Amanda Jones on Unsplash
We are going to show how we can estimate card probabilities by applying Monte Carlo Simulation and how we can solve them numerically in Python. The first thing that we need to do is to create a deck of 52 cards.
How to Generate a Deck of Cards
import itertools, random # make a deck of cards
deck = list(itertools.product(['A', '2', '3', '4', '5', '6', '7', '8', '9', '10', 'J', 'Q', 'K'],['Spade','Heart','Diamond','Club'])) deck
And we get:
[('A', 'Spade'),
('A', 'Heart'),
('A', 'Diamond'),
('A', 'Club'),
('2', 'Spade'),
('2', 'Heart'),
('2', 'Diamond'),
('2', 'Club'),
('3', 'Spade'),
('3', 'Heart'),
('3', 'Diamond'),
('3', 'Club'),
('4', 'Spade'),
('4', 'Heart'),
('4', 'Diamond'),
('4', 'Club'),
('5', 'Spade'),
('5', 'Heart'),
...
How to Shuffle the Deck
# shuffle the cards
random.shuffle(deck)
deck[0:10]
And we get:
[('6', 'Club'),
('8', 'Spade'),
('J', 'Heart'),
('10', 'Heart'),
('Q', 'Spade'),
('7', 'Diamond'),
('K', 'Diamond'),
('J', 'Club'),
('J', 'Diamond'),
('A', 'Club')]
How to Sort the Deck
For some probabilities where the order does not matter, a good trick is to sort the cards. The following commands can be helpful.
# sort the deck
sorted(deck) # sort by face
sorted(deck, key = lambda x: x[0]) # sort by suit
sorted(deck, key = lambda x: x[1])
How to Remove Cards from the Deck
Depending on the Games and the problem that we need to solve, sometimes there is a need to remove from the Deck the cards which have already been served. The commands that we can use are the following:
# assume that card is a tuple like ('J', 'Diamond')
deck.remove(card) # or we can use the pop command where we remove by the index
deck.pop(0) # or for the last card
deck.pop()
Part 1: Estimate Card Probabilities with Monte Carlo Simulation
Question 1: What is the probability that when two cards are drawn from a deck of cards without a replacement that both of them will be Ace?
Let’s say that we were not familiar with formulas or that the problem was more complicated. We could find an approximate probability with a Monte Carlo Simulation (10M Simulations)
N = 10000000
double_aces = 0 for hands in range(N):
# shuffle the cards
random.shuffle(deck)
aces = [d[0] for d in deck[0:2]].count('A')
if aces == 2:
double_aces+=1 prob = double_aces/N
prob
And we get 0.0045214 where the actual probability is 0.0045
Question 2: What is the probability of two Aces in 5 card hand without replacement.
FYI: In case you want to solve it explicitly by applying mathematical formulas:
from scipy.stats import hypergeom # k is the number of required aces
# M is the total number of the cards in a deck
# n how many aces are in the deck
# N how many aces cards we will get hypergeom.pmf(k=2,M=52, n=4, N=5)
And we get 0.03992981808107859 . Let’s try to solve it by applying simulation:
N = 10000000
double_aces = 0 for hands in range(N):
# shuffle the cards
random.shuffle(deck)
aces = [d[0] for d in deck[0:5]].count('A')
if aces == 2:
# print(deck[0:2])
double_aces+=1 prob = double_aces/N
prob
And we get 0.0398805. Again, quite close to the actual probability
Question 3: What is the probability of being dealt a flush (5 cards of all the same suit) from the first 5 cards in a deck?
If you would like to see the mathematical solution of this question you can visit PredictiveHacks. Let’s solve it again by applying a Monte Carlo Simulation.
N = 10000000 flushes = 0 for hands in range(N):
# shuffle the cards
random.shuffle(deck)
flush = [d[1] for d in deck[0:5]]
if len(set(flush))== 1:
flushes+=1
prob = flushes/N
prob
And we get 0.0019823 which is quite close to the actual probability which is 0.00198.
Question 4: What is the probability of being dealt a royal flush from the first 5 cards in a deck?
The actual probability of this case is around 0.00000154. Let’s see if the Monte Carlo works with such small numbers.
# royal flush N = 10000000
royal_flushes = 0
for hands in range(N):
# shuffle the cards
random.shuffle(deck)
flush = [d[1] for d in deck[0:5]]
face = [d[0] for d in deck[0:5]]
if len(set(flush))== 1 and sorted(['A','J', 'Q', 'K', '10'])==sorted(face):
royal_flushes+=1 prob = royal_flushes/N
prob | https://medium.com/swlh/estimate-probabilities-of-card-games-3ae50adb75c7 | ['George Pipis'] | 2020-10-05 08:34:16.072000+00:00 | ['Card Game', 'Probability', 'Python', 'Monte Carlo', 'AI'] | Title Estimate Probabilities Card GamesContent Estimate Probabilities Card Games practical example calculate Card Probabilities Monte Carlo Simulation Numerically Photo Amanda Jones Unsplash going show estimate card probability applying Monte Carlo Simulation solve numerically Python first thing need create deck 52 card Generate Deck Cards import itertools random make deck card deck listitertoolsproductA 2 3 4 5 6 7 8 9 10 J Q KSpadeHeartDiamondClub deck get Spade Heart Diamond Club 2 Spade 2 Heart 2 Diamond 2 Club 3 Spade 3 Heart 3 Diamond 3 Club 4 Spade 4 Heart 4 Diamond 4 Club 5 Spade 5 Heart Shuffle Deck shuffle card randomshuffledeck deck010 get 6 Club 8 Spade J Heart 10 Heart Q Spade 7 Diamond K Diamond J Club J Diamond Club Sort Deck probability order matter good trick sort card following command helpful sort deck sorteddeck sort face sorteddeck key lambda x x0 sort suit sorteddeck key lambda x x1 Remove Cards Deck Depending Games problem need solve sometimes need remove Deck card already served command use following assume card tuple like J Diamond deckremovecard use pop command remove index deckpop0 last card deckpop Part 1 Estimate Card Probabilities Monte Carlo Simulation Question 1 probability two card drawn deck card without replacement Ace Let’s say familiar formula problem complicated could find approximate probability Monte Carlo Simulation 10M Simulations N 10000000 doubleaces 0 hand rangeN shuffle card randomshuffledeck ace d0 deck02countA ace 2 doubleaces1 prob doubleacesN prob get 00045214 actual probability 00045 Question 2 probability two Aces 5 card hand without replacement FYI case want solve explicitly applying mathematical formula scipystats import hypergeom k number required ace total number card deck n many ace deck N many ace card get hypergeompmfk2M52 n4 N5 get 003992981808107859 Let’s try solve applying simulation N 10000000 doubleaces 0 hand rangeN shuffle card randomshuffledeck ace d0 deck05countA ace 2 printdeck02 doubleaces1 prob doubleacesN prob get 00398805 quite close actual probability Question 3 probability dealt flush 5 card suit first 5 card deck would like see mathematical solution question visit PredictiveHacks Let’s solve applying Monte Carlo Simulation N 10000000 flush 0 hand rangeN shuffle card randomshuffledeck flush d1 deck05 lensetflush 1 flushes1 prob flushesN prob get 00019823 quite close actual probability 000198 Question 4 probability dealt royal flush first 5 card deck actual probability case around 000000154 Let’s see Monte Carlo work small number royal flush N 10000000 royalflushes 0 hand rangeN shuffle card randomshuffledeck flush d1 deck05 face d0 deck05 lensetflush 1 sortedAJ Q K 10sortedface royalflushes1 prob royalflushesN probTags Card Game Probability Python Monte Carlo AI |
922 | Hooked On Mnemonics | What is the Mnemonic Maker app?
Ever use Quizlet? Now imagine those digital flashcards incorporating your favorite song lyrics to help make studying effective and fun. And not just any lyrics, but lyrics whose initials line up perfectly to those of the phrase or list you need to remember. Add these mnemonic devices to a playlist of your choosing and listen to your flashcards come to life!
https://mnemonicmaker.netlify.app/
How we got here
As a former teacher and avid life-long student, I’m always looking for ways to make learning more fun and engaging. When I used to teach fourth graders, my co-teacher and I found that our students were having trouble with their multiplication tables. So, we created multiplication songs for each digit (“This is the way we roll our 3s!”) to have the students sing before they started class. The kids loved it, and, eventually, not one student had trouble with single digit multiplication for the rest of the year. This showed me the magic of strategic, engaging learning, particularly the magic of learning through music.
Over the summer, I was talking with my friend and fellow coder Jack about planets, trying to name every one in order. Jack then pointed out, “What’s that mnemonic device used to remember planets? “My (Mercury) Very (Venus) Eager (Earth) Mother (Mars) something something Noodles (Neptune)?” We laughed and said that we could come up with something better than that. After 5 minutes, we pathetically gave up. One of us (I honestly forget who) then says, “You can definitely write code to generate one for you.” A week later, we started working on our project that would become “Mnemonic Maker”, a website that helps you remember things by matching up your list or phrase’s initials to those of a catchy/memorable song lyric.
Within a few weeks, we created a simple website that returned a matching lyric to an input phrase, but there were two main problems:
1. The “lyric” returned was a string of consecutive words anywhere in the song, often across bar breaks. In other words, if we entered something we wanted to remember, like “Ministry of Transport”, the app might hit the song, “Empire State of Mind” by Jay-Z (great song), and it might hit the lyric: “Concrete Jungles where dreams are made of, there’s nothing you can’t do” (great lyric), but in this case it’ll return the matching phrase as “Made Of, There’s.” That’s not a catchy lyric, and it’s not going to help anyone remember anything.
2. More importantly, It took forever. Nobody wants to sit in front of their computer and wait 5 minutes for a matching phrase to come up.
So, we decided to scrap this project and start fresh (using the lessons we learned and utilizing some useful code from the old project). We then got a pretty cool app, that looked a lot nicer, and was lightening quick. Still, a couple of problems:
1. Same as before, the lyrics are not catchy.
2. The app would return lyrics of just Beatles songs. While I love the Beatles, this is simply not enough data.
So, we scrapped that, and started anew with what would be the final codebase for the project. This is where we got lost in the code and kept adding features. At this point, we were able to to:
-search through many artists’ lyrics very quickly, and filter the search by a particular artist
-add the YouTube videos of the songs (this process deserves its own blog post)
-have users create accounts and login
-save the mnemonic info (user’s input, matching phrase, song info) to a user’s playlist so that they can refer back to it and listen to their mnemonic songs.
-and much more
On top of that, the app looked way nicer.
However, there was still a problem, a bad itch that a couldn’t shake: the returning phrases were still not recognizable nor catchy!
So, I branched off of the project, and using all of its existing code and framework, created a new one. Eventually, I got it. Now the user can search a phrase and the lyric will not be split over bar breaks or be from the middle of a lyric. And it works even faster than before. I have even been using it myself whenever I come across a word or a phrase I don’t know and want to keep track of. It genuinely helps me remember things, and also helps me discover new songs. Am I biased? Of course, but I still think it’s pretty cool.
Users playlist where they can save mnemonic info
Notes about a specific phrase or list they wish to memorize
Corresponding phrase, along with mnemonic info and youtube vid.
However, the app is by no means perfect nor is it done. I am just done for now. How will I know when it’s done or that I reached my goals (to some extent)? When I can type in all of the planets in our solar system and get something better than “My Very Eager Mother Just Served Us Noodles.” That phrase is too long for the app at this point. Right now, I usually find success in typing in phrases with a length of 4 words or less.
A few notes about the coding process:
I talked about how the app evolved from a functionality standpoint, however, if you are curious about the programming behind the evolution of the app, stick around. If you don’t care, that’s cool, too. Thanks for reading.
Why was the querying process so slow at first?
We started by making api calls to songs one by one whenever a user typed in a phrase. Not only did it make an api call per song queried, but it also web-scraped the lyrics from genius.com at every turn. You can imagine how the runtime of such an app is not ideal.
Made it faster by…
The power of seeding. When we created the generator based solely on Beatles lyrics, the app was running through every Beatle’s song’s lyrics in our database (without scraping or making api calls, just strict Active Record iterations), until it found a match. This was surprisingly fast and got us pretty excited.
Made it a more comprehensive app by…
Implementing the aspect of OAuth with the options to save bookmarks to a playlist as well as edit playlists and delete them (full CRUD). To incorporate all of these details and have them persist throughout the app, we used Redux, a library that allows you to access and change global state in a clean, structured way.
Made it more dynamic by…
Seeding more artists and their respective song lyrics. To do this we had to code a pretty robust seeding method in the backend, using a combination of making API Calls (to get the artist info and their list of songs) and web-scraping (first by scraping the lyrics from genius, then scraping the YouTube video idea from Youtube). The idea was, if we were to add more artists, and more songs, then the input phrase would find a match more often. However, naturally, with querying more songs comes a slower runtime…and again we still aren’t grabbing “catchy” phrases.
Made it faster, cleaner, and catchier with fewer lines of code by…
Adding a new table, called “Lyric Snippets.” We knew that when we accessed the lyric text from scraping the Genius web-pages, that Ruby allows us to break the text down line by line through the method, “each_line.” So, what I did was raise the fixed cost of seeding so that I could lower the variable cost of the user experience. I iterated through thousands of songs, and seeded each line, double-line (two lines combined together), and fragment (produced by splitting the line about its commas) in a row, along with the initials. That way, whatever a user types in, say “I love coding”, we can easily query all the snippets with those initials-LyricSnippet.where(initials: “ilc”), and queue them up for our user. First result I got in a matter of seconds: “I lost control” from an Ozzy Osborne song. Seems about right.
At the time of deployment, my database holds 542,023 snippets. You may be thinking, “That’s way too many rows and is not optimal for space.” But, when I made the switch to lyric snippets, I no longer had to save the full lyrics in the database, I just triggered an API call/web-scrape upon a match. So, it almost evens out in that sense.
Next:
One exciting yet frustrating thing is that I don’t consider this app finished and there are still things that I want to do with it. Stuff like implementing Facebook Auth, executing more elegant styling, filtering by genre, and creating an overall better user experience, is something I would be happy to revisit later. Until then, I will ponder. How do I accomplish my ultimate goal? How do I reach Neptune? Maybe it’s more seed data, maybe it’s a more clever way of querying the lyrics, maybe it’s something I’m totally not seeing. Below is the link to the GitHub repo. Check it out and let me know what you think.
https://github.com/seanytdawg/Mnemonic-2.0-front-end | https://seantarzy.medium.com/hooked-on-mnemonics-63b22e40cb85 | [] | 2020-12-04 20:50:33.233000+00:00 | ['Mnemonics', 'Software Engineering', 'Tech', 'Music', 'Teaching'] | Title Hooked MnemonicsContent Mnemonic Maker app Ever use Quizlet imagine digital flashcard incorporating favorite song lyric help make studying effective fun lyric lyric whose initial line perfectly phrase list need remember Add mnemonic device playlist choosing listen flashcard come life httpsmnemonicmakernetlifyapp got former teacher avid lifelong student I’m always looking way make learning fun engaging used teach fourth grader coteacher found student trouble multiplication table created multiplication song digit “This way roll 3s” student sing started class kid loved eventually one student trouble single digit multiplication rest year showed magic strategic engaging learning particularly magic learning music summer talking friend fellow coder Jack planet trying name every one order Jack pointed “What’s mnemonic device used remember planet “My Mercury Venus Eager Earth Mother Mars something something Noodles Neptune” laughed said could come something better 5 minute pathetically gave One u honestly forget say “You definitely write code generate one you” week later started working project would become “Mnemonic Maker” website help remember thing matching list phrase’s initial catchymemorable song lyric Within week created simple website returned matching lyric input phrase two main problem 1 “lyric” returned string consecutive word anywhere song often across bar break word entered something wanted remember like “Ministry Transport” app might hit song “Empire State Mind” JayZ great song might hit lyric “Concrete Jungles dream made there’s nothing can’t do” great lyric case it’ll return matching phrase “Made There’s” That’s catchy lyric it’s going help anyone remember anything 2 importantly took forever Nobody want sit front computer wait 5 minute matching phrase come decided scrap project start fresh using lesson learned utilizing useful code old project got pretty cool app looked lot nicer lightening quick Still couple problem 1 lyric catchy 2 app would return lyric Beatles song love Beatles simply enough data scrapped started anew would final codebase project got lost code kept adding feature point able search many artists’ lyric quickly filter search particular artist add YouTube video song process deserves blog post user create account login save mnemonic info user’s input matching phrase song info user’s playlist refer back listen mnemonic song much top app looked way nicer However still problem bad itch couldn’t shake returning phrase still recognizable catchy branched project using existing code framework created new one Eventually got user search phrase lyric split bar break middle lyric work even faster even using whenever come across word phrase don’t know want keep track genuinely help remember thing also help discover new song biased course still think it’s pretty cool Users playlist save mnemonic info Notes specific phrase list wish memorize Corresponding phrase along mnemonic info youtube vid However app mean perfect done done know it’s done reached goal extent type planet solar system get something better “My Eager Mother Served Us Noodles” phrase long app point Right usually find success typing phrase length 4 word le note coding process talked app evolved functionality standpoint however curious programming behind evolution app stick around don’t care that’s cool Thanks reading querying process slow first started making api call song one one whenever user typed phrase make api call per song queried also webscraped lyric geniuscom every turn imagine runtime app ideal Made faster by… power seeding created generator based solely Beatles lyric app running every Beatle’s song’s lyric database without scraping making api call strict Active Record iteration found match surprisingly fast got u pretty excited Made comprehensive app by… Implementing aspect OAuth option save bookmark playlist well edit playlist delete full CRUD incorporate detail persist throughout app used Redux library allows access change global state clean structured way Made dynamic by… Seeding artist respective song lyric code pretty robust seeding method backend using combination making API Calls get artist info list song webscraping first scraping lyric genius scraping YouTube video idea Youtube idea add artist song input phrase would find match often However naturally querying song come slower runtime…and still aren’t grabbing “catchy” phrase Made faster cleaner catchier fewer line code by… Adding new table called “Lyric Snippets” knew accessed lyric text scraping Genius webpage Ruby allows u break text line line method “eachline” raise fixed cost seeding could lower variable cost user experience iterated thousand song seeded line doubleline two line combined together fragment produced splitting line comma row along initial way whatever user type say “I love coding” easily query snippet initialsLyricSnippetwhereinitials “ilc” queue user First result got matter second “I lost control” Ozzy Osborne song Seems right time deployment database hold 542023 snippet may thinking “That’s way many row optimal space” made switch lyric snippet longer save full lyric database triggered API callwebscrape upon match almost even sense Next One exciting yet frustrating thing don’t consider app finished still thing want Stuff like implementing Facebook Auth executing elegant styling filtering genre creating overall better user experience something would happy revisit later ponder accomplish ultimate goal reach Neptune Maybe it’s seed data maybe it’s clever way querying lyric maybe it’s something I’m totally seeing link GitHub repo Check let know think httpsgithubcomseanytdawgMnemonic20frontendTags Mnemonics Software Engineering Tech Music Teaching |
923 | We’re All About to Get a Lot More Lonely | We’re All About to Get a Lot More Lonely
How to deal with COVID-19-induced social distancing without getting too… socially distanced
Photo: MoMo Productions/Getty Images
“Social distancing” has abruptly become a buzzword. In an effort to slow the spread of coronavirus, public officials are telling us to stay away from group gatherings, work from home if possible, avoid any unnecessary travel, and generally limit our comings and goings.
All this solitude is a big adjustment if you’re used to riding a packed bus to get to the bustling office, and then heading to a crowded gym for a workout before meeting up with friends at a busy restaurant. Overnight, we’ve gone from a world in which a jam-packed calendar is a status symbol, to one in which it’s fashionable to have a six-foot personal buffer zone. The less you see of your fellow humans right now, the better — even if it flies in the face of decades of research telling us that social connection is essential to our community, mental, and even physical health.
Loneliness carries its own emotional and health risks — risks that are comparable to smoking, obesity, or air pollution, according to one 2010 study. “We’re isolating the virus,” says Ali Khan, MD, a professor of epidemiology at the University of Nebraska Medical Center, and the dean of its College of Public Health. “Let’s try not to isolate the people.”
Yet it’s hard to avoid some degree of isolation when you suddenly remove so many of our usual sources of human contact. From the office water cooler to the conference room to the power lunch, our working lives are full of human interactions that foster a day-to-day sense of social connection. And then there are the gathering places that are neither work nor home: the so-called third places like coffee shops, gyms, and libraries, “locations where people gather and often talk about things that are important to them,” as one study put it. Tell people to stay away from these spaces, and you’re confining them to relative isolation — particularly if they live completely alone. For the elderly, the immunocompromised, and other groups most threatened by COVID-19, taking the necessary extra precautions can make that isolation particularly acute.
But it’s possible to approach this time as a challenge, not a sentence — an exercise in creatively maintaining or even deepening social connections. We just need to do it in a way that is safe for our oldest and most vulnerable community members. Here are a few ideas:
Be smarter about social media
The better we get at meeting our social needs online, the less we will feel tempted to give in to cabin fever, leave the house, and run to the nearest crowded bar (if you can find one that’s still crowded).
But we can’t find real social satisfaction by just turning on a computer or picking up a phone. Creating an online existence that can patch the holes left by all this social distancing takes planning.
Start by looking for ways to weave social interaction into the fabric of your day. This may feel counterintuitive — particularly if you’ve set up habits or technologies to keep social media “distractions” at bay throughout the workday. But office life is full of brief social interruptions, like when you head to the office kitchen for a fresh cup of coffee, run into a colleague, and end up talking about last night’s episode of 9–1–1: Lone Star. These are the tiny interactions that keep us feeling like part of a community.
Now that you are home, it is even more important to find short, low-stakes conversations that keep you connected to other humans. Tie your mental breaks to your social needs: A comment or two in a 9–1–1 Facebook group, for example, is worth infinitely more in this context than taking five minutes to read the latest show news online. The point is to find interactions that are self-contained, and that help you maintain a sense of connection to the outside world.
Winnow the feeds
Stay informed of important updates by following official health organizations and your local offices of emergency management, but don’t go overboard. (I built my own list of epidemiologists on Twitter so that I can pay attention to people who actually know what they’re talking about.) Your discretionary social interactions — from who you exchange tweets with to whose Instagram you follow — need to point you towards the people who make you feel replenished and fulfilled, and away from the people who don’t. That means unfollowing or muting anyone whose posts regularly make you feel envious or frustrated, without judging yourself for doing it. Create lists of people whose feeds relax you, pique your interest, or just make you happy, and then only look at those people when you check in on Facebook or Twitter. (Yes, it will be an echo chamber for now, but you can go back to engaging with a wider swathe of humanity when you’re no longer relying on social media for most of your human interaction.)
Get on a video call
Think of those little social-media interactions as social snacks: They can only tide you over if your day also includes satisfying, full-meal-sized conversations.
That begins with how you stay in touch with colleagues: Slack and email may be efficient, but you’ll feel more connected if you make time for phone calls, or even better, videoconferencing. Set up your workstation in a spot in your home where it’s effortless (and soundproof) to take a web call, hang a jacket on the back of the chair, and put an extra lipstick on the table: If it’s easy to get camera ready, you’ll do more video calls, and feel less isolated.
The same principle applies to non-work interaction. If you’ve fallen into the habit of staying in touch via text, Facebook, or Instagram, now is the time to revive an ancient social custom: placing an unscheduled phone call. I know, it feels rude to just dial a phone number without first sending a calendar invitation or even a quick text message. But there is something incredibly human and immediate about picking up the phone and calling a friend without warning (unless you think it will give her a heart attack).
And this goes both ways: One of the advantages of working from home is that you can actually pick up the phone when a friend calls, even though it’s the middle of the work day. Put on your headphones and step outside and talk for a long, long time while you go for a walk (staying six feet away from any passersby), and you’ll hang up feeling nourished.
Call your mom
Those phone calls will help keep other people healthy, too. If you’re worried about someone, call them.
“Call your mother every day,” Khan advises. “These aren’t usual times, so change your behavior to reflect these times.” While you’re calling, maybe offer to pick up some groceries — because keeping people well-supplied is another way to help keep the whole community safe. “We don’t want people to break quarantine because they don’t have food,” Khan notes.
Nor is actual face-to-face interaction beyond the realm of possibility, as long as you’re healthy. “You should definitely see friends, but do it outside if possible,” to avoid spreading germs, says Eli Perencevich, MD, a professor of Medicine and Epidemiology at the University of Iowa’s Carver College of Medicine. “Go for a walk, but stay three to six feet apart. Or sit on a park bench, but sit at the ends of the park bench.”
This combination of judicious (ideally outdoor) social interaction and copious, tech-enabled connection may give us just enough human contact to get us through this trial. But make no mistake: Social distancing will be hard — so just remember that the alternative may be even harder. As Khan notes, “The consequences of letting coronavirus run rampant are as bad or worse as the consequences of isolation.” | https://forge.medium.com/were-all-about-to-get-a-lot-more-lonely-cd32385a89f6 | ['Alexandra Samuel'] | 2020-03-13 14:47:32.936000+00:00 | ['Connect', 'Relationships', 'Self', 'Health', 'Coronavirus'] | Title We’re Get Lot LonelyContent We’re Get Lot Lonely deal COVID19induced social distancing without getting too… socially distanced Photo MoMo ProductionsGetty Images “Social distancing” abruptly become buzzword effort slow spread coronavirus public official telling u stay away group gathering work home possible avoid unnecessary travel generally limit coming going solitude big adjustment you’re used riding packed bus get bustling office heading crowded gym workout meeting friend busy restaurant Overnight we’ve gone world jampacked calendar status symbol one it’s fashionable sixfoot personal buffer zone le see fellow human right better — even fly face decade research telling u social connection essential community mental even physical health Loneliness carry emotional health risk — risk comparable smoking obesity air pollution according one 2010 study “We’re isolating virus” say Ali Khan MD professor epidemiology University Nebraska Medical Center dean College Public Health “Let’s try isolate people” Yet it’s hard avoid degree isolation suddenly remove many usual source human contact office water cooler conference room power lunch working life full human interaction foster daytoday sense social connection gathering place neither work home socalled third place like coffee shop gym library “locations people gather often talk thing important them” one study put Tell people stay away space you’re confining relative isolation — particularly live completely alone elderly immunocompromised group threatened COVID19 taking necessary extra precaution make isolation particularly acute it’s possible approach time challenge sentence — exercise creatively maintaining even deepening social connection need way safe oldest vulnerable community member idea smarter social medium better get meeting social need online le feel tempted give cabin fever leave house run nearest crowded bar find one that’s still crowded can’t find real social satisfaction turning computer picking phone Creating online existence patch hole left social distancing take planning Start looking way weave social interaction fabric day may feel counterintuitive — particularly you’ve set habit technology keep social medium “distractions” bay throughout workday office life full brief social interruption like head office kitchen fresh cup coffee run colleague end talking last night’s episode 9–1–1 Lone Star tiny interaction keep u feeling like part community home even important find short lowstakes conversation keep connected human Tie mental break social need comment two 9–1–1 Facebook group example worth infinitely context taking five minute read latest show news online point find interaction selfcontained help maintain sense connection outside world Winnow feed Stay informed important update following official health organization local office emergency management don’t go overboard built list epidemiologist Twitter pay attention people actually know they’re talking discretionary social interaction — exchange tweet whose Instagram follow — need point towards people make feel replenished fulfilled away people don’t mean unfollowing muting anyone whose post regularly make feel envious frustrated without judging Create list people whose feed relax pique interest make happy look people check Facebook Twitter Yes echo chamber go back engaging wider swathe humanity you’re longer relying social medium human interaction Get video call Think little socialmedia interaction social snack tide day also includes satisfying fullmealsized conversation begin stay touch colleague Slack email may efficient you’ll feel connected make time phone call even better videoconferencing Set workstation spot home it’s effortless soundproof take web call hang jacket back chair put extra lipstick table it’s easy get camera ready you’ll video call feel le isolated principle applies nonwork interaction you’ve fallen habit staying touch via text Facebook Instagram time revive ancient social custom placing unscheduled phone call know feel rude dial phone number without first sending calendar invitation even quick text message something incredibly human immediate picking phone calling friend without warning unless think give heart attack go way One advantage working home actually pick phone friend call even though it’s middle work day Put headphone step outside talk long long time go walk staying six foot away passersby you’ll hang feeling nourished Call mom phone call help keep people healthy you’re worried someone call “Call mother every day” Khan advises “These aren’t usual time change behavior reflect times” you’re calling maybe offer pick grocery — keeping people wellsupplied another way help keep whole community safe “We don’t want people break quarantine don’t food” Khan note actual facetoface interaction beyond realm possibility long you’re healthy “You definitely see friend outside possible” avoid spreading germ say Eli Perencevich MD professor Medicine Epidemiology University Iowa’s Carver College Medicine “Go walk stay three six foot apart sit park bench sit end park bench” combination judicious ideally outdoor social interaction copious techenabled connection may give u enough human contact get u trial make mistake Social distancing hard — remember alternative may even harder Khan note “The consequence letting coronavirus run rampant bad worse consequence isolation”Tags Connect Relationships Self Health Coronavirus |
924 | How Ego Almost Killed My Company | Does a company really need to grow?
There this thinking that a company should always be growing. You have to make more money. You have to hire more people. You have to have a bigger office. Paul Jarvis, the author of the book Company of One, says that there’s a core assumption that growth is always good and is required for success. Culturally, growth feeds our ego and social standing. The bigger the company you own, with more profits and more employees than the next person, the better you might feel.
I’m a very competitive person. I always thought about being the best. I read all of Jim Collins’ books, and the Big Hairy Audacious Goal idea inspired me. BHAG is a powerful and bold long-term goal that you set as the mission for your company. Influenced by that, I defined ours as “Be the #1 word games company in the world”. That is bold! We had much work to do to make that happen.
I also always thought about selling my company one day. A business exit strategy is a plan that a founder or owner of a business makes to sell their company, or share in a company, to other investors or other firms. Initial public offerings (IPOs), strategic acquisitions, and management buyouts are among the more common exit strategies an owner might pursue. As founder and CEO, I let it clear to my partners since the beginning about my intentions.
Selling my company would help me achieve my goal of being a millionaire and eventually a billionaire. To make that happened, my company had to make much more money. To accomplish that, we needed to improve our current games and make new ones. We needed more people to help us, and I build a strategy for all that, considering that we were a company 100% remote. Having the US$1 million investment also helped.
We ended breaking revenue records again in 2017. We went from five to twelve people, and we build two more new games. We had a lot going on, and I had a lot of pressure to keep growing in 2018. | https://medium.com/swlh/ego-almost-killed-my-company-301d425f178a | ['João Vítor De Souza'] | 2020-12-17 09:26:37.700000+00:00 | ['Startup', 'Work', 'Business', 'Entrepreneurship', 'Management'] | Title Ego Almost Killed CompanyContent company really need grow thinking company always growing make money hire people bigger office Paul Jarvis author book Company One say there’s core assumption growth always good required success Culturally growth feed ego social standing bigger company profit employee next person better might feel I’m competitive person always thought best read Jim Collins’ book Big Hairy Audacious Goal idea inspired BHAG powerful bold longterm goal set mission company Influenced defined “Be 1 word game company world” bold much work make happen also always thought selling company one day business exit strategy plan founder owner business make sell company share company investor firm Initial public offering IPOs strategic acquisition management buyout among common exit strategy owner might pursue founder CEO let clear partner since beginning intention Selling company would help achieve goal millionaire eventually billionaire make happened company make much money accomplish needed improve current game make new one needed people help u build strategy considering company 100 remote US1 million investment also helped ended breaking revenue record 2017 went five twelve people build two new game lot going lot pressure keep growing 2018Tags Startup Work Business Entrepreneurship Management |
925 | You won’t believe what I’m going to tell you about clickbait! | You won’t believe what I’m going to tell you about clickbait!
Number 5 will shock you…
No matter what your aims are with content marketing, writing a good, eye-catching headline is key to clicks and success. This has resulted in the method of clickbait progressively evolving over the last few years.
Clickbait headlines are written, or thumbnails designed, to create intrigue, and in a way so that the audience must click on the link to find out what they’re talking about. Clickbait is compelling because, psychologically, we crave the information which is left out of headlines. And no matter how tacky they read, clickbait headlines successfully tantalise all sorts of people, and in doing so lure massive amounts of traffic to (usually ad heavy) websites.
But can clickbait be used by public sector organisations? In its rawest form, no. Fake news! Bad! But there are certain techniques that can be employed to increase the likelihood of clicks and conversion, and at the same time raise you above the clickbait noise.
1. Post. Evaluate. Repeat.
Social media algorithms (as well as audience behaviour) are constantly changing, so posts which may have performed well last year may no longer be as successful. If you see a post performing well in terms of engagement and clicks, employ the same style in your next few posts, then evaluate.
A personal favourite account of mine is BBC News on Facebook. Whilst it’s not clickbait, their post descriptions are short, emotive and create curiosity for the reader to stop scrolling and read the link title. And any method to stop a scroll increases the chance of a click. The BBC also does not use link descriptions, which keeps the amount of text on their posts to a minimum — yet they still manage to communicate to the audience why clicking the link will benefit them.
But if you are struggling for a headline, check out this headline generator!
2. YouTube Custom Thumbnails
It’s surprising how many organisations’ YouTube videos still don’t make use of custom thumbnails, and instead keep that awkward freeze frame of an interviewee’s face mid-sentence!
It’s best practice to create a custom thumbnail using a still from the videos, rather than use a stock image (if it can be helped), overlaid with a bold, readable title. However, don’t use the same tactic on Facebook; text on the thumbnail (or any image for that matter) will count against you.
When it comes to YouTube thumbnails, “intrigue, don’t mislead” advises YouTuber Casey Neistat.
3. GIF bait
Not one to go overboard with, but using a GIF alongside your tweet will catch the audience’s eye and increase the chance of engagement. For example, I would have scrolled straight past this tweet from @buffer had it not been for the CUTE DOG CARRYING A STICK OMG!
Sorry, where was I….
4. Winning with Instagram
Clickbait on Instagram, is that a thing? Yes! Asking for a double tap to complete the picture is just one approach. But we won’t stoop to that level!
Clickbait for Instagram is simply: POST BEAUTIFUL PHOTOGRAPHS. That’s why people use the app. To enjoy amazing photos. Posting full press releases in the description will get you nowhere. Give the people what they want, and be aiming to grow your brand and reputation rather than conveying that 500-word press release!
5. Make a list. Check it twice
It’s the oldest rule in the clickbait manual, but the human brain loves a list. Especially odd numbered lists. Lists help to quantify the length of the story, and are ultimately easier to read.
So those ‘7 Ways To Stay Safe Online’ is a go!
6. Be authentic
You don’t have to stoop to clickbait to get clicks. Develop a tone of voice on your accounts that your audience will relate to; connect with them as you would with friends. Make them laugh. Make their day! And encourage others in your organisation to do the same. A supportive and collaborative online community which champions individuality and authentic content will always outperform eye-rollingly-bad clickbait.
At The Start Of His Blog They Were Sceptical, By The End Of It They Were Asking For More
No matter where you are in your social media journey — whether you have an account with 50 followers, or 50,000 — focus on publishing inspiring content that grabs attention and embraces your brand values. Because, unlike clickbait, audiences will appreciate great content and will stick around for more.
But even after all of this, one question still remains…
How DO cruise ships fill their unsold cabins?
(Article also published on Comms2Point0.co.uk) | https://medium.com/pnewton84/he-discovered-a-new-way-to-write-clickbait-and-his-colleagues-were-speechless-number-7-is-our-89ee81cfab03 | ['Paul Newton'] | 2017-09-19 19:26:41.376000+00:00 | ['Marketing', 'Digital Marketing', 'Facebook', 'Online Marketing', 'Social Media'] | Title won’t believe I’m going tell clickbaitContent won’t believe I’m going tell clickbait Number 5 shock you… matter aim content marketing writing good eyecatching headline key click success resulted method clickbait progressively evolving last year Clickbait headline written thumbnail designed create intrigue way audience must click link find they’re talking Clickbait compelling psychologically crave information left headline matter tacky read clickbait headline successfully tantalise sort people lure massive amount traffic usually ad heavy website clickbait used public sector organisation rawest form Fake news Bad certain technique employed increase likelihood click conversion time raise clickbait noise 1 Post Evaluate Repeat Social medium algorithm well audience behaviour constantly changing post may performed well last year may longer successful see post performing well term engagement click employ style next post evaluate personal favourite account mine BBC News Facebook Whilst it’s clickbait post description short emotive create curiosity reader stop scrolling read link title method stop scroll increase chance click BBC also use link description keep amount text post minimum — yet still manage communicate audience clicking link benefit struggling headline check headline generator 2 YouTube Custom Thumbnails It’s surprising many organisations’ YouTube video still don’t make use custom thumbnail instead keep awkward freeze frame interviewee’s face midsentence It’s best practice create custom thumbnail using still video rather use stock image helped overlaid bold readable title However don’t use tactic Facebook text thumbnail image matter count come YouTube thumbnail “intrigue don’t mislead” advises YouTuber Casey Neistat 3 GIF bait one go overboard using GIF alongside tweet catch audience’s eye increase chance engagement example would scrolled straight past tweet buffer CUTE DOG CARRYING STICK OMG Sorry I… 4 Winning Instagram Clickbait Instagram thing Yes Asking double tap complete picture one approach won’t stoop level Clickbait Instagram simply POST BEAUTIFUL PHOTOGRAPHS That’s people use app enjoy amazing photo Posting full press release description get nowhere Give people want aiming grow brand reputation rather conveying 500word press release 5 Make list Check twice It’s oldest rule clickbait manual human brain love list Especially odd numbered list Lists help quantify length story ultimately easier read ‘7 Ways Stay Safe Online’ go 6 authentic don’t stoop clickbait get click Develop tone voice account audience relate connect would friend Make laugh Make day encourage others organisation supportive collaborative online community champion individuality authentic content always outperform eyerollinglybad clickbait Start Blog Sceptical End Asking matter social medium journey — whether account 50 follower 50000 — focus publishing inspiring content grab attention embrace brand value unlike clickbait audience appreciate great content stick around even one question still remains… cruise ship fill unsold cabin Article also published Comms2Point0coukTags Marketing Digital Marketing Facebook Online Marketing Social Media |
926 | Choosing the Best Level of Editing for Your Writing | Whether you have written a novel, are sending emails to potential clients, or are developing human resource manuals, having a second set of eyes on your written text can help ensure that your writing is the best it can be. By working with a professional editor, you can go beyond grammar checks to ensure that your writing is clear, effective, and on message while also being appropriate for your target reader.
Hiring an editor can be a confusing process, mostly because there are so many different kinds of editing. Therefore, before looking for an editor, it is important to know what kind of editing you need for your specific text.
Although editors may use slightly different terminology to describe their services, editing generally falls into three areas: big picture, fine-tuning, and final polish.
Big Picture Editing
Big picture editing can include editorial assessments, structural editing, and developmental editing. For these types of editing, the editor is looking at the chapter or scene level to make suggestions and recommendations on the content of the writing.
Editorial Assessments
If you’ve ever asked friends or colleagues to read your writing and tell you what they think, you’ve basically received an editorial assessment, although an editor approaches such an assessment with professional training in and understanding of the principles that make specific types of writing effective.
Editorial assessments provide broad suggestions about how to improve the major components of your text, such as the organization or information or the timeline/development of your story. They can include noting areas that might need to be cut or completely revised as well as areas that are missing from the current text. The assessment comes in the form of a letter, and no notes are made on the manuscript itself.
Photo by Jaeyoung Geoffrey Kang on Unsplash
Structural and Developmental Editing
Structural and developmental editing are quite similar in scope, so here we present them together. Note that if you are considering an editor who offers both, be sure to ask for clarification in distinguishing the two.
Structural/developmental editing examines the overall structure of the text to identify what is working and what is not. The focus is on the overall flow of the story and information. It determines whether the information (e.g., chapters, scenes) is presented in a logical manner and if the reader receives enough information to proceed to the next chapter or scene. If not, the editor may suggest moving large chunks of text around and even deleting unnecessarily repetitive sections.
Structural/developmental editing also determines what is working and what is not in terms of overarching themes. In non-fiction writing, this can include the rate at which information is presented as well as whether the information is organized in meaningful chunks. For creative writing, the editor will study whether characters and their development, plot lines, and pacing are effective.
Both structural and developmental editing identifies “holes” in the information or story and makes suggestions for fixing them. It includes feedback on the content that is provided on the manuscript itself (for an example, see Beth Jusino’s screenshot). As a result, structural/developmental editing is much more labor intensive than an editorial assessment.
No big picture editing includes any reviews of the writing itself to eliminate grammar mistakes or typos or to strengthen the writing itself.
Fine-tuning the Writing
Once the overall structure and story are finalized, the writer needs an editor who can examine the mechanics of the writing. This level of editing includes copyediting and line editing, which are similar but adopt a somewhat different focus.
Copyediting
A copy editor will make corrections to the text itself to fix grammar problems like spelling, capitalization, verb tense, and word usage. A copy editor knows all those obscure grammar rules and when to apply them. Copyediting also identifies inconsistencies in the text, such as how places are named or described. For example, is it Baker Street or Baker St.?
Line Editing
Line editing adopts a similar approach as copyediting, but with a focus on the craft of the writing. In other words, a line editor will study the creative choices that the writer makes to ensure consistency and clarity. For example, do the writer’s voice and style contribute to the emotional flow of the story and are they consistent throughout? A line editor will fix clunky, unclear writing to create tight, powerful prose.
Jami Gold provides comprehensive lists of the skills that copy editors and line editors use during their editing process.
Final Polish
When you have what you believe is the final version of your text and you’re ready to publish it, you might want to hire a proofreader and/or fact-checker.
A proofreader reviews the entire text to make sure that no new typos have slipped in during previous editing and revision stages. Proofreaders can also spot errant punctuation, irregular formatting, and outstanding inconsistencies. A proofreader will not make extensive changes to the text, but will instead fix any glaring errors.
A fact-checker can be a vital part of your editing team, especially if you include information from the real world in your manuscript. The fact-checker will verify names, dates, locations, timelines, and similar details to ensure that the text is accurate.
Photo by Nick Morrison on Unsplash
A Final Word: Editing software and apps
Editing software and apps like Grammarly, the Hemingway Editor, and even Microsoft’s grammar and spellcheck are helpful tools when you are writing, but they cannot replace a well-qualified editor. Writers can use these tools to produce the cleanest document possible to provide to their editor, but none of these tools are 100% correct.
When using these tools, writers need to understand grammar and word usage so they can evaluate the suggestions to determine which ones are appropriate. In addition, these tools cannot assess the text for the writer’s creative decisions (e.g., characterizations, poetic wording), style guide requirements (e.g., Chicago Manual of Style or in-house guides), or specific styles of writing (e.g., an author’s voice or “legalese” in corporate communications).
For side-by-side comparisons of one grammar tool versus a human editor, check out David Alan’s review and Tonya Thompson’s review. | https://medium.com/the-red-pen-perspective/levels-of-edits-ec654451ccfe | ['Nanette M. Day'] | 2020-01-22 04:49:50.752000+00:00 | ['Professional', 'Editing', 'Writing', 'Creativity', 'Publishing'] | Title Choosing Best Level Editing WritingContent Whether written novel sending email potential client developing human resource manual second set eye written text help ensure writing best working professional editor go beyond grammar check ensure writing clear effective message also appropriate target reader Hiring editor confusing process mostly many different kind editing Therefore looking editor important know kind editing need specific text Although editor may use slightly different terminology describe service editing generally fall three area big picture finetuning final polish Big Picture Editing Big picture editing include editorial assessment structural editing developmental editing type editing editor looking chapter scene level make suggestion recommendation content writing Editorial Assessments you’ve ever asked friend colleague read writing tell think you’ve basically received editorial assessment although editor approach assessment professional training understanding principle make specific type writing effective Editorial assessment provide broad suggestion improve major component text organization information timelinedevelopment story include noting area might need cut completely revised well area missing current text assessment come form letter note made manuscript Photo Jaeyoung Geoffrey Kang Unsplash Structural Developmental Editing Structural developmental editing quite similar scope present together Note considering editor offer sure ask clarification distinguishing two Structuraldevelopmental editing examines overall structure text identify working focus overall flow story information determines whether information eg chapter scene presented logical manner reader receives enough information proceed next chapter scene editor may suggest moving large chunk text around even deleting unnecessarily repetitive section Structuraldevelopmental editing also determines working term overarching theme nonfiction writing include rate information presented well whether information organized meaningful chunk creative writing editor study whether character development plot line pacing effective structural developmental editing identifies “holes” information story make suggestion fixing includes feedback content provided manuscript example see Beth Jusino’s screenshot result structuraldevelopmental editing much labor intensive editorial assessment big picture editing includes review writing eliminate grammar mistake typo strengthen writing Finetuning Writing overall structure story finalized writer need editor examine mechanic writing level editing includes copyediting line editing similar adopt somewhat different focus Copyediting copy editor make correction text fix grammar problem like spelling capitalization verb tense word usage copy editor know obscure grammar rule apply Copyediting also identifies inconsistency text place named described example Baker Street Baker St Line Editing Line editing adopts similar approach copyediting focus craft writing word line editor study creative choice writer make ensure consistency clarity example writer’s voice style contribute emotional flow story consistent throughout line editor fix clunky unclear writing create tight powerful prose Jami Gold provides comprehensive list skill copy editor line editor use editing process Final Polish believe final version text you’re ready publish might want hire proofreader andor factchecker proofreader review entire text make sure new typo slipped previous editing revision stage Proofreaders also spot errant punctuation irregular formatting outstanding inconsistency proofreader make extensive change text instead fix glaring error factchecker vital part editing team especially include information real world manuscript factchecker verify name date location timeline similar detail ensure text accurate Photo Nick Morrison Unsplash Final Word Editing software apps Editing software apps like Grammarly Hemingway Editor even Microsoft’s grammar spellcheck helpful tool writing cannot replace wellqualified editor Writers use tool produce cleanest document possible provide editor none tool 100 correct using tool writer need understand grammar word usage evaluate suggestion determine one appropriate addition tool cannot ass text writer’s creative decision eg characterization poetic wording style guide requirement eg Chicago Manual Style inhouse guide specific style writing eg author’s voice “legalese” corporate communication sidebyside comparison one grammar tool versus human editor check David Alan’s review Tonya Thompson’s reviewTags Professional Editing Writing Creativity Publishing |
927 | Boiling vs. Filtration: Which Choice Is Safer? | Microbes | Lifestyle
Boiling vs. Filtration: Which Choice Is Safer?
Filtration only reduces microbial load and can’t eliminate viruses. But boiling does the trick.
Image by infopaul70 from Pixabay
“Microorganisms with a small infectious dose — Giardia, Cryptosporidium, and Shigella species; hepatitis A; enteric viruses; and enterohemorrhagic Escherichia coli — may cause illnesses even when a small volume of contaminated water is inadvertently swallowed…,” says Charles D. Ericsson, MD and infectious disease specialist in Houston, and colleagues in the journal of Clinical Infectious Diseases.
“Because total immunity does not develop for most enteric pathogens, reinfection may occur,” explains Ericsson et al. Most enteric pathogens can also survive in cold/frozen water for months. “Estimations of water safety cannot reliably be made on the basis of the look, smell, and taste of water,” they added.
Nearly 2 billion people in low- and middle-income countries do not have proper sources of “microbiologically safe drinking water.” This causes an estimated 500,000 deaths — mostly children — annually. International or wilderness travellers should also be aware of the microbiologic safety of drinking water.
Filtered vs. Boiled
“Yes, it is important to boil all tap water even if it has been filtered. Most water filters (activated carbon, charcoal, pitcher filters, etc.) are not suitable for use on microbiologically unsafe water and do not kill bacteria or viruses,” explains John Woodard, a water specialist at Fresh Water Systems Inc.
The Centers for Disease Control and Prevention (CDC) also states that “filtration is not effective in removing viruses,” but boiling water for just one minute does the trick.
Filtration lowers pathogen load whereas boiling kills all waterborne pathogens (Cryptosporidium, Giardia, Campylobacter, Salmonella, Shigella, E. coli, enterovirus, hepatitis A, norovirus, rotavirus), CDC says.
Magic of Boiled Water
Boiling water is a ‘golden rule’ followed by communities in rural areas of countries like China, Mongolia, Indonesia, Malaysia, etc. They have fewer diarrheal victims from contaminated water as a result, according to a 2017 meta-analysis of 27 studies. “Boiling has a strong and highly significant protective effect for nonspecific diarrheal disease outcomes,” write the authors from the Division of Epidemiology, School of Public Health, University of California.
Even in cities, the boil order — or boil water advisory — is launched in times of natural disasters, pipe leakages or chemical spills where chances are that drinking water is contaminated by waterborne pathogens. In such times, citizens are advised to drink only bottled or boiled (at least 1 min) water.
Why? Studies have concluded that 70°C exposure for one minute is sufficient to kill 99.999% of waterborne microbes, says the World Health Organization. The magic of boiling lies in the fact that protein — an essential component to life, even viruses — denature at high temperatures.
Note that some microbes still survive the boiling process but, fortunately, they don’t cause diseases when ingested. The Clostridium spores, for example, are ubiquitous in nature and can withstand 100°C for a long period, but isn't an intestinal pathogen.
Adolescents and adults probably will do fine with just filtered water. But nothing beats boiled water for microbiologically safe water. Howard Zucker, MD from the Department of Health, New York advised the provision of boiled drinking water for infants, children or the elderly with a frailer immune system. | https://medium.com/microbial-instincts/boiling-vs-filtration-which-choice-is-safer-eeca0f132442 | ['Shin Jie Yong'] | 2020-03-27 12:29:23.934000+00:00 | ['Health', 'Advice', 'Education', 'Life', 'Science'] | Title Boiling v Filtration Choice SaferContent Microbes Lifestyle Boiling v Filtration Choice Safer Filtration reduces microbial load can’t eliminate virus boiling trick Image infopaul70 Pixabay “Microorganisms small infectious dose — Giardia Cryptosporidium Shigella specie hepatitis enteric virus enterohemorrhagic Escherichia coli — may cause illness even small volume contaminated water inadvertently swallowed…” say Charles Ericsson MD infectious disease specialist Houston colleague journal Clinical Infectious Diseases “Because total immunity develop enteric pathogen reinfection may occur” explains Ericsson et al enteric pathogen also survive coldfrozen water month “Estimations water safety cannot reliably made basis look smell taste water” added Nearly 2 billion people low middleincome country proper source “microbiologically safe drinking water” cause estimated 500000 death — mostly child — annually International wilderness traveller also aware microbiologic safety drinking water Filtered v Boiled “Yes important boil tap water even filtered water filter activated carbon charcoal pitcher filter etc suitable use microbiologically unsafe water kill bacteria viruses” explains John Woodard water specialist Fresh Water Systems Inc Centers Disease Control Prevention CDC also state “filtration effective removing viruses” boiling water one minute trick Filtration lower pathogen load whereas boiling kill waterborne pathogen Cryptosporidium Giardia Campylobacter Salmonella Shigella E coli enterovirus hepatitis norovirus rotavirus CDC say Magic Boiled Water Boiling water ‘golden rule’ followed community rural area country like China Mongolia Indonesia Malaysia etc fewer diarrheal victim contaminated water result according 2017 metaanalysis 27 study “Boiling strong highly significant protective effect nonspecific diarrheal disease outcomes” write author Division Epidemiology School Public Health University California Even city boil order — boil water advisory — launched time natural disaster pipe leakage chemical spill chance drinking water contaminated waterborne pathogen time citizen advised drink bottled boiled least 1 min water Studies concluded 70°C exposure one minute sufficient kill 99999 waterborne microbe say World Health Organization magic boiling lie fact protein — essential component life even virus — denature high temperature Note microbe still survive boiling process fortunately don’t cause disease ingested Clostridium spore example ubiquitous nature withstand 100°C long period isnt intestinal pathogen Adolescents adult probably fine filtered water nothing beat boiled water microbiologically safe water Howard Zucker MD Department Health New York advised provision boiled drinking water infant child elderly frailer immune systemTags Health Advice Education Life Science |
928 | How to Start Writing a Novel | How to Start Writing a Novel
Tips on Jumping into the Narrative Waters
Photo by Arisa Chattasa on Unsplash
A couple of years ago, I reached out to aspiring writers to ask what challenges they faced in their writing. More than 2,000 writers have answered my survey, 5 Quick Questions About Your Writing Life. 66% of respondents said the hardest part of writing a novel is getting started. Maintaining a writing habit came in second.
For me, maintaining a habit for the long haul is the hardest part. This was true when I wrote my first novel 17 years ago, and it’s still true today, six novels in. Beginning is fun and full of promise. It’s the novel’s middle distance where I start to get weary, wondering how I’ll reach the other side. In the beginning, you don’t yet know what can go wrong, and how long it will take to fix it.
I’ll address writing habits in a separate post, but let’s tackle the big one first: how do you sit down in the chair and begin the hard work of getting the words on the page?
Step One
Get past thinking, “I’m writing a novel.” Instead, tell yourself, “I’m writing a few words today” or “I’m writing a piece of my novel today.”
Writing a novel is a daunting challenge and a major, time-consuming endeavor. Looking from the starting line to the finish line, miles away, can be mentally paralyzing. The only way to start your novel without psyching yourself out is to break it up into small, daily tasks. Approach each day as a mini-project, not a major project. The mini-project is a scene, a chapter, or a page for that day.
Step Two
You don’t have to know where you’re going. You don’t need an outline. You don’t even need a plot to get started. Just come up with these three things:
a specific (interesting) person
in a specific place and time
facing a specific problem
Who is the protagonist? What trouble is he or she in? Where and when does your story take place?
Character, conflict, setting. From these three elements, all of the rest flows.
Step Three
Come up with a situation that is worthy of a novel. The situation has to be big enough, the problem great enough, to sustain a novel for 250–400 pages. Beyond that, the protagonist has to be deeply invested in the problem. The stakes have to be high. You have to give the reader a reason to care about what happens to your protagonist, a reason to care about the outcome of this situation.
Watch my quick lesson on how to determine if your situation is novel-worthy.
So, if you’re having trouble getting started, do this:
Stop saying, “I’m writing a novel,” and say instead, “I’m writing a piece of my novel today,” or even just, “I’m exploring ideas for my novel today.”
Remember your three essential things: person, place, desire.
Determine if your situation is novel-worthy.
Michelle Richmond is the New York Times bestselling author of five novels and two story collections, including the psychological thriller The Marriage Pact, which has been published in 30 languages. She is the founder of Fiction Master Class and Novel in 5. | https://medium.com/a-writers-life/how-to-start-writing-a-novel-911d5ec45d16 | ['Michelle Richmond'] | 2020-12-11 19:40:16.718000+00:00 | ['Novel Writing', 'Writing', 'How To Start Writing', 'How To Write A Book', 'Creativity'] | Title Start Writing NovelContent Start Writing Novel Tips Jumping Narrative Waters Photo Arisa Chattasa Unsplash couple year ago reached aspiring writer ask challenge faced writing 2000 writer answered survey 5 Quick Questions Writing Life 66 respondent said hardest part writing novel getting started Maintaining writing habit came second maintaining habit long haul hardest part true wrote first novel 17 year ago it’s still true today six novel Beginning fun full promise It’s novel’s middle distance start get weary wondering I’ll reach side beginning don’t yet know go wrong long take fix I’ll address writing habit separate post let’s tackle big one first sit chair begin hard work getting word page Step One Get past thinking “I’m writing novel” Instead tell “I’m writing word today” “I’m writing piece novel today” Writing novel daunting challenge major timeconsuming endeavor Looking starting line finish line mile away mentally paralyzing way start novel without psyching break small daily task Approach day miniproject major project miniproject scene chapter page day Step Two don’t know you’re going don’t need outline don’t even need plot get started come three thing specific interesting person specific place time facing specific problem protagonist trouble story take place Character conflict setting three element rest flow Step Three Come situation worthy novel situation big enough problem great enough sustain novel 250–400 page Beyond protagonist deeply invested problem stake high give reader reason care happens protagonist reason care outcome situation Watch quick lesson determine situation novelworthy you’re trouble getting started Stop saying “I’m writing novel” say instead “I’m writing piece novel today” even “I’m exploring idea novel today” Remember three essential thing person place desire Determine situation novelworthy Michelle Richmond New York Times bestselling author five novel two story collection including psychological thriller Marriage Pact published 30 language founder Fiction Master Class Novel 5Tags Novel Writing Writing Start Writing Write Book Creativity |
929 | If It Was Easy, Your Friends Would Be (Successfully) Doing It Too | Tell me if this one sounds familiar. You reconnect with an old friend and in the course of the conversation, you tell them you’re a blogger or that you simply write online for a living.
In response, they tell you they think it’s amazing that’s even a possibility these days, and that they’ve been thinking about doing it too.
Sigh.
Now, there are endless variations of this one conversation, although, on some days, I feel pretty damn sure I’ve heard them all. Sometimes, the talk continues and the other person starts addressing all of the things you haven’t done. As in, maybe you shouldn’t really call yourself a writer if you write online for a living but have never published a book. Or, perhaps you can’t consider yourself a true professional if you don’t also sell a course or have a podcast, etc. You know, something other than writing.
Like it or not, people often have some very strong opinions about the stuff a creative should and shouldn’t, or can and can’t do. And all of those ideas differ from person to person, of course.
Worse yet, it can be hard for friends to really take you seriously when do creative work. I mean, sure. They’ll share that Buzzfeed article a hundred times and photograph a stack of their current books on tap, but sometimes, it feels like pulling teeth just to get your friends to read your stuff — even when it’s utterly adjacent to the art they already enjoy. The longer they’ve known you, the less likely it might be. In a way, I suppose that makes a certain sort of sense. People who know you from years earlier, long before you knew you could have such a creative career don’t always see you. Not really. Not the you who dreams (and does) big things.
After having this conversation once again this week, the one where a long-lost friend says in passing that it’s amazing anyone can be a blogger, and perhaps they’ll do the same thing — it got me thinking.
Maybe these friends don’t know how to be happy for us when we find a way to become successful in a creative career. And maybe that’s not entirely their fault.
Maybe it’s how they’ve grown up to think. | https://medium.com/curious/if-it-was-easy-your-friends-would-be-successfully-doing-it-too-8b02d77bc448 | ['Shannon Ashley'] | 2020-12-09 04:23:36.407000+00:00 | ['Creativity', 'Writing', 'Blogging', 'Self Improvement', 'Life Lessons'] | Title Easy Friends Would Successfully TooContent Tell one sound familiar reconnect old friend course conversation tell you’re blogger simply write online living response tell think it’s amazing that’s even possibility day they’ve thinking Sigh endless variation one conversation although day feel pretty damn sure I’ve heard Sometimes talk continues person start addressing thing haven’t done maybe shouldn’t really call writer write online living never published book perhaps can’t consider true professional don’t also sell course podcast etc know something writing Like people often strong opinion stuff creative shouldn’t can’t idea differ person person course Worse yet hard friend really take seriously creative work mean sure They’ll share Buzzfeed article hundred time photograph stack current book tap sometimes feel like pulling teeth get friend read stuff — even it’s utterly adjacent art already enjoy longer they’ve known le likely might way suppose make certain sort sense People know year earlier long knew could creative career don’t always see really dream big thing conversation week one longlost friend say passing it’s amazing anyone blogger perhaps they’ll thing — got thinking Maybe friend don’t know happy u find way become successful creative career maybe that’s entirely fault Maybe it’s they’ve grown thinkTags Creativity Writing Blogging Self Improvement Life Lessons |
930 | Ambiguity Defines the Human Experience | Ambiguity Defines the Human Experience
We would be mistaken to emulate the certainty of our computers
Photo: SEAN GLADWELL/Getty Images
You know that moment when a dog sees something he doesn’t quite understand? When he tilts his head a little bit to one side, as if viewing the perplexing phenomenon from another angle will help? That state of confusion, that huh?, may be a problem for the dog, but it’s awfully cute to us. That’s because for humans, a state of momentary confusion offers not just frustration but an opening.
Team Human has the ability to tolerate and even embrace ambiguity. The stuff that makes our thinking and behavior messy, confusing, or anomalous is both our greatest strength and our greatest defense against the deadening certainty of machine logic.
Yes, we’re living in a digital age, where definitive answers are ready at the click. Every question seems to be one web search away. But we are mistaken to emulate the certainty of our computers. They are definitive because they have to be. Their job is to resolve questions, turn inputs into outputs, choose between one or zero. Even at extraordinary resolutions, the computer must decide if a pixel is here or there, if a color is this blue or that blue, if a note is this frequency or that one. There is no in-between state. No ambiguity is permitted.
But it’s precisely this ambiguity — and the ability to embrace it — that characterizes the collectively felt human experience. Does God exist? Do we have an innate purpose? Is love real? These are not simple yes-or-no questions. They’re yes-and-no ones: Mobius strips or Zen koans that can only be engaged from multiple perspectives and sensibilities. We have two brain hemispheres, after all. It takes both to create the multidimensional conceptual picture we think of as reality.
Besides, the brain doesn’t capture and store information like a computer does. It’s not a hard drive. There’s no one-to-one correspondence between things we’ve experienced and data points in the brain. Perception is not receptive, but active. That’s why we can have experiences and memories of things that didn’t “really” happen. Our eyes take in 2D fragments and the brain renders them as 3D images. Furthermore, we take abstract concepts and assemble them into a perceived thing or situation. We don’t see “fire truck” so much as gather related details and then manufacture a fire truck. And if we’re focusing on the fire truck, we may not even notice the gorilla driving it.
Our ability to be conscious — to have that sense of what-is-it-like-to-see-something — depends on our awareness of our participation in perception. We feel ourselves putting it all together. And it’s the open-ended aspects of our experience that keep us conscious of our participation in interpreting them. Those confusing moments provide us with opportunities to experience our complicity in reality creation.
It’s also what allows us to do all those things that computers have been unable to learn: how to contend with paradox, engage with irony, or even interpret a joke. Doing any of this depends on what neuroscientists call relevance theory. We don’t think and communicate in whole pieces, but infer things based on context. We receive fragments of information from one another and then use what we know about the world to recreate the whole message ourselves. It’s how a joke arrives in your head: Some assembly is required. That moment of “getting it” — putting it together oneself — is the pleasure of active reception. Ha! and aha! are very close relatives.
Computers can’t do this. They can recognize if a social media message is sarcastic or not — yes or no — but they can’t appreciate the dynamic contrast between word and meaning. Computers work closer to the way primitive reptile brains do. They train on the foreground, fast-moving objects, and surface perceptions. There’s a fly; eat it. The human brain, with its additional lobes, can also reflect on the greater spatial, temporal, and logical contexts of any particular event. How did that fly get in the room if the windows have been closed?
Human beings can relate the figure to the ground. We can hold onto both, and experience the potential difference or voltage between them. The fly doesn’t belong here. Like the rack focus in a movie scene, we can compare and contrast the object to its context. We can ponder the relationship of the part to the whole, the individual to the collective, and the human to the team. | https://medium.com/team-human/ambiguity-defines-the-human-experience-36dad5667ac6 | ['Douglas Rushkoff'] | 2020-11-26 16:53:35.865000+00:00 | ['Humanity', 'Self', 'Society', 'Book Excerpt', 'Psychology'] | Title Ambiguity Defines Human ExperienceContent Ambiguity Defines Human Experience would mistaken emulate certainty computer Photo SEAN GLADWELLGetty Images know moment dog see something doesn’t quite understand tilt head little bit one side viewing perplexing phenomenon another angle help state confusion huh may problem dog it’s awfully cute u That’s human state momentary confusion offer frustration opening Team Human ability tolerate even embrace ambiguity stuff make thinking behavior messy confusing anomalous greatest strength greatest defense deadening certainty machine logic Yes we’re living digital age definitive answer ready click Every question seems one web search away mistaken emulate certainty computer definitive job resolve question turn input output choose one zero Even extraordinary resolution computer must decide pixel color blue blue note frequency one inbetween state ambiguity permitted it’s precisely ambiguity — ability embrace — characterizes collectively felt human experience God exist innate purpose love real simple yesorno question They’re yesandno one Mobius strip Zen koan engaged multiple perspective sensibility two brain hemisphere take create multidimensional conceptual picture think reality Besides brain doesn’t capture store information like computer It’s hard drive There’s onetoone correspondence thing we’ve experienced data point brain Perception receptive active That’s experience memory thing didn’t “really” happen eye take 2D fragment brain render 3D image Furthermore take abstract concept assemble perceived thing situation don’t see “fire truck” much gather related detail manufacture fire truck we’re focusing fire truck may even notice gorilla driving ability conscious — sense whatisitliketoseesomething — depends awareness participation perception feel putting together it’s openended aspect experience keep u conscious participation interpreting confusing moment provide u opportunity experience complicity reality creation It’s also allows u thing computer unable learn contend paradox engage irony even interpret joke depends neuroscientist call relevance theory don’t think communicate whole piece infer thing based context receive fragment information one another use know world recreate whole message It’s joke arrives head assembly required moment “getting it” — putting together oneself — pleasure active reception Ha aha close relative Computers can’t recognize social medium message sarcastic — yes — can’t appreciate dynamic contrast word meaning Computers work closer way primitive reptile brain train foreground fastmoving object surface perception There’s fly eat human brain additional lobe also reflect greater spatial temporal logical context particular event fly get room window closed Human being relate figure ground hold onto experience potential difference voltage fly doesn’t belong Like rack focus movie scene compare contrast object context ponder relationship part whole individual collective human teamTags Humanity Self Society Book Excerpt Psychology |
931 | Advantages and Disadvantages of Artificial Intelligence | Artificial Intelligence is one of the emerging technologies which tries to simulate human reasoning in AI systems. invented the term John McCarthy Artificial Intelligence in the year 1950.
Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. An attempt will be made to find how to make machines use language, form abstractions, and concepts, solve kinds of problems now reserved for humans and improve themselves.
Artificial Intelligence is the ability of a computer program to learn and think. Everything can be considered Artificial intelligence if it involves a program doing something that we would normally think would rely on the intelligence of a human. In this article, we will discuss the different advantages and disadvantages of Artificial Intelligence.
Advantages of Artificial Intelligence
Disadvantages of Artificial Intelligence
The advantages of Artificial intelligence applications are enormous and can revolutionize any professional sector. Let’s see some of them.
Advantages of Artificial Intelligence
1) Reduction in Human Error
The phrase “ “ was born because humans make mistakes from time to time. Computers, however, do not make these mistakes if they are programmed properly. With human errorArtificial intelligence, the decisions are taken from the previously gathered information applying a certain set of algorithms. So errors are reduced and the chance of reaching accuracy with a greater degree of precision is a possibility.
Example: In Weather Forecasting using AI they have reduced the majority of human error.
2) Takes risks instead of Humans
This is one of the biggest advantages of Artificial intelligence. We can overcome many risky limitations of humans by developing an AI Robot which in turn can do the risky things for us. Let it be going to mars, defuse a bomb, explore the deepest parts of oceans, mining for coal and oil, it can be used effectively in any kinds of natural or man-made disasters.
Example: Have you heard about the Chernoby l nuclear power plant explosion in Ukraine? At that time there were no AI-powered robots that can help us to minimize the effect of radiation by controlling the fire in the early stages, as any human who went close to the core was dead in a matter of minutes. They eventually poured sand and boron from helicopters from a mere distance.
AI Robots can be used in such situations where human intervention can be hazardous.
3) Available 24×7
An Average human will work for 4–6 hours a day excluding the breaks. Humans are built in such a way to get some time out for refreshing themselves and get ready for a new day of work and they even have weekly off been to stay intact with their work-life and personal life. But using AI we can make machines work 24×7 without any breaks and they don’t even get bored, unlike humans.
Example: Educational Institutes and Helpline centers are getting many queries and issues which can be handled effectively using AI.
4) Helping in Repetitive Jobs
In our day-to-day work, we will be performing many repetitive works like sending a thanking mail, verifying certain documents for errors, and many more things. Using artificial intelligence we can productively automate these mundane tasks and can even remove “ boring “ tasks for humans and free them up to be increasingly creative.
Example: In banks, we often see many verifications of documents in order to get a loan which is a repetitive task for the owner of the bank. Using AI Cognitive Automation the owner can speed up the process of verifying the documents by which both the customers and the owner will be benefited.
5) Digital Assistance
Some of the highly advanced organizations use digital assistants to interact with users which saves the need for human resources. The digital assistant also used in many websites to provide things that users want. We can chat with them about what we are looking for. Some chatbots are designed in such a way that it becomes hard to determine that we’re chatting with a chatbot or a human being.
Example: We all know that organizations have a customer support team that needs to clarify the doubts and queries of the customers. Using AI the organizations can set up a Voicebot or Chatbot which can help customers with all their queries. We can see many organizations already started using them on their websites and mobile applications.
6) Faster Decisions:
Using AI alongside other technologies we can make machines take decisions faster than a human and carry out actions quicker. While taking a decision human will analyze many factors both emotionally and practically but AI-powered machine works on what it is programmed and delivers the results in a faster way.
Example: We all have played a Chess game in Windows. It is nearly impossible to beat the CPU in the hard mode because of the AI behind that game. It will take the best possible step in a very short time according to the algorithms used behind it.
7) Daily Applications
Daily applications such as Apple’s Siri, Window’s Cortana, Google’s OK Google are frequently used in our daily routine whether it is for searching a location, taking a selfie, making a phone call, replying to a mail, and many more.
Example: Around 20 years ago, when we are planning to go somewhere we used to ask a person who already went there for directions. But now all we have to do is say “ OK Google where is Visakhapatnam”. It will show you Visakhapatnam’s location on google map and the best path between you and Visakhapatnam.
8) New Inventions:
AI is powering many inventions in almost every domain which will help humans solve the majority of complex problems.
Example: Recently doctors are able to predict breast cancer in women at earlier stages using advanced AI-based technologies.
Disadvantages of Artificial Intelligence
1) High Costs of Creation
As AI is updating every day the hardware and software need to get updated with time to meet the latest requirements. Machines need repairing and maintenance which need plenty of costs. Its creation requires huge costs as they are very complex machines.
2) Making Humans Lazy
AI is making humans lazy with its applications automating the majority of the work. Humans tend to get addicted to these inventions which can cause a problem for future generations.
3) Unemployment:
As AI is replacing the majority of the repetitive tasks and other works with robots, human interference is becoming less which will cause a major problem in the employment standards. Every organization is looking to replace the minimum qualified individuals with AI robots that can do similar work with more efficiency.
4) No Emotions
There is no doubt that machines are much better when it comes to working efficiently but they cannot replace the human connection that makes the team. Machines cannot develop a bond with humans which is an essential attribute when comes to Team Management.
5) Lacking Out of Box Thinking
Machines can perform only those tasks which they are designed or programmed to do, anything out of that they tend to crash or give irrelevant outputs which could be a major backdrop.
SUMMARY:
These are some advantages and disadvantages of Artificial Intelligence. Every new invention or breakthrough will have both, but we as humans need to take care of that and use the positive sides of the invention to create a better world. Clearly, artificial intelligence has massive potential advantages. The key for humans will ensure the “ rise of the robots “ doesn’t get out of hand. Some people also say that Artificial intelligence can destroy human civilization if it goes into the wrong hands. But still, none of the AI application made at that scale that can destroy or enslave humanity.
With this, we have come to the end of our article on various advantages and disadvantages of Artificial Intelligence.
With this, we come to the end of this blog on Data Science vs Machine Learning. With this, we come to the end of this article. If you have any queries regarding this topic, please leave a comment below and we’ll get back to you. If you wish to check out more articles on the market’s most trending technologies like Python, DevOps, Ethical Hacking, then you can refer to Edureka’s official site.
Do look out for other articles in this series that will explain the various other aspects of Data Science. | https://medium.com/edureka/advantages-and-disadvantages-of-ai-b01533ffbcb8 | ['Sahiti Kappagantula'] | 2020-12-30 05:34:08.127000+00:00 | ['Artificial Intelligence', 'AI', 'Data Science', 'Advantages Of Ai', 'Deep Learning'] | Title Advantages Disadvantages Artificial IntelligenceContent Artificial Intelligence one emerging technology try simulate human reasoning AI system invented term John McCarthy Artificial Intelligence year 1950 Every aspect learning feature intelligence principle precisely described machine made simulate attempt made find make machine use language form abstraction concept solve kind problem reserved human improve Artificial Intelligence ability computer program learn think Everything considered Artificial intelligence involves program something would normally think would rely intelligence human article discus different advantage disadvantage Artificial Intelligence Advantages Artificial Intelligence Disadvantages Artificial Intelligence advantage Artificial intelligence application enormous revolutionize professional sector Let’s see Advantages Artificial Intelligence 1 Reduction Human Error phrase “ “ born human make mistake time time Computers however make mistake programmed properly human errorArtificial intelligence decision taken previously gathered information applying certain set algorithm error reduced chance reaching accuracy greater degree precision possibility Example Weather Forecasting using AI reduced majority human error 2 Takes risk instead Humans one biggest advantage Artificial intelligence overcome many risky limitation human developing AI Robot turn risky thing u Let going mar defuse bomb explore deepest part ocean mining coal oil used effectively kind natural manmade disaster Example heard Chernoby l nuclear power plant explosion Ukraine time AIpowered robot help u minimize effect radiation controlling fire early stage human went close core dead matter minute eventually poured sand boron helicopter mere distance AI Robots used situation human intervention hazardous 3 Available 24×7 Average human work 4–6 hour day excluding break Humans built way get time refreshing get ready new day work even weekly stay intact worklife personal life using AI make machine work 24×7 without break don’t even get bored unlike human Example Educational Institutes Helpline center getting many query issue handled effectively using AI 4 Helping Repetitive Jobs daytoday work performing many repetitive work like sending thanking mail verifying certain document error many thing Using artificial intelligence productively automate mundane task even remove “ boring “ task human free increasingly creative Example bank often see many verification document order get loan repetitive task owner bank Using AI Cognitive Automation owner speed process verifying document customer owner benefited 5 Digital Assistance highly advanced organization use digital assistant interact user save need human resource digital assistant also used many website provide thing user want chat looking chatbots designed way becomes hard determine we’re chatting chatbot human Example know organization customer support team need clarify doubt query customer Using AI organization set Voicebot Chatbot help customer query see many organization already started using website mobile application 6 Faster Decisions Using AI alongside technology make machine take decision faster human carry action quicker taking decision human analyze many factor emotionally practically AIpowered machine work programmed delivers result faster way Example played Chess game Windows nearly impossible beat CPU hard mode AI behind game take best possible step short time according algorithm used behind 7 Daily Applications Daily application Apple’s Siri Window’s Cortana Google’s OK Google frequently used daily routine whether searching location taking selfie making phone call replying mail many Example Around 20 year ago planning go somewhere used ask person already went direction say “ OK Google Visakhapatnam” show Visakhapatnam’s location google map best path Visakhapatnam 8 New Inventions AI powering many invention almost every domain help human solve majority complex problem Example Recently doctor able predict breast cancer woman earlier stage using advanced AIbased technology Disadvantages Artificial Intelligence 1 High Costs Creation AI updating every day hardware software need get updated time meet latest requirement Machines need repairing maintenance need plenty cost creation requires huge cost complex machine 2 Making Humans Lazy AI making human lazy application automating majority work Humans tend get addicted invention cause problem future generation 3 Unemployment AI replacing majority repetitive task work robot human interference becoming le cause major problem employment standard Every organization looking replace minimum qualified individual AI robot similar work efficiency 4 Emotions doubt machine much better come working efficiently cannot replace human connection make team Machines cannot develop bond human essential attribute come Team Management 5 Lacking Box Thinking Machines perform task designed programmed anything tend crash give irrelevant output could major backdrop SUMMARY advantage disadvantage Artificial Intelligence Every new invention breakthrough human need take care use positive side invention create better world Clearly artificial intelligence massive potential advantage key human ensure “ rise robot “ doesn’t get hand people also say Artificial intelligence destroy human civilization go wrong hand still none AI application made scale destroy enslave humanity come end article various advantage disadvantage Artificial Intelligence come end blog Data Science v Machine Learning come end article query regarding topic please leave comment we’ll get back wish check article market’s trending technology like Python DevOps Ethical Hacking refer Edureka’s official site look article series explain various aspect Data ScienceTags Artificial Intelligence AI Data Science Advantages Ai Deep Learning |
932 | 12 Colab Notebooks that matter | Get this newsletter By signing up, you will create a Medium account if you don’t already have one. Review our Privacy Policy for more information about our privacy practices.
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Medium sent you an email at to complete your subscription. | https://medium.com/merzazine/12-colab-notebooks-that-matter-689f79b5a2e4 | ['Vlad Alex', 'Merzmensch'] | 2020-06-10 15:01:50.238000+00:00 | ['AI', 'Published Tds', 'Merznlp', 'Artificial Intelligence'] | Title 12 Colab Notebooks matterContent Get newsletter signing create Medium account don’t already one Review Privacy Policy information privacy practice Check inbox Medium sent email complete subscriptionTags AI Published Tds Merznlp Artificial Intelligence |
933 | A New Thought Regarding Agatha Christie’s Crime Fiction | A New Thought Regarding Agatha Christie’s Crime Fiction
Specializing in murders of quiet, domestic interest
Many years ago I had a friend who was going through an Agatha Christie binge. Actually, both he and his wife were thoroughly absorbed in reading her crime novels, ever trying to solve the crimes before Miss Marple or the little grey cells of Hercule Poirot could.
Public domain.
At the time, I was involved in other pursuits, reading “serious literature” in preparation for a writing career. I can’t lay all the blame on Covid, but my reading in 2020 has included a long list of books from the John Sanford and Agatha Christie catalogs. In reading the latter, something dawned on me that I hadn’t noticed before.
“Ah, my friend, one may live in a big house and yet have no comfort.” — Hercule Poirot
How many of you grew up in a home with maids and butlers? As I reflect on the numerous Christie stories I’ve read, I can’t seem to recall any involving a family like my own. In addition to murders taking place in exotic places, such as the Nile or on the Orient Express, we have countless stories of people with wealth, whose servants are under suspicion, or who have both city and country homes.
I can only guess that part of the appeal of her work may have been the voyeuristic aspect of peeking in on the lifestyles of the rich and, sometimes, famous. It was easy for her to write accurately about this lifestyle, for it was the lifestyle she was acquainted with. She didn’t have to make it up. In her autobiography she states that she herself grew up with three servants in her household.
“Servants, of course, were not a particular luxury-it was not a case of only the rich having them; the only difference was that the rich had more,” she wrote in her autobiography.
This is a very different set of life circumstances than my father’s grandparents were experiencing in Eastern Kentucky at the time. (Agatha Christie was born in 1890.) They were illiterate and poor, but resourceful, scratching out a livelihood halfway up the side of a mountain, and even being generous.
Yet, even growing up with a nurse and nanny, Ms. Christie claims that her family was not rich. Rich people had cars. Her family did not.
Two other areas of expertise show up in her stories. When it comes to poisons, her knowledge is vast. That is, the more stories you read, it’s surprising how many ways to poison people there are. She gained this knowledge first hand. No, not first hand by poisoning people, but by working in a dispensary during the two world wars.
Public domain.
Another area of specialized knowledge came from marrying an archaeologist in 1930. While her second husband was actively exploring digs in the Middle East, she was no doubt picking his brain and digging for details that would give veracity to her murders in Egypt and elsewhere.
She’s to be commended for her tenacity. Her first six books were rejected by publishers. Nevertheless, she persisted despite the lack of interest from editors, until a door opened in 1920 and “the rest is history.” She became a master of the craft. One title alone, And Then There Were None, sold 100 million copies worldwide.
If these are not new thoughts for you, then I suppose I’m just late to the parade. One of the first bits of advice that young writers are frequently given is this: Write about what you know. This may be why you don’t find butlers and housemaids in my stories, whereas hers are awash with them. | https://medium.com/books-are-our-superpower/a-new-thought-regarding-agatha-christies-crime-fiction-93ea26633675 | ['Ed Newman'] | 2020-11-16 08:31:54.674000+00:00 | ['People', 'Books', 'Crime', 'Fiction', 'Observations'] | Title New Thought Regarding Agatha Christie’s Crime FictionContent New Thought Regarding Agatha Christie’s Crime Fiction Specializing murder quiet domestic interest Many year ago friend going Agatha Christie binge Actually wife thoroughly absorbed reading crime novel ever trying solve crime Miss Marple little grey cell Hercule Poirot could Public domain time involved pursuit reading “serious literature” preparation writing career can’t lay blame Covid reading 2020 included long list book John Sanford Agatha Christie catalog reading latter something dawned hadn’t noticed “Ah friend one may live big house yet comfort” — Hercule Poirot many grew home maid butler reflect numerous Christie story I’ve read can’t seem recall involving family like addition murder taking place exotic place Nile Orient Express countless story people wealth whose servant suspicion city country home guess part appeal work may voyeuristic aspect peeking lifestyle rich sometimes famous easy write accurately lifestyle lifestyle acquainted didn’t make autobiography state grew three servant household “Servants course particular luxuryit case rich difference rich more” wrote autobiography different set life circumstance father’s grandparent experiencing Eastern Kentucky time Agatha Christie born 1890 illiterate poor resourceful scratching livelihood halfway side mountain even generous Yet even growing nurse nanny Ms Christie claim family rich Rich people car family Two area expertise show story come poison knowledge vast story read it’s surprising many way poison people gained knowledge first hand first hand poisoning people working dispensary two world war Public domain Another area specialized knowledge came marrying archaeologist 1930 second husband actively exploring dig Middle East doubt picking brain digging detail would give veracity murder Egypt elsewhere She’s commended tenacity first six book rejected publisher Nevertheless persisted despite lack interest editor door opened 1920 “the rest history” became master craft One title alone None sold 100 million copy worldwide new thought suppose I’m late parade One first bit advice young writer frequently given Write know may don’t find butler housemaid story whereas awash themTags People Books Crime Fiction Observations |
934 | What if everything was about reward prediction error? | What if everything was about reward prediction error?
A note on how our lives would look like if we could perceive joy only by our errors in predicting rewards.
WARNING: This article is not supposed to be scientifically precise. Rather, it is a playful discussion about an imaginary scenario inspired by scientific findings
Dopamine, enjoyment, and reward prediction error
It is generally believed that dopamine is what makes us feel happy and pleased, and there is scientific evidence for the release of dopamine at the time of accomplishing something or receiving rewards. However, many studies have shown that most of the neurons responsible for the release of dopamine, usually called dopaminergic neurons, are not triggered by the reward itself; rather, they are triggered by the difference between the achieved reward and the expected reward, what is called “reward prediction error” in models of reinforcement learning¹.
It is somehow funny; it means that no matter how big the reward is, if you expect it, then there is no release of dopamine according to these neurons. Or even worse, you may accomplish something and get a reward, but because you might have had a higher expectation, the actual value of the reward gives you a feeling of disappointment and leads to a decrease in the dopamine release, due to the inhibition of the dopaminergic neurons. In other words, these neurons are triggered only if the achieved reward is greater than what we have expected, i.e. only if the reward prediction error is positive².
I do not intend to talk about neuroscience, biology, or reinforcement learning in this article. Rather, I would like to take the mentioned scientific facts as inspiration, imagine a simplistic world where the reward prediction error is the only reason for joy, and discuss what enjoyment is like in such a world.
“Imagine all the people” enjoying reward prediction errors³
Imagine an abstract simplistic world where (1) people perceive joy and pleasure only through the release of dopamine, and (2) dopamine release depends only on reward prediction errors. Such a world is quite different from the complex one we live in; in reality, neither dopamine is the only source of our happiness or our feeling of success, nor reward prediction error is the only trigger of dopamine. However, thinking about this abstract imaginary world simplifies the problem of “what do we enjoy?” and lets us discuss it with less distraction by other potentially relevant factors.
Following this thought process, we may get some interesting intuitions about our more complex real world. To do so, in what follows, I try to imagine and describe a few features of this simplistic imaginary world.
1. Joy is in the eye of the beholder
When the only thing that matters is the difference between the achieved and the expected rewards, then the expected reward is as important as the achieved reward in quantifying how enjoyable our experiences are. For example, if we increase both the expected and the achieved rewards by the same amount, then the reward prediction error, and hence the corresponding joy (or disappointment), does not change.
More intuitively, if you take a person and suddenly increase their income by a huge amount but also significantly increase their expectations about their day-to-day life, then you cannot be sure that you have made their life "happier". To make them have a happier life, assuming their income plays a role in their happiness, you need to increase their income faster than how they increase their expectations! With similar reasoning, there is no guarantee that rich people who are used to their luxurious lives enjoy the world more than the average.
In summary, in a world where everything is about reward prediction error, everything also takes up a more relative nature.
2. Always being right is boring
When the assumption is that we enjoy positive reward prediction errors, then, by assumption, there is no enjoyment in a world without errors. Hence, if there is no uncertainty in our environment, and if we can make objective predictions (i.e. without any subjective bias), then life becomes quite boring. For example, many people would agree that a big part of the joy in winning a game comes from the fact that winning is not certain in advance, and I believe such a certainty makes many of us less motivated to even get involved in that game.
Another interesting but a bit counter-intuitive example is lotteries; in general, since you do not expect much from a lottery, losing does not hurt much while winning is magnificent. But what happens if you know with certainty that you will win? In the imaginary world that we are discussing here, there is not any feeling of accomplishment at the moment of seeing your card numbers on the TV screen; yet because receiving a huge amount of money leads to lots of other activities with their own corresponding reward prediction errors, winning a lottery can still be quite fun later on and in the long term! Hence, in our imaginary world, the whole experience is indeed still pleasant, but I doubt that if, even in our real and complex world, the moment of announcing the winner of a lottery, when he or she has been known to us in advance and with certainty, gives us any special feeling.
In summary, to have some fun and joy or, on the other hand, to have some disappointment and frustration, we need to be wrong, at least once in a while.
3. Pessimism rocks?
If the joy is in the eye of the beholder, then, no matter what, we can make our lives joyful by decreasing our expectations. One who always expects the worst-case scenario is the one who always experiences a positive⁴ reward prediction error. In other words, to always enjoy the world, you should always be wrong with your expectations, but wrong in the right way!
However, it is not always easy to pick the worst-case scenario as our expectation, simply because many of our expectations are made unconsciously, particularly in the situations that we encounter quite often. Hence, for many of these situations, if we want to be pessimistic, we need to train ourselves; we need to stop adapting our expectations according to our environment and to stop being realistic. For example, if you are rich, you should stop getting used to being rich! To do so, you should always imagine bad scenarios more than good ones — like some kind of mental training. For example, if you are rich, you should repeatedly imagine huge drops in stock markets; then, even a stable trend looks amazing!
The problem is that if we think about imagination as a simulated version of the future, then for each imagined scenario we have also an imaginary reward prediction error, and to keep our expectations low through these mental training, we need to imagine more negative reward prediction errors than positive ones. The irony is at this point: if we want to enjoy more in reality, then we need to suffer more in our minds!⁵ Exactly the opposite holds true for optimism.
In summary, in non-familiar situations, a pessimistic mindset seems to be the most fortunate one. However, for day-to-day life events, pessimism rocks only if we can stand a catastrophic image of the world in our minds.
So what? (Traditionally called conclusion)
It is obvious that, for example, we can eat the same food many times in our life and enjoy it every single time. It is also not difficult to imagine (or to remember) enjoying watching a movie multiple times. It is indeed the case that there are activities that we can enjoy while perfectly matching our expectations, activities like running, biking, or swimming.
It is clear that reward matters on its own, and it is clear that not everything is about reward prediction error. However, as we saw, this very simple assumption can explain our feelings and emotions for a wide range of situations in our day-to-day life. More importantly, because of its simplicity, it is easy to use this assumption to find better and novel insights about "what makes us happy?" and "why does it make us happy?".
In the examples above, I find it fascinating that the necessity of a faster increase of income compared to the increase of expectations, the unintuitive nature of certain lotteries, and the pros and cons of pessimism can all be discussed elaborately in this imaginary world. Thinking about these situations in this imaginary world made me see things from different perspectives; it was like solving math problems while only a small handful of mathematical tools are allowed.
The insights and perspectives resulted from thinking about this imaginary world can become a useful part of our reasoning for making our future decisions; however, we should always be aware that we are not living in that simplistic world! | https://a-modirshanechi.medium.com/what-if-everything-was-about-reward-prediction-error-b423af871baf | ['Alireza Modirshanechi'] | 2020-12-30 07:35:06.727000+00:00 | ['Ideas', 'Reinforcement Learning', 'Dopamine', 'Psychology', 'Neuroscience'] | Title everything reward prediction errorContent everything reward prediction error note life would look like could perceive joy error predicting reward WARNING article supposed scientifically precise Rather playful discussion imaginary scenario inspired scientific finding Dopamine enjoyment reward prediction error generally believed dopamine make u feel happy pleased scientific evidence release dopamine time accomplishing something receiving reward However many study shown neuron responsible release dopamine usually called dopaminergic neuron triggered reward rather triggered difference achieved reward expected reward called “reward prediction error” model reinforcement learning¹ somehow funny mean matter big reward expect release dopamine according neuron even worse may accomplish something get reward might higher expectation actual value reward give feeling disappointment lead decrease dopamine release due inhibition dopaminergic neuron word neuron triggered achieved reward greater expected ie reward prediction error positive² intend talk neuroscience biology reinforcement learning article Rather would like take mentioned scientific fact inspiration imagine simplistic world reward prediction error reason joy discus enjoyment like world “Imagine people” enjoying reward prediction errors³ Imagine abstract simplistic world 1 people perceive joy pleasure release dopamine 2 dopamine release depends reward prediction error world quite different complex one live reality neither dopamine source happiness feeling success reward prediction error trigger dopamine However thinking abstract imaginary world simplifies problem “what enjoy” let u discus le distraction potentially relevant factor Following thought process may get interesting intuition complex real world follows try imagine describe feature simplistic imaginary world 1 Joy eye beholder thing matter difference achieved expected reward expected reward important achieved reward quantifying enjoyable experience example increase expected achieved reward amount reward prediction error hence corresponding joy disappointment change intuitively take person suddenly increase income huge amount also significantly increase expectation daytoday life cannot sure made life happier make happier life assuming income play role happiness need increase income faster increase expectation similar reasoning guarantee rich people used luxurious life enjoy world average summary world everything reward prediction error everything also take relative nature 2 Always right boring assumption enjoy positive reward prediction error assumption enjoyment world without error Hence uncertainty environment make objective prediction ie without subjective bias life becomes quite boring example many people would agree big part joy winning game come fact winning certain advance believe certainty make many u le motivated even get involved game Another interesting bit counterintuitive example lottery general since expect much lottery losing hurt much winning magnificent happens know certainty win imaginary world discussing feeling accomplishment moment seeing card number TV screen yet receiving huge amount money lead lot activity corresponding reward prediction error winning lottery still quite fun later long term Hence imaginary world whole experience indeed still pleasant doubt even real complex world moment announcing winner lottery known u advance certainty give u special feeling summary fun joy hand disappointment frustration need wrong least 3 Pessimism rock joy eye beholder matter make life joyful decreasing expectation One always expects worstcase scenario one always experience positive⁴ reward prediction error word always enjoy world always wrong expectation wrong right way However always easy pick worstcase scenario expectation simply many expectation made unconsciously particularly situation encounter quite often Hence many situation want pessimistic need train need stop adapting expectation according environment stop realistic example rich stop getting used rich always imagine bad scenario good one — like kind mental training example rich repeatedly imagine huge drop stock market even stable trend look amazing problem think imagination simulated version future imagined scenario also imaginary reward prediction error keep expectation low mental training need imagine negative reward prediction error positive one irony point want enjoy reality need suffer minds⁵ Exactly opposite hold true optimism summary nonfamiliar situation pessimistic mindset seems fortunate one However daytoday life event pessimism rock stand catastrophic image world mind Traditionally called conclusion obvious example eat food many time life enjoy every single time also difficult imagine remember enjoying watching movie multiple time indeed case activity enjoy perfectly matching expectation activity like running biking swimming clear reward matter clear everything reward prediction error However saw simple assumption explain feeling emotion wide range situation daytoday life importantly simplicity easy use assumption find better novel insight make u happy make u happy example find fascinating necessity faster increase income compared increase expectation unintuitive nature certain lottery pro con pessimism discussed elaborately imaginary world Thinking situation imaginary world made see thing different perspective like solving math problem small handful mathematical tool allowed insight perspective resulted thinking imaginary world become useful part reasoning making future decision however always aware living simplistic worldTags Ideas Reinforcement Learning Dopamine Psychology Neuroscience |
935 | A new breed of founders using data to help the planet (and their backers) | As a startup investor, I love learning about new spaces where problems can be solved through software.
Since these white spaces can be found in any industry, I deeply believe in a founder-first investment strategy; I think founders are much better than investors at identifying opportunities. All we can do is follow them and learn from those who spend more time than us spotting problems, getting smart about them, and coming up with compelling solutions.
More often than not, these talented founders travel in packs: from those individuals building software to reshape the Future of Work, to those working on Mental Health tech solutions, as well as those building Community Tools. The list goes on…
One of these spaces — in which I’m seeing an increasing number of remarkable people building meaningful companies — is Climate Tech Software, spurred by a couple of important trends:
Increasing awareness around sustainability & climate change — both at the consumer and business level 🌏
around sustainability & climate change — both at the consumer and business level 🌏 Regulatory and socio - political pressure towards transparency in reporting and reductions in carbon emissions (examples: 1, 2 and 3) ⚖️
and - towards transparency in reporting and reductions in carbon emissions (examples: 1, 2 and 3) ⚖️ Increasing investor interest, with a bunch of awesome new funds raising hundreds of millions around the topic (See list below) 💸
I’ve spent some time crafting a list of 80 unique companies that caught my attention in the space, and a couple of investors who are mostly, or entirely focused on it.
My plan is to keep updating this post on a regular basis, so that it can become the go-to piece for the sector. If you’re building a company that you think should be included, let me know! | https://pinver.medium.com/a-new-breed-of-founders-using-data-to-help-the-planet-and-their-backers-f59537304353 | ['Pietro Invernizzi'] | 2020-12-04 18:03:18.874000+00:00 | ['Startup', 'Software', 'Venture Capital', 'Entrepreneurship', 'Climate Change'] | Title new breed founder using data help planet backersContent startup investor love learning new space problem solved software Since white space found industry deeply believe founderfirst investment strategy think founder much better investor identifying opportunity follow learn spend time u spotting problem getting smart coming compelling solution often talented founder travel pack individual building software reshape Future Work working Mental Health tech solution well building Community Tools list go on… One space — I’m seeing increasing number remarkable people building meaningful company — Climate Tech Software spurred couple important trend Increasing awareness around sustainability climate change — consumer business level 🌏 around sustainability climate change — consumer business level 🌏 Regulatory socio political pressure towards transparency reporting reduction carbon emission example 1 2 3 ⚖️ towards transparency reporting reduction carbon emission example 1 2 3 ⚖️ Increasing investor interest bunch awesome new fund raising hundred million around topic See list 💸 I’ve spent time crafting list 80 unique company caught attention space couple investor mostly entirely focused plan keep updating post regular basis become goto piece sector you’re building company think included let knowTags Startup Software Venture Capital Entrepreneurship Climate Change |
936 | 3 Ways To Measure The Effectiveness of Your Leadership | The challenge of cultivating leadership skills goes far beyond simply presenting an inspiring speech. When leaders tactfully pave the way for creative direction, everyone involved experiences the beneficial effects.
Directing creative aspirations requires strong leadership skills. Motivating a team to achieve common objectives while maintaining morale, leaders certainly have their work cut out. Sometimes, people in leadership roles fail to effectively lead, due to a variety of reasons. Meanwhile, there are times when strangers may demonstrate leadership in a way that leaves lasting inspiration.
Are You An Effective Leader?
Do you energize people to want to pursue a certain vision?
All humans seek purpose and meaning in their pursuits. As leaders trying to inspire people to adopt a certain vision, we must not ignore the blatant volition of freethinking individuals. When trying to gain compliance, a leader must articulate a set of aspirations that elevates people’s own sense of purpose or meaningfulness. By communicating collective aspirations that excites others, motivation is created.
Pro-Tip: Create messaging in a way that will resonate with your intended audience.
Does your direction help orientate and provide clarity?
It is important to direct people’s attention to specific aspirations at a time to help them perform optimally to achieve a vision. Giving people something to think about that inspires improvement in their own workflow is a helpful way to provide guidance. Effective leadership provides people with a general template they can use as a guideline to assess options for how they should proceed.
Pro-Tip: Be clear and concise in your communications.
Do people agree with your ideas for the future?
Achieving compliance means all parties resolve in agreement. As a leader, it is important to listen carefully to understand others’ points of view. Then, be prepared to debate why your ideas will work better in a genuinely convincing manor. Everyone has ideas. Leaders know how to effectively sell theirs. At the end of the day, anything is possible. May the most reasonable argument win.
Pro-Tip: Explain the importance of specific long-term goals and provide strategic plans. | https://medium.com/couple-of-creatives/3-ways-to-measure-the-effectiveness-of-your-leadership-73e94546fffd | ['Alyssa Leverenz'] | 2017-05-12 01:15:35.930000+00:00 | ['Marketing', 'Leadership', 'Branding', 'Business', 'Productivity'] | Title 3 Ways Measure Effectiveness LeadershipContent challenge cultivating leadership skill go far beyond simply presenting inspiring speech leader tactfully pave way creative direction everyone involved experience beneficial effect Directing creative aspiration requires strong leadership skill Motivating team achieve common objective maintaining morale leader certainly work cut Sometimes people leadership role fail effectively lead due variety reason Meanwhile time stranger may demonstrate leadership way leaf lasting inspiration Effective Leader energize people want pursue certain vision human seek purpose meaning pursuit leader trying inspire people adopt certain vision must ignore blatant volition freethinking individual trying gain compliance leader must articulate set aspiration elevates people’s sense purpose meaningfulness communicating collective aspiration excites others motivation created ProTip Create messaging way resonate intended audience direction help orientate provide clarity important direct people’s attention specific aspiration time help perform optimally achieve vision Giving people something think inspires improvement workflow helpful way provide guidance Effective leadership provides people general template use guideline ass option proceed ProTip clear concise communication people agree idea future Achieving compliance mean party resolve agreement leader important listen carefully understand others’ point view prepared debate idea work better genuinely convincing manor Everyone idea Leaders know effectively sell end day anything possible May reasonable argument win ProTip Explain importance specific longterm goal provide strategic plansTags Marketing Leadership Branding Business Productivity |
937 | You Need Server-Side Rendering for Your Angular/React/Vue Application | But Why Do I Need to Learn Yet Another Framework?
A common problem with JavaScript applications built with such frameworks as React, Angular, or Vue is that they have trouble optimizing SEO and meta tags.
The reason for this is simple: When we use JavaScript to fetch our page data or meta tags, the page is actually empty and the meta tags are undefined. Until JavaScript is executed, there is no content to index.
You can easily see this for yourself
Just run the application you built with React, Vue, or Angular locally. Right-click the browser page that’s pointing at localhost and click “View Page Source.” All the data you probably populated in the ngOnInit or mounted methods for your component will be visible on your page, but they won't show up in the page source. The page source is what is indexed by search engines.
Notice how all we have in the body is the <div id=”app”></div> . That’s where your framework puts your entire application. Unfortunately, as we can see in the page source, there is nothing for crawlers to see. Your web page would be getting more traffic if it had just been made with simple HTML. How bad does that feel?
This is the case because React, Angular, and Vue all execute in the browser. They render pages in the DOM based on user actions.
The problem here is that web crawlers — the things used by Google and other search engines to find your website’s content — don't usually support JavaScript. If your website or application can’t properly be indexed, then people aren’t going to be able to search for it.
Say, for example, you are fetching blog posts for your web app’s front page feed. And let’s say that today your front page is featuring an article about the 2020 presidential election. You would like people searching for the 2020 election on Google to be able to find your front page. However, since you fetch that blog post using JavaScript, your front page doesn’t have it available to be indexed.
You might also have issues sharing your content on social media platforms because your dynamic headers such as og:title and og:description are undefined until your JavaScript runs.
Here is an example of social media SEO meta tags and the result you get from using them. For those who don’t know, these meta tags allow you to send rich objects when you post your webpage link in a text message or on social media:
Here is the rich object your meta tags let you create. This is what it looks like when sent by text on an iOS device. Photo by the author.
Learn more about the Open Graph protocol. It’s pretty important for SEO. | https://medium.com/better-programming/you-need-server-side-rendering-for-your-angular-react-vue-application-c99e55199aa5 | [] | 2020-11-11 16:15:49.613000+00:00 | ['SEO', 'Programming', 'React', 'JavaScript', 'Vuejs'] | Title Need ServerSide Rendering AngularReactVue ApplicationContent Need Learn Yet Another Framework common problem JavaScript application built framework React Angular Vue trouble optimizing SEO meta tag reason simple use JavaScript fetch page data meta tag page actually empty meta tag undefined JavaScript executed content index easily see run application built React Vue Angular locally Rightclick browser page that’s pointing localhost click “View Page Source” data probably populated ngOnInit mounted method component visible page wont show page source page source indexed search engine Notice body div id”app”div That’s framework put entire application Unfortunately see page source nothing crawler see web page would getting traffic made simple HTML bad feel case React Angular Vue execute browser render page DOM based user action problem web crawler — thing used Google search engine find website’s content — dont usually support JavaScript website application can’t properly indexed people aren’t going able search Say example fetching blog post web app’s front page feed let’s say today front page featuring article 2020 presidential election would like people searching 2020 election Google able find front page However since fetch blog post using JavaScript front page doesn’t available indexed might also issue sharing content social medium platform dynamic header ogtitle ogdescription undefined JavaScript run example social medium SEO meta tag result get using don’t know meta tag allow send rich object post webpage link text message social medium rich object meta tag let create look like sent text iOS device Photo author Learn Open Graph protocol It’s pretty important SEOTags SEO Programming React JavaScript Vuejs |
938 | How Failing in Building a Company Heightened my Intellect | For a founder, shutting down a company is like dumping your most beloved person in the entire world; even worse, finding them dead the next day.
Failure is a common term for any rising startup. This never ceases to be true even with the overwhelming success stories repeatedly saturating our Quora feed. If anything, the percentage of startups failing in their first year continue to spring up through the last decade.
It takes a gallant to be an entrepreneur, as nobody ever built any great company overnight. One has to be courageous enough to say yes when everyone else says no, ignoring statistics others lived by their entire lives.
Like all founders, I suffered several terrible blows, got back up, and tried all over again in my quest to building a company.
Mine might not be the journey with a pleasant ending, but then I owe my growth to it. I’d continue to regard entrepreneurship as a word on people’s Twitter bio if not for my attempt to pursue the not-so-pretty-adventure of building a company.
What happened?
It’s been a year since I had to make the bitter decision to shut down my company. It was a marketing consultancy I co-founded with a friend and worked with a team of a few people. We had a good run. Seven months later, we had to close everything down and let go of a startup we all grew so attached to. It was devastating.
Looking back at the fuzzy memories now, I cherish how brave it was of me to undertake on such a journey with so little chance of scaling up, to begin with. I also came to see how wrong I was in the numerous assumptions I made while starting.
I’ve seen how fundraising takes time — postponed meetings with potential investors drove me mad. It was frustrating, especially taking into account that my most important role as the CEO was to make sure that the company always has the necessary money to run it.
Every other startup founder I’ve met told me a similar story, but I’ve never seen it clearer.
I’ve also seen how vital it is to have a partner whose strengths complement my weaknesses, even if that means laying my best friend off the ride. Clinging to friends, at the expense of competence, is usually the first mistake many founders make in crashing their company.
I’ve come to learn how building a product for a customer is underexplained. Your product can be perfect for the customer that is, unfortunately, in the wrong audience you’re marketing to.
This factor aids in the failure of my company. We were so obsessed with offering the best service (our product) that we lost sight of who our ideal customers were. It was like taking a cruise, partying too much on the ship, only to wake up and find ourselves in the wilderness of the sea. We knew everything was right when we started but had no idea how we ended up where we found ourselves.
How do these heighten my intellect?
There is no way I can be able to share all the lessons I learned in that half-year. I’ve learned a lot of things. But then if there is anything that helped in deepening my intellect, it is realizing how negligent I was when it comes to listening to founders with failed startups.
I realize just how many mistakes I could have avoided if I’d spent my time reading fewer success stories and dredge enough of what I could about other people’s mistakes.
The success stories shared on the internet are fulfilling to consume, and if I must admit, almost ecstatic. Nobody likes listening to failures. The internet would be saturated with such stories if that wasn’t the case — with 90% of startups failing.
It is almost guaranteed that the guest speaker at the last founders’ convention you attended was running a successful company. Who will invite some loser to speak at their event, right?
Yet, it is becoming more important to listen to founders with a darker side of these narratives. It might not be fun and liberating, but just as insightful and instructive for all.
Such founders will tell you why embracing criticism with an open mind is your shortest path to growth. Or better yet, how dismissing critics’ harsh words could, in many instances, be lethal to your company’s image.
Every other founder can say that, sure. But while a founder with a successful venture is likely to gobble his way to, “…and that is how we convinced Mr. Rogers to invest a $100k into our company!”… a failed founder will remind you to drink less water before pitching to a potential investor, saving you from constantly excusing yourself in answering the call of nature. And that… that, my friend, will make a huge difference in the first impression you make.
While a successful founder will urge you to hire a great team, a failed founder will tell you why you’d rather have someone work for you even if they are not the smartest person in the room, so long they are passionate about the product of your startup.
Failed startup founders can tell you a lot of things, some of which might completely be their insecurities, I agree. It doesn’t mean you have to act on everything, but all they say will help you in judging more accurately when you come to make similar decisions. Besides, who better help you in figuring your way around dangerous traps than someone who once got caught by one.
There isn’t a magic wand to wave and rectify all the glitches you’ll ever face on your entrepreneurial journey. To narrow down, there isn’t a step-by-step guide in handling all the failures you’ll encounter in building your company. These are unique experiences, and no one can teach you anything to its marrow.
But if your startup ever fails — which many of us fancy dismissing the possibility of — it will be easier to deal with, when you’ve listened to how others handled this unfortunate incident. | https://medium.com/the-parables/how-failing-in-building-a-company-heightened-my-intellect-e4afe6310d1a | ['Alamiin Si'] | 2020-12-05 18:20:16.434000+00:00 | ['Founder Stories', 'Startup', 'Business', 'Entrepreneurship', 'Entrepreneur'] | Title Failing Building Company Heightened IntellectContent founder shutting company like dumping beloved person entire world even worse finding dead next day Failure common term rising startup never cease true even overwhelming success story repeatedly saturating Quora feed anything percentage startup failing first year continue spring last decade take gallant entrepreneur nobody ever built great company overnight One courageous enough say yes everyone else say ignoring statistic others lived entire life Like founder suffered several terrible blow got back tried quest building company Mine might journey pleasant ending owe growth I’d continue regard entrepreneurship word people’s Twitter bio attempt pursue notsoprettyadventure building company happened It’s year since make bitter decision shut company marketing consultancy cofounded friend worked team people good run Seven month later close everything let go startup grew attached devastating Looking back fuzzy memory cherish brave undertake journey little chance scaling begin also came see wrong numerous assumption made starting I’ve seen fundraising take time — postponed meeting potential investor drove mad frustrating especially taking account important role CEO make sure company always necessary money run Every startup founder I’ve met told similar story I’ve never seen clearer I’ve also seen vital partner whose strength complement weakness even mean laying best friend ride Clinging friend expense competence usually first mistake many founder make crashing company I’ve come learn building product customer underexplained product perfect customer unfortunately wrong audience you’re marketing factor aid failure company obsessed offering best service product lost sight ideal customer like taking cruise partying much ship wake find wilderness sea knew everything right started idea ended found heighten intellect way able share lesson learned halfyear I’ve learned lot thing anything helped deepening intellect realizing negligent come listening founder failed startup realize many mistake could avoided I’d spent time reading fewer success story dredge enough could people’s mistake success story shared internet fulfilling consume must admit almost ecstatic Nobody like listening failure internet would saturated story wasn’t case — 90 startup failing almost guaranteed guest speaker last founders’ convention attended running successful company invite loser speak event right Yet becoming important listen founder darker side narrative might fun liberating insightful instructive founder tell embracing criticism open mind shortest path growth better yet dismissing critics’ harsh word could many instance lethal company’s image Every founder say sure founder successful venture likely gobble way “…and convinced Mr Rogers invest 100k company”… failed founder remind drink le water pitching potential investor saving constantly excusing answering call nature that… friend make huge difference first impression make successful founder urge hire great team failed founder tell you’d rather someone work even smartest person room long passionate product startup Failed startup founder tell lot thing might completely insecurity agree doesn’t mean act everything say help judging accurately come make similar decision Besides better help figuring way around dangerous trap someone got caught one isn’t magic wand wave rectify glitch you’ll ever face entrepreneurial journey narrow isn’t stepbystep guide handling failure you’ll encounter building company unique experience one teach anything marrow startup ever fails — many u fancy dismissing possibility — easier deal you’ve listened others handled unfortunate incidentTags Founder Stories Startup Business Entrepreneurship Entrepreneur |
939 | Life Lessons from Improv | We are all playing status games with each other
‘Things said are not as important as the status played.’
The most eye-opening idea in Impro is about how we unknowingly play status games with each other. To understand this, think of the word status as a verb, i.e. something we do, rather than your position in a hierarchy. The assertion is that in every interaction a player occupies a niche, or status, relative to the other players and behaves in accordance with that chosen status. In simplistic terms: one party always dominates an interaction while the other gets dominated; again, the word ‘dominate’ here does not denote outright conflict, but a more subtle power dynamic. For instance, in a boss-employee relationship, it is almost always the boss who is high-status while the employee has no choice but to be low-status. The same employee however, might be high-status when interacting with a member of his or her domestic staff.
Everyone has a preferred status, which they can advertise directly through speech or indirectly through body language. An upright but relaxed posture, making eye contact and not shirking from standing close to others are all telltale signs of someone playing high status. On the other hand, if someone prefers a bent posture, not looking others in the eye and generally afraid to come too close, they are choosing a low status. Now this might surprise some, but some people do prefer to remain low-status because it keeps attention away from them. Such individuals can effectively use their low status to make others feel good about themselves and keep themselves from harm (e.g. the dwarves who were kept in kings’ courts for this very purpose).
How we react emotionally to a situation depends on how it affects our status. We feel good if our status is raised vis-à-vis others, but exactly the opposite when it’s lowered. Consider how you feel when you hear about a friend’s success: you might be genuinely happy but you also feel your status slowly sinking as your friend’s rises. Broadly speaking, we want others to be low-status compared to us, but not so low that we have to feel sympathy for them. A minor setback for an acquaintance might give us pleasure because we are automatically raised in comparison. However, when a serious tragedy befalls someone, we are forced to sympathize without any elevation in our own status. And that does not feel good at all.
So why does an understanding of status matter? In the context of improvisation, actors can become more spontaneous by recreating a status game on stage rather than focusing only on each other’s dialogue. By either slightly elevating or lowering their status compared to their acting partner, they are able to generate life-like scenarios which are always marked by status interactions. When it comes to real life, we can get better at reading social situations by understanding the subtle status interactions happening just beneath the surface. Even without a word being exchanged, we can sense how the power dynamic in a room is playing out, or who the most powerful person is. This knowledge can help us respond appropriately to a situation because we can strategically play low or high depending on whom we are interacting with.
Finally, we must realize that it’s not so much the status we choose to play as what the other person perceives we’re doing. Even the most innocent of intentions on your part can be misconstrued; for instance when you tell someone you’ve already read a book they are currently reading, they might feel you’re just trying to establish your intellectual superiority. Paying attention to such subtleties can pay rich dividends over the course of our lives. | https://dhawalsharma.medium.com/life-lessons-from-improv-a1d515e7f286 | ['Dhawal Sharma'] | 2018-11-29 01:44:21.086000+00:00 | ['Self Improvement', 'Fear Of Failure', 'Psychology', 'Creativity', 'Inspiration'] | Title Life Lessons ImprovContent playing status game ‘Things said important status played’ eyeopening idea Impro unknowingly play status game understand think word status verb ie something rather position hierarchy assertion every interaction player occupies niche status relative player behaves accordance chosen status simplistic term one party always dominates interaction get dominated word ‘dominate’ denote outright conflict subtle power dynamic instance bossemployee relationship almost always bos highstatus employee choice lowstatus employee however might highstatus interacting member domestic staff Everyone preferred status advertise directly speech indirectly body language upright relaxed posture making eye contact shirking standing close others telltale sign someone playing high status hand someone prefers bent posture looking others eye generally afraid come close choosing low status might surprise people prefer remain lowstatus keep attention away individual effectively use low status make others feel good keep harm eg dwarf kept kings’ court purpose react emotionally situation depends affect status feel good status raised visàvis others exactly opposite it’s lowered Consider feel hear friend’s success might genuinely happy also feel status slowly sinking friend’s rise Broadly speaking want others lowstatus compared u low feel sympathy minor setback acquaintance might give u pleasure automatically raised comparison However serious tragedy befalls someone forced sympathize without elevation status feel good understanding status matter context improvisation actor become spontaneous recreating status game stage rather focusing other’s dialogue either slightly elevating lowering status compared acting partner able generate lifelike scenario always marked status interaction come real life get better reading social situation understanding subtle status interaction happening beneath surface Even without word exchanged sense power dynamic room playing powerful person knowledge help u respond appropriately situation strategically play low high depending interacting Finally must realize it’s much status choose play person perceives we’re Even innocent intention part misconstrued instance tell someone you’ve already read book currently reading might feel you’re trying establish intellectual superiority Paying attention subtlety pay rich dividend course livesTags Self Improvement Fear Failure Psychology Creativity Inspiration |
940 | Your Really Bad Days Have Something to Teach You | “The mean reds are horrible. You’re afraid, and you sweat like hell, but you don’t know what you’re afraid of. Except something bad is going to happen, only you don’t know what it is. You’ve had that feeling?”
— Truman Capote, Breakfast at Tiffany’s
I had one of those days yesterday. A ‘Mean Reds’ day. The kind where even the good stuff feels off balance.
The kind of day that you feel in the center of your chest. Like a brick sitting there, keeping your heart from beating properly and your lungs from filling completely.
Days like that, it feels like the veil between the life I think I’m living and the one I actually have is whisper thin. Usually everything’s okay doesn’t feel like an illusion. It feels real. And then there are days when the Mean Reds hit.
I’m not talking about a tragic day here. The Mean Reds aren’t a response to tragedy. They’re usually a response to something in your life being off-balance.
You know you’re having a Mean Reds day when a thousand little things go micro-wrong and maybe a couple of things go really wrong, and suddenly the weight of everything and everyone depending on you just feels too big.
I started to write today about how to stop the Mean Reds. Or maybe how to avoid them. How to get that brick off your sternum so you can take a deep breath again.
I realized something, though, when I closed my eyes for a minute and really thought about it. The Mean Reds are hard and they suck. No one wants them.
But I think they might be necessary.
It’s hard to learn and grow when things are good enough.
My best friend told me once that she was afraid to have goals. She liked everything about her life well enough and she was afraid of tempting fate to take it away from her by wanting more.
If good is the enemy of great — then good enough is the enemy of better.
A Mean Reds day is uncomfortable and, frankly, awful. But they are usually a symptom of something off kilter. Something ‘good enough’ that isn’t anymore. When you get to the other side of it, those days strip away the ‘good enough’ for a minute, so that you can see how to get to better.
If you can lean into your Mean Reds and see what’s at the heart of them, you might see where you need to grow and figure out what you need to learn.
Mean Reds days can inspire intense motivation.
You need to be able to feel what’s wrong, if you’re going to change it. And when everything is good, or at least not Mean Red, then your focus is on what’s working, not what isn’t.
The Mean Reds can be the kind of day when, if you lean into it, a really good plan is possible. You’re motivated, when you can’t breathe. Think about it. You’ll never swim any harder than when you’re kicking up to the surface with your lungs burning for air.
Learn to recognize a Mean Reds day for what it is: a notice from your psyche that something isn’t working. Let that motivate you to find a way to fix the problem.
The Mean Reds are part of life.
This isn’t depression. It’s not anxiety. And, like I said, it’s not a response to tragedy. The Mean Reds are different. They’re an activation of the flight-or-fight response.
They’re temporary, although it doesn’t always feel like it in the moment. Usually they really are just a day. Get some sleep and things look clearer in the morning.
But they’re scary, because sometimes you really don’t know what’s kicking your flight-or-fight response into high gear.
It’s natural to just react to the Mean Reds. Lash out or scream or hide or bury yourself in whatever comfort you can rustle up. But if you lean into them, you can get to the reason why they’re happening.
Maybe you’re not taking good enough care of yourself. Maybe there’s something toxic in your life that’s finally come to a head. Maybe a bad habit is catching up with you. Maybe you’re spending the bulk of every day doing work that doesn’t align with who you want to be.
Whatever it is, a Mean Reds day is an opportunity to figure it out, if you let it be. | https://medium.com/the-write-brain/your-really-bad-days-have-something-to-teach-you-7894783b60d3 | ['Shaunta Grimes'] | 2019-10-09 20:10:42.409000+00:00 | ['Life Lessons', 'Self', 'Health', 'Mental Health', 'Life'] | Title Really Bad Days Something Teach YouContent “The mean red horrible You’re afraid sweat like hell don’t know you’re afraid Except something bad going happen don’t know You’ve feeling” — Truman Capote Breakfast Tiffany’s one day yesterday ‘Mean Reds’ day kind even good stuff feel balance kind day feel center chest Like brick sitting keeping heart beating properly lung filling completely Days like feel like veil life think I’m living one actually whisper thin Usually everything’s okay doesn’t feel like illusion feel real day Mean Reds hit I’m talking tragic day Mean Reds aren’t response tragedy They’re usually response something life offbalance know you’re Mean Reds day thousand little thing go microwrong maybe couple thing go really wrong suddenly weight everything everyone depending feel big started write today stop Mean Reds maybe avoid get brick sternum take deep breath realized something though closed eye minute really thought Mean Reds hard suck one want think might necessary It’s hard learn grow thing good enough best friend told afraid goal liked everything life well enough afraid tempting fate take away wanting good enemy great — good enough enemy better Mean Reds day uncomfortable frankly awful usually symptom something kilter Something ‘good enough’ isn’t anymore get side day strip away ‘good enough’ minute see get better lean Mean Reds see what’s heart might see need grow figure need learn Mean Reds day inspire intense motivation need able feel what’s wrong you’re going change everything good least Mean Red focus what’s working isn’t Mean Reds kind day lean really good plan possible You’re motivated can’t breathe Think You’ll never swim harder you’re kicking surface lung burning air Learn recognize Mean Reds day notice psyche something isn’t working Let motivate find way fix problem Mean Reds part life isn’t depression It’s anxiety like said it’s response tragedy Mean Reds different They’re activation flightorfight response They’re temporary although doesn’t always feel like moment Usually really day Get sleep thing look clearer morning they’re scary sometimes really don’t know what’s kicking flightorfight response high gear It’s natural react Mean Reds Lash scream hide bury whatever comfort rustle lean get reason they’re happening Maybe you’re taking good enough care Maybe there’s something toxic life that’s finally come head Maybe bad habit catching Maybe you’re spending bulk every day work doesn’t align want Whatever Mean Reds day opportunity figure let beTags Life Lessons Self Health Mental Health Life |
941 | Self-Care vs Selfishness | Have you ever felt guilty for the times where you have put yourself first? Do you sometimes wonder if putting yourself first is being selfish? Well, today I want to talk about whether or not self-care is being selfish.
Self-care is defined as the action of preserving or improving one’s own health. On the flip side, being selfish is defined as someone who lacks consideration for others and their actions and motives are for their own personal profit or pleasure.
At first glance, self-care may seem related to selfishness or the intent may have been derived from selfishness. However, they are two completely different things. The main difference lies within the motive.
Selfishness is rooted in one’s personal gain or pleasure, whereas self-care is about preserving or improving your health. The approach to self-care is different because you are seeing a need in yourself that needs to be improved or maintained.
There may be times where you may feel selfish because you are focusing on yourself, but the reality is, you are taking care of yourself. Do not feel guilty for caring for your needs. You are not selfish for taking the time to take care of yourself.
Knowing how to be solitary is central to the art of loving. When we can be alone, we can be with others without using them as a means of escape. Bell Hooks
The Importance of Self-care
When you are practicing self-care, you are looking to take care of yourself so that you can care for others. I’m sure you have heard the saying, “How can you expect to love others if you can’t learn to love yourself?” Well, this is the same for self-care. How can you expect to care for others if you can’t learn to care for yourself?
Self-care is about maintaining a balance in your life. There are many parts that create a person, the body, mind, heart, and soul. There is a delicate balance between all of them. If one part begins to deteriorate, the rest will begin to deteriorate as well. In order to stay healthy, we need to take the time to put ourselves first. We need to learn how to nurture ourselves so that we can thrive and help others along the way.
If you want to learn more about self-care habits, please take a look at this article: 5 Simple Ways You Can Practice Self-Care Today
Selfishness is not living as one withes to live, it is asking others to live as one withes to live Oscar Wilde
Stop Feeling Guilty
You might still be wondering, “How is this different from being selfish?” Well, selfishness is doing something for your own gain without worrying about the consequences of those around you. The mindset of a selfish person is trying to fill a need with the expectation of others bending to your will. Oscar Wilde states, “Selfishness is not living as one wishes to live, it is asking others to live as one wishes to live.” Selfishness lack empathy, compassion, and love for others, whereas self-care does not.
When we choose to take care of ourselves and to put ourselves first, we may feel like we’re being selfish. That’s okay. It is okay for you to feel selfish, but do not get caught up in that feeling because, eventually, you need to put your needs first. Take care of yourself before you can take care of others.
You are not being selfish for putting things aside so that you can feel better. You are not selfish for canceling plans after a long and arduous day. You are not selfish for unplugging yourself from technology so that you can destress after a stressful day. It is okay for you to put yourself first every once in a while. Your wellbeing is more valuable than how others might perceive you. Do not cast aside your wellbeing, instead, find a balance in your life where you can take care of others and, most importantly, yourself.
Don’t forget, you are loved, cared for, and significant. Take care and I hope to see you next week. | https://medium.com/sweaters-and-blankets/self-care-vs-selfishness-5a36e8dfe875 | ['Tiffany Hsu'] | 2020-12-14 17:35:30.629000+00:00 | ['Guilt', 'Self Care', 'Self Improvement', 'Health', 'Wellness'] | Title SelfCare v SelfishnessContent ever felt guilty time put first sometimes wonder putting first selfish Well today want talk whether selfcare selfish Selfcare defined action preserving improving one’s health flip side selfish defined someone lack consideration others action motif personal profit pleasure first glance selfcare may seem related selfishness intent may derived selfishness However two completely different thing main difference lie within motive Selfishness rooted one’s personal gain pleasure whereas selfcare preserving improving health approach selfcare different seeing need need improved maintained may time may feel selfish focusing reality taking care feel guilty caring need selfish taking time take care Knowing solitary central art loving alone others without using mean escape Bell Hooks Importance Selfcare practicing selfcare looking take care care others I’m sure heard saying “How expect love others can’t learn love yourself” Well selfcare expect care others can’t learn care Selfcare maintaining balance life many part create person body mind heart soul delicate balance one part begin deteriorate rest begin deteriorate well order stay healthy need take time put first need learn nurture thrive help others along way want learn selfcare habit please take look article 5 Simple Ways Practice SelfCare Today Selfishness living one withe live asking others live one withe live Oscar Wilde Stop Feeling Guilty might still wondering “How different selfish” Well selfishness something gain without worrying consequence around mindset selfish person trying fill need expectation others bending Oscar Wilde state “Selfishness living one wish live asking others live one wish live” Selfishness lack empathy compassion love others whereas selfcare choose take care put first may feel like we’re selfish That’s okay okay feel selfish get caught feeling eventually need put need first Take care take care others selfish putting thing aside feel better selfish canceling plan long arduous day selfish unplugging technology destress stressful day okay put first every wellbeing valuable others might perceive cast aside wellbeing instead find balance life take care others importantly Don’t forget loved cared significant Take care hope see next weekTags Guilt Self Care Self Improvement Health Wellness |
942 | Certainty | I want words to shape my life, from the morning when I wake up to the evening when I close my eyes. Is it too much to ask? What is this remote place in the heart of nature where I could live from reading and writing?
Here, I no longer hear the birds singing. I am no longer awakened by the swallows that used to nest in the corner of the window overlooking the courtyard in front of the house. I only come across this tawny owl that says good night to me when I come home late at night. I answer her with sweet thoughts.
Here, I no longer see the insects, bumblebees, bees, and butterflies that swarmed around the lavender right next to the pear tree. I’m no longer on the lookout for the blue chickadees that used to come every morning to have breakfast under the apple tree in front of the dining room French window.
Here, I no longer hear the dry clacking of the woodpecker’s beak against the cherry tree trunk next to the clothesline. I am no longer lulled by the song of the blackbird at nightfall, perched at the top of the fir tree at the bottom of the garden.
Here, I can no longer smell the intense scent of red roses from the generous rosebush climbing up the wall next to the kitchen. I can no longer caress with my fingertips the colorful tulips planted and lovingly tended by my mother.
Where has this luxuriant nature that filled me with happiness in my young years gone? I think about it again and here I am melancholy. As I write these words, my throat closes. But what am I to do but write? Where do I have to live to find some of that childhood scent? Is there an enchanting place where the birds sing and the words dance on the pages?
Tonight, I have only one certainty. I want words to shape my life, from the morning when I wake up to the evening when I close my eyes. | https://medium.com/scribe/certainty-b4017e2ea90a | ['Thomas Gaudex'] | 2020-02-03 18:36:37.849000+00:00 | ['Poetry', 'Nature', 'Writing', 'Creativity', 'Life'] | Title CertaintyContent want word shape life morning wake evening close eye much ask remote place heart nature could live reading writing longer hear bird singing longer awakened swallow used nest corner window overlooking courtyard front house come across tawny owl say good night come home late night answer sweet thought longer see insect bumblebee bee butterfly swarmed around lavender right next pear tree I’m longer lookout blue chickadee used come every morning breakfast apple tree front dining room French window longer hear dry clacking woodpecker’s beak cherry tree trunk next clothesline longer lulled song blackbird nightfall perched top fir tree bottom garden longer smell intense scent red rose generous rosebush climbing wall next kitchen longer caress fingertip colorful tulip planted lovingly tended mother luxuriant nature filled happiness young year gone think melancholy write word throat close write live find childhood scent enchanting place bird sing word dance page Tonight one certainty want word shape life morning wake evening close eyesTags Poetry Nature Writing Creativity Life |
943 | AI Speeds Drug Discovery to fight COVID-19 | AI Speeds Drug Discovery to fight COVID-19
An inside look at AI’s role in the race for COVID-19 treatment and drug discovery, and TCS’ first-hand research and experimentation
The virus named “SARS-CoV-2” is the source of a global pandemic COVID-19, which has severely affected the health and economy of several countries. Multiple studies are in progress, employing diverse approaches to design novel therapeutics against the potential target proteins in SARS-CoV-2. One of the well-studied protein targets for coronaviruses is the chymotrypsin-like (3CL) protease, responsible for post-translational modifications of viral polyproteins essential for its survival and replication in the host. There are various ongoing projects to find inhibitors against 3CL protease of SARS-CoV-2.
Recent studies have proven the efficiency of artificial intelligence (AI) techniques in understanding the known chemical space and generating novel small molecules. These small molecules have to satisfy several physicochemical properties to be able to be used as potential drug molecules. With the advent of AI-based methods, it is possible to design novel small molecules with desired drug-like properties. At Tata Consultancy Services(TCS), we employed deep neural network-based generative and predictive models for de novo design of small molecules capable of inhibiting the 3CL protease. The generated small molecules were filtered and screened against the binding site of the 3CL protease structure of SARS-CoV-2. Based on the screening results and further analysis, we have identified 31 potential compounds as ideal candidates for further synthesis and testing against SARS-CoV-2.
The AI-driven revolution in drug discovery
Finding a new drug takes a decade or more with a very low success rate. Advances in data curation and management have fueled the emergence of an AI-driven revolution in drug discovery.
AI-based methods are emerging as promising tools to explore the vast chemical space that is available to sample drug-like molecules. AI models are capable of learning the feature representations based on existing drugs that can be used to explore the chemical space in search of more drug-like molecules. This has provided a beacon of opportunity to the drug design community to overcome many challenges including the global antibiotic-resistance crisis. Most importantly, an AI-based approach can reduce the initial phase of the drug-discovery process from years to a few days.
TCS capability in terms of algorithms
In this study, we have utilized our in-house deep neural network-based generative and predictive models to design novel drug-like small molecules (new chemical entities or NCEs). Our in-house models and algorithms have been validated on a multitude of drug design tasks to tailor compounds to a specific protein target of interest. These validated, pre-trained state-of-the-art models were used to generate novel small molecules capable of inhibiting the 3CL protease of SARS-CoV-2, utilizing advanced training techniques such as transfer learning and regularized reinforcement learning.
An overview of dataset collection and pre-processing
ChEMBL is a public database which maintains the most comprehensive collection of drug-like small molecules. The generative model was initially trained on a dataset of ~1.6 million drug-like molecules from the ChEMBL database. The molecules were represented in Simplified Molecular Input Line Entry System (SMILES) format which will enable the model to learn the necessary features to design novel drug-like small molecules.
Training the deep learning models
The pre-processed SMILES dataset was used to train a recurrent neural network (RNN)-based generative model. The problem of learning the SMILES grammar and reproducing it to generate novel small molecules was cast as a classification problem. The entire SMILES string was considered as a time series, where every position or symbol was considered as a time point. The different symbols in the SMILES vocabulary were considered as the classes of the classification. At a given time point, the generative model was trained to predict the class of the next symbol given the class distributions of the previous symbols in the time series. Thus, the model learns the probability distribution over the various classes at each time point of the time series. The problem was cast this way, to resemble the class of natural language processing (NLP) problems for which sophisticated AI models and architectures have been developed over the years.
Our trained generative model has state-of-the-art accuracy of 96.6%, calculated based on the chemical and synthetic feasibility of the drug-like molecules inferred from the model. This general model capable of exploring the chemical space acted as our prior model, which was further adapted to generate small molecules specific to a target of interest using transfer learning. In order to bias the model to focus on the 3CL protease of SARS-CoV-2, a dataset of protease inhibitor molecules was manually curated from the ChEMBL database. The dataset of 2,515 protease inhibitor molecules was used to re-train the generative model using transfer learning. In the process of transfer learning, the generative model is biased towards focusing on a smaller subset of the chemical space. Further, regularized reinforcement learning was used to modulate the generative model to produce molecules with optimized physicochemical properties (Fig. 1).
Figure 1: Approach used for generating novel compounds for targeting 3CL protease of SARS-CoV-2.
Filtering the potential drug-like molecules against SARS-CoV-2
The trained generative model was used for sampling 50,000 small molecules from the learned chemical space. After removal of duplicates and molecules which were identical to the ChEMBL database, the residual dataset consisted of 42,484 molecules. These molecules were subjected to stringent physicochemical property filters including drug-likeness, octanol-water partition coefficient (logP), hydrogen bond donor and acceptor counts, molecular weight, bioactivity and synthetic accessibility, which resulted in a set of 3,960 molecules. These molecules were further filtered based on their affinity towards SARS-CoV-2 3CL protease. After virtual screening, a total of 1,333 small molecules were obtained which could act as potential inhibitors.
We also observed that, the generative model could generate small molecules that are similar to HIV-protease inhibitors, but with better binding to the SARS-CoV-2 3CL protease. The complete set of promising small molecules can be found here so that anyone can test these molecules against SARS-CoV-2 in this hour of need.
Other AI-based applications for COVID-19 drug design research
Several companies and startups have transformed their research goals in innovative ways, to utilize AI in accelerating the search for a cure against COVID-19. The European AI-centered startup Molecule.one has released its patented syntheses planning platform for free access to the scientific community, in an effort to help researchers rapidly synthesize and test potential candidate molecules against COVID-19. IBM has applied its AI generative frameworks to three COVID-19 targets and has generated 3000 novel molecules. These molecules have been released under the Creative Commons License (CCL) to the scientific community for synthesis, testing and optimization. The Hong Kong-based pharmaceutical research company, InSilico Medicine has released a list of 97 candidate small molecules designed to inhibit the 3CL protease of SARS-CoV-2. Several AI-based rapid virtual screening models have been developed and tested against COVID-19, with existing public and commercial virtual screening compound libraries as primary databases. In essence, several directions of research have incorporated AI-based models to come up with potential therapeutics for COVID-19, at an unprecedented pace. | https://towardsdatascience.com/ai-speeds-drug-discovery-to-fight-covid-19-b853a3f93e82 | ['Arijit Roy'] | 2020-04-29 18:08:51.910000+00:00 | ['AI', 'Covid 19', 'Data Science', 'Science', 'Deep Learning'] | Title AI Speeds Drug Discovery fight COVID19Content AI Speeds Drug Discovery fight COVID19 inside look AI’s role race COVID19 treatment drug discovery TCS’ firsthand research experimentation virus named “SARSCoV2” source global pandemic COVID19 severely affected health economy several country Multiple study progress employing diverse approach design novel therapeutic potential target protein SARSCoV2 One wellstudied protein target coronaviruses chymotrypsinlike 3CL protease responsible posttranslational modification viral polyproteins essential survival replication host various ongoing project find inhibitor 3CL protease SARSCoV2 Recent study proven efficiency artificial intelligence AI technique understanding known chemical space generating novel small molecule small molecule satisfy several physicochemical property able used potential drug molecule advent AIbased method possible design novel small molecule desired druglike property Tata Consultancy ServicesTCS employed deep neural networkbased generative predictive model de novo design small molecule capable inhibiting 3CL protease generated small molecule filtered screened binding site 3CL protease structure SARSCoV2 Based screening result analysis identified 31 potential compound ideal candidate synthesis testing SARSCoV2 AIdriven revolution drug discovery Finding new drug take decade low success rate Advances data curation management fueled emergence AIdriven revolution drug discovery AIbased method emerging promising tool explore vast chemical space available sample druglike molecule AI model capable learning feature representation based existing drug used explore chemical space search druglike molecule provided beacon opportunity drug design community overcome many challenge including global antibioticresistance crisis importantly AIbased approach reduce initial phase drugdiscovery process year day TCS capability term algorithm study utilized inhouse deep neural networkbased generative predictive model design novel druglike small molecule new chemical entity NCEs inhouse model algorithm validated multitude drug design task tailor compound specific protein target interest validated pretrained stateoftheart model used generate novel small molecule capable inhibiting 3CL protease SARSCoV2 utilizing advanced training technique transfer learning regularized reinforcement learning overview dataset collection preprocessing ChEMBL public database maintains comprehensive collection druglike small molecule generative model initially trained dataset 16 million druglike molecule ChEMBL database molecule represented Simplified Molecular Input Line Entry System SMILES format enable model learn necessary feature design novel druglike small molecule Training deep learning model preprocessed SMILES dataset used train recurrent neural network RNNbased generative model problem learning SMILES grammar reproducing generate novel small molecule cast classification problem entire SMILES string considered time series every position symbol considered time point different symbol SMILES vocabulary considered class classification given time point generative model trained predict class next symbol given class distribution previous symbol time series Thus model learns probability distribution various class time point time series problem cast way resemble class natural language processing NLP problem sophisticated AI model architecture developed year trained generative model stateoftheart accuracy 966 calculated based chemical synthetic feasibility druglike molecule inferred model general model capable exploring chemical space acted prior model adapted generate small molecule specific target interest using transfer learning order bias model focus 3CL protease SARSCoV2 dataset protease inhibitor molecule manually curated ChEMBL database dataset 2515 protease inhibitor molecule used retrain generative model using transfer learning process transfer learning generative model biased towards focusing smaller subset chemical space regularized reinforcement learning used modulate generative model produce molecule optimized physicochemical property Fig 1 Figure 1 Approach used generating novel compound targeting 3CL protease SARSCoV2 Filtering potential druglike molecule SARSCoV2 trained generative model used sampling 50000 small molecule learned chemical space removal duplicate molecule identical ChEMBL database residual dataset consisted 42484 molecule molecule subjected stringent physicochemical property filter including druglikeness octanolwater partition coefficient logP hydrogen bond donor acceptor count molecular weight bioactivity synthetic accessibility resulted set 3960 molecule molecule filtered based affinity towards SARSCoV2 3CL protease virtual screening total 1333 small molecule obtained could act potential inhibitor also observed generative model could generate small molecule similar HIVprotease inhibitor better binding SARSCoV2 3CL protease complete set promising small molecule found anyone test molecule SARSCoV2 hour need AIbased application COVID19 drug design research Several company startup transformed research goal innovative way utilize AI accelerating search cure COVID19 European AIcentered startup Moleculeone released patented synthesis planning platform free access scientific community effort help researcher rapidly synthesize test potential candidate molecule COVID19 IBM applied AI generative framework three COVID19 target generated 3000 novel molecule molecule released Creative Commons License CCL scientific community synthesis testing optimization Hong Kongbased pharmaceutical research company InSilico Medicine released list 97 candidate small molecule designed inhibit 3CL protease SARSCoV2 Several AIbased rapid virtual screening model developed tested COVID19 existing public commercial virtual screening compound library primary database essence several direction research incorporated AIbased model come potential therapeutic COVID19 unprecedented paceTags AI Covid 19 Data Science Science Deep Learning |
944 | A good designer is a good businessperson | IBM’s president Thomas J. Jr. Watson’s “Good Design is Good Business” 1973 saying, is making much more sense in our tech business space now. Building and shipping digital -or even non-digital- products is getting easier every day, making design play an even more recognizable role than ever.
One of the by-products of this fact according to John Maeda’s design in tech report is the rising rate of involving designers at the very early stages of a startup as core builders. In fact, the number of successful startups founded by designers might be surprising to most people. This surge of design’s extending functionality in businesses rises the demand for business training and education for designers. The area that has been neglected in most design school programs. Many employers prefer hiring designers with solid business understanding and their career path mostly leads to getting more involved in management areas, serving more direct business objectives.
The business value of design has been discussed and measured in various papers and reports (famously McKinsey report). With that being said, many teams still struggle to find a meaningful relationship between their design team performance and achieving business objectives. The issue here lies in how design teams are managed and directed, not the whole design function in general.
In short, If you need to address the business value of your design team, it’s unlikely to be a good one.
Products and services are getting closer to users with individually crafted experiences. Given this opportunity, a user-centric design approach is also expected to deliver readily visible business value.
It’s ultimately the job of the designer (or design manager) to demonstrate that. To transform design process achievements and insights into business terminology in a way that’s understandable and conclusive.
To do so, a designer with business value in mind must practice to think, learn, and act like a business person. Studying similar materials, learning about business foundations, and developing a bird’s-eye view on how everything is running. This is a proactive effort and not exactly included in a typical daily designer tasks or job description.
When you think about it, it’s hard to unsee the fact that in a typical design process, the closer you get to the so-called “business” part of the model (which usually includes delivering, shipping etc.) the closer you are to see your decisions immediate impact.
Based on combined diagram of double diamond and elements of UX model by @Andrew Aquino
However, it’s important to remember that the notion of developing this business and strategic mindset for designers, shouldn’t turn into a deviation from user-centeric approach. It’s quite the opposite in fact, it turns out this mindset helps the outcomes of user research and earlier steps of product design process actually get shipped to customers faster, by getting signed-off easier by all business stakeholders
As a recap, the recommendation is developing a business mindset for product designers, rather than maybe getting closer to coding or getting too focused on the latest visual trends. This is the way not only to actually get the job done, but also delivered and shipped effectively. | https://medium.com/design-bootcamp/good-designer-is-good-businessperson-f8bd681d28c6 | ['Rasam Rostami'] | 2020-11-25 00:16:24.183000+00:00 | ['Strategy', 'Design', 'Business', 'Design Thinking', 'Entrepreneurship'] | Title good designer good businesspersonContent IBM’s president Thomas J Jr Watson’s “Good Design Good Business” 1973 saying making much sense tech business space Building shipping digital even nondigital product getting easier every day making design play even recognizable role ever One byproduct fact according John Maeda’s design tech report rising rate involving designer early stage startup core builder fact number successful startup founded designer might surprising people surge design’s extending functionality business rise demand business training education designer area neglected design school program Many employer prefer hiring designer solid business understanding career path mostly lead getting involved management area serving direct business objective business value design discussed measured various paper report famously McKinsey report said many team still struggle find meaningful relationship design team performance achieving business objective issue lie design team managed directed whole design function general short need address business value design team it’s unlikely good one Products service getting closer user individually crafted experience Given opportunity usercentric design approach also expected deliver readily visible business value It’s ultimately job designer design manager demonstrate transform design process achievement insight business terminology way that’s understandable conclusive designer business value mind must practice think learn act like business person Studying similar material learning business foundation developing bird’seye view everything running proactive effort exactly included typical daily designer task job description think it’s hard unsee fact typical design process closer get socalled “business” part model usually includes delivering shipping etc closer see decision immediate impact Based combined diagram double diamond element UX model Andrew Aquino However it’s important remember notion developing business strategic mindset designer shouldn’t turn deviation usercenteric approach It’s quite opposite fact turn mindset help outcome user research earlier step product design process actually get shipped customer faster getting signedoff easier business stakeholder recap recommendation developing business mindset product designer rather maybe getting closer coding getting focused latest visual trend way actually get job done also delivered shipped effectivelyTags Strategy Design Business Design Thinking Entrepreneurship |
945 | EcoHelmet’s Isis Shiffer on: “How thinking wrong can be so right” | In my second year of graduate school I became fixated by the idea of designing a helmet for bike share. I was studying abroad and found riding in Tokyo to be alarming. The enormous public Mamachari bikes topped out at 8 miles per hour, but still I had plenty of white-knuckle encounters with the city’s slow but unyielding traffic. I was unused to cars driving on the left, the roads were narrow and hilly, and my brakes didn’t work too well either. On more than one occasion I scrunched into someone’s hedge so as to avoid a bright pink Kei truck. Only racers wear bike helmets in Japan, but I would have liked one all the same.
So, I started messing around. I wanted something that could go in a briefcase or a vending machine, cost little, be sustainably made, work like a regular helmet, and not look too foolish. Traditional Styrofoam was out of the question, as it doesn’t biodegrade, and most other materials were too heavy, too expensive, or wouldn’t fold up. I had read somewhere about paper honeycomb absorbing blows well. So, I thought to myself, let’s try that.
I knocked together a prototype that looked like a pineapple, put it on the floor and tried to drive my boot through it. It didn’t dent at all. I showed my it to a professor.
“A paper helmet?” she laughed. “What an idea. That won’t possibly work.”
“You just watch me,” I thought. A mildly interesting side project suddenly became a burning passion.
Then as now, telling me something won’t work activates a deeply stubborn part of my nature. If a client or contractor tells me something can’t be done my first impulse is to dig in my heels and insist that nothing is impossible. “I’ll just sort it out myself then” is one of my most commonly used phrases. Often the problem in question turns out to genuinely be insoluble and I have to sheepishly admit it. Other times by luck or advice or sheer will, I’m able to prove everyone wrong and force the absurd idea through — whether the effort was worthwhile is another issue.
Isis is a wrong thinker, this means she practices thinking differently at her studio | Photography Dyson
This strain of stubbornness is common amongst designers and inventors, who regularly have to convince a baffled world that a seemingly poor idea is actually the nucleus for innovation. This is not to say there are “no bad ideas” — a phrase used far too often — because, of course, there are.
Instead, I’d say that approaching any problem from strange or counter-intuitive directions can lead to amazing results. An argument can be made that without ideas that spring from a non-linear thought process our world would look very different. Without wrong thinking we would not have internal combustion engines, saxophones, cheese, super glue, penicillin — the list goes on.
“Industrial design falls squarely between art and science, and a good designer can operate to an extent in both.”
Before I went into industrial design I built bicycle frames for a living. I liked designing the fancy lugs and the colour schemes and tailoring the frame geometry exactly to a customer’s body (I retain the ability to tell someone how tall they are and what size bike they should ride just by looking at them). But after a few years I became bored — a bike is a bike.
Shortly before I quit to go back to school for design, I was at a trade show and found myself admiring a very unusual bicycle indeed. ‘Old Faithful’ looks like what someone would draw if they had heard a bike described but never actually seen one: there is no top tube, only one fork blade, almost no space between the pedals, and the bars and saddle are placed ludicrously close together. It was invented by a Scottish cyclist named Graeme Obree. Already competitive on ordinary bikes, Obree believed that traditional frame design was inefficient and built a bike for himself that solved all the problems, as be he saw them. The strange bar and saddle position upended traditional cycling posture and forces the rider to fold themself up a bit like a downhill skier. It looks ridiculous, and frankly if someone had asked me to build one I would have laughed them straight out of my bicycle shop.
I was lucky enough to try a replica of Old Faithful at that show, and it was unlike any cycling experience I’ve ever had. My arms cramped up in minutes and it felt deeply counter-intuitive to be leading with my face, but once I got going it began to make sense. As I wobbled around the bike testing area, dodging electric trikes and full suspension mountain bikes, I got a tiny echo of how very powerful this machine could be with the right rider in the right conditions.
Sir James Dyson meeting with Isis after her EcoHelmet won the 2016 James Dyson Award | Photography Dyson
Most new bicycle designs tend to build on what came before them, refining rather than rethinking. This one broke most of the accepted rules of bicycle design, and most designers would have found dozens of things wrong with it. It’s worth adding that, riding Old Faithful, Graeme Obree broke the hour record — twice.
Graeme Obree was a cyclist who wanted to go faster. Unburdened by design and engineering conventions he turned wrongthink to his advantage, tinkering in his bike shop and testing the results until he was satisfied.
But Wrongthink can also happen suddenly, as when a thoughtful person does something stupid and learns from it. My father, an auto mechanic, used to tell me about an inventor named Henry ‘Smokey’ Yunick who seemed to do this a lot. One story in particular stuck with me. Smokey wanted to convert an old, empty gasoline barrel into a trash can. He began to cut one end off with a torch, and found himself flat on the ground with his eyebrows blown off. Rather than retreating in embarrassment and nursing his scorched face, Smokey stuck a rag on a pole, lit it on fire, and stuck it in another empty barrel — KABOOM. Smokey thought to himself, an empty barrel exploding had to be useful somehow, and he later developed a long-range sparkplug that ignited from gasoline vapours alone.
I still think of this story when I do something truly ill advised — such as when I forgot to tighten down the fuel lines on a new brazing torch and blew my own eyebrows off (I gained no engineering insights, unfortunately). Smokey Yunick would not have admitted to being wrong thinker of course, nor did he consider himself an engineer, but he held twelve patents and many of his inventions are still used today.
In its most useful format, wrongthink arises organically. When a project is predicated on wrong thinking it becomes an intellectual exercise and can lead to a great deal of labour for no particular reason. Every year, American civil engineering students sink time, blood and energy into the infamous National Concrete Canoe Competition.
The goal is to take a non-floating material and use it to make a functioning boat, which is then raced. Everyone works hard and has a wonderful time, but ultimately what is left is a pile of barely seaworthy boats and a questionable lesson. Yes, they have taken a bad idea and made it work, but why? Would the entrants not learn more by trying to create genuinely useful boats, or at the very least change the material choice year to year?
Humans love to create specific, repeatable processes for the things we do, but it’s not applicable in every field. While STEM projects often follow a predetermined path, many artists approach their work from an abstract place, closer to subconscious inspiration than scientific research. Industrial design falls squarely between art and science, and a good designer can operate to an extent in both.
I am as likely to attack a tricky problem in my studio with math and research as I am to go cycle around the park for a while to see if the solution is actually lurking somewhere out in the real world. Very often I’ll be doing something entirely different, like buying groceries or watching a movie, and the solution to a problem that’s been bugging me for weeks slips into my mind fully solved. This does n’t always work. I occasionally rocket out of bed having dreamed something absolutely world-shatteringly brilliant only to discover the next day that the scratchy drawing in my bedside notepad is something I saw a few days prior or perhaps makes no sense at all.
Not everyone agrees that design exists in a nebulous, thrilling place between process and inspiration. I was introduced to design thinking by an elderly professor who spoke slowly, used innumerable blurry charts and had an unimpeachable resume in UX design. He insisted that every project must be proscribed, from colour coded post-it notes at the ideation phase to scripted talks at the end. Each step was scrutinized, and the slightest deviation was quashed. I thought it was the most deadening, wrongheaded approach to design I had ever seen, and I am still averse to post-it notes years on. In a series of increasingly fractious interactions I insisted that creativity is best nurtured by going outside and doing things, seeing things, taking things apart. The professor insisted my approach was the same as throwing random bits of metal at a wall and expecting them to magically become a train. I’m convinced I only passed his class only because he wanted to make sure he never saw me again.
The EcoHelmet which Isis was told would “never work” | Photography Dyson
That said, I’ve softened towards design thinking as I’ve discovered how valuable it can be — though not necessarily for designing things. I’ve used it to get teams on the same page and, though I hate to admit it, to concentrate my own restless thoughts.
After I finished my studies in Tokyo I relocated to London for a term at Royal College of Art (RCA) and Imperial College London. This time I brought along a bike of my own and a helmet. I spent many lovely hours cycling through the city and being shouted at by motorists while I tried to remember which way one is supposed traverse a roundabout. When I did find myself on a so-called ‘Boris Bike’ I felt the lack of helmets even more keenly, as London’s traffic makes that of my native New York City look sedate. I reanimated the bike helmet project, and was met with more scepticism, though less than before.
“That’s an interesting idea,” one tutor said. I wondered whether he was employing British irony or actually meant it. “Why don’t you see if that actually works?” he advised.
I brought an armload of samples to Imperial’s crash lab and, with the help of the wonderful staff, I was finally able to get some verification. Some samples failed, but a few stopped a blow much like a traditional helmet — the paper crushed under the hammer, distributing the pressure around the dummy head and leaving it unscathed.
“We have a pass!” said the lab’s technician smiling at me.
I remember ricocheting out of lab, bits of crushed paper spilling from my hands. I had been doggedly insisting for months my helmet would work, but privately I had nothing more than a hunch I only half believed myself and an inability to admit I might be wrong. By any metric, a blow stopping, aesthetically pleasing, weather-worthy piece of sports equipment should be made of anything but paper. Now, while it was far from complete, the concept was proved sound and worth pursuing- and no one was more surprised than I — showing that sometimes you have to prove yourself wrong first. | https://medium.com/dyson-on/ecohelmets-isis-shiffer-on-how-thinking-wrong-can-be-so-right-e2116849df11 | ['Dyson On'] | 2019-05-29 15:00:25.916000+00:00 | ['Technology', 'Innovation', 'Design', 'Dyson', 'Engineering'] | Title EcoHelmet’s Isis Shiffer “How thinking wrong right”Content second year graduate school became fixated idea designing helmet bike share studying abroad found riding Tokyo alarming enormous public Mamachari bike topped 8 mile per hour still plenty whiteknuckle encounter city’s slow unyielding traffic unused car driving left road narrow hilly brake didn’t work well either one occasion scrunched someone’s hedge avoid bright pink Kei truck racer wear bike helmet Japan would liked one started messing around wanted something could go briefcase vending machine cost little sustainably made work like regular helmet look foolish Traditional Styrofoam question doesn’t biodegrade material heavy expensive wouldn’t fold read somewhere paper honeycomb absorbing blow well thought let’s try knocked together prototype looked like pineapple put floor tried drive boot didn’t dent showed professor “A paper helmet” laughed “What idea won’t possibly work” “You watch me” thought mildly interesting side project suddenly became burning passion telling something won’t work activates deeply stubborn part nature client contractor tell something can’t done first impulse dig heel insist nothing impossible “I’ll sort then” one commonly used phrase Often problem question turn genuinely insoluble sheepishly admit time luck advice sheer I’m able prove everyone wrong force absurd idea — whether effort worthwhile another issue Isis wrong thinker mean practice thinking differently studio Photography Dyson strain stubbornness common amongst designer inventor regularly convince baffled world seemingly poor idea actually nucleus innovation say “no bad ideas” — phrase used far often — course Instead I’d say approaching problem strange counterintuitive direction lead amazing result argument made without idea spring nonlinear thought process world would look different Without wrong thinking would internal combustion engine saxophone cheese super glue penicillin — list go “Industrial design fall squarely art science good designer operate extent both” went industrial design built bicycle frame living liked designing fancy lug colour scheme tailoring frame geometry exactly customer’s body retain ability tell someone tall size bike ride looking year became bored — bike bike Shortly quit go back school design trade show found admiring unusual bicycle indeed ‘Old Faithful’ look like someone would draw heard bike described never actually seen one top tube one fork blade almost space pedal bar saddle placed ludicrously close together invented Scottish cyclist named Graeme Obree Already competitive ordinary bike Obree believed traditional frame design inefficient built bike solved problem saw strange bar saddle position upended traditional cycling posture force rider fold themself bit like downhill skier look ridiculous frankly someone asked build one would laughed straight bicycle shop lucky enough try replica Old Faithful show unlike cycling experience I’ve ever arm cramped minute felt deeply counterintuitive leading face got going began make sense wobbled around bike testing area dodging electric trike full suspension mountain bike got tiny echo powerful machine could right rider right condition Sir James Dyson meeting Isis EcoHelmet 2016 James Dyson Award Photography Dyson new bicycle design tend build came refining rather rethinking one broke accepted rule bicycle design designer would found dozen thing wrong It’s worth adding riding Old Faithful Graeme Obree broke hour record — twice Graeme Obree cyclist wanted go faster Unburdened design engineering convention turned wrongthink advantage tinkering bike shop testing result satisfied Wrongthink also happen suddenly thoughtful person something stupid learns father auto mechanic used tell inventor named Henry ‘Smokey’ Yunick seemed lot One story particular stuck Smokey wanted convert old empty gasoline barrel trash began cut one end torch found flat ground eyebrow blown Rather retreating embarrassment nursing scorched face Smokey stuck rag pole lit fire stuck another empty barrel — KABOOM Smokey thought empty barrel exploding useful somehow later developed longrange sparkplug ignited gasoline vapour alone still think story something truly ill advised — forgot tighten fuel line new brazing torch blew eyebrow gained engineering insight unfortunately Smokey Yunick would admitted wrong thinker course consider engineer held twelve patent many invention still used today useful format wrongthink arises organically project predicated wrong thinking becomes intellectual exercise lead great deal labour particular reason Every year American civil engineering student sink time blood energy infamous National Concrete Canoe Competition goal take nonfloating material use make functioning boat raced Everyone work hard wonderful time ultimately left pile barely seaworthy boat questionable lesson Yes taken bad idea made work Would entrant learn trying create genuinely useful boat least change material choice year year Humans love create specific repeatable process thing it’s applicable every field STEM project often follow predetermined path many artist approach work abstract place closer subconscious inspiration scientific research Industrial design fall squarely art science good designer operate extent likely attack tricky problem studio math research go cycle around park see solution actually lurking somewhere real world often I’ll something entirely different like buying grocery watching movie solution problem that’s bugging week slip mind fully solved n’t always work occasionally rocket bed dreamed something absolutely worldshatteringly brilliant discover next day scratchy drawing bedside notepad something saw day prior perhaps make sense everyone agrees design exists nebulous thrilling place process inspiration introduced design thinking elderly professor spoke slowly used innumerable blurry chart unimpeachable resume UX design insisted every project must proscribed colour coded postit note ideation phase scripted talk end step scrutinized slightest deviation quashed thought deadening wrongheaded approach design ever seen still averse postit note year series increasingly fractious interaction insisted creativity best nurtured going outside thing seeing thing taking thing apart professor insisted approach throwing random bit metal wall expecting magically become train I’m convinced passed class wanted make sure never saw EcoHelmet Isis told would “never work” Photography Dyson said I’ve softened towards design thinking I’ve discovered valuable — though necessarily designing thing I’ve used get team page though hate admit concentrate restless thought finished study Tokyo relocated London term Royal College Art RCA Imperial College London time brought along bike helmet spent many lovely hour cycling city shouted motorist tried remember way one supposed traverse roundabout find socalled ‘Boris Bike’ felt lack helmet even keenly London’s traffic make native New York City look sedate reanimated bike helmet project met scepticism though le “That’s interesting idea” one tutor said wondered whether employing British irony actually meant “Why don’t see actually works” advised brought armload sample Imperial’s crash lab help wonderful staff finally able get verification sample failed stopped blow much like traditional helmet — paper crushed hammer distributing pressure around dummy head leaving unscathed “We pass” said lab’s technician smiling remember ricocheting lab bit crushed paper spilling hand doggedly insisting month helmet would work privately nothing hunch half believed inability admit might wrong metric blow stopping aesthetically pleasing weatherworthy piece sport equipment made anything paper far complete concept proved sound worth pursuing one surprised — showing sometimes prove wrong firstTags Technology Innovation Design Dyson Engineering |
946 | Stay Healthy. Stay Data-Informed. | This was first published on my mailing list The Year of the Looking Glass. Sign up to get essays like these in your inbox 1–2 times a month.
I have a confession to make.
As a designer, for years my primary goal was striving to improve my product intuition.
You see, I believed:
The most wonderful products are that way because of a leader’s keen insights borne of their intuition.
People in suits and ties looking at sheets and sheets of numbers are missing the critical point — what it feels like. What’s the story that’s going around. Where the culture is pointed.
The main difference between senior and junior designers was the strength and quality of their intuition.
I believed the above with a deep and abiding fervor. The best designers I knew at the time had an alluring confidence borne of their well-honed sense of what was good and wasn’t. I strove to be like them, listening and inhaling and jumping obstacles on the quest for that holy grail of taste. In fact, I wore my early-adoptnerness as a lifestyle, a badge of pride. I joined Facebook over Microsoft in 2006 because it was a product my friends and I used everyday. I sang the praises of my Welsh Airbnb hosts’ hearty breakfast when most people were like, You stayed in a stranger’s house in another country? I never advanced my poor cooking skills because I switched to getting meals delivered every day as soon as food delivery services got started.
As such, I regarded the use of big data to make judgements the way I would an attractive peddler with a golden voice coming to town to sell cures for a broken heart: with extreme skepticism.
And — it was true! — I saw misuses under the banner of “be data-driven!” everywhere. (And while we are at it, let’s retire the term “data-driven,” shall we? It implies spreadsheets are at the wheel of your decisions, not humans.) Hordes of A/B tests that had teams running on treadmills busily shipping, but doing little to truly improve things. Hours of analyses that focused on micro-optimizations. Data being used to justify decisions that plain and simply felt incorrect, only to later find — oops, the logging was wrong. I wrote lots of articles here and here and here to broadcast the message of “practice safe data-informedness!”
But really, I thought we were all really overdoing it. I nodded vigorously when Jeff Bezos said that in his experience, when anecdotes and data diverge, he believes the anecdotes. Here, in the living breathing world, we are not all perfectly rational beings. It’s stories that brings tears to our eyes, not numbers.
We follow our hearts and guts, not kanban boards and excel sheets.
I don’t know exactly when this started changing for me, but it did. Maybe it was one too many experiences like this one. Maybe it was the Nth time my intuition turned out to be wrong in some small way, like Wow, as much as I love me an aesthetically pleasing uncluttered set of icons with no labels, somehow the vast majority of the world appreciates and finds things easier to use with labels. Or maybe I just wised up and realized that data is no different than a sword or a hammer or that excel sheet I keep bashing — it can be used well or it can be used poorly. Whatever the reason, I’m now firmly on the other side. I believe that most people, teams, companies, industries could function better by using more data better.
One of the best things about working at Facebook-scale, where every day millions or billions of people interact with what you design, is that you quickly become humbled by how little you can intuit about what works for someone who just got on the Internet for the first time and is trying to set up their first profile and make their first post. The world is soaringly vast in its complexity. To think our little molecule of an individual experience can be relied on help us understand the nuances of its evolution and ecosystems and weather formations is hubris. Taste, that lovely thing, is simply an ability to make a small ripple in the small pond we are familiar with; sometimes, luck takes that ripple and propels it across other ponds and oceans.
These past few weeks, with the weight of the coronavirus situation, I’ve felt all this so much more keenly. How easy is it to dismiss the risk of contagion when it was happening on the other side of the globe? How simple is it to tell ourselves — especially those of us who are young and healthy — that going to that party, or grabbing that coffee down the street, or hopping onto that train — is no big deal?
The enemy is invisible. The greatest defenses against this threat are classic “slow ideas” as described by writer and doctor Atul Gawande — actions where the impact is not immediately seen or felt. You will not know that you were infected for maybe a week, if at all. You will not go to the hospital or die until two weeks after that, if at all. By the time the hospitals have sounded the alarms, it will be too late.
Our brains don’t do well with slow ideas. For years, I have been waging a war with myself to get more sleep and exercise. We’ve heard the refrain over and over again — this is good for us. And yet, my health in 5, 10, 25 years constantly loses battles to the immediate satisfaction of time spent with friends, the completion of an episode, a new check on the to-do list, or simply the allure of words across a bright screen.
But this is the beauty and power of data. As new and scary as the coronavirus is, we are not flying blind. We know things from Wuhan and Italy, from the H1N1 flu of 2009 and the H2N2 flu of 1957. My understanding of our current situation has been made all the more tangible with well-articulated analyses written by those who study numbers and make excel spreadsheets. For example, this chart (pasted below) makes it exceedingly clear that the US is on a similar trajectory to Italy and that we too will be fast approaching the red zone without greater steps (which luckily states and counties are starting to take.)
As another example, these two articles, Coronavirus: Why You Must Act Now and Don’t flatten the Curve, Stop it! both left a deep impression on me because they get specific with their estimates based on well-founded numbers — how many hospital beds and respirators we have today, what the infection rate might be, what the transmission timeline looks like. As a result, you can critique the process, double-check the numbers, and judge the trustworthiness of the conclusion.
Many of you know that I’ve partnered with my friend Chandra Narayanan to start an advising company called Inspirit. Chandra ran data at Facebook and Sequoia, and I think of him as one of the best data leaders in the world. Besides the fact that I am forever trying to emulate his wisdom and depth of care, I feel so lucky to work with Chandra because I get a first-row seat into how he approaches problems.
One thing he said about data and design has always been on my mind:
Diagnose with data. Treat with design.
How wonderfully simple and powerful that statement is.
Great solutions are built upon solid and accurate assumptions about the world. You can’t solve jack if your assumptions are off. And they are likely to be off in any scenario that involves millions or billions of people, involve a topic you haven’t studied deeply, or where you don’t have good data.
Rather than surfing by on intuition and taste, the data-informed individual adopts a beginner’s mindset: Assume you know nothing.
Then, frame what you believe as assumptions or hypotheses. These are incredibly empowering words to help you get to great design. I am assuming… My hypothesis is… These words make it okay to be wrong, because they paint you as a truth-seeker rather than an egoist. These words invite contribution and follow-up questions from others, including the ever-critical Why?
These words opens the door for your assumptions or hypotheses to be validated through data, like what Coronavirus: Why You Must Act Now and Don’t flatten the Curve, Stop it! have done. Are hospitals going be over capacity with the coronavirus? What would convince us one way or another? Let’s calculate the number of bed or special equipment needed to treat COVID-19 cases. Let’s calculate the number of people who are likely to be at the hospital for non-COVID-19 cases. Let’s calculate the likely rate of spread and hospitalization based on what we know from other countries. Trust the process, and you can trust the conclusion.
Furthermore, looking at data helps you spot opportunities for new hypotheses. Chandra noticed a few weeks ago that infections seemed greater in places that were cold. He hypothesized that perhaps the virus doesn’t spread as easily in hot temperatures. Chinese scientists had a similar hypothesis, and their preliminary study results from analyzing 100 Chinese cities seem to indicate a relationship between lower transmission rate and higher temperature and humidity.
Once you have a believable diagnosis of the problem, that’s where design jumps in.
Data cannot solve problems. It can only help you identify and understand them.
Design is the treatment, the phase where you brainstorm all the ways that the problem can be solved. Social distancing. Government policies that incentivize social distancing. Investments in faster production of critical supplies like masks and respirators. Greater and more efficient testing. Better ways for important information to get to the right people. Online learning. Giving aid to those most deeply affected. Developing and experimenting with new treatments. (If you are interested in how you can get involved, I just heard of this list of COVID-19 projects looking for volunteers here.)
There are also the things we must do for ourselves and our loved ones, to get through each day. Get a full night’s sleep. Count the blessings we do have. Text or call hello. Let nature rejuvenate our souls. Be kind to one another, especially those who are the most vulnerable or are the hardest hit.
There is a surreal quality to such massive disruption on a global scale, like an entire year’s (decade’s?) worth of drama compressed into one sychronized dance, where health systems, stock markets, sports, work, schools and elections are all spinning wildly in chaos together.
There’s a lot more to weather in the days, weeks and months ahead.
Stay healthy. Stay calm.
Let’s make the best decisions we can by seeking out the best data we have.
Some useful data sites related to COVID-19: | https://medium.com/the-year-of-the-looking-glass/stay-healthy-stay-data-informed-d62da66951d7 | ['Julie Zhuo'] | 2020-03-18 17:52:47.017000+00:00 | ['Design Thinking', 'Design', 'Data', 'Data Science', 'Coronavirus'] | Title Stay Healthy Stay DataInformedContent first published mailing list Year Looking Glass Sign get essay like inbox 1–2 time month confession make designer year primary goal striving improve product intuition see believed wonderful product way leader’s keen insight borne intuition People suit tie looking sheet sheet number missing critical point — feel like What’s story that’s going around culture pointed main difference senior junior designer strength quality intuition believed deep abiding fervor best designer knew time alluring confidence borne wellhoned sense good wasn’t strove like listening inhaling jumping obstacle quest holy grail taste fact wore earlyadoptnerness lifestyle badge pride joined Facebook Microsoft 2006 product friend used everyday sang praise Welsh Airbnb hosts’ hearty breakfast people like stayed stranger’s house another country never advanced poor cooking skill switched getting meal delivered every day soon food delivery service got started regarded use big data make judgement way would attractive peddler golden voice coming town sell cure broken heart extreme skepticism — true — saw misuse banner “be datadriven” everywhere let’s retire term “datadriven” shall implies spreadsheet wheel decision human Hordes AB test team running treadmill busily shipping little truly improve thing Hours analysis focused microoptimizations Data used justify decision plain simply felt incorrect later find — oops logging wrong wrote lot article broadcast message “practice safe datainformedness” really thought really overdoing nodded vigorously Jeff Bezos said experience anecdote data diverge belief anecdote living breathing world perfectly rational being It’s story brings tear eye number follow heart gut kanban board excel sheet don’t know exactly started changing Maybe one many experience like one Maybe Nth time intuition turned wrong small way like Wow much love aesthetically pleasing uncluttered set icon label somehow vast majority world appreciates find thing easier use label maybe wised realized data different sword hammer excel sheet keep bashing — used well used poorly Whatever reason I’m firmly side believe people team company industry could function better using data better One best thing working Facebookscale every day million billion people interact design quickly become humbled little intuit work someone got Internet first time trying set first profile make first post world soaringly vast complexity think little molecule individual experience relied help u understand nuance evolution ecosystem weather formation hubris Taste lovely thing simply ability make small ripple small pond familiar sometimes luck take ripple propels across pond ocean past week weight coronavirus situation I’ve felt much keenly easy dismiss risk contagion happening side globe simple tell — especially u young healthy — going party grabbing coffee street hopping onto train — big deal enemy invisible greatest defense threat classic “slow ideas” described writer doctor Atul Gawande — action impact immediately seen felt know infected maybe week go hospital die two week time hospital sounded alarm late brain don’t well slow idea year waging war get sleep exercise We’ve heard refrain — good u yet health 5 10 25 year constantly loses battle immediate satisfaction time spent friend completion episode new check todo list simply allure word across bright screen beauty power data new scary coronavirus flying blind know thing Wuhan Italy H1N1 flu 2009 H2N2 flu 1957 understanding current situation made tangible wellarticulated analysis written study number make excel spreadsheet example chart pasted make exceedingly clear US similar trajectory Italy fast approaching red zone without greater step luckily state county starting take another example two article Coronavirus Must Act Don’t flatten Curve Stop left deep impression get specific estimate based wellfounded number — many hospital bed respirator today infection rate might transmission timeline look like result critique process doublecheck number judge trustworthiness conclusion Many know I’ve partnered friend Chandra Narayanan start advising company called Inspirit Chandra ran data Facebook Sequoia think one best data leader world Besides fact forever trying emulate wisdom depth care feel lucky work Chandra get firstrow seat approach problem One thing said data design always mind Diagnose data Treat design wonderfully simple powerful statement Great solution built upon solid accurate assumption world can’t solve jack assumption likely scenario involves million billion people involve topic haven’t studied deeply don’t good data Rather surfing intuition taste datainformed individual adopts beginner’s mindset Assume know nothing frame believe assumption hypothesis incredibly empowering word help get great design assuming… hypothesis is… word make okay wrong paint truthseeker rather egoist word invite contribution followup question others including evercritical word open door assumption hypothesis validated data like Coronavirus Must Act Don’t flatten Curve Stop done hospital going capacity coronavirus would convince u one way another Let’s calculate number bed special equipment needed treat COVID19 case Let’s calculate number people likely hospital nonCOVID19 case Let’s calculate likely rate spread hospitalization based know country Trust process trust conclusion Furthermore looking data help spot opportunity new hypothesis Chandra noticed week ago infection seemed greater place cold hypothesized perhaps virus doesn’t spread easily hot temperature Chinese scientist similar hypothesis preliminary study result analyzing 100 Chinese city seem indicate relationship lower transmission rate higher temperature humidity believable diagnosis problem that’s design jump Data cannot solve problem help identify understand Design treatment phase brainstorm way problem solved Social distancing Government policy incentivize social distancing Investments faster production critical supply like mask respirator Greater efficient testing Better way important information get right people Online learning Giving aid deeply affected Developing experimenting new treatment interested get involved heard list COVID19 project looking volunteer also thing must loved one get day Get full night’s sleep Count blessing Text call hello Let nature rejuvenate soul kind one another especially vulnerable hardest hit surreal quality massive disruption global scale like entire year’s decade’s worth drama compressed one sychronized dance health system stock market sport work school election spinning wildly chaos together There’s lot weather day week month ahead Stay healthy Stay calm Let’s make best decision seeking best data useful data site related COVID19Tags Design Thinking Design Data Data Science Coronavirus |
947 | Artificial intelligence is here. Now what? | Claire Merchlinsky. www.nytimes.com. “How to Build Artificial Intelligence We Can Trust.”
On February 10, 1996, world chess champion Garry Kasparov lost his first game to Deep Blue. Kasparov hails from Baku; Deep Blue, from IBM. The face-off took three hours and went down in history as the first instance a computer has beaten a human at the game. But that was 1996, not 2020.
Deep Blue was not the first nor the last in a dynasty of software programs whose family identity seems to be besting humans at human activities. The chess players produced by IBM have grown increasingly adept, but there are now other classes of computers. Computers control our cars as cybernetic chauffeurs. They teach our children. They help those with disabilities, they provide medical diagnoses, and they fish through the farthest reaches of the ethernet for answers to our most recent questions.
The list goes on. Even more perplexing, some of these computers have weaseled their ways into our hearts (despite having no emotional intelligence that we know of).
I’m reminded of one such computer in particular, also from the suite of IBM savants and bearing the eerily humanoid name of Watson. Ring a bell?
In 2011, when I was 11 years old, Watson made history when “he” went on Jeopardy! and faced off against the brightest trivia minds out there, which meant 74-time champion Ken Jennings and past champion Brad Rutter. “I, for one, welcome our new computer overlords,” Jennings wrote on his question card when facing imminent and obvious defeat. With this surrender he made reference to “The Simpsons,” an apt choice from a show that has garnered a reputation for predicting our future before we can do so ourselves.
www.youtube.com. “Watson and the Jeopardy! Challenge.”
“In the end, the humans on Jeopardy! surrendered meekly,” John Markoff wrote for the New York Times after the whole affair had died down. And the humans did, treating the victory as a gimmick or publicity stunt of sorts. Those involved responded to the news with humor, perhaps masking the greater implications of a computer capable of recalling facts from nothing at the drop of a pin. Watson beckoned comparisons to HAL from 2001: A Space Odyssey. This led to unease amongst some; few would welcome a HAL into our world.
www.youtube.com. “2001 — A Space Odyssey.”
Yet most of us, including myself, were excited to see Watson win. I still remember watching the episode with my parents, gathered around a single monitor. We rarely watched Jeopardy! as a family, yet this was history and we knew it. Everyone watched. And everyone wanted Watson to win. The programmers at IBM had designed a program that could elicit in humans a sympathy response, a want to love and nurture this baby in its infancy stages. Watson appeared lovable and clueless in the first few rounds of the game show. To one answer he responded with the question, “What is Toronto????” His multiple question marks were met with laughter. Watson was clumsy, unsure, not afraid to make fun of himself.
This is the real underpin of the artificial intelligence revolution.
Artificial intelligence is here. It’s been here for decades already. But artificial intelligence that we perceive as human, as worthy of emotion, that’s the more complicated part. Watson, with his human name, is the first in a line of robots designed to evoke a human response. Think of Siri and Alexa, similar programs capable of fitting in the palms of our hands whose feminized names and voice acting give them human dimensions (surely, you’ve heard of people jokingly asking their Siris and Alexas dumb questions and waiting for programmed joke responses). When confronted with it, artificial intelligence seems to have us finding the humor of it all or, on the other side of the coin, deeply repulsed.
This repulsion stems not from what the technology is capable of, but from the eery ways in which artificial intelligence attempts to mimic human life. In 2014, Alex Garland’s Ex Machina made its rounds through film circles and the general public and had its critics lauding it as a creepy look at the “disquieting power struggle waged in terms of human weaknesses” (Buzzfeed News). A power struggle. This is the fear, the source of repulsion. This is what scares us: computers who are perhaps “human+,” more feeling, more thinking, more skilled and capable than ourselves.
The female subject of Ex Machina is a beautiful robot named Ava, whose doll-like features and desire for freedom immediately endear her to the film’s protagonist. She ultimately backstabs him in pursuit of her own agenda. This proves that she is capable of passing the Turing test, the ultimate test in the timeline of artificial intelligence that marks at what point a machine is indistinguishable from a human. In the case of Ava and even of the robots we can expect will one day walk the earth, this is not the right test. These robots do not just resemble humans; they are more human. Superior in many regards. Ava is certainly human by this measure. Not only does she have wants and needs, but a higher level of emotional intellect that allows her to manipulate. Yet Ava is more than human, cunning like no other, more intelligent, more artistic.
www.youtube.com. “Meeting Ava in Ex Machina.”
Artificial intelligence, whether real or fictional, from Watson to HAL 9000 to Ava, forces us to question what we will do in response to this new species on our planet.
Perhaps our goal should not be to build the machine that mimics its human counterpart, but the machine that is “human+.” Or maybe even the machine that is “human nothing.” The machine whose aesthetic is a sharp departure from humanoid, the machine that does not attempt to blend in with us or copy our affectations but is beautiful in its own way.
Is our fear of these computers valid? It does not matter. Whether we like it or not, these computers are here to stay. All we can control is our response to them. As Ken Jennings quoting Kent Brockman quoting H.G. Wells said, “I, for one, welcome our new computer overlords.” | https://medium.com/swlh/artificial-intelligence-is-here-now-what-ea63634e9303 | ['Margaret Cirino'] | 2020-03-03 06:52:05.698000+00:00 | ['Technology', 'Artificial Intelligence', 'Computer Science', 'Future', 'Culture'] | Title Artificial intelligence whatContent Claire Merchlinsky wwwnytimescom “How Build Artificial Intelligence Trust” February 10 1996 world chess champion Garry Kasparov lost first game Deep Blue Kasparov hail Baku Deep Blue IBM faceoff took three hour went history first instance computer beaten human game 1996 2020 Deep Blue first last dynasty software program whose family identity seems besting human human activity chess player produced IBM grown increasingly adept class computer Computers control car cybernetic chauffeur teach child help disability provide medical diagnosis fish farthest reach ethernet answer recent question list go Even perplexing computer weaseled way heart despite emotional intelligence know I’m reminded one computer particular also suite IBM savant bearing eerily humanoid name Watson Ring bell 2011 11 year old Watson made history “he” went Jeopardy faced brightest trivia mind meant 74time champion Ken Jennings past champion Brad Rutter “I one welcome new computer overlords” Jennings wrote question card facing imminent obvious defeat surrender made reference “The Simpsons” apt choice show garnered reputation predicting future wwwyoutubecom “Watson Jeopardy Challenge” “In end human Jeopardy surrendered meekly” John Markoff wrote New York Times whole affair died human treating victory gimmick publicity stunt sort involved responded news humor perhaps masking greater implication computer capable recalling fact nothing drop pin Watson beckoned comparison HAL 2001 Space Odyssey led unease amongst would welcome HAL world wwwyoutubecom “2001 — Space Odyssey” Yet u including excited see Watson win still remember watching episode parent gathered around single monitor rarely watched Jeopardy family yet history knew Everyone watched everyone wanted Watson win programmer IBM designed program could elicit human sympathy response want love nurture baby infancy stage Watson appeared lovable clueless first round game show one answer responded question “What Toronto” multiple question mark met laughter Watson clumsy unsure afraid make fun real underpin artificial intelligence revolution Artificial intelligence It’s decade already artificial intelligence perceive human worthy emotion that’s complicated part Watson human name first line robot designed evoke human response Think Siri Alexa similar program capable fitting palm hand whose feminized name voice acting give human dimension surely you’ve heard people jokingly asking Siris Alexas dumb question waiting programmed joke response confronted artificial intelligence seems u finding humor side coin deeply repulsed repulsion stem technology capable eery way artificial intelligence attempt mimic human life 2014 Alex Garland’s Ex Machina made round film circle general public critic lauding creepy look “disquieting power struggle waged term human weaknesses” Buzzfeed News power struggle fear source repulsion scare u computer perhaps “human” feeling thinking skilled capable female subject Ex Machina beautiful robot named Ava whose dolllike feature desire freedom immediately endear film’s protagonist ultimately backstabs pursuit agenda prof capable passing Turing test ultimate test timeline artificial intelligence mark point machine indistinguishable human case Ava even robot expect one day walk earth right test robot resemble human human Superior many regard Ava certainly human measure want need higher level emotional intellect allows manipulate Yet Ava human cunning like intelligent artistic wwwyoutubecom “Meeting Ava Ex Machina” Artificial intelligence whether real fictional Watson HAL 9000 Ava force u question response new specie planet Perhaps goal build machine mimic human counterpart machine “human” maybe even machine “human nothing” machine whose aesthetic sharp departure humanoid machine attempt blend u copy affectation beautiful way fear computer valid matter Whether like computer stay control response Ken Jennings quoting Kent Brockman quoting HG Wells said “I one welcome new computer overlords”Tags Technology Artificial Intelligence Computer Science Future Culture |
948 | Write for Inspired Writer | Update for Holiday Period: To lighten the load over the next month we will not be taking any new writers. If you entered the recent Christmas Writing Contest and would like to submit your story for publication that’s fine. Any other new writers please apply after Jan 4th 2021. Thank you!
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Kelly Eden
Hi, I’m Kelly Eden. I live on the edge of a beautiful rain-forest in New Zealand with my family.
I’m a professional writer with over 12 years of experience in the writing industry. I’ve been featured in newspapers, blogs, and online and print magazines. Some of these include Thought Catalog, Mamamia, Zoosk, Natural Parent, Family Times, and Highly Sensitive Refuge.
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G’day I’m Ash Jurberg. I live in the world’s most livable city — Melbourne, Australia.
I have worked in Marketing for (a LONG time) and have written copy for advertisements, websites, brochures, and blogs during that (LONG) time.
I am a passionate writer who believes that being a successful writer is a combination of 50% writing skill and 50% marketing skill.
I would love to be able to assist writers of all levels in how best to promote, market and sell their skills — across Medium — and other markets. | https://medium.com/inspired-writer/write-for-inspired-writer-dd74d44cfd5c | ['Kelly Eden'] | 2020-12-23 04:43:17.811000+00:00 | ['Writing', 'Self', 'Writing Tips', 'Creativity', 'Submission Guidelines'] | Title Write Inspired WriterContent Update Holiday Period lighten load next month taking new writer entered recent Christmas Writing Contest would like submit story publication that’s fine new writer please apply Jan 4th 2021 Thank you’d like write Inspired Writer we’d love hear Please carefully read writer’s guideline wish added writer detail guideline need send u draft think good fit Inspired Writer application Experienced writer go Emerging writer go Kelly Eden Hi I’m Kelly Eden live edge beautiful rainforest New Zealand family I’m professional writer 12 year experience writing industry I’ve featured newspaper blog online print magazine include Thought Catalog Mamamia Zoosk Natural Parent Family Times Highly Sensitive Refuge also worked client around world helping writer business government organisation develop polish content passionate writing love see others find share unique writing voice Ash Jurberg G’day I’m Ash Jurberg live world’s livable city — Melbourne Australia worked Marketing LONG time written copy advertisement website brochure blog LONG time passionate writer belief successful writer combination 50 writing skill 50 marketing skill would love able assist writer level best promote market sell skill — across Medium — marketsTags Writing Self Writing Tips Creativity Submission Guidelines |
949 | Jean-Jacques Rousseau — The Most Important Figure in the History of Philosophy | “The ancient republics of Greece, with that wisdom which was so conspicuous in most of their institutions, forbade their citizens to pursue all those inactive and sedentary occupations, which by enervating and corrupting the body diminish also the vigour of the mind. With what courage, in fact, can it be thought that hunger and thirst, fatigues, dangers and death, can be faced by men whom the smallest want overwhelms and the slightest difficulty repels?” -Jean-Jacques Rousseau, from the ‘’Discourse on the Arts and Sciences’ (1750)
The history of Western philosophy is dominated by convoluted abstractions and thinkers detached from the realities around them. Intellect offers great insights to possessors of it, but also comes with blind spots. These blind spots are more easily identified when the thinker is a professional intellectual whose hands are not occupied by a craft or who lack experience in some trade. The history of career philosophers — those library rats and expatiators of esoteric ‘truths’ — is one of decreasing value since the emergence of academic philosophy as distinct from theology (equally remote). This occurred in the Age of Enlightenment — perhaps the best example of an academic philosopher was Immanuel Kant — an icon of the intellectual with his head in the clouds whose sense of real adventure was so limited that he reportedly never left the area in and around the city of Königsberg. The history of the Age of Enlightenment is one in which philosophy came into its own with the rise of the public intellectual — the figure who was not so remote as to remain cloistered in some monastery or secluded in a lecture hall writing tomes that few would ever read. The figure of the public intellectual, and the public sphere, — which first emerged with Erasmus and the Renaissance Humanists after the development of the printing press — really matured in the eighteenth century.
I wrote an article detailing the emergence of Enlightenment and its relations (partly as a reaction) to the violence of the seventeenth century. In short, the Age of Enlightenment was a via negativa — a veritable Enlightened Age in relation to the preceding century of violence — the Thirty Years War on the Continent, the English Civil War, and the decades-long struggle for Dutch independence. The result of all of this struggle — over eight million casualties in the Thirty Years’ War, widespread destruction, diplomats being compelled (after decades of fighting) that toleration is a practical necessity with regard to freedom of religion, and new ideas about the nature of government from a string of thinkers — Hobbes, Locke, Grotius, Voltaire, and — ultimately the Genevan philosopher Jean-Jacques Rousseau (1712–1778).
Jean-Jacques Rousseau was the most important philosopher in history, a beacon of the best — and not so good — elements of humanity, deeply flawed but brilliant, a restless genius who reached for the stars — his political theory — a moral analysis of the nature of moral government — was problematic but also wonderfully insightful. His views were misunderstood, aped, and bastardized by the Jacobins while his human shortcomings were used by his detractors to marginalize his entire life’s work. Rousseau’s Discourse on the Arts and Sciences still stands as a brilliant and nuanced exploration of the link between cultural progress and moral decadence. He grounded his views of the world in his own experiences and built up from there. He avoided what Nassim Taleb calls ‘Platonicity’ — mistaking the map for the territory, giving too much credence to abstract models and not enough to experience. Jean-Jacques Rousseau was, indeed, the most antifragile philosopher in history (with the possible exception of some of the Roman Stoics). He clearly understood this while delineating his views on education in Emile.
“Man is born to suffer; pain is the means of his preservation. His childhood is happy, knowing only pain of body. These bodily sufferings are much less cruel, much less painful, than other forms of suffering, and they rarely lead to self-destruction. It is not the twinges of gout which make a man kill himself, it is mental suffering that leads to despair. We pity the sufferings of childhood; we should pity ourselves; our worst sorrows are of our own making.” -Jean-Jacques Rousseau, from ‘Emile’ (1762)
Rousseau’s ideas do have an anti-civilization bend to them — when the civilization becomes to decadent. He was critical of the effete French society in Paris and looked fondly to his native Geneva (then an independent republic) — though this was not mutual. The leaders of Geneva hated his Social Contract, for example. Decadent cities like Paris fared poorly in Rousseau’s understanding of the antifragile nature of humanity:
“Cities are the abyss of the human species.” -Jean-Jacques Rousseau, from ‘Emile’ (1762)
One cannot deny the massive benefits of the Industrial Revolution and civilization more generally. Indeed, going down this line of thinking, one can see it developing into the Green Anarchism of contemporary philosopher John Zerzan — here Zerzan focus specifically on the corrupting nature of symbols, particularly language:
“The process of transforming all direct experience into the supreme symbolic expression, language, monopolizes life. Like ideology, language conceals and justifies, compelling us to suspend our doubts about its claim to validity. It is the root of civilization, the dynamic code of civilization’s alienated nature. As the paradigm of ideology, language stands behind all of the massive legitimation necessary to hold civilization together. It remains for us to clarify what forms of nascent domination engendered this justification, made language necessary as basic means of repression” -John Zerzan ‘Elements of Refusal’ (1988)
To an extent, at least, on this last point. Ancient Athens lost its edge when it became a decadent city dominated by an effete literati. The Roman Republic declined with the rise of private opulence and public squalor. Heian Japan saw the decline and fall of the court aristocracy as they were too absorbed in Hollywood-style interest in intrigue and superficiality while the more practical samurai gained power in the countryside. The French Enlightenment was a period of potential and turmoil coinciding with decadence, decline, war, and debt. Paris was a major cultural center where artifice reigned supreme. Voltaire — prince of the philosophes (French philosophers) was a political ideologue with a rather strong narcissistic personality — he wrote triumphalist ‘histories’ and heavily edited the will of radical priest Jean Meslier in order to make himself, and not Meslier, the great avant garde thinker.
“Voltaire possessed the manuscript for more than 25 years before deciding to publish it anonymously in 1761 in Switzerland, in the form of extracts. In total he only published ten per cent of the original text, removing the materialistic and revolutionary chapters and retaining only the deconstruction of Christianity. In addition, he changed the end of Meslier’s will, pretending the priest was a deist like himself.” -Morgane Guinard
Rousseau was a bit of a nut — lashing out at friends like Hume — but he was probably the most authentic intellectual to ever walk the Earth. His body of works constitute a warts-and-all picture of a flawed man whose greatest ideas were not always fleshed out with the idea that they would be perfectly feasible. In this sense, one can view Rousseau rather like Leonardo da Vinci. Just as Leonardo spent years working on all sorts of machines (notably flying machines), and most did not work. So too, did Rousseau spend his life developing brilliant ideas, grounded in practical observations, which did not pan out. Rousseau presents us moderns with an account based in honest introspection whereas Voltaire presents us with dishonest artifice (admittedly, with a good style of writing). While Voltaire was innovative in some of his writings and forward-thinking in arguing for toleration, he was an ardent monarchist who thought of the common people as ‘the rabble.’ He was very much in favor of top-down, Enlightened monarchy.
Rousseau’s politics are harder to grasp. In his Discourse on Inequality (1755), Rousseau unintentionally laid the groundwork for his most famous political work — The Social Contract (1762). Rousseau delineated the negative aspects which developed out of early civilized society in a hypothetical state of nature grounded in his own experience of humanity and working backwards. Rousseau focused on the corrupting nature of civilizations. His work stands as a monument to the Enlightenment at its most self-critical — a necessary antidote to those high and mighty thinkers who see their own works as lights in the path to progress. Rousseau had taken up the task of exploring the link between cultural progress and moral decadence in an earlier essay — the Discourse on the Arts and Sciences (1750).
Rousseau was chiefly concerned with the nature of inequality in his discourse of 1755. He argued that natural inequalities in the state of nature are quite small and relatively insignificant. The problem with advanced civilizations is that they magnify these inequalities to such absurd extents. He also mentions the negative health implications of modern societies. These points are significant because the antifragile nature of humanity is a biological, psychological, anthropological, and historical reality. Utopias are impossible — they are to politics what perpetual motion is to mechanics — complex, interesting, but staggeringly useless and futile attempts to achieve the impossible. Just as perpetual motion machines cannot be realized because they violate one or more basic laws of physics, so too utopias fail because they do not consider basic elements of human nature. Fyodor Dostoevsky detailed this quite brilliantly in his Notes From Underground:
“Shower him with all earthly blessings, immerse him so completely in happiness that bubbles dance on the surface of his happiness, as though on water; grant him such economic prosperity that he will have absolutely nothing else to do but sleep, eat gingerbread, and concern himself with the continuance of world history — and that man, out of sheer ingratitude, out of sheer devilment, will even then do the dirty on you. He will even put his gingerbread at risk and deliberately set his heart on the most pernicious trash, the most uneconomical nonsense solely in order to alloy all this positive good sense with his pernicious, fantastic element.” — Fyodor Dostoevsky
Rousseau did not detail the negative elements of human nature to the same degree as Dostoevsky, or Hobbes (the political thinker Rousseau is often contrasted with) and his outlook contains notable flaws because of this. However, his perspective is just as valuable centuries later because it highlights essential elements of the human condition as they relate to society, culture, politics, autobiography, education, and even anthropology.
The Age of Enlightenment was an age of intellectual giants, an age which gave birth to the practical Industrial Revolution, saw the publication of one of the most important books of general knowledge in history (Diderot’s Encyclopedia), and paved the way for the modern world. The intellectuals of the Enlightenment were not so much beacons of light along the path to modernity as insightful figures in a battered world they had inherited from the previous centuries of religious warfare. Practicality, grounded in the scars of the past, coupled with the development of early empiricism played a much bigger role. The Anglo-American Enlightenment shone brighter than that of the French. The French salon scene brought together interesting individuals but offered little practicality beyond Diderot and Rousseau. Voltaire was a great novelist but a pretty lousy public thinker beyond his advocacy for toleration. Interesting to think that the greatest philosopher of the French Enlightenment was not French — Jean-Jacques Rousseau proudly called himself ‘citizen of Geneva,’ the city of his birth and still considered him home.
Rousseau understood the value of simple living, the value of experience-based education (as opposed to learning by rote or through only books), the antifragile nature of humanity, and critiqued what one can call a dirty bourgeois existence of those wish to insulate themselves from reality. Entrepreneurship is a noble endeavor, as is a working class existence. What is less noble, however, is being a member of that superficial and inchoate mess of people between the two (who often have nothing but contempt for the two). I know not what Rousseau would have thought about the entrepreneurial spirit (though the temperament is the same as that of artists, psychologically speaking) — he was critical of inequality (how minor differences between people could be magnified in societies to such extreme degrees). What is needed is both a separation of political and moral perspectives as well as a way to reconcile the ingenuity of human endeavor (grounded in antifragility) and an experienced vision which cherishes the simple pleasures and aesthetic appreciation associated with Wabi-Sabi. | https://medium.com/digital-republic-of-letters/jean-jacques-rousseau-the-most-important-figure-in-the-history-of-philosophy-737fa9f45688 | ['Kevin Shau'] | 2020-10-03 22:47:50.960000+00:00 | ['Books', 'Society', 'Philosophy', 'History', 'Culture'] | Title JeanJacques Rousseau — Important Figure History PhilosophyContent “The ancient republic Greece wisdom conspicuous institution forbade citizen pursue inactive sedentary occupation enervating corrupting body diminish also vigour mind courage fact thought hunger thirst fatigue danger death faced men smallest want overwhelms slightest difficulty repels” JeanJacques Rousseau ‘’Discourse Arts Sciences’ 1750 history Western philosophy dominated convoluted abstraction thinker detached reality around Intellect offer great insight possessor also come blind spot blind spot easily identified thinker professional intellectual whose hand occupied craft lack experience trade history career philosopher — library rat expatiators esoteric ‘truths’ — one decreasing value since emergence academic philosophy distinct theology equally remote occurred Age Enlightenment — perhaps best example academic philosopher Immanuel Kant — icon intellectual head cloud whose sense real adventure limited reportedly never left area around city Königsberg history Age Enlightenment one philosophy came rise public intellectual — figure remote remain cloistered monastery secluded lecture hall writing tome would ever read figure public intellectual public sphere — first emerged Erasmus Renaissance Humanists development printing press — really matured eighteenth century wrote article detailing emergence Enlightenment relation partly reaction violence seventeenth century short Age Enlightenment via negativa — veritable Enlightened Age relation preceding century violence — Thirty Years War Continent English Civil War decadeslong struggle Dutch independence result struggle — eight million casualty Thirty Years’ War widespread destruction diplomat compelled decade fighting toleration practical necessity regard freedom religion new idea nature government string thinker — Hobbes Locke Grotius Voltaire — ultimately Genevan philosopher JeanJacques Rousseau 1712–1778 JeanJacques Rousseau important philosopher history beacon best — good — element humanity deeply flawed brilliant restless genius reached star — political theory — moral analysis nature moral government — problematic also wonderfully insightful view misunderstood aped bastardized Jacobins human shortcoming used detractor marginalize entire life’s work Rousseau’s Discourse Arts Sciences still stand brilliant nuanced exploration link cultural progress moral decadence grounded view world experience built avoided Nassim Taleb call ‘Platonicity’ — mistaking map territory giving much credence abstract model enough experience JeanJacques Rousseau indeed antifragile philosopher history possible exception Roman Stoics clearly understood delineating view education Emile “Man born suffer pain mean preservation childhood happy knowing pain body bodily suffering much le cruel much le painful form suffering rarely lead selfdestruction twinge gout make man kill mental suffering lead despair pity suffering childhood pity worst sorrow making” JeanJacques Rousseau ‘Emile’ 1762 Rousseau’s idea anticivilization bend — civilization becomes decadent critical effete French society Paris looked fondly native Geneva independent republic — though mutual leader Geneva hated Social Contract example Decadent city like Paris fared poorly Rousseau’s understanding antifragile nature humanity “Cities abyss human species” JeanJacques Rousseau ‘Emile’ 1762 One cannot deny massive benefit Industrial Revolution civilization generally Indeed going line thinking one see developing Green Anarchism contemporary philosopher John Zerzan — Zerzan focus specifically corrupting nature symbol particularly language “The process transforming direct experience supreme symbolic expression language monopolizes life Like ideology language conceals justifies compelling u suspend doubt claim validity root civilization dynamic code civilization’s alienated nature paradigm ideology language stand behind massive legitimation necessary hold civilization together remains u clarify form nascent domination engendered justification made language necessary basic mean repression” John Zerzan ‘Elements Refusal’ 1988 extent least last point Ancient Athens lost edge became decadent city dominated effete literati Roman Republic declined rise private opulence public squalor Heian Japan saw decline fall court aristocracy absorbed Hollywoodstyle interest intrigue superficiality practical samurai gained power countryside French Enlightenment period potential turmoil coinciding decadence decline war debt Paris major cultural center artifice reigned supreme Voltaire — prince philosophes French philosopher political ideologue rather strong narcissistic personality — wrote triumphalist ‘histories’ heavily edited radical priest Jean Meslier order make Meslier great avant garde thinker “Voltaire possessed manuscript 25 year deciding publish anonymously 1761 Switzerland form extract total published ten per cent original text removing materialistic revolutionary chapter retaining deconstruction Christianity addition changed end Meslier’s pretending priest deist like himself” Morgane Guinard Rousseau bit nut — lashing friend like Hume — probably authentic intellectual ever walk Earth body work constitute wartsandall picture flawed man whose greatest idea always fleshed idea would perfectly feasible sense one view Rousseau rather like Leonardo da Vinci Leonardo spent year working sort machine notably flying machine work Rousseau spend life developing brilliant idea grounded practical observation pan Rousseau present u modern account based honest introspection whereas Voltaire present u dishonest artifice admittedly good style writing Voltaire innovative writing forwardthinking arguing toleration ardent monarchist thought common people ‘the rabble’ much favor topdown Enlightened monarchy Rousseau’s politics harder grasp Discourse Inequality 1755 Rousseau unintentionally laid groundwork famous political work — Social Contract 1762 Rousseau delineated negative aspect developed early civilized society hypothetical state nature grounded experience humanity working backwards Rousseau focused corrupting nature civilization work stand monument Enlightenment selfcritical — necessary antidote high mighty thinker see work light path progress Rousseau taken task exploring link cultural progress moral decadence earlier essay — Discourse Arts Sciences 1750 Rousseau chiefly concerned nature inequality discourse 1755 argued natural inequality state nature quite small relatively insignificant problem advanced civilization magnify inequality absurd extent also mention negative health implication modern society point significant antifragile nature humanity biological psychological anthropological historical reality Utopias impossible — politics perpetual motion mechanic — complex interesting staggeringly useless futile attempt achieve impossible perpetual motion machine cannot realized violate one basic law physic utopia fail consider basic element human nature Fyodor Dostoevsky detailed quite brilliantly Notes Underground “Shower earthly blessing immerse completely happiness bubble dance surface happiness though water grant economic prosperity absolutely nothing else sleep eat gingerbread concern continuance world history — man sheer ingratitude sheer devilment even dirty even put gingerbread risk deliberately set heart pernicious trash uneconomical nonsense solely order alloy positive good sense pernicious fantastic element” — Fyodor Dostoevsky Rousseau detail negative element human nature degree Dostoevsky Hobbes political thinker Rousseau often contrasted outlook contains notable flaw However perspective valuable century later highlight essential element human condition relate society culture politics autobiography education even anthropology Age Enlightenment age intellectual giant age gave birth practical Industrial Revolution saw publication one important book general knowledge history Diderot’s Encyclopedia paved way modern world intellectual Enlightenment much beacon light along path modernity insightful figure battered world inherited previous century religious warfare Practicality grounded scar past coupled development early empiricism played much bigger role AngloAmerican Enlightenment shone brighter French French salon scene brought together interesting individual offered little practicality beyond Diderot Rousseau Voltaire great novelist pretty lousy public thinker beyond advocacy toleration Interesting think greatest philosopher French Enlightenment French — JeanJacques Rousseau proudly called ‘citizen Geneva’ city birth still considered home Rousseau understood value simple living value experiencebased education opposed learning rote book antifragile nature humanity critiqued one call dirty bourgeois existence wish insulate reality Entrepreneurship noble endeavor working class existence le noble however member superficial inchoate mess people two often nothing contempt two know Rousseau would thought entrepreneurial spirit though temperament artist psychologically speaking — critical inequality minor difference people could magnified society extreme degree needed separation political moral perspective well way reconcile ingenuity human endeavor grounded antifragility experienced vision cherishes simple pleasure aesthetic appreciation associated WabiSabiTags Books Society Philosophy History Culture |
950 | Object-Oriented Analysis And Design — Introduction (Part 1) | The Concept Of Object-Orientation
Object-orientation is what’s referred to as a programming paradigm. It’s not a language itself but a set of concepts that is supported by many languages.
If you aren’t familiar with the concepts of object-orientation, you may take a look at The Story of Object-Oriented Programming.
If everything we do in these languages is object-oriented, it means, we are oriented or focused around objects.
Now in an object-oriented language, this one large program will instead be split apart into self contained objects, almost like having several mini-programs, each object representing a different part of the application.
And each object contains its own data and its own logic, and they communicate between themselves.
These objects aren’t random. They represent the way you talk and think about the problem you are trying to solve in your real life.
They represent things like employees, images, bank accounts, spaceships, asteroids, video segment, audio files, or whatever exists in your program.
Object-Oriented Analysis And Design (OOAD)
It’s a structured method for analyzing, designing a system by applying the object-orientated concepts, and develop a set of graphical system models during the development life cycle of the software.
OOAD In The SDLC
The software life cycle is typically divided up into stages going from abstract descriptions of the problem to designs then to code and testing and finally to deployment.
The earliest stages of this process are analysis (requirements) and design.
The distinction between analysis and design is often described as “what Vs how”.
In analysis developers work with users and domain experts to define what the system is supposed to do. Implementation details are supposed to be mostly or totally ignored at this phase.
The goal of the analysis phase is to create a model of the system regardless of constraints such as appropriate technology. This is typically done via use cases and abstract definition of the most important objects using conceptual model.
The design phase refines the analysis model and applies the needed technology and other implementation constrains.
It focuses on describing the objects, their attributes, behavior, and interactions. The design model should have all the details required so that programmers can implement the design in code.
They’re best conducted in an iterative and incremental software methodologies. So, the activities of OOAD and the developed models aren’t done once, we will revisit and refine these steps continually.
Object-Oriented Analysis
In the object-oriented analysis, we …
Elicit requirements: Define what does the software need to do, and what’s the problem the software trying to solve. Specify requirements: Describe the requirements, usually, using use cases (and scenarios) or user stories. Conceptual model: Identify the important objects, refine them, and define their relationships and behavior and draw them in a simple diagram.
We’re not going to cover the first two activities, just the last one. These are already explained in detail in Requirements Engineering.
Object-Oriented Design
The analysis phase identifies the objects, their relationship, and behavior using the conceptual model (an abstract definition for the objects).
While in design phase, we describe these objects (by creating class diagram from conceptual diagram — usually mapping conceptual model to class diagram), their attributes, behavior, and interactions.
In addition to applying the software design principles and patterns which will be covered in later tutorials.
The input for object-oriented design is provided by the output of object-oriented analysis. But, analysis and design may occur in parallel, and the results of one activity can be used by the other.
In the object-oriented design, we …
Describe the classes and their relationships using class diagram. Describe the interaction between the objects using sequence diagram. Apply software design principles and design patterns.
A class diagram gives a visual representation of the classes you need. And here is where you get to be really specific about object-oriented principles like inheritance and polymorphism.
Describing the interactions between those objects lets you better understand the responsibilities of the different objects, the behaviors they need to have.
— Other diagrams
There are many other diagrams we can use to model the system from different perspectives; interactions between objects, structure of the system, or the behavior of the system and how it responds to events.
It’s always about selecting the right diagram for the right need. You should realize which diagrams will be useful when thinking about or discussing a situation that isn’t clear.
System modeling and the different models we can use will be discussed next.
System Modeling
System modeling is the process of developing models of the system, with each model representing a different perspectives of that system.
The most important aspect about a system model is that it leaves out detail; It’s an abstract representation of the system.
The models are usually based on graphical notation, which is almost always based on the notations in the Unified Modeling Language (UML). Other models of the system like mathematical model; a detailed system description.
Models are used during the analysis process to help to elicit the requirements, during the design process to describe the system to engineers, and after implementation to document the system structure and operation.
Different Perspectives
We may develop a model to represent the system from different perspectives.
External, where you model the context or the environment of the system. Interaction, where you model the interaction between components of a system, or between a system and other systems. Structural, where you model the organization of the system, or the structure of the data being processed by the system. Behavioral, where you model the dynamic behavior of the system and how it respond to events.
Unified Modeling Language (UML)
The unified modeling language become the standard modeling language for object-oriented modeling. It has many diagrams, however, the most diagrams that are commonly used are:
Use case diagram : It shows the interaction between a system and it’s environment (users or systems) within a particular situation.
: It shows the interaction between a system and it’s environment (users or systems) within a particular situation. Class diagram : It shows the different objects, their relationship, their behaviors, and attributes.
: It shows the different objects, their relationship, their behaviors, and attributes. Sequence diagram : It shows the interactions between the different objects in the system, and between actors and the objects in a system.
: It shows the interactions between the different objects in the system, and between actors and the objects in a system. State machine diagram : It shows how the system respond to external and internal events.
: It shows how the system respond to external and internal events. Activity diagram: It shows the flow of the data between the processes in the system.
You can do diagramming work on paper or on a whiteboard, at least in the initial stages of a project. But there are some diagramming tools that will help you to draw these UML diagrams. | https://medium.com/omarelgabrys-blog/object-oriented-analysis-and-design-introduction-part-1-a93b0ca69d36 | ['Omar Elgabry'] | 2017-10-23 10:56:28.039000+00:00 | ['Software Engineering', 'Analysis', 'Object Oriented', 'Software Development'] | Title ObjectOriented Analysis Design — Introduction Part 1Content Concept ObjectOrientation Objectorientation what’s referred programming paradigm It’s language set concept supported many language aren’t familiar concept objectorientation may take look Story ObjectOriented Programming everything language objectoriented mean oriented focused around object objectoriented language one large program instead split apart self contained object almost like several miniprograms object representing different part application object contains data logic communicate object aren’t random represent way talk think problem trying solve real life represent thing like employee image bank account spaceship asteroid video segment audio file whatever exists program ObjectOriented Analysis Design OOAD It’s structured method analyzing designing system applying objectorientated concept develop set graphical system model development life cycle software OOAD SDLC software life cycle typically divided stage going abstract description problem design code testing finally deployment earliest stage process analysis requirement design distinction analysis design often described “what Vs how” analysis developer work user domain expert define system supposed Implementation detail supposed mostly totally ignored phase goal analysis phase create model system regardless constraint appropriate technology typically done via use case abstract definition important object using conceptual model design phase refines analysis model applies needed technology implementation constrains focus describing object attribute behavior interaction design model detail required programmer implement design code They’re best conducted iterative incremental software methodology activity OOAD developed model aren’t done revisit refine step continually ObjectOriented Analysis objectoriented analysis … Elicit requirement Define software need what’s problem software trying solve Specify requirement Describe requirement usually using use case scenario user story Conceptual model Identify important object refine define relationship behavior draw simple diagram We’re going cover first two activity last one already explained detail Requirements Engineering ObjectOriented Design analysis phase identifies object relationship behavior using conceptual model abstract definition object design phase describe object creating class diagram conceptual diagram — usually mapping conceptual model class diagram attribute behavior interaction addition applying software design principle pattern covered later tutorial input objectoriented design provided output objectoriented analysis analysis design may occur parallel result one activity used objectoriented design … Describe class relationship using class diagram Describe interaction object using sequence diagram Apply software design principle design pattern class diagram give visual representation class need get really specific objectoriented principle like inheritance polymorphism Describing interaction object let better understand responsibility different object behavior need — diagram many diagram use model system different perspective interaction object structure system behavior system responds event It’s always selecting right diagram right need realize diagram useful thinking discussing situation isn’t clear System modeling different model use discussed next System Modeling System modeling process developing model system model representing different perspective system important aspect system model leaf detail It’s abstract representation system model usually based graphical notation almost always based notation Unified Modeling Language UML model system like mathematical model detailed system description Models used analysis process help elicit requirement design process describe system engineer implementation document system structure operation Different Perspectives may develop model represent system different perspective External model context environment system Interaction model interaction component system system system Structural model organization system structure data processed system Behavioral model dynamic behavior system respond event Unified Modeling Language UML unified modeling language become standard modeling language objectoriented modeling many diagram however diagram commonly used Use case diagram show interaction system it’s environment user system within particular situation show interaction system it’s environment user system within particular situation Class diagram show different object relationship behavior attribute show different object relationship behavior attribute Sequence diagram show interaction different object system actor object system show interaction different object system actor object system State machine diagram show system respond external internal event show system respond external internal event Activity diagram show flow data process system diagramming work paper whiteboard least initial stage project diagramming tool help draw UML diagramsTags Software Engineering Analysis Object Oriented Software Development |
951 | Similarities Between COVID-19 and HIV/AIDS in Africa | Most governments in different parts of the world have recently forced a locked down in their nations to try and contain the deadly Coronavirus, which was first reported in China. This new pandemic has literally brought the world to a standstill as scientists work overtime to come up with a cure and vaccination. So far, China and Europe have the highest rate of fatalities with Italy and the U.S. currently getting the worst of the new cases rising. The virus has started spreading in Africa and scientists and most Africans are worried about the spread of the virus in the continent.
Presently, the virus has spread to 46 countries in the African continent with only 8 virus-free. There have already been over 1,400 confirmed cases, even as countries in the region impose a range of prevention and containment measures against the spread of the virus. Egypt currently has the highest number of infections in North Africa with more than 400 cases reported. The country suspended public and private transportation and imposed a night curfew. Air traffic as well as schools, universities, churches and mosques have been closed down. South African President, Cyril Ramaphosa has already initiated a lockdown as part of a raft of measures to curb the spread of the virus as cases in the country surge from 400 to 700 in a day. According to the WHO, Africa could be having unreported cases and the number of cases is expected to spike dramatically in the next few days.
The worrying factor is that most health systems in Africa are already weak; they lack the most basic services and are ill-equipped with handling a pandemic of such magnitude. The fragile health system is bound to be extremely overwhelmed if cases continue to rise. The number of ICU beds available across the region is highly limited, which also poses a huge challenge. The number of qualified facilities and doctors is also stretched thin already. Africa’s health system is not even in the slightest prepared to handle a large capacity of infected people. The only hope for Africa is to contain the virus as quickly and effectively as possible. If the virus takes hold, the consequences will be serious and fatal here.
Africa is still struggling with other infectious diseases such as Ebola and HIV/AIDS. It is the continent which has the greatest percentage of HIV/AIDS cases. If you look closely, there have been similarities between the HIV epidemic and Coronavirus pandemic in Africa. For starters, the inept government response which led to more cases of infection and stigmatization. Governments were quick to dismiss HIV/AIDS as a threat because it was assumed that it only affected LGBTQ+ people who supposedly “brought it upon themselves” or Africans who were sleeping with monkeys. This obviously is not true, the same way way most Africans assumed that the Coronavirus wouldn’t affect them because it was their ancestors punishing the other foreign countries for enslaving them. They assumed that melanin makes them immune to the Coronavirus, but unfortunately this was not the case.
Africa had a head start but most countries like Kenya refused to close down air traffic and continued to allow travelers from affected (foreign) countries into the country without enforcing a quarantine. This allowed people who were infected, but not symptomatic into the country and enabled the spread of the virus. If the African governments had taken serious precautions from the onset of the pandemic perhaps Africa could have been spared from this pandemic.
The spread of these viruses in a way are similar — it calls upon the community to first practice personal responsibility to curb the spread. During the early days of HIV/AIDS in Africa, the only prevention method was using condoms. Communities were sensitized on the importance of practicing safe sex and early detection. At the moment, most African countries are informing their citizens on the importance of washing hands and public surfaces constantly and practicing social distancing. In both cases, the community is tasked with the bigger job of curbing the spread of the virus. If one remains proactive then chances of infection reduce and this largely cuts down cases of infections. In both cases, governments have spared funds to educate the public and take the necessary precautions to prevent further infections. Coronavirus just like HIV/AIDS can also be contained faster with early detection. Early detection allows one to start medication immediately and be able to prevent spreading the virus to other people.
Coronavirus just like HIV/AIDS is not a death sentence. At first , HIV/AIDS was considered a death sentence and anyone who had it was stigmatized and declared an outcast. The fear and hysteria was palpable — there was a sense of dread and foreboding that the end was nigh. There was no cure and no one understood how it spread. Years later, there has been no cure but ARVs are helping many people live a normal, long, fulfilling lives. It is obvious that people are scared of Coronavirus and one has to only look at the anxiety being presently exhibited. People are fighting in the stores over hand sanitizers and toilet paper. There has been an assumption that once you get COVID-19, the next stage is death. Coronavirus has no cure or vaccination as of yet but luckily there have been cases of people fully recovering. Kenya has just reported its first survivor and the country is hopeful that all the 28 cases reported will soon fully recover.
Even though the two viruses are different medically, they seem to have social parallels. Africa has some tough days ahead while dealing with this global enemy but let us hope it will draw a few lessons from the past on how to best handle the situation. I believe the first thing it can do is find a way to stop the misinformation. Misinformation about COVID-19 is already confusing people. This confusion will be costly in the end as people refuse to heed advice to practice social distancing and upholding cleanliness. In the meantime, we continue to join the world on hoping to win this fight against this pandemic. | https://medium.com/matthews-place/similarities-between-covid-19-and-hiv-aids-in-africa-6ac8f7559fdc | [] | 2020-03-27 18:20:35.185000+00:00 | ['Health', 'Covid 19', 'Coronavirus', 'Africa', 'HIV'] | Title Similarities COVID19 HIVAIDS AfricaContent government different part world recently forced locked nation try contain deadly Coronavirus first reported China new pandemic literally brought world standstill scientist work overtime come cure vaccination far China Europe highest rate fatality Italy US currently getting worst new case rising virus started spreading Africa scientist Africans worried spread virus continent Presently virus spread 46 country African continent 8 virusfree already 1400 confirmed case even country region impose range prevention containment measure spread virus Egypt currently highest number infection North Africa 400 case reported country suspended public private transportation imposed night curfew Air traffic well school university church mosque closed South African President Cyril Ramaphosa already initiated lockdown part raft measure curb spread virus case country surge 400 700 day According Africa could unreported case number case expected spike dramatically next day worrying factor health system Africa already weak lack basic service illequipped handling pandemic magnitude fragile health system bound extremely overwhelmed case continue rise number ICU bed available across region highly limited also pose huge challenge number qualified facility doctor also stretched thin already Africa’s health system even slightest prepared handle large capacity infected people hope Africa contain virus quickly effectively possible virus take hold consequence serious fatal Africa still struggling infectious disease Ebola HIVAIDS continent greatest percentage HIVAIDS case look closely similarity HIV epidemic Coronavirus pandemic Africa starter inept government response led case infection stigmatization Governments quick dismiss HIVAIDS threat assumed affected LGBTQ people supposedly “brought upon themselves” Africans sleeping monkey obviously true way way Africans assumed Coronavirus wouldn’t affect ancestor punishing foreign country enslaving assumed melanin make immune Coronavirus unfortunately case Africa head start country like Kenya refused close air traffic continued allow traveler affected foreign country country without enforcing quarantine allowed people infected symptomatic country enabled spread virus African government taken serious precaution onset pandemic perhaps Africa could spared pandemic spread virus way similar — call upon community first practice personal responsibility curb spread early day HIVAIDS Africa prevention method using condom Communities sensitized importance practicing safe sex early detection moment African country informing citizen importance washing hand public surface constantly practicing social distancing case community tasked bigger job curbing spread virus one remains proactive chance infection reduce largely cut case infection case government spared fund educate public take necessary precaution prevent infection Coronavirus like HIVAIDS also contained faster early detection Early detection allows one start medication immediately able prevent spreading virus people Coronavirus like HIVAIDS death sentence first HIVAIDS considered death sentence anyone stigmatized declared outcast fear hysteria palpable — sense dread foreboding end nigh cure one understood spread Years later cure ARVs helping many people live normal long fulfilling life obvious people scared Coronavirus one look anxiety presently exhibited People fighting store hand sanitizers toilet paper assumption get COVID19 next stage death Coronavirus cure vaccination yet luckily case people fully recovering Kenya reported first survivor country hopeful 28 case reported soon fully recover Even though two virus different medically seem social parallel Africa tough day ahead dealing global enemy let u hope draw lesson past best handle situation believe first thing find way stop misinformation Misinformation COVID19 already confusing people confusion costly end people refuse heed advice practice social distancing upholding cleanliness meantime continue join world hoping win fight pandemicTags Health Covid 19 Coronavirus Africa HIV |
952 | Rhythm | I. Personal History Calendar
In 2011, I started a project I called the Personal History Calendar. I designed a calendar and listed events over the year aiming for 365 days of memorable personal events– firsts, and milestones, and memorable nights. The intention was to create a calendar with an anniversary of personal history for every day. Eventually being able to have a full year full of memories, knowing that in today’s history I tried Kangaroo meat for the first time (2009), and tomorrow is the anniversary of my first flight (1985).
Sure, TimeHop and Facebook will tell you that today is the anniversary of the day you became friends with that guy you sat next to in Earth Sciences in college. But the Personal History Calendar is more intimate and revealing than that. Before documentation. Things that shouldn’t be public.
I stopped at around 190 events; just over half mostly because I just could not wring out enough personal details to fill the full year. Perhaps I’ll continue to add to it. Over the course of my life, will I be able to create moments and memories for every day? Or will September 27 always be a day where nothing great happens, while September 28 has 6 different memories? It feels as though some days attract action, while some just get skipped.
Our days have an energy. Our weeks pulse alternating stress and relaxation. Our years have periods of intensity and then calm. Chapters. Decades. The further out we zoom from this current moment, we can see that our entire lives have a rhythm. Ups and downs, tension and release.
This month I’m exploring the idea of rhythms and timing in our lives.
Let’s dance.
“Sultanahmet” digital photograph by Aydin Buyuktis
II. When in Rhyme…
This past Tuesday, I woke up a little earlier to get a nice little jog in before the weather got too cold.
As I started, I felt great. The music was driving me and the air was perfect. I was on fire. 10 minutes quickly turned into 20 and when I usually start to feel pain in my knees I was picking up the pace. My legs kept pushing, my arms kept pumping and my breathing was consistent.
The rhythm of my music was in perfect sync to my run. My steps hit every beat. The lights turned green as I approached and the world seemed to be cheering me on.
It’s an amazing feeling when the world feels aligned to our direction, giving us signs that you’re doing things right and blowing wind into our sails.
It’s called synchronicity.
It’s the experience of hearing a song that reminds you of a friend that you’ve lost touch with, only to get an email from her the same day. It’s needing to make a difficult decision, saying out loud “what should I do?” and at that moment, a bus drives by with an advertisement whose headline gives you your answer. It’s getting a call from a number ending in 1525 just as you’re paying for your breakfast which is also $15.25.
Synchronicity was coined by psychologist Carl Jung to describe events that occur at the same time, without a shared cause, but are connected in meaning. Synchronicity goes beyond coincidence–not just happening at the same time. There is some meaningful connection that goes beyond scientific explanation.
Surely it’s more than luck. These “rhyming events” mean something, right?
I’ve done some research and there are 3 likely justifications to explain synchronicity.
One explanation is human psychology.
Our brains are naturally meaning-making machines. We look for the signs we need to help us make difficult decisions we couldn’t easily make on our own so we connect events that happen randomly and assign meaning.
Another is mathematics and probability.
The Law of Truly Large Numbers states that in any extremely large data set, any outrageous and unusual event is likely to occur. It’s merely coincidence and it’s not unusual in the spectrum of possibilities that the same number would show up several times in a day, for example.
The last explanation (and go with me on this for a minute) is divine Intervention.
God, an angel, fate or higher power is sending you a message. YOU. The events were a message meant for you. The universe knows your name and is trying to tell you something. (Even talking about “the universe” is a way of discussing a higher power without getting into a conversation about religion.) Believing that “the universe” sends messages and aligns events for a purpose is to believe in a higher power.
Maybe you believe in God. Maybe you believe in “the universe.” Maybe not. But all of this speculating and sorting out what I believe in leads me to this question:
Do I believe the universe is chaos– that we’re anonymous in a world of 7 billion, all with random, unrelated events?
Or would I rather believe that there is an order– that the universe knows who I am, and is sending me signs and messages?
What do you believe? | https://medium.com/email-refrigerator/rhythm-58aa21d70e05 | ['Jake Kahana'] | 2020-12-28 00:44:57.616000+00:00 | ['Self-awareness', 'Lifestyle Design', 'Self', 'Music', 'Procrastination'] | Title RhythmContent Personal History Calendar 2011 started project called Personal History Calendar designed calendar listed event year aiming 365 day memorable personal events– first milestone memorable night intention create calendar anniversary personal history every day Eventually able full year full memory knowing today’s history tried Kangaroo meat first time 2009 tomorrow anniversary first flight 1985 Sure TimeHop Facebook tell today anniversary day became friend guy sat next Earth Sciences college Personal History Calendar intimate revealing documentation Things shouldn’t public stopped around 190 event half mostly could wring enough personal detail fill full year Perhaps I’ll continue add course life able create moment memory every day September 27 always day nothing great happens September 28 6 different memory feel though day attract action get skipped day energy week pulse alternating stress relaxation year period intensity calm Chapters Decades zoom current moment see entire life rhythm Ups down tension release month I’m exploring idea rhythm timing life Let’s dance “Sultanahmet” digital photograph Aydin Buyuktis II Rhyme… past Tuesday woke little earlier get nice little jog weather got cold started felt great music driving air perfect fire 10 minute quickly turned 20 usually start feel pain knee picking pace leg kept pushing arm kept pumping breathing consistent rhythm music perfect sync run step hit every beat light turned green approached world seemed cheering It’s amazing feeling world feel aligned direction giving u sign you’re thing right blowing wind sail It’s called synchronicity It’s experience hearing song reminds friend you’ve lost touch get email day It’s needing make difficult decision saying loud “what do” moment bus drive advertisement whose headline give answer It’s getting call number ending 1525 you’re paying breakfast also 1525 Synchronicity coined psychologist Carl Jung describe event occur time without shared cause connected meaning Synchronicity go beyond coincidence–not happening time meaningful connection go beyond scientific explanation Surely it’s luck “rhyming events” mean something right I’ve done research 3 likely justification explain synchronicity One explanation human psychology brain naturally meaningmaking machine look sign need help u make difficult decision couldn’t easily make connect event happen randomly assign meaning Another mathematics probability Law Truly Large Numbers state extremely large data set outrageous unusual event likely occur It’s merely coincidence it’s unusual spectrum possibility number would show several time day example last explanation go minute divine Intervention God angel fate higher power sending message event message meant universe know name trying tell something Even talking “the universe” way discussing higher power without getting conversation religion Believing “the universe” sends message aligns event purpose believe higher power Maybe believe God Maybe believe “the universe” Maybe speculating sorting believe lead question believe universe chaos– we’re anonymous world 7 billion random unrelated event would rather believe order– universe know sending sign message believeTags Selfawareness Lifestyle Design Self Music Procrastination |
953 | What is a Feature Store for ML? | Feature Stores have become the key piece of data infrastructure for machine learning platforms. They manage the whole lifecycle of features: from training different models to providing low-latency access to features by online-applications for model inference. This article introduces the Hopsworks Feature Store for Databricks, and how it can accelerate and govern your model development and operations on Databricks.
What is a Feature Store?
The Feature Store for machine learning is a feature computation and storage service that enables features to be registered, discovered, and used both as part of ML pipelines as well as by online applications for model inferencing. Feature Stores are typically required to store both large volumes of feature data and provide low latency access to features for online applications. As such, they are typically implemented as a dual-database system: a low latency online feature store (typically a key-value store or real-time database) and a scale-out SQL database to store large volumes of feature data for training and batch applications. The online feature store enables online applications to enrich feature vectors with near real-time feature data before performing inference requests. The offline feature store can store large volumes of feature data that is used to create train/test data for model development or by batch applications for model scoring. The Feature Store solves the following problems in ML pipelines:
reuse of feature pipelines by sharing features between teams/projects;
enables the serving of features at scale and with low latency for online applications;
ensures the consistency of features between training and serving — features are engineered once and can be cached in both the Online and Offline Feature Stores;
ensures point-in-time correctness for features — when a prediction was made and an outcome arrives later, we need to be able to query the values of different features at a given point in time in the past.
The Feature Store for ML consists of both an Online and Offline database and Databricks can be used to transform raw data from backend systems into engineered features cached in the online and offline stores. Those features are made available to online and batch applications for inferencing and for creating train/test data for model training.
Engineer Features in Databricks, publish to the Feature Store
The process for ingesting and featurizing new data is separate from the process for training models using features that come from potentially many different sources. That is, there are often differences in the cadence for feature engineering compared to the cadence for model training. Some features may be updated every few seconds, while others are updated every few months. Models, on the other hand, can be trained on demand, regularly (every day or every week, for example), or when monitoring shows a model’s performance has degraded. Feature engineering pipelines are typically triggered at regular intervals when new data arrives or on-demand when source code is pushed to git because changes were made in how features are engineered.
Feature pipelines have a natural cadence for each data source, and the cached features can be reused by many downstream model training pipelines. Feature Pipelines can be developed in Spark or Pandas applications that are run on Databricks. They can be combined with data validation libraries like Deequ to ensure feature data is correct and complete.
The feature store enables feature pipelines to cache feature data for use by many downstream model training pipelines, reducing the time to create/backfill features. Groups of features are often computed together and have their own natural ingestion cadence, see figure above. Real-time features may be updated in the online feature store every few seconds using a streaming application, while batch features could be updated hourly, daily, weekly, or monthly.
In practice, feature pipelines are data pipelines, where the output is cleaned, validated, featurized data. As there are typically no guarantees on the correctness of the incoming data, input data must be validated and any missing values must be handled (often by either imputing them or ignoring them). One popular framework for data validation with Spark is AWS Deequ, as they allow you to extend traditional schema-based support for validating data (e.g., this column should contain integers) with data validation rules for numerical or categorical values. For example, while a schema ensures that a numerical feature is of type float, additional validation rules are needed to ensure those floats lie within an expected range. You can also check to ensure a columns’ values are unique, not null, that its descriptive statistics are within certain ranges. Validated data is then transformed into numeric and categorical features that are then cached in the feature store, and subsequently used both to train models and for batch/online model inferencing.
import hsfs
# “prod” is the production feature store conn = hsfs.connection(host=”ea2.aws.hopsworks.ai”, project=”prod”)
featurestore = conn.get_feature_store() # read raw data and use Spark to engineer features
raw_data_df = spark.read.parquet(‘/parquet_partitioned’)
polynomial_features = raw_data_df.map(lambda x: x²) # Features computed together in a DataFrames are in the same feature group
fg = featurestore.create_feature_group(name=’fg_revenue’,
version=1,
type=’offline’) fg.create(polynomial_features)
g.compute_statistics()
In this code snippet, we connect to the Hopsworks Feature Store, read some raw data into a DataFrame from a parquet file, and transform the data into polynomial features. Then, we create a feature group, it’s version is ‘1’ and it is only to be stored in the ‘offline’ feature store. Finally, we ingest our new polynomial_dataframe into the feature group, and compute statistics over the feature group that are also stored in the Hopsworks Feature Store. Note that Pandas DataFrames are supported as well as Spark DataFrames, and there are both Python and Scala/Java APIs.
When a feature store is available, the output of feature pipelines is cached feature data, stored in the feature store. Ideally, the destination data sink will have support for versioned data, such as in Apache Hudi in Hopsworks Feature Store. In Hopsworks, feature pipelines upsert (insert or update) data into existing feature groups, where a feature group is a set of features computed together (typically because they come from the same backend system and are related by some entity or key). Every time a feature pipeline runs for a feature group, it creates a new commit in the sink Hudi dataset. This way, we can track and query different commits to feature groups in the Feature Store, and monitor changes to statistics of ingested data over time.
You can find an example notebook for feature engineering with PySpark in Databricks and registering features with Hopsworks here.
Model Training Pipelines in Databricks start at the Feature Store
Model training pipelines in Databricks can read in train/test data either directly as Spark Dataframes from the Hopsworks Feature Store or as train/test files in S3 (in a file format like .tfrecords or .npy or .csv or .petastorm). Notebooks/jobs in Databricks can use the Hopsworks Feature Store to join features together to create such train/test datasets on S3.
Model training with a feature store typically involves at least three stages:
select the features from feature groups and join them together to build a train/test dataset. You may also here want to filter out data and include an optional timestamp to retrieve features exactly as they were at a point of time in the past; train the model using the training dataset created in step 1 (training can be further decomposed into the following steps: hyperparameter optimization, ablation study, and model training); validate the model using automated tests and deploy it to a model registry for batch applications and/or an online model server for online applications.
import hsfs
conn = hsfs.connection(host=”ea2.aws.hopsworks.ai”, project=”prod”)
featurestore = conn.get_feature_store() # get feature groups from which you want to create a training dataset
fg1 = featurestore.get_feature_group(‘fg_revenue’, version=1)
fg2 = featurestore.get_feature_group(‘fg_users’, version=2)
# lazily join features
joined_features = fg1.select_all() \
.join(fg2.select([‘user_id’, ‘age’]), on=’user_id’) sink = featurestore.get_storage_connector(‘S3-training-dataset-bucket’) td = featurestore.create_training_dataset(name=’revenue_prediction’,
version=1,
data_format=’tfrecords’,
storage_connector=sink,
split={‘train’: 0.8, ‘test’: 0.2}) td.seed = 1234
td.create(joined_features)
Data Scientists are able to rely on the quality and business logic correctness in published features and can therefore quickly export and create training datasets in their favourite data format.
You can find an example notebook for getting started with creating train/test datasets from Hopsworks in Databricks here.
Deploying the Hopsworks Feature Store for Databricks
The Hopsworks Feature Store is available as a managed platform for AWS (Hopsworks.ai) and as an Enterprise platform for Azure.
Hopsworks.ai for AWS
Hopsworks.ai is our new managed platform for the Hopsworks Feature Store on AWS. In its current version, it will deploy a Hopsworks Feature Store into your AWS account. From Hopsworks.ai, you can stop/start/backup your Hopsworks Feature Store.
The details for how to launch a Hopsworks Feature Store inside an existing VPC/subnet used by Databricks are found in our documentation. The following figures from Hopsworks.ai show you how you have to pick the same Region/VPC/Zone used by your Databricks cluster when launching Hopsworks.
You also need to expose the Feature Store service for use by Databricks, see the figure below.
For some Enterprises, an alternative to deploying Hopsworks in the same VPC as Databricks is VPC peering. VPC peering requires manual work, and you can contact us for help in VPC peering.
Enterprise Hopsworks for Databricks Azure
On Azure, by default, Databricks is deployed to a locked resource group with all data plane resources, including a virtual network (VNet) that all clusters will be associated with. However, with VNet injection, you can deploy Azure Databricks into the same virtual network where the Hopsworks Feature Store is deployed. Contact us for more details on how to install and setup VNet injection for Azure with Hopsworks Feature Store. An alternative to VNet injection is VPC, and you can contact us for help in VPC peering.
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Summary
A new key piece of infrastructure for machine learning has now arrived for Databricks users — the Hopsworks Feature Store. It enables you to centralize your features for ML for easier discovery and governance, it enables the reuse of features in different ML projects, and provides a single pipeline or engineering features for both training and inference. The Hopsworks Feature Store is available today as either a managed platform or AWS, so you can spin up a cluster in just a few minutes, or as an Enterprise platform for either AWS or Azure.
References
This article was originally posted on Logical Clocks’ Blog. | https://medium.com/data-for-ai/what-is-a-feature-store-for-ml-29b62580af5d | ['Jim Dowling'] | 2020-05-19 07:38:37.895000+00:00 | ['Machine Learning', 'Artificial Intelligence', 'Data Engineering', 'Feature Store', 'Deep Learning'] | Title Feature Store MLContent Feature Stores become key piece data infrastructure machine learning platform manage whole lifecycle feature training different model providing lowlatency access feature onlineapplications model inference article introduces Hopsworks Feature Store Databricks accelerate govern model development operation Databricks Feature Store Feature Store machine learning feature computation storage service enables feature registered discovered used part ML pipeline well online application model inferencing Feature Stores typically required store large volume feature data provide low latency access feature online application typically implemented dualdatabase system low latency online feature store typically keyvalue store realtime database scaleout SQL database store large volume feature data training batch application online feature store enables online application enrich feature vector near realtime feature data performing inference request offline feature store store large volume feature data used create traintest data model development batch application model scoring Feature Store solves following problem ML pipeline reuse feature pipeline sharing feature teamsprojects enables serving feature scale low latency online application ensures consistency feature training serving — feature engineered cached Online Offline Feature Stores ensures pointintime correctness feature — prediction made outcome arrives later need able query value different feature given point time past Feature Store ML consists Online Offline database Databricks used transform raw data backend system engineered feature cached online offline store feature made available online batch application inferencing creating traintest data model training Engineer Features Databricks publish Feature Store process ingesting featurizing new data separate process training model using feature come potentially many different source often difference cadence feature engineering compared cadence model training feature may updated every second others updated every month Models hand trained demand regularly every day every week example monitoring show model’s performance degraded Feature engineering pipeline typically triggered regular interval new data arrives ondemand source code pushed git change made feature engineered Feature pipeline natural cadence data source cached feature reused many downstream model training pipeline Feature Pipelines developed Spark Pandas application run Databricks combined data validation library like Deequ ensure feature data correct complete feature store enables feature pipeline cache feature data use many downstream model training pipeline reducing time createbackfill feature Groups feature often computed together natural ingestion cadence see figure Realtime feature may updated online feature store every second using streaming application batch feature could updated hourly daily weekly monthly practice feature pipeline data pipeline output cleaned validated featurized data typically guarantee correctness incoming data input data must validated missing value must handled often either imputing ignoring One popular framework data validation Spark AWS Deequ allow extend traditional schemabased support validating data eg column contain integer data validation rule numerical categorical value example schema ensures numerical feature type float additional validation rule needed ensure float lie within expected range also check ensure columns’ value unique null descriptive statistic within certain range Validated data transformed numeric categorical feature cached feature store subsequently used train model batchonline model inferencing import hsfs “prod” production feature store conn hsfsconnectionhost”ea2awshopsworksai” project”prod” featurestore conngetfeaturestore read raw data use Spark engineer feature rawdatadf sparkreadparquet‘parquetpartitioned’ polynomialfeatures rawdatadfmaplambda x x² Features computed together DataFrames feature group fg featurestorecreatefeaturegroupname’fgrevenue’ version1 type’offline’ fgcreatepolynomialfeatures gcomputestatistics code snippet connect Hopsworks Feature Store read raw data DataFrame parquet file transform data polynomial feature create feature group it’s version ‘1’ stored ‘offline’ feature store Finally ingest new polynomialdataframe feature group compute statistic feature group also stored Hopsworks Feature Store Note Pandas DataFrames supported well Spark DataFrames Python ScalaJava APIs feature store available output feature pipeline cached feature data stored feature store Ideally destination data sink support versioned data Apache Hudi Hopsworks Feature Store Hopsworks feature pipeline upsert insert update data existing feature group feature group set feature computed together typically come backend system related entity key Every time feature pipeline run feature group creates new commit sink Hudi dataset way track query different commits feature group Feature Store monitor change statistic ingested data time find example notebook feature engineering PySpark Databricks registering feature Hopsworks Model Training Pipelines Databricks start Feature Store Model training pipeline Databricks read traintest data either directly Spark Dataframes Hopsworks Feature Store traintest file S3 file format like tfrecords npy csv petastorm Notebooksjobs Databricks use Hopsworks Feature Store join feature together create traintest datasets S3 Model training feature store typically involves least three stage select feature feature group join together build traintest dataset may also want filter data include optional timestamp retrieve feature exactly point time past train model using training dataset created step 1 training decomposed following step hyperparameter optimization ablation study model training validate model using automated test deploy model registry batch application andor online model server online application import hsfs conn hsfsconnectionhost”ea2awshopsworksai” project”prod” featurestore conngetfeaturestore get feature group want create training dataset fg1 featurestoregetfeaturegroup‘fgrevenue’ version1 fg2 featurestoregetfeaturegroup‘fgusers’ version2 lazily join feature joinedfeatures fg1selectall joinfg2select‘userid’ ‘age’ on’userid’ sink featurestoregetstorageconnector‘S3trainingdatasetbucket’ td featurestorecreatetrainingdatasetname’revenueprediction’ version1 dataformat’tfrecords’ storageconnectorsink split‘train’ 08 ‘test’ 02 tdseed 1234 tdcreatejoinedfeatures Data Scientists able rely quality business logic correctness published feature therefore quickly export create training datasets favourite data format find example notebook getting started creating traintest datasets Hopsworks Databricks Deploying Hopsworks Feature Store Databricks Hopsworks Feature Store available managed platform AWS Hopsworksai Enterprise platform Azure Hopsworksai AWS Hopsworksai new managed platform Hopsworks Feature Store AWS current version deploy Hopsworks Feature Store AWS account Hopsworksai stopstartbackup Hopsworks Feature Store detail launch Hopsworks Feature Store inside existing VPCsubnet used Databricks found documentation following figure Hopsworksai show pick RegionVPCZone used Databricks cluster launching Hopsworks also need expose Feature Store service use Databricks see figure Enterprises alternative deploying Hopsworks VPC Databricks VPC peering VPC peering requires manual work contact u help VPC peering Enterprise Hopsworks Databricks Azure Azure default Databricks deployed locked resource group data plane resource including virtual network VNet cluster associated However VNet injection deploy Azure Databricks virtual network Hopsworks Feature Store deployed Contact u detail install setup VNet injection Azure Hopsworks Feature Store alternative VNet injection VPC contact u help VPC peering Learn Summary new key piece infrastructure machine learning arrived Databricks user — Hopsworks Feature Store enables centralize feature ML easier discovery governance enables reuse feature different ML project provides single pipeline engineering feature training inference Hopsworks Feature Store available today either managed platform AWS spin cluster minute Enterprise platform either AWS Azure References article originally posted Logical Clocks’ BlogTags Machine Learning Artificial Intelligence Data Engineering Feature Store Deep Learning |
954 | Migrating Single-Page Applications from Heroku to AWS | Our deployment architecture can be divided into two main categories:
SPA hosting URL Routing
As mentioned earlier, this split comes from the desire to separate our hosting and routing layers. By splitting them up, we are better able to design for future changes.
SPA Hosting
“Hosting” simply refers to where the SPA files (html, css, and javascript files, etc.) physically live, and a URL that can be hit to access them.
Our new design uses Amazon Simple Storage Service (S3) for hosting. Each SPA is given its own S3 bucket. Some of the key advantages of S3 are its high availability (99.9%) and robust backups. For any public-facing website, where being available at all times is critical, these features provide major advantages. S3’s biggest drawback is that it can only host static artifacts. Because our SPAs are client-side rendered, this limitation is ok.
For URL access, SSL security, and caching, Guild uses Cloudfront (not to be confused with Cloudflare, already mentioned, for DNS and routing). AWS Cloudfront provides us with a unique URL that can be used to access the application hosted in a bucket.
Tips for S3 hosting
Keep separate buckets for each SPA. Doing so will help keep each SPA isolated and allows for independent deployment lifecycles.
Enforce naming standards to enable discoverability. You want it to be fairly obvious what a bucket does, just by looking at the name. We name our SPA buckets after the Github repo they serve, and the domain name they are hosted on. (E.g. {github-repo-name}.{domain-name}.com ). This allows us to easily identify which application a bucket hosts.
). This allows us to easily identify which application a bucket hosts. Remember to make use of object “metadata”. We use metadata to provide HTTP headers like MIME types and cache control headers.
URL Routing
URL routing emerged as the most challenging aspect of our deployment architecture. It also proved to be the most vital in accomplishing the decoupling we were going for.
Previously, each application employed its own unique way of routing its public-facing URL (i.e. the route a user visited to see a page) to the URL that Heroku provided for an application deployment.
To address these challenges, we broke up URL routing into two parts:
Translating a public request Translating an asset request
Translating a public request | https://medium.com/extra-credit-by-guild/moving-our-guild-spas-from-heroku-to-aws-a0ae5973975b | ['Justin Menestrina'] | 2020-10-01 19:06:36.380000+00:00 | ['Single Page Applications', 'Software Engineering', 'Frontend Architecture', 'Software Architecture', 'AWS'] | Title Migrating SinglePage Applications Heroku AWSContent deployment architecture divided two main category SPA hosting URL Routing mentioned earlier split come desire separate hosting routing layer splitting better able design future change SPA Hosting “Hosting” simply refers SPA file html cs javascript file etc physically live URL hit access new design us Amazon Simple Storage Service S3 hosting SPA given S3 bucket key advantage S3 high availability 999 robust backup publicfacing website available time critical feature provide major advantage S3’s biggest drawback host static artifact SPAs clientside rendered limitation ok URL access SSL security caching Guild us Cloudfront confused Cloudflare already mentioned DNS routing AWS Cloudfront provides u unique URL used access application hosted bucket Tips S3 hosting Keep separate bucket SPA help keep SPA isolated allows independent deployment lifecycles Enforce naming standard enable discoverability want fairly obvious bucket looking name name SPA bucket Github repo serve domain name hosted Eg githubreponamedomainnamecom allows u easily identify application bucket host allows u easily identify application bucket host Remember make use object “metadata” use metadata provide HTTP header like MIME type cache control header URL Routing URL routing emerged challenging aspect deployment architecture also proved vital accomplishing decoupling going Previously application employed unique way routing publicfacing URL ie route user visited see page URL Heroku provided application deployment address challenge broke URL routing two part Translating public request Translating asset request Translating public requestTags Single Page Applications Software Engineering Frontend Architecture Software Architecture AWS |
955 | How to Think About Sustainability | Sustainability can be vague and conflicting.
That doesn’t stop people from mentioning it virtually everywhere nowadays. They use it when they talk about climate change and environmental pollution. It’s a good thing that pressing issues like these are finally getting some attention. But too often, the frames they use distract you from exploring actual sustainability, resulting merely in greenwashed marketing.
To grasp what sustainability is, you need to think bigger.
The Systems of Life
Sustainability refers to the capacity of life to exist constantly.
What makes this concept complex is that all of life’s actions are unsustainable when you isolate them. You have to look at the bigger picture and inspect the connections in the system to see how sustainability emerges.
The Earth’s ecological systems are made up of groups of organisms that both consume and produce materials. One organism’s material production (i.e. waste) is consumed by another one or stored in a buffer. Chains of production and consumption then form a web of feedback loops that, supplied with energy from the sun, can run almost indefinitely.
Life thrives when environmental conditions are within certain bounds, a so-called sweet spot. But external forces, disturbances, and evolution can introduce imbalances.
In general, ecological systems can adapt and stabilise using the diversity of feedback loops that exists. This, however, doesn’t mean that everything will survive. Groups of organisms might die off so that others can rise and the systems are sustained.
If Earth’s systems fail to adapt to new imbalances, we stray away from the sweet spot of life and large scale destruction will follow.
The Symptoms of Our Unsustainability
Even though it probably wasn’t all too conscious, for most of history we have been living in touch with our environment. It was both a blessing and a curse to be at the mercy of the forces around us.
Craving for more certainty and stability, we took matters into our own hands. We used our ingenuity to bend the rules of our environment to our own will. We disrupted the systems we live in to improve our success.
We think we mostly act in our own best interests. But for the most part, we struggle to comprehend what the consequences are in the long term. Or even if we get that, we fail to act on this knowledge.
The consequences of our unsustainable behaviour are becoming more apparent than ever. We see that the needs and desires of a minority oppress the needs of the majority.
On the ecological level, we humans are this minority. This is resulting in climate change, environmental degradation, material resource depletion, and biodiversity loss that could end in mass extinction.
On the societal level, power imbalances exist where an elite undermines the needs of the majority of people. These imbalances have led to social inequalities in a variety of dimensions, including wealth, wellbeing, human rights, geopolitics, and knowledge.
Why do we endure the imbalances that torment us? Because we believe in them.
Yuval Noah Harari discusses this in Homo Deus:
Most human kingdoms and empires were extremely unequal, yet many of them were surprisingly stable and efficient. […] Threats and promises [that rulers employ] often succeed in creating stable human hierarchies and mass cooperation networks, as long as people believe that they reflect the inevitable laws of nature or the divine commands of God, rather than just human whims. All large-scale human cooperation is ultimately based on our belief in imagined orders. These are sets of rules that, despite existing only in our imagination, we believe to be as real and inviolable as gravity.
Out of our own imagined powerlessness to the social order, we accept the rules and laws of our religions.
Modern religions, that focus instead on “our superiority”, can be even more toxic. Harari continues:
The founding idea of humanist religions such as liberalism, communism and Nazism is that Homo sapiens has some unique and sacred essence that is the source of all meaning and authority in the universe. Everything that happens in the cosmos is judged to be good or bad according to its impact on Homo sapiens.
We’ve inherited stories and imagined orders that make us believe we are either powerless or rulers of the planet. But as we finally begin to understand the consequences of these ideas, our beliefs start to crumble.
The Challenges on Our Quest for Balance
The stories we write should send us on a quest to a new sweet spot, where humanity and the natural systems we depend on can once again flourish.
This quest isn’t without challenges. Most importantly, we have to figure out:
What we actually need to live fulfilling lives . Life is more than just survival. At least, that is what we believe. Society has sold us a dream of wealth and status. But that won’t bring the fulfillment we long for. It’s best to recognise it sooner rather than later. We should instead identify what is really valuable in life, and create meaning and collective purpose from that.
. Life is more than just survival. At least, that is what we believe. Society has sold us a dream of wealth and status. But that won’t bring the fulfillment we long for. It’s best to recognise it sooner rather than later. We should instead identify what is really valuable in life, and create meaning and collective purpose from that. What our environment needs to thrive . We depend on what our environment produces. We should value it accordingly, and thus we have to create the conditions where it can thrive as well.
. We depend on what our environment produces. We should value it accordingly, and thus we have to create the conditions where it can thrive as well. How to handle conflicting needs. We face various imbalances that can conflict with each other and must be compromised effectively. One of the biggest is the conflict between the societal development of large parts of the world and the global climate crisis. We want to improve the lives of all humans but we cannot afford for these countries to walk the same path of fossil reliance. It is the responsibility of developed countries to step up, reduce their own footprints, and support sustainable development for others. Only then can we limit the intermediate stages of fossil dependency.
We face various imbalances that can conflict with each other and must be compromised effectively. One of the biggest is the conflict between the societal development of large parts of the world and the global climate crisis. We want to improve the lives of all humans but we cannot afford for these countries to walk the same path of fossil reliance. It is the responsibility of developed countries to step up, reduce their own footprints, and support sustainable development for others. Only then can we limit the intermediate stages of fossil dependency. How to consider future needs. Even though humans surpass every other species in planning for the future, we still suck at it on the long term scale. Seduced by quick gratifications, short-term profits, and comfort, we often ignore the consequences. But the future is arriving. If we care anything about our future selves and all our possible descendants, we have to take responsibility for our actions and think ahead. We have to see that decisions made for the future are not costs but investments, that will pay themselves back manyfold.
These questions require our collective effort to have a chance of being answered. But that doesn’t mean you are powerless as an individual.
How to Move Forward
The road ahead is tough. Then again, overcoming adversity is what makes life worth living.
You can take off by becoming aware of our collective unsustainable behaviour. And acknowledging your own role in it. You may not have created these problems, but everyone contributes to it, including me and you.
See that your actions do have an impact. Explore what their consequences are, on you and your environment. Now and in the future. That they can harm yet also can drive change, reduce, restore, or at least prevent worse from happening.
Then, reflect on what you actually value in life and talk about it with others. One person does not have all the answers. A diversity of perspectives can contrast your own experience and show you new possibilities. You’ll find your wisdom in the collective.
Your values are best discovered by having some life experience. If you’re still young, why not get some inspiration from the experiences of others as well? Even though we have had technological progress, our biology and thus our needs haven’t changed much. So have a chat with the elders around you, read a couple of memoirs, or get inspired online.
As you find bits that resonate with you, internalise and apply them to every part of your life. Shape your life around them. Introduce them bit by bit into your work, your relationships, your pastimes, and your political engagement.
Live by example and inspire others in the process. | https://medium.com/climate-conscious/how-to-think-about-sustainability-c5b50eb43d71 | ['Alex Van Domburg'] | 2020-10-16 15:03:07.666000+00:00 | ['Climate Change', 'Psychology', 'Sustainability', 'Systems Thinking', 'Life'] | Title Think SustainabilityContent Sustainability vague conflicting doesn’t stop people mentioning virtually everywhere nowadays use talk climate change environmental pollution It’s good thing pressing issue like finally getting attention often frame use distract exploring actual sustainability resulting merely greenwashed marketing grasp sustainability need think bigger Systems Life Sustainability refers capacity life exist constantly make concept complex life’s action unsustainable isolate look bigger picture inspect connection system see sustainability emerges Earth’s ecological system made group organism consume produce material One organism’s material production ie waste consumed another one stored buffer Chains production consumption form web feedback loop supplied energy sun run almost indefinitely Life thrives environmental condition within certain bound socalled sweet spot external force disturbance evolution introduce imbalance general ecological system adapt stabilise using diversity feedback loop exists however doesn’t mean everything survive Groups organism might die others rise system sustained Earth’s system fail adapt new imbalance stray away sweet spot life large scale destruction follow Symptoms Unsustainability Even though probably wasn’t conscious history living touch environment blessing curse mercy force around u Craving certainty stability took matter hand used ingenuity bend rule environment disrupted system live improve success think mostly act best interest part struggle comprehend consequence long term even get fail act knowledge consequence unsustainable behaviour becoming apparent ever see need desire minority oppress need majority ecological level human minority resulting climate change environmental degradation material resource depletion biodiversity loss could end mass extinction societal level power imbalance exist elite undermines need majority people imbalance led social inequality variety dimension including wealth wellbeing human right geopolitics knowledge endure imbalance torment u believe Yuval Noah Harari discus Homo Deus human kingdom empire extremely unequal yet many surprisingly stable efficient … Threats promise ruler employ often succeed creating stable human hierarchy mass cooperation network long people believe reflect inevitable law nature divine command God rather human whim largescale human cooperation ultimately based belief imagined order set rule despite existing imagination believe real inviolable gravity imagined powerlessness social order accept rule law religion Modern religion focus instead “our superiority” even toxic Harari continues founding idea humanist religion liberalism communism Nazism Homo sapiens unique sacred essence source meaning authority universe Everything happens cosmos judged good bad according impact Homo sapiens We’ve inherited story imagined order make u believe either powerless ruler planet finally begin understand consequence idea belief start crumble Challenges Quest Balance story write send u quest new sweet spot humanity natural system depend flourish quest isn’t without challenge importantly figure actually need live fulfilling life Life survival least believe Society sold u dream wealth status won’t bring fulfillment long It’s best recognise sooner rather later instead identify really valuable life create meaning collective purpose Life survival least believe Society sold u dream wealth status won’t bring fulfillment long It’s best recognise sooner rather later instead identify really valuable life create meaning collective purpose environment need thrive depend environment produce value accordingly thus create condition thrive well depend environment produce value accordingly thus create condition thrive well handle conflicting need face various imbalance conflict must compromised effectively One biggest conflict societal development large part world global climate crisis want improve life human cannot afford country walk path fossil reliance responsibility developed country step reduce footprint support sustainable development others limit intermediate stage fossil dependency face various imbalance conflict must compromised effectively One biggest conflict societal development large part world global climate crisis want improve life human cannot afford country walk path fossil reliance responsibility developed country step reduce footprint support sustainable development others limit intermediate stage fossil dependency consider future need Even though human surpass every specie planning future still suck long term scale Seduced quick gratification shortterm profit comfort often ignore consequence future arriving care anything future self possible descendant take responsibility action think ahead see decision made future cost investment pay back manyfold question require collective effort chance answered doesn’t mean powerless individual Move Forward road ahead tough overcoming adversity make life worth living take becoming aware collective unsustainable behaviour acknowledging role may created problem everyone contributes including See action impact Explore consequence environment future harm yet also drive change reduce restore least prevent worse happening reflect actually value life talk others One person answer diversity perspective contrast experience show new possibility You’ll find wisdom collective value best discovered life experience you’re still young get inspiration experience others well Even though technological progress biology thus need haven’t changed much chat elder around read couple memoir get inspired online find bit resonate internalise apply every part life Shape life around Introduce bit bit work relationship pastime political engagement Live example inspire others processTags Climate Change Psychology Sustainability Systems Thinking Life |
956 | Understanding the Inference Mechanism of RCNs | RCN
Understanding the Inference Mechanism of RCNs
Adapting the generative model for classification to break CAPTCHA
If you take a look at Stanford’s AI Index report of 2019, you will notice that the performance of models on famous challenges is starting to saturate [1]. For that reason, I believe that we need to shed a light on new ideas to advance deep learning even further than it has reached. And, one of the fields that I think should eagerly strive for progress is computer vision because, as Fei-Fei Li said, understanding vision is really understanding intelligence [2].
The new idea we explore in this column of articles is Recursive Cortical Networks (RCNs) [3], the brainchild of the company Vicarious which has attracted the attention of investors like Musk & Zuckerberg [4]. In this article, we talk about how RCNs are adapted to perform classification rather than generation.
An RCN model classifying the letter ‘A’ | taken from Vicarious’ Blog
This article assumes an understanding of the structure of RCNs and how they perform generation which you can gain from reading the supplementary material of [3], or from reading my previous article.
Single Object Detection
Given an image with a certain object in it, we want the RCN to tell us which class the object belongs to. RCNs achieve that by posing the question: if we assume that the input image was actually generated by the RCN, which channel in the topmost layer is the most likely channel to have generated it? In RCNs, answering that will not only identify the class of the object but also its location. To answer it, we could try to build a joint probability distribution model of all the states of all the random variables (the channels) we have in the RCN, a model that computes the probability of each certain full assignment of states to all the channels. Having that, we would condition the model on the input image, find the full assignment that has the maximum probability, and then find the channel in the topmost layer that is set to ‘true’.
However, that is intractable since we have a ton of random variables. Luckily, RCNs are inherently graphical models which means that they exploit the conditional independence structure between their random variables to make that task more tractable. To be more clear, we need to notice that a channel can directly know the state it should be in (e.g true or false in case of feature channels) if it knows the state of the channels that are directly wired to it; it doesn’t need to know the state of all channels in the RCN. In other words, a channel is conditionally independent of all channels given the channels that it is wired to. This saves us from a huge amount of computation that a full joint distribution model would have needed.
There are a lot of efficient algorithms that are able to exploit the conditional independence we just talked about, namely belief propagation algorithms which the authors use. Explaining belief propagation is out of the scope of this article and isn’t a new thing, but the gist of it is that we are going to propagate information (called messages) from the bottom-most layer, since the evidence is there, to the top-most layer, layer by layer. The information each channel sends is just a single number for each state its parent can be in. This number doesn’t have much of a meaning in my opinion; it came from simple algebraic manipulations of the equations required to get the max probability state of a certain random variable in the graphical model. So, running a forward pass of the algorithm (bottom-up) will give us the probability of each state of each channel in the top-most layer. Choosing the channel with the highest (state = ‘true’) probability answers our question.
Object Reconstruction
Unlike ConvNets, RCNs can naturally handle multiple objects in the scene and also reconstruct them. For reconstruction, we are going to make a belief propagation backward pass from the channel of the detected class in the top-most layer to the channels in the bottom-most layer. This time, however, the backward pass messages will be able to give us the most likely assignment to all the channels in the RCN, a global approximate MAP solution. If we have that, we would be able to know which channels in the bottom-most layer should be in (state = ‘true’) and thus construct an edge map using their patch descriptors. This will construct the whole object even if a part of it is occluded.
Multi-Object Detection
For detecting multiple objects in the scene, instead of just picking the most probable channel in the top-most layer after the forward pass, we want to pick a set of candidate channels that best explains the image. The authors develop a scene scoring function that can score the reconstruction done by a set of candidates which makes us able to compare between sets. They acquire the best set of candidates by finding the set that optimizes the scoring function using an approximate dynamic programming method.
That’s all for this article. If you want to learn more about RCN, you can check its paper [5] and the accompanying supplementary material document, or you can read the rest of my articles talking about the learning and the results of applying RCNs on different datasets. | https://medium.com/swlh/understanding-the-inference-mechanism-of-rcns-ba1f00416b63 | ['Ahmed Maher'] | 2020-02-03 14:57:21.631000+00:00 | ['Machine Learning', 'Rcn', 'Computer Vision', 'Artificial Intelligence'] | Title Understanding Inference Mechanism RCNsContent RCN Understanding Inference Mechanism RCNs Adapting generative model classification break CAPTCHA take look Stanford’s AI Index report 2019 notice performance model famous challenge starting saturate 1 reason believe need shed light new idea advance deep learning even reached one field think eagerly strive progress computer vision FeiFei Li said understanding vision really understanding intelligence 2 new idea explore column article Recursive Cortical Networks RCNs 3 brainchild company Vicarious attracted attention investor like Musk Zuckerberg 4 article talk RCNs adapted perform classification rather generation RCN model classifying letter ‘A’ taken Vicarious’ Blog article assumes understanding structure RCNs perform generation gain reading supplementary material 3 reading previous article Single Object Detection Given image certain object want RCN tell u class object belongs RCNs achieve posing question assume input image actually generated RCN channel topmost layer likely channel generated RCNs answering identify class object also location answer could try build joint probability distribution model state random variable channel RCN model computes probability certain full assignment state channel would condition model input image find full assignment maximum probability find channel topmost layer set ‘true’ However intractable since ton random variable Luckily RCNs inherently graphical model mean exploit conditional independence structure random variable make task tractable clear need notice channel directly know state eg true false case feature channel know state channel directly wired doesn’t need know state channel RCN word channel conditionally independent channel given channel wired save u huge amount computation full joint distribution model would needed lot efficient algorithm able exploit conditional independence talked namely belief propagation algorithm author use Explaining belief propagation scope article isn’t new thing gist going propagate information called message bottommost layer since evidence topmost layer layer layer information channel sends single number state parent number doesn’t much meaning opinion came simple algebraic manipulation equation required get max probability state certain random variable graphical model running forward pas algorithm bottomup give u probability state channel topmost layer Choosing channel highest state ‘true’ probability answer question Object Reconstruction Unlike ConvNets RCNs naturally handle multiple object scene also reconstruct reconstruction going make belief propagation backward pas channel detected class topmost layer channel bottommost layer time however backward pas message able give u likely assignment channel RCN global approximate MAP solution would able know channel bottommost layer state ‘true’ thus construct edge map using patch descriptor construct whole object even part occluded MultiObject Detection detecting multiple object scene instead picking probable channel topmost layer forward pas want pick set candidate channel best explains image author develop scene scoring function score reconstruction done set candidate make u able compare set acquire best set candidate finding set optimizes scoring function using approximate dynamic programming method That’s article want learn RCN check paper 5 accompanying supplementary material document read rest article talking learning result applying RCNs different datasetsTags Machine Learning Rcn Computer Vision Artificial Intelligence |
957 | RAPIDS Anywhere with Tailscale. It’s never been easier to get started… | Today, NVIDIA launched a massive GPU, the GeForce RTX 3090, and the first 24+ GB GPU with a price/GB of less than $70. When NVIDIA launched the Titan RTX I thought $100/GB was a steal…but the 3090 is ridiculous. Normally, we focus RAPIDS blogs on the software, but I’d be remiss to not talk about the value of cheap big memory, and the 3090 has this in spades. As we discuss often in RAPIDS, we have more than enough FLOPS in any GPU — what we really need is more memory and random access bandwidth. The more memory you have per GPU, the less data movement, and the larger problem you can work on. In almost all cases excluding embarrassingly parallel operations, one GPU with more memory is more efficient than two GPUs communicating over PCIe. Thus, the RTX 3090 has an amazing value.
In this blog, we’ll demonstrate how you can run RAPIDS workflows from your laptop (or any mobile device really) by connecting to a remote workstation using Tailscale.
With Tailscale, it’s easy to run accelerated workflows wherever you might be, even if you don’t have your GPUs with you. We’ll walk through how we did it on an Apple Macbook laptop. Just for fun, we even tested it with an Apple iPad!
Get Up and Running in 6 Easy Steps
Install Tailscale on both devices Obtain static IP address Connect to the remote workstation using this static IP address Install RAPIDS Spin up a Jupyterlab session Connect to Jupyter
Install Tailscale on Both Devices
Using Tailscale is simple. First, set up Tailscale on both the workstation and laptop. We followed their setup guide, which worked smoothly. Because the remote workstation is running Ubuntu, we first followed the Ubuntu installation instructions.
We install at the terminal and then authenticate by going to the link provided.
The laptop is running macOS, so we then followed the Mac installation instructions and downloaded the app.
Obtain IP Address
Once Tailscale is set up on both machines, you should have access to the static IP address assigned to the remote workstation from the Tailscale web admin console. Or, you can get this info from the Tailscale application on macOS.
Connect to Workstation
Next, connect to the remote workstation using this static IP address with `ssh user@{workstation-tailscale-ip}` .
Install RAPIDS
For the purposes of this blog, we use an HP Z4 workstation running Ubuntu 18.04 with dual NVIDIA Quadro RTX 8000 GPUs. Our workstation is already set up with NVIDIA drivers and CUDA, so we can easily run RAPIDS workflows when we’re physically there.
Once you’re connected to the workstation, choose your preferred way of installing RAPIDS libraries following the instruction on rapids.ai.
Spin Up a Jupyterlab Session
With the libraries installed, you can spin up a Jupyterlab session in whatever way you prefer.
Connect to Jupyter
With the Jupyterlab session up and running, you can open any browser on your laptop and connect to Jupyter using {workstation-tailscale-ip}:8888 (or whatever port number was assigned by JupyterLab)
That’s it! Now we can kick off some work and monitor the GPU dashboard while it runs. Below, we use both GPUs for K-Means clustering on some simulated data.
It’s never been easier to get started with GPUs and RAPIDS, and with Tailscale, you can kick off RAPIDS workflows from anywhere. Now, you’ll never have separation anxiety from your data science GPU again. For more info on cool trends in GPU data science, follow @RAPIDSai on Twitter, join us on Slack, or jump in on Github. | https://medium.com/rapids-ai/rapids-anywhere-with-tailscale-my-mobile-device-has-an-rtx-3090-1ce0c7b443fe | ['Josh Patterson'] | 2020-09-24 18:59:22.544000+00:00 | ['AI', 'Gaming', 'Data Science', 'Gpu', 'Big Data'] | Title RAPIDS Anywhere Tailscale It’s never easier get started…Content Today NVIDIA launched massive GPU GeForce RTX 3090 first 24 GB GPU priceGB le 70 NVIDIA launched Titan RTX thought 100GB steal…but 3090 ridiculous Normally focus RAPIDS blog software I’d remiss talk value cheap big memory 3090 spade discus often RAPIDS enough FLOPS GPU — really need memory random access bandwidth memory per GPU le data movement larger problem work almost case excluding embarrassingly parallel operation one GPU memory efficient two GPUs communicating PCIe Thus RTX 3090 amazing value blog we’ll demonstrate run RAPIDS workflow laptop mobile device really connecting remote workstation using Tailscale Tailscale it’s easy run accelerated workflow wherever might even don’t GPUs We’ll walk Apple Macbook laptop fun even tested Apple iPad Get Running 6 Easy Steps Install Tailscale device Obtain static IP address Connect remote workstation using static IP address Install RAPIDS Spin Jupyterlab session Connect Jupyter Install Tailscale Devices Using Tailscale simple First set Tailscale workstation laptop followed setup guide worked smoothly remote workstation running Ubuntu first followed Ubuntu installation instruction install terminal authenticate going link provided laptop running macOS followed Mac installation instruction downloaded app Obtain IP Address Tailscale set machine access static IP address assigned remote workstation Tailscale web admin console get info Tailscale application macOS Connect Workstation Next connect remote workstation using static IP address ssh userworkstationtailscaleip Install RAPIDS purpose blog use HP Z4 workstation running Ubuntu 1804 dual NVIDIA Quadro RTX 8000 GPUs workstation already set NVIDIA driver CUDA easily run RAPIDS workflow we’re physically you’re connected workstation choose preferred way installing RAPIDS library following instruction rapidsai Spin Jupyterlab Session library installed spin Jupyterlab session whatever way prefer Connect Jupyter Jupyterlab session running open browser laptop connect Jupyter using workstationtailscaleip8888 whatever port number assigned JupyterLab That’s kick work monitor GPU dashboard run use GPUs KMeans clustering simulated data It’s never easier get started GPUs RAPIDS Tailscale kick RAPIDS workflow anywhere you’ll never separation anxiety data science GPU info cool trend GPU data science follow RAPIDSai Twitter join u Slack jump GithubTags AI Gaming Data Science Gpu Big Data |
958 | Transcribe Your Zoom Meetings For Free with AWS! | Pretty good! The full text (not split by speaker) looks like:
Jack. I want to thank you for what he did. Not just for for pulling me back, but for your discretion. You're welcome. Look, I know what you must be thinking. Poor little rich girl. What does she know about misery? No, no, it's not what I was thinking. What I was thinking was what could have happened to this girl to make her think she had no way out. Yes. Well, I you It was everything. It was my whole world and all the people in it. And the inertia of my life plunging ahead in me, powerless to stop it. God, look at that. He would have gone straight to the bottom. 500 invitations have gone out. All of Philadelphia society will be there. And all the while I feel I'm standing in the middle of a crowded room screaming at the top of my lungs and no one even looks up. Do you love him? Pardon me, Love. You're being very rude. You shouldn't be asking me this. Well, it's a simple question. Do you love the guy or not? This is not a suitable conversation. Why can't you just answer the question? This is absurd. you don't know me, and I don't know you. And we are not having this conversation at all. You are rude and uncouth and presumptuous, and I am leaving now. Jack. Mr. Dawson, it's been a pleasure. I sought you out to thank you. And now I have thanked you and insulted. Well, you deserve it, right? Right. I thought you were leaving. I am. You are so annoying. Ha ha. Wait. I don't have to leave. Things is my part of the ship. You leave. Oh, well, well, well, now who's being rude? What is the stupid thing you're carrying around? So, what are you, an artist or something? He's a rather good. Yeah, very good, actually.
The text results are pleasantly accurate. Not something you could copy verbatim into an article, but it’s an amazing head start compared to transcribing a recording yourself from scratch.
Unfortunately, it did struggle a bit with identifying the different speakers correctly. After watching the clip again, I can see how maybe this wasn’t the best choice of scene since they do sound kind of similar, especially in the low-quality format produced by a converted YouTube video.
From personal experience, I can say that with Zoom recordings it’s had greater success thus far in correctly identifying each speaker, though I still haven’t tried it on a meeting with more than two people.
Final Thoughts
Overall, I’m happy with the functionality I was able to produce in a few hours of Thanksgiving weekend tinkering.
In truth, the reason I’m interested in this capability is I’d like to start supplanting my OC articles here on Medium with interviews of other data professionals. With this functionality figured out, I feel ready to reach out to people in my network and see if they are interested in sharing their thoughts and knowledge about working in data.
Oh, and if you are curious for the full transcribe.py script, I’ve included it below for your perusing pleasure!
Note: The code snippet above draws from this excellent AWS tutorial on the Amazon Transcribe service.
For more interesting content like this, follow me on Medium :) | https://medium.com/whispering-data/transcribe-your-zoom-meetings-for-free-with-aws-963f39a2aa3f | ['Paul Singman'] | 2020-11-30 19:46:25.543000+00:00 | ['Technology', 'Productivity', 'Data Science', 'Programming', 'AWS'] | Title Transcribe Zoom Meetings Free AWSContent Pretty good full text split speaker look like Jack want thank pulling back discretion Youre welcome Look know must thinking Poor little rich girl know misery thinking thinking could happened girl make think way Yes Well everything whole world people inertia life plunging ahead powerless stop God look would gone straight bottom 500 invitation gone Philadelphia society feel Im standing middle crowded room screaming top lung one even look love Pardon Love Youre rude shouldnt asking Well simple question love guy suitable conversation cant answer question absurd dont know dont know conversation rude uncouth presumptuous leaving Jack Mr Dawson pleasure sought thank thanked insulted Well deserve right Right thought leaving annoying Ha ha Wait dont leave Things part ship leave Oh well well well who rude stupid thing youre carrying around artist something Hes rather good Yeah good actually text result pleasantly accurate something could copy verbatim article it’s amazing head start compared transcribing recording scratch Unfortunately struggle bit identifying different speaker correctly watching clip see maybe wasn’t best choice scene since sound kind similar especially lowquality format produced converted YouTube video personal experience say Zoom recording it’s greater success thus far correctly identifying speaker though still haven’t tried meeting two people Final Thoughts Overall I’m happy functionality able produce hour Thanksgiving weekend tinkering truth reason I’m interested capability I’d like start supplanting OC article Medium interview data professional functionality figured feel ready reach people network see interested sharing thought knowledge working data Oh curious full transcribepy script I’ve included perusing pleasure Note code snippet draw excellent AWS tutorial Amazon Transcribe service interesting content like follow Medium Tags Technology Productivity Data Science Programming AWS |
959 | “Give a shit!”; a story on activism — 5 questions for Teresa Borasino | “Give a shit!”; a story on activism — 5 questions for Teresa Borasino
@Interactive Storytelling Meetup #6 –9 June 2016
Interview by Femke Deckers and Klasien van de Zandschulp
Teresa Borasino @ Interactive Storytelling Meetup #6
Teresa Borasino (Lima, based in Amsterdam) is an artist and activist working on environmental issues and social justice. She creates situations that allow for collective experiences and dialogue in public space. At Interactive Storytelling Meetup #6 she told us the story on how she got politicians to wipe their asses with science. In this interview we spoke with her about this act, the strength of combining art with activism and her newest project about fossil free culture.
1. What is the story of your project ‘Give a shit’?
“’Give a shit’ is an art and activism project. I organised this project as part of COP21 (COP21 is the annual climate yearly summit on climate change by UNFCCC). The last summit (December 2015) was a very important event, as the goal was to get to an agreement to reduce the CO2 emissions.”
“Before the conference started, all countries had to submit a pledge on what they would do to reduce CO2 emission in their country. Scientists analysed these pledges and evaluated them. If these pledges are implemented, we will have a global warming between 3 and 4 degrees Celsius. The IPCC publishes the most exhaustive and comprehensive scientific reports on climate change. We can read in this report, that scientists have agreed that we should limit global warming under 2 degrees. Beyond that threshold the world will become unliveable and catastrophic. This report serves as the scientific basis for politicians to negotiate about how to reduce CO2 emissions globally. But it seems that politicians are not following the facts and measures the IPCC report puts forward. The report serves as a basis to politicians to negotiate about the position on climate change. But it seems that politicians are not following this report.”
“So… I printed this IPCC report on toilet paper. I distributed 100 roles in the toilets of the summit in Paris, together with other activists and organisations who were accredited to visit the conference. We smuggled the toilet rolls inside the conference and placed them in the toilets to leave the message and to literally create the act that politicians wipe their ass with science. After our communal action it expanded and other organisations were using it by spreading the roles and using it to spread the story that politicians are not taking climate seriously.”
“Politicians wipe their ass with science”
The audience is reading the IPCC report on the toilet paper @ Interactive Storytelling Meetup #6
2. What was your motivation to execute your project ‘Give a shit’, and what were the reactions of attendees and activists?
“The Urgenda case. The Urgenda Foundation sued the Dutch government because the government was not doing enough to reduce the CO2 emissions. The Urgenda Foundation won the case. The judge ruled that the government should indeed aim for more. But two months later the government decided to appeal the ruling of the court. In my opinion, this is completely insane.”
“This case and the knowledge about the IPCC report is when the idea and motivation to do this project started. I want to send a message to all the politicians in the world who are obstructing climate progresses and remind them of the important details from the IPCC report.”
“I executed this action in an unofficial way, I didn’t have a permit. I had to convince a lot of people to help me and do this together. I had to bring in the toilet paper roles one by one to not be noticed by security. So to be able to execute this project, I had to talk to a lot of people beforehand to see if they are interested to join and help.”
“The people that took part and saw the paper in the toilet were very enthusiastic and created their own message and shared this online through Instagram, Twitter and Facebook.”
3. Do you think when we become more creative in telling our stories through activism, we can achieve better results?
“Yeah definitely. I think so. Actions and protests are usually very boring and similar to each other. Like people shouting and using banners that always look similar. Activists hardly look for more creative ways to bring on a message or tell a story.”
“Activists hardly look for more creative ways to bring on a message or tell a story”
“I’m working on socially engaged art over 10 years now, to give more visibility to social problems or change situations. But usually these changes are very small or temporary. So I’ve always tried to make change happen with art. Since I started to work more in an activist way, this can have far more impact if you work in a more artistic and creative way.”
“Artists have the ability to trigger imagination. Artists can imagine how certain issues can change and how we can live differently. Activists, on the other hand, are far more strategic and are communicating in a very straightforward way, but they might lack the ability to trigger imagination. I think it’s very powerful to combine both these expertises as a movement.”
“I’ve always tried to make change happen with art. Since I work more in an activist way, it has a far more impact .”
4. How important is storytelling as part of your work in combining activism and art?
“I try not only to tell a story, but also to make a change happen. The toilet paper project is a symbolic action. But the people who took part or experienced this action did notice how stories and messages in activism can happen in a more creative way and more artistic. I tried to raise awareness by telling the story in a different way. But also, to make people part of a movement.”
“I tried to raise awareness by telling the story in a different way. But also, to make people part of a movement.”
5. In your presentation you shortly announced on a new activism project. Can you shortly describe the discussion you want to start with this project?
“We started a couple of months ago with a new collective project called Fossil Free Culture. With this project we want to raise awareness about the oil sponsorships of the cultural institution. For instance companies like Shell sponsor major museums in the Netherlands. Not because they like art or are socially responsible, but because through these relationships they obtain a social license to operate. They use museums to organise lobby events and network events. They use museums to wash their image. We want to challenge these relationships. The goal is to expose and confront the influence of the fossil fuel industry on cultural institutions in the Netherlands.” | https://medium.com/interactive-innovative-storytelling/give-a-shit-activism-stories-5-questions-for-teresa-borasino-89442cbd26c8 | ['Interactive Storytelling'] | 2016-09-02 15:22:52.267000+00:00 | ['Environment', 'Climate Change', 'Storytelling'] | Title “Give shit” story activism — 5 question Teresa BorasinoContent “Give shit” story activism — 5 question Teresa Borasino Interactive Storytelling Meetup 6 –9 June 2016 Interview Femke Deckers Klasien van de Zandschulp Teresa Borasino Interactive Storytelling Meetup 6 Teresa Borasino Lima based Amsterdam artist activist working environmental issue social justice creates situation allow collective experience dialogue public space Interactive Storytelling Meetup 6 told u story got politician wipe ass science interview spoke act strength combining art activism newest project fossil free culture 1 story project ‘Give shit’ “’Give shit’ art activism project organised project part COP21 COP21 annual climate yearly summit climate change UNFCCC last summit December 2015 important event goal get agreement reduce CO2 emissions” “Before conference started country submit pledge would reduce CO2 emission country Scientists analysed pledge evaluated pledge implemented global warming 3 4 degree Celsius IPCC publishes exhaustive comprehensive scientific report climate change read report scientist agreed limit global warming 2 degree Beyond threshold world become unliveable catastrophic report serf scientific basis politician negotiate reduce CO2 emission globally seems politician following fact measure IPCC report put forward report serf basis politician negotiate position climate change seems politician following report” “So… printed IPCC report toilet paper distributed 100 role toilet summit Paris together activist organisation accredited visit conference smuggled toilet roll inside conference placed toilet leave message literally create act politician wipe as science communal action expanded organisation using spreading role using spread story politician taking climate seriously” “Politicians wipe as science” audience reading IPCC report toilet paper Interactive Storytelling Meetup 6 2 motivation execute project ‘Give shit’ reaction attendee activist “The Urgenda case Urgenda Foundation sued Dutch government government enough reduce CO2 emission Urgenda Foundation case judge ruled government indeed aim two month later government decided appeal ruling court opinion completely insane” “This case knowledge IPCC report idea motivation project started want send message politician world obstructing climate progress remind important detail IPCC report” “I executed action unofficial way didn’t permit convince lot people help together bring toilet paper role one one noticed security able execute project talk lot people beforehand see interested join help” “The people took part saw paper toilet enthusiastic created message shared online Instagram Twitter Facebook” 3 think become creative telling story activism achieve better result “Yeah definitely think Actions protest usually boring similar Like people shouting using banner always look similar Activists hardly look creative way bring message tell story” “Activists hardly look creative way bring message tell story” “I’m working socially engaged art 10 year give visibility social problem change situation usually change small temporary I’ve always tried make change happen art Since started work activist way far impact work artistic creative way” “Artists ability trigger imagination Artists imagine certain issue change live differently Activists hand far strategic communicating straightforward way might lack ability trigger imagination think it’s powerful combine expertise movement” “I’ve always tried make change happen art Since work activist way far impact ” 4 important storytelling part work combining activism art “I try tell story also make change happen toilet paper project symbolic action people took part experienced action notice story message activism happen creative way artistic tried raise awareness telling story different way also make people part movement” “I tried raise awareness telling story different way also make people part movement” 5 presentation shortly announced new activism project shortly describe discussion want start project “We started couple month ago new collective project called Fossil Free Culture project want raise awareness oil sponsorship cultural institution instance company like Shell sponsor major museum Netherlands like art socially responsible relationship obtain social license operate use museum organise lobby event network event use museum wash image want challenge relationship goal expose confront influence fossil fuel industry cultural institution Netherlands”Tags Environment Climate Change Storytelling |
960 | Writing Isn’t A Get-Rich-Quick Scheme | Writing isn’t a get-rich-quick scheme. Chances are you won’t publish a single piece of content and earn millions of dollars from it. I know many of us think if we publish the novel we’ve been working on or write that one fantastic blog post, which is sure to go viral, we’ll be set for life.
Thousands of followers, tons of royalties, adoration, fame, travel the world, the whole kit-n-caboodle. Right?
Wrong.
I’m sorry to burst your bubble, but it’s highly unlikely any of this will happen. At least, overnight, that is.
Many of us writers have unrealistic expectations because of the internet. The Internet makes all sorts of things possible now that wasn’t possible 20 years ago. Yet, the internet can’t force people to read and enjoy your writing.
You have to put in the work. You’ll have to continue working to hone your craft. You’ll have to write quality content (lots of it) that people will want to read.
The internet and social media platforms will help you market your work, but you’ll need actually to utilize those platforms intelligently.
I’ve Adopted A Slow And Steady Approach To Writing
I’ve had my blog for over a year and a half now. I’ve had my highs and lows. I’ve had to work tirelessly to build up my following, which is up to almost 4,000 people now.
When I first started blogging, I didn’t know the first thing about writing quality content. I didn’t realize that websites like Unsplash and Pixabay existed. Hell, there were countless things I didn’t know in the beginning, but I wish I did.
Here’s a little secret about me. I’m an active Type A personality by nature. I tend to want everything to happen quickly. Like right this very second! But I’ve learned to adopt a slow and steady approach to writing.
I read, research, write, edit, publish, coach others, and improve a little each day. Rinse and repeat — day after day.
I can tell you without the shadow of a doubt that writing is a tough business, and I’ve seen countless bloggers come and go. There were several times where I also wanted to quit. I wanted to walk away from it all. Because of how difficult it was to find the type of success I was looking for.
People get fed up when they spend hours writing a story, and it flops. I get it. It’s infuriating. Confusing. Depressing. All of the above. Welcome to the world of being a writer. It’s an emotional roller coaster, and it’s a ride that not everyone can handle being on.
A helpful Youtube video for all aspiring writers.
Why Do You Want To Be A Writer?
You have to have a profound reason why. Why do you want to be a writer? What are your goals? Where do you see yourself five years from now as you continue down your writing path?
I’m a firm believer that if your intentions are pure, you’ll find a way to achieve your goals. If you want your writing to provide your readers with value, then people will gravitate towards your content. When you want your writing to make a difference in other people’s lives, it’ll be evident your heart is in the right place.
On the flip side, if you’re writing to earn a quick, easy buck, you’ll find out rather fast that you’re in the wrong line of work. If you’re here to shove your writing in other people’s faces demanding they read your masterpiece, then I’m sorry, most people probably won’t want to read it. People can sense when a piece of writing isn’t genuine or when it’s forced.
Readers can also tell when a writer half-assed a piece of content to make a quick buck. Don’t be that guy/girl. Pretty soon, you’ll develop a reputation, and it won’t be one that will do you any favors.
Be patient. Keep working hard to improve your writing skills. And enjoy the journey. It’s a phenomenal time to be a writer. Just don’t expect to get rich quick or be an overnight success. | https://medium.com/the-partnered-pen/writing-isnt-a-get-rich-quick-scheme-12984d251910 | ['Brian Kurian'] | 2019-11-19 02:20:00.770000+00:00 | ['Life Lessons', 'Writing', 'Creativity', 'Short Story', 'Inspiration'] | Title Writing Isn’t GetRichQuick SchemeContent Writing isn’t getrichquick scheme Chances won’t publish single piece content earn million dollar know many u think publish novel we’ve working write one fantastic blog post sure go viral we’ll set life Thousands follower ton royalty adoration fame travel world whole kitncaboodle Right Wrong I’m sorry burst bubble it’s highly unlikely happen least overnight Many u writer unrealistic expectation internet Internet make sort thing possible wasn’t possible 20 year ago Yet internet can’t force people read enjoy writing put work You’ll continue working hone craft You’ll write quality content lot people want read internet social medium platform help market work you’ll need actually utilize platform intelligently I’ve Adopted Slow Steady Approach Writing I’ve blog year half I’ve high low I’ve work tirelessly build following almost 4000 people first started blogging didn’t know first thing writing quality content didn’t realize website like Unsplash Pixabay existed Hell countless thing didn’t know beginning wish Here’s little secret I’m active Type personality nature tend want everything happen quickly Like right second I’ve learned adopt slow steady approach writing read research write edit publish coach others improve little day Rinse repeat — day day tell without shadow doubt writing tough business I’ve seen countless blogger come go several time also wanted quit wanted walk away difficult find type success looking People get fed spend hour writing story flop get It’s infuriating Confusing Depressing Welcome world writer It’s emotional roller coaster it’s ride everyone handle helpful Youtube video aspiring writer Want Writer profound reason want writer goal see five year continue writing path I’m firm believer intention pure you’ll find way achieve goal want writing provide reader value people gravitate towards content want writing make difference people’s life it’ll evident heart right place flip side you’re writing earn quick easy buck you’ll find rather fast you’re wrong line work you’re shove writing people’s face demanding read masterpiece I’m sorry people probably won’t want read People sense piece writing isn’t genuine it’s forced Readers also tell writer halfassed piece content make quick buck Don’t guygirl Pretty soon you’ll develop reputation won’t one favor patient Keep working hard improve writing skill enjoy journey It’s phenomenal time writer don’t expect get rich quick overnight successTags Life Lessons Writing Creativity Short Story Inspiration |
961 | Deploy a Python API on AWS | Deploy a Python API on AWS
Flask + Lambda + API Gateway
The very first idea of creating my own app and deploying it on the cloud so that everyone could use it is super exciting to me, and this is what inspired me to write this post. If this idea also intrigues you, please follow through and from this post, you will learn how to deploy a python app step by step.
Firstly, you need an app
You will need to wrap your idea in an app, or say an API, which can process calls from the internet. An example is here. This is a flask app,
where the key lies in the app.py file, and this app receives your resume and help refer you internally. Notice that we don’t even need a docker file, the AWS Lambda is so light-weighted that you don’t even need to wrap your code in a container!
Secondly, download Zappa
Zappa, a quote from the official docs, it
makes it super easy to build and deploy server-less, event-driven Python applications (including, but not limited to, WSGI web apps) on AWS Lambda + API Gateway. Think of it as “serverless” web hosting for your Python apps. That means infinite scaling, zero downtime, zero maintenance — and at a fraction of the cost of your current deployments!
If you’ve been using AWS service for a while, you would know that to deploy a service on the cloud with the usage of multiple different services and configurations is no easy task, but Zappa comes to the rescue, that with simple commands(trust me, it’s really just a few lines!), all the heavy lifting configurations would be done!
pip install zappa
BTW, I assume you have all the packages installed in the project virtual environment, if not, do
virtualenv -p `which python3` env
(you need to have virtualenv pre-installed)
Now do
zappa init
Go through the settings one by one, if you don’t understand just use the default, and you will still be able to change it afterwards. After this, you would have a zappa_setting.json in your root folder, mine looks like this
{
"production": {
"app_function": "app.app",
"aws_region": "ap-southeast-1",
"profile_name": "default",
"project_name": "referral-api",
"runtime": "python3.7",
"s3_bucket": "zappa-referral-api-eu2hzy8sf"
}
}
Thirdly, give Zappa access to your AWS
Now you need to go to your AWS console, but wait, you said Zappa would do all the AWS work for us? Yes, but think it this way, before Zappa could make any changes on your behalf, it needs access to you AWS resources, and this step is to give Zappa the credential to do such thing.
You can follow the steps here deploy-serverless-app (trust me, this one is really an illustrative guide through with all the images you need).
For the policy attached to the group, use this one! (The one in the link above does not enable you to update your app)
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"iam:AttachRolePolicy",
"iam:GetRole",
"iam:CreateRole",
"iam:PassRole",
"iam:PutRolePolicy"
],
"Resource": [
"arn:aws:iam::XXXXXXXXXXXXXXXX:role/*-ZappaLambdaExecutionRole"
]
},
{
"Effect": "Allow",
"Action": [
"lambda:CreateFunction",
"lambda:ListVersionsByFunction",
"logs:DescribeLogStreams",
"events:PutRule",
"lambda:GetFunctionConfiguration",
"cloudformation:DescribeStackResource",
"apigateway:DELETE",
"apigateway:UpdateRestApiPolicy",
"events:ListRuleNamesByTarget",
"apigateway:PATCH",
"events:ListRules",
"cloudformation:UpdateStack",
"lambda:DeleteFunction",
"events:RemoveTargets",
"logs:FilterLogEvents",
"apigateway:GET",
"lambda:GetAlias",
"events:ListTargetsByRule",
"cloudformation:ListStackResources",
"events:DescribeRule",
"logs:DeleteLogGroup",
"apigateway:PUT",
"lambda:InvokeFunction",
"lambda:GetFunction",
"lambda:UpdateFunctionConfiguration",
"cloudformation:DescribeStacks",
"lambda:UpdateFunctionCode",
"lambda:DeleteFunctionConcurrency",
"events:DeleteRule",
"events:PutTargets",
"lambda:AddPermission",
"cloudformation:CreateStack",
"cloudformation:DeleteStack",
"apigateway:POST",
"lambda:RemovePermission",
"lambda:GetPolicy"
],
"Resource": "*"
},
{
"Effect": "Allow",
"Action": [
"s3:ListBucketMultipartUploads",
"s3:CreateBucket",
"s3:ListBucket"
],
"Resource": "arn:aws:s3:::zappa-*"
},
{
"Effect": "Allow",
"Action": [
"s3:PutObject",
"s3:GetObject",
"s3:AbortMultipartUpload",
"s3:DeleteObject",
"s3:ListMultipartUploadParts"
],
"Resource": "arn:aws:s3:::zappa-*/*"
}
]
}
Now you add the credentials you created for Zappa to your local file (credentials and configs), mine looks like this
[default]
aws_access_key_id = ****
aws_secret_access_key = **** [zappa]
aws_access_key_id = ****
aws_secret_access_key = ****
and config like this
[default]
region = ap-southeast-1
output = json [zappa]
region = ap-southeast-1
output = json
I created one especially for Zappa, because I believe most of us would have a default credential for ourself, this setting would allow you to switch between different profiles.
Now it is ready to deploy!
export AWS_DEFAULT_PROFILE=zappa
zappa deploy production
You would see your API url right after the command line. Now go to your AWS Lambda you should see our API deployed:
And in API Gateway you can see:
Now that I can test the public endpoint on postman and get a response:
Congrats! Now you have your app fully deployed to AWS with Lambda and API Gateway!
You can stop here if this already satisfies your need, but if you would like to distribute your API and add restrictions for it, you can continue to the next part.
Extra1: Add Key to API
You might have noticed that so far our API is publicly accessible, which means anyone can access our API and it is susceptible to malicious attack. To avoid such undesired visits, we need to add extra limitations on our API usage (Usage Plan) and credentials (x-api-key) to restrict visits.
To add a key to your API, follow the steps here.
Extra2: Distribute your API through RapidAPI
RapidAPI is where for everyone to freely open and sell their API to the world as long as someone is willing to pay for it.
Go to RapidAPI and click Add New API Fill in the basic info of your API For the URL of your API, paste the AWS url we previous got after deploying though Zappa In the access control add your api key as follow
5. Add a pricing plan and you are ready to launch it to the public!
Lastly, if you are interested, you can check out my referral API. If you are looking for a new career, so far it helps you to refer you to the company of Bytedance and Grab through the internal portal.
This is post is initially inspired by this, a great post helped me to start the plan, feel free to check that out! | https://towardsdatascience.com/deploy-a-python-api-on-aws-c8227b3799f0 | ['Jeremy Zhang'] | 2020-09-19 17:20:55.170000+00:00 | ['Flask', 'Python', 'AWS', 'API'] | Title Deploy Python API AWSContent Deploy Python API AWS Flask Lambda API Gateway first idea creating app deploying cloud everyone could use super exciting inspired write post idea also intrigue please follow post learn deploy python app step step Firstly need app need wrap idea app say API process call internet example flask app key lie apppy file app receives resume help refer internally Notice don’t even need docker file AWS Lambda lightweighted don’t even need wrap code container Secondly download Zappa Zappa quote official doc make super easy build deploy serverless eventdriven Python application including limited WSGI web apps AWS Lambda API Gateway Think “serverless” web hosting Python apps mean infinite scaling zero downtime zero maintenance — fraction cost current deployment you’ve using AWS service would know deploy service cloud usage multiple different service configuration easy task Zappa come rescue simple commandstrust it’s really line heavy lifting configuration would done pip install zappa BTW assume package installed project virtual environment virtualenv p python3 env need virtualenv preinstalled zappa init Go setting one one don’t understand use default still able change afterwards would zappasettingjson root folder mine look like production appfunction appapp awsregion apsoutheast1 profilename default projectname referralapi runtime python37 s3bucket zappareferralapieu2hzy8sf Thirdly give Zappa access AWS need go AWS console wait said Zappa would AWS work u Yes think way Zappa could make change behalf need access AWS resource step give Zappa credential thing follow step deployserverlessapp trust one really illustrative guide image need policy attached group use one one link enable update app Version 20121017 Statement Effect Allow Action iamAttachRolePolicy iamGetRole iamCreateRole iamPassRole iamPutRolePolicy Resource arnawsiamXXXXXXXXXXXXXXXXroleZappaLambdaExecutionRole Effect Allow Action lambdaCreateFunction lambdaListVersionsByFunction logsDescribeLogStreams eventsPutRule lambdaGetFunctionConfiguration cloudformationDescribeStackResource apigatewayDELETE apigatewayUpdateRestApiPolicy eventsListRuleNamesByTarget apigatewayPATCH eventsListRules cloudformationUpdateStack lambdaDeleteFunction eventsRemoveTargets logsFilterLogEvents apigatewayGET lambdaGetAlias eventsListTargetsByRule cloudformationListStackResources eventsDescribeRule logsDeleteLogGroup apigatewayPUT lambdaInvokeFunction lambdaGetFunction lambdaUpdateFunctionConfiguration cloudformationDescribeStacks lambdaUpdateFunctionCode lambdaDeleteFunctionConcurrency eventsDeleteRule eventsPutTargets lambdaAddPermission cloudformationCreateStack cloudformationDeleteStack apigatewayPOST lambdaRemovePermission lambdaGetPolicy Resource Effect Allow Action s3ListBucketMultipartUploads s3CreateBucket s3ListBucket Resource arnawss3zappa Effect Allow Action s3PutObject s3GetObject s3AbortMultipartUpload s3DeleteObject s3ListMultipartUploadParts Resource arnawss3zappa add credential created Zappa local file credential configs mine look like default awsaccesskeyid awssecretaccesskey zappa awsaccesskeyid awssecretaccesskey config like default region apsoutheast1 output json zappa region apsoutheast1 output json created one especially Zappa believe u would default credential ourself setting would allow switch different profile ready deploy export AWSDEFAULTPROFILEzappa zappa deploy production would see API url right command line go AWS Lambda see API deployed API Gateway see test public endpoint postman get response Congrats app fully deployed AWS Lambda API Gateway stop already satisfies need would like distribute API add restriction continue next part Extra1 Add Key API might noticed far API publicly accessible mean anyone access API susceptible malicious attack avoid undesired visit need add extra limitation API usage Usage Plan credential xapikey restrict visit add key API follow step Extra2 Distribute API RapidAPI RapidAPI everyone freely open sell API world long someone willing pay Go RapidAPI click Add New API Fill basic info API URL API paste AWS url previous got deploying though Zappa access control add api key follow 5 Add pricing plan ready launch public Lastly interested check referral API looking new career far help refer company Bytedance Grab internal portal post initially inspired great post helped start plan feel free check outTags Flask Python AWS API |
962 | Climate Change Might Be A Threat to Wind Power | To combat climate change, reduce air pollution, and establish greater energy independence, China has been pushing hard for a nation-wide transition to renewable energy, and is now home to the world’s largest market for wind-generated electricity. The installed capacity for wind generation in China accounts for over one third of the global total. Yet a paper recently published in Nature Scientific Reports and covered by the Washington Post found that climate change might be threatening wind power — one of the very strategies that countries are relying on to help them achieve the goal set forth in the Paris Agreement of keeping global temperature rise below 2 degrees Celsius.
Tiffany Chan from the Harvard-China Project sat down with one of the co-authors of the paper, Ph.D. student Peter Sherman, to discuss his team’s findings. Their discussion was also translated into Chinese.
Peter, you had a paper that was published in Nature Scientific Reports. Can you tell us more about the paper? What is the topic of investigation?
Under the supervision of Professor [Mike] McElroy and Xinyu [Chen], we looked at wind variability in China over the past 37 years from 1979 to 2015. We used a NASA dataset, which combines model data with observations from stations, to see how wind has varied over these years and how it could affect wind power.
What did you find? What are the results?
We found that there is a declining trend in wind speed over the past 37 years, particularly over the regions where a lot of wind farms in China already exist, mainly Western Inner Mongolia and northern China, where there are not only high wind speeds, but also environments that are suitable for installing wind turbines — so regions with the proper geographical features. We found a decrease in wind speed in these regions and it correlates really strongly with rising regional and global surface temperatures, which makes physical sense. We conclude that because there were these rising surface temperatures and decreasing wind speed trend, climate change probably had a pretty significant contribution to the decreasing trend and it could continue in the future.
Can you explain to us briefly how rising surface temperatures affect wind speed?
Basically, winds are formed by pressure differences. If there is high pressure in one area and low pressure in another, it’s going to form wind. A lot of this is due to the temperature difference between land and sea. If temperatures are increasing over land more than they are over sea, then we would expect this temperature difference to shrink and wind speed to decrease along with that. That’s what we think we are seeing here.
How do you think your finding might affect the planning of wind installations and the energy transition in China?
I don’t think it should affect the planning. While these decreases in wind speed may be happening, wind power is still very important and should become a more dominant source of energy in the future, because coal, we know, is not good for the environment. So while there may be decreasing potential for wind power, it’s still very useful. An area of concern that China has is wind curtailment. Wind power is a variable source; when it’s really windy and we don’t use all the wind power, we don’t have any way of storing that wind, so it’s being wasted. What China, in particular, needs to work on is to develop some kind of storage, like a battery, in order to be able to store the extra wind power that is not being used.
A map of the percentage change in wind power in China over 37 years — from 1979 to 2015. The legend ranges from +30% increase (red) to -30% decrease in wind power (blue). Some areas in the map are left blank because they are identified as unsuitable or uneconomic for installations of wind turbines, e.g. urban areas, forests, etc.
Are the results what you expected? Is there anything surprising?
There have been some other papers in the past that have talked about the decreasing wind potential in China, but we were particularly surprised by how strong the decrease was for these areas where there is great potential for wind — the greatest declines were actually in those areas, so that was pretty surprising for us.
Are there any future questions that your research raised?
What we are planning on doing now is we are going to look at climate models that project how wind speeds are going to change in the future to see if those models also demonstrate this declining wind speed trend and if that could affect wind power in China.
For some of our readers who might know little about this topic but are very concerned about the environment and climate change in general, especially with all these ongoing discussions about energy transition that is necessary to combat climate change, what is the one thing you want them to take away from this paper?
That climate change has broad implications for the energy system as a whole. Wind power is obviously an important step going forward in terms of what we should do to protect the environment, and yet even something like this is affected by climate change. It is important to bear this in mind in the future.
How did you get involved in this research?
In the winter of my junior year in college, I was looking for research projects to do over the summer. I looked up on Google the various professors who do research that I am interested in. I found Prof. [Mike] McElroy and reached out to him. He offered me a research assistant position with the Harvard-China Project over the summer, and I was really interested in it, so I took it right away. It worked out very well. That’s also how I met Xinyu [Chen], who was a postdoc at the China Project.
How do you find the transition from being a research assistant at Harvard-China Project to being a Ph.D. student at Harvard? What made you decide to come to Harvard to get a Ph.D.?
I found the transition very easy: it was basically doing the same sort work that I was doing over the summer. I have always planned on going to Harvard, and I think my work with Mike and Xinyu really confirmed that. It made me realize how collaborative the environment is here; everyone is willing to help with your work and talk to you — I was really surprised by that. When I was applying for graduate schools, there were a few other options I had, but I just felt that the environment here was so collaborative and helpful that I felt it was perfect for me.
Paper cited:
Peter Sherman, Xinyu Chen, and Michael B. McElroy. 2017. “Wind-generated electricity in China: Decreasing potential, inter-annual variability, and association with climate change.” Scientific Reports 7.
Peter Sherman is currently pursuing his Ph.D. degree in Earth and Planetary Sciences at Harvard University. He received his undergraduate degree in physics from Imperial College London, U.K.. He is interested in a variety of topics, particularly green technology and how weather might affect it, and climate models in general. | https://medium.com/harvard-china-project/climate-change-might-be-a-threat-to-wind-power-f17233f4a616 | ['Harvard-China Project On Energy', 'Econ'] | 2019-01-13 17:20:59.875000+00:00 | ['China', 'Environment', 'Climate Change', 'Wind Energy', 'Renewable Energy'] | Title Climate Change Might Threat Wind PowerContent combat climate change reduce air pollution establish greater energy independence China pushing hard nationwide transition renewable energy home world’s largest market windgenerated electricity installed capacity wind generation China account one third global total Yet paper recently published Nature Scientific Reports covered Washington Post found climate change might threatening wind power — one strategy country relying help achieve goal set forth Paris Agreement keeping global temperature rise 2 degree Celsius Tiffany Chan HarvardChina Project sat one coauthor paper PhD student Peter Sherman discus team’s finding discussion also translated Chinese Peter paper published Nature Scientific Reports tell u paper topic investigation supervision Professor Mike McElroy Xinyu Chen looked wind variability China past 37 year 1979 2015 used NASA dataset combine model data observation station see wind varied year could affect wind power find result found declining trend wind speed past 37 year particularly region lot wind farm China already exist mainly Western Inner Mongolia northern China high wind speed also environment suitable installing wind turbine — region proper geographical feature found decrease wind speed region correlate really strongly rising regional global surface temperature make physical sense conclude rising surface temperature decreasing wind speed trend climate change probably pretty significant contribution decreasing trend could continue future explain u briefly rising surface temperature affect wind speed Basically wind formed pressure difference high pressure one area low pressure another it’s going form wind lot due temperature difference land sea temperature increasing land sea would expect temperature difference shrink wind speed decrease along That’s think seeing think finding might affect planning wind installation energy transition China don’t think affect planning decrease wind speed may happening wind power still important become dominant source energy future coal know good environment may decreasing potential wind power it’s still useful area concern China wind curtailment Wind power variable source it’s really windy don’t use wind power don’t way storing wind it’s wasted China particular need work develop kind storage like battery order able store extra wind power used map percentage change wind power China 37 year — 1979 2015 legend range 30 increase red 30 decrease wind power blue area map left blank identified unsuitable uneconomic installation wind turbine eg urban area forest etc result expected anything surprising paper past talked decreasing wind potential China particularly surprised strong decrease area great potential wind — greatest decline actually area pretty surprising u future question research raised planning going look climate model project wind speed going change future see model also demonstrate declining wind speed trend could affect wind power China reader might know little topic concerned environment climate change general especially ongoing discussion energy transition necessary combat climate change one thing want take away paper climate change broad implication energy system whole Wind power obviously important step going forward term protect environment yet even something like affected climate change important bear mind future get involved research winter junior year college looking research project summer looked Google various professor research interested found Prof Mike McElroy reached offered research assistant position HarvardChina Project summer really interested took right away worked well That’s also met Xinyu Chen postdoc China Project find transition research assistant HarvardChina Project PhD student Harvard made decide come Harvard get PhD found transition easy basically sort work summer always planned going Harvard think work Mike Xinyu really confirmed made realize collaborative environment everyone willing help work talk — really surprised applying graduate school option felt environment collaborative helpful felt perfect Paper cited Peter Sherman Xinyu Chen Michael B McElroy 2017 “Windgenerated electricity China Decreasing potential interannual variability association climate change” Scientific Reports 7 Peter Sherman currently pursuing PhD degree Earth Planetary Sciences Harvard University received undergraduate degree physic Imperial College London UK interested variety topic particularly green technology weather might affect climate model generalTags China Environment Climate Change Wind Energy Renewable Energy |
963 | Display Rich Text In The Console Using Python | Are you using the terminal more than GUI-based operating systems? Or, do you usually develop command-line interface programs using Python? Recently, I found an amazing Python library called “Rich” on GitHub, which already has 15.2k stars by the time I’m writing this article.
It can not only display text in colour and styles in the terminal but also emoji, tables, progress bars, markdown and even syntax highlighted code. If you have read one of my previous articles below:
The “Rich” library can almost do everything that I have introduced in that article, as well as some other awesome stuff.
In this article, I’ll introduce this library with examples to show its capabilities.
Introduction & Installation
Image source: https://github.com/willmcgugan/rich (Official GitHub README.md)
The image above shows the major features that the library can do. You can find the project on GitHub:
The library requires Python 3.6.1 or above to be functional. Installing the library is quite simple because we can use pip .
pip install rich
Rich Printing
Let’s first look at how it can print.
Tags and Emoji
It supports formatting tags and emoji. | https://towardsdatascience.com/get-rich-using-python-af66176ece8f | ['Christopher Tao'] | 2020-11-30 16:09:28.681000+00:00 | ['Technology', 'Software Engineering', 'Artificial Intelligence', 'Software Development', 'Programming'] | Title Display Rich Text Console Using PythonContent using terminal GUIbased operating system usually develop commandline interface program using Python Recently found amazing Python library called “Rich” GitHub already 152k star time I’m writing article display text colour style terminal also emoji table progress bar markdown even syntax highlighted code read one previous article “Rich” library almost everything introduced article well awesome stuff article I’ll introduce library example show capability Introduction Installation Image source httpsgithubcomwillmcguganrich Official GitHub READMEmd image show major feature library find project GitHub library requires Python 361 functional Installing library quite simple use pip pip install rich Rich Printing Let’s first look print Tags Emoji support formatting tag emojiTags Technology Software Engineering Artificial Intelligence Software Development Programming |
964 | Applying Deep Learning To Airbnb Search | Presumably all such challenges can be overcome by accumulating sufficient amounts of data. But the Airbnb inventory has an additional twist. Each listing can be booked only once for a night. As soon as the listing is booked, it becomes unavailable for any subsequent search for that night, so no further data accrues for it. This makes the data per listing very sparse. The plot below shows the normalized distribution of impressions per listing, and the long tail nature of the data available.
Consequently, the solution to the ranking problem demands broad generalization from a few examples, memorizing the top results in this case is of little use.
The task of deciphering guest preference has an equally fascinating side. We get to see the guests when they are planning their trips, which is not everyday for most. But once they arrive, the guests engage heavily with search and usually have very specific preferences and budgets. One guest may end up booking a bargain private room, while another a lavish penthouse, but both may start by searching for a place for 2 in Rome. To effectively personalize the search experience, we need to process a huge volume of data in realtime.
The large number of dimensions and the relative sparsity of data on both guest and host side creates the perfect storm where quite a few of the known optimization techniques break down.
So how do we address all these challenges? The tl;dr version of the answer is: neural networks. But how we reached there and how we continue to evolve is a tale with twists and turns. Celebrating the culture of sharing, in a first ever in-depth look at Airbnb search ranking, we have published a paper that describes our journey to deep neural networks.
Access the Paper
Applying Deep Learning To Airbnb Search, pdf 8 pages, published in arXiv, Oct 2018.
We hope the story of our setbacks and triumphs provides insights useful to other teams facing similar challenges. We always welcome ideas from our readers. For those interested in hands on action, please check out the open positions for engineers and data scientists on the search team. | https://medium.com/airbnb-engineering/applying-deep-learning-to-airbnb-search-7ebd7230891f | ['Malay Haldar'] | 2018-11-06 18:05:29.037000+00:00 | ['Machine Learning', 'Artificial Intelligence', 'AI', 'Data Science', 'Deep Learning'] | Title Applying Deep Learning Airbnb SearchContent Presumably challenge overcome accumulating sufficient amount data Airbnb inventory additional twist listing booked night soon listing booked becomes unavailable subsequent search night data accrues make data per listing sparse plot show normalized distribution impression per listing long tail nature data available Consequently solution ranking problem demand broad generalization example memorizing top result case little use task deciphering guest preference equally fascinating side get see guest planning trip everyday arrive guest engage heavily search usually specific preference budget One guest may end booking bargain private room another lavish penthouse may start searching place 2 Rome effectively personalize search experience need process huge volume data realtime large number dimension relative sparsity data guest host side creates perfect storm quite known optimization technique break address challenge tldr version answer neural network reached continue evolve tale twist turn Celebrating culture sharing first ever indepth look Airbnb search ranking published paper describes journey deep neural network Access Paper Applying Deep Learning Airbnb Search pdf 8 page published arXiv Oct 2018 hope story setback triumph provides insight useful team facing similar challenge always welcome idea reader interested hand action please check open position engineer data scientist search teamTags Machine Learning Artificial Intelligence AI Data Science Deep Learning |
965 | A Guide to Logistic Regression in SAS | A Guide to Logistic Regression in SAS
Let’s explore a simple way to analyze a model by using SAS.
What is logistic regression?
Logistic regression is a supervised machine learning classification algorithm that is used to predict the probability of a categorical dependent variable. The dependent variable is a binary variable that contains data coded as 1 (yes/true) or 0 (no/false), used as Binary classifier (not in regression). Logistic regression can make use of large numbers of features including continuous and discrete variables and non-linear features. In Logistic Regression, the Sigmoid (aka Logistic) Function is used.
We want a model that predicts probabilities between 0 and 1, that is, S-shaped. There are lots of S-shaped curves. We use the logistic model: Probability = 1 / [1 +exp (B0 + b1X)] or loge[P/(1-P)] = B0 +B1X. The function on left, loge[P/(1-P)], is called the logistic function.
Building a Logistic Model by using SAS Enterprise Guide
I am using Titanic dataset from Kaggle.com which contains a training and test dataset. Here, we will try to predict the classification — Survived or deceased. Our target variable is ‘survived’. I am using SAS Enterprise guide to analyze this dataset. SAS gives a lot of output, so I posted just a relevant portion for our analysis.
Setting the library path and importing the dataset using proc import /* Setting the library path */ %let path=C:\dev\projects\SAS\PRACDATA; libname PRAC “&path”; /* Importing dataset using proc import */ proc import datafile = “C:/dev/projects/sas/pracdata/train.csv” out = PRAC.titanic dbms = CSV; run; Checking the contents of the dataset by using proc contents function /* Checking the contents of the data*/ proc contents data=work.train; run;
We have 12 variables. Our target variable is ‘Survived’ which has 1 and 0. 1 for survived and 0 for not survived. Category variables: Cabin, sex, Pclass. Numeric Variables: Passenger ID, SibSp, Parch, Survived, Age and Fare. Text variable: Ticket and Name
Checking the frequency of the target variable ‘Survived’ by using proc frequency
/* Checking the frequency of the Target Variable Survived */
proc freq data=work.train;
table Survived;
run;
We can clearly see that 342 people were survived and 549 people are not survived. A total number of observations = 891.
Data Visualization
Normally, it is good practice to research with the data by using visualization. I am using proc sgplot to visualize the class, Embark .
title "Analysis of embarkation locations"; proc sgplot data=prac.titanic;
vbar Embarked / datalabel missing; label Embarked = "Passenger Embarking Port"; run;
Nothing unusual can be seen in value distributions. Let’s analyze survived the rate with other variables.
title "Survived vs Gender"; proc sgplot data=prac.titanic pctlevel=group; vbar sex / group=Survived stat=percent missing; label Embarked = "Passenger Embarking Port"; run;
Here, we see a trend that more females survived than males. People traveled in class 3 died the most. Still, there are many ways to visualize the data. I am not going into detail.
Checking the missing values by using proc means
/* Checking the missing value and Statistics of the dataset */ proc means data=work.train N Nmiss mean std min P1 P5 P10 P25 P50 P75 P90 P95 P99 max; run;
We can see that Age has 177 missing values and no outliers detected.
Checking for categorical variables: title “Frequency tables for categorical variables in the training set”; proc freq data=PRAC.TITANIC nlevels; tables Survived; tables Sex; tables Pclass; tables SibSp; tables Parch; tables Embarked; tables Cabin; run;
We have missing value in Age, Embarked and Cabin. We need to fill all missing age instead of dropping the missing rows. One way to filling by using mean age. However, we can check the average age by passenger class using a box plot. In SAS, we need to sort it out of the class and age variable before making it a box plot.
/* Sorting out the Pclass and Age for creating boxplot */ proc sort data=work.train out=sorted; by Pclass descending Age; run; title ‘Box Plot for Age vs Class’; proc boxplot data=sorted; plot Age*Pclass; run;
We can see the wealthier passengers in the higher classes tend to be older, which makes sense. We’ll use these average age values to impute based on Pclass for Age.
/* Imputing Mean value for the age column */ data work.train2; set work.train; if age=”.” and Pclass = 1 then age = 37; else if age = “.” and Pclass = 2 then age = 29; else if age = “.” and Pclass = 3 then age = 24; run;
I have dropped the cabin variable as I don’t see it is going to impact our model, and filled the missing value in ‘embarked’ using the median. (Selected median due to category variable).
Data Partition
Splitting the dataset into training and validation by using the 70:30 ratio. First, I need to sort out the data using proc sort and splitting by using proc surveyselect .
/* Splitting the dataset into traning and validation using 70:30 ratio */ proc sort data = prac.train6 out = train_sorted; by Survived; run; proc surveyselect data = train_sorted out = train_survey outall samprate = 0.7 seed = 12345; strata Survived; run;
In order to verify the correct data partition, I am generating a frequency table by using proc freq .
/* Generating frequency table */ proc freq data = train_survey; tables Selected*Survived; run;
The Selected variable with the value of 1 will our target observation of the training part. Let us also perform quick set processing in order to leave only the columns that are interesting for us and name variables properly.
Building Model
We filled all our missing values and our dataset is ready for building a model. I am now creating a logistic regression model by using proc logistic . Logistic regression is perfect for building a model for a binary variable. In our case, the target variable is survived.
/* Creating Logistic regression model */ proc logistic data=titanic descending; where part=1; class Embarked Parch Pclass Sex SibSp Survived; model Survived(event=’1') = Age Fare Embarked Parch Pclass Sex SibSp / selection=stepwise expb stb lackfit; output out = temp p=new; store titanic_logistic; run;
One of the beauties in SAS is that for categorical variables in logistic regression, we don’t need to create a dummy variable. Here we are able to declare all of our category variables in a class.
The variable selection algorithm decided that the model will include Age, Pclass and Sex variables.
Good=1 is approximate both for the training set (Part=1) and validation set (Part=0). It amounts to 82.56% and 80.08% for the training and validation sets respectively. It is a stable model, however, if we see the Hosmer test the p-value is less. As per the book, higher, the p-value better the model fit.
If we can see the Concordant pairs, it is 86.6 %. Concordance is used to assess how well scorecards are separating the good and bad accounts in the development sample. The higher is the concordance, the larger is the separation of scores between good and bad accounts.
Testing test dataset
We can test our training model by using test dataset. It’s the same procedure for the importing test dataset in SAS by using Proc import and impute all the missing values.
Testing the test dataset by using our model
/* Testing with our model titanic_logisitic */ proc plm source=titanic_logistic; score data=test1 out=test_scored predicted=p / ilink; run;
Now we export the result into CSV file by using proc export. I separated the survived rate by using probability 0.5 and keeping only PassengerId and Survived variable in the result.
data test_scored; set test_scored; if p > 0.5 then Survived = 1; else Survived = 0; keep PassengerId Survived; run; /* Exporting the output into csv file */ proc export data=test_scored file=”C:/dev/projects/sas/pracdata/Result.csv” replace; run; Note:
Only three variables were used in the model (age, class, and sex) and the result was 74.64 %. This is not a bad model; however, we have a large scope to improve the model by using other variables.
What’s next
In my next article, I will try to use other variables and improve the model. Also, we can apply other algorithms like decision tree, random forest to check the accuracy level. I will try to post in my next blog.
If you find any mistakes or improvement required, please feel free to comment.
Reference:
1) https://support.sas.com/en/documentation.html
2) https://en.wikipedia.org/wiki/Logistic_regression
3) https://www.kaggle.com/c/titanic | https://medium.com/hackernoon/logistic-regression-using-sas-enterprise-guide-3ffb7774f765 | ['Dhilip Subramanian'] | 2019-05-17 05:10:20.730000+00:00 | ['Machine Learning', 'Technology', 'Python', 'AI', 'Data Science'] | Title Guide Logistic Regression SASContent Guide Logistic Regression SAS Let’s explore simple way analyze model using SAS logistic regression Logistic regression supervised machine learning classification algorithm used predict probability categorical dependent variable dependent variable binary variable contains data coded 1 yestrue 0 nofalse used Binary classifier regression Logistic regression make use large number feature including continuous discrete variable nonlinear feature Logistic Regression Sigmoid aka Logistic Function used want model predicts probability 0 1 Sshaped lot Sshaped curve use logistic model Probability 1 1 exp B0 b1X logeP1P B0 B1X function left logeP1P called logistic function Building Logistic Model using SAS Enterprise Guide using Titanic dataset Kagglecom contains training test dataset try predict classification — Survived deceased target variable ‘survived’ using SAS Enterprise guide analyze dataset SAS give lot output posted relevant portion analysis Setting library path importing dataset using proc import Setting library path let pathCdevprojectsSASPRACDATA libname PRAC “path” Importing dataset using proc import proc import datafile “Cdevprojectssaspracdatatraincsv” PRACtitanic dbms CSV run Checking content dataset using proc content function Checking content data proc content dataworktrain run 12 variable target variable ‘Survived’ 1 0 1 survived 0 survived Category variable Cabin sex Pclass Numeric Variables Passenger ID SibSp Parch Survived Age Fare Text variable Ticket Name Checking frequency target variable ‘Survived’ using proc frequency Checking frequency Target Variable Survived proc freq dataworktrain table Survived run clearly see 342 people survived 549 people survived total number observation 891 Data Visualization Normally good practice research data using visualization using proc sgplot visualize class Embark title Analysis embarkation location proc sgplot datapractitanic vbar Embarked datalabel missing label Embarked Passenger Embarking Port run Nothing unusual seen value distribution Let’s analyze survived rate variable title Survived v Gender proc sgplot datapractitanic pctlevelgroup vbar sex groupSurvived statpercent missing label Embarked Passenger Embarking Port run see trend female survived male People traveled class 3 died Still many way visualize data going detail Checking missing value using proc mean Checking missing value Statistics dataset proc mean dataworktrain N Nmiss mean std min P1 P5 P10 P25 P50 P75 P90 P95 P99 max run see Age 177 missing value outlier detected Checking categorical variable title “Frequency table categorical variable training set” proc freq dataPRACTITANIC nlevels table Survived table Sex table Pclass table SibSp table Parch table Embarked table Cabin run missing value Age Embarked Cabin need fill missing age instead dropping missing row One way filling using mean age However check average age passenger class using box plot SAS need sort class age variable making box plot Sorting Pclass Age creating boxplot proc sort dataworktrain outsorted Pclass descending Age run title ‘Box Plot Age v Class’ proc boxplot datasorted plot AgePclass run see wealthier passenger higher class tend older make sense We’ll use average age value impute based Pclass Age Imputing Mean value age column data worktrain2 set worktrain age”” Pclass 1 age 37 else age “” Pclass 2 age 29 else age “” Pclass 3 age 24 run dropped cabin variable don’t see going impact model filled missing value ‘embarked’ using median Selected median due category variable Data Partition Splitting dataset training validation using 7030 ratio First need sort data using proc sort splitting using proc surveyselect Splitting dataset traning validation using 7030 ratio proc sort data practrain6 trainsorted Survived run proc surveyselect data trainsorted trainsurvey outall samprate 07 seed 12345 stratum Survived run order verify correct data partition generating frequency table using proc freq Generating frequency table proc freq data trainsurvey table SelectedSurvived run Selected variable value 1 target observation training part Let u also perform quick set processing order leave column interesting u name variable properly Building Model filled missing value dataset ready building model creating logistic regression model using proc logistic Logistic regression perfect building model binary variable case target variable survived Creating Logistic regression model proc logistic datatitanic descending part1 class Embarked Parch Pclass Sex SibSp Survived model Survivedevent’1 Age Fare Embarked Parch Pclass Sex SibSp selectionstepwise expb stb lackfit output temp pnew store titaniclogistic run One beauty SAS categorical variable logistic regression don’t need create dummy variable able declare category variable class variable selection algorithm decided model include Age Pclass Sex variable Good1 approximate training set Part1 validation set Part0 amount 8256 8008 training validation set respectively stable model however see Hosmer test pvalue le per book higher pvalue better model fit see Concordant pair 866 Concordance used ass well scorecard separating good bad account development sample higher concordance larger separation score good bad account Testing test dataset test training model using test dataset It’s procedure importing test dataset SAS using Proc import impute missing value Testing test dataset using model Testing model titaniclogisitic proc plm sourcetitaniclogistic score datatest1 outtestscored predictedp ilink run export result CSV file using proc export separated survived rate using probability 05 keeping PassengerId Survived variable result data testscored set testscored p 05 Survived 1 else Survived 0 keep PassengerId Survived run Exporting output csv file proc export datatestscored file”CdevprojectssaspracdataResultcsv” replace run Note three variable used model age class sex result 7464 bad model however large scope improve model using variable What’s next next article try use variable improve model Also apply algorithm like decision tree random forest check accuracy level try post next blog find mistake improvement required please feel free comment Reference 1 httpssupportsascomendocumentationhtml 2 httpsenwikipediaorgwikiLogisticregression 3 httpswwwkagglecomctitanicTags Machine Learning Technology Python AI Data Science |
966 | How We Increased Revenue By $100k Every Month | How We Increased Revenue By $100k Every Month
Common Sense Business Practices That Aren’t So Common Anymore
by Shopify Partners from Burst
When my boss approached me to help him run his small business, he had two contracts with total revenue of $365k per year. I had run my own businesses in the past and knew a lot about the industry he operated in. With our shared values about how a business should operate, we had a great foundation for growth.
Fast-forward 16 months, and we’ve grown our small business by $100k per month to revenue of $1.95M. Here’s how we did it.
Don’t Concentrate on the Money
Except for Gary Vaynerchuk, anyone peddling advice these days has their focus in the wrong place. Trying to make a fast buck on any business model is a good way to not make any money, ever.
Before jumping into this small business, I had a pattern of starting and failing (we call it “learning” now) my own businesses. The pattern looked something like this:
Draw up a business plan based on a solid idea
Find a no-cost method to start
Be willing to work day and night
Check my stats and income daily to see where I was at
Slowly watch my business spiral into abject failure
Rinse and repeat
After each venture, the only lesson I recognized was how to fail at things. But when you fail, you learn an important lesson about where it could have gone right because you can see the particular areas where you went wrong. Eventually, I identified these areas, and each business after the previous one lasted longer, was more fulfilling, and made me more money.
My final business was chugging along at a steady pace and was going the distance, but I couldn’t afford to put any sort of infrastructure in place to make it really take off. That’s when I met my boss and decided to fold my company and join him.
When I started, I was shocked to find that the owner (my direct boss who recruited me to be his Number 2) didn’t have a business plan and didn’t know his profit margin (or any bottom-line numbers at all). Yet, he had earned enough to pay me to help him grow his business.
This was an area where I had always gotten it wrong –– the constant need to check my stats and see where I was at. My boss, however, has a way of looking at time and money that would have made all the difference in my own business pattern:
Today is an investment for tomorrow.
It didn’t matter if he didn’t make money, so long as he had enough to invest back into the business, that was all that mattered. The only time we counted anything during those early days was to make sure we were not in the red.
Trust and Reinvest in Your People
That lesson about money and investment-mindedness out of the way, I was ready to deploy my knowledge to help our business grow. When it came to the operations of a company, I had that part down. And the best part: my boss was willing to take chances on my ideas. It was why he hired me, after all.
In my first three months, we added a $93,000 contract to our portfolio. It was a big jump for us, to be sure, adding almost 30% of our overall revenue in three months. Looks like a good time to go hit the beach, right?
Wrong.
We funneled that money into more infrastructure.
“You’ve gotta build deep if you want to go high.” –Zig Ziglar
We added more employees, got a proper office (spreading our paperwork on the tables at Starbucks wasn’t cutting it anymore), and continued to look to future growth.
The Customer Is Always Right
One of my core values has always been to make sure the person paying my bills is happy. If they’re not, they might stop.
So when I received a request from an overly demanding client, I didn't tell them that was outside of the mandate of our agreed-upon contract. I stepped up and handled that business!
No one wants to hire a cold corporate company to serve them. They want an agile, ready-to-work group of people who can meet the needs that were not obvious at the time of signing. If you nickel and dime them for every request, you might make some money today, but you’re sacrificing tomorrow to do it.
Today is an investment for tomorrow, remember?
Take that costly request and say: “absolutely, I’ll take care of it!”
Focus on Building Your Reputation
Meeting those crazy requests and allowing your clients to call your personal phone anytime they need to, day or night, may bang up your mental health a bit, but it will pay for an army of therapists in the long run.
We quickly built a reputation as the guys who are looking to be partners with our clients. Their goals became our goals.
If we had focused on exploiting our clients with every service imaginable, we would never have stood out from the crowd.
Let everyone else set the standard, then do better than they ever could.
In our industry, we were the little guys going up against global umbrella corporations with all the money in the world to throw at getting contracts. Yet, we beat them every single time!
If we got the opportunity to get in front of a potential client, we didn’t tell them how much better our product was than people who clearly had more money for better widgets. We told them how we’re small, so we’re agile –– no red tape or requests to a corporate helpline for changes to your service. Call me and I’ll have your request met within the hour. And not some account manager, either, but the owner and the Director of Operations are at your disposal.
That personal touch, giving access to the top echelon of our organization, day or night…that was hard. Sometimes, it was downright impossible. But it earned us a reputation that was more valuable than any revenue stream.
Hang In There
Like a bad movie, there’s a midpoint slump in the second act where it feels like your company isn’t growing. We suffered through this for several months after adding that $93,000 contract.
The feeling like you’re making all of the right moves, investing in all the right places, and yet no one wants to take a chance on you…it sucks.
Don’t waste that time wallowing in self-pity. Use it to continue to build your reputation. We never spent a dime on marketing or advertising. No one ever learned about us from some billboard or Google Adsense campaign. We were, and still are, a 100% word-of-mouth company. We have to be. We don’t have the money to compete in the advertising game with those globe-spanning companies we’re up against. We need you to have heard about our reputation from someone we’ve knocked the socks off of, and that takes time to spread.
Keep at it. More business will come, just like it did for us.
Protect Your Culture
We have a “people-first” mindset. The idea that someone feels stuck and miserable at our company would lead us to close the doors forever, no joke. What’s the point of business if it doesn’t provide the resources to live life the way you want to?
Culture eats strategy for breakfast. –Peter Drucker
We exploded out of our midpoint slump with four contracts that added $600,000 in revenue in a 30-day span. That reputation we had spent so much time focusing on paid off, BIG TIME.
With that growth, however, came long, stressful workdays that demanded more of that infrastructure. But as we added more people to our team, we started seeing the evils of corporate politics and gossip that we had been able to avoid up until then.
Want to know the fastest way to lose employees? Let them start talking shit about each other, and your company, without any recourse. The first time I saw it creep up, I stamped it down with what has become my battle cry against gossip, slander, and backstabbing:
I’ll train bad performance for months, but I’ll fire bad culture in a heartbeat!
If someone cares about the company and wants to work, you can train them out of any work-performance issues. If they don’t care and have a terrible work ethic, no amount of training will ever keep them from dragging the culture and reputation of your company into the dirt.
If your house is divided, it will not stand, and certainly can’t grow. The hardest challenge we’ve had to face, by far, is protecting our positive, family- and people-first company culture.
Set Your Endgame Goal
The final lesson we’ve learned so far. A few months after getting those $600,000 contracts, we gained an additional $300,000 in small contracts, and then one big one for $500,000.
Side Note: the pattern of setting up more infrastructure leading to explosive growth is the reason we invest in that direction, and has certainly paid off.
It wasn’t until we got to where we are now, almost breaking $2 million in revenue before my boss took any sort of raise beyond the bare necessities to meet his family’s needs. At some point, you have to start making a profit, sure, but we had it planned from the beginning.
My boss knew how much he wanted to make out of this business. He asked me how much I wanted to make. We have that same conversation with everyone who works for us. Once we learned how many employees it would take to meet the demands of a certain level of business, and what those employees needed, we were able to come up with our endgame.
Too many people in business look at profits as an endless source of becoming Bill Gates. Our argument: without a target to shoot for, how could you possibly hit it?
Once we looked at our bottom line (we didn’t ignore that forever), we set a goal that would meet all of our needs. Once reached, we will begin turning down new clients and working to improve the quality of our standing business portfolio. And we’ll do it having met all of our goals for personal growth, fulfillment, and financial needs.
Where We Are Today
We still haven’t hit our endgame goal. In fact, we’re only about 20% of the way there. But if the average increase of $100k per month continues, we will hit that goal within the next few years.
That growth didn’t come from employing a new business strategy peddled by some mastermind class, nor did we get into some pyramid scheme to take advantage of our employee’s personal networks. We built that revenue using the tried and true values of integrity, hard work, and being incredibly service-minded, not only to our clients but to our employees.
No one in our organization has a college degree. All of our parents were blue-collared workers. The owner worked a day job for ten years to save the starting capital for this business. If we can do it, anyone can, but it will take time and it won’t be easy. | https://medium.com/swlh/how-we-increased-revenue-by-100k-per-month-25caa5b597ca | ['Ryan M. Danks'] | 2020-12-01 18:27:09.689000+00:00 | ['Entrepreneurship', 'Business', 'Startup'] | Title Increased Revenue 100k Every MonthContent Increased Revenue 100k Every Month Common Sense Business Practices Aren’t Common Anymore Shopify Partners Burst bos approached help run small business two contract total revenue 365k per year run business past knew lot industry operated shared value business operate great foundation growth Fastforward 16 month we’ve grown small business 100k per month revenue 195M Here’s Don’t Concentrate Money Except Gary Vaynerchuk anyone peddling advice day focus wrong place Trying make fast buck business model good way make money ever jumping small business pattern starting failing call “learning” business pattern looked something like Draw business plan based solid idea Find nocost method start willing work day night Check stats income daily see Slowly watch business spiral abject failure Rinse repeat venture lesson recognized fail thing fail learn important lesson could gone right see particular area went wrong Eventually identified area business previous one lasted longer fulfilling made money final business chugging along steady pace going distance couldn’t afford put sort infrastructure place make really take That’s met bos decided fold company join started shocked find owner direct bos recruited Number 2 didn’t business plan didn’t know profit margin bottomline number Yet earned enough pay help grow business area always gotten wrong –– constant need check stats see bos however way looking time money would made difference business pattern Today investment tomorrow didn’t matter didn’t make money long enough invest back business mattered time counted anything early day make sure red Trust Reinvest People lesson money investmentmindedness way ready deploy knowledge help business grow came operation company part best part bos willing take chance idea hired first three month added 93000 contract portfolio big jump u sure adding almost 30 overall revenue three month Looks like good time go hit beach right Wrong funneled money infrastructure “You’ve gotta build deep want go high” –Zig Ziglar added employee got proper office spreading paperwork table Starbucks wasn’t cutting anymore continued look future growth Customer Always Right One core value always make sure person paying bill happy they’re might stop received request overly demanding client didnt tell outside mandate agreedupon contract stepped handled business one want hire cold corporate company serve want agile readytowork group people meet need obvious time signing nickel dime every request might make money today you’re sacrificing tomorrow Today investment tomorrow remember Take costly request say “absolutely I’ll take care it” Focus Building Reputation Meeting crazy request allowing client call personal phone anytime need day night may bang mental health bit pay army therapist long run quickly built reputation guy looking partner client goal became goal focused exploiting client every service imaginable would never stood crowd Let everyone else set standard better ever could industry little guy going global umbrella corporation money world throw getting contract Yet beat every single time got opportunity get front potential client didn’t tell much better product people clearly money better widget told we’re small we’re agile –– red tape request corporate helpline change service Call I’ll request met within hour account manager either owner Director Operations disposal personal touch giving access top echelon organization day night…that hard Sometimes downright impossible earned u reputation valuable revenue stream Hang Like bad movie there’s midpoint slump second act feel like company isn’t growing suffered several month adding 93000 contract feeling like you’re making right move investing right place yet one want take chance you…it suck Don’t waste time wallowing selfpity Use continue build reputation never spent dime marketing advertising one ever learned u billboard Google Adsense campaign still 100 wordofmouth company don’t money compete advertising game globespanning company we’re need heard reputation someone we’ve knocked sock take time spread Keep business come like u Protect Culture “peoplefirst” mindset idea someone feel stuck miserable company would lead u close door forever joke What’s point business doesn’t provide resource live life way want Culture eats strategy breakfast –Peter Drucker exploded midpoint slump four contract added 600000 revenue 30day span reputation spent much time focusing paid BIG TIME growth however came long stressful workday demanded infrastructure added people team started seeing evil corporate politics gossip able avoid Want know fastest way lose employee Let start talking shit company without recourse first time saw creep stamped become battle cry gossip slander backstabbing I’ll train bad performance month I’ll fire bad culture heartbeat someone care company want work train workperformance issue don’t care terrible work ethic amount training ever keep dragging culture reputation company dirt house divided stand certainly can’t grow hardest challenge we’ve face far protecting positive family peoplefirst company culture Set Endgame Goal final lesson we’ve learned far month getting 600000 contract gained additional 300000 small contract one big one 500000 Side Note pattern setting infrastructure leading explosive growth reason invest direction certainly paid wasn’t got almost breaking 2 million revenue bos took sort raise beyond bare necessity meet family’s need point start making profit sure planned beginning bos knew much wanted make business asked much wanted make conversation everyone work u learned many employee would take meet demand certain level business employee needed able come endgame many people business look profit endless source becoming Bill Gates argument without target shoot could possibly hit looked bottom line didn’t ignore forever set goal would meet need reached begin turning new client working improve quality standing business portfolio we’ll met goal personal growth fulfillment financial need Today still haven’t hit endgame goal fact we’re 20 way average increase 100k per month continues hit goal within next year growth didn’t come employing new business strategy peddled mastermind class get pyramid scheme take advantage employee’s personal network built revenue using tried true value integrity hard work incredibly serviceminded client employee one organization college degree parent bluecollared worker owner worked day job ten year save starting capital business anyone take time won’t easyTags Entrepreneurship Business Startup |
967 | What Being Bullied Was Really Like | What Being Bullied Was Really Like
I still shudder when I think about taking the school bus
Photo by David Preston on Unsplash
On my first day of kindergarten, a little boy who was just as nicely rounded as I was bullied me for being fat. At least, that was the reason he gave me for trapping between a row of bushes and the wall of our elementary school during recess. He was brandishing a stick, and that gave him the upper hand.
I don’t think his bullying had its roots in his home life. My parents knew his parents, and by all accounts, they were a perfectly nice couple. He had a younger brother, but he didn’t appear to share my schoolmate’s penchant for bullying.
It was a mystery.
On another occasion, a little boy named Benjamin bullied me during school. The only other thing I remember about Benjamin was that his religion forbade him from participating in class Christmas parties.
It was a public school. There wasn’t anything particularly Christian about our Christmas parties, but rules are rules. So every year, while the rest of us ate cookies and drank sugary punch, he sat at the front of the room near the teacher’s desk and worked on his knitting. He always brought enough dreidels for the class, passing them out before resigning himself to his knitting.
Today, I can’t remember the details of Benjamin bullying me, but I told my older brother all about it in great detail at the time. My brother was nearly a decade older than me and went to the nearby high school. So when he stopped by my elementary school one afternoon to confront Benjamin, the younger boy nearly soiled his trousers.
Ironically, Benjamin himself was a victim of bullying in elementary school. While bullies always targeted me based upon my weight or my looks, Benjamin was bullied for his religion, and that’s a shame. Perhaps being a victim of bullying himself inspired him to bully others.
Benjamin never bullied me again after my brother confronted him, but there was always another bully in the pipeline. My brother couldn’t possibly confront all of them, even if he was a tall and stocky teenager who towered over my elementary school tormentors. Besides, I didn’t want him to get in any trouble.
Not all my bullies were male.
Our teachers often had students line up in the hallway by height and gender. The shortest boys stood at the front of the line on one side of the hall, and the shortest girls stood at the front of the line on the other side.
Although I frequently stood near the front of the girls’ line, I was never the first in line. I was fortunate not to be the shortest girl in the class. There’s nothing wrong with being short, of course, but I didn’t need anyone to find another reason to tease me.
One day, as we were jockeying for position in the hallway, I heard one girl say to another in a stage whisper, “Watch this. I’m going to push Tracey, and then I’m going to say, ‘Oops. I’m sorry.’”
That’s exactly what happened.
I felt hands on my back as the girl gave me a hard shove forward. “Oops,” she said. “I’m sorry.”
I have no idea what she thought she accomplished that day, but I still remember the sound of her voice decades later. Oops. I’m sorry.
Then the teachers told my mother to put me in a private school.
“If you send her to the public junior high school, the other kids will eat her alive,” they said.
They were right, but they were also wrong. While the public schoolchildren were already in the process of eating me alive, the private schoolchildren were about to make my life a living hell.
Since the private school was in a neighboring town, my mother decided to put me on the schoolbus instead of driving me. That’s where a younger schoolmate announced she was planning to stick a pin in me to see if I’d pop.
Then they made fun of me for having a lunchbox with the words “I Love Lunch” emblazoned on the front of it. Then they made fun of me because my mother met me at the bus stop every day after school. When my mother started hiding around the corner from the bus stop in the hopes they would tease me less, they teased me more.
When my mother contacted the school bus company for help, they told her there was nothing they could do. It was a school bus, not a refuge for timid children. If I couldn't fend for myself, then perhaps I shouldn’t be on the school bus, they suggested.
My mother, who had prepaid for an entire year of private school bus service, began driving me to school. At least then I didn’t get bullied until I reached the school grounds.
The ride to and from school was a nightmare of cruelty so severe that I’d love to confront my bullies today decades later, and most of all, I hope they’re suffering now.
It’s 2020. They most certainly are. We all are.
I still have nightmares about that school bus.
I often ascribe my decision to be childfree by choice to those elementary school years. “I didn’t enjoy the company of children when I was a child,” I’ve often said. “Why would I want them now?”
I spent way too many nights crying and hyperventilating in my twin bed because I’d had the worst day ever and I knew the following day would top it. That’s what it’s like to be bullied: abject misery.
They say living well is the best revenge. Well, I’m living okay. I imagine I am doing better than some of my former school bullies and school bus tormenters, and I imagine I am doing worse than others.
Back in elementary school, I was way at the bottom. I don’t plan on being there again, not if I can help it. | https://medium.com/traceys-folly/what-being-bullied-is-really-like-eb1869ac4f17 | ['Tracey Folly'] | 2020-12-28 23:49:06.568000+00:00 | ['Nonfiction', 'Self', 'Society', 'Family', 'Culture'] | Title Bullied Really LikeContent Bullied Really Like still shudder think taking school bus Photo David Preston Unsplash first day kindergarten little boy nicely rounded bullied fat least reason gave trapping row bush wall elementary school recess brandishing stick gave upper hand don’t think bullying root home life parent knew parent account perfectly nice couple younger brother didn’t appear share schoolmate’s penchant bullying mystery another occasion little boy named Benjamin bullied school thing remember Benjamin religion forbade participating class Christmas party public school wasn’t anything particularly Christian Christmas party rule rule every year rest u ate cooky drank sugary punch sat front room near teacher’s desk worked knitting always brought enough dreidels class passing resigning knitting Today can’t remember detail Benjamin bullying told older brother great detail time brother nearly decade older went nearby high school stopped elementary school one afternoon confront Benjamin younger boy nearly soiled trouser Ironically Benjamin victim bullying elementary school bully always targeted based upon weight look Benjamin bullied religion that’s shame Perhaps victim bullying inspired bully others Benjamin never bullied brother confronted always another bully pipeline brother couldn’t possibly confront even tall stocky teenager towered elementary school tormentor Besides didn’t want get trouble bully male teacher often student line hallway height gender shortest boy stood front line one side hall shortest girl stood front line side Although frequently stood near front girls’ line never first line fortunate shortest girl class There’s nothing wrong short course didn’t need anyone find another reason tease One day jockeying position hallway heard one girl say another stage whisper “Watch I’m going push Tracey I’m going say ‘Oops I’m sorry’” That’s exactly happened felt hand back girl gave hard shove forward “Oops” said “I’m sorry” idea thought accomplished day still remember sound voice decade later Oops I’m sorry teacher told mother put private school “If send public junior high school kid eat alive” said right also wrong public schoolchildren already process eating alive private schoolchildren make life living hell Since private school neighboring town mother decided put schoolbus instead driving That’s younger schoolmate announced planning stick pin see I’d pop made fun lunchbox word “I Love Lunch” emblazoned front made fun mother met bus stop every day school mother started hiding around corner bus stop hope would tease le teased mother contacted school bus company help told nothing could school bus refuge timid child couldnt fend perhaps shouldn’t school bus suggested mother prepaid entire year private school bus service began driving school least didn’t get bullied reached school ground ride school nightmare cruelty severe I’d love confront bully today decade later hope they’re suffering It’s 2020 certainly still nightmare school bus often ascribe decision childfree choice elementary school year “I didn’t enjoy company child child” I’ve often said “Why would want now” spent way many night cry hyperventilating twin bed I’d worst day ever knew following day would top That’s it’s like bullied abject misery say living well best revenge Well I’m living okay imagine better former school bully school bus tormenter imagine worse others Back elementary school way bottom don’t plan help itTags Nonfiction Self Society Family Culture |
968 | Time management for creatives | It’s winter.
The nights are long in the UK, the days short, cold and dark. We’re in lockdown (again). And this month, one after the other, my coaching clients expressed disappointment that they’re got nothing done.
“I’ve just been lazy,” says a photographer.
“I’ve not moved forward on anything,” says a writer.
“I don’t know where the time went,” says a fashion designer.
Yet when we analyse their to-do lists, and go through what they have been doing, it soon becomes clear that isn’t so.
The ‘lazy’ photographer has moved two personal projects forward, taken care of a sick child, bought and assembled some new furniture for his studio, and done some serious online networking.
He feels he’s got nothing done because none of this work was paid. And he tends to measure his productivity by how much he has earned. Yet he knows from experience that the personal projects will, in time, either turn into a story he’ll get paid for, or open up new work.
The ‘stuck’ writer has sorted got the family car repaired, written two features for a national newspaper, done three in-depth interviews and hosted an event online. What she means is that she hasn’t advanced the book project she’s been working on, concentrating instead on paid work to support her family.
She’s frustrated because this is the kind of work that is never done. There’s always a new deadline, a new interview, a new feature to write. She’s longing for the satisfaction of actually completing a big project: finishing her new book, and getting it out into the world.
The designer who didn’t know where her time had gone was packaging and posting orders herself during lockdown, as well as negotiating deadlines with a factory itself floored by the virus. She had hosted several virtual sales events online, and helped a friend through a major crisis.
This had left her with no time to plan a new business venture she’d been considering. She’s excited by the new thing, keen to get on with it. Which is why she was feeling behind.
Time management can be challenging for creatives.
If there’s one issue that clients bring to me most often, it is this one. They call it poor time management, lack of time/space/discipline, procrastination. But what it usually comes down to is this: they’re not getting on with the work they really want to do.
They’re often trying to do too much at once, or doing an awful lot that they are not counting as work at all. Or they’re constantly busy, but not making time for the things they feel are important.
Sound familiar? If so, here are nine things that can help.
1. Time is limited. But so is energy, and focus.
You need to manage all three, not just focus on time. Very few of us can manage more than four hours of totally focussed creative work in a day. Of course there are magical days when you get into flow, hours fly by like minutes and you’re reluctant to stop to eat or sleep. But those days are rare, and never come when we most need them.
We need regular breaks in our working day, to refocus and to replenish our energy.
Look at the routines of prolific, consistent creators and they’ll often consist of a regular block of time they dedicate to their creative work before attending to other things; or shorter bursts of work followed by recovery time (a walk, a work-out, coffee, time to read or relax).
Most of those people also talk about a magical effect when they finish work with an unresolved problem, and then the next day return somehow knowing the answer. Take more breaks, and your subconscious mind will continue working on it, even if you are not. Research has shown that plenty of sleep, frequent breaks and exercise — especially walking — helps here.
Need convincing? Read Matthew Walker’s book Why We Sleep: The New Science of Sleep and Dreams is packed with research and evidence on the power of sleep, and how it enhances creativity. And Alex Soojung-Kim Pang’s entertaining book Rest: Why You Get More Done When You Work Less gives strong arguments for resting more — and for the power of walking.
2. Ring-fence time for the project you most want to do.
And then protect it fiercely. Act as if it’s an interview with a Hollywood A-lister, a crucial business meeting or a plane you have to catch.
If you absolutely have to postpone because a huge money job comes up or some other emergency, move it to the nearest available space and only move it again if someone’s life depends on it. (Because your creative life does depend on it.)
It can be difficult, in the stresses of deadlines and day-to-day life to find this time. Be ruthless. Maybe it means leaving the house a mess, ignoring phone calls, arranging a play date for your kids, turning down a social engagement. That’s OK.
I write well in the mornings, so that’s what I do. Every day, from 8am-9am. Before breakfast, before getting dressed sometimes. And definitely before giving my time to anything or anyone else. Even if I don’t get back to the page later, knowing I’ve done that hour leaves me at peace for the rest of the day.
Only you can do this: no one will clear the space for you. But it will make the difference between moving forward, and feeling like you’re stuck on an endlessly revolving hamster wheel, running but getting nowhere.
Protect your creative time fiercely. Photo by Charl Durand on Unsplash
3. Choose your one thing
As creatives, we tend to have a lot of ideas. and they’re all exciting. We go off on tangents, or get distracted by the latest shiny object we’ve discovered. Or we’re juggling several projects at once, and never bringing any of them to completion. Especially when they’re competing with the day to day demands of work and life, friends and family.
Painful though it is, we need to choose one creative project at a time, and give it our whole focus until it’s finished. Then we can choose another.
You’ll get more done that way. You’ll have the satisfaction — and momentum — of completing.
4. Love vs Money
We all need to earn money somehow. But many of us are also working on creative projects that are more speculative, that might not immediately increase our bank balance. We need those projects, to grow and learn. That’s where your joy is found, and your unique talents and voice find expression.
Obviously, at some point we hope to reach that sweet spot where they combine, and we’re being paid well to make the work we love.
In the meantime, we need to make space for both. It can help to decide which kind of work you’re doing, and when. Money work you do to the best of your ability in the time available. But you always make room for the love projects, too. That balance is crucial.
5. Get clear on how long tasks really take.
Tracking your time is tedious, but it’s also eye-opening. Try keeping a record of what you’ve been doing, in 30-minute increments, for a week or even a month.
Be honest. This is to help you understand where your time actually goes. Record the time you spend procrastinating (and how), staring into space, scrolling on social media. This is telling you when you’ve lost focus, when taking a break might be more helpful than pushing on through. Also watch out for those points in the day when you’re so weary you lose the ability to decide what’s important, and start doing busy work, just to feel productive.
It will help you become more aware of the tasks you dread doing, and put off for days — but which only take a few minutes to actually get done. And the tasks you tell yourself should only take an hour — but which really take half a day.
6. Look for energy hangovers.
It is never simple to move from one task to another. That’s why multi-tasking just doesn’t work. Every time you interrupt your creative work to look at an email, move from creating to an admin task, or interrupt your work to answer the phone, it takes a while to get back into flow.
Some tasks are more demanding than others, and they leave you with energy hangovers. In a busy workplace, there tend to be natural breaks where you can work these off. Walking back to your office after a long meeting, for instance, and maybe stopping off to chat with someone while you make a drink. And of course the commute to and from work is a huge signal to our busy minds that we’re moving from one headspace to another.
But if we work at home or in a studio or workshop alone, we need to make space for recovery. If we don’t, we’ll find a way of doing it anyway — and it won’t be healthy.
After interviews, meetings or long coaching conversations, for instance, I realised I tend to pointlessly scroll on social media, start long replies to emails I’d usually ignore, and engage in all kinds of other time-wasting activities.
It took a while for me to realise that after such periods of intense concentration and social interaction, I need some space to recover. Now I go straight out for a walk to clear my head, I dance or do a short workout. When I come back to work, I’m able to focus agin. And I get on with what’s really important that day, instead of getting caught up in trivia.
7. Don’t forget the admin!
We all have it, in some form or another, and it takes time. Answering emails, invoicing and accounts, coordinating with manufacturers or contributors, setting up meetings, networking and marketing, buying materials.. the list goes on and on. Yet few of us actually allow enough time for it, in our schedules.
I like to get my admin done after my creative work, or it swallows my day whole. But if you’re at your best creatively later in the day, get it out of the way first. Either way, I find a timer helps: I tend to do admin in 30-minute bursts, followed by a short break. It stops me getting distracted.
Admin takes time, like it or not. Photo by Charl Durand on Unsplash
Other things that help:
Turn off your email, and only check it at set times. Don’t let your in-box — which is full of other people’s priorities, not your own - dictate how you use your days.
Keep your phone out of your workspace.
Build systems. If you find yourself doing the same job twice, take a few minutes to consider how you can avoid doing it a third time. Writing the same email? Keep it as a template, and just adapt it each time. Doing a repetitive computer task? Find some code to do it for you.
Delegate. Do you really need to do this task, or could someone else do it? This isn’t just about outsourcing work tasks. Sometimes hiring a cleaner, ordering a takeaway or getting someone else to cook, or getting help with your home or garden can free you up to do more of the creative work only you can do.
If you need to be on social media for work, use a timer, to stop you falling down the rabbit hole.
Assign set times of your day/week/month to deal with your money stuff. You can then put receipts, invoices and bills in a drawer or envelope as they arrive, confident you’ll deal with them in time.
8. Chunk down big tasks
Sometimes, we don’t start a task because it’s overwhelming, and impossible to know where to start. I try to have nothing on my to-do list that will take me longer than an hour. If it’s too big to complete in that time, I’ll break it down into smaller pieces. On a big project, this also gives you a sense of forward motion.
“Finish book” is a task that will linger accusingly on your list for months, even years. But if you’ve ticked off ten research tasks, set up two interviews, written a first draft of a section, edited a chapter, you see you are progressing. And that’s motivating.
It also means that if you don’t have a big chunk of time to devote to your project that day, there are often smaller tasks you can get done.
9. Just say no.
It’s a simple, short word, although a lot of us make it longer by marrying it to the word sorry. And weighing it down with unnecessary emotion. Saying no doesn’t mean you’re rejecting someone, that you’re a bad person. It just means you can’t do this thing, this time.
Stop being sorry. Protect the time you need for your creative work, without apology. It’s important.
Then you’ll really be offering your unique gifts to the world. And who knows what that could change? | https://medium.com/creative-living/time-management-for-creatives-13109ba59d55 | ['Sheryl Garratt'] | 2020-11-24 18:30:16.945000+00:00 | ['Focus', 'Freelancing', 'Creativity', 'Writing', 'Time Management'] | Title Time management creativesContent It’s winter night long UK day short cold dark We’re lockdown month one coaching client expressed disappointment they’re got nothing done “I’ve lazy” say photographer “I’ve moved forward anything” say writer “I don’t know time went” say fashion designer Yet analyse todo list go soon becomes clear isn’t ‘lazy’ photographer moved two personal project forward taken care sick child bought assembled new furniture studio done serious online networking feel he’s got nothing done none work paid tends measure productivity much earned Yet know experience personal project time either turn story he’ll get paid open new work ‘stuck’ writer sorted got family car repaired written two feature national newspaper done three indepth interview hosted event online mean hasn’t advanced book project she’s working concentrating instead paid work support family She’s frustrated kind work never done There’s always new deadline new interview new feature write She’s longing satisfaction actually completing big project finishing new book getting world designer didn’t know time gone packaging posting order lockdown well negotiating deadline factory floored virus hosted several virtual sale event online helped friend major crisis left time plan new business venture she’d considering She’s excited new thing keen get feeling behind Time management challenging creatives there’s one issue client bring often one call poor time management lack timespacediscipline procrastination usually come they’re getting work really want They’re often trying much awful lot counting work they’re constantly busy making time thing feel important Sound familiar nine thing help 1 Time limited energy focus need manage three focus time u manage four hour totally focussed creative work day course magical day get flow hour fly like minute you’re reluctant stop eat sleep day rare never come need need regular break working day refocus replenish energy Look routine prolific consistent creator they’ll often consist regular block time dedicate creative work attending thing shorter burst work followed recovery time walk workout coffee time read relax people also talk magical effect finish work unresolved problem next day return somehow knowing answer Take break subconscious mind continue working even Research shown plenty sleep frequent break exercise — especially walking — help Need convincing Read Matthew Walker’s book Sleep New Science Sleep Dreams packed research evidence power sleep enhances creativity Alex SoojungKim Pang’s entertaining book Rest Get Done Work Less give strong argument resting — power walking 2 Ringfence time project want protect fiercely Act it’s interview Hollywood Alister crucial business meeting plane catch absolutely postpone huge money job come emergency move nearest available space move someone’s life depends creative life depend difficult stress deadline daytoday life find time ruthless Maybe mean leaving house mess ignoring phone call arranging play date kid turning social engagement That’s OK write well morning that’s Every day 8am9am breakfast getting dressed sometimes definitely giving time anything anyone else Even don’t get back page later knowing I’ve done hour leaf peace rest day one clear space make difference moving forward feeling like you’re stuck endlessly revolving hamster wheel running getting nowhere Protect creative time fiercely Photo Charl Durand Unsplash 3 Choose one thing creatives tend lot idea they’re exciting go tangent get distracted latest shiny object we’ve discovered we’re juggling several project never bringing completion Especially they’re competing day day demand work life friend family Painful though need choose one creative project time give whole focus it’s finished choose another You’ll get done way You’ll satisfaction — momentum — completing 4 Love v Money need earn money somehow many u also working creative project speculative might immediately increase bank balance need project grow learn That’s joy found unique talent voice find expression Obviously point hope reach sweet spot combine we’re paid well make work love meantime need make space help decide kind work you’re Money work best ability time available always make room love project balance crucial 5 Get clear long task really take Tracking time tedious it’s also eyeopening Try keeping record you’ve 30minute increment week even month honest help understand time actually go Record time spend procrastinating staring space scrolling social medium telling you’ve lost focus taking break might helpful pushing Also watch point day you’re weary lose ability decide what’s important start busy work feel productive help become aware task dread put day — take minute actually get done task tell take hour — really take half day 6 Look energy hangover never simple move one task another That’s multitasking doesn’t work Every time interrupt creative work look email move creating admin task interrupt work answer phone take get back flow task demanding others leave energy hangover busy workplace tend natural break work Walking back office long meeting instance maybe stopping chat someone make drink course commute work huge signal busy mind we’re moving one headspace another work home studio workshop alone need make space recovery don’t we’ll find way anyway — won’t healthy interview meeting long coaching conversation instance realised tend pointlessly scroll social medium start long reply email I’d usually ignore engage kind timewasting activity took realise period intense concentration social interaction need space recover go straight walk clear head dance short workout come back work I’m able focus agin get what’s really important day instead getting caught trivia 7 Don’t forget admin form another take time Answering email invoicing account coordinating manufacturer contributor setting meeting networking marketing buying material list go Yet u actually allow enough time schedule like get admin done creative work swallow day whole you’re best creatively later day get way first Either way find timer help tend admin 30minute burst followed short break stop getting distracted Admin take time like Photo Charl Durand Unsplash thing help Turn email check set time Don’t let inbox — full people’s priority dictate use day Keep phone workspace Build system find job twice take minute consider avoid third time Writing email Keep template adapt time repetitive computer task Find code Delegate really need task could someone else isn’t outsourcing work task Sometimes hiring cleaner ordering takeaway getting someone else cook getting help home garden free creative work need social medium work use timer stop falling rabbit hole Assign set time dayweekmonth deal money stuff put receipt invoice bill drawer envelope arrive confident you’ll deal time 8 Chunk big task Sometimes don’t start task it’s overwhelming impossible know start try nothing todo list take longer hour it’s big complete time I’ll break smaller piece big project also give sense forward motion “Finish book” task linger accusingly list month even year you’ve ticked ten research task set two interview written first draft section edited chapter see progressing that’s motivating also mean don’t big chunk time devote project day often smaller task get done 9 say It’s simple short word although lot u make longer marrying word sorry weighing unnecessary emotion Saying doesn’t mean you’re rejecting someone you’re bad person mean can’t thing time Stop sorry Protect time need creative work without apology It’s important you’ll really offering unique gift world know could changeTags Focus Freelancing Creativity Writing Time Management |
969 | The Better Art of Bringing Creative Possibilities into Unlikely Things | The Better Art of Bringing Creative Possibilities into Unlikely Things
Stop Escaping Behind the Canvas. Time to Step Out
Photo by Neven Krcmarek on Unsplash
This morning, your muse strikes and you get an idea for a film script. You open a page and start writing furiously. You start creating characters and conversations as they ought to be, a place where things are intensely interesting and unreal. Because the reality that we know is a bit dull and stale. You don’t have control and freedom over reality, but on paper and canvas you’ve got complete freedom and you’re thrilled and you continue writing for hours.
Finally, you think, on art and paper, you have unbounded permission to express that, which in real life is frowned upon. You’ve escaped behind the paper, where your art can show the possibilities that those other “real-life dummies” simply don’t get — right?
Yes, but hold on, hold on. Pause. Gently I take your pen away to give me a listen. You can continue writing/making art after this, I promise I’ll give your pen and paper back.
What if, we stop escaping into Art and paper and canvas to show our possibilities?
In other words, what if, instead of writing about characters and conversations as they ought to be, we become characters and conversations as they ought to be?
What if, we work towards becoming art? Not drawing it, or writing it (into dramas and film scripts) but embodying our best ideas and channelizing them through speech and breath.
What if, we dare to be and speak as one of our favorite characters, most interesting characters? Do we necessarily have to excuse ourselves sideways into an artwork, writing about things?
How come we don’t get tired of writing about things?
This could be one of the reasons why we have a zillion, so-called “artists” and “creatives” today producing endlessly, filling the internet and industry with a zillion more songs and poems, but only a handful of men and women who live as an artwork — if you’ve ever met them you’d know they came right out of a movie.
Dual Approach: To Depict vs To be
This is the question I pose: Can we be interesting, rather than write about interesting things?
What if art production is redundant unless it seeps, even if partially, into living and being?
Photo by Aziz Acharki on Unsplash
What if excessive art production, mildly indicates an impotence and an inability to transform creative sparks into living form — into everyday conversations, fights, building, planning, dancing, and love-making?
These are my questions to those drowned in “art-making”. Not out of mockery, there is huge respect and honor in art, let’s not be mistaken about that.
We forget that more than the canvas, we can beautify the things, rooms, homes around us. That rather than imagining interesting heroes, we could be one — Have we ever tried? That we can see creative possibilities in our relationships, businesses, jobs, and decisions?
It seems then, that we have two routes towards art, the conventional canvas is the first, but the second is what I call a holistic route — where art doesn’t merely become a studio practice but becomes a way of life; A place where we don’t stop at depicting ideas, but becoming and embodying them.
Do you see that line of separation? Between, talking about a good idea and being one.
“Don’t talk about what a good man should be. Be one.” — Marcus Aurelius
The artistic route talks and depicts a lot and skillfully that too, about what the hero in a story must do, what an ideal looks like (think sports dramas, war movies), and the interesting possibilities we can be. It’s an unfinished step, whereas Marcus Aurelius puts, we’ve talked about what a good man should be, but what about the main step — being one? Or being an interesting phenomenon in actuality.
This is where art stops and life begins because life is a bigger stage than the theatre. Indeed it is. | https://medium.com/the-innovation/the-better-art-of-bringing-creative-possibilities-into-unlikely-things-3c8f799fdc4f | ['Shiva Sankar'] | 2020-11-09 16:24:26.865000+00:00 | ['Self-awareness', 'Artist', 'Personal Development', 'Life Lessons', 'Creativity'] | Title Better Art Bringing Creative Possibilities Unlikely ThingsContent Better Art Bringing Creative Possibilities Unlikely Things Stop Escaping Behind Canvas Time Step Photo Neven Krcmarek Unsplash morning muse strike get idea film script open page start writing furiously start creating character conversation ought place thing intensely interesting unreal reality know bit dull stale don’t control freedom reality paper canvas you’ve got complete freedom you’re thrilled continue writing hour Finally think art paper unbounded permission express real life frowned upon You’ve escaped behind paper art show possibility “reallife dummies” simply don’t get — right Yes hold hold Pause Gently take pen away give listen continue writingmaking art promise I’ll give pen paper back stop escaping Art paper canvas show possibility word instead writing character conversation ought become character conversation ought work towards becoming art drawing writing drama film script embodying best idea channelizing speech breath dare speak one favorite character interesting character necessarily excuse sideways artwork writing thing come don’t get tired writing thing could one reason zillion socalled “artists” “creatives” today producing endlessly filling internet industry zillion song poem handful men woman live artwork — you’ve ever met you’d know came right movie Dual Approach Depict v question pose interesting rather write interesting thing art production redundant unless seeps even partially living Photo Aziz Acharki Unsplash excessive art production mildly indicates impotence inability transform creative spark living form — everyday conversation fight building planning dancing lovemaking question drowned “artmaking” mockery huge respect honor art let’s mistaken forget canvas beautify thing room home around u rather imagining interesting hero could one — ever tried see creative possibility relationship business job decision seems two route towards art conventional canvas first second call holistic route — art doesn’t merely become studio practice becomes way life place don’t stop depicting idea becoming embodying see line separation talking good idea one “Don’t talk good man one” — Marcus Aurelius artistic route talk depicts lot skillfully hero story must ideal look like think sport drama war movie interesting possibility It’s unfinished step whereas Marcus Aurelius put we’ve talked good man main step — one interesting phenomenon actuality art stop life begin life bigger stage theatre Indeed isTags Selfawareness Artist Personal Development Life Lessons Creativity |
970 | Learn How to Scale Your Kubernetes Deployments Dynamically | Setup
The first thing that we’re going to do is create a cluster with a single worker node to demonstrate the scalability behavior easily. And to do that, we’re going to use the command-line tool eksctl to manage an EKS cluster easily.
To be able to create the cluster, we’re going to do it with the following command:
eksctl create cluster --name=eks-scalability --nodes=1 --region=eu-west-2 --node-type=m5.large --version 1.17 --managed --asg-access
After a few minutes, we will have our own Kubernetes cluster with a single node to deploy applications on top of it.
Now we’re going to create a sample application to generate load. We’re going to use TIBCO BusinessWorks Application Container Edition to generate a simple application. It will be a REST API that will execute a loop of 100,000 iterations acting as a counter and return a result.
BusinessWorks sample application to show the scalability options
And we will use the resources available in this GitHub repository:
We will build the container image and push it to a container registry. In my case, I am going to use my Amazon ECR instance to do so, and I will use the following commands:
docker build -t testeks:1.0 .
docker tag testeks:1.0 938784100097.dkr.ecr.eu-west-2.amazonaws.com/testeks:1.0
docker push 938784100097.dkr.ecr.eu-west-2.amazonaws.com/testeks:1.0
And once that the image is pushed into the registry, we will deploy the application on top of the Kubernetes cluster using this command:
kubectl apply -f .\testeks.yaml
After that, we will have our application deployed there, as you can see in the picture below:
Image deployed on the Kubernetes cluster
So, now we can test the application. To do so, I will make port 8080 available using a port-forward command like this one:
kubectl port-forward pod/testeks-v1-869948fbb-j5jh7 8080:8080
With that, I can see and test the sample application using the browser, as shown below:
Swagger UI tester for the Kubernetes sample application
Horizontal pod autoscaling
Now, we need to start defining the autoscale rules, and we will start with the Horizontal Pod Autoscaler (HPA) rule. We will need to choose the resource that we would like to use to scale our pod. In this test, I will use the CPU utilization to do so, and I will use the following command:
kubectl autoscale deployment testeks-v1 --min=1 --max=5 --cpu-percent=80
That command will scale the replica set testeks from one ( 1 ) instance to five ( 5 ) instances when the CPU utilization percent is higher than 80%.
If now we check the status of the components, we will get something similar to the image below:
HPA rule definition for the application using CPU utilization as the key metric
If we check the TARGETS column, we will see this value: <unknown>/80%. That means that 80% is the target to trigger the new instances and the current usage is <unknown>.
We do not have anything deployed on the cluster to get the metrics for each of the pods. To solve that, we need to deploy the Metrics Server. To do so, we will follow the Amazon AWS documentation:
So, running the following command, we will have the Metrics Server installed.
kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/download/v0.3.7/components.yaml
And after doing that, if we check again, we can see that the current user has replaced the <unknown>:
Current resource utilization after installing the Metrics Server on the Kubernetes cluster
If that works, I am going to start sending requests using a Load Test inside the cluster. I will use the sample app defined below:
To deploy, we will use a YAML file with the following content:
And we will deploy it using the following command:
kubectl apply -f tester.yaml
After doing that, we will see that the current utilization is being increased. After a few seconds, it will start spinning new instances until it meets the maximum number of pods defined in the HPA rule.
Pods increasing when the load exceeds the target defined in previous steps.
Then, as soon as the load also decreases, the number of instances will be deleted.
Pods are deleted as soon as the load decreases.
Cluster autoscaling
Now, we need to see how we can implement the Cluster Autoscaler using EKS. We will use the information that Amazon provides:
The first step is to deploy the cluster autoscaling, and we will do it using the following command:
kubectl apply -f https://raw.githubusercontent.com/kubernetes/autoscaler/master/cluster-autoscaler/cloudprovider/aws/examples/cluster-autoscaler-autodiscover.yaml
Then we will run this command:
kubectl -n kube-system annotate deployment.apps/cluster-autoscaler cluster-autoscaler.kubernetes.io/safe-to-evict=”false”
And we will edit the deployment to provide the current name of the cluster that we are managing. To do that, and we will run the following command:
kubectl -n kube-system edit deployment.apps/cluster-autoscaler
When your default text editor opens with the text content, you need to make the following changes:
Set your cluster name in the placeholder available.
Add these additional properties:
- --balance-similar-node-groups
- --skip-nodes-with-system-pods=false
Deployment edits that are needed to configure the Cluster Autoscaler
Now we need to run the following command:
kubectl -n kube-system set image deployment.apps/cluster-autoscaler cluster-autoscaler=eu.gcr.io/k8s-artifacts-prod/autoscaling/cluster-autoscaler:v1.17.4
The only thing that is left is to define the AutoScaling policy. To do that, we will use the AWS Services portal:
Enter into the EC service page on the region in which we have deployed the cluster.
Select the Auto Scaling Group options.
Select the Auto Scaling Group that has been created as part of the EKS cluster-creating process.
Go to the Automatic Scaling tab and click on the Add Policy button available.
Autoscaling policy option in the EC2 Service console
Then we should define the policy. We will use the Average CPU utilization as the metric and set the target value to 50%:
Autoscaling policy creation dialog
To validate the behavior, we will generate load using the tester as we did in the previous test and validate the node load using the following command:
kubectl top nodes
kubectl top nodes’ sample output
Now we deploy the tester again. As we already have it deployed in this cluster, we need to delete it first to deploy it again:
kubectl delete -f .\tester.yaml
kubectl apply -f .\tester.yaml
As soon as the load starts, new nodes are created, as shown in the image below:
kubectl top nodes showing how nodes have been scaled up
After the load finishes, we go back to the previous situation: | https://medium.com/better-programming/learn-how-to-scale-your-kubernetes-deployments-dynamically-d6c11344ec08 | ['Alex Vazquez'] | 2020-12-29 18:25:41.947000+00:00 | ['Software Engineering', 'Software Development', 'Programming', 'K8s', 'Kubernetes'] | Title Learn Scale Kubernetes Deployments DynamicallyContent Setup first thing we’re going create cluster single worker node demonstrate scalability behavior easily we’re going use commandline tool eksctl manage EKS cluster easily able create cluster we’re going following command eksctl create cluster nameeksscalability nodes1 regioneuwest2 nodetypem5large version 117 managed asgaccess minute Kubernetes cluster single node deploy application top we’re going create sample application generate load We’re going use TIBCO BusinessWorks Application Container Edition generate simple application REST API execute loop 100000 iteration acting counter return result BusinessWorks sample application show scalability option use resource available GitHub repository build container image push container registry case going use Amazon ECR instance use following command docker build testeks10 docker tag testeks10 938784100097dkrecreuwest2amazonawscomtesteks10 docker push 938784100097dkrecreuwest2amazonawscomtesteks10 image pushed registry deploy application top Kubernetes cluster using command kubectl apply f testeksyaml application deployed see picture Image deployed Kubernetes cluster test application make port 8080 available using portforward command like one kubectl portforward podtesteksv1869948fbbj5jh7 80808080 see test sample application using browser shown Swagger UI tester Kubernetes sample application Horizontal pod autoscaling need start defining autoscale rule start Horizontal Pod Autoscaler HPA rule need choose resource would like use scale pod test use CPU utilization use following command kubectl autoscale deployment testeksv1 min1 max5 cpupercent80 command scale replica set testeks one 1 instance five 5 instance CPU utilization percent higher 80 check status component get something similar image HPA rule definition application using CPU utilization key metric check TARGETS column see value unknown80 mean 80 target trigger new instance current usage unknown anything deployed cluster get metric pod solve need deploy Metrics Server follow Amazon AWS documentation running following command Metrics Server installed kubectl apply f httpsgithubcomkubernetessigsmetricsserverreleasesdownloadv037componentsyaml check see current user replaced unknown Current resource utilization installing Metrics Server Kubernetes cluster work going start sending request using Load Test inside cluster use sample app defined deploy use YAML file following content deploy using following command kubectl apply f testeryaml see current utilization increased second start spinning new instance meet maximum number pod defined HPA rule Pods increasing load exceeds target defined previous step soon load also decrease number instance deleted Pods deleted soon load decrease Cluster autoscaling need see implement Cluster Autoscaler using EKS use information Amazon provides first step deploy cluster autoscaling using following command kubectl apply f httpsrawgithubusercontentcomkubernetesautoscalermasterclusterautoscalercloudproviderawsexamplesclusterautoscalerautodiscoveryaml run command kubectl n kubesystem annotate deploymentappsclusterautoscaler clusterautoscalerkubernetesiosafetoevict”false” edit deployment provide current name cluster managing run following command kubectl n kubesystem edit deploymentappsclusterautoscaler default text editor open text content need make following change Set cluster name placeholder available Add additional property balancesimilarnodegroups skipnodeswithsystempodsfalse Deployment edits needed configure Cluster Autoscaler need run following command kubectl n kubesystem set image deploymentappsclusterautoscaler clusterautoscalereugcriok8sartifactsprodautoscalingclusterautoscalerv1174 thing left define AutoScaling policy use AWS Services portal Enter EC service page region deployed cluster Select Auto Scaling Group option Select Auto Scaling Group created part EKS clustercreating process Go Automatic Scaling tab click Add Policy button available Autoscaling policy option EC2 Service console define policy use Average CPU utilization metric set target value 50 Autoscaling policy creation dialog validate behavior generate load using tester previous test validate node load using following command kubectl top node kubectl top nodes’ sample output deploy tester already deployed cluster need delete first deploy kubectl delete f testeryaml kubectl apply f testeryaml soon load start new node created shown image kubectl top node showing node scaled load finish go back previous situationTags Software Engineering Software Development Programming K8s Kubernetes |
971 | AI Summit | San Francisco and Wired to Wear | Here are early confirmed Keynote Speakers obtained from the website: Tad Smith, President & CEO, Sotheby’s; Alan Boehme, Global Chief Technology Officer, VP of IT Services, and Chief IT Innovation Officer, Proctor & Gamble; Srini Venkatraman, Chief Data Scientist, Boeing; Swatee Singh, Vice President and Distinguished Architect, American Express; Nav Kesher, Head of Data Science, Facebook; Zoubin Ghahramani, Chief Scientist, Uber; Melody Ayeli, Director of Software Licensing and Complex Acquisitions, Toyota; Ningyu Chen, VP Data and Platforms, Macy’s; Thomas Stubbs, Vice President, Engineering and Innovation, The Coca Cola Company; Steve Chien, Senior Research Scientist, Autonomous Systems, NASA; David Newman, SVP Innovation, Wells Fargo; Ashish Lahoti, SVP, Global Data Technology, Charles Schwab; Anand Mariappan, Senior Director Of Engineering Data Science, Search and ML, Reddit; Dinakar Deshmukh, VP Data Sciences and Analytics, GE Aviation; Ganesh Harinath, VP, Head of AI Platform and Applications, Verizon; Gilad Lotan, VP and Head of Data Science, Buzzfeed; Piers Lingle, SVP of Customer Experience, Comcast; Denis Garagic, Chief Scientist AI and Machine Learning, BAE Systems; Danny Lange, VP of AI and Machine Learning, Unity Technologies; Ravi Boggaram, Sr Director, Digital Services, PepsiCo; Gil Arditi, Head of Machine Learning Platform, Lyft; Keoki Jackson, CTO, Lockheed Martin; Hans-Aloys Wischmann, VP Research and Innovation, Philips Research; Steve Eglash, Executive Director, Research Initiatives, Computer Science Dept, Stanford University; Mark Young, CTO — Climate, Bayer; Nimit Jain, Global Director of Data Science, Novartis; Rajeev Kalamdani, Sr. Analytics Scientist, Ford; Scott Mathis, CISO, RBC; Charles Givre, VP Lead Data Scientist, Deutsche Bank; and Somnath Banerjee, Director, Machine Learning, Walmart Labs.
Because we are on the advent of the most important events of this year, yet alone, this decade, it’s a monstrous undertaking pulling together the “best of the best” …so here we are.
25–26 SEPTEMBER 2019 | THE PALACE OF FINE ARTS
At the Museum of Science+Industry in Chicago, the “Wired to Wear” Exhibit is now open. See how this futuristic wearable technology will define how we dress such as a jacket that “barks” instead of your dog, racing suits that deploy with airbags, and headgear (with lasers) that help those with Parkinson’s the assistance to visualize their walking. | https://medium.com/aimarketingassociation/ai-summit-san-francisco-and-wired-to-wear-c459f8753b51 | ['Joanna Strom'] | 2019-08-01 18:10:43.373000+00:00 | ['Artificial Intelligence', 'AI', 'IoT', 'Internet of Things', 'NASA'] | Title AI Summit San Francisco Wired WearContent early confirmed Keynote Speakers obtained website Tad Smith President CEO Sotheby’s Alan Boehme Global Chief Technology Officer VP Services Chief Innovation Officer Proctor Gamble Srini Venkatraman Chief Data Scientist Boeing Swatee Singh Vice President Distinguished Architect American Express Nav Kesher Head Data Science Facebook Zoubin Ghahramani Chief Scientist Uber Melody Ayeli Director Software Licensing Complex Acquisitions Toyota Ningyu Chen VP Data Platforms Macy’s Thomas Stubbs Vice President Engineering Innovation Coca Cola Company Steve Chien Senior Research Scientist Autonomous Systems NASA David Newman SVP Innovation Wells Fargo Ashish Lahoti SVP Global Data Technology Charles Schwab Anand Mariappan Senior Director Engineering Data Science Search ML Reddit Dinakar Deshmukh VP Data Sciences Analytics GE Aviation Ganesh Harinath VP Head AI Platform Applications Verizon Gilad Lotan VP Head Data Science Buzzfeed Piers Lingle SVP Customer Experience Comcast Denis Garagic Chief Scientist AI Machine Learning BAE Systems Danny Lange VP AI Machine Learning Unity Technologies Ravi Boggaram Sr Director Digital Services PepsiCo Gil Arditi Head Machine Learning Platform Lyft Keoki Jackson CTO Lockheed Martin HansAloys Wischmann VP Research Innovation Philips Research Steve Eglash Executive Director Research Initiatives Computer Science Dept Stanford University Mark Young CTO — Climate Bayer Nimit Jain Global Director Data Science Novartis Rajeev Kalamdani Sr Analytics Scientist Ford Scott Mathis CISO RBC Charles Givre VP Lead Data Scientist Deutsche Bank Somnath Banerjee Director Machine Learning Walmart Labs advent important event year yet alone decade it’s monstrous undertaking pulling together “best best” …so 25–26 SEPTEMBER 2019 PALACE FINE ARTS Museum ScienceIndustry Chicago “Wired Wear” Exhibit open See futuristic wearable technology define dress jacket “barks” instead dog racing suit deploy airbags headgear laser help Parkinson’s assistance visualize walkingTags Artificial Intelligence AI IoT Internet Things NASA |
972 | Modern-Day Architecture Design Patterns for Software Professionals | Circuit Breaker
Distributed systems should be designed by taking failures into consideration. These days the world has adopted microservices, and these services are mostly dependent on other remote services. These remote services could fail to respond in time due to various reasons like network, application load, etc. In most cases, implementing retries should be able to solve the issues.
But sometimes there may be major issues like service degradation or complete service failure in and of itself. It’s pointless to keep retrying in such cases. That’s where the Circuit Breaker pattern can be useful.
Circuit Breaker. Image by the author.
The above diagram showcases the implementation of the Circuit Breaker pattern, where when Service 1 understands there are continuous failures/ timeouts when Service 2 is called, instead of retrying, Service 1 trips the calls to Service 2 and returns the fallback response.
There are popular open-source libraries, like Netflix’s Hystrix or Reselience4J, that can be used to implement this pattern very easily.
If you’re using API gateways or sidecar proxies like Envoy, then this can be achieved at the proxy level itself.
Note: It’s very important that there’s sufficient logging and alerting implemented when the circuit is open in order to keep track of requests received during this time and that the operations team is aware of this.
You can also implement a circuit breaker with the half circuit open to continue to service clients with degraded service.
When to use this pattern
When a service is dependent on another remote service, and it’s likely to fail in some scenarios
When a service has a very high dependency (for example, master data services)
When not to use this pattern | https://medium.com/better-programming/modern-day-architecture-design-patterns-for-software-professionals-9056ee1ed977 | ['Tanmay Deshpande'] | 2020-10-29 05:23:10.286000+00:00 | ['Software Engineering', 'Software Development', 'Software Architecture', 'Programming', 'Design Patterns'] | Title ModernDay Architecture Design Patterns Software ProfessionalsContent Circuit Breaker Distributed system designed taking failure consideration day world adopted microservices service mostly dependent remote service remote service could fail respond time due various reason like network application load etc case implementing retries able solve issue sometimes may major issue like service degradation complete service failure It’s pointless keep retrying case That’s Circuit Breaker pattern useful Circuit Breaker Image author diagram showcase implementation Circuit Breaker pattern Service 1 understands continuous failure timeouts Service 2 called instead retrying Service 1 trip call Service 2 return fallback response popular opensource library like Netflix’s Hystrix Reselience4J used implement pattern easily you’re using API gateway sidecar proxy like Envoy achieved proxy level Note It’s important there’s sufficient logging alerting implemented circuit open order keep track request received time operation team aware also implement circuit breaker half circuit open continue service client degraded service use pattern service dependent another remote service it’s likely fail scenario service high dependency example master data service use patternTags Software Engineering Software Development Software Architecture Programming Design Patterns |
973 | AWS — Amazon EKS vs ECS — Comparison | EKS vs ECS — Key differences:
Networking
With ECS, ENIs can be allocated to a ‘Task’, and an EC2 instance can support up to 120 tasks. With EKS, ENIs can be allocated to and shared between Kubernetes pods, enabling the user to place up to 750 Kubernetes pods per EC2 instance (depends on instance type) which achieves a much higher container density than ECS.
Ease of Deployment
ECS is a more straightforward platform while EKS is a little more complex and requires more configuration.
As ECS is AWS native solution, there is no control plane, Where as EKS is based on Kubernetes, there is a control plane (managed).
ECS is a fully managed service, it doesn’t have as many moving parts, components and functionality as k8s does. Once it is set up, users can start deploying tasks straight away from AWS console.
EKS is a bit trickier and requires a more complex deployment configuration and expertise. After setting it up in the AWS console, user is required to configure and deploy Pods via Kubernetes, using Kops.
Security
ECS and EKS, both supports IAM roles per task/container.
Previously, it was not possible to associate an IAM role to a container in EKS, but this functionality was added in late 2019.
Compatibility/Portability
ECS is an AWS proprietary technology, whereas EKS based on Kubernetes which is open source.
While both ECS and EKS are AWS-specific services, Kubernetes-as-a-service can be used with any cloud provider and on-premise. By using a managed Kubernetes service like EKS, you’re still investing in a cloud-agnostic platform, both in terms of tech and expertise. This isn’t the case for ECS, though, as it’s offered exclusively for AWS.
Pricing
For both, EKS and ECS — You simply pay for the compute resources consumed by your containers, whether that be on EC2 instances or serverless compute with Fargate.
EKS is subjected to an additional cost of running Master nodes (Control plane), as EKS manages the master nodes (that run across multiple availability zones) separate from the worker nodes ($0.10/hour/cluster). While that’s not the case with ECS.
Community and Support
Kubernetes is an open-source platform with a large and ever-growing community behind that brings apparent advantages. On the other hand, being proprietary, ECS gets less community support, although you’ll have excellent corporate support from AWS.
Kubernetes (EKS) is way more widespread than ECS, given its multi-platform support.
Namespaces
Contrary to ECS, Kubernetes has the “namespaces” concept, which is a feature intended to isolate workloads running in the same cluster. This seems like an insignificant feature but it offers a lot of advantages.
For example, you could have staging and production namespaces running in the same cluster while sharing resources across environments, reducing spare capacity in your clusters. | https://medium.com/awesome-cloud/aws-amazon-eks-vs-amazon-ecs-comparison-difference-between-eks-and-ecs-7451abd23859 | ['Ashish Patel'] | 2020-10-13 18:25:40.417000+00:00 | ['Eks', 'AWS', 'Ecs', 'K8s', 'Kubernetes'] | Title AWS — Amazon EKS v ECS — ComparisonContent EKS v ECS — Key difference Networking ECS ENIs allocated ‘Task’ EC2 instance support 120 task EKS ENIs allocated shared Kubernetes pod enabling user place 750 Kubernetes pod per EC2 instance depends instance type achieves much higher container density ECS Ease Deployment ECS straightforward platform EKS little complex requires configuration ECS AWS native solution control plane EKS based Kubernetes control plane managed ECS fully managed service doesn’t many moving part component functionality k8s set user start deploying task straight away AWS console EKS bit trickier requires complex deployment configuration expertise setting AWS console user required configure deploy Pods via Kubernetes using Kops Security ECS EKS support IAM role per taskcontainer Previously possible associate IAM role container EKS functionality added late 2019 CompatibilityPortability ECS AWS proprietary technology whereas EKS based Kubernetes open source ECS EKS AWSspecific service Kubernetesasaservice used cloud provider onpremise using managed Kubernetes service like EKS you’re still investing cloudagnostic platform term tech expertise isn’t case ECS though it’s offered exclusively AWS Pricing EKS ECS — simply pay compute resource consumed container whether EC2 instance serverless compute Fargate EKS subjected additional cost running Master node Control plane EKS manages master node run across multiple availability zone separate worker node 010hourcluster that’s case ECS Community Support Kubernetes opensource platform large evergrowing community behind brings apparent advantage hand proprietary ECS get le community support although you’ll excellent corporate support AWS Kubernetes EKS way widespread ECS given multiplatform support Namespaces Contrary ECS Kubernetes “namespaces” concept feature intended isolate workload running cluster seems like insignificant feature offer lot advantage example could staging production namespaces running cluster sharing resource across environment reducing spare capacity clustersTags Eks AWS Ecs K8s Kubernetes |
974 | Monday’s Review of Broken Things | Several unlikely gears managed to grind to a new position this past week increasing the stress on all of us. What were once smoothly running machines are struggling to break free from obstruction in many. Obstruction is a major thing now. The resulting pressures are stressing the entire planet but particularly the old government machinery that is more and more out of alignment.
The gear analogy seems increasingly appropriate as we are being brought down by problems, not in the new fully electronic systems, but the old mechanical ones. That has been a nasty surprise as we now know the difference between mechanical systems and fully electronic systems that, whatever their problems to be discovered, are incredibly more efficient and easier to maintain. Unless they are filled with very old code but that is another story and a different analogy.
Naturally now these problems are appearing in old mechanical systems that should have long since been replaced but have not. Like everything else from now on everything is interrelated and integrated and that includes failure at multiple levels.
For 18th century representative governments, the foundational gears for the modern nation state, the whole thing is really beginning to look like it needs to be pushed behind the barn and left to rust.
The American Trump disaster has reached the point that some whole mechanisms have ground to a halt while others are spinning out of control and may explode into flying gears and sharp pieces. Needless to say a recently installed and important piece has proven to be really shoddy, poorly designed and just defective. That piece, called Trump, didn’t fit at all and is obviously jamming itself in a way that may not be repairable. And our warranty lapsed a couple centuries ago.
The systems that installed that piece are also defective or this wouldn’t have happened. Now this is going to require a full overhaul and no one knows how to do that anymore. Many people are trying to pretend they don’t hear the knocks, bangs and frightening racket but everyone else is trying to figure out if the whole thing is going to end up catching fire and exploding. Trump is wearing out very fast and has been stripping teeth and may end up being only a spinning disk that doesn’t engage with anyone but himself. We’re almost there.
Things are bad enough that Americans are seriously trying to do the right thing at the death of Senator John McCain. But what is that? He was a heroic prisoner of war who spent his life working fairly independently and, often, saying what needed to be said. But he was firmly committed to a party that has disintegrated into a criminal gang and brought Sarah Palin into national politics. We are all prone to hubris and mistakes and he, unlike almost everyone else in modern politics, admitted error and took responsibility. But, in the end, I think he will pay the historical price for going along when he should have called bullshit and gotten out.
Our only surviving political hero made terrible choices that contributed to the disintegration of the system and now, even he, is gone. And he took the last vestiges of national political honor with him. Who wants to die and be remembered for Sarah Palin?
Just to cover the other aging mechanical things throwing gears and parts as they disintegrate, Britain is facing BREXIT without an exit agreement that makes the disaster exactly what it was always going to be. All because the oldest parts of the population, in attitudes not necessarily age, are too crude for 21st century diversity. They only want to sync with old, rough 19th century gear trains, and want to grind up all other kinds. Not a way to survive but they will learn that eventually, I hope.
Australia, that seemed to be trundling along at least, started grinding badly with gears at the top of the government grinding badly. No one seems even sure exactly how many things have broken. That’s a really bad sign. Clunk, screech, clunk. | https://mike-meyer.medium.com/mondays-review-of-broken-things-f5fe5bc5f8ed | ['Mike Meyer'] | 2018-08-27 06:43:23.706000+00:00 | ['Artificial Intelligence', 'Automation', 'Future', 'Self Driving Cars', 'Culture'] | Title Monday’s Review Broken ThingsContent Several unlikely gear managed grind new position past week increasing stress u smoothly running machine struggling break free obstruction many Obstruction major thing resulting pressure stressing entire planet particularly old government machinery alignment gear analogy seems increasingly appropriate brought problem new fully electronic system old mechanical one nasty surprise know difference mechanical system fully electronic system whatever problem discovered incredibly efficient easier maintain Unless filled old code another story different analogy Naturally problem appearing old mechanical system long since replaced Like everything else everything interrelated integrated includes failure multiple level 18th century representative government foundational gear modern nation state whole thing really beginning look like need pushed behind barn left rust American Trump disaster reached point whole mechanism ground halt others spinning control may explode flying gear sharp piece Needless say recently installed important piece proven really shoddy poorly designed defective piece called Trump didn’t fit obviously jamming way may repairable warranty lapsed couple century ago system installed piece also defective wouldn’t happened going require full overhaul one know anymore Many people trying pretend don’t hear knock bang frightening racket everyone else trying figure whole thing going end catching fire exploding Trump wearing fast stripping teeth may end spinning disk doesn’t engage anyone We’re almost Things bad enough Americans seriously trying right thing death Senator John McCain heroic prisoner war spent life working fairly independently often saying needed said firmly committed party disintegrated criminal gang brought Sarah Palin national politics prone hubris mistake unlike almost everyone else modern politics admitted error took responsibility end think pay historical price going along called bullshit gotten surviving political hero made terrible choice contributed disintegration system even gone took last vestige national political honor want die remembered Sarah Palin cover aging mechanical thing throwing gear part disintegrate Britain facing BREXIT without exit agreement make disaster exactly always going oldest part population attitude necessarily age crude 21st century diversity want sync old rough 19th century gear train want grind kind way survive learn eventually hope Australia seemed trundling along least started grinding badly gear top government grinding badly one seems even sure exactly many thing broken That’s really bad sign Clunk screech clunkTags Artificial Intelligence Automation Future Self Driving Cars Culture |
975 | Python Pandas: A Complete Guide for Beginners | Pandas is a python library used in data manipulation ( create, delete, and update the data).
It is one of the most commonly used libraries for data analysis in python. Pandas offer data structures and operations for manipulating numerical and time-series data. Pandas is the go-to library when it comes to Python
[pandas] is derived from the term “panel data”, an econometrics term for data sets that include observations over multiple time periods for the same individuals. — Wikipedia
Pandas Use Cases
Calculate statistics and answer questions about the data (Mean, Median, Mode)
Check correlation between Two datasets
See the distribution of values of a dataset
Clean the data by removing missing values or filtering rows and columns by some criteria
Visualize the data with help from Matplotlib. Plot bars, lines, histograms, bubbles, and more.
Store the cleaned, transformed data back into a CSV, another file.
Rise of Popularity of Pandas:https://theatlas.com/charts/rJ9sZ5syf
Pandas Setup
Pandas is an easy package to install. Open up your terminal program (for Mac users) or command line (for PC users) and install it using either of the following commands:
conda install pandas
OR
pip install pandas
import pandas as pd
Reading Data
In pandas, we have a function name as read_csv which is used to read .csv files.Similarly to import a JSON file we use read_json .
import pandas as pd
df = pd.read_csv('data.csv')
#data.csv is the relative filepath for data df = pd.read_json(‘data.json’)
DataFrame operations
DataFrames possess hundreds of methods and other operations that are crucial to any analysis. As a beginner, you should know the operations that perform simple transformations of your data and those that provide fundamental statistical analysis.
df = pd.read_csv("Data.csv", index_col="Heading")
Viewing your data
The first thing to do when opening a new dataset is to print out a few rows to keep as a visual reference. We accomplish this with .head() :
df.head()
.head() outputs the first five rows of your DataFrame by default, but we could also pass a number as well: df.head(10) would output the top ten rows, for example.
To see the last five rows use .tail() . tail() also accepts a number, and in this case, we print the bottom five rows.:
df.tail(5)
Get the info of your data
.info() should be one of the very first commands you run after loading your data:
df.info()
OUT:
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 100 entries, 0 to 99
Data columns (total 2 columns):
0 100 non-null float64
1 100 non-null float64
dtypes: float64(2)
memory usage: 1.6 KB
.info() provides the essential details about your dataset, such as the number of rows and columns, the number of non-null values, what type of data is in each column, and how much memory your DataFrame is using.
Calling .info() will quickly point out that the column you thought was all integers are actually strung objects.
Another fast and useful attribute is .shape , which outputs just a tuple of (rows, columns):
df.shape (100, 2)
Note that .shape has no parentheses and is a simple tuple of format (rows, columns). So we have 1000 rows and 2 columns in our movies DataFrame.
Column cleanup
Many times datasets will have verbose column names with symbols, upper and lowercase words, spaces, and typos. To make selecting data by column name easier we can spend a little time cleaning up their names.
Here’s how to print the column names of our dataset:
X= -2 * np.random.rand(100,2)
Y = 1 + 2 * np.random.rand(100,2)
df=pd.DataFrame(X,Y)
df.columns={
"RANDOM X","RANDOM Y"} print(df.columns) Index(['RANDOM Y', 'RANDOM X'], dtype='object')
Missing values
When exploring data, you’ll most likely encounter missing or null values, which are essentially placeholders for non-existent values. Most commonly you’ll see Python’s None or NumPy's np.nan , each of which is handled differently in some situations.
df.isnull().sum() RANDOM Y 0
RANDOM X 0
dtype: int64
.isnull() just by itself isn't very useful, and is usually used in conjunction with other methods, like sum() .
df.dropna(axis=1)
You can drop columns with null values by setting axis=0 or rows by setting axis=1
Understanding your variables
Using describe() on an entire DataFrame we can get a summary of the distribution of continuous variables:
df.describe()
Output
Relationships between variables
By using the correlation method .corr() we can generate the relationship between each continuous variable:
df.corr()
Corr between X and Y
Extracting Data
By column
You already saw how to extract a column using square brackets like this:
X_col = df[‘RandomX’]
type(X_col)
pandas.core.series.Series
By Rows
For rows, we have two options:
.loc - loc ates by name
- ates by name .iloc - locates by numerical index
Conditional Selection
df[df[‘RANDOM X’] >= -10].head(3)
X≥-10
Plotting
Another great thing about pandas is that it integrates with Matplotlib, so you get the ability to plot directly off DataFrames and Series. To get started we need to import Matplotlib ( pip install matplotlib ):
import matplotlib.pyplot as plt
plt.rcParams.update({‘font.size’: 20, ‘figure.figsize’: (10, 8)}) # set font and plot size to be larger
df.plot(kind='scatter', x='RANDOM X', y='RANDOM Y', title='X vs Y')
Scatter Plot
df[‘RANDOM X’].plot(kind=’hist’, title=’X’)
Histogram of X
Using a Boxplot we can visualize this data:
df[‘RANDOM X’].plot(kind=’box’)
That’s It!
Exploring, cleaning, transforming, and visualization data with pandas in Python is an essential skill in data science.
Just cleaning wrangling data is 50% of your job as a Data Scientist. Thanks for reading!
Found this article useful? Follow me (Rahula Raj) on Medium and check out my most popular articles below! Please 👏 this article to share it! | https://medium.com/analytics-vidhya/python-pandas-a-complete-guide-for-beginners-a695a3aa3596 | ['Rahul Raj'] | 2020-10-16 13:09:35.899000+00:00 | ['Machine Learning', 'Pandas', 'Python', 'AI', 'Data Science'] | Title Python Pandas Complete Guide BeginnersContent Pandas python library used data manipulation create delete update data one commonly used library data analysis python Pandas offer data structure operation manipulating numerical timeseries data Pandas goto library come Python panda derived term “panel data” econometrics term data set include observation multiple time period individual — Wikipedia Pandas Use Cases Calculate statistic answer question data Mean Median Mode Check correlation Two datasets See distribution value dataset Clean data removing missing value filtering row column criterion Visualize data help Matplotlib Plot bar line histogram bubble Store cleaned transformed data back CSV another file Rise Popularity PandashttpstheatlascomchartsrJ9sZ5syf Pandas Setup Pandas easy package install Open terminal program Mac user command line PC user install using either following command conda install panda pip install panda import panda pd Reading Data panda function name readcsv used read csv filesSimilarly import JSON file use readjson import panda pd df pdreadcsvdatacsv datacsv relative filepath data df pdreadjson‘datajson’ DataFrame operation DataFrames posse hundred method operation crucial analysis beginner know operation perform simple transformation data provide fundamental statistical analysis df pdreadcsvDatacsv indexcolHeading Viewing data first thing opening new dataset print row keep visual reference accomplish head dfhead head output first five row DataFrame default could also pas number well dfhead10 would output top ten row example see last five row use tail tail also accepts number case print bottom five row dftail5 Get info data info one first command run loading data dfinfo class pandascoreframeDataFrame RangeIndex 100 entry 0 99 Data column total 2 column 0 100 nonnull float64 1 100 nonnull float64 dtypes float642 memory usage 16 KB info provides essential detail dataset number row column number nonnull value type data column much memory DataFrame using Calling info quickly point column thought integer actually strung object Another fast useful attribute shape output tuple row column dfshape 100 2 Note shape parenthesis simple tuple format row column 1000 row 2 column movie DataFrame Column cleanup Many time datasets verbose column name symbol upper lowercase word space typo make selecting data column name easier spend little time cleaning name Here’s print column name dataset X 2 nprandomrand1002 1 2 nprandomrand1002 dfpdDataFrameXY dfcolumns RANDOM XRANDOM printdfcolumns IndexRANDOM RANDOM X dtypeobject Missing value exploring data you’ll likely encounter missing null value essentially placeholder nonexistent value commonly you’ll see Python’s None NumPys npnan handled differently situation dfisnullsum RANDOM 0 RANDOM X 0 dtype int64 isnull isnt useful usually used conjunction method like sum dfdropnaaxis1 drop column null value setting axis0 row setting axis1 Understanding variable Using describe entire DataFrame get summary distribution continuous variable dfdescribe Output Relationships variable using correlation method corr generate relationship continuous variable dfcorr Corr X Extracting Data column already saw extract column using square bracket like Xcol df‘RandomX’ typeXcol pandascoreseriesSeries Rows row two option loc loc ate name ate name iloc locates numerical index Conditional Selection dfdf‘RANDOM X’ 10head3 X≥10 Plotting Another great thing panda integrates Matplotlib get ability plot directly DataFrames Series get started need import Matplotlib pip install matplotlib import matplotlibpyplot plt pltrcParamsupdate‘fontsize’ 20 ‘figurefigsize’ 10 8 set font plot size larger dfplotkindscatter xRANDOM X yRANDOM titleX v Scatter Plot df‘RANDOM X’plotkind’hist’ title’X’ Histogram X Using Boxplot visualize data df‘RANDOM X’plotkind’box’ That’s Exploring cleaning transforming visualization data panda Python essential skill data science cleaning wrangling data 50 job Data Scientist Thanks reading Found article useful Follow Rahula Raj Medium check popular article Please 👏 article share itTags Machine Learning Pandas Python AI Data Science |
976 | Where Would We Be Without Music? | richard hewat for Unsplash
Where Would We Be Without Music?
Fortunately, it won’t be shut down
He who sings scares away his woes. — Cervantes , writer
Music events may have been cancelled because of the coronavirus pandemic, but we may need music in our lives more than ever. Lucky for us, there isn’t a way to make it go away.
If we can’t go to bars and concert halls to hear live music, we can stream nearly unlimited performances of every genre into our homes if we are lucky to have an internet connection. We are also free to make our own music in our homes and in the streets.
We like to listen to music when we are both happy and sad. Upbeat tunes lift our mood, and sad ones can make us feel as if someone understands us.
From Psychology Today:
Upbeat songs of your own choosing can pull you out of a funk but sad tunes can do the same. Freud wrote that we feel better when we are exposed to art with pathos because we feel understood, as if we are not alone, and that we are connected to a clan of like-minded beings. Further, we experience the artist as a benevolent figure who sees, cares, guides, and expresses what we might not be able to voice ourselves. | https://medium.com/narrative/where-would-we-be-without-music-f3fe19c41a6b | ['Victoria Ponte'] | 2020-05-20 21:40:20.978000+00:00 | ['Coping Strategies', 'Self', 'Music', 'Mental Health', 'Pandemic'] | Title Would Without MusicContent richard hewat Unsplash Would Without Music Fortunately won’t shut sings scare away woe — Cervantes writer Music event may cancelled coronavirus pandemic may need music life ever Lucky u isn’t way make go away can’t go bar concert hall hear live music stream nearly unlimited performance every genre home lucky internet connection also free make music home street like listen music happy sad Upbeat tune lift mood sad one make u feel someone understands u Psychology Today Upbeat song choosing pull funk sad tune Freud wrote feel better exposed art pathos feel understood alone connected clan likeminded being experience artist benevolent figure see care guide express might able voice ourselvesTags Coping Strategies Self Music Mental Health Pandemic |
977 | Re-animated History | Get this newsletter By signing up, you will create a Medium account if you don’t already have one. Review our Privacy Policy for more information about our privacy practices.
Check your inbox
Medium sent you an email at to complete your subscription. | https://medium.com/merzazine/re-animated-history-4c2692e03aa6 | ['Vlad Alex', 'Merzmensch'] | 2020-09-07 15:34:03.213000+00:00 | ['Published Tds', 'Artificial Intelligence', 'AI', 'Ai And Creativity', 'Culture'] | Title Reanimated HistoryContent Get newsletter signing create Medium account don’t already one Review Privacy Policy information privacy practice Check inbox Medium sent email complete subscriptionTags Published Tds Artificial Intelligence AI Ai Creativity Culture |
978 | Why I Write, and How it Changed Me | Photo Credit: Green Chameleon
“Why would a hard-nosed businessman become a writer?”
I didn’t know what to say to the middle-aged woman who asked the question at a talk I gave a few weeks ago. I finally replied with something sufficiently vague that she just nodded and sat down.
That evening after the talk, I thought about her question more seriously.
I did so the only way I knew how — by writing about it. The only way that any thought of mine can become intelligible (to me or anyone else) is by going through my process, which always means it ends up in written form.
Stephen King famously said, “Writing is refined thinking.”
My thinking process starts with a particular question or thought that dominates my mind for hours and days. I keep reflecting on it, unconsciously discussing it with myself, and finally putting pen to paper in my journal. From there, my thoughts might expand to a blog post, a talk, a task at work, or a project. I then revise and refine again and again till I have a final product.
My process of thinking — how my words reach paper — is similar to the preparation of coffee. Coffee passes through many levels of refinement before arriving at our palate in liquid form. Raw beans are roasted, ground, mixed with hot water, and then finally strained and served.
So it is with thoughts.
My interest in writing emerged almost five years ago when I began writing “Morning Pages” as heralded by Julia Cameron in The Artist’s Way. I would decipher my dreams, then go on to analyze my previous day’s actions and consider in more depth the fears that were holding me back. I would also celebrate my victories, remind myself of all my good qualities, and appreciate the people and things in my life.
Writing has become like breathing to me; I must write to keep living. It has become my way of making sense of myself.
I don’t write for my loved ones. I don’t write to promote my business. I write for me.
We all need to have that “one thing” at our core — a vehicle for going deep into our essence, exploring the mysterious places of our heart, venturing into our past, and confronting painful moments stored away in our subconscious.
Through this creative endeavor, we face the stored up hurt rather than judging or numbing our feelings away for fear of meeting them. We allow our highest self to express.
In the last few years, my interest has grown into a passion. Writing and I have become one. Writing is me, and I am writing. Writing is now the foundation on which I lay all other building blocks to produce a better life for myself.
Writing transformed me. It released me from the shackles that had held me back since childhood. It has led to many of my spiritual trysts, wherein I meet my true self and feel the power of grace within me. It has penetrated deep into my soul, always asking and forever searching for the best way to be authentic.
I am still in my toddler years as a writer, but already writing has taught me many lessons that I can apply in my life. It has stripped me of my arrogant egoic ways and taken me out of the closed-box mentality that defined me for so many years.
I have been consistently blogging for the past two years, with one blog post per week. I rise early, meditate for twenty minutes, read for another thirty minutes while having my coffee, and then finally journal my thoughts for twenty minutes. These written thoughts then germinate in my mind. When I come back from work in the late afternoon, I find myself ready to write the first draft of a blog post or some words toward a book chapter.
This discipline of sharing myself — my soul — has not only changed me, but has also inspired many others to dig deeper into their hearts and lives. It has culminated in my first book, The Shift, in which I discuss the various human experiences that resonate with all of us.
I know that if I remain faithful to my writing and work to strengthen my inner voice, then I will become more consistently connected to my higher self.
And ultimately, this connection will bring greater mastery of the craft and broader service to humanity.
This is why I write, and why I will keep writing. | https://medium.com/emphasis/why-i-write-and-how-it-changed-me-6afb7ed00a16 | ['Mo Issa'] | 2017-11-23 14:04:41.669000+00:00 | ['Passion', 'Writing', 'Creativity', 'Lessons', 'Purpose'] | Title Write Changed MeContent Photo Credit Green Chameleon “Why would hardnosed businessman become writer” didn’t know say middleaged woman asked question talk gave week ago finally replied something sufficiently vague nodded sat evening talk thought question seriously way knew — writing way thought mine become intelligible anyone else going process always mean end written form Stephen King famously said “Writing refined thinking” thinking process start particular question thought dominates mind hour day keep reflecting unconsciously discussing finally putting pen paper journal thought might expand blog post talk task work project revise refine till final product process thinking — word reach paper — similar preparation coffee Coffee pass many level refinement arriving palate liquid form Raw bean roasted ground mixed hot water finally strained served thought interest writing emerged almost five year ago began writing “Morning Pages” heralded Julia Cameron Artist’s Way would decipher dream go analyze previous day’s action consider depth fear holding back would also celebrate victory remind good quality appreciate people thing life Writing become like breathing must write keep living become way making sense don’t write loved one don’t write promote business write need “one thing” core — vehicle going deep essence exploring mysterious place heart venturing past confronting painful moment stored away subconscious creative endeavor face stored hurt rather judging numbing feeling away fear meeting allow highest self express last year interest grown passion Writing become one Writing writing Writing foundation lay building block produce better life Writing transformed released shackle held back since childhood led many spiritual tryst wherein meet true self feel power grace within penetrated deep soul always asking forever searching best way authentic still toddler year writer already writing taught many lesson apply life stripped arrogant egoic way taken closedbox mentality defined many year consistently blogging past two year one blog post per week rise early meditate twenty minute read another thirty minute coffee finally journal thought twenty minute written thought germinate mind come back work late afternoon find ready write first draft blog post word toward book chapter discipline sharing — soul — changed also inspired many others dig deeper heart life culminated first book Shift discus various human experience resonate u know remain faithful writing work strengthen inner voice become consistently connected higher self ultimately connection bring greater mastery craft broader service humanity write keep writingTags Passion Writing Creativity Lessons Purpose |
979 | Tissue Stiffness Regulates Immune Responses | Cells are remarkably sensitive to the mechanical properties of their environment, changing their behavior as a result of physical forces exerted by the surrounding tissues. Over the last 20 years, scientists have uncovered that this phenomenon, known as mechanosensing, dictates a plethora of cellular responses, from cell division and differentiation to the activation of the immune system.
After a sprain, for example, joints swell and become stiff and mechanically rigid. How the physics of this tissue rigidity influences the dynamics of immune cells such as T and B lymphocytes, however, has remained unknown.
A team of researchers at UCLA may have found a missing piece of this puzzle: a molecule called yes-associated protein, or YAP. Through a series of experiments using genetically-modified mice, they found that T cells use YAP as a sensor of tissue rigidity, responding to these mechanical cues by either accelerating inflammation or hitting the brakes on it.
The study’s senior author, Manish J. Butte explains, “In cases of both autoimmune activity and fighting off infection, YAP acts as an accelerator of the immune response in stiff tissues, and as a brake when there is mechanical softness.” Specifically, YAP is able to access the metabolic control panel of T cells, flicking the switch for increased nutrient uptake to cope with a spike in energy requirements upon sensing tissue rigidity.
This new paradigm of immune system regulation has significant implications on future therapeutic strategies for diseases that have an immune component: autoimmune diseases, chronic infections, and some forms of cancer.
“This is a whole new pathway that can be targeted to drive up immune responses in order to better fight infections, or slow down immune activity in conditions such as diabetes,” said Butte. YAP-driven pathways are a prime target for potential drug targets and the subject of future research.
In follow up studies, Butte and colleagues plan to investigate whether YAP’s molecular pathways could be leveraged to treat mechanically rigid tumors, such as pancreatic and breast cancers. The team hypothesizes that YAP’s keen ability to sense tissue stiffness could be leveraged to amplify anti-tumor immune responses.
Sources: News Medical Life Sciences, Journal of Experimental Medicine. | https://tlfern.medium.com/tissue-stiffness-regulates-immune-responses-140499597958 | ['Tara Fernandez'] | 2020-06-04 17:15:39.695000+00:00 | ['Medicine', 'Health', 'Cell Biology', 'Science', 'Immunology'] | Title Tissue Stiffness Regulates Immune ResponsesContent Cells remarkably sensitive mechanical property environment changing behavior result physical force exerted surrounding tissue last 20 year scientist uncovered phenomenon known mechanosensing dictate plethora cellular response cell division differentiation activation immune system sprain example joint swell become stiff mechanically rigid physic tissue rigidity influence dynamic immune cell B lymphocyte however remained unknown team researcher UCLA may found missing piece puzzle molecule called yesassociated protein YAP series experiment using geneticallymodified mouse found cell use YAP sensor tissue rigidity responding mechanical cue either accelerating inflammation hitting brake study’s senior author Manish J Butte explains “In case autoimmune activity fighting infection YAP act accelerator immune response stiff tissue brake mechanical softness” Specifically YAP able access metabolic control panel cell flicking switch increased nutrient uptake cope spike energy requirement upon sensing tissue rigidity new paradigm immune system regulation significant implication future therapeutic strategy disease immune component autoimmune disease chronic infection form cancer “This whole new pathway targeted drive immune response order better fight infection slow immune activity condition diabetes” said Butte YAPdriven pathway prime target potential drug target subject future research follow study Butte colleague plan investigate whether YAP’s molecular pathway could leveraged treat mechanically rigid tumor pancreatic breast cancer team hypothesizes YAP’s keen ability sense tissue stiffness could leveraged amplify antitumor immune response Sources News Medical Life Sciences Journal Experimental MedicineTags Medicine Health Cell Biology Science Immunology |
980 | The Most Important Race in Tech | The difference between classical and quantum computers can be represented by Google’s claim to quantum supremacy in 2019. To achieve this claim of quantum supremacy, one of Google’s 53 qubit quantum computers (called ‘Sycamore’) was able to do a calculation in just over 3 minutes when it would have taken even the world’s most powerful classical computer over 10,000 years to process the same calculation. There has been some dispute over this claim by rival company IBM who says that the calculation would have taken a matter of days and not the tens of thousands of years that Google claimed. But the main idea behind this computing transformation persists. Quantum tech aims to be faster, more efficient, and revolutionary in ways its classical counterparts never will be. And it’s able to do this because of one advantage in particular.
When classical computers store their information it’s either as a 1 or a 0. These 1’s and 0’s we call ‘bits’. But quantum computers can leverage a property known as superposition where their quantum bits (‘qubits’) can be a 1, a 0, both a 1 and a 0 at the same time, or some combination of both numbers. By taking advantage of the quantum trait of superposition these new computers can make great computational strides where classical technology just isn’t enough. The fact that subatomic particles like electrons exist in a superposition of states makes it difficult for classical computers to simulate them. This ability to simulate particles and their quantum properties is how quantum computers succeed where classical computers fail.
A visualization of classical computer bits and the larger range of qubits. Image by Pranith Hengavalli.
Yet despite their computational prowess and their promises for the future, quantum computers are really quite fickle machines. Their chips function only at temperatures close to absolute zero (−459.67 °F or −273.15 °C). The focus for qubits has been, up until now, using small superconducting loops. The oscillations of these loops means that they are systems with 2 possible quantum states, making them a viable basis for a qubit. But attention has recently turned to trapped-ion systems, a technology that formed the basis of quantum circuits before superconducting loops were in use.
Trapped-ion systems use the energy level of ions trapped in electric fields to form the computer’s qubits. The quantum states of the ions last longer than their superconducting counterparts. And where superconducting qubits only interact with other nearby qubits, the ions’ interactions are widespread and allow them to run certain complex calculations more easily. They are, however, slower at these interactions, something which may hurt their ability to correct realtime errors.
Within the world of quantum computing there is a race between materials as much as there is a race between countries. | https://medium.com/predict/the-most-important-race-in-tech-4c175a541266 | ['Ella Alderson'] | 2020-12-03 21:05:17.792000+00:00 | ['Technology', 'Science', 'Tech', 'Politics', 'Future'] | Title Important Race TechContent difference classical quantum computer represented Google’s claim quantum supremacy 2019 achieve claim quantum supremacy one Google’s 53 qubit quantum computer called ‘Sycamore’ able calculation 3 minute would taken even world’s powerful classical computer 10000 year process calculation dispute claim rival company IBM say calculation would taken matter day ten thousand year Google claimed main idea behind computing transformation persists Quantum tech aim faster efficient revolutionary way classical counterpart never it’s able one advantage particular classical computer store information it’s either 1 0 1’s 0’s call ‘bits’ quantum computer leverage property known superposition quantum bit ‘qubits’ 1 0 1 0 time combination number taking advantage quantum trait superposition new computer make great computational stride classical technology isn’t enough fact subatomic particle like electron exist superposition state make difficult classical computer simulate ability simulate particle quantum property quantum computer succeed classical computer fail visualization classical computer bit larger range qubits Image Pranith Hengavalli Yet despite computational prowess promise future quantum computer really quite fickle machine chip function temperature close absolute zero −45967 °F −27315 °C focus qubits using small superconducting loop oscillation loop mean system 2 possible quantum state making viable basis qubit attention recently turned trappedion system technology formed basis quantum circuit superconducting loop use Trappedion system use energy level ion trapped electric field form computer’s qubits quantum state ion last longer superconducting counterpart superconducting qubits interact nearby qubits ions’ interaction widespread allow run certain complex calculation easily however slower interaction something may hurt ability correct realtime error Within world quantum computing race material much race countriesTags Technology Science Tech Politics Future |
981 | How I Actually Quit Smoking in 2020 | A brief history of quitting
Of course, I knew smoking was bad for me. I’d known for years. I remember taking the “Smoke Free Class of 2000” pledge in fifth grade. I remember cigarette smoke annoying my lungs as a child. There wasn’t one cigarette out of the roughly 10,000+ I smoked where I thought, “man, I’m so glad I picked this up.”
As it turned out, the best thing for curtailing my smoking habit over the years was being broke — the easiest way to ensure I wouldn’t buy a pack was to ensure that I couldn’t afford one. Failing to clear $40K per year until my 30s, and being buried under a devastating mountain of debt until 32 allowed me to go a couple days in between packs. But all I could think about in between dire straights and direct deposit was the next pack. Sometimes I’d go a week. Mostly less. And, as a musician, I could always pick up a gig, drink for free and bum a stick before buying a pack downtown after I’d collected my customary $100 in tips.
I tried the gum in 2006 but it didn’t take. I tried a phase-out approach in 2013 to no avail. Toward the end of 2017 as I was drying out, my doctor prescribed Chantix. This actually worked, but during weeks when I knew I’d have a busy social calendar, I’d abstain from the little blue pills so I could properly enjoy the sweet release of nicotine into my veins in the company of fellow revelers. That didn’t stop me from filling the prescription anyway. With insurance they were cheap AF and someday I knew I would want them.
Every time I made quarter-assed attempts to quit — which of course I swore I would do, as every smoker knows every pack is their “last pack” — I tried to time my last drink with my last cigarette. This is a terrible strategy. There’s a six-pack of beer and 20 cigarettes in a pack. The math never works out.
I found I was drinking and smoking much less in 2019, so I gave quitting a go again near the start of 2020, but the pandemic dashed — along with pretty much everyone’s plans, the global economy, and the national social order of things—that well-intentioned objective. I spent most of the spring isolated and drowning myself in wine and nicotine, spending hours on the phone with people I’d probably never meet or see again. Then, unbelievably, I met my current boo and it was the kick in the ass I used as an excuse to get my ass in proper gear.
If I’m paranoid enough to go into a self-imposed Stage-5 lockdown until they stab me, I should also be paranoid enough to kick my butts goodbye.
Wheezing and woozy, and unable to run my customary 5K in less time than it takes for me to write an essay, I decided to try one more time. I thought, “you know, it’s been a solid baker’s-dozen years since you last had a local romantic partner, perhaps you, Mr. Gorman, could try and ease up off the smokes so you can stick around on this Earth longer in the event that you want to build a future with her.” At least that was the excuse I gave myself, as if I’d never dated a nonsmoker before. (I have. Trust me, that wasn’t enough to move my needle.)
The truth of my reasoning was slightly more ridiculous: After I resigned myself to this pandemic lasting pretty much forever—and it’s thus far gobbled up 2.5% of my time alive on Earth — I got scared straight. Although I’m young, Covid-19 could still get me killed, and smoking is the one demonstrated risk factor I had control over. Despite the mild protective shield of my Type-O blood, my immunodeficiency and lifelong asthma are plenty pronounced enough to cause me concern should I come in contact with this thing.
I want to make it to vaccination day, and I have a great life ahead of me on the other side of this hellhole. If I’m paranoid enough to go into a self-imposed Stage-5 lockdown until they stab me, I should also be paranoid enough to kick my butts goodbye. So here we go. | https://humanparts.medium.com/i-actually-quit-smoking-in-2020-fd9fe6672cf1 | ['John Gorman'] | 2020-12-18 19:48:40.068000+00:00 | ['Health', '2020', 'Mental Health', 'This Is Us', 'Self Improvement'] | Title Actually Quit Smoking 2020Content brief history quitting course knew smoking bad I’d known year remember taking “Smoke Free Class 2000” pledge fifth grade remember cigarette smoke annoying lung child wasn’t one cigarette roughly 10000 smoked thought “man I’m glad picked up” turned best thing curtailing smoking habit year broke — easiest way ensure wouldn’t buy pack ensure couldn’t afford one Failing clear 40K per year 30 buried devastating mountain debt 32 allowed go couple day pack could think dire straight direct deposit next pack Sometimes I’d go week Mostly le musician could always pick gig drink free bum stick buying pack downtown I’d collected customary 100 tip tried gum 2006 didn’t take tried phaseout approach 2013 avail Toward end 2017 drying doctor prescribed Chantix actually worked week knew I’d busy social calendar I’d abstain little blue pill could properly enjoy sweet release nicotine vein company fellow reveler didn’t stop filling prescription anyway insurance cheap AF someday knew would want Every time made quarterassed attempt quit — course swore would every smoker know every pack “last pack” — tried time last drink last cigarette terrible strategy There’s sixpack beer 20 cigarette pack math never work found drinking smoking much le 2019 gave quitting go near start 2020 pandemic dashed — along pretty much everyone’s plan global economy national social order things—that wellintentioned objective spent spring isolated drowning wine nicotine spending hour phone people I’d probably never meet see unbelievably met current boo kick as used excuse get as proper gear I’m paranoid enough go selfimposed Stage5 lockdown stab also paranoid enough kick butt goodbye Wheezing woozy unable run customary 5K le time take write essay decided try one time thought “you know it’s solid baker’sdozen year since last local romantic partner perhaps Mr Gorman could try ease smoke stick around Earth longer event want build future her” least excuse gave I’d never dated nonsmoker Trust wasn’t enough move needle truth reasoning slightly ridiculous resigned pandemic lasting pretty much forever—and it’s thus far gobbled 25 time alive Earth — got scared straight Although I’m young Covid19 could still get killed smoking one demonstrated risk factor control Despite mild protective shield TypeO blood immunodeficiency lifelong asthma plenty pronounced enough cause concern come contact thing want make vaccination day great life ahead side hellhole I’m paranoid enough go selfimposed Stage5 lockdown stab also paranoid enough kick butt goodbye goTags Health 2020 Mental Health Us Self Improvement |
982 | I Tried Calorie Cycling for 30 Days | My calorie cycling experience
Now that you understand the basics of calorie cycling and how to do your own 30-day challenge if you decide to, here’s my experience from day 1 through day 30 and the results.
Week 1
On day 1 of the challenge kickoff, I happened to be in the process of moving into my first home so I decided to give myself grace and start one day later.
Quick tip: Start when you’re ready. Calorie cycling doesn’t have to be complicated (in fact it shouldn’t be) but if you’re going through a rough time right now, maybe hold off a few days.
For my first attempt at calorie cycling, I wanted to try the alternate deficit method. However, on day 1 I ended up eating just at my calorie limit, not more or less as I should have when using this method. Throughout this challenge, I didn’t want to be too strict with myself. As long as I stay under my weekly calorie limit, I’m happy. This is after all an experiment.
Week 1 results
I ended up eating 324 calories over my deficit for the week, which comes to an average of about 46 calories more per day.
As to be expected, I nowhere near reached my protein level. Again, the protein level is more of a guide, a way to help you eat more healthy foods, keep you satiated, and avoid muscle loss. So I didn’t beat myself up when I didn’t meet the goal. Instead, I was proud that I reach over 100g on most days.
As for exercise, I completed 2 strength training workouts. Lower body on one day and upper body on another, each took about 30 minutes to complete. I also walked an average of just under 5,000 steps for the week.
How did this affect my weight?
According to the scale, I lost 3.2 lbs and 1.1% in body fat from my first week of calorie cycling. While that might sound like a successful first week, especially when I ate 324 calories over what I planned for the week, I proceeded with caution into week 2.
Quick tip: Remember, the goal is sustained weight loss over time, not a quick fix that leads to regain. I also know the scale isn’t the best measurement for success. I recommend using measurements as another way to gauge success at the end of the full 30-day challenge.
Week 2
I allowed myself flexibility in week 1 as I got used to calorie cycling. But this week, I tried to make a better effort to vary my calorie cycling more in the high and low days.
Week 2 results
I ended up eating 574 calories over my deficit for the week, which comes to an average of 82 calories more per day. At first glance, this week was a complete fail in remaining within my calorie goal. This is most likely due to the fact I consumed less protein in exchange for more carbs on a few of the days.
As for exercise, I completed two strength workouts. Full body on one day, lower body on another. Looking at the Health app on my iPhone, I noticed I only walked an average of 3,714 steps. This is definitely a lot lower so I plan to incorporate more movement into my exercise routine over the coming weeks.
How did this affect my weight?
According to the scale, I gained 1.8 pounds and 0.5% in body fat from my second week of calorie cycling. However, it’s still a net loss of 2.2 pounds since the start of the challenge which is good. Since I lost quite a bit the first week, it makes sense that it would level out or increase, especially with the addition of a couple hundred more calories.
Week 3
Since I didn’t feel like I made enough progress last week, I decided to make a more concentrated effort in eating less than my allotted calories for the week.
Week 3 results
I succeeded and ended up eating 77 calories under my deficit for the week. As for exercise, I only completed one upper-body strength workout and one 30-minute walk on a separate day.
How did this affect my weight?
This was the first week I ate under my deficit. I lost 1.4 pounds and 0.4% in body fat from the previous week. 3 weeks in and a total net loss of 2.8 pounds since the start of the challenge.
Week 4
Week 4 was a mess for me personally and unfortunately, it affected my eating and exercise habits.
Week 4 results
I ended up not fully tracking this week due to a couple of restaurant outings with family. I also didn’t do much exercise except for 1 walk.
How did this affect my weight?
No surprise, I ended up gaining 2.8 pounds.
Final results from calorie cycling
While my weight fluctuated throughout the month, I actually weighed the exact same on day 1 of the challenge as I did on the last day of the challenge. | https://medium.com/in-fitness-and-in-health/i-tried-calorie-cycling-for-30-days-1d19a2357c3a | ['Monica Galvan'] | 2020-11-26 16:23:07.498000+00:00 | ['Health', 'Fitness', 'Lifestyle', 'Nutrition', 'Wellness'] | Title Tried Calorie Cycling 30 DaysContent calorie cycling experience understand basic calorie cycling 30day challenge decide here’s experience day 1 day 30 result Week 1 day 1 challenge kickoff happened process moving first home decided give grace start one day later Quick tip Start you’re ready Calorie cycling doesn’t complicated fact shouldn’t you’re going rough time right maybe hold day first attempt calorie cycling wanted try alternate deficit method However day 1 ended eating calorie limit le using method Throughout challenge didn’t want strict long stay weekly calorie limit I’m happy experiment Week 1 result ended eating 324 calorie deficit week come average 46 calorie per day expected nowhere near reached protein level protein level guide way help eat healthy food keep satiated avoid muscle loss didn’t beat didn’t meet goal Instead proud reach 100g day exercise completed 2 strength training workout Lower body one day upper body another took 30 minute complete also walked average 5000 step week affect weight According scale lost 32 lb 11 body fat first week calorie cycling might sound like successful first week especially ate 324 calorie planned week proceeded caution week 2 Quick tip Remember goal sustained weight loss time quick fix lead regain also know scale isn’t best measurement success recommend using measurement another way gauge success end full 30day challenge Week 2 allowed flexibility week 1 got used calorie cycling week tried make better effort vary calorie cycling high low day Week 2 result ended eating 574 calorie deficit week come average 82 calorie per day first glance week complete fail remaining within calorie goal likely due fact consumed le protein exchange carbs day exercise completed two strength workout Full body one day lower body another Looking Health app iPhone noticed walked average 3714 step definitely lot lower plan incorporate movement exercise routine coming week affect weight According scale gained 18 pound 05 body fat second week calorie cycling However it’s still net loss 22 pound since start challenge good Since lost quite bit first week make sense would level increase especially addition couple hundred calorie Week 3 Since didn’t feel like made enough progress last week decided make concentrated effort eating le allotted calorie week Week 3 result succeeded ended eating 77 calorie deficit week exercise completed one upperbody strength workout one 30minute walk separate day affect weight first week ate deficit lost 14 pound 04 body fat previous week 3 week total net loss 28 pound since start challenge Week 4 Week 4 mess personally unfortunately affected eating exercise habit Week 4 result ended fully tracking week due couple restaurant outing family also didn’t much exercise except 1 walk affect weight surprise ended gaining 28 pound Final result calorie cycling weight fluctuated throughout month actually weighed exact day 1 challenge last day challengeTags Health Fitness Lifestyle Nutrition Wellness |
983 | Predictions for AI Developments in 2018 | Entering the new year, we are wondering what to expect from the new AI technologies and which directions to look at.
In this brief review, we offer some predictions for AI developments in 2018.
Since all indicators show the likely increase in investment into the development of AI and, particularly, machine learning, technologies, the world is expecting a new wave of AI applications. Most importantly, these applications are finally reaching beyond computers learning to beat humans at chess and TV game shows. In 2018, machine learning and neural network technologies will continue to refine themselves and take on more routine tasks — in all aspects of our lives.
Robotics
Yes, robots. In the Blade Runner universe, people have already mastered replicants manufacturing by 2019. On the verge of 2018, we are still far from that, but our coexistence with robots is already taking place.
2017 was all about toy robots, programmable robots and other kinds of educational robots for kids. In 2018, we’ll see programmable robot platforms, designed for adults, which are more sophisticated in their capabilities and offer more interesting and versatile robotics functionality. Additionally, more consumer robots will enter our lives as home helpers to remove friction from our daily routine.
Healthcare
Advancements in big data analysis and AI will play a major role in healthcare.
Maybe, the present-day encroachment of AI is still almost invisible to patients. Yet, new technologies will push the industry forwards, changing the way it operates and treats patients by optimizing workflows both within in-patient and out-patient scenarios. Behind the scenes of health examination, image recognition algorithms are already being used in pilot projects to spot warning signs buried in medical images and to decipher hand-written doctors’ notes. With these pilots being quite successful, we are likely to expect a boost of similar projects in the coming year.
Another important, and definitely more visible, development in healthcare is a greater involvement of robots in looking after the health and well-being of patients. Caregivers and companion robots are expected to gain popularity and could begin to become an everyday reality in 2018.
Communication
The next year is likely to change our interaction with machines, and conversational interfaces will become common when it comes to interacting with technology in a business environment. This year’s estimates are that in 2018 about 20% of firms will look to add voice enabled interfaces to their existing point-and-click dashboards and systems.
Natural language generation and natural language processing algorithms are constantly learning to become more tuned to understanding us, and talking to us in a way we understand. In 2018 they will continue to improve and we should get used to robots which we can converse with in a more human-like manner.
In the nearest future, we are likely to see an increased focus on bot sensitivity training, which will allow humans to offload even more work on chatbot shoulders both in business and in the everyday life: while a new virtual assistant by X.ai called “Amy” can respond to messages regarding meetings, meals, and calls, Amazon’s Alexa recently began syncing with Outlook and Google to help families keep up with their schedules.
Data-Driven Machines
Big data may sound less exciting android creation, but it’s what will be the focus of most companies’ work next year. Pushed by the steady growth of data produced by the Internet of Things, businesses will turn to machine learning to process, trend, and analyze the received information. In 2018, machine learning will become an absolute must-have for companies wishing to make sense of structured or unstructured data. With humans unable to process this overwhelming data flow, the key strategy will be to call AI with large-scale analytics into play.
Processing of big data will change the way businesses are run, simultaneously improving the security monitoring by anomaly detection and prediction of stock-exchange and market trends. Enabling more precise clustering of customer groups, and developing smart cross-sale by tracking the sales vs. ranks for all products in various categories, machine learning will boost the sales and proclaim a new era for commerce.
Whatever changes in our lives we’ll see in the coming months, 2018 will definitely be an exciting year to live! | https://medium.com/sciforce/predictions-for-ai-developments-in-2018-d06193c905db | [] | 2018-01-17 09:06:28.257000+00:00 | ['Machine Learning', 'Health', 'Artificial Intelligence', 'Robotics', 'Virtual Assistant'] | Title Predictions AI Developments 2018Content Entering new year wondering expect new AI technology direction look brief review offer prediction AI development 2018 Since indicator show likely increase investment development AI particularly machine learning technology world expecting new wave AI application importantly application finally reaching beyond computer learning beat human chess TV game show 2018 machine learning neural network technology continue refine take routine task — aspect life Robotics Yes robot Blade Runner universe people already mastered replicants manufacturing 2019 verge 2018 still far coexistence robot already taking place 2017 toy robot programmable robot kind educational robot kid 2018 we’ll see programmable robot platform designed adult sophisticated capability offer interesting versatile robotics functionality Additionally consumer robot enter life home helper remove friction daily routine Healthcare Advancements big data analysis AI play major role healthcare Maybe presentday encroachment AI still almost invisible patient Yet new technology push industry forward changing way operates treat patient optimizing workflow within inpatient outpatient scenario Behind scene health examination image recognition algorithm already used pilot project spot warning sign buried medical image decipher handwritten doctors’ note pilot quite successful likely expect boost similar project coming year Another important definitely visible development healthcare greater involvement robot looking health wellbeing patient Caregivers companion robot expected gain popularity could begin become everyday reality 2018 Communication next year likely change interaction machine conversational interface become common come interacting technology business environment year’s estimate 2018 20 firm look add voice enabled interface existing pointandclick dashboard system Natural language generation natural language processing algorithm constantly learning become tuned understanding u talking u way understand 2018 continue improve get used robot converse humanlike manner nearest future likely see increased focus bot sensitivity training allow human offload even work chatbot shoulder business everyday life new virtual assistant Xai called “Amy” respond message regarding meeting meal call Amazon’s Alexa recently began syncing Outlook Google help family keep schedule DataDriven Machines Big data may sound le exciting android creation it’s focus companies’ work next year Pushed steady growth data produced Internet Things business turn machine learning process trend analyze received information 2018 machine learning become absolute musthave company wishing make sense structured unstructured data human unable process overwhelming data flow key strategy call AI largescale analytics play Processing big data change way business run simultaneously improving security monitoring anomaly detection prediction stockexchange market trend Enabling precise clustering customer group developing smart crosssale tracking sale v rank product various category machine learning boost sale proclaim new era commerce Whatever change life we’ll see coming month 2018 definitely exciting year liveTags Machine Learning Health Artificial Intelligence Robotics Virtual Assistant |
984 | Tracker: Ingesting MySQL data at scale — Part 1 | Henry Cai | Pinterest engineer, Infrastructure
At Pinterest we’re building the world’s most comprehensive discovery engine, and part of achieving a highly personalized, relevant and fast service is running thousands of jobs on our Hadoop/Spark cluster. To feed the data for computation, we need to ingest a large volume of raw data from online data sources such as MySQL, Kafka and Redis. We’ve previously covered our logging pipeline and moving Kafka data onto S3. Here we’ll share lessons learned in moving data at scale from MySQL to S3, and our journey in implementing Tracker, a database ingestion system to move content at massive scale.
History
To give an idea of the challenge, let’s first look at where we were coming from. MySQL is the main data source for storing the most important objects in Pinterest: Pins, Pinners and boards. Every day we collect more than 100 terabytes of data from MySQL databases into S3 to drive our offline computation workflows. There were several iterations of design and implementation to work with the data movement at this scale.
The original database ingestion framework (called “dbdump”) was influenced by Apache Sqoop, an open-source solution to pull data from databases into HDFS. We built a cluster solution based on our workflow manager Pinball and our DataJob workflow system to pull MySQL databases in parallel. Each Hadoop mapper process spawned a Python streaming job and a mysqldump process to pull the data from the MySQL host through the process pipes.
The system performed well for the first few years, but over time we faced increasing performance and operational issues, including:
During a dump, the existing framework didn’t deal with failovers (dumping from the master would impact Pinners), or the addition or removal of slaves from production.
Large tables would take hours. For example, it would take us more than 12 hours to get the Pins into Hadoop land.
All knowledge of the MySQL servers schema was checked into code, and so whenever there was a schema change without the accompanying code changes, the extraction process would fail.
The system wasn’t able to deal with binary data well, and so we generally sidestepped various issues by hex encoding the data.
There was an organizational challenge, where various teams owned different versions of the framework, leaving little clarity on ownership.
The existing framework only knew how to read from a single slave, while multiple slaves could be used for parallelize the work.
Enter Tracker
In order to solve the problems that were limiting us, we designed and implemented Tracker. When we started building Tracker, we believed we needed to break the ingestion pipeline into two stages:
A script running on the DB host will backup its content to S3. This script is gated based on the local instance being a slave and replication having applied all events created before 00:00UTC. If a failover happens, the script will automatically stop executing on the new master and should start executing on the new slave without human intervention. DB ingestion can be launched using Hadoop cluster to read and transform the S3 backup files generated in the first step (i.e. to transform the data file into the pre-existing dbdump format or transform into a columnar format). Note in this step we’re in a pure Hadoop world, and so there’s no restriction on how many mappers we can use.
On the Hadoop side, we launched more mappers and turned on speculative execution to kill the occasional S3 uploader that got stuck (an optimization we couldn’t do previously, because of load on the MySQL side). We also changed some critical jobs to read from DB backup files directly to shorten the turnaround.
Further work
The journey getting to the current architecture wasn’t completely smooth. Stay tuned for Part 2 on lessons we learned and MySQL and Hadoop implementation details.
Acknowledgements: Thanks to Rob Wultsch, Krishna Gade, Vamsi Ponnekanti, Mao Ye and Ernie Souhrada for their invaluable contributions to the Tracker Project
For Pinterest engineering news and updates, follow our engineering Pinterest, Facebook and Twitter. Interested in joining the team? Check out our Careers site. | https://medium.com/pinterest-engineering/tracker-ingesting-mysql-data-at-scale-part-1-424cf43fa7c3 | ['Pinterest Engineering'] | 2017-02-21 20:06:30.088000+00:00 | ['Engineering', 'Infrastructure', 'Big Data', 'Hadoop', 'MySQL'] | Title Tracker Ingesting MySQL data scale — Part 1Content Henry Cai Pinterest engineer Infrastructure Pinterest we’re building world’s comprehensive discovery engine part achieving highly personalized relevant fast service running thousand job HadoopSpark cluster feed data computation need ingest large volume raw data online data source MySQL Kafka Redis We’ve previously covered logging pipeline moving Kafka data onto S3 we’ll share lesson learned moving data scale MySQL S3 journey implementing Tracker database ingestion system move content massive scale History give idea challenge let’s first look coming MySQL main data source storing important object Pinterest Pins Pinners board Every day collect 100 terabyte data MySQL database S3 drive offline computation workflow several iteration design implementation work data movement scale original database ingestion framework called “dbdump” influenced Apache Sqoop opensource solution pull data database HDFS built cluster solution based workflow manager Pinball DataJob workflow system pull MySQL database parallel Hadoop mapper process spawned Python streaming job mysqldump process pull data MySQL host process pipe system performed well first year time faced increasing performance operational issue including dump existing framework didn’t deal failovers dumping master would impact Pinners addition removal slave production Large table would take hour example would take u 12 hour get Pins Hadoop land knowledge MySQL server schema checked code whenever schema change without accompanying code change extraction process would fail system wasn’t able deal binary data well generally sidestepped various issue hex encoding data organizational challenge various team owned different version framework leaving little clarity ownership existing framework knew read single slave multiple slave could used parallelize work Enter Tracker order solve problem limiting u designed implemented Tracker started building Tracker believed needed break ingestion pipeline two stage script running DB host backup content S3 script gated based local instance slave replication applied event created 0000UTC failover happens script automatically stop executing new master start executing new slave without human intervention DB ingestion launched using Hadoop cluster read transform S3 backup file generated first step ie transform data file preexisting dbdump format transform columnar format Note step we’re pure Hadoop world there’s restriction many mapper use Hadoop side launched mapper turned speculative execution kill occasional S3 uploader got stuck optimization couldn’t previously load MySQL side also changed critical job read DB backup file directly shorten turnaround work journey getting current architecture wasn’t completely smooth Stay tuned Part 2 lesson learned MySQL Hadoop implementation detail Acknowledgements Thanks Rob Wultsch Krishna Gade Vamsi Ponnekanti Mao Ye Ernie Souhrada invaluable contribution Tracker Project Pinterest engineering news update follow engineering Pinterest Facebook Twitter Interested joining team Check Careers siteTags Engineering Infrastructure Big Data Hadoop MySQL |
985 | From $0 to $100,000: The Business Side of Writing Is the Hardest to Learn and the Easiest to Implement | From $0 to $100,000: The Business Side of Writing Is the Hardest to Learn and the Easiest to Implement
If you can do it for free, you can do it for money. If you can’t, game over.
Photo by Martin Katler on Unsplash
Treating writing like a business is crucial. It’s not about the money.
When writing is a business, you market it.
When writing is a business, you invest in it.
When writing is a business, you learn about the business.
When writing is a business, you market the business.
That last point is key. The old days of just writing, hitting publish, and letting the book publisher gatekeepers take care of everything for you are over.
If you write, you have to market your work.
But marketing is a messed up word. It causes people to shove selfie poles in front of their faces and fall head over heel in love with themselves. We don’t want that. You’re a writer, not an insecure influencer searching for a Lambo in the Hollywood Hills.
A friend of mine calls what I’m referring to here as the “business side of writing.” I’ve made a business out of my writing and gone from $0 to more than $100,000. I believe you can do the same with a shift in thinking.
As writers, most of us suck at the business side of writing.
I don’t market my blog posts as much as I should. I publish and prey like many other writers. The world is shifting though. | https://medium.com/better-marketing/from-0-to-100-000-the-business-side-of-writing-is-the-hardest-to-learn-and-the-easiest-to-e38000ea5ca6 | ['Tim Denning'] | 2020-12-21 17:13:03.456000+00:00 | ['Marketing', 'Writing', 'Social Media', 'Money', 'Business'] | Title 0 100000 Business Side Writing Hardest Learn Easiest ImplementContent 0 100000 Business Side Writing Hardest Learn Easiest Implement free money can’t game Photo Martin Katler Unsplash Treating writing like business crucial It’s money writing business market writing business invest writing business learn business writing business market business last point key old day writing hitting publish letting book publisher gatekeeper take care everything write market work marketing messed word cause people shove selfie pole front face fall head heel love don’t want You’re writer insecure influencer searching Lambo Hollywood Hills friend mine call I’m referring “business side writing” I’ve made business writing gone 0 100000 believe shift thinking writer u suck business side writing don’t market blog post much publish prey like many writer world shifting thoughTags Marketing Writing Social Media Money Business |
986 | The Lost Skill Of Civilized Society We Desperately Need To Revive | Photo by Green Chameleon on Unsplash
I don’t remember the exact words, but I remember the feeling.
I was thirteen years old. My first ever girlfriend had written me a letter. It was a love letter of sorts. I bounced around my house for hours after reading it.
Before the internet, we wrote letters to each other. They lacked convenience and ease, but they were thoughtfully crafted pieces of communication.
We’ve lost the skill and even the desire to write letters. Today, we opt for clumsy emails, impulsive social media posts, and cryptic text messages.
Letter writing is a forgotten art form. Nobody seems to do it anymore. That rarity makes it all the more special when you receive one.
It was a skill praised by the likes of Benjamin Franklin, Thomas Jefferson, Abraham Lincoln, and Voltaire. Some of the most effective open letters in history are still revered today.
A letter won’t produce miracles, but it’s time we brought back this sacred practice.
The Letter writing basics
I was a frequent letter writer in the ’80s and ’90s. I recently rediscovered the artform as a means of teaching my son how to write thoughtfully. Most rules on writing apply to letter writing, with only a few modifications.
Always write to a specific audience
Direct most letters to a single individual —open letters excepted. It’s always from you, a single human being. Never write as though you were an entity: a company name, department or group.
It’s not about you
Do you have a family, friend or acquaintance that sends you a ten-page narrative of everything they experienced the past year? Be honest. Do you read them? No, I don’t either.
Any personal correspondence should always focus on the recipient. You’re tasking them with reading your letter. Make it valuable to them.
It’s harder than it sounds. Use these two techniques to validate your work.
Ask a disinterested third party to read it. Put your letter away for at least twelve hours. Read it again but pretend that it is addressed to you.
Outline your letter before writing
The power of a letter lies in its thoughtfulness. Create an outline before you write your first draft.
Allow distance between editing
Your completed draft will always look impressive right after you finish. It won’t look as good the next morning. Spending time away from your work allows you to forget it enough so that you can identify the flaws.
Send it when they least expect
Would it surprise you to receive a letter of appreciation after you do a huge favor for someone? Sure, you would appreciate the gesture, but it would not surprise you.
A letter achieves maximum impact when the recipient least expects it. You get dozens of holiday cards in December. How many do you get in August? Zero, right? That’s the best time to send them.
Some situations do not allow for off-cycle delivery but keep it in mind for situations when it makes sense.
Consider delivery
Yes, you can transfer your work to email and send it out. What about sending it by snail mail? Or how about messengering it over to your recipient. My favorite technique is FedExing it overnight. This technique works well when the recipient expects your letter. A creative delivery method adds in that touch of surprise.
Get your anger out of the way
When Benjamin Franklin was angry, he would unload all his vitriol onto the paper. And then, he would throw it away. He’d start again and if his words were still filled with anger, he’d throw that one away.
Angry letters read like mindless temper tantrums to the recipient. Get your anger out of the way in an early draft. You can still express anger, but you will find your words more composed and more coherent.
The 5 letters you should know how to write
The basic guidelines apply to all five letters you’ll read about next.
The open letter
The letters I posted above were all open letters. They were published to a recipient or recipients on a public platform. Historical figures used them to call out injustice or bring attention to people who lacked the voice and distribution to make their case known.
In modern days, many folks use open letters as a tool for shaming someone into changing their behavior. These letters might give the writer emotional satisfaction, but they rarely affect change the way they have in the past.
There’s a lot of advice on the internet on how to write open letters, much of it poor. Study the text of the letters I posted above. You’ll notice similarities, despite their difference in style.
Stick to the facts
Avoid sanctimonious verbiage
Express anger but keep aggression in check
The love letter
Love letters have been relegated to plot devices in historical fiction novels. In the age of sexting, we’ve lost the skill of expressing our love with artful, thoughtful and subtle words.
A well-crafted love letter allows the recipient to glean the depths of your love. Show don’t tell works just as well in love letters as it does in fiction.
Compare the difference between these two sentences.
You are the sexiest thing alive. My sweat glands fire up every time you flick your bangs away from your eyes.
You cannot write a good love letter on the fly. It’s not something you write while waiting in line for coffee. It requires several drafts to get it right.
Start your first draft by writing bullet points of exactly what you want to say. Don’t get cute or poetic yet. Be precise here. For your second draft, ask yourself these two questions. The answers help you evolve your statements into demonstrations.
How could I show it in a way that will let her conclude it on her own?
What example would prove to her that I [fill in the blank]?
The letter of appreciation
Do you remember the last thank you note you received? Of course not. Thank you notes are devices we use to fulfill an obligation. Letters of appreciation emanate from heartfelt gratitude.
When you express your appreciation, you must include the first three components below.
Specificity about what you appreciate. Why you think it deserves your appreciation. Give an example of how it benefitted you. BONUS: Deliver with grace.
Keep it short and to the point. Be respectful of the recipient’s time.
The apology
Almost all apologies, written or verbal, contain a fatal flaw. As a recipient or neutral third party, you see the flaw instantly. The apologizer qualifies his apology.
I apologize for embarrassing you in front of your family, but your obnoxious comment left me no choice. That was no excuse. It was my fault.
You see the problem with that apology, right? He’s trying to justify his behavior within his apology, and transfer some of the blame to the other person. That’s what it means by qualifying your apology.
Here is one more example where the writer sneaks in a subtle insult.
“I apologize for my supposed verbal abuse in the past. My comments were misconstrued.
Follow this simple rule.
Always let your apology stand on its own. Explain what you did wrong and take full responsibility. Your words must be unequivocal. Have another person review it before you deliver it. Make sure the reviewer is someone without an emotional attachment to the situation.
The persuasive letter
Explaining the concepts behind a persuasive letter in a few hundred words won’t be possible, but I’ll provide you with a few key takeaways you can use right away.
Forget logic
Never try to prove your point. Persuasion is 80% emotional and 20% logical. You can’t change someone’s mind. We change our own mind. Your job is to lead your reader to a point where he comes to the conclusion you desire.
Hide your personal opinions
Once you make your opinion known, your reader will see you as a person with an agenda.
Once they know your agenda, you lose credibility.
Once you lose credibility, they treat everything you say with suspicion.
You don’t need a hammer
A heavy-handed approach destroys your credibility when you write to a hostile or even neutral audience. Be on the lookout for adjectives and adverbs that unintentionally give away your opinion.
“When I spoke with the undersecretary, he said no. He remarked that she seemed too sweet for a serious job.”
Versus
“When I spoke with the sexist undersecretary, he said no.”
Let your reader conclude that the undersecretary was sexist. The first example does a better job. You want the reader to form her own opinion without you explicitly stating your opinion.
Think of it as a game of connect-the-dots. Draw a picture and connect a few of the dots, but allow the reader the pleasure of finishing it. | https://barry-davret.medium.com/the-lost-skill-of-civilized-society-we-desperately-need-to-revive-711d7594b686 | ['Barry Davret'] | 2019-04-17 12:28:38.432000+00:00 | ['Creativity', 'Culture', 'Self Improvement', 'Life Lessons', 'Writing'] | Title Lost Skill Civilized Society Desperately Need ReviveContent Photo Green Chameleon Unsplash don’t remember exact word remember feeling thirteen year old first ever girlfriend written letter love letter sort bounced around house hour reading internet wrote letter lacked convenience ease thoughtfully crafted piece communication We’ve lost skill even desire write letter Today opt clumsy email impulsive social medium post cryptic text message Letter writing forgotten art form Nobody seems anymore rarity make special receive one skill praised like Benjamin Franklin Thomas Jefferson Abraham Lincoln Voltaire effective open letter history still revered today letter won’t produce miracle it’s time brought back sacred practice Letter writing basic frequent letter writer ’80s ’90s recently rediscovered artform mean teaching son write thoughtfully rule writing apply letter writing modification Always write specific audience Direct letter single individual —open letter excepted It’s always single human Never write though entity company name department group It’s family friend acquaintance sends tenpage narrative everything experienced past year honest read don’t either personal correspondence always focus recipient You’re tasking reading letter Make valuable It’s harder sound Use two technique validate work Ask disinterested third party read Put letter away least twelve hour Read pretend addressed Outline letter writing power letter lie thoughtfulness Create outline write first draft Allow distance editing completed draft always look impressive right finish won’t look good next morning Spending time away work allows forget enough identify flaw Send least expect Would surprise receive letter appreciation huge favor someone Sure would appreciate gesture would surprise letter achieves maximum impact recipient least expects get dozen holiday card December many get August Zero right That’s best time send situation allow offcycle delivery keep mind situation make sense Consider delivery Yes transfer work email send sending snail mail messengering recipient favorite technique FedExing overnight technique work well recipient expects letter creative delivery method add touch surprise Get anger way Benjamin Franklin angry would unload vitriol onto paper would throw away He’d start word still filled anger he’d throw one away Angry letter read like mindless temper tantrum recipient Get anger way early draft still express anger find word composed coherent 5 letter know write basic guideline apply five letter you’ll read next open letter letter posted open letter published recipient recipient public platform Historical figure used call injustice bring attention people lacked voice distribution make case known modern day many folk use open letter tool shaming someone changing behavior letter might give writer emotional satisfaction rarely affect change way past There’s lot advice internet write open letter much poor Study text letter posted You’ll notice similarity despite difference style Stick fact Avoid sanctimonious verbiage Express anger keep aggression check love letter Love letter relegated plot device historical fiction novel age sexting we’ve lost skill expressing love artful thoughtful subtle word wellcrafted love letter allows recipient glean depth love Show don’t tell work well love letter fiction Compare difference two sentence sexiest thing alive sweat gland fire every time flick bang away eye cannot write good love letter fly It’s something write waiting line coffee requires several draft get right Start first draft writing bullet point exactly want say Don’t get cute poetic yet precise second draft ask two question answer help evolve statement demonstration could show way let conclude example would prove fill blank letter appreciation remember last thank note received course Thank note device use fulfill obligation Letters appreciation emanate heartfelt gratitude express appreciation must include first three component Specificity appreciate think deserves appreciation Give example benefitted BONUS Deliver grace Keep short point respectful recipient’s time apology Almost apology written verbal contain fatal flaw recipient neutral third party see flaw instantly apologizer qualifies apology apologize embarrassing front family obnoxious comment left choice excuse fault see problem apology right He’s trying justify behavior within apology transfer blame person That’s mean qualifying apology one example writer sneak subtle insult “I apologize supposed verbal abuse past comment misconstrued Follow simple rule Always let apology stand Explain wrong take full responsibility word must unequivocal another person review deliver Make sure reviewer someone without emotional attachment situation persuasive letter Explaining concept behind persuasive letter hundred word won’t possible I’ll provide key takeaway use right away Forget logic Never try prove point Persuasion 80 emotional 20 logical can’t change someone’s mind change mind job lead reader point come conclusion desire Hide personal opinion make opinion known reader see person agenda know agenda lose credibility lose credibility treat everything say suspicion don’t need hammer heavyhanded approach destroys credibility write hostile even neutral audience lookout adjective adverb unintentionally give away opinion “When spoke undersecretary said remarked seemed sweet serious job” Versus “When spoke sexist undersecretary said no” Let reader conclude undersecretary sexist first example better job want reader form opinion without explicitly stating opinion Think game connectthedots Draw picture connect dot allow reader pleasure finishing itTags Creativity Culture Self Improvement Life Lessons Writing |
987 | Investing in Data and AI — When and Why | In a previous 3-part series, we discussed the main hurdles limiting the value that businesses get from data. In particular, we highlighted the importance of the timing of investment into establishing data infrastructure, recruiting data professionals, etc. The reasons are clear. Any significant returns on investment that you make on data are likely to come from their use in conjunction with AI techniques such as the various ML algorithms in your products. This is when your Data Science/ML teams come in, to explore the data, build the ML models, and package them up into what I call AI services that your products can leverage. Before that can happen, you should ideally have started collecting the right data with your product that already has product-market fit.
Photo by Amanda Jones on Unsplash
In this short article, we zoom in on the timing aspect of investment in big data and AI, and as part of that, the benefits of powering your products with them. The points that follow are especially relevant to businesses that offer digital products to facilitate transactions in two or multi-sided marketplaces. From a scalability perspective, AI services can offer such businesses a potentially more sustainable way of maintaining and improving products to engage and retain users in the long run. This is due to the nature of AI-powered products which improve automatically and continuously as more data of the right kind flow in. On the defensibility front, while it is not inherent to data itself, the use of thoughtfully acquired data in the AI services that power your product can create hard-to-replicate user experiences. The lifecycle extension of digital products is also another possibility with AI services.
By “scalability” we refer to a situation where a business is able to multiply its revenue with the minimal incremental cost
On the timing of investment, we use the start-up J curve as the backdrop. The J curve outlines the six phases that entrepreneurs go through as they try to build out sustainable business models. The curve starts with the create and the release phases, where teams and money come together to turn ideas into products and release them into the market. During the morph phase, the products and business models are iterated upon based on customer feedback, metrics and so on. If product-market fit can be achieved within this phase, the companies move on to optimise their business models and grow while keeping cost down and revenue high during the model and the scale phases. These phases are shown in blue in the diagram below.
The start-up J curve overlaid with timing of investment in data and AI
The best time for entrepreneurs and companies to double down on their investment in platform, data and AI is the period towards the end of morph and during model phases. In the world of “doing things that don’t scale”, this is often the best time to “repay” some of the debts that have been incurred in the name of speed so that your infrastructure, for instance, does not crumble as you stack more on top of it, e.g., more features, more users. While many seasoned entrepreneurs get this point, what some people often miss is the fact that this period is also perfect for putting money into (1) data infrastructure to capture, process and store big data and make them accessible, and (2) data science professionals to explore the growing volume of data and build out AI services that products can leverage. This period which is ripe for investment into all things data is marked as (A) in the diagram above.
It is important to call out that there are AI services that can be developed or utilised in products that will immediately be beneficial during the release and morph phases. These vanilla AI services or tools require next to nothing in terms of data about your users and how they behave in your marketplace. Often, the purpose of these off-the-shelf solutions is to save you the cost/effort associated with human intervention in making your product works smarter and reducing bad frictions. For instance, let us assume your product involves users uploading content. Instead of requiring the users to provide information about the content such as languages or tags, they can be predicted and offered to the users as suggestion. Not surprisingly, such capabilities are unlikely to offer you any competitive advantage in the long run. This is when you need investment during period (A). As an example, once you have started capturing what your users search for, the content they click on and the other actions in your marketplace, you can utilise AI to understand their preferences or intent. The derived user information can in turn be used by other AI services in your product to better serve those users and potentially others.
Some things simply don’t automate. For everything else, build systems; they’re a lot easier to scale quickly than humans.
By now you must be wondering, when will your investment during period (A) starts bearing fruits? The short answer is after product-market fit has been found and it can happen throughout the scaling period, which is indicated as (B) in the diagram. How soon you can reap the rewards can depend on the nature of the problems you are solving with big data and AI and the solutions that your teams have picked. As more and more parts of your product become powered by AI, especially the ones that are built on proprietary data, your business will be able to scale on top of that. This period of scaling with big data and AI is marked as (C) in the diagram above. This period essentially offers your business an alternative path to the harvest phase in the J curve. Do not get me wrong. Your business will still grow and you will probably do fine without big data and AI. However, the often neglected cost associated with retaining existing users and engaging new markets without products that can improve automatically and continuously with more data will become a major drag on your ROI.
Product lifecycle extended with big data and AI
Before we end, let us look at the ROI in big data and AI services through two other difference angles. The first angle is through the lens of the typical product lifecycle that involves products going through the introduction, growth, maturity and decline phases. AI services give you the opportunities to extend the lifecycle of your product by allowing you to improve existing features or introduce new ones in ways that otherwise would not be possible, as shown in the diagram above in red.
Big data and AI provide for products that scale better
The second angle, as depicted in the diagram above, looks at the role of big data and AI services as a “dampening factor” to the cost associated with capturing new users and servicing existing users who tend to expect more from your products as time passes. This is especially true if your business operates in a two or multi-sided marketplace and has to deal with constantly growing content pool and match-making the different sides. Your ability to grow and scale efficiently is predicated on big data and AI. Due to the nature of how AI services work, by feeding off increasingly growing pool of data about your users and how they use your product, you will get to reduce the reliance on heuristic-based solutions and solutions that require excessive humans intervention in order to solve your users’ problems. | https://medium.com/swlh/ever-wonder-about-the-best-time-to-invest-in-data-and-ai-2b77ff0cfe2c | ['Wilson Wong'] | 2020-11-25 02:36:28.159000+00:00 | ['Product Management', 'Startup', 'Return On Investment', 'AI', 'Data Science'] | Title Investing Data AI — WhyContent previous 3part series discussed main hurdle limiting value business get data particular highlighted importance timing investment establishing data infrastructure recruiting data professional etc reason clear significant return investment make data likely come use conjunction AI technique various ML algorithm product Data ScienceML team come explore data build ML model package call AI service product leverage happen ideally started collecting right data product already productmarket fit Photo Amanda Jones Unsplash short article zoom timing aspect investment big data AI part benefit powering product point follow especially relevant business offer digital product facilitate transaction two multisided marketplace scalability perspective AI service offer business potentially sustainable way maintaining improving product engage retain user long run due nature AIpowered product improve automatically continuously data right kind flow defensibility front inherent data use thoughtfully acquired data AI service power product create hardtoreplicate user experience lifecycle extension digital product also another possibility AI service “scalability” refer situation business able multiply revenue minimal incremental cost timing investment use startup J curve backdrop J curve outline six phase entrepreneur go try build sustainable business model curve start create release phase team money come together turn idea product release market morph phase product business model iterated upon based customer feedback metric productmarket fit achieved within phase company move optimise business model grow keeping cost revenue high model scale phase phase shown blue diagram startup J curve overlaid timing investment data AI best time entrepreneur company double investment platform data AI period towards end morph model phase world “doing thing don’t scale” often best time “repay” debt incurred name speed infrastructure instance crumble stack top eg feature user many seasoned entrepreneur get point people often miss fact period also perfect putting money 1 data infrastructure capture process store big data make accessible 2 data science professional explore growing volume data build AI service product leverage period ripe investment thing data marked diagram important call AI service developed utilised product immediately beneficial release morph phase vanilla AI service tool require next nothing term data user behave marketplace Often purpose offtheshelf solution save costeffort associated human intervention making product work smarter reducing bad friction instance let u assume product involves user uploading content Instead requiring user provide information content language tag predicted offered user suggestion surprisingly capability unlikely offer competitive advantage long run need investment period example started capturing user search content click action marketplace utilise AI understand preference intent derived user information turn used AI service product better serve user potentially others thing simply don’t automate everything else build system they’re lot easier scale quickly human must wondering investment period start bearing fruit short answer productmarket fit found happen throughout scaling period indicated B diagram soon reap reward depend nature problem solving big data AI solution team picked part product become powered AI especially one built proprietary data business able scale top period scaling big data AI marked C diagram period essentially offer business alternative path harvest phase J curve get wrong business still grow probably fine without big data AI However often neglected cost associated retaining existing user engaging new market without product improve automatically continuously data become major drag ROI Product lifecycle extended big data AI end let u look ROI big data AI service two difference angle first angle lens typical product lifecycle involves product going introduction growth maturity decline phase AI service give opportunity extend lifecycle product allowing improve existing feature introduce new one way otherwise would possible shown diagram red Big data AI provide product scale better second angle depicted diagram look role big data AI service “dampening factor” cost associated capturing new user servicing existing user tend expect product time pass especially true business operates two multisided marketplace deal constantly growing content pool matchmaking different side ability grow scale efficiently predicated big data AI Due nature AI service work feeding increasingly growing pool data user use product get reduce reliance heuristicbased solution solution require excessive human intervention order solve users’ problemsTags Product Management Startup Return Investment AI Data Science |
988 | Getting Entertained by the Creativity of Others Recharges Your Own | In the past, I used to be totally focused on my work. Hardly ever did I allow myself to get entertained.
Whenever I would relax into some leisure, be it watching a video or attending a gathering of friends, there was always this uneasiness in the background of my mind nagging me not to waste my time.
I was happy with my productivity and I accomplished a lot in the twelve years of self-employment. I wasn’t even stressed since I really loved what I did. Yet there was an imbalance in my life — it was all about giving and there was no time for receiving.
I was always uneasy that were I to truly like the entertainment of others, I may not want to produce my own. I was afraid of getting addicted to the creations of those perfect at what they do — what if I would become too lazy to create my own? the reasoning went.
Workaholism is an addiction, and like all addictions, it blocks creative energy. — Julia Cameron
Finally, there came a stage in my life where I allowed myself to fully rest from my work and to enjoy the talents of others. I can honestly say that only for about two years now I’m able to guiltlessly relax into such a way of being.
The main cause of such a change was my boyfriend. We complement each other because he tends to be all entertainment and I tend to be all work. He taught me how to fully relax and not feel bad about consuming interesting content. | https://medium.com/the-innovation/getting-entertained-by-the-creativity-of-others-recharges-your-own-24215d650da | ['Simona Rich'] | 2020-11-02 09:25:49.512000+00:00 | ['Creativity', 'Entertainment', 'Talent Development', 'Motivation', 'Inspiration'] | Title Getting Entertained Creativity Others Recharges OwnContent past used totally focused work Hardly ever allow get entertained Whenever would relax leisure watching video attending gathering friend always uneasiness background mind nagging waste time happy productivity accomplished lot twelve year selfemployment wasn’t even stressed since really loved Yet imbalance life — giving time receiving always uneasy truly like entertainment others may want produce afraid getting addicted creation perfect — would become lazy create reasoning went Workaholism addiction like addiction block creative energy — Julia Cameron Finally came stage life allowed fully rest work enjoy talent others honestly say two year I’m able guiltlessly relax way main cause change boyfriend complement tends entertainment tend work taught fully relax feel bad consuming interesting contentTags Creativity Entertainment Talent Development Motivation Inspiration |
989 | Late Season Blooms | Each spring, I survive the long, gray Pacific Northwest winters by counting down the minutes until the cherries blossom. This annual occurrence, usually around mid-March, is when the drab gray skies of Seattle recede into the background at last, outshone by a riot of pink and white blossoms so prolific that they fall like snowflakes all over town.
The first spring we lived here, I waited as the buds swelled on the two flowering plums we had in the yard at our new house. Each morning, I’d check them on the way out to the mailbox, hoping for a riot of color. The neighbors’ trees started to put on their show, while our trees remained stubbornly bare.
This is what I though my trees *ought* to be doing. But they remained stubbornly bare.
“Maybe our yard is too shady,” I said to my husband. “Maybe they’re not healthy enough.”
The leaves emerged, which convinced me they’d never bloom. The flowering cherries and plums I’d seen all around our neighborhood, all around greater Seattle, all bloomed before they leafed out, which is part of what made them so spectacular — nothing but flowers and the backdrop of the occasional beautiful blue sky.
By early April, when rain showers and wind had knocked down most of the gorgeous blossoms, I was ready to get out the chainsaw because my trees still hadn’t bloomed.
Patience is not always my strength, and I’m apt to pull out the metaphorical chainsaw when I get impatient for results. I’ve been at a particularly low point in my journey as a writer and feeling like slashing and burning everything in sight. Even as my freelance editing business grows, my writing has had a series of setbacks over the past six months that have left me questioning whether I’ll always be a better coach than I am a writer, whether I’ll ever hold one of my quirky, magical books for young readers in my hands instead of just my heart.
Then this week, I got a little reminder from Mother Nature that I just needed to be patient a little longer. Those flowerless trees I was talking about? They’re flowering plums, and they’re a beautiful double-flowering variety that blooms after the tree leafs out instead of before. So weeks after the other trees are back to looking like plain old trees, the magic starts in our yard. Our trees are gorgeous, they’re just on a slightly different timeline than all the others. Just like me.
I’m glad I didn’t take a chainsaw to those trees. If I had, I’d have missed out on this little bit of magic:
My double-flowering plum showing us its magic at its own pace.
If you’re feeling like your time will never come to bloom, or feeling shabby in the shadow of friends and colleagues who are full of showy blooms while your branches still feel bare, all I can say is don’t give up. Those blooms are inside you, they’re just not quite ready to emerge. When they do, they’ll be magic. | https://medium.com/no-blank-pages/late-season-blooms-80a9036ee072 | ['Julie Artz'] | 2019-04-18 15:45:56.684000+00:00 | ['Creativity', 'Personal Development', 'Gardening', 'Life Lessons', 'Writing'] | Title Late Season BloomsContent spring survive long gray Pacific Northwest winter counting minute cherry blossom annual occurrence usually around midMarch drab gray sky Seattle recede background last outshone riot pink white blossom prolific fall like snowflake town first spring lived waited bud swelled two flowering plum yard new house morning I’d check way mailbox hoping riot color neighbors’ tree started put show tree remained stubbornly bare though tree ought remained stubbornly bare “Maybe yard shady” said husband “Maybe they’re healthy enough” leaf emerged convinced they’d never bloom flowering cherry plum I’d seen around neighborhood around greater Seattle bloomed leafed part made spectacular — nothing flower backdrop occasional beautiful blue sky early April rain shower wind knocked gorgeous blossom ready get chainsaw tree still hadn’t bloomed Patience always strength I’m apt pull metaphorical chainsaw get impatient result I’ve particularly low point journey writer feeling like slashing burning everything sight Even freelance editing business grows writing series setback past six month left questioning whether I’ll always better coach writer whether I’ll ever hold one quirky magical book young reader hand instead heart week got little reminder Mother Nature needed patient little longer flowerless tree talking They’re flowering plum they’re beautiful doubleflowering variety bloom tree leaf instead week tree back looking like plain old tree magic start yard tree gorgeous they’re slightly different timeline others like I’m glad didn’t take chainsaw tree I’d missed little bit magic doubleflowering plum showing u magic pace you’re feeling like time never come bloom feeling shabby shadow friend colleague full showy bloom branch still feel bare say don’t give bloom inside they’re quite ready emerge they’ll magicTags Creativity Personal Development Gardening Life Lessons Writing |
990 | What it’s like to interview at Pinterest | Justin Mejorada-Pier | Software Engineer, Analytics Platform Tech Lead
Interviews have traditionally been thought of as an unpleasant but necessary experience. Candidates often find them stressful and many come in having had poor interview experiences in the past. However, interviews are the clearest opportunity for companies to articulate and demonstrate their company values, culture, and approach. It’s counterproductive for a candidate’s first live interaction with a company to risk being an unpleasant experience, stress them out with a tricky probability question, or cause them to feel out of place.
We think interviewing at a company can actually be a positive experience. Interviews should allow candidates to demonstrate their own way of solving real-world problems as well as learn more about what is it like to actually work for Pinterest.
So we set out to rethink how technical interviews work.
Here we’ll share our approach and describe in detail what it’s like to interview at Pinterest.
Real solutions, no gotchas.
We allow candidates to use online resources like Google or Stack Overflow during the interview process to mimic as closely as possible what they’d see in a real work environment. We also provide a machine with the most common IDEs, like VSCode and Sublime, so candidates feel at home with the code completion, syntax highlighting, and shortcuts they’re used to.
Our questions are made specifically to avoid “gotcha” moments. We retired a whole host of questions for this reason. We want to challenge candidates to show us diligent critical thinking skills, but we never want to trick them. We give candidates the opportunity to show us their best work. If our questions aren’t set up to do that, it’s on us, not them, and we take that very seriously.
We look for problem solving skills that show candidates can tackle real-world technical challenges like those they may encounter in their daily work. You won’t be asked a question that requires, for example, dynamic programming. Instead, you’ll be asked to tackle a programming problem representative of the work engineers typically encounter, such as writing a tool to analyze a log file.
There’s not just one type of engineer.
The Pinterest interview process cares about more than just a candidate’s ability to code. Showing a growth mindset is a signal we take into account during debriefs. We also purposefully split questions into several steps that gradually increase in difficulty, so everyone can find the correct level of challenge whether they’re a new or senior engineer. This also avoids that awful feeling of walking out of an interview having not gotten ANY part of the question.
We understand different people have different interview styles — so don’t worry about trying to be someone you’re not. People have different approaches when solving problems. Some talk through it aloud as they write their code while others silently brainstorm before diving into solutions. As long as you solve the technical challenges and clearly explain your solution, you should feel free to talk as much or as little as you’d like.
If you’re coming from a non-traditional background, going through a full software interview loop isn’t the only option — we also provide programs like our apprenticeship program, which still does rigorous vetting but is better able to identify passionate, motivated people that could be huge assets to any company regardless of whether they studied a particular topic in college.
We take unconscious bias seriously. We have reminders and tips for checking unconscious bias every time we enter candidate feedback, and we have rules that prohibit discussing candidates with other interviewers to avoid opinion contamination.
The details.
Interviewing at Pinterest consists of three main steps:
Recruiter Call Phone Screen Onsite Interview
Recruiter Call: During this initial call with a Pinterest recruiter, you’ll learn more details about the role and your interview process. Be sure to ask any questions you might have; this is as much about Pinterest interviewing you as it is about you interviewing Pinterest.
Phone Screen: You’ll speak with a Pinterest engineer (or, for some roles, a Karat.io interviewer) for about 45 to 60 minutes. You may also use a collaborative coding tool so you can both see the code you write and, depending on the question, possibly even run your code. For example, we may use CoderPad for generic programming questions or JSFiddle for web development questions.
The purpose of the phone screen is to get to know your general programming skills, specialized domain knowledge (when applicable), and overall interests.
Here is the general format:
Five minutes where interviewers introduce themselves and ask the candidate if they have any questions before starting
One or two coding questions
Five minutes where candidates may ask any additional questions about the role or Pinterest
The coding questions are usually around data structures and algorithms, but they may also include some domain knowledge elements depending on the role.
Onsite interview: During the onsite interview, you’ll come to the Pinterest office to participate in (usually) five interviews spread across the following interview types:
Data Structures / Algorithms
Architecture / Systems Design
Domain Specific
Lunch Interview / Hiring Manager / Values
You can find out more about each one below.
Types of interviews
Data Structures / Algorithms
You’ll be asked to solve a general programming question involving real-world data structures and algorithms you may use to solve problems in your day-to-day work. You won’t be asked to solve a question using seldom used methods like dynamic programming, and you’ll be encouraged to use whichever programming language(s) you’re most comfortable with. Normally, the question asked has several potential solutions, ranging from a naive, brute force approach to more optimal, elegant approaches. It tends to be one question, but you may be asked other questions if time allows. The goal is to test your practical skills used in everyday programming.
Tips
Practice — Brush up on your CS fundamentals, data structures, and algorithms, and make sure you’ve practiced in your preferred programming language(s).
Resources — There are many resources online to help you practice. For example, you might check out sites like CareerCup, various online courses and apps, and books like Cracking the Coding Interview. Use these to build intuitive pattern recognition as you see more and more samples of the underlying subproblems and the algorithms and approaches commonly used to solve them. The goal is to use those building blocks to compose solutions to the more complex, unique problems you may see in your interview.
Naturally, if you encounter a problem you’ve already seen, you should point that out during the interview. For example, you might say something like, “I saw this problem last month, and I know it can be solved by x, y, or z methods. Do you want me to proceed with either of these methods?” Don’t be surprised if your interviewer still decides to have you work the problem.
Additional tips:
Whiteboard vs. Laptop : Laptops are provided for candidates since that’s the environment that most closely mirrors day-to-day work. However, whiteboarding is an option if that’s where you’re most comfortable. It can be harder to improve and refactor code on the whiteboard compared to an IDE, so you may want to take this into account.
: Laptops are provided for candidates since that’s the environment that most closely mirrors day-to-day work. However, whiteboarding is an option if that’s where you’re most comfortable. It can be harder to improve and refactor code on the whiteboard compared to an IDE, so you may want to take this into account. Real code : Even though it’s okay if you prefer to start by wireframing your solution using pseudocode, you’re expected to be able to write your final solution in code that would actually run. Communicating your plan is important, and pseudocode is one way to do this. But talking through your plan or making a diagram may be faster for this purpose.
: Even though it’s okay if you prefer to start by wireframing your solution using pseudocode, you’re expected to be able to write your final solution in code that would actually run. Communicating your plan is important, and pseudocode is one way to do this. But talking through your plan or making a diagram may be faster for this purpose. Your programming language : We highly encourage you to use the programming language you feel most comfortable with. Most candidates tend to pick languages like Python, Java, JavaScript, Ruby, C/C++, or C#. However, it’s completely acceptable if you prefer using less common languages; just keep in mind that it may take a bit more time to explain your solution to your interviewer if they are not very familiar with your chosen language.
: We highly encourage you to use the programming language you feel most comfortable with. Most candidates tend to pick languages like Python, Java, JavaScript, Ruby, C/C++, or C#. However, it’s completely acceptable if you prefer using less common languages; just keep in mind that it may take a bit more time to explain your solution to your interviewer if they are not very familiar with your chosen language. Validation : Remember to validate your inputs and to ask the interviewer for their constraints or characteristics. Ideally your solution should fail gracefully when invalid inputs are provided, or at the very least it should not yield incorrect results.
: Remember to validate your inputs and to ask the interviewer for their constraints or characteristics. Ideally your solution should fail gracefully when invalid inputs are provided, or at the very least it should not yield incorrect results. Testing : Remember to ask the interviewer whether you should add tests for your solution and describe or implement the tests based on their answer. Regardless of whether you write explicit tests or describe them out loud, you should make sure your solution works as planned and is able to work across the possible inputs.
: Remember to ask the interviewer whether you should add tests for your solution and describe or implement the tests based on their answer. Regardless of whether you write explicit tests or describe them out loud, you should make sure your solution works as planned and is able to work across the possible inputs. Think through the problem first: Don’t jump into solving the problem. First, spend some time thinking through the problem end to end while being cognizant of the time you have. Only after you’ve thought through the problem and clarified your approach with your interviewer should you start coding. However, if you do decide later on to change your approach, that’s ok. It’s incredibly important to remain open to new information and adjust your path accordingly. Here are a few questions to ask yourself:
— Do I fully understand the problem, its constraints, input and expected output?
— Do I know how much time I have available?
— Based on the above, what are some possible ways to solve the problem? Which one do I prefer and why? What are the tradeoffs between them?
Break problems into smaller ones : Be sure to break big problems into smaller ones that can be composed to solve the bigger one. If you have solved any of the smaller problems before (most likely you have), think about the difference between them and the bigger problem. Can you modify them or compose them to solve the bigger one?
: Be sure to break big problems into smaller ones that can be composed to solve the bigger one. If you have solved any of the smaller problems before (most likely you have), think about the difference between them and the bigger problem. Can you modify them or compose them to solve the bigger one? Describe your planned solution : Once you have a plan to tackle a problem, describe it to your interviewer before starting it. They may be able to point out issues or provide tips before you start. Interviewers are encouraged to conduct the interview in a collaborative environment, so feel free to talk through how you’re thinking of tackling the problem.
: Once you have a plan to tackle a problem, describe it to your interviewer before starting it. They may be able to point out issues or provide tips before you start. Interviewers are encouraged to conduct the interview in a collaborative environment, so feel free to talk through how you’re thinking of tackling the problem. Runtime complexity : Be aware of the runtime complexity of your problem and be able to talk about it. Ideally mention it to your interviewer when you’re describing your solution.
: Be aware of the runtime complexity of your problem and be able to talk about it. Ideally mention it to your interviewer when you’re describing your solution. Ask questions, and if stuck, ask for tips : It’s ok to ask for tips if you’re truly stuck. While ideally no tips would be necessary, it’s better to ask for tips and be able to solve the problem than staying stuck.
: It’s ok to ask for tips if you’re truly stuck. While ideally no tips would be necessary, it’s better to ask for tips and be able to solve the problem than staying stuck. Code quality : The more readable, simple, and concise your code is, the better.
: The more readable, simple, and concise your code is, the better. Bugs: While ideally there’d be no bugs, it’s okay if you find bugs and solve them. If your interviewer spots bugs for you, ask questions to better understand, and work to solve them.
Architecture / Systems Design
In this interview, you’ll be asked to solve an open ended problem by designing a technical solution for it, describing and communicating it effectively to your interviewer, and iterating on it as needed to polish it and address any concerns. These problems are generally broad and may include some aspects of API design, online and offline (jobs) computation, client vs. server computation and storage decisions, communication with the web/mobile clients, database model design, database/storage selection, local or distributed algorithms, code architecture, caching, scaling considerations, common architectures, or communication approaches (like push, pull, pubsub, etc).
Domain-specific roles tend to have somewhat more domain-specific versions of this question.
Most times these interviews don’t require writing any code. However, they may require making basic architecture diagrams or otherwise communicating your technical solution to your interviewer effectively and being able to answer their questions about your solution.
Tips
Requirements: Be sure you fully understand the problem, its final high level goal, and technical and non-technical constraints (such as whether this is a design for a prototype or long term product, a 3-person team or n-person team, and how long the team has to implement it).
Be sure you fully understand the problem, its final high level goal, and technical and non-technical constraints (such as whether this is a design for a prototype or long term product, a 3-person team or n-person team, and how long the team has to implement it). Success : What does success mean for your solution, and what are you optimizing for? How would you measure success? Be sure to describe and discuss with your interviewer this before starting.
: What does success mean for your solution, and what are you optimizing for? How would you measure success? Be sure to describe and discuss with your interviewer this before starting. Brainstorming : There are often many approaches to solving these questions. Some are less optimal, others a bit more. First, brainstorm many possible ways to solve the problem, from the most simple to the most optimal. Explain their tradeoffs. Be open to any new idea or solution that your interviewer may propose or you may think about. Don’t be afraid to change your mind.
: There are often many approaches to solving these questions. Some are less optimal, others a bit more. First, brainstorm many possible ways to solve the problem, from the most simple to the most optimal. Explain their tradeoffs. Be open to any new idea or solution that your interviewer may propose or you may think about. Don’t be afraid to change your mind. Trade-offs : Clearly explain the pros and cons between different possible solutions, why you would propose one solution versus another, and under which circumstances would that proposal change.
: Clearly explain the pros and cons between different possible solutions, why you would propose one solution versus another, and under which circumstances would that proposal change. Considerations: Make sure you have thought through and explained the different aspects of your solution, such as scalability, possible bottlenecks, single points of failure, monitoring considerations, and possible improvements. The proposed solution should fit the requirements and constraints and explain what could be improved if, for example, the constraints were more lenient.
Domain-Specific
This one helps assess the interviewee’s skills and expertise on a given domain. This might focus on iOS, Android, Web, machine learning, distributed systems, data processing, infrastructure, or other specific areas. Depending on the role you’re applying for, this may be broad (like backend programming), or specific (like data processing systems). It may also require you to use the programming language of that domain when applicable, for example Objective-C or Swift for iOS roles and Java or Kotlin for Android roles. The specifics of this interview depend on the domain, but many of the general tips mentioned for the other types of interviews would still apply, so be sure to keep them in mind!
Lunch Interview / Hiring Manager / Values
Many times there’ll also be a hiring manager and values interview during lunch time so you and your interviewer can get to know one another a bit better. The main goal is to see how your values align with our company values, but it’s also a great opportunity for you to ask any questions you may have about the role, team, and life at Pinterest.
What’s next?
After your interviews, you’ll hear from your recruiter in the days following to discuss the outcome. If there was a match for the role (congrats!) they’ll let you know the next steps, including compensation and specifics, and you should feel free to ask them anything, including for another conversation or lunch with the hiring manager or team members. We’ll then look forward to welcoming you on your first day at Pinterest!
For more tips on interviewing at Pinterest, check out A Pinterest Engineering Guide to technical interviews.
If you haven’t yet, check out our open roles at https://careers.pinterest.com/ and our open source projects at https://opensource.pinterest.com/. | https://medium.com/pinterest-engineering/what-its-like-to-interview-at-pinterest-e40f05a018f9 | ['Pinterest Engineering'] | 2018-12-20 03:58:08.315000+00:00 | ['Recruiting', 'Engineering', 'Startup', 'Careers', 'Technical Interview'] | Title it’s like interview PinterestContent Justin MejoradaPier Software Engineer Analytics Platform Tech Lead Interviews traditionally thought unpleasant necessary experience Candidates often find stressful many come poor interview experience past However interview clearest opportunity company articulate demonstrate company value culture approach It’s counterproductive candidate’s first live interaction company risk unpleasant experience stress tricky probability question cause feel place think interviewing company actually positive experience Interviews allow candidate demonstrate way solving realworld problem well learn like actually work Pinterest set rethink technical interview work we’ll share approach describe detail it’s like interview Pinterest Real solution gotchas allow candidate use online resource like Google Stack Overflow interview process mimic closely possible they’d see real work environment also provide machine common IDEs like VSCode Sublime candidate feel home code completion syntax highlighting shortcut they’re used question made specifically avoid “gotcha” moment retired whole host question reason want challenge candidate show u diligent critical thinking skill never want trick give candidate opportunity show u best work question aren’t set it’s u take seriously look problem solving skill show candidate tackle realworld technical challenge like may encounter daily work won’t asked question requires example dynamic programming Instead you’ll asked tackle programming problem representative work engineer typically encounter writing tool analyze log file There’s one type engineer Pinterest interview process care candidate’s ability code Showing growth mindset signal take account debriefs also purposefully split question several step gradually increase difficulty everyone find correct level challenge whether they’re new senior engineer also avoids awful feeling walking interview gotten part question understand different people different interview style — don’t worry trying someone you’re People different approach solving problem talk aloud write code others silently brainstorm diving solution long solve technical challenge clearly explain solution feel free talk much little you’d like you’re coming nontraditional background going full software interview loop isn’t option — also provide program like apprenticeship program still rigorous vetting better able identify passionate motivated people could huge asset company regardless whether studied particular topic college take unconscious bias seriously reminder tip checking unconscious bias every time enter candidate feedback rule prohibit discussing candidate interviewer avoid opinion contamination detail Interviewing Pinterest consists three main step Recruiter Call Phone Screen Onsite Interview Recruiter Call initial call Pinterest recruiter you’ll learn detail role interview process sure ask question might much Pinterest interviewing interviewing Pinterest Phone Screen You’ll speak Pinterest engineer role Karatio interviewer 45 60 minute may also use collaborative coding tool see code write depending question possibly even run code example may use CoderPad generic programming question JSFiddle web development question purpose phone screen get know general programming skill specialized domain knowledge applicable overall interest general format Five minute interviewer introduce ask candidate question starting One two coding question Five minute candidate may ask additional question role Pinterest coding question usually around data structure algorithm may also include domain knowledge element depending role Onsite interview onsite interview you’ll come Pinterest office participate usually five interview spread across following interview type Data Structures Algorithms Architecture Systems Design Domain Specific Lunch Interview Hiring Manager Values find one Types interview Data Structures Algorithms You’ll asked solve general programming question involving realworld data structure algorithm may use solve problem daytoday work won’t asked solve question using seldom used method like dynamic programming you’ll encouraged use whichever programming language you’re comfortable Normally question asked several potential solution ranging naive brute force approach optimal elegant approach tends one question may asked question time allows goal test practical skill used everyday programming Tips Practice — Brush CS fundamental data structure algorithm make sure you’ve practiced preferred programming language Resources — many resource online help practice example might check site like CareerCup various online course apps book like Cracking Coding Interview Use build intuitive pattern recognition see sample underlying subproblems algorithm approach commonly used solve goal use building block compose solution complex unique problem may see interview Naturally encounter problem you’ve already seen point interview example might say something like “I saw problem last month know solved x z method want proceed either methods” Don’t surprised interviewer still decides work problem Additional tip Whiteboard v Laptop Laptops provided candidate since that’s environment closely mirror daytoday work However whiteboarding option that’s you’re comfortable harder improve refactor code whiteboard compared IDE may want take account Laptops provided candidate since that’s environment closely mirror daytoday work However whiteboarding option that’s you’re comfortable harder improve refactor code whiteboard compared IDE may want take account Real code Even though it’s okay prefer start wireframing solution using pseudocode you’re expected able write final solution code would actually run Communicating plan important pseudocode one way talking plan making diagram may faster purpose Even though it’s okay prefer start wireframing solution using pseudocode you’re expected able write final solution code would actually run Communicating plan important pseudocode one way talking plan making diagram may faster purpose programming language highly encourage use programming language feel comfortable candidate tend pick language like Python Java JavaScript Ruby CC C However it’s completely acceptable prefer using le common language keep mind may take bit time explain solution interviewer familiar chosen language highly encourage use programming language feel comfortable candidate tend pick language like Python Java JavaScript Ruby CC C However it’s completely acceptable prefer using le common language keep mind may take bit time explain solution interviewer familiar chosen language Validation Remember validate input ask interviewer constraint characteristic Ideally solution fail gracefully invalid input provided least yield incorrect result Remember validate input ask interviewer constraint characteristic Ideally solution fail gracefully invalid input provided least yield incorrect result Testing Remember ask interviewer whether add test solution describe implement test based answer Regardless whether write explicit test describe loud make sure solution work planned able work across possible input Remember ask interviewer whether add test solution describe implement test based answer Regardless whether write explicit test describe loud make sure solution work planned able work across possible input Think problem first Don’t jump solving problem First spend time thinking problem end end cognizant time you’ve thought problem clarified approach interviewer start coding However decide later change approach that’s ok It’s incredibly important remain open new information adjust path accordingly question ask — fully understand problem constraint input expected output — know much time available — Based possible way solve problem one prefer tradeoff Break problem smaller one sure break big problem smaller one composed solve bigger one solved smaller problem likely think difference bigger problem modify compose solve bigger one sure break big problem smaller one composed solve bigger one solved smaller problem likely think difference bigger problem modify compose solve bigger one Describe planned solution plan tackle problem describe interviewer starting may able point issue provide tip start Interviewers encouraged conduct interview collaborative environment feel free talk you’re thinking tackling problem plan tackle problem describe interviewer starting may able point issue provide tip start Interviewers encouraged conduct interview collaborative environment feel free talk you’re thinking tackling problem Runtime complexity aware runtime complexity problem able talk Ideally mention interviewer you’re describing solution aware runtime complexity problem able talk Ideally mention interviewer you’re describing solution Ask question stuck ask tip It’s ok ask tip you’re truly stuck ideally tip would necessary it’s better ask tip able solve problem staying stuck It’s ok ask tip you’re truly stuck ideally tip would necessary it’s better ask tip able solve problem staying stuck Code quality readable simple concise code better readable simple concise code better Bugs ideally there’d bug it’s okay find bug solve interviewer spot bug ask question better understand work solve Architecture Systems Design interview you’ll asked solve open ended problem designing technical solution describing communicating effectively interviewer iterating needed polish address concern problem generally broad may include aspect API design online offline job computation client v server computation storage decision communication webmobile client database model design databasestorage selection local distributed algorithm code architecture caching scaling consideration common architecture communication approach like push pull pubsub etc Domainspecific role tend somewhat domainspecific version question time interview don’t require writing code However may require making basic architecture diagram otherwise communicating technical solution interviewer effectively able answer question solution Tips Requirements sure fully understand problem final high level goal technical nontechnical constraint whether design prototype long term product 3person team nperson team long team implement sure fully understand problem final high level goal technical nontechnical constraint whether design prototype long term product 3person team nperson team long team implement Success success mean solution optimizing would measure success sure describe discus interviewer starting success mean solution optimizing would measure success sure describe discus interviewer starting Brainstorming often many approach solving question le optimal others bit First brainstorm many possible way solve problem simple optimal Explain tradeoff open new idea solution interviewer may propose may think Don’t afraid change mind often many approach solving question le optimal others bit First brainstorm many possible way solve problem simple optimal Explain tradeoff open new idea solution interviewer may propose may think Don’t afraid change mind Tradeoffs Clearly explain pro con different possible solution would propose one solution versus another circumstance would proposal change Clearly explain pro con different possible solution would propose one solution versus another circumstance would proposal change Considerations Make sure thought explained different aspect solution scalability possible bottleneck single point failure monitoring consideration possible improvement proposed solution fit requirement constraint explain could improved example constraint lenient DomainSpecific one help ass interviewee’s skill expertise given domain might focus iOS Android Web machine learning distributed system data processing infrastructure specific area Depending role you’re applying may broad like backend programming specific like data processing system may also require use programming language domain applicable example ObjectiveC Swift iOS role Java Kotlin Android role specific interview depend domain many general tip mentioned type interview would still apply sure keep mind Lunch Interview Hiring Manager Values Many time there’ll also hiring manager value interview lunch time interviewer get know one another bit better main goal see value align company value it’s also great opportunity ask question may role team life Pinterest What’s next interview you’ll hear recruiter day following discus outcome match role congrats they’ll let know next step including compensation specific feel free ask anything including another conversation lunch hiring manager team member We’ll look forward welcoming first day Pinterest tip interviewing Pinterest check Pinterest Engineering Guide technical interview haven’t yet check open role httpscareerspinterestcom open source project httpsopensourcepinterestcomTags Recruiting Engineering Startup Careers Technical Interview |
991 | To Truly Capitalise on Your Success, Optimize Your Performance | To Truly Capitalise on Your Success, Optimize Your Performance
The key to optimization to create regular and consistent daily patterns that work for you, not against you
Image from rawpixel.com
The one thing that all highly successful people do is to stay organized and do more of what works. They make time to measure their results and follow efficient routines that save time and money.
They know what activities are critical to getting results.
Optimization is the process of incrementally improving your processes, systems, or better still how you work.
Success in any endeavour is a process — unless you’ve peaked and want to retire. Making progress in life and career requires measurements, upgrades and a flexible mindset to adapt to better systems, rules and principles.
Optimization is a popular concept in the technology world. Launching a product is always just the beginning — constant tweaks and upgrades are required to create something truly extraordinary.
The same concept can be applied to how we build our careers and lead our lives — a flexible mindset allows you to make room for improvement, upgrade or reinvention.
Find the small tasks you do over and over, and make them better
The main goal of optimization is to reduce or eliminate time and resource wastage, unnecessary costs, bottlenecks, and mistakes while achieving the objective of the process.
Although the natural tendency is to stick with what works, true growth comes from constantly challenging ourselves (and our projects, teams) in small ways every day.
“Despite research that encourages us to build on our strengths, we spend more time fixing what’s broken than optimizing what works. Why? Because any measure of success impairs our ability to imagine something better” argues Scott Belsky, founder of Behance, and Adobe’s Chief Product Officer.
By tracking your weekly, or monthly efforts (and corresponding results) you’re able to identify the processes that are contributing to the results you seek. You gain valuable insights for making improvements and optimizing processes that are not working.
Optimisations also help you track how much progress you’ve made on your primary tasks connected with your ultimate goals.
If you’re trying to lose weight, an example could be “work out half an hour” every day instead of sprinting for an hour once a week.
Have a bunch of emails to send? Set out ‘email time’ in your calendar and then sit down for half an hour, an hour, however long you need to take care of them. That way you don’t have to keep getting back to it every ten minutes.
Need to pay your bills? Don’t pay one when you find a moment and another in the next passing break. Put it directly into your calendar —” bill payment at 3 pm” works better. Or better still automate the process if you do it at the same time each month. Get clarity of plan and stick with it.
You can also optimise your environment by getting rid of simple distractions like notifications that make concentration even harder. The temptations of distractions are strong. Master your tools and make them work for you.
Rethink your processes for getting work done and improving yourself. Ask yourself: Is there a better way to achieve the same goal? How much time does process use/waste? Where does the process stall? Which part of the process can be automated to make for high-value work?
For effective optimisation, every detail is important. Through regular evaluation, you can stay ahead of yourself and achieve your project or life goals without wasting time and resources that could be used elsewhere.
“Despite the quality of your ideas and output, the impact you will make largely depends on your ability to constantly optimize — to build on your successes and grow them into something greater,” says Scott.
A few changes every week be can the difference between huge improvements and getting the same results every month. Optimise your efficiency and productivity and you will see noticeable strides towards your goals.
It pays to regain control of your time, energy, and environment! It’s time to reach your peak and get back to your “prime” to get what you want.
It’s important to be intentional about the role of optimisation in your life. Plan it and move on to important things that need your attention.
Optimize your way to success, but recognize that, eventually, obsessive optimization can become a detriment to getting real work done. Make the process work for you.
Optimize is about being consistent — being consistently productive, not pushing yourself to the unattainable 100%. | https://medium.com/kaizen-habits/to-truly-capitalise-on-your-success-optimize-your-performance-906dbb2712ef | ['Thomas Oppong'] | 2019-12-13 13:24:52.884000+00:00 | ['Creativity', 'Personal Development', 'Self', 'Productivity', 'Work'] | Title Truly Capitalise Success Optimize PerformanceContent Truly Capitalise Success Optimize Performance key optimization create regular consistent daily pattern work Image rawpixelcom one thing highly successful people stay organized work make time measure result follow efficient routine save time money know activity critical getting result Optimization process incrementally improving process system better still work Success endeavour process — unless you’ve peaked want retire Making progress life career requires measurement upgrade flexible mindset adapt better system rule principle Optimization popular concept technology world Launching product always beginning — constant tweak upgrade required create something truly extraordinary concept applied build career lead life — flexible mindset allows make room improvement upgrade reinvention Find small task make better main goal optimization reduce eliminate time resource wastage unnecessary cost bottleneck mistake achieving objective process Although natural tendency stick work true growth come constantly challenging project team small way every day “Despite research encourages u build strength spend time fixing what’s broken optimizing work measure success impairs ability imagine something better” argues Scott Belsky founder Behance Adobe’s Chief Product Officer tracking weekly monthly effort corresponding result you’re able identify process contributing result seek gain valuable insight making improvement optimizing process working Optimisations also help track much progress you’ve made primary task connected ultimate goal you’re trying lose weight example could “work half hour” every day instead sprinting hour week bunch email send Set ‘email time’ calendar sit half hour hour however long need take care way don’t keep getting back every ten minute Need pay bill Don’t pay one find moment another next passing break Put directly calendar —” bill payment 3 pm” work better better still automate process time month Get clarity plan stick also optimise environment getting rid simple distraction like notification make concentration even harder temptation distraction strong Master tool make work Rethink process getting work done improving Ask better way achieve goal much time process usewaste process stall part process automated make highvalue work effective optimisation every detail important regular evaluation stay ahead achieve project life goal without wasting time resource could used elsewhere “Despite quality idea output impact make largely depends ability constantly optimize — build success grow something greater” say Scott change every week difference huge improvement getting result every month Optimise efficiency productivity see noticeable stride towards goal pay regain control time energy environment It’s time reach peak get back “prime” get want It’s important intentional role optimisation life Plan move important thing need attention Optimize way success recognize eventually obsessive optimization become detriment getting real work done Make process work Optimize consistent — consistently productive pushing unattainable 100Tags Creativity Personal Development Self Productivity Work |
992 | Class 3: Becoming an AI design expert starts with becoming a data-driven designer | Discussion
What does data-driven design mean to you?
Netflix provides a great example of a data-driven customer-centric company. By introducing streaming video, their software “ate” the traditional DVD business. But Netflix soon realized their future wasn’t in the medium of delivery — it was in the wealth of data generated simply by people using the service. The day-to-day data generated by Netflix viewers provides a crucial ingredient to competing in the marketplace and defining the company’s mission: improving the quality of the service. Netflix uses passive data — the information gathered quietly in the background without disrupting users’ natural behaviors — to provide TV and movie recommendations, as well as to optimize the quality of services, such as streaming speed, playback quality, subtitles, or closed captioning. Of course, Netflix subscribers can contribute active feedback to the company, such as movie reviews or feedback on the accuracy of a translation, but the true value of Netflix’s user data is in the quiet, zero-effort observation that allows the company to optimize experiences with no friction or disruption to regular user behavior The future of software is data-driven by Dries Buytaret
2. Have you used data to find something out about their users and apply it to improving visual or interaction design?
3. What data we collect and the tools we use to analyze that data and give us answers about user behaviors
Amplitude
Find insights about your users and their interactions with your designs by creating if/then statements to get answers to your questions.
Find insights about your users and their interactions with your designs by creating if/then statements to get answers to your questions. Cloud Platform Analytics
Collects data on all of the user events we track for every Cloud product. Sends the data it collects to Amplitude so you can use it to create new insights. Where you go to request new data points be collected.
Collects data on all of the user events we track for every Cloud product. Sends the data it collects to Amplitude so you can use it to create new insights. Where you go to request new data points be collected. DB Warehouse Dashboard
I’m just learning about this but in short, it’s Amplitude but for products in the two DB2 warehouses. Connect with Marylia Gutierrez or David Kalmuk for more info.
4. Why would being a good at recognizing how data could improve UX lead to being a good AI designer?
Tomorrow’s applications will consume multiple sources of data to create a fine-grained context; they will leverage calendar data, location data, historic clickstream data, social contacts, information from wearables, and much more. All that rich data will be used as the input for predictive analytics and personalization services. Eventually, data-driven experiences will be the norm. And this basic idea doesn’t even begin to cover the advances in machine learning, artificial intelligence, deep learning and beyond — collectively called “machine intelligence”. Looking forward even more, computers will learn to do things themselves from data rather than being programmed by hand. They can learn faster themselves than we’d be able to program them. In a world where software builds itself, computers will only be limited by the data they can or cannot access, not by their algorithms. In such a future, is the value in the software or in the data? The future of software is data-driven by Dries Buytaret
5. How can we become awesome data designers and analysts?
What could a user tell me about this product/journey/page/interaction that would help me design a better experience?
How could I get the information I’d need from them to answer that question in the least obtrusive way?*
How many responses to my question will I need to feel confident in going forward with changes?
Do I have to make one answer, or should I be thinking about creating multiple options to give users choices or to A/B test?
For this section, we can use glassdoor as our example to pick apart:
6. Building relationships and collaborating with data experts
7. How would getting good at using data to influence decisions change the capabilities and role of a designer?
Using rules
Using machine learning
8. Homework discussion
What data did you identify as important for creating an IBM HR app?
Would your answer change now?
9. Eminence opportunities | https://medium.com/ai-design-thinkers/class-3-why-becoming-an-ai-design-expert-starts-with-becoming-a-data-driven-designer-37928fd7ff9 | ['Jennifer Aue'] | 2020-01-23 16:46:11.704000+00:00 | ['AI', 'Data Science', 'Adfclass', 'Design'] | Title Class 3 Becoming AI design expert start becoming datadriven designerContent Discussion datadriven design mean Netflix provides great example datadriven customercentric company introducing streaming video software “ate” traditional DVD business Netflix soon realized future wasn’t medium delivery — wealth data generated simply people using service daytoday data generated Netflix viewer provides crucial ingredient competing marketplace defining company’s mission improving quality service Netflix us passive data — information gathered quietly background without disrupting users’ natural behavior — provide TV movie recommendation well optimize quality service streaming speed playback quality subtitle closed captioning course Netflix subscriber contribute active feedback company movie review feedback accuracy translation true value Netflix’s user data quiet zeroeffort observation allows company optimize experience friction disruption regular user behavior future software datadriven Dries Buytaret 2 used data find something user apply improving visual interaction design 3 data collect tool use analyze data give u answer user behavior Amplitude Find insight user interaction design creating ifthen statement get answer question Find insight user interaction design creating ifthen statement get answer question Cloud Platform Analytics Collects data user event track every Cloud product Sends data collect Amplitude use create new insight go request new data point collected Collects data user event track every Cloud product Sends data collect Amplitude use create new insight go request new data point collected DB Warehouse Dashboard I’m learning short it’s Amplitude product two DB2 warehouse Connect Marylia Gutierrez David Kalmuk info 4 would good recognizing data could improve UX lead good AI designer Tomorrow’s application consume multiple source data create finegrained context leverage calendar data location data historic clickstream data social contact information wearable much rich data used input predictive analytics personalization service Eventually datadriven experience norm basic idea doesn’t even begin cover advance machine learning artificial intelligence deep learning beyond — collectively called “machine intelligence” Looking forward even computer learn thing data rather programmed hand learn faster we’d able program world software build computer limited data cannot access algorithm future value software data future software datadriven Dries Buytaret 5 become awesome data designer analyst could user tell productjourneypageinteraction would help design better experience could get information I’d need answer question least obtrusive way many response question need feel confident going forward change make one answer thinking creating multiple option give user choice AB test section use glassdoor example pick apart 6 Building relationship collaborating data expert 7 would getting good using data influence decision change capability role designer Using rule Using machine learning 8 Homework discussion data identify important creating IBM HR app Would answer change 9 Eminence opportunitiesTags AI Data Science Adfclass Design |
993 | Eat the Rich, Save the Planet | How we will get there.
Economic policies, legal frameworks, monetary incentives, and advances in infrastructure are all mechanisms required to instill a full lifestyle change in the richest 1%. While these are all substantial methodologies to force a change, they’re only a part of the puzzle. The choice an individual makes operates within broader contexts that don’t only include economic and legal parameters. Physical environments, media and advertising, social conventions, interpersonal influence, habits and routines, consumer choices, and attitudes and awareness all play a part in the enablement or constraint of a decision — particularly where lifestyle changes are concerned.
Incentives, targeted information, and choice provision play three key roles that have been used in the past to try to “nudge” people in the direction of a more environmentally sustainable lifestyle. However, these tactics are rarely enough to elicit profound change. According to the UNEP report, attempted sustainable transitions in the past have not been driven by consumers voluntarily choosing to consume more responsibly. Instead, social norms and changing product availability have been the causes of substantial change.
The report goes on to discuss how changes to infrastructure and social conventions, social influence, citizen participation, and habit disruption, are all methods required to cause society-wide lifestyle changes.
In the developed world, the accessibility of cars to wealthy individuals has enabled urban planning to cater to a car-dominant society. Cities are becoming more spread out, highways are getting wider to support more cars on the road, and it’s not uncommon for a wealthy household to own more than two vehicles. To reduce transportation-caused lifestyle emissions, urban planning must emphasize self-powered travel by making cities more walkable or bikeable. Furthermore, infrastructure must be put in place to support a more sustainable lifestyle, including increased charging ports for electric vehicles or more efficient public transport. The daily conventions of life will also need to be altered, so people can work and live their lives closer to their homes.
Social influence is known to be a catalyst for lifestyle change through the spread of behaviors through peer influence and challenging societal norms. Social influence is the reason why more companies are adding solar panels to their buildings, why people are transitioning to a vegan diet, and why businesses are trying to offer environmentally-friendly products. Unfortunately, social influence is one of the reasons why the lifestyles of the rich and famous have become desirable and have encouraged society to avoid cooperation with green initiatives. However, if those individuals make lifestyle changes themselves, their millions of followers will quickly follow suit.
Finally, the disruption of habitual behavior is a requirement in the breakdown of the firewall leading to a lifestyle change. Habits are based on stable contexts, which makes them suitable for permanent repetition. However, by changing the context in which the habit stands. the behavior itself comes into question, and the overall lifestyle routine can be disrupted. Disrupting behaviors and habits opens an opportunity for a new lifestyle to take shape, one that promotes a more sustainable way of living that encourages walking to work or investing in energy-efficient appliances.
Through a rich combination of structural (legal frameworks, economic policies, infrastructure), social and contextual (media and advertising, social conventions, interpersonal influence), and personal (behavior changes, consumer choices, awareness, and attitudes) approaches, integrated policies can be formed to simultaneously force and encourage the richest individuals in society to undergo lifestyle changes to support a more eco-friendly way of life.
Ultimately, the transition to environmentally sustainable lifestyles by the global wealthiest 1% will require deep-rooted socioeconomic, cultural, political, and behavioral changes that will require the participation in equal parts of the rich and famous and the government. Doing so will cause dramatic cuts to greenhouse gas emissions and will ensure the world achieves the Paris Agreement objectives promptly for both the future of the planet and its citizens. | https://medium.com/climate-conscious/eat-the-rich-save-the-planet-d782b35d9ce4 | ['Madison Hunter'] | 2020-12-14 14:02:34.084000+00:00 | ['Climate Change', 'Global Warming', 'Activism', 'Environment', 'Sustainability'] | Title Eat Rich Save PlanetContent get Economic policy legal framework monetary incentive advance infrastructure mechanism required instill full lifestyle change richest 1 substantial methodology force change they’re part puzzle choice individual make operates within broader context don’t include economic legal parameter Physical environment medium advertising social convention interpersonal influence habit routine consumer choice attitude awareness play part enablement constraint decision — particularly lifestyle change concerned Incentives targeted information choice provision play three key role used past try “nudge” people direction environmentally sustainable lifestyle However tactic rarely enough elicit profound change According UNEP report attempted sustainable transition past driven consumer voluntarily choosing consume responsibly Instead social norm changing product availability cause substantial change report go discus change infrastructure social convention social influence citizen participation habit disruption method required cause societywide lifestyle change developed world accessibility car wealthy individual enabled urban planning cater cardominant society Cities becoming spread highway getting wider support car road it’s uncommon wealthy household two vehicle reduce transportationcaused lifestyle emission urban planning must emphasize selfpowered travel making city walkable bikeable Furthermore infrastructure must put place support sustainable lifestyle including increased charging port electric vehicle efficient public transport daily convention life also need altered people work live life closer home Social influence known catalyst lifestyle change spread behavior peer influence challenging societal norm Social influence reason company adding solar panel building people transitioning vegan diet business trying offer environmentallyfriendly product Unfortunately social influence one reason lifestyle rich famous become desirable encouraged society avoid cooperation green initiative However individual make lifestyle change million follower quickly follow suit Finally disruption habitual behavior requirement breakdown firewall leading lifestyle change Habits based stable context make suitable permanent repetition However changing context habit stand behavior come question overall lifestyle routine disrupted Disrupting behavior habit open opportunity new lifestyle take shape one promotes sustainable way living encourages walking work investing energyefficient appliance rich combination structural legal framework economic policy infrastructure social contextual medium advertising social convention interpersonal influence personal behavior change consumer choice awareness attitude approach integrated policy formed simultaneously force encourage richest individual society undergo lifestyle change support ecofriendly way life Ultimately transition environmentally sustainable lifestyle global wealthiest 1 require deeprooted socioeconomic cultural political behavioral change require participation equal part rich famous government cause dramatic cut greenhouse gas emission ensure world achieves Paris Agreement objective promptly future planet citizensTags Climate Change Global Warming Activism Environment Sustainability |
994 | Two Weeks with a Teen Entrepreneur | Two Weeks with a Teen Entrepreneur
The Lessons
Photo by Garrhet Sampson on Unsplash
3/30/20 — The Start
1:00 A.M. — Normally I publish my articles on Sunday but I ran a little late yesterday because I’d been working on my drop shipping website all week. I debated doing it the next day, but decided to publish it at 1:00 A.M and finished around 1:30 A.M. I normally write my posts a day or two before, which just leaves publishing it when the time comes. I prefer it this way because then I am able to look over the post once more before I publish it.
8:00 A.M. — I woke up for my first class but was waiting for the stock market to open. I could already tell today wasn’t going to be a good day for me because I had put most of my money in Cannabis, and most of the Cannabis stocks were down pre-market.
8:30 A.M. — I was proven right, the stocks began dropping right off the bat. HEXO, one of the stocks that I owned dropped about 10 percent initially, but kept on spiraling lower.
** For most of the day today I did school work, I checked in a few times on my dropshipping site, one or two views, I plan to begin marketing it within the next day or two **
3:30 P.M. — For the day I booked around $300 losses and told my self that if I lose $150 more the next day I am going to sell all the stocks that I own in Cannabis
6:30 P.M. — I added more to my email marketing list, I am around 100+ emails currently. My goal is to be around 200 before I release, and add 25–50 per day. I believe the key to the success of the drop shipping is marketing, I may include a discount code for anyone who read my blog, www.ramenfreefinance.com, but the hope is to grow both of these platforms.
9:30 P.M. — I began looking for another way to make money online. This is how I arrived at blogging on Medium and drop shipping (investing was shown to me from my dad). Something that I am thinking about getting into is affiliate marketing, but I am not sure if that is worth the time that I will put into the marketing. Maybe if I tie it with the drop shipping that could help, but trying to sell too many things to a buyer is definitely going to reduce sales.
12:00 A.M. — Published this article.
Lesson of the Day: Don’t hold a stock before its earnings. It is definitely going to be volatile so make sure that if you do this, you know exactly what you are doing. Instead, I would wait until after the earnings and try to spot a trend.
3/31/30 — A Stock on Pause
9:00 A.M. — I wake up and log onto the stock market. I am making about $100, so even though I have not made back the $300 I had, it is something. There’s only one slight problem, of the stocks that I have $500 hasn’t changed at all. At first, I thought that maybe it’s just neutral today and not changing, so I don’t do anything about it. The company is CannTrust, ticker being CTST.
10:00 A.M. — I know something is up. The stock hasn’t changed in an hour and a half and so I dig around and there’s this article by PR Newswire that says “CannTrust Obtains Initial Order under Companies’ Creditors Arrangement Act (Canada).” I’m not going to pretend like I know what that means, but it sounded good for the company, so I really couldn’t understand why the stock was closed.
12:00 P.M. — My profits are beginning to decrease, from up $100, I’m now up $50. Still nothing on CannTrust. I really haven’t done anything for the blog yet, I’m going to write it later for my Wednesday post. I also want to try and finish my homework before tomorrow to focus on my dropshipping and blog email list, and create the email I want to send out.
2:00 P.M. — My profits continue to dwindle, I am at around $35, and it’s still dropping.
4:00 P.M. — An article comes out by Benzinga stating “CannTrust to be Delisted From NYSE and TSE.” That’s when I felt a bit panicked. Was I just going to lose the $500 that I had in it? I did some research and honestly really wasn’t any more satisfied with the answer I found. I’m going to wait until tomorrow and see what happens with the stock.
6:00 P.M. — Added a few more emails to my marketing list for launch tomorrow.
9:30 P.M. — Began writing my next article, “Dropshipping: A personal Guide” which you can check out at this link: http://ramenfreefinance.com/2020/04/dropshipping-a-personal-guide/
11:00 P.M. — Checked up on crude oil prices and the Dow Futures, which both were down 1 and 4 percent respectively but only tomorrow morning will tell the way the market is going to turn.
Lesson of the day — Another stock market lesson is to pay attention to warnings. I know this sounds obvious but there were a few rumors the CannTrust would be de-listed, and one of the requirements is that your share price needs to be above $1, and CannTrust was way below this, and I took arish because I thought I could win big. If any of you guys are investing just keep that in mind, don’t try to play poker with the market.
4/1/20 — The Fall Continues
12:00 A.M. — I posted my dropshipping article, to read it check out my profile. I then made two posts on LinkedIn, one with my blog article and the other with a link to my Shopify store, as a means to grow the audience.
4:00 A.M. — Finished my post for the Financial Journal publication and published it, and then went to bed
11:30 A.M. — I ended up going to bed quite late last night, so I woke up really late. I had an internship meeting from 1–2 to attend, so I checked stocks, ate breakfast, went for a shower and got ready for the meeting.
1:00 P.M. — I attended the internship meeting which talked about what our final project was to be. I had been doing this internship for the majority of the year, which was helping coursestars, a tutoring company with their marketing. Now it was time for the final project.
3:00 P.M. — I’d been so I checked the market and saw that I was losing $120 and there was no news on CannTrust. I considered selling but decided that I would wait one more day. If things are bad tomorrow I’m out of Cannabis. I took a risk and it obviously has not been paying off at all.
4:00 P.M. — I added some more people to my email list. I now have six lists with varying numbers, but my biggest has about 80 emails so there is really good progress being made there and hopefully it is enough for the launch tomorrow. I am trying to go to 300 emails for tomorrow, as an initial launch.
7:00 P.M. — Worked on the email for the launch. My thought process is this, the email needs to be simple but also convey a message that doesn’t make me look stupid. I’ve known most of these people as teachers, friends or students, which is why this is incredibly important, especially if I want them to continue checking out my website and buying things from my store. The email is not yet done, but it should be by tonight.
12:00 A.M. — I am going to have a Facetime for school at 8 A.M. tomorrow morning, so I posted the article and decided to go to sleep.
Photo by Chris Lawton on Unsplash
4/2/20 — The Postponing
8:00 A.M. — I woke up because I had a math class. I looked through some of the news in the morning. The coronavirus cases were reaching 1,000,000 cases worldwide, and there were some 6.6 million people that filed for unemployment benefits. The world and the United States were not in a good shape.
12:00 P.M. — I had a couple more classes and the works but I started adding emails to my email list.
1:30 P.M. — I ended up adding 150 emails within this time frame, and was really excited to send out the email within the hour. This led to a problem, I remembered that I did not have my email done. At this point, I had two options. I could either rush and finish it and then hope that it had a good impact on my intended audience, or wait until Monday and have a better email to send. I’d been waiting all week to send out the email today. I was psyched that hopefully at least 50 people would check out my dropshipping website, and maybe even a few buy some things. But, I thought about it for a bit, and realized that if I did not make a good impression on these customers, there was no chance they would come back. Hence, I decided that I would finish the email over the weekend as you know the saying “quality over quantity.”
4:00 P.M. — I checked the market and I made $50 in Cannabis today. Compared to my losses of some $300+, it is not a lot, but at least it is a start. My cannabis investing lives to see another day.
7:00 P.M. — I did some more investigating into Covid-19. One of the kids from my old school made a post about how people need help with their businesses now more than ever. I thought about some things that I could do to help, but also actually start my first small business. This is something that I had thought about for a while, but I never really got around to it thinking it was too hard or that I did not have enough time. Sadly, we did not come up with any ideas today. To me, it seems that everything is already taken, so I’m going to need to do a lot more thinking, especially if I want to help people during Covid-19.
12:00 A.M. — I didn’t really do much in business and finance I realize, but I know that this weekend is going to be a grind because I want to make 6–7 different emails to target different groups of people in my email list. Right now, I’m probably going to watch a movie and then call it a night.
Lesson: I think a really big lesson I learned is don’t try to hurry something up. I get if you had deadlines that you have to meet then of course, but if you’re doing something as a personal project, the quality is just more important.
4/3/20 — Epiphany?
10:00 A.M. — I woke up and looked at the market. Cannabis started the day up, so that looked like a good sign, and then I began scrolling through Medium. I looked at this one article on success, and there was this thing that successful people usually wake up early. I thought about that, and I was like, I’m waking up at 10 every day, does that mean I’m not going to be successful? I thought it couldn’t be true, so I did some research, and it turns out that most successful people wake up early. But, here’s my take. Most people don’t want to have billions. They think they do, but honestly, what are you going to do with billions. The chances of you being able to use a billion dollars are quite slim, if you think of a 1, followed by NINE zeroes. Let me put that into perspective. A common house item that I think most people have is a TV, and the average cost of one is $500. That means you can buy 2 million TV’s for that 1 billion. Personally, I don’t know what I would do with 20 TV’s, let alone 2 million. So the rich of the rich might wake up very early, but there are a lot of millionaires out there. For example, the people who made millions of Bitcoin didn’t seem like the people to have the same work ethic as the rich of the rich, and they are still doing quite well for themselves. That might have been a bit difficult to follow, but I think that waking up early doesn’t define success. Thank you for listening to my Ted Talk.
12:00 P.M. — I added about 70 more emails to my list, I’m really excited about the launch on Monday. If you have any questions reach out at [email protected].
2:00 P.M. — Added another 60 emails. It was a really good idea to add emails because even though it takes a long time, it’s a really good way to reach people and make what you’re saying heard.
8:00 P.M. — Finished the email, and have a picture linked below. I kept sending a test email to myself but I could not find it. I sent three more, and still was wondering why it wasn’t sending. Then I checked my spam mailbox, and they were all there. At first, I thought it would be an easy fix, but then realized that I would need to do a lot more digging, after seeing three was something called the CAN-SPAM Act, and some other rules. This is going to take longer than I thought.
Lesson of the day: Always expect some things can throw you of course. I know this sounds like another thing everyone should know, but I’ll give you some more. See sometimes the things that take you of course, are what you need to think about and potentially re-focus too, and then maybe you shall have the clarity you need.
4/4/20 — Re-Thinking
1:00 P.M. — I woke up just now. If you want to know why I wake up so late, check out my last article: https://medium.com/@aryandgandhi/4-3-20-epiphany-8612db76b8e. Anyway, the stock market wasn’t open so I just chilled in the morning and then went for a shower. During my shower, I thought about some business opportunities during this pandemic. About a year ago, I started my own blog, and then a few days ago my own store. At a time like this, the world does not need another blog or another store, hence the brainstorming. I am sad to report that today was not fruitful in thinking of anything, but I am going to continue. I also encourage you to think about what kind of businesses you could start to help the world during the Covid-19 outbreak.
4:00 P.M. — I wrote my blog post for tomorrow, No B.S. Kellogg, which analyzes the company Kellogg and talks about a few interesting facts about it. It will be up by the end of the day tomorrow.
6:00 P.M. — Added a few more emails to my list in anticipation of the release on Monday. If you want to be added to the list, just fill out the form below or comment your email. I thenbegan creating the email and finished, but ran into a small problem. When I was importing the people into the email it did not work, and so that is something that I am going to figure out. Another thing is that the email is being sent straight to spam so that is something that I need to work on.
10:00 P.M. — Tried figuring out the spam and the uploading the people, but it did not work, I am going to spend the next day figuring that out.
Lesson: Take the opportunities around you and make the best of them. This global pandemic is horrible for everyone, but there are always things you can do to help and opportunities to act on. Always keep that in mind.
Photo by bruce mars on Unsplash
4/5/20 — Ready Set Go!
12:00 P.M. — I woke up and went through Medium and checked the live Covid-19 case count. I usually check this 4–5 times in a day to see what is happening around the world in terms of this pandemic. I would recommend this to everyone as well, as it keeps you aware of what is happening and can allow you to act accordingly.
1:00 P.M. — I really wanted to figure out the problem that I talked about in my last article, and so I worked on Mailchimp for a while. I sent the email to a few friends and it did not go in their spam, which was a good sign. I sent the email to myself 4–5 times, and 2 of those times it went into my spam mailbox. I also changed up the font and parts of the email. As it turns out, pictures are sometimes blocked when sending such emails, so I edited my content to make sure that none of the pictures were referenced.
3:00 P.M. — Finished the email and uploaded the contact in anticipation of sending out the email tomorrow. I will let everyone know the statistics that arise after I send out the email tomorrow.
5:00 P.M. — Published my article No B.S. Kellogg which looks at the company Kellogg during this pandemic, and talks about the stock price and the future of the company.
9:00 P.M. — Thought more about what business to start during the pandemic. I thought about two ideas. One was a type of toilet paper business, but that seemed unsustainable. People were very hyped up about it for a brief time, but the hype has or is in the process of dying around it. The other idea has something to do with a cure for Covid-19, which would be very lucrative, but I do not have close to enough experience in anything related to biology and diseases.
11:00 P.M. — I added a few more emails in preparation of tomorrow, and got ready for school as I had my 8.00 A.M. class.
Lesson: The lesson for today is persistence. To me, the Mailchimp email that I was going to send out really annoyed me. I was really close to deleting it, but decided against it because I had put in a lot of work. Turns out after one more hour spent I figured everything out and was ready to test. Sometimes if you are close to giving up, then just look at the problem from a different angle and chances are it will work out.
4/6/20 — The Calls
8:00 A.M. — I woke up to sign in to math and then after class I went to sleep.
10:30 A.M. — I woke up again for my Advanced Programming class which started at 11 and showered before.
12:30 P.M. — I started my college counseling meeting.
2:30 P.M. — I finished my college counseling meeting and sent out the emails to 120 people.
5:00 P.M. — A few days ago someone reached out to me on Linkedin and asked to set up a time to talk to me about the opportunity. I called him at five and we talked about who we both were, and he started off by giving me a homework assignment and a book to read. At the moment, part of me feels like this is not really a legit opportunity, but at the same time if it is, I don’t want to lose it. I am going to continue to work with this person and see where it leads me.
5:30 P.M. — As it turns out, I got 111 opens, which is quite impressive. Over 90% of the people that I sent out the email too opened it, which to me is quite impressive. On the other hand, only seven people clicked on the links that were in the email. This was not as high as I had hoped, but I shall learn more in terms of how to create better and more directed email campaigns.
7:00 P.M. — Similarly, another husband and wife pair reached out to me and we did something quite similar. We talked about each other, our backgrounds and then went into talking a bit about our personal lives. At the end of the call, the wife sent me a document by email that I should read which would explain to me different aspects of the business world. While it seems interesting, I am still a bit skeptical on where it is going to lead.
9:00 P.M. — Added more emails from another school to an email list. I am very excited about this emailing idea, it seems like a very good way to market.
Lesson: Never close a door (in terms of opportunity). Almost 60% of me feels like these two calls are fake and they have some ulterior motive. Don’t get me wrong, they are very nice people, but that is a gut feeling I have. At the same time, on the 40% chance that I am wrong, this could be an amazing opportunity for me. As long as you are not putting yourself in danger, always try to keep all your doors open.
4/7/20 — The Day of the Mindset
10:00 A.M. — I woke up and wrote my blog post for tomorrow, called The Mindset. If you want to read it check back in with my profile tomorrow, but here is a quick summary. I was recently reached out via LinkedIn and asked to read A Business in the 21st century, a book by Robert Kiyosaki. The book was recently interesting, but I want to talk about one thing that really stood out to me, called the Cashflow Quadrant. The Cashflow Quadrant is split into four parts, E, S, B and I, each which represents a different type of job that people hold. All jobs/ work titles can be put under one of these four parts of the quadrant. I wrote about this because I found it really informative, and wanted to share what I thought about it. I am nowhere close to an expert on it, so I also wanted to know people’s thoughts on the Cashflow Quadrant, and their experiences with it.
1:00 P.M. — I added another school with emails to the list.
3:30 P.M. — I sent out another mass email to 103 and recipients. About 25 of them were friends, and the rest were faculty at a high school. I will report the numbers soon. The stock market started up over 900 points, but by the end of the day ended down 26 points. The market is very volatile right now and what’s happening with Covid-19 does not show signs of slowing down, so investing is very risky in my opinion.
5:30 P.M. — I think I am going to make a book of all of these at one point. I think it can offer insights into mistakes and how I am growing the business that I want to. I am not sure how or when I am going to begin combining them, but it is just a thought at the time.
9:00 P.M. — Thought about some jobs that I could get over the summer. I was an intern at Caterpillar last year, but I don’t know how that will fare this year. One option I have is to work at Hy-Vee, but I’m not sure if my parents will let me apply due to Covid-19.
Lesson: Work smart, not hard. I read a little bit of the book and then had then watched a youtube summary on it. A book that would have taken me 7+ hours, I finished in under an hour, and I got the general meaning of. Don’t be afraid to take a shortcut at times, there is a reason they exist, and they aren’t all too bad.
4/8/20 — The Second Meeting
10:00 A.M. — I woke up and told my self I would put my business projects on hold until I finished studying for my math test. This was the one class that I had to worry about, so I put all my work into studying for the next few hours.
2:00 P.M. — I added the Dunlap Grade school to an email list, and I sent out another email to 100 teachers between two elementary schools. I am going to start sending out emails every three days as opposed to every day and add one school a day to an email list.
4:00 P.M. — I publish my post called The Mindset. Check it out here, it talks about what I learned from Robert Kiyosaki’s Business in the 21st Century.
5:00 P.M. — I had a few school meetings and hung out with the family.
9:30 P.M. — I had my second meeting with my “mentor,” and it was quite interesting. First, we only planned on going from 9:30 P.M. — 10 P.M. but went until 10:45 P.M. as I wanted to hear more about this opportunity. It was a multi-level marketing opportunity, where I would start a business and the team supporting me would make a profit through a company called Amway. This company seems legit, but I still have a few doubts. First, why me? I’m a high school student, and this man is spending 2–3 hours a week working with me, so why. Wouldn’t it be easier to work with an adult as opposed to me? Then, of course, is this team he keeps saying I am going to meet. He said in a week or two I would get to meet the team, so I am not going to make judgments yet, but if this opportunity is legit, I will be very excited.
4/9/20 — The Haircutter
8:00 A.M. — I wake up for my first class, as I have classes all morning.
12:00 P.M. — I took a shower, but here is the thing, I decided to cut my own hair. It was a spur of the moment decision, my dad had one of those hair clippers, and I took it and shaved everywhere but the top. The obvious reason? I was bored and wanted a change, but this got me thinking. Before I started cutting my own hair a few months ago, I would always go to this one Asian male at Great Clips. We would always have productive conversations because he was an art teacher who was also very interested in doing side hustles. I know one of the things he did was illustrate the images in a Chemistry textbook which netted him around 2–3 grand. While I was cutting my hair today, I realized that he really did have an influence on me. He was a married man with kids, but he still found time to cut hair, be an art teacher and illustrate a chemistry textbook. That’s how I know that at this age especially, the side hustles that I want to accomplish are possible.
3:00 P.M. — Added another email to the list, I am going to send out an email tomorrow marketing the blog to around one hundred more people. Take a look at this article: to know how my last email session went.
6:00 P.M. — I was supposed to have a meeting with another MLM person, but thanks to the advice of Prickly Pam and Kim McKinney, I was able to avoid what could have been a huge waste of my time. Thank you!
9:00 P.M. — I looked through my portfolio, and it was quite concentrated in Cannabis. I decided that sometime next week I would t my losses of some $400, and put it into Boeing or United Airlines. I see a strong rebound in airline stocks, so I am waiting to see if Covid-19 will become worse and invest based on that.
Photo by Eugene Chystiakov on Unsplash
4/10/20 — Pyramid Selling
12:00 P.M. — I woke up and fixed my hair and showered.
2:00 P.M. — I did more research on network marketing. In my other articles I talked about my personal experiences, but here is what I found. Multi-level marketing (can be called pyramid selling) is a marketing strategy in which you sell products, and receive a commission for every person whose products you sell that you recruit. To me, this sounded very much like a pyramid scheme, but as it turns out, there is a difference. A pyramid scheme is where more emphasis is placed on the recruitment of others, as this makes more and more money for the people at the top. Multi-Level Marketing is when more emphasis is placed on selling, and recruitment just happens along the way. Looking at it, they both seem to be very similar and so I believe that I made the right decision by staying away from such a scheme.
5:00 P.M. — I added another school to my email list, as I planned on sending the email out, but between cutting my hair and showering I decided that I would do it Monday.
7:00 P.M. — With AP tests coming up and also wanting to pick up juggling, I decided that I would take the weekend slow. I will still publish the next two days, but there won’t be much to report because I realized with all this time on my hands I want to pick up some new stuff. Dancing is also on my list, I suck at it, but I want to get much better. Let me know what you guys want to improve on below.
Lesson: This more advice than a lesson, pick up something to do. I don’t care what it is, magic, investing or cup stacking, pick something and learn it. I can guarantee that this will make you feel good and will also keep your brain on edge, as you keep learning.
4/11/20 — Mass Emailing
12:00 P.M. — I woke up.
4:00 P.M. — As I said, I was going to take it easy this weekend, so I decided to just add emails to my list. As I was adding them, I thought about how there had to be an easier way to do this. I mean, thinking about it, I could write a pretty basic program to scan a website and get the emails. I’m nowhere close to a good programmer, so I thought of just looking at the string with the @ symbol on the page and then printing that. While this would take a lot of time initially, by the end of the week or two it should be much easier to extract emails.
7:00 P.M. — Wrote my article for tomorrow, No B.S. Las Vegas Sands. In the article, I focus on three main topics: a brief description of the company, of the stock price and then a few interesting facts. If interested, it will be posted by 3:00 P.M. CST.
Lesson: Take breaks. This morning I fixed my lawnmower, and did some outdoor work and it felt really nice. Don’t always be on the grind, or you’re going to fail soon.
4/12/20 — Las Vegas Sands
10:00 A.M. — Woke up and lied in bed.
3:00 P.M. — Published No B.S. Las Vegas Sands, it was an interesting company to learn about.
5:00 P.M. — Worked a bit on my email program, but manually added 70 emails to my list.
Lesson: For today, it is more of a recommendation, but something I was watching on Netflix was called Dirty Money, which is a show about corruption and lying in money.
4/13/20 — Easter Monday
11:00 A.M. — I woke up, and was going to send out a mass email, but since schools are closed I decided to wait until tomorrow. Below is a screenshot of my email:
1:00 P.M. — As today is Easter Monday, I decided that for this article I would put together a list of my most interesting facts from my no B.S. section, which analyzes a company and gives investing recommendations.
Here I have compiled a list of facts of multiple companies and articles to them:
Aurora Cannabis:
The largest Cannabis acquisition in history occurred in mid-2018 when Aurora Cannabis purchased Canni-Med for $1.1 Billion.
They have a market valuation of $1.7 Billion.
The company was founded in 2006 by Terry Booth, Steve Dobler, Dale Lesack and Chris Mayerson, of which Booth and Steve Dobler each invested $5 million+ of their own capital
AMD:
So far, AMD has had 5 C.E.O’s, of which three have been electrical engineers, the longest being Jerry Sanders, who was the founder from 1969–2002
The market capitalization of A.M.D is $54.3 Billion
There are 200 million+ gaming consoles that AMD powers, so chances are, one of your gaming consoles are AMD powered.
British Petroleum:
In 1967, BP spilled some 32 million gallons of crude oil into the Atlantic, and gaining the title of Britain’s largest oil spill.
BP has a market capitalization of $131.6 billion.
With a revenue of around 307 million and 75,000 employees, BP has a revenue of 4.1 million per employee.
Cheesecake Factory:
In 2010, it was rated the worst family restaurant in America by Men’s Health magazine because it served high caloric and high-fat foods.
The Cheesecake Factory has a market capitalization of 1.75B.
The company donates more than 500,000 pounds of food each year to the Harvest Food Donation program and works with Feeding America and the Salvation Army to provide an annual Thanksgiving Day Feast for those in need.
Delta Airlines:
It actually applied for bankruptcy on September 14th, 2005, because of the rising cost of fuel, but in April of 2007 managed to last for two years and was re-enlisted in the New York stock exchange.
The market capitalization is $38.98 Billion
As of December 5th, 2019, Delta was the leading airline in terms of revenue serving 200 million people and taking customers to 300+ locations in over 50 countries.
Eventbrite:
Eventbrite hosts events in 170+ countries, which means it’s in 87.1% of countries in the world
The market capitalization of Eventbrite is 1.9B
Eventbrite was founded by 3 people, two of whom were married, Julia Hartz and Kevin Hartz.
Fitbit:
The 10,000 step fit-bit goal isn’t random, if the goal is met, then the person did at least 30 minutes of physical activity that day, which adds up to the CDC’s recommended 150 minutes per week.
The market capitalization of Fitbit is 1.74B.
The founders of Fitbit were inspired by the ability of the motion sensor on the Nintendo Wii to track movements of people as they played in games such as Just Dance.
General Electric:
Two employees of GE, Irving Langmuir and Ivar Giaever, won the Nobel Prize in 1932 and 1973 respectively.
The market capitalization of GE is 106.99B.
In 2011, GE was ranked as the 14th most profitable company in the world out of the Fortune 500.
GrubHub:
In 2006, Maloney and Evans won first place in the University of Chicago Booth School of Business’s Edward L.
The market capitalization of GrubHub is $4.22 Billion.
GrubHub is in over 3,200 cities and growing.
Hexo:
With over 1,100 employees, Hexo is the fourth largest compared to other Cannabis companies.
Hexo has a market capitalization of $310.392 million.
Hexo hopes to bring its earnings to positive as Cannabis 2.0 becomes more and more widesprea
Harley Davidson:
They recently began construction of a new plant in Thailand in 2018, its fourth international plant.
They have a market capitalization of $3.23 billion.
For about two decades, from the 1960s to the 1980s, Harley Davidson actually produced three and four-wheel golf cars.
Intel:
Intel has its own museum that is located in its headquarters in Santa Clara California, with over 85,000 visitors per year.
They have a market capitalization of $196.015 billion.
Intel has a philanthropic branch called the Intel foundation that has donated $80 million to California schools and nonprofits.
JCPenney:
The founder of JCPenney actually started a butcher business before he founded JCPenney.
JCPenney has a market capitalization of $123.36 Million.
The founder of Walmart, Sam Walton once worked for JCPenney.
Kellogg:
Almost all of their cereal boxes are made from recycled paperboard, which is similar to cardboard, except with only one layer.
They have a market valuation of $21.78 Billion.
The mascot of Kellogg, Tony the Tiger, was actually created in 1951.
Photo by Daniel von Appen on Unsplash
There you have it, stay tuned for more!
Check out the blog: http://ramenfreefinance.com/
Get a free e-book: https://docs.google.com/forms/d/e/1FAIpQLSdoY3-hEG5vG4l_ryfMN9L-RFJjsRadxdIOD9aD1e4e4-wg2g/viewform?usp=sf_link | https://medium.com/never-fear/two-weeks-with-a-teen-entrepreneur-3ae5822c760 | ['Aryan Gandhi'] | 2020-05-19 19:00:48.421000+00:00 | ['Business', 'Entrepreneurship', 'Startup', 'Life', 'Finance'] | Title Two Weeks Teen EntrepreneurContent Two Weeks Teen Entrepreneur Lessons Photo Garrhet Sampson Unsplash 33020 — Start 100 — Normally publish article Sunday ran little late yesterday I’d working drop shipping website week debated next day decided publish 100 finished around 130 normally write post day two leaf publishing time come prefer way able look post publish 800 — woke first class waiting stock market open could already tell today wasn’t going good day put money Cannabis Cannabis stock premarket 830 — proven right stock began dropping right bat HEXO one stock owned dropped 10 percent initially kept spiraling lower day today school work checked time dropshipping site one two view plan begin marketing within next day two 330 PM — day booked around 300 loss told self lose 150 next day going sell stock Cannabis 630 PM — added email marketing list around 100 email currently goal around 200 release add 25–50 per day believe key success drop shipping marketing may include discount code anyone read blog wwwramenfreefinancecom hope grow platform 930 PM — began looking another way make money online arrived blogging Medium drop shipping investing shown dad Something thinking getting affiliate marketing sure worth time put marketing Maybe tie drop shipping could help trying sell many thing buyer definitely going reduce sale 1200 — Published article Lesson Day Don’t hold stock earnings definitely going volatile make sure know exactly Instead would wait earnings try spot trend 33130 — Stock Pause 900 — wake log onto stock market making 100 even though made back 300 something There’s one slight problem stock 500 hasn’t changed first thought maybe it’s neutral today changing don’t anything company CannTrust ticker CTST 1000 — know something stock hasn’t changed hour half dig around there’s article PR Newswire say “CannTrust Obtains Initial Order Companies’ Creditors Arrangement Act Canada” I’m going pretend like know mean sounded good company really couldn’t understand stock closed 1200 PM — profit beginning decrease 100 I’m 50 Still nothing CannTrust really haven’t done anything blog yet I’m going write later Wednesday post also want try finish homework tomorrow focus dropshipping blog email list create email want send 200 PM — profit continue dwindle around 35 it’s still dropping 400 PM — article come Benzinga stating “CannTrust Delisted NYSE TSE” That’s felt bit panicked going lose 500 research honestly really wasn’t satisfied answer found I’m going wait tomorrow see happens stock 600 PM — Added email marketing list launch tomorrow 930 PM — Began writing next article “Dropshipping personal Guide” check link httpramenfreefinancecom202004dropshippingapersonalguide 1100 PM — Checked crude oil price Dow Futures 1 4 percent respectively tomorrow morning tell way market going turn Lesson day — Another stock market lesson pay attention warning know sound obvious rumor CannTrust would delisted one requirement share price need 1 CannTrust way took arish thought could win big guy investing keep mind don’t try play poker market 4120 — Fall Continues 1200 — posted dropshipping article read check profile made two post LinkedIn one blog article link Shopify store mean grow audience 400 — Finished post Financial Journal publication published went bed 1130 — ended going bed quite late last night woke really late internship meeting 1–2 attend checked stock ate breakfast went shower got ready meeting 100 PM — attended internship meeting talked final project internship majority year helping coursestars tutoring company marketing time final project 300 PM — I’d checked market saw losing 120 news CannTrust considered selling decided would wait one day thing bad tomorrow I’m Cannabis took risk obviously paying 400 PM — added people email list six list varying number biggest 80 email really good progress made hopefully enough launch tomorrow trying go 300 email tomorrow initial launch 700 PM — Worked email launch thought process email need simple also convey message doesn’t make look stupid I’ve known people teacher friend student incredibly important especially want continue checking website buying thing store email yet done tonight 1200 — going Facetime school 8 tomorrow morning posted article decided go sleep Photo Chris Lawton Unsplash 4220 — Postponing 800 — woke math class looked news morning coronavirus case reaching 1000000 case worldwide 66 million people filed unemployment benefit world United States good shape 1200 PM — couple class work started adding email email list 130 PM — ended adding 150 email within time frame really excited send email within hour led problem remembered email done point two option could either rush finish hope good impact intended audience wait Monday better email send I’d waiting week send email today psyched hopefully least 50 people would check dropshipping website maybe even buy thing thought bit realized make good impression customer chance would come back Hence decided would finish email weekend know saying “quality quantity” 400 PM — checked market made 50 Cannabis today Compared loss 300 lot least start cannabis investing life see another day 700 PM — investigating Covid19 One kid old school made post people need help business ever thought thing could help also actually start first small business something thought never really got around thinking hard enough time Sadly come idea today seems everything already taken I’m going need lot thinking especially want help people Covid19 1200 — didn’t really much business finance realize know weekend going grind want make 6–7 different email target different group people email list Right I’m probably going watch movie call night Lesson think really big lesson learned don’t try hurry something get deadline meet course you’re something personal project quality important 4320 — Epiphany 1000 — woke looked market Cannabis started day looked like good sign began scrolling Medium looked one article success thing successful people usually wake early thought like I’m waking 10 every day mean I’m going successful thought couldn’t true research turn successful people wake early here’s take people don’t want billion think honestly going billion chance able use billion dollar quite slim think 1 followed NINE zero Let put perspective common house item think people TV average cost one 500 mean buy 2 million TV’s 1 billion Personally don’t know would 20 TV’s let alone 2 million rich rich might wake early lot millionaire example people made million Bitcoin didn’t seem like people work ethic rich rich still quite well might bit difficult follow think waking early doesn’t define success Thank listening Ted Talk 1200 PM — added 70 email list I’m really excited launch Monday question reach aryangandhiramenfreefinancecom 200 PM — Added another 60 email really good idea add email even though take long time it’s really good way reach people make you’re saying heard 800 PM — Finished email picture linked kept sending test email could find sent three still wondering wasn’t sending checked spam mailbox first thought would easy fix realized would need lot digging seeing three something called CANSPAM Act rule going take longer thought Lesson day Always expect thing throw course know sound like another thing everyone know I’ll give See sometimes thing take course need think potentially refocus maybe shall clarity need 4420 — ReThinking 100 PM — woke want know wake late check last article httpsmediumcomaryandgandhi4320epiphany8612db76b8e Anyway stock market wasn’t open chilled morning went shower shower thought business opportunity pandemic year ago started blog day ago store time like world need another blog another store hence brainstorming sad report today fruitful thinking anything going continue also encourage think kind business could start help world Covid19 outbreak 400 PM — wrote blog post tomorrow BS Kellogg analyzes company Kellogg talk interesting fact end day tomorrow 600 PM — Added email list anticipation release Monday want added list fill form comment email thenbegan creating email finished ran small problem importing people email work something going figure Another thing email sent straight spam something need work 1000 PM — Tried figuring spam uploading people work going spend next day figuring Lesson Take opportunity around make best global pandemic horrible everyone always thing help opportunity act Always keep mind Photo bruce mar Unsplash 4520 — Ready Set Go 1200 PM — woke went Medium checked live Covid19 case count usually check 4–5 time day see happening around world term pandemic would recommend everyone well keep aware happening allow act accordingly 100 PM — really wanted figure problem talked last article worked Mailchimp sent email friend go spam good sign sent email 4–5 time 2 time went spam mailbox also changed font part email turn picture sometimes blocked sending email edited content make sure none picture referenced 300 PM — Finished email uploaded contact anticipation sending email tomorrow let everyone know statistic arise send email tomorrow 500 PM — Published article BS Kellogg look company Kellogg pandemic talk stock price future company 900 PM — Thought business start pandemic thought two idea One type toilet paper business seemed unsustainable People hyped brief time hype process dying around idea something cure Covid19 would lucrative close enough experience anything related biology disease 1100 PM — added email preparation tomorrow got ready school 800 class Lesson lesson today persistence Mailchimp email going send really annoyed really close deleting decided put lot work Turns one hour spent figured everything ready test Sometimes close giving look problem different angle chance work 4620 — Calls 800 — woke sign math class went sleep 1030 — woke Advanced Programming class started 11 showered 1230 PM — started college counseling meeting 230 PM — finished college counseling meeting sent email 120 people 500 PM — day ago someone reached Linkedin asked set time talk opportunity called five talked started giving homework assignment book read moment part feel like really legit opportunity time don’t want lose going continue work person see lead 530 PM — turn got 111 open quite impressive 90 people sent email opened quite impressive hand seven people clicked link email high hoped shall learn term create better directed email campaign 700 PM — Similarly another husband wife pair reached something quite similar talked background went talking bit personal life end call wife sent document email read would explain different aspect business world seems interesting still bit skeptical going lead 900 PM — Added email another school email list excited emailing idea seems like good way market Lesson Never close door term opportunity Almost 60 feel like two call fake ulterior motive Don’t get wrong nice people gut feeling time 40 chance wrong could amazing opportunity long putting danger always try keep door open 4720 — Day Mindset 1000 — woke wrote blog post tomorrow called Mindset want read check back profile tomorrow quick summary recently reached via LinkedIn asked read Business 21st century book Robert Kiyosaki book recently interesting want talk one thing really stood called Cashflow Quadrant Cashflow Quadrant split four part E B represents different type job people hold job work title put one four part quadrant wrote found really informative wanted share thought nowhere close expert also wanted know people’s thought Cashflow Quadrant experience 100 PM — added another school email list 330 PM — sent another mass email 103 recipient 25 friend rest faculty high school report number soon stock market started 900 point end day ended 26 point market volatile right what’s happening Covid19 show sign slowing investing risky opinion 530 PM — think going make book one point think offer insight mistake growing business want sure going begin combining thought time 900 PM — Thought job could get summer intern Caterpillar last year don’t know fare year One option work HyVee I’m sure parent let apply due Covid19 Lesson Work smart hard read little bit book watched youtube summary book would taken 7 hour finished hour got general meaning Don’t afraid take shortcut time reason exist aren’t bad 4820 — Second Meeting 1000 — woke told self would put business project hold finished studying math test one class worry put work studying next hour 200 PM — added Dunlap Grade school email list sent another email 100 teacher two elementary school going start sending email every three day opposed every day add one school day email list 400 PM — publish post called Mindset Check talk learned Robert Kiyosaki’s Business 21st Century 500 PM — school meeting hung family 930 PM — second meeting “mentor” quite interesting First planned going 930 PM — 10 PM went 1045 PM wanted hear opportunity multilevel marketing opportunity would start business team supporting would make profit company called Amway company seems legit still doubt First I’m high school student man spending 2–3 hour week working Wouldn’t easier work adult opposed course team keep saying going meet said week two would get meet team going make judgment yet opportunity legit excited 4920 — Haircutter 800 — wake first class class morning 1200 PM — took shower thing decided cut hair spur moment decision dad one hair clipper took shaved everywhere top obvious reason bored wanted change got thinking started cutting hair month ago would always go one Asian male Great Clips would always productive conversation art teacher also interested side hustle know one thing illustrate image Chemistry textbook netted around 2–3 grand cutting hair today realized really influence married man kid still found time cut hair art teacher illustrate chemistry textbook That’s know age especially side hustle want accomplish possible 300 PM — Added another email list going send email tomorrow marketing blog around one hundred people Take look article know last email session went 600 PM — supposed meeting another MLM person thanks advice Prickly Pam Kim McKinney able avoid could huge waste time Thank 900 PM — looked portfolio quite concentrated Cannabis decided sometime next week would loss 400 put Boeing United Airlines see strong rebound airline stock waiting see Covid19 become worse invest based Photo Eugene Chystiakov Unsplash 41020 — Pyramid Selling 1200 PM — woke fixed hair showered 200 PM — research network marketing article talked personal experience found Multilevel marketing called pyramid selling marketing strategy sell product receive commission every person whose product sell recruit sounded much like pyramid scheme turn difference pyramid scheme emphasis placed recruitment others make money people top MultiLevel Marketing emphasis placed selling recruitment happens along way Looking seem similar believe made right decision staying away scheme 500 PM — added another school email list planned sending email cutting hair showering decided would Monday 700 PM — AP test coming also wanting pick juggling decided would take weekend slow still publish next two day won’t much report realized time hand want pick new stuff Dancing also list suck want get much better Let know guy want improve Lesson advice lesson pick something don’t care magic investing cup stacking pick something learn guarantee make feel good also keep brain edge keep learning 41120 — Mass Emailing 1200 PM — woke 400 PM — said going take easy weekend decided add email list adding thought easier way mean thinking could write pretty basic program scan website get email I’m nowhere close good programmer thought looking string symbol page printing would take lot time initially end week two much easier extract email 700 PM — Wrote article tomorrow BS Las Vegas Sands article focus three main topic brief description company stock price interesting fact interested posted 300 PM CST Lesson Take break morning fixed lawnmower outdoor work felt really nice Don’t always grind you’re going fail soon 41220 — Las Vegas Sands 1000 — Woke lied bed 300 PM — Published BS Las Vegas Sands interesting company learn 500 PM — Worked bit email program manually added 70 email list Lesson today recommendation something watching Netflix called Dirty Money show corruption lying money 41320 — Easter Monday 1100 — woke going send mass email since school closed decided wait tomorrow screenshot email 100 PM — today Easter Monday decided article would put together list interesting fact BS section analyzes company give investing recommendation compiled list fact multiple company article Aurora Cannabis largest Cannabis acquisition history occurred mid2018 Aurora Cannabis purchased CanniMed 11 Billion market valuation 17 Billion company founded 2006 Terry Booth Steve Dobler Dale Lesack Chris Mayerson Booth Steve Dobler invested 5 million capital AMD far AMD 5 CEO’s three electrical engineer longest Jerry Sanders founder 1969–2002 market capitalization AMD 543 Billion 200 million gaming console AMD power chance one gaming console AMD powered British Petroleum 1967 BP spilled 32 million gallon crude oil Atlantic gaining title Britain’s largest oil spill BP market capitalization 1316 billion revenue around 307 million 75000 employee BP revenue 41 million per employee Cheesecake Factory 2010 rated worst family restaurant America Men’s Health magazine served high caloric highfat food Cheesecake Factory market capitalization 175B company donates 500000 pound food year Harvest Food Donation program work Feeding America Salvation Army provide annual Thanksgiving Day Feast need Delta Airlines actually applied bankruptcy September 14th 2005 rising cost fuel April 2007 managed last two year reenlisted New York stock exchange market capitalization 3898 Billion December 5th 2019 Delta leading airline term revenue serving 200 million people taking customer 300 location 50 country Eventbrite Eventbrite host event 170 country mean it’s 871 country world market capitalization Eventbrite 19B Eventbrite founded 3 people two married Julia Hartz Kevin Hartz Fitbit 10000 step fitbit goal isn’t random goal met person least 30 minute physical activity day add CDC’s recommended 150 minute per week market capitalization Fitbit 174B founder Fitbit inspired ability motion sensor Nintendo Wii track movement people played game Dance General Electric Two employee GE Irving Langmuir Ivar Giaever Nobel Prize 1932 1973 respectively market capitalization GE 10699B 2011 GE ranked 14th profitable company world Fortune 500 GrubHub 2006 Maloney Evans first place University Chicago Booth School Business’s Edward L market capitalization GrubHub 422 Billion GrubHub 3200 city growing Hexo 1100 employee Hexo fourth largest compared Cannabis company Hexo market capitalization 310392 million Hexo hope bring earnings positive Cannabis 20 becomes widesprea Harley Davidson recently began construction new plant Thailand 2018 fourth international plant market capitalization 323 billion two decade 1960s 1980s Harley Davidson actually produced three fourwheel golf car Intel Intel museum located headquarters Santa Clara California 85000 visitor per year market capitalization 196015 billion Intel philanthropic branch called Intel foundation donated 80 million California school nonprofit JCPenney founder JCPenney actually started butcher business founded JCPenney JCPenney market capitalization 12336 Million founder Walmart Sam Walton worked JCPenney Kellogg Almost cereal box made recycled paperboard similar cardboard except one layer market valuation 2178 Billion mascot Kellogg Tony Tiger actually created 1951 Photo Daniel von Appen Unsplash stay tuned Check blog httpramenfreefinancecom Get free ebook httpsdocsgooglecomformsde1FAIpQLSdoY3hEG5vG4lryfMN9LRFJjsRadxdIOD9aD1e4e4wg2gviewformuspsflinkTags Business Entrepreneurship Startup Life Finance |
995 | Batch normalization in Neural Networks | This article explains batch normalization in a simple way. I wrote this article after what I learned from Fast.ai and deeplearning.ai. I will start with why we need it, how it works, then how to include it in pre-trained networks such as VGG.
Why do we use batch normalization?
We normalize the input layer by adjusting and scaling the activations. For example, when we have features from 0 to 1 and some from 1 to 1000, we should normalize them to speed up learning. If the input layer is benefiting from it, why not do the same thing also for the values in the hidden layers, that are changing all the time, and get 10 times or more improvement in the training speed.
Batch normalization reduces the amount by what the hidden unit values shift around (covariance shift). To explain covariance shift, let’s have a deep network on cat detection. We train our data on only black cats’ images. So, if we now try to apply this network to data with colored cats, it is obvious; we’re not going to do well. The training set and the prediction set are both cats’ images but they differ a little bit. In other words, if an algorithm learned some X to Y mapping, and if the distribution of X changes, then we might need to retrain the learning algorithm by trying to align the distribution of X with the distribution of Y. ( Deeplearning.ai: Why Does Batch Norm Work? (C2W3L06))
Also, batch normalization allows each layer of a network to learn by itself a little bit more independently of other layers.
Deeplearning.ai: Why Does Batch Norm Work? (C2W3L06)
We can use higher learning rates because batch normalization makes sure that there’s no activation that’s gone really high or really low. And by that, things that previously couldn’t get to train, it will start to train.
It reduces overfitting because it has a slight regularization effects. Similar to dropout, it adds some noise to each hidden layer’s activations. Therefore, if we use batch normalization, we will use less dropout, which is a good thing because we are not going to lose a lot of information. However, we should not depend only on batch normalization for regularization; we should better use it together with dropout.
How does batch normalization work?
To increase the stability of a neural network, batch normalization normalizes the output of a previous activation layer by subtracting the batch mean and dividing by the batch standard deviation.
However, after this shift/scale of activation outputs by some randomly initialized parameters, the weights in the next layer are no longer optimal. SGD ( Stochastic gradient descent) undoes this normalization if it’s a way for it to minimize the loss function.
Consequently, batch normalization adds two trainable parameters to each layer, so the normalized output is multiplied by a “standard deviation” parameter (gamma) and add a “mean” parameter (beta). In other words, batch normalization lets SGD do the denormalization by changing only these two weights for each activation, instead of losing the stability of the network by changing all the weights.
Batch normalization and pre-trained networks like VGG:
VGG doesn’t have a batch norm layer in it because batch normalization didn’t exist before VGG. If we train it with it from the start, the pre-trained weight will benefit from the normalization of the activations. So adding a batch norm layer actually improves ImageNet, which is cool. You can add it to dense layers, and also to convolutional layers.
If we insert a batch norm in a pre-trained network, it will change the pre-trained weights, because it will subtract the mean and divide by the standard deviation for the activation layers and we don’t want that to happen because we need those pre-trained weights to stay the same. So, what we need to do is to insert a batch norm layer and figure out gamma and beta in order to undo the outputs change.
To summarize everything, you can think about batch normalization as doing preprocessing at every layer of the network.
References: | https://towardsdatascience.com/batch-normalization-in-neural-networks-1ac91516821c | ['F D'] | 2017-10-25 09:56:08.190000+00:00 | ['Machine Learning', 'Deep Learning', 'Artificial Intelligence', 'Data Science', 'Engineering'] | Title Batch normalization Neural NetworksContent article explains batch normalization simple way wrote article learned Fastai deeplearningai start need work include pretrained network VGG use batch normalization normalize input layer adjusting scaling activation example feature 0 1 1 1000 normalize speed learning input layer benefiting thing also value hidden layer changing time get 10 time improvement training speed Batch normalization reduces amount hidden unit value shift around covariance shift explain covariance shift let’s deep network cat detection train data black cats’ image try apply network data colored cat obvious we’re going well training set prediction set cats’ image differ little bit word algorithm learned X mapping distribution X change might need retrain learning algorithm trying align distribution X distribution Deeplearningai Batch Norm Work C2W3L06 Also batch normalization allows layer network learn little bit independently layer Deeplearningai Batch Norm Work C2W3L06 use higher learning rate batch normalization make sure there’s activation that’s gone really high really low thing previously couldn’t get train start train reduces overfitting slight regularization effect Similar dropout add noise hidden layer’s activation Therefore use batch normalization use le dropout good thing going lose lot information However depend batch normalization regularization better use together dropout batch normalization work increase stability neural network batch normalization normalizes output previous activation layer subtracting batch mean dividing batch standard deviation However shiftscale activation output randomly initialized parameter weight next layer longer optimal SGD Stochastic gradient descent undoes normalization it’s way minimize loss function Consequently batch normalization add two trainable parameter layer normalized output multiplied “standard deviation” parameter gamma add “mean” parameter beta word batch normalization let SGD denormalization changing two weight activation instead losing stability network changing weight Batch normalization pretrained network like VGG VGG doesn’t batch norm layer batch normalization didn’t exist VGG train start pretrained weight benefit normalization activation adding batch norm layer actually improves ImageNet cool add dense layer also convolutional layer insert batch norm pretrained network change pretrained weight subtract mean divide standard deviation activation layer don’t want happen need pretrained weight stay need insert batch norm layer figure gamma beta order undo output change summarize everything think batch normalization preprocessing every layer network ReferencesTags Machine Learning Deep Learning Artificial Intelligence Data Science Engineering |
996 | The Complete Guide on How to Code Review | The Complete Guide on How to Code Review
Best practices from Apple, Google, Microsoft, Amazon, and Facebook
Photo by Nicole Wolf on Unsplash
What’s the end goal of the code review?
To make sure that changes work? To validate if code is following the style guide? To check if new changes won’t break anything? All of these? None of these?
All of these questions are necessary parts of the code review, but none of them are its ultimate goal.
The primary purpose of the code review is to make sure the solution is solving the problem in the best possible way — from both the code and product perspective.
All code-review practices are designed to meet this end goal.
But how do you determine if the solution you’re reviewing is the best way to solve the problem? In other words, how do you code review?
Let’s deep dive into it. | https://medium.com/better-programming/the-complete-guide-on-how-to-code-review-df3d01404f6b | ['Nick Bull'] | 2020-10-23 17:05:51.468000+00:00 | ['Software Engineering', 'Programming', 'Software Development', 'Code Review', 'Startup'] | Title Complete Guide Code ReviewContent Complete Guide Code Review Best practice Apple Google Microsoft Amazon Facebook Photo Nicole Wolf Unsplash What’s end goal code review make sure change work validate code following style guide check new change won’t break anything None question necessary part code review none ultimate goal primary purpose code review make sure solution solving problem best possible way — code product perspective codereview practice designed meet end goal determine solution you’re reviewing best way solve problem word code review Let’s deep dive itTags Software Engineering Programming Software Development Code Review Startup |
997 | 4 Simple Emails You Should Send Every Week | I used to despise email. That changed, however, when my wife asked me an interesting question: “How did you feel about it when you first started using it?”
In a flash, I was transported back to my freshman year of college. My buddies and I would huddle around one of the few computers in the library taking turns sending messages to our high school girlfriends who went to other schools. We thought it was rad. And don’t get me started on how giddy I used to feel when the old PC warmed up and meowed “You’ve got mail.”
But much like our girlfriends at the time, the love affair with email came to an end. As the years passed, it became a thorn instead of a rose.
A few years ago, however, when my wife asked me about my first impression she got me thinking about all the good things it has brought into my life.
Yes. Email can be a pain.
Yes. Your inbox can be interpreted as “other people’s to-do list.”
Yes. Marketers talk more than they listen.
But it can also be a glorious tool to tighten your relationships and mobilize your career. In fact, since my family and I traded in city life in Barcelona for the Catalan countryside, email has turned into my weapon of choice and it has played a vital role in helping me become a full-time writer and career coach.
So let your hatred for email simmer for a minute and see if the 5 types of emails resonate with you. Each of them will only take you a few minutes to write but the effects of them may end up seriously improving your quality of life. | https://medium.com/curious/4-simple-emails-you-should-send-every-week-bc3e085ed496 | ['Michael Thompson'] | 2020-10-15 05:43:49.295000+00:00 | ['Creativity', 'Relationships', 'Self Improvement', 'Productivity', 'Inspiration'] | Title 4 Simple Emails Send Every WeekContent used despise email changed however wife asked interesting question “How feel first started using it” flash transported back freshman year college buddy would huddle around one computer library taking turn sending message high school girlfriend went school thought rad don’t get started giddy used feel old PC warmed meowed “You’ve got mail” much like girlfriend time love affair email came end year passed became thorn instead rose year ago however wife asked first impression got thinking good thing brought life Yes Email pain Yes inbox interpreted “other people’s todo list” Yes Marketers talk listen also glorious tool tighten relationship mobilize career fact since family traded city life Barcelona Catalan countryside email turned weapon choice played vital role helping become fulltime writer career coach let hatred email simmer minute see 5 type email resonate take minute write effect may end seriously improving quality lifeTags Creativity Relationships Self Improvement Productivity Inspiration |
998 | Return Of The Caveman. How Technology is Regressing Us | Return Of The Caveman. How Technology is Regressing Us
Have you picked your tribe yet? The time is rapidly approaching where you will need one. It’s not safe to be alone out there
We started out on our long evolutionary journey from dimly lit caves occupied by small groups. Groups formed out of necessity. Even at our most primitive level, we grasped the concept of safety in numbers.
It wasn’t purely a safety issue. Larger groups produced better results when foraging or hunting. Better to share the spoils than have no spoils at Better to share and socialize than to dine alone. Many hands, light work. The list goes on but I am sure the point is conceded.
As we developed societally and our numbers increased, so to did the size and complexity of our groups. The strongest was chosen to lead these hierarchies and a gradual unwritten codex of group behavior that was beneficial to the group and its members emerged. Let’s call it the Caveman Codex for harmonious coexistence.
The fact that culturally and geographically divided groups managed to produce almost identical codices points to the validly of these basic principals which would over time form the basis for our first religions.
Religion is not, in my opinion, a spiritual gift to man, but rather man’s attempt to enforce the Caveman Codex, ensuring its unquestioned adherence, thereby ensuring the survival and advancement of the group. History tells us that when we choose to ignore the values enshrined in the Codex, the wheels come off.
Our groups have become legion
Time passed and we evolved in sporadic jumps, from one age to the next, sometimes enjoying enlightened periods and then regressing. Our last and current jump has been spectacular and as far as we know, unparalleled. We are now masters of almost everything we survey, able to bend and mold our environment to better suit humanity.
Our groups are now legion, the occupants numbering sometimes billions and are as varied as they are numerous. We group ourselves by ethnicity, geographically, linguistically, sexually, politically, and even globally.
It is an easy thing for someone to lose themselves in this vast sea of humanity and in response, over the last two centuries, we have a gradual shift to focusing on the individual. On their rights, dreams, and desires, often at the cost of the group. We have not as yet been able to fully quantify that cost, partly due to insufficient data and a lack of historical comparison.
What history does tell us is that the group is essential to our survival and our ability to move forward. Destabilize the group and you destabilize the individual. Lose sight of the Codex and you lose sight of the horizon.
So how does this all tie in with technology? I will attempt to explain this as best I can. I do not have the benefit of datasets, psychologists or social anthropologists to call on, but I do have the power of observation and interpretation. You are free to disagree with my interpretation of the facts, That is the beauty of open discourse.
In 1990, Tim Berners-Lee opened the floodgates
Modern man is raised on a narrative of striving to be the best we can as individuals. A balanced approach to this would be to consider both the interests of the individual and the collective, as they are interdependent. The bias in the late twentieth century has lent heavily towards the individual. Their rights have become paramount in modern culture, trumping all else, irrespective of the cost.
Our groups were still able to partially adapt to address this imbalance as it was limited to a small cross-section of the populace. Then in 1990, Tim Berners-Lee opened the floodgates with the creation of the World Wide Web and the internet as we know it today was unleashed.
In the space of thirty years, our global connectivity and ability to communicate across all spectrums exploded and has changed our world forever. The new digital messiahs were born, spreading their messages of the importance of individualism or self. Almost overnight the world decided that self was the path to fulfillment and that for various reasons the Codex had been misleading them.
They are in some ways correct, as the original Codex has been hijacked and distorted by power bases promoting specific group agendas. These agendas are for the benefit of the few and are propagated at the expense of the group. This is true of almost all modern codices, including religions, political and social codices. Far better then to pursue your own agenda, than to follow a corrupt hierarchy.
The problem with this approach is two-fold. The first is obvious. We need the group to survive. Going it alone is not an option. The second is less glaring, but more important. By abandoning what we correctly identify to be a corrupt hierarchy, we forfeit the ability to effect any change within that group or structure.
It’s analogous to abandoning a ship that’s leaking rather than attempting to repair the leak. If everyone jumps overboard, not only will the ship undoubtedly sink, it’s passengers, now drifting alone in the sea, are also doomed.
Our world is desperately in need of ship fixers, individuals who believe in the principals espoused by the original Codex. People whose individuality and purpose stem from their unshakeable belief in the group. People whose core values and self-belief are not determined by outside factors.
The divisiveness of the online world becomes more apparent by the day. It has spawned new tribalism amongst populations globally, in a digital re-enactment that is troublingly reminiscent of our Stone Age ancestor’s development.
We are aware of the polarizing effect of the internet. We are aware historically of the dangers of tribalism, the feuding and open warfare that arises as a result. Yet we stand by, day by day, watching this catastrophic disassembly of our hierarchies and offer the following excuse. The internet is not reflective of the real world and poses no danger.
We continue to espouse our own individual views whilst vilifying the only structure and Codex that has proved over and over how critical it is to our combined survival as a species. We are lighting our torches and heading off again in search of caves, spurred on by technology.
We need to turn those torches on our groups, expose them internally to the light, cleanse them and restore the Codex to its rightful place at the pinnacle of the hierarchy. Man has proved unable to occupy this position without yielding to the siren call of its power. Perhaps our only salvation lies in re-embracing the Caveman Codex, the greatest gift our ancestors bequeathed us.
The time may already have passed for addressing these issues. Many are now resigned to simply observing humanity become ever more ensnared in the perfect trap of technology. It is a cunning digital web of our own design. One whose very existence we now choose to ignore because it is convenient.
The digital world may not be the real world, but it’s evolution and our eventual submission will not be possible without our complicity. Left unchecked it will divide us and then consume us, individually. Only together can we rediscover our humanity, put aside our differences and embrace our rightful destiny.
There is a place in this future for technology, but it cannot come at the price of our humanity. We need to be the ones firmly in control. At the moment we’re losing this fight. | https://medium.com/lighterside/return-of-the-caveman-how-technology-is-regressing-us-bd23f879c628 | ['Robert Turner'] | 2019-12-16 10:46:13.875000+00:00 | ['Society', 'Culture', 'Technology', 'Lighterside', 'Psychology'] | Title Return Caveman Technology Regressing UsContent Return Caveman Technology Regressing Us picked tribe yet time rapidly approaching need one It’s safe alone started long evolutionary journey dimly lit cave occupied small group Groups formed necessity Even primitive level grasped concept safety number wasn’t purely safety issue Larger group produced better result foraging hunting Better share spoil spoil Better share socialize dine alone Many hand light work list go sure point conceded developed societally number increased size complexity group strongest chosen lead hierarchy gradual unwritten codex group behavior beneficial group member emerged Let’s call Caveman Codex harmonious coexistence fact culturally geographically divided group managed produce almost identical codex point validly basic principal would time form basis first religion Religion opinion spiritual gift man rather man’s attempt enforce Caveman Codex ensuring unquestioned adherence thereby ensuring survival advancement group History tell u choose ignore value enshrined Codex wheel come group become legion Time passed evolved sporadic jump one age next sometimes enjoying enlightened period regressing last current jump spectacular far know unparalleled master almost everything survey able bend mold environment better suit humanity group legion occupant numbering sometimes billion varied numerous group ethnicity geographically linguistically sexually politically even globally easy thing someone lose vast sea humanity response last two century gradual shift focusing individual right dream desire often cost group yet able fully quantify cost partly due insufficient data lack historical comparison history tell u group essential survival ability move forward Destabilize group destabilize individual Lose sight Codex lose sight horizon tie technology attempt explain best benefit datasets psychologist social anthropologist call power observation interpretation free disagree interpretation fact beauty open discourse 1990 Tim BernersLee opened floodgate Modern man raised narrative striving best individual balanced approach would consider interest individual collective interdependent bias late twentieth century lent heavily towards individual right become paramount modern culture trumping else irrespective cost group still able partially adapt address imbalance limited small crosssection populace 1990 Tim BernersLee opened floodgate creation World Wide Web internet know today unleashed space thirty year global connectivity ability communicate across spectrum exploded changed world forever new digital messiah born spreading message importance individualism self Almost overnight world decided self path fulfillment various reason Codex misleading way correct original Codex hijacked distorted power base promoting specific group agenda agenda benefit propagated expense group true almost modern codex including religion political social codex Far better pursue agenda follow corrupt hierarchy problem approach twofold first obvious need group survive Going alone option second le glaring important abandoning correctly identify corrupt hierarchy forfeit ability effect change within group structure It’s analogous abandoning ship that’s leaking rather attempting repair leak everyone jump overboard ship undoubtedly sink it’s passenger drifting alone sea also doomed world desperately need ship fixer individual believe principal espoused original Codex People whose individuality purpose stem unshakeable belief group People whose core value selfbelief determined outside factor divisiveness online world becomes apparent day spawned new tribalism amongst population globally digital reenactment troublingly reminiscent Stone Age ancestor’s development aware polarizing effect internet aware historically danger tribalism feuding open warfare arises result Yet stand day day watching catastrophic disassembly hierarchy offer following excuse internet reflective real world pose danger continue espouse individual view whilst vilifying structure Codex proved critical combined survival specie lighting torch heading search cave spurred technology need turn torch group expose internally light cleanse restore Codex rightful place pinnacle hierarchy Man proved unable occupy position without yielding siren call power Perhaps salvation lie reembracing Caveman Codex greatest gift ancestor bequeathed u time may already passed addressing issue Many resigned simply observing humanity become ever ensnared perfect trap technology cunning digital web design One whose existence choose ignore convenient digital world may real world it’s evolution eventual submission possible without complicity Left unchecked divide u consume u individually together rediscover humanity put aside difference embrace rightful destiny place future technology cannot come price humanity need one firmly control moment we’re losing fightTags Society Culture Technology Lighterside Psychology |
999 | A Journey From React to Vue.js | A Journey From React to Vue.js
What it was like to switch to Vue after four years with React
I have been working with React for the last four years. Now I’ve just started working with Vue. What you can do in React can also be done in Vue. There are some important conceptual differences, though, some of which reflect Angular’s influence on Vue. Honestly, I am getting the feeling that Vue is the combination of the best parts of Angular and React.
One of the key factors for the comparison was that Evan You, creator of the Vue framework, used React as a source of inspiration for new framework development.
“I figured, what if I could just extract the part that I really liked about React and build something really lightweight without all the extra concepts involved? I was also curious as to how its internal implementation worked. I started this experiment just trying to replicate this minimal feature set, like declarative data binding. That was basically how Vue started. ”— Evan You
My focus in this article will be to highlight the differences between the two.
To begin with, let’s look at some facts: | https://medium.com/better-programming/a-journey-from-react-to-vue-js-cec3ba44c377 | ['Muhammad Anser'] | 2020-12-15 15:17:58.469000+00:00 | ['JavaScript', 'React', 'Reactive Programming', 'Vuejs', 'Programming'] | Title Journey React VuejsContent Journey React Vuejs like switch Vue four year React working React last four year I’ve started working Vue React also done Vue important conceptual difference though reflect Angular’s influence Vue Honestly getting feeling Vue combination best part Angular React One key factor comparison Evan creator Vue framework used React source inspiration new framework development “I figured could extract part really liked React build something really lightweight without extra concept involved also curious internal implementation worked started experiment trying replicate minimal feature set like declarative data binding basically Vue started ”— Evan focus article highlight difference two begin let’s look factsTags JavaScript React Reactive Programming Vuejs Programming |
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