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"Deloitte looks to bring AI to the frontline with a little help from Nvidia | VentureBeat"
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"https://venturebeat.com/ai/deloitte-looks-to-bring-ai-to-the-frontline-with-a-little-help-from-nvidia"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Deloitte looks to bring AI to the frontline with a little help from Nvidia Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Deloitte is growing its set of artificial intelligence (AI) capabilities with the launch this week of a pair of new services for its quartz AI offering.
The quartz AI services include compass AI for logistics and frontline AI for customer care deployments. The new quartz AI services are built with technologies from Nvidia, which Deloitte has partnered closely with in recent years to help advance its own AI initiatives. Deloitte is making use of Nvidia omniverse as well as technologies from the Nvidia enterprise AI stack as a foundation to help build out Quartz AI.
The new quartz AI services follow an announcement from Deloitte earlier this month that the consulting firm was building a new generative AI and foundation model practice to help organizations benefit from the capabilities of large language models (LLMs).
Deloitte isn’t the only consulting firm investing in AI. PwC has announced plans to invest $1 billion over the next three years in generative AI. In February, Bain and Company also announced a partnership with OpenAI.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! “Deloitte’s overall strategy with AI is to take AI from a kind of a workshop from the back office to actually enhance front office processes to unlock operational value,” Goutham Belliappa, Deloitte managing director, told VentureBeat.
Bringing AI to the frontline of business processes Belliappa commented that Nvidia provides the general purpose compute surface for AI and also provides software development kits (SDK) that can be used for specific purposes.
“The quartz AI solutions involve specific packages from Deloitte that embed Nvidia SDKs that solve very specific business problems such as route optimization or supply chain optimization or frontline enhancements,” said Belliappa.
The goal with frontline AI is to introduce technology that will improve frontline customer care processes. Belliappa said that clients come to Deloitte knowing that they have a specific issue — or in some cases it’s an issue that Deloitte is able to identify. For example, if there is a high call transfer rate in the customer support center, which can lead to low customer satisfaction.
With supply chain optimization, there are myriad of variables that can complicate and delay the flow of goods. That’s where the compass AI solutions will help. Compass provides fleet routing and dispatch optimization, which is all about getting products to customers faster.
Deloitte outlines the challenges and opportunities of AI While AI in recent months has been the subject of much hype, enterprises still often need a fair bit of education.
Belliappa noted that most of Deloitte’s clients have an idea of what AI is all about. However, his firm has to educate by explaining the application of AI, where it can be real and where the maturity is not yet right.
“We have customers that think of AI as kind of science fiction, saying, you know, ‘I’ll be able to handle my customer service with zero touch without humans,'” said Belliappa. “That’s aspirational; one day, we’ll get there but we’re not there yet.” He added that there is still a need, particularly with things like the supply chain, for organizations to deal with physical machines and processes that humans need to touch. Part of what Deloitte continues to do is help sort out the fact from fiction as it applies to an organization’s specific industry, solution and challenges.
Among the challenges that many organizations continue to face with the adoption of AI is both the quality and availability of data. The second biggest challenge according to Belliappa is that of organizational alignment to actually benefit from AI. In many situations for AI to be effective, Belliappa said that different parts of the organization come together and they may not always be aligned.
“What we’re hoping for is our customers will transform and embrace game-changing AI technologies so that they’ll be able to get the benefits that improve the customer experience while also lowering the cost,” he said.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Databricks and Hugging Face integrate Apache Spark for faster AI model building | VentureBeat"
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"https://venturebeat.com/ai/databricks-and-hugging-face-integrate-apache-spark-for-faster-ai-model-building"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Databricks and Hugging Face integrate Apache Spark for faster AI model building Share on Facebook Share on X Share on LinkedIn Photo by Kevin Ku on Pexels.com Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Databricks and Hugging Face have collaborated to introduce a new feature that allows users to create a Hugging Face dataset from an Apache Spark data frame. This new integration provides a more straightforward method of loading and transforming data for artificial intelligence (AI) model training and fine-tuning. Users can now map their Spark data frame into a Hugging Face dataset for integration into training pipelines.
With this feature, Databricks and Hugging Face aim to simplify the process of creating high-quality datasets for AI models. In addition, this integration offers a much-needed tool for data scientists and AI developers who require efficient data management tools to train and fine-tune their models.
Databricks says that the new integration brings the best of both worlds: cost-saving and speed advantages of Spark with memory-mapping and smart caching optimizations from Hugging Face datasets , adding that organizations would now be able to achieve more efficient data transformations over massive AI datasets.
Unlocking the full Spark potential Databricks employees wrote and committed (revised the source code to the repository) Spark updates to the Hugging Face repository.
Through a simple call to the from_spark function and by providing a Spark data frame, users can now obtain a fully-loaded Hugging Face dataset in their codebase that is ready for model training or tuning. This integration eliminates the need for complex and time-consuming data preparation processes.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Databricks claims that the integration marks a major step forward for AI model development, enabling users to unlock the full potential of Spark for model tuning.
“AI, at the core, is all about data and models,” Jeff Boudier, head of monetization and growth at Hugging Face, told VentureBeat. “Making these two worlds work better together at the open-source layer will accelerate AI adoption to create robust AI workflows accessible to everyone. This integration significantly reduces the friction bringing data from Spark to Hugging Face datasets to train new models and get work done. We’re excited to see our users take advantage of it.” A new way to integrate Spark dataframes for model development Databricks believes that the new feature will be a game-changer for enterprises that need to crunch massive amounts of data quickly and reliably to power their machine learning (ML) workflows.
Traditionally, users had to write data into parquet files — an open-source columnar format, and then reload them using Hugging Face datasets. Spark dataframes were previously not supported by Hugging Face datasets, despite the platform’s extensive range of supported input types.
However, with the new “ from_spark ” function, users can now use Spark to efficiently load and transform their data for training, drastically reducing data processing time and costs.
“While the old method worked, it circumvents a lot of the efficiencies and parallelism inherent to Spark,” said Craig Wiley, senior director of product management at Databricks. “An analogy would be taking a PDF and printing out each page then rescanning them, instead of being able to upload the original PDF. With the latest Hugging Face release, you can get back a Hugging Face dataset loaded directly into your codebase, ready to train or tune your models with.” Dramatically reduced processing time The new integration harnesses Spark’s parallelization capabilities to download and process datasets, skipping extra steps to reformat the data. Databricks claims that the new Spark integration has reduced the processing time for a 16GB dataset by more than 40%, dropping from 22 to 12 minutes.
“Since AI models are inherently dependent on the data used to train them, organizations will discuss the tradeoffs between cost and performance when deciding how much of their data to use and how much fine-tuning or training they can afford,” Wiley explained. “Spark will help bring efficiency at scale for data processing, while Hugging Face provides them with an evolving repository of open-source models, datasets and libraries that they can use as a foundation for training their own AI models.” Contributing to open-source AI development Databricks aims to support the open-source community through the new release, saying that Hugging Face excels in delivering open-source models and datasets. The company also plans to bring streaming support via Spark to enhance the dataset loading.
“Databricks has always been a very strong believer in the open-source community, in no small part because we’ve seen first-hand the incredible collaboration in projects like Spark, Delta Lake, and MLflow,” said Wiley.” We think it will take a village to raise the next generation of AI, and we see Hugging Face as a fantastic supporter of these same ideals.” Recently, Databricks introduced a PyTorch distributor for Spark to facilitate distributed PyTorch training on its platform and added AI functions to its SQL service, allowing users to integrate OpenAI (or their own models in the future) into their queries.
In addition, the latest MLflow release supports the transformers library, OpenAI integration and Langchain support.
“We have quite a lot in the works, both related to generative AI and more broadly in the ML platform space,” added Wiley. “Organizations will need easy access to the tools needed to build their own AI foundation, and we’re working hard to provide the world’s best platform for them.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Cybersecurity meets AI: Augmenting and accelerating humans | VentureBeat"
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"https://venturebeat.com/ai/cybersecurity-meets-ai-augmenting-and-accelerating-humans"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Cybersecurity meets AI: Augmenting and accelerating humans Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
~“ May you live in interesting times ”~ Having the blessing and the curse of working in the field of cybersecurity, I often get asked about my thoughts on how that intersects with another popular topic — artificial intelligence (AI). Given the latest headline-grabbing developments in generative AI tools, such as OpenAI’s ChatGPT , Microsoft’s Sydney, and image generation tools like Dall-E and Midjourney, it is no surprise that AI has catapulted into the public’s awareness.
As is often the case with many new and exciting technologies, the perceived short-term impact of the latest news-making developments is probably overestimated. At least that’s my view of the immediate within the narrow domain of application security. Conversely, the long-term impact of AI for security is huge and is probably underappreciated, even by many of us in the field.
Fantastic accomplishments; tragic failures Stepping back for a moment, machine learning (ML) has a long and deeply storied history. It may have first captured the public’s attention with chess-playing software 50 years ago, advancing over time to IBM Watson winning a Jeopardy championship to today’s chatbots that come close to passing the fabled Turing test.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! What strikes me is how each of these milestones was a fantastic accomplishment at one level and a tragic failure at another. On the one hand, AI researchers were able to build systems that came close to, and often surpassed, the best humans in the world on a specific problem.
On the other hand, those same successes laid bare how much difference remained between an AI and a human. Typically, the AI success stories excelled not by outreasoning a human or being more creative but by doing something more basic orders of magnitude faster or at exponentially larger scale.
Augmenting and accelerating humans So, when I’m asked, “How do you think AI, or ML, will affect cybersecurity going forward?” my answer is that the biggest impact in the short-term will come not from replacing humans, but by augmenting and accelerating humans.
Calculators and computers are one good analogy — neither replaced humans, but instead, they allowed specific tasks — arithmetic, numeric simulations, document searches — to be offloaded and performed more efficiently.
The use of these tools provided a quantum leap in quantitative performance, allowing these tasks to be performed more pervasively. This enabled entirely new ways of working, such as new modes of analysis that spreadsheets like VisiCalc, and later Excel, to the benefit of humans and society at large. A similar story played out with computer chess, where the best chess in the world is now played when humans and computers collaborate , each contributing to the area they are best in.
Immediate impacts on cybersecurity The most immediate impacts of AI on cybersecurity based on the latest “new kid on the block” generative AI chatbots are already being seen. One predictable example, a pattern that often occurs anytime a trendy internet-exposed service becomes available, whether ChatGPT or Taylor Swift tickets, is the plethora of phony ChatGPT websites set up by criminals to fraudulently collect sensitive information from consumers.
Naturally, the corporate world is also quick to embrace the benefits. For example, software engineers are increasing development efficiency by using AI-based code creation accelerators such as Copilot.
Of course, these same tools can also accelerate software development for cyber-attackers, reducing the amount of time required from discovering a vulnerability until code exists that exploits it.
As is almost always the case, society is usually quicker to embrace a new technology than they are to consider the implications. Continuing with the Copilot example, the use of AI code generation tools opens up new threats.
One such threat is data leakage — key intellectual property of a developer’s company may be revealed as the AI “learns” from the code the developer writes and shares it with the other developers it assists. In fact, we already have examples of passwords being leaked via Copilot.
Another threat is unwarranted trust in the generated code that may not have had sufficient experienced human oversight, which runs the risk of vulnerable code being deployed and opening more security holes. In fact, a recent NYU study found that about 40% of a representative set of Copilot-generated code had common vulnerabilities.
More sophisticated chatbots Looking slightly, though not too much, further forward, I expect bad actors will co-opt the latest AI technology to do what AI has done best: Allowing humans, including criminals, to scale exponentially. Specifically, the latest generation of AI chatbots has the ability to impersonate humans at scale and at high quality.
This is a great windfall (from the cybercriminals’ perspective), because in the past, they were forced to choose to either go “broad and shallow” or “narrow and deep” in their selection of targets. That is, they could either target many potential victims, but in a generic and easy-to-discern manner (phishing), or they could do a much better, much harder to detect job of impersonation to target just a few, or even just one, potential victim ( spearphishing ).
With the latest AI chatbots, a lone attacker can more closely and easily impersonate humans — whether in chat or in a personalized email — at a much-increased attack scale. Protection countermeasures will, of course, react to this move and evolve, likely using other forms of AI, such as deep learning classifiers. In fact, we already have AI-powered detectors of faked images.
The ongoing cat-and-mouse game will continue, just with AI-powered tools on both sides.
AI as a cybersecurity force multiplier Looking a bit deeper into the crystal ball, AI will be increasingly used as a force multiplier for security services and the professionals who use them. Again, AI enables quantum leaps in scale — by virtue of accelerating what humans already do routinely but slowly.
I expect AI-powered tools to greatly increase the effectiveness of security solutions, just as calculators hugely sped up accounting. One real-world example that has already put this thinking into practice is in the security domain of DDoS mitigation. In legacy solutions, when an application was subjected to a DDoS attack, the human network engineers first had to reject the vast majority of incoming traffic, both valid and invalid, just to prevent cascading failures downstream.
Then, having bought some time, the humans could engage in a more intensive process of analyzing the traffic patterns to identify particular attributes of the malicious traffic so it could be selectively blocked. This process would take minutes to hours, even with the best and most skilled humans. Today, however, AI is being used to continuously analyze the incoming traffic, automatically generate the signature of invalid traffic, and even automatically apply the signature-based filter if the application’s health is threatened — all in a matter of seconds. This, too, is an example of the core value proposition of AI: Performing routine tasks immensely faster.
AI in cybersecurity: Advancing fraud detection This same pattern of using AI to accelerate humans can, and is, being adopted for other next-generation cybersecurity solutions such as fraud detection. When a real-time response is required, and especially in cases where trust in the AI’s evaluation is high, the AI is being empowered to react immediately.
That said, AI systems still do not out-reason humans or understand nuance or context. In such cases where the likelihood or business impact of false positives is too great, the AI can still be used in an assistive mode — flagging and prioritizing the security events of most interest for the human.
The net result is a collaboration between humans and AIs, each doing what they are best at, improving efficiency and efficacy over what either could do independently, again rhyming with the analogy of computer chess.
I have a great deal of faith in the progression thus far. Peering yet deeper into the crystal ball, I feel the adage “history rarely repeats, but it often rhymes” is apt. The longer-term impact of human-AI collaboration,that is, the results of AI being a force multiplier for humans, is as hard for me to predict as it might have been for the designer of the electronic calculator to predict the spreadsheet.
In general, I imagine it will allow humans to further specify the intent, priorities and guardrails for the security policy, with AI assisting and dynamically mapping that intent onto the next level of detailed actions.
Ken Arora is a distinguished engineer at F5.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Amazon is building a 'more generalized and capable' LLM to power Alexa, says CEO | VentureBeat"
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"https://venturebeat.com/ai/amazon-is-building-a-more-generalized-and-capable-llm-to-power-alexa-says-ceo"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Amazon is building a ‘more generalized and capable’ LLM to power Alexa, says CEO Share on Facebook Share on X Share on LinkedIn Image by Canva Pro Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
In what comes as welcome news to long-suffering Alexa users who can’t do much more than set alarms and check the local weather, Amazon is building a “more generalized and capable” large language model (LLM) to power the device, according to comments yesterday from CEO Andy Jassy in the company’s first-quarter earnings call with investors. And just like Google, Microsoft and Meta did in their earnings calls this week, Amazon placed a strong focus on its overall commitment to AI.
In a response to questions from Brian Nowak, managing director at Morgan Stanley, Jassy went into considerable depth about Amazon’s AI efforts around Alexa, which comes in the context of viral generative AI tools like ChatGPT and Microsoft 365 Copilot stealing Alexa’s thunder as a go-to personal assistant. Critics have said Alexa has stagnated — for example, last month The Information reported that Toyota planned to phase out its Alexa integration and is even considering integrating ChatGPT into its in-house voice assistant.
Generative AI ‘accelerates the possibility’ of improving Alexa In the Amazon earnings call yesterday, Jassy said Amazon continues to have “conviction” about building “the world’s best personal assistant,” but that it is difficult to do across many domains and a broad surface area.
“However, if you think about the advent of large language models and generative AI, it makes the underlying models that much more effective such that I think it really accelerates the possibility of building that world’s best personal assistant,” he said.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Jassy added that the company starts from “a pretty good spot with Alexa, with its couple of hundred million of endpoints being used across entertainment and shopping and smart home and information and a lot of involvement from third-party ecosystem partners.” Amazon has had an LLM underneath it, Jassy explained, “but we’re building one that’s much larger and much more generalized and capable. And I think that’s going to really rapidly accelerate our vision of becoming the world’s best personal assistant. I think there’s a significant business model underneath it.” Amazon CEO also focused heavily on AWS and AI In response to another question from Nowak, Jassy also focused on key offerings from AWS around AI, emphasizing that Amazon has been heavily investing in LLMs for several years, as well as in the chips, particularly GPUs, that are optimized for LLM workloads.
“In AWS, we’ve been working for several years on building customized machine learning chips, and we built a chip that’s specialized for training — machine learning training — which we call Trainium. [It’s] a chip that’s specialized for inference or the predictions that come from the model called Inferentia,” he said, pointing out that the company just released its second versions of Trainium and Inferentia.
“The combination of price and performance that you can get from those chips is pretty differentiated and very significant,” he said. “So we think that a lot of that machine learning training, inference will run on AWS.” And while he said Amazon will be one of the small number of companies investing billions of dollars in building significant, leading LLMs, Jassy also focused on Amazon’s ability to offer options to companies who want to use a foundational model in AWS and then have the ability to customize it for their own proprietary data, needs and customer experience. Companies want to do that in a way where they don’t leak their unique IP to the broader generalized model, he explained.
“That’s what Bedrock is, which we just announced a week ago or so,” he said. Bedrock is a managed foundational model service where people can run foundational models from Amazon, or leading LLM providers like AI21 , Anthropic or Stability AI.
“They can run those models, take the baseline, customize them for their own purposes and then be able to run it with the same security and privacy and all the features they use for the rest of their applications in AWS,” he said. “That’s very compelling for customers.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"AI startup Synthesia made waves this week on both sides of deepfake debate | VentureBeat"
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"https://venturebeat.com/ai/ai-startup-synthesia-made-waves-this-week-on-both-sides-of-deepfake-debate"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages AI startup Synthesia made waves this week on both sides of deepfake debate Share on Facebook Share on X Share on LinkedIn Image by Synthesia Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Two articles this week highlighted the complex debate around the companies creating deepfakes, or synthetic media, in which a person’s voice, image or video is replaced by an AI-generated version. Both involved Synthesia , a London-based startup that says you can create “professional AI videos in 15 minutes” by typing in text in over 120 languages.
Synthesia reportedly in talks to raise over $50 million First of all, yesterday a report from Business Insider said that Synthesia is in talks to raise funds in a deal that could value it at around $1 billion. One source claimed the company could raise between $50 million and $75 million — which is big money in a category that many are pushing back on.
An NPR article yesterday, for example, said that policymakers can’t keep up with AI-generated deepfakes, which also made headlines this week when the Republican National Committee used AI to create a 30- second ad imagining what President Joe Biden’s second term might look like.
Deepfake tools could ‘fool my family and trick my bank’ Meanwhile, in the Wall Street Journal , columnist Joanna Stern wrote about testing Synthesia to see if the AI tool could make her voice and video work more productive and less like drudgery. Her “AI Joanna,” she said, had its good points: “She never loses her voice, she has outstanding posture and not even a convertible driving 120 mph through a tornado could mess up her hair.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Unfortunately, she also found that AI Joanna could “fool my family and trick my bank.” She cloned her voice using a different tool by ElevenLabs. While her cloned voice didn’t ultimately deceive her family, it did get around her Chase credit card’s voice biometric system.
Still, Stern said she would continue using these tools. While the video clone and voice weren’t perfect (“lacking the things that make me me “) they can be helpful to save time “to be a real human.” The authorized, business side of deepfakes And that’s the point of the other side of the deepfake debate, which maintains that the word “deepfake” implies the unauthorized use of synthetic media and generative AI.
But tools like Synthesia, as well as offerings from companies like Hour One , are about the authorized use of this technology for use cases such as business video production.
And that is what investors are interested in: One of Forrester’s top 2023 AI predictions was that 10% of Fortune 500 enterprises will generate content with AI tools. The report mentioned startups such as Hour One and Synthesia which “are using AI to accelerate video content generation.” In an interview with VentureBeat last November, Victor Riparbelli, CEO of Synthesia, said that the business side is a “hugely under-appreciated” part of the deepfake debate.
“It’s very interesting how the lens has been very narrow on all the bad things you could do with this technology,” Riparbelli said. “I think what we’ve seen is just more and more interest in this and more and more use cases.” Riparbelli added that its AI is trained on real actors, and besides users creating videos of themselves, it offers actors’ images and voices as virtual characters clients can choose from to create training, learning, compliance and marketing videos. The actors are paid per video that’s generated with their image and voice.
For enterprise clients, a video created this way becomes a “living video” that they can always go back to and edit, he explained.
And in terms of creating authorized AI versions of users, Riparbelli said this kind of authorization is common in all kinds of licensing agreements that already exist.
“Kim Kardashian has literally licensed her likeness to app developers to build a game that grossed billions of dollars,” said Riparbelli. “Every actor or celebrity licenses their likeness.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"AI startup Pinecone raises $100 million as vector database market for LLMs heats up | VentureBeat"
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"https://venturebeat.com/ai/ai-startup-pinecone-raises-100-million-as-vector-database-market-for-llms-heats-up"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages AI startup Pinecone raises $100 million as vector database market for LLMs heats up Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Pinecone , the buzzy New York City-based vector database company that provides long-term memory for large language models (LLMs) like OpenAI’s GPT-4 , announced today that it has raised $100 million in series B funding at a $750 million valuation. The funding round was led by Andreessen Horowitz.
Pinecone introduced the vector database in 2021, a managed service which lets engineers build fast and scalable applications using embeddings from AI models and get them into production quickly. In today’s generative AI era, Pinecone helps engineers connect chatbots with their own company data to provide the right answer, and not hallucinate.
The rise of ChatGPT last fall sent Pinecone soaring, with the tool quickly becoming an integral part of the software stack — the memory layer — for AI applications. The company said that so far in 2023 it has seen an explosion in paying customers — including Gong and Zapier — across all industries and sizes. The vector database category has grown to include other tools, such as Chroma , Weaviate and Milvus.
>>Follow VentureBeat’s ongoing generative AI coverage<< VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Pinecone took off with the explosive shift to generative AI While the company was founded with an eye on the rise of LLMs, the speed and explosiveness of the generative AI shift came as a surprise, Edo Liberty, founder and CEO of Pinecone (and former director of research and head of Amazon AI Labs), told VentureBeat in a Zoom interview.
“It kind of breached the collective psyche,” he said. “It grew gradually but then it just took off overnight.” When ChatGPT launched, he explained, “millions of developers all over the world got excited and got super-creative about the kinds of stuff that you can do with this — they started building amazing applications.” In addition, he pointed out that generative AI suddenly became a boardroom-level discussion. “It doesn’t matter if you’re an architect or a law firm or a consulting company, this is potentially going to undermine or strengthen and you have to figure out what to do with it,” he said. “I don’t think there’s a single company that I speak with that doesn’t have something going on related to language and AI.” And interest in Pinecone keeps building among developers, who continue to research how to use LLMs. For example, over the past two months, the AI community has been buzzing about the long-term potential of autonomous AI agents , with tools popping up including Auto-GPT and BabyAGI. “Both of those projects use Pinecone,” said Liberty. “Again, that’s something that drove tremendous growth; I think at some point we were getting 10,000 signups a day.” The long-term outlook for vector databases Coincidentally, this week there was a great deal of Twitter chatter about a new research paper about the potential of a new architecture, the recurrent memory transformer (RMT), to allow LLMs to retain information across up to 2 million tokens. Some some said RMT could lessen the need for vector databases, but others said would not because the RMT requires much longer inference time.
But Greg Kogan, VP of marketing at Pinecone, told VentureBeat earlier this week that while the company had no comment about the specific paper, “there’s a big gap between something that works in the lab and something that works for large-scale, real-world applications where cost, performance, ease of use, and engineering overhead are important factors. That’s the gap we want to bridge.” He added that chatbots are a breakthrough technology Pinecone leaned into and “found a way to empower for real-world, large-scale applications.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"AI for security is here. Now we need security for AI | VentureBeat"
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"https://venturebeat.com/ai/ai-for-security-is-here-now-we-need-security-for-ai"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest AI for security is here. Now we need security for AI Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
After the release of ChatGPT, artificial intelligence (AI), machine learning (ML) and large language models (LLMs) have become the number one topic of discussion for cybersecurity practitioners, vendors and investors alike. This is no surprise; as Marc Andreessen noted a decade ago, software is eating the world, and AI is starting to eat software.
Despite all the attention AI received in the industry, the vast majority of the discussions have been focused on how advances in AI are going to impact defensive and offensive security capabilities. What is not being discussed as much is how we secure the AI workloads themselves.
Over the past several months, we have seen many cybersecurity vendors launch products powered by AI, such as Microsoft Security Copilot , infuse ChatGPT into existing offerings or even change the positioning altogether, such as how ShiftLeft became Qwiet AI.
I anticipate that we will continue to see a flood of press releases from tens and even hundreds of security vendors launching new AI products. It is obvious that AI for security is here.
A brief look at attack vectors of AI systems Securing AI and ML systems is difficult, as they have two types of vulnerabilities: Those that are common in other kinds of software applications and those unique to AI/ML.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! First, let’s get the obvious out of the way: The code that powers AI and ML is as likely to have vulnerabilities as code that runs any other software. For several decades, we have seen that attackers are perfectly capable of finding and exploiting the gaps in code to achieve their goals. This brings up a broad topic of code security, which encapsulates all the discussions about software security testing, shift left, supply chain security and the like.
Because AI and ML systems are designed to produce outputs after ingesting and analyzing large amounts of data, several unique challenges in securing them are not seen in other types of systems. MIT Sloan summarized these challenges by organizing relevant vulnerabilities across five categories: data risks, software risks, communications risks, human factor risks and system risks.
Some of the risks worth highlighting include: Data poisoning and manipulation attacks. Data poisoning happens when attackers tamper with raw data used by the AI/ML model. One of the most critical issues with data manipulation is that AI/ML models cannot be easily changed once erroneous inputs have been identified.
Model disclosure attacks happen when an attacker provides carefully designed inputs and observes the resulting outputs the algorithm produces.
Stealing models after they have been trained. Doing this can enable attackers to obtain sensitive data that was used for training the model, use the model itself for financial gain, or to impact its decisions. For example, if a bad actor knows what factors are considered when something is flagged as malicious behavior, they can find a way to avoid these markers and circumvent a security tool that uses the model.
Model poisoning attacks. Tampering with the underlying algorithms can make it possible for attackers to impact the decisions of the algorithm.
In a world where decisions are made and executed in real time, the impact of attacks on the algorithm can lead to catastrophic consequences. A case in point is the story of Knight Capital which lost $460 million in 45 minutes due to a bug in the company’s high-frequency trading algorithm. The firm was put on the verge of bankruptcy and ended up getting acquired by its rival shortly thereafter. Although in this specific case, the issue was not related to any adversarial behaviors, it is a great illustration of the potential impact an error in an algorithm may have.
AI security landscape As the mass adoption and application of AI are still fairly new, the security of AI is not yet well understood. In March 2023, the European Union Agency for Cybersecurity (ENISA) published a document titled Cybersecurity of AI and Standardisation with the intent to “provide an overview of standards (existing, being drafted, under consideration and planned) related to the cybersecurity of AI, assess their coverage and identify gaps” in standardization. Because the EU likes compliance, the focus of this document is on standards and regulations, not on practical recommendations for security leaders and practitioners.
There is a lot about the problem of AI security online, although it looks significantly less compared to the topic of using AI for cyber defense and offense. Many might argue that AI security can be tackled by getting people and tools from several disciplines including data, software and cloud security to work together, but there is a strong case to be made for a distinct specialization.
When it comes to the vendor landscape, I would categorize AI/ML security as an emerging field. The summary that follows provides a brief overview of vendors in this space. Note that: The chart only includes vendors in AI/ML model security. It does not include other critical players in fields that contribute to the security of AI such as encryption, data or cloud security.
The chart plots companies across two axes: capital raised and LinkedIn followers. It is understood that LinkedIn followers are not the best metric to compare against, but any other metric isn’t ideal either.
Although there are most definitely more founders tackling this problem in stealth mode, it is also apparent that AI/ML model security space is far from saturation. As these innovative technologies gain widespread adoption, we will inevitably see attacks and, with that, a growing number of entrepreneurs looking to tackle this hard-to-solve challenge.
Closing notes In the coming years, we will see AI and ML reshape the way people, organizations and entire industries operate. Every area of our lives — from the law, content creation, marketing, healthcare, engineering and space operations — will undergo significant changes. The real impact and the degree to which we can benefit from advances in AI/ML, however, will depend on how we as a society choose to handle aspects directly affected by this technology, including ethics, law, intellectual property ownership and the like. However, arguably one of the most critical parts is our ability to protect data, algorithms and software on which AI and ML run.
In a world powered by AI, any unexpected behavior of the algorithm compromised of the underlying data or the systems on which they run will have real-life consequences. The real-world impact of compromised AI systems can be catastrophic: misdiagnosed illnesses leading to medical decisions which cannot be undone, crashes of financial markets and car accidents, to name a few.
Although many of us have great imaginations, we cannot yet fully comprehend the whole range of ways in which we can be affected. As of today, it does not appear possible to find any news about AI/ML hacks; it may be because there aren’t any, or more likely because they have not yet been detected. That will change soon.
Despite the danger, I believe the future can be bright. When the internet infrastructure was built, security was an afterthought because, at the time, we didn’t have any experience designing digital systems at a planetary scale or any idea of what the future may look like.
Today, we are in a very different place. Although there is not enough security talent, there is a solid understanding that security is critical and a decent idea of what the fundamentals of security look like. That, combined with the fact that many of the brightest industry innovators are working to secure AI, gives us a chance to not repeat the mistakes of the past and build this new technology on a solid and secure foundation.
Will we use this chance? Only time will tell. For now, I am curious about what new types of security problems AI and ML will bring and what new types of solutions will emerge in the industry as a result.
Ross Haleliuk is a cybersecurity product leader, head of product at LimaCharlie and author of Venture in Security.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"The evolution of Web3 and the year crypto got serious | VentureBeat"
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"https://venturebeat.com/virtual/the-evolution-of-web3-and-the-year-crypto-got-serious"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest The evolution of Web3 and the year crypto got serious Share on Facebook Share on X Share on LinkedIn Beautiful abstract of cryptocurrency illustration concept shows lines and symbol of the Bitcoin in the dark background.
Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
The passing year may very well be considered seminal when it comes to the evolution of cryptocurrencies and Web3 in general. Numerous events across the globe, some tragic, have put digital assets in the scopes of financial regulators like never before — prompting many to conclude that the sector has finally “gotten serious” this year.
At the same time, the mass adoption of cryptocurrencies continues unabated among regular users and institutions alike, and this trend will only grow in 2023 and beyond.
Hard-learned lessons The main event that affected crypto — and the whole world — over the past year is undoubtedly the war in Ukraine. When it began, governments around the globe realized that it was possible to send millions of dollars worth of digital assets to a country to buy weapons — without any oversight. While the Western world agreed this was acceptable in Ukraine’s case, it dawned on policymakers that the same could be done for any terrorist organization.
As a result, Germany’s Federal Intelligence Service (Bundesnachrichtendienst) and the FBI started hiring tech specialists en masse to mitigate the risk of Russia subverting sanctions via crypto.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! This is where Western law enforcement agencies started putting more focus on regulation.
In turn, and in what was the second-biggest event for crypto, came the Queen’s Speech in the U.K., which set out the government’s plans to introduce legislation to reduce economic crime and help crypto businesses grow. Correspondingly, the European Parliament introduced a legal framework for crypto assets in the EU in March 2022 to “boost benefits and curb threats” of crypto. Moreover, the U.S. Securities and Exchange Commission recently announced that it would make cryptocurrencies its focus going forward, setting forth plans to enact its own regulations.
While heated debates about crypto regulation have been taking place for years, we now know that regulators are in favor of championing new technologies while ensuring consumers are protected and criminal elements removed. This represents a watershed moment for crypto — the point at which the industry grew up.
Crypto tech needs to “disappear” As for where we go next, when it comes to the mass adoption of cryptocurrencies, we really need the technology to “disappear.” In other words, it shouldn’t be visible to regular retail users, nor should they need a degree in cybersecurity to be able to interact with it. This starts with the basics, i.e., user experience. You can’t expect people to remember highly complex addresses or write down 12 random words on a piece of paper.
Moreover, the idea of decentralized finance (DeFi) and “Not your keys, not your coins” is a fallacy — more money has been lost due to people misplacing their keys than via any exchange hack ever. DeFi is a great tool when you know exactly what you’re doing, but that can’t be applied to the vast majority of users, especially those who aren’t crypto-native.
Most people don’t care whether they spend crypto or fiat currencies when swiping their phones at a grocery store. To become truly useful, these intricacies need to disappear “under the hood” so users won’t be inundated with superfluous technological challenges.
Institutional involvement in 2023 Meanwhile, it’s not only retail users that can benefit from the seamless integration of crypto into traditional finance systems. Over the past years, many institutional companies and brands have started to dip their toes into decentralized technologies, and this trend will pick up even more steam in 2023.
For example, brokerage giant Fidelity Investments recently launched a new crypto trading product for retail investors. Meanwhile, a lot more non-crypto-native firms and even family offices have started to actively look for new ways to get involved with digital assets.
Notably, some of them did get into crypto via prominent and well-respected, at least at the time, crypto platforms — some of which haven’t turned out so well. So going forward, these firms will focus even more on due diligence, and that’s why regulatory frameworks will need to evolve further.
Firms should be able to discover their crypto partners’ backgrounds, where the assets are, how they are stored and whether they’re compliant — everything you expect to be able to find out about your bank, essentially.
Further, more non-crypto platforms will likely start offering digital products in 2023. This will likely result in an ecosystem where financial services tend to merge. Instead of different apps for insurance, savings, bank accounts or crypto, we will see the concentration of different trading options and savings and retirement plans in the fintech space.
For this to happen, however, certain elements need to be anchored in authority. Even DeFi platforms still depend on centralized operators, like stablecoin issuers, for instance, so there is no such thing as “absolute” decentralization.
Ultimately, digital assets will become “the norm” and so ingrained in our day-to-day life that even the term “crypto” itself will disappear in just a few years. Web3 will become an inextricable part of the worldwide financial system and services going forward.
Larry Fink, CEO of investment monolith Blackrock, has already nodded toward this future, noting that “the next generation for markets, the next generation for securities, will be tokenization of securities.” With blockchain tech offering reduced fees, reduced reliance on intermediaries, and instant settlement, its introduction into the traditional financial system is a no-brainer. In turn, this will bring much-needed legitimacy to the sector, further validating existing products and fostering greater adoption.
“Crypto winter” is a time for building As for the current “crypto winter,” it could actually be a net positive for the industry in the long term. Even though many are referring to this period as the harshest crypto winter in the industry’s history, the builders and the developers haven’t gone into hibernation.
Instead, the industry is working hard to bring out better products and services. Algorand boosted its performance by more than five times via a network upgrade in September.
And the Ethereum Merge — which saw the network transition to the more efficient proof-of-stake mechanism — went off without a hitch, increasing Ethereum’s sustainability credentials and paving the way toward greater scalability in 2023.
So, while some projects have fallen this year, and some have been washed out of the market, the industry hasn’t come to a standstill. Valuable lessons have been learned this year and will, in turn, create better, more trustworthy and more secure services as we go into 2023. As crypto gets serious, so will the considerations of adoption from mainstream firms and audiences.
Martin Hiesboeck, Ph.D. is head of research at Uphold and a consultant for data analytics, blockchain and crypto implementation, tokenization, DeFi, web3, stablecoins and CBDCs.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Working in cybersecurity and zero trust with Ericom Software's David Canellos | VentureBeat"
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"https://venturebeat.com/security/working-in-cybersecurity-and-zero-trust-with-ericom-softwares-david-canellos"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Working in cybersecurity and zero trust with Ericom Software’s David Canellos Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
VentureBeat sat down (virtually) with David Canellos, president and CEO of Ericom Software , to gain his insights into the unique challenges and opportunities of helming a leading cybersecurity provider today. Previously, Canellos was SVP of global service providers for Symantec , which he joined through the acquisition of Blue Coat Systems. He has also held various executive positions with the Oracle Corporation , Versatility and SAIC.
The following is an excerpt of VentureBeat’s interview with David Canellos: Why cybersecurity? VentureBeat: How did you get started in the cybersecurity industry, and what keeps the field fascinating to you? David Canellos: Nearly 20 years ago, I peered around the corner and realized that the pace of technological advancement and digitalization of every aspect of life was escalating — the internet was expanding, ecommerce was challenging the brick-and-mortar model, smartphones had just been introduced, premium digital content was available online, cloud computing was starting to emerge, Google search had become a thing — but cybersecurity wasn’t keeping up. If anything, it was an afterthought, bolted on versus being built in by design.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Since insiders were trusted, network security was “castle-and-moat,” designed to protect against external threats like distributed denial of service attacks on popular or important websites. The gaps that this model left open represent a large attack surface that continues to grow as digital transformation proceeds.
Back then, I lucked out and found Cloakware , an early-stage cybersecurity provider that created software to protect source code. A fascinating proposition — to secure sensitive software like digital rights management and online gaming, defend military equipment from reverse-engineering by a potential adversary to get at highly sensitive software secrets, secure root passwords of critical infrastructure, and so on. Once bitten, I went all in on cyber and haven’t looked back.
What keeps me going is the dynamic, constantly evolving nature of the cybersecurity industry — always something new to learn and new challenges to tackle. And the stakes are higher than ever, which makes the industry exciting.
VentureBeat: What led you to take on the CEO role at Ericom? What are the favorite parts of your role? Canellos: Ericom is a fascinating company that went beyond intriguing for me.
When I joined, the company was in the early innings of an intentional pivot from its successful heritage of remote access to cybersecurity, and the foundational pieces were in place: a blue-chip customer base, real revenues from production customers vs. pilots or POCs, technology and GTM partners and, most importantly, a talented core team. My belief was I could have an impact by stimulating further growth, in particular, by extending the strategy to develop a cybersecurity access platform on the public cloud, delivered globally as a true, cloud-native service.
The roots and epicenter of Ericom are in Israel, a country known as a startup nation in large part due to its disruptive cybersecurity innovations. Security is intertwined in the culture and way of life in Israel, and hence the access to talented and creative people — especially engineers — aiming for cybersecurity careers was attractive.
The company was and is bootstrapped. There’s no venture capital or private equity, so customer sales are what funds the company. So no preferred class of shares, a simple cap table and a level playing field for all Ericom stakeholders. This results in a sense of ownership and shared mission across our employees, allowing us to feel connected to what really matters and that the work we do has a greater sense of purpose.
It’s been a heavy lift for all of us. For me personally, it’s been satisfying that Ericom scratched my itch to (1) learn and grow professionally, (2) make some money, and (3) have fun. Wrapping all of this into one phrase, it’s the creation of a company culture embodied in what we call #OneEricom.
Zero trust and the security stack VentureBeat: What is Ericom’s vision of zero trust, and how does that guide the roadmap of your products and services? Canellos: Consistent with the view of our chief strategy officer, Chase Cunningham, who helped validate and extend the zero-trust concept while at Forrester, our products implicitly trust no one, verify often, and make sure if and when an attacker gets in, they are restricted by segmentation so they can’t cause widespread damage. In effect, minimizing the blast radius of anything that goes wrong.
Our roadmap is guided by our commitment to creating products that help our customers actualize that zero-trust vision in their organizations.
VentureBeat: Ericom’s first move into the cybersecurity market was with a remote browser isolation (RBI) solution for web security. Why did the company start there? Canellos: Ericom has a strong history of developing remote access and connectivity solutions. At one point, we found that our virtualization solutions were being used in Japan, one of our key markets, to help organizations comply with an “internet separation” requirement — basically ensuring that any system accessing the web was separated from the rest of the network for security purposes.
While these customers were achieving effective separation, virtualization was not a great solution from either the user experience or cost perspective.
By developing a highly scalable and cost-effective remote browser isolation solution, we made a real difference for our customers.
VentureBeat: How has your solution evolved over the past few years? Canellos: More than our RBI solution has evolved; our product portfolio has evolved well beyond RBI to provide a full cybersecurity stack.
Ericom now delivers a full-stack cybersecurity platform aligned with Gartner’s Security Services Edge (SSE) model on a global cloud infrastructure. This multi-tenant platform includes an integrated set of controls that simplifies operations and improves security outcomes. It includes a secure web gateway with built-in RBI core, clientless and client-based zero-trust network access (ZTNA) options, cloud access security broker (CASB), data loss prevention (DLP), and more.
We invested heavily in developing this cloud-native solution, including the underlying architecture, which we call the Ericom Global Cloud. It is a high-availability, elastic, cloud-native infrastructure that scales to deliver an outstanding, low-latency user experience. We built it on public cloud IaaS, so it’s not tied to any specific provider’s infrastructure, which results in unique flexibility, performance and cost advantages. To date, more than 50 Ericom Global Cloud points of presence (POPs) are available, and we are adding more this year.
VentureBeat: What are the primary security use cases you are seeing organizations address with your SSE solution? Canellos: Despite some return to the office, distributed remote/home-based work has become a permanent fixture in most of the markets we serve. There is a huge need to connect these workers to corporate apps securely — whether to SaaS apps like Salesforce or ServiceNow, or corporate cloud or legacy apps, so this is a key use case. We address this need with the ZTNA capabilities in our platform and our CASB solution.
On the topic of securing work from home, I’m particularly excited about our clientless ZTNA solution, which protects corporate apps and data from risks and threats from unmanaged devices and BYOD — a big challenge for organizations.
Use of unmanaged devices is on the rise. For example, new distributed work environments and flexible team structures have made use of third-party contractors the norm in most organizations. Contractors typically need to access many of the same apps and data that an organization’s salaried employees use each day.
But unlike employees, contractors typically don’t use laptops that are provisioned and managed by IT departments, so it is challenging — or impossible — to deploy and configure the necessary VPN software and endpoint security on their laptops. As a result, unmanaged devices represent a unique threat to a company’s data, as well as the security of their entire network.
Our solution allows IT teams to set and enforce granular app access and data-use policies for unmanaged devices in the cloud without installing any agents or changing configurations on contractors’ devices. Using their standard web browser, contractors log in as normal, yet their privileges and application use can be controlled. The extensive, policy-based security controls provided by the solution are noteworthy in a solution that is simple to use and deploy.
Our customers also need to protect all users as they interact with the web, whether they are onsite or remote. To address web security, our SWG has web isolation capabilities built-in, as well as DLP for data security.
Phishing prevention is a particular concern since, despite widespread mandatory antiphishing training, users keep clicking on emails and links. Our platform’s unique antiphishing solution allows IT teams to have websites launched from links in emails open in a read-only, isolated mode to help prevent credential theft and block malware.
Unlike nearly all other SSE vendors, Ericom’s platform includes identity management capabilities with multifactor authentication as a standard component. Zero-trust starts with understanding identity. Once an enterprise authenticates an identity, it can enforce the appropriate user-level authorization and access policies. This is fundamental to zero trust, so it is core to our platform.
Building a global cloud infrastructure VentureBeat: I’ve seen a number of announcements about the build-out of your global cloud infrastructure. Why are additional POPs important enough that you announce them? Canellos: Having differentiated security capabilities in your SSE service is only half the equation for a security vendor like us. Equally important is how you deliver these capabilities — and that is what makes our growing number and distribution of POPs newsworthy.
We are very proud of the cloud infrastructure we’ve developed. The Ericom Global Cloud is a high-availability, elastic, cloud-native infrastructure that scales to deliver an outstanding, low-latency user experience. It is built on public cloud IaaS without being tied to any specific provider’s infrastructure, giving it unique flexibility, performance and cost advantages.
As you mentioned, we are quite active in building it out. To date, more than 50 Ericom Global Cloud POPs are available.
VentureBeat: Can you discuss any challenges Ericom has faced in developing its technology or bringing its solutions to market and how it overcame them? Canellos: Well, on the technology front we’ve discussed a few, such as designing an IaaS provider-agnostic global cloud infrastructure or developing new solutions for thorny issues like unmanaged device access, phishing or virtual meeting security. We tackled all of these as a boot-strapped organization, taking in no outside institutional capital.
This required us to stay very disciplined on the technology side of the house, working side by side with customers and partners, staying laser-focused on key priorities, and closely following the build-measure-learn approach defined in The Lean Startup , Eric Ries’ famous book (which lives right here, on my desk).
On the go-to-market front, we took the time up front to identify strategic partners with strong mutual technology/product/service alignment in order to create efficient routes to market.
Building a cybersecurity career VentureBeat: What advice would you give someone interested in pursuing a career in cybersecurity? Canellos: Three things come to mind: To embark on a career in cybersecurity, it is crucial to familiarize yourself with the various areas of specialization in an ever-broadening field. This can include network security, application security, cloud security, cryptography, and other areas. Setting up a personal lab environment to experiment with different tools and techniques can help you gain practical experience and develop your skills.
The cybersecurity landscape is continually evolving. Staying current with the latest trends and technologies is essential for success. So read blogs, listen to webinars, attend conferences like RSA and Black Hat, and read industry publications.
Building a network of cybersecurity professionals can give you opportunities to learn about new prospects, obtain industry insights and establish valuable relationships that can help advance your career. Keep in mind that staying engaged and connected is critical in such a competitive and rapidly evolving industry.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Securing cloud tech stacks with zero trust will drive growth of confidential computing | VentureBeat"
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"https://venturebeat.com/security/securing-cloud-tech-stacks-with-zero-trust-will-drive-growth-of-confidential-computing"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Securing cloud tech stacks with zero trust will drive growth of confidential computing Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
For enterprises to realize the potential that real-time datasets can deliver, cloud tech stacks need hardening with zero trust. In this, confidential computing is essential to securing data at rest, in transit and in use.
VentureBeat spoke with CIOs from banking, financial services and insurance industries who say they are at various stages of piloting confidential computing to see how well it handles their compliance, regulatory reporting and real-time auditing of data transactions. Notably, compliance and support for zero trust frameworks are emerging as the killer apps.
One CIO who spoke on condition of anonymity said that their board of directors’ team assigned to risk management wants to see proof that data is secured during use within protected CPU enclaves and Trusted Execution Environments (TEEs), two foundational elements of confidential computing.
Board members on risk management teams recall Meltdown and Spectre vulnerabilities that target processors that rely on branch prediction and advanced speculative actions. CIOs and CISOs say boards need to see pilot data and simulated attacks thwarted before they go into production with confidential computing.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Based on period pilots that VentureBeat is briefed on, it’s clear that confidential computing strengthens zero trust in multicloud tech stacks on which highly regulated businesses rely on. Compliance, privacy, and security use cases, particularly on public cloud, have gained the most significant traction, accounting for 30 to 35% of the worldwide market, according to Everest Groups’ report Confidential Computing: The Next Frontier in Data Security.
And, the confidential computing market is predicted to grow to $54 billion by 2026.
What is confidential computing? Confidential Computing is a cloud computing technology that secures data during processing by isolating sensitive data in a protected CPU enclave.
The contents of each enclave , including the data and analysis techniques, are only accessed with authorized programming codes, remaining invisible and protected from external access.
Confidential computing is gaining momentum because it provides greater data confidentiality, data and code integrity than current security technologies protecting cloud tech stacks and infrastructure.
The Confidential Computing Consortium (CCC) is instrumental in promoting and defining confidential computing across the industry. The CCC is a Linux Foundation project that combines the efforts of hardware vendors, cloud providers and software developers to help increase the adoption and standardization of TEE technologies.
TEEs protect proprietary business logic, analytics functions, machine learning (ML) algorithms and applications. Founding members include Alibaba, Arm, Google, Huawei, Intel, Microsoft and Red Hat. The CCC defines confidential computing as protecting data in use by computing in a hardware-based TEE.
Compliance a growth driver What’s working in confidential computing’s favor with boards is how effective it is at ensuring regulatory compliance. It’s also proven to be effective at enforcing end-to-end security and least privileged access to data at rest, in transit and in use. CIOs and CISOs tell VentureBeat that they expect confidential computing to be complimentary to their Zero Trust Network Access (ZTNA) frameworks and supporting initiatives.
John Kindervag created zero trust and currently serves as SVP for cybersecurity strategy and is a group fellow at ON2IT Cybersecurity. He is also an advisory board member for several organizations, including to the offices of the CEO and president of the Cloud Security Alliance.
He recently told VentureBeat that “the biggest and best-unintended consequence of zero trust was how much it improves the ability to deal with compliance and auditors.” And, he said that a Forrester client called and informed him how perfectly aligned zero trust was with their compliance and audit automation process.
Securing cloud tech stacks with confidential computing Mark Russinovich , CTO and technical fellow of Microsoft Azure writes that: “Our vision is to transform the Azure cloud into the Azure confidential cloud, moving from computing in the clear to computing confidentially across the cloud and edge. We want to empower customers to achieve the highest levels of privacy and security for all their workloads.” Cloud platform providers endorsed and began integrating CCC’s requirements into their product roadmaps as early as 2019, when the CC was formed. What’s guiding cloud platform providers is the goal of providing their customers with the technical controls necessary to isolate data from cloud platform operators, their operators, or both.
Microsoft’s Azure confidential computing is considered an industry leader because their DevOps teams designed the platform to go beyond hypervisor isolation between customer tenants to safeguard customer data from Microsoft operator access.
CIOs and CISOs have identified to VentureBeat what they’re looking for when it comes to a baseline level of performance with confidential computing. First, remote attestation needs to be proven in live customer sites with referenceable accounts willing to speak to how they are using it to check the integrity of the environment. Second, trusted launch workflows and processes ideally need to be cloud-based, in production, and proven to validate virtual machines starting up with authorized software and continuous remote attestation to check for customers.
Silicon-based zero trust is the way Martin G. Dixon, Intel fellow and VP of Intel’s security architecture and engineering group writes that, “I believe the zero trust concepts shouldn’t stop at the network or system. Rather, they can be applied down inside the silicon. We even refer to infrastructure on the chip as a network or ‘network on a chip.'” Part of that vision at Intel included the need for attestation to become more pervasive and portable to fuel confidential computing’s growth, starting at the silicon level.
To address this, the company introduced Project Amber , whose goals include providing independent attestation, more uniform, portable attestation and improved policy verification.
“With the introduction of Project Amber, Intel is taking confidential computing to the next level in our commitment to a zero trust approach to attestation and the verification of compute assets at the network, edge and in the cloud,” Greg Lavender, Intel’s CTO said at the company’s Intel Vision conference last year.
He continued that Intel is focused on “extending attestation services in the cloud data center in the edge computing environments to provide unprecedented security. The Intel Software as a Service offering Project Amber is a trusted service solution that will provide organizations with independent verification and trustworthiness of customer assets no matter where they run.” Getting silicon-based zero trust security right needs to start with TEEs hardened enough to protect sensitive data at rest, in transit and in use. Migrating zero trust into silicon also strengthens authentication and authorization, taking identity and access management (IAM) and privileged access management to the hardware level, which makes it harder for attackers to bypass or manipulate authentication systems and improves the security of confidential computing environments.
Additional benefits of moving zero trust into silicon include encrypting all data and ensuring a higher level of data integrity and applying zero trust principles to data encryption and authentication. With zero trust frameworks requiring continuous security configuration and posture validation for all users and devices, supporting monitoring in silicon will reduce the overhead on cloud platform performance.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"DataDome raises $42M to leverage machine learning for confronting bot attacks | VentureBeat"
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"https://venturebeat.com/security/datadome-raises-42m-to-leverage-machine-learning-for-confronting-bot-attacks"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages DataDome raises $42M to leverage machine learning for confronting bot attacks Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Malicious traffic is something that any organization with a website has to address. According to Imperva , 42.3% of internet traffic belongs to bots, and many of these are designed to crawl through online websites and APIs to identify vulnerabilities.
In response, companies like bot management provider DataDome have turned Artificial Intelligence (AI) to identify account takeover, credential stuffing, fake account creation and payment fraud threats orchestrated by bots. To support this mission, DataDome today announced it has raised $42 million as part of a Series C funding round.
DataDome’s platform uses machine learning (ML) at the edge and an AI-powered bot detection engine to process over 3 trillion signals a day and automatically identify bot attacks targeting websites, mobile apps and APIs.
Confronting automated bot attacks The announcement comes as more and more organizations are struggling to confront the onslaught of automated website attacks.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! “Attacks leveraging bots have undeniably become a common path to fraud,” said Benjamin Fabre, CEO of DataDome. “To complicate matters, AI is making it easier for threat actors to create sophisticated attacks in minutes that target any point in the customer journey (and profit along the way). This is particularly true for bot-driven attacks.” “Now consider that cybersecurity and fraud mitigation have traditionally bee3n handled by siloed departments, which enables attackers to take advantage of vulnerabilities,” said Fabre. “It’s a perfect storm.” By leveraging automation, DataDome functions to assure organizations that the users accessing their websites are real, and also that data and accounts aren’t at risk of compromise.
Organizations that are experiencing a bot attack on their website also receive 24/7 support from DataDome’s specialist threat intelligence team so they can remediate the incident and maintain normal operations.
Reviewing the bot security market DataDome’s solution falls loosely within the bot security market, which MarketsandMarkets estimates will increase from a value of $408 million in 2021 to $983 million by 2026.
Some of DataDome’s main competitors are content delivery networks (CDNs) like Cloudflare and Akamai , which offer additional bot management solutions.
Cloudflare, which raised $975.2 million in revenue in 2022, uses ML to analyze traffic and score requests to identify anomalous activity and bot attacks. Traffic fingerprinting enables the solution to pinpoint bot traffic and identify credential stuffing, content scraping, Distributed-Denial-of-Service (DDoS) attempts targeting apps and credit card stuffing attempts.
Similarly, Akamai, which recently announced raising over $3.6 billion in revenue in 2022, offers its own traffic protection product; Bot Manager. Bot Manager uses AI models and fingerprinting to analyze user behavior against a continuously updated directory of over 1,500 bots.
However, one of the key differentiators between DataDome and these providers, the company says, is its external security support.
“DataDome detects and responds to attacks with unparalleled speed, accuracy, reliability and expertise using ML monitored by our in-house Security Operation Center (SOC),” said Fabre.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Cybersecurity experts argue that pausing GPT-4 development is pointless | VentureBeat"
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"https://venturebeat.com/security/cybersecurity-experts-argue-that-pausing-gpt-4-development-is-pointless"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Cybersecurity experts argue that pausing GPT-4 development is pointless Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Earlier this week, a group of more than 1,800 artificial intelligence (AI) leaders and technologists ranging from Elon Musk to Steve Wozniak issued an open letter calling on all AI labs to immediately pause development for six months on AI systems more powerful than GPT-4 due to “profound risks to society and humanity.” While a pause could serve to help better understand and regulate the societal risks created by generative AI , some argue that it’s also an attempt for lagging competitors to catch up on AI research with leaders in the space like OpenAI.
According to Gartner distinguished VP analyst Avivah Litan, who spoke with VentureBeat about the issue, “The six-month pause is a plea to stop the training of models more powerful than GPT-4. GPT 4.5 will soon be followed by GPT-5, which is expected to achieve AGI (artificial general intelligence).
Once AGI arrives, it will likely be too late to institute safety controls that effectively guard human use of these systems.” >>Follow VentureBeat’s ongoing generative AI coverage<< VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Despite concerns about the societal risks posed by generative AI, many cybersecurity experts are doubtful that a pause in AI development would help at all. Instead, they argue that such a pause would provide only a temporary reprieve for security teams to develop their defenses and prepare to respond to an increase in social engineering , phishing and malicious code generation.
Why a pause on generative AI development isn’t feasible One of the most convincing arguments against a pause on AI research from a cybersecurity perspective is that it only impacts vendors, and not malicious threat actors. Cybercriminals would still have the ability to develop new attack vectors and hone their offensive techniques.
“Pausing the development of the next generation of AI will not stop unscrupulous actors from continuing to take the technology in dangerous directions,” Steve Grobman, CTO of McAfee, told VentureBeat. “When you have technological breakthroughs, having organizations and companies with ethics and standards that continue to advance the technology is imperative to ensuring that the technology is used in the most responsible way possible.” At the same time, implementing a ban on training AI systems could be considered a regulatory overreach.
“AI is applied math, and we can’t legislate, regulate or prevent people from doing math. Rather, we need to understand it, educate our leaders to use it responsibly in the right places and recognise that our adversaries will seek to exploit it,” Grobman said.
So what is to be done? If a complete pause on generative AI development isn’t practical, instead, regulators and private organizations should look at developing a consensus surrounding the parameters of AI development, the level of inbuilt protections that tools like GPT-4 need to have and the measures that enterprises can use to mitigate associated risks.
“AI regulation is an important and ongoing conversation, and legislation on the moral and safe use of these technologies remains an urgent challenge for legislators with sector-specific knowledge, since the use case range is partially boundless from healthcare through to aerospace,” Justin Fier, SVP of Red Team Operations, Darktrace , told VentureBeat.
“Reaching a national or international consensus on who should be held liable for misapplications of all kinds of AI and automation, not just gen AI, is an important challenge that a short pause on gen AI model development specifically is not likely to solve,” Fier said.
Rather than a pause, the cybersecurity community would be better served by focusing on accelerating the discussion on how to manage the risks associated with the malicious use of generative AI, and urging AI vendors to be more transparent about the guardrails implemented to prevent new threats.
How to gain back trust in AI solutions For Gartner’s Litan, current large language model (LLM) development requires users to put their trust in a vendor’s red-teaming capabilities. However, organizations like OpenAI are opaque in how they manage risks internally, and offer users little ability to monitor the performance of those inbuilt protections.
As a result, organizations need new tools and frameworks to manage the cyber risks introduced by generative AI.
“We need a new class of AI trust, risk and security management [TRiSM] tools that manage data and process flows between users and companies hosting LLM foundation models. These would be [cloud access security broker] CASB -like in their technical configurations but, unlike CASB functions, they would be trained on mitigating the risks and increasing the trust in using cloud-based foundation AI models,” Litan said.
As part of an AI TRiSM architecture, users should expect the vendors hosting or providing these models to provide them with the tools to detect data and content anomalies, alongside additional data protection and privacy assurance capabilities, such as masking.
Unlike existing tools like ModelOps and adversarial attack resistance, which can only be executed by a model owner and operator, AI TRiSM enables users to play a greater role in defining the level of risk presented by tools like GPT-4.
Preparation is key Ultimately, rather than trying to stifle generative AI development, organizations should look for ways they can prepare to confront the risks provided by generative AI.
One way to do this is to find new ways to fight AI with AI, and follow the lead of organizations like Microsoft , Orca Security , ARMO and Sophos , which have already developed new defensive use cases for generative AI.
For instance, Microsoft Security Copilot uses a mix of GPT-4 and its own proprietary data to process alerts created by security tools, and translates them into a natural language explanation of security incidents. This gives human users a narrative to refer to to respond to breaches more effectively.
This is just one example of how GPT-4 can be used defensively. With generative AI readily available and out in the wild, it’s on security teams to find out how they can leverage these tools as a false multiplier to secure their organizations.
“This technology is coming … and quickly,” Jeff Pollard, Forrester VP principal analyst, told VentureBeat. “The only way cybersecurity will be ready is to start dealing with it now. Pretending that it’s not coming — or pretending that a pause will help — will just cost cybersecurity teams in the long run. Teams need to start researching and learning now how these technologies will transform how they do their job.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"The role missing from the tech company C-suite | VentureBeat"
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"https://venturebeat.com/programming-development/the-role-missing-from-the-tech-company-c-suite"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest The role missing from the tech company C-suite Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
C-suite roles typically map onto each of a company’s major needs. They are usually filled to create and implement business and technology strategies, manage financials and ensure that the right people are hired. However, leadership typically lacks a voice that advocates for developers at the executive level — a surprising oversight, given the competitive advantage that good developer experience (DX) can bring.
If companies sell directly to developers, the value of focusing on DX is likely self-evident. But a reputation for catering to developers can help you get your foot in the door, either when appealing to potential clients or improving your own company’s development and UX workflows.
Additionally, it’s an important focus for companies because at least 70% of developers feel they substantially or completely influence purchasing decisions, with 87% of companies consulting developers during the procurement process, and 91% of developers saying it matters that they are consulted.
A small number of pioneering firms are now creating chief developer experience officer ( CDXO ) roles. While many companies do have lower-level developer advocates, the CDXO represents a major shift in the role developers can play in company strategy. The role can provide a competitive advantage by orchestrating DX improvements to executives at a greater scale and faster timeframe than a lower-level role could often permit. The DX focus also goes hand in hand with a product-led growth (PLG) strategy.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Why DX falls short without a CDXO Without a DX voice in the C-suite, executives often fail to see the urgency of DX improvements and underestimate the substantial benefits they can bring. This results in a gap between lower-level discussions and the C-suite, and as a result, DX improvements are frequently sluggish and insufficient.
A potential consequence is that many developers may not have their needs efficiently met. A recent developer survey from Stack Overflow found that more than 65% of developers encounter knowledge silos, and more than 60% spend 30 minutes or more a day looking for the answers they need.
The developer role is dynamic and requires a lot of problem solving. Focusing on optimal DX requires both reactive and proactive improvements — meeting developer needs while adding useful features ahead of a demand for them. And only a CDXO has the high-level vantage point needed to make sure this happens.
The CDXO role is also useful for keeping a company honest about whether it’s actually succeeding in its DX goals. It’s easy to brag about great DX (and many companies do), but it’s also easy for developers to recognize when much-hyped offerings fail to meet their needs. Without a CDXO, getting a DX reality check may not occur quickly enough for executives to factor it into their decision-making.
The CDXO’s greatest asset: Their stakeholder connections The utility of the CDXO is more than just the connection to the C-suite: It’s the connection to the entire company and the customer base.
Even as more companies embrace the CDXO role, we will likely not see dedicated DX departments. Instead, DX excellence is a company mindset. The developer user experience is split across the web, command line interface, APIs and many more tools, and each of these elements needs to be optimized with DX in mind for a more efficient development lifecycle. The CDXO will serve as the link between these departments to coordinate improvements.
The CDXO can also help to build, foster and support a developer community. That community may include the company’s own developers, as well as ones to whom the company’s products are sold. If the CDXO consistently acts on feedback to implement changes, developers will grow to trust them and want to interact with them. Open sourcing products goes even further by communicating transparency by making the community feel part of the solution by allowing them to contribute directly to improving the product in a way that achieves their goals.
If DX is straightforward to the point that developers can quickly solve their own problems, and this remains the case even as the industry evolves, it will solidify the CDXO’s connection to the community.
Qualities to look for in a CDXO As someone who needs to understand the developer’s viewpoint, the CDXO should come from a technical development background. This is the only way to ensure the CDXO fully understands the developer process, pains and major challenges, as well as the places where fixes are most needed and the most important projects to launch for proactive improvement.
The CDXO also needs to have strong leadership skills. After all, the crux of the role is explaining to fellow C-suite members why improvements are necessary for the organization to gain a competitive advantage. There will likely be more issues to tackle than time to do so, and the ability to prioritize effectively is also essential for the CDXO.
Finally, enthusiasm is a must. For the CDXO, DX should be a true passion. Engaging with the developer community should not be a chore, but something done regularly and out of interest. If the CDXO legitimately engages with and cares about developers, everyday users become dedicated supporters.
The eight questions to ask if you need a CDXO It’s entirely possible that some organizations already hold themselves accountable for DX without a CDXO. However, if you are considering establishing a CDXO role, consider the following questions, split into three categories, when evaluating your company: Positively impacting DX: Unless your organization can answer “yes” to these questions, your DX may lag behind competitors: Does your approach to DX accelerate delivery and increase productivity? Does it deliver value to developers? Does it help to improve the quality of the product? Promoting the human aspect of DX: The answers to these questions reflect your ability to tap into developers’ drive to experiment: Does your approach to DX allow developers to experiment and innovate? Does it promote loyalty and a human connection? Driving DX decision-making: Prompt DX improvements require quick communication and coordination between every part of a company: Does your approach to DX allow shortcomings to be quickly communicated between departments? Does it impact the C-suite’s decision-making? Does it keep developers in the loop about improvements? The CDXO makes the tech C-suite more complete As the driver of the entire company, the C-suite needs to actively seek out and address any failures that deter the firm from operating as effectively as possible. As developers’ voices receive more recognition that can potentially impact bottom lines, many companies will realize how essential DX is for improving productivity, appealing to clients, and building dedicated developer communities.
The CDXO role is perfect for coordinating the entire company in making major DX improvements, thereby marketing efficiently to the company’s core audience, while serving as a friendly point of contact who developers can trust.
Alessandro Cauduro is chief development experience officer at Azion Technologies.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"4 key things IoT developers need to keep in mind as the number of connected devices explodes | VentureBeat"
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"https://venturebeat.com/programming-development/4-key-things-iot-developers-need-to-keep-in-mind-as-the-number-of-connected-devices-explodes"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest 4 key things IoT developers need to keep in mind as the number of connected devices explodes Share on Facebook Share on X Share on LinkedIn European telecommunication network connected over Europe, France, Germany, UK, Italy, concept about internet and global communication technology for finance, blockchain or IoT.
Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
When it comes to the internet of things (IoT), it’s time for developers to place a greater focus on the “things” — connected devices. The number of cellular IoT connections will more than double to upwards of 5 billion in 2027. And as they develop for the cloud and data centers, developers must start paying attention to the challenges that could arise with the explosion of connected devices.
With this backdrop, managing devices at scale is an ever-increasing problem. Each device is effectively a remote computer, and companies delivering IoT solutions will soon find themselves dealing with the problem of managing a large fleet of devices that need to be updated, secured and monitored.
This comes along with the traditional problems of running production software to a new scale, with potential issues including lack of visibility, devices running outdated software, devices having security exploits that need to be stopped and patched and more.
Further, devices are often not physically accessible to allow recovery from bad updates, meaning groups of devices could be “bricked” if they’re updated without the ability to apply a rollback mechanism. With all of these moving parts in play, there are four key things IoT developers need to keep in mind.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Device management The first secret of effective device management is making sure all devices are well-identified in a secure fashion. Even though devices can be thought of as “cattle” — meaning no individual device is itself important — in practice, devices are often not interchangeable with one another. Rather, each device is a unique runtime, acting almost as a mini data center. Therefore, it is important to uniquely identify them at scale.
Once device identity is established, devices can be annotated with the right metadata for management and grouping.
Next, teams need to ensure management can work across many network topologies, including intermittently disconnected scenarios. Many devices sit behind double Network Address Translation (NAT) topologies and cannot accept remote connections, requiring a gateway or a secure tunneling agent that runs on the device.
Finally, you need to guarantee that such an agent mechanism running on the device is lightweight and can self-update with a high degree of trust.
Real-time device monitoring It’s challenging to see the big picture across many data points when monitoring devices and also still identify issues with individual devices. The “big picture” view can be achieved by applying metrics on groups of devices, and aggregating it with metadata tags assigned to devices (or device groups).
Identifying issues with an individual device can be solved by adding “smartness” in the device agent, which can be updated dynamically. The agent applies rules assigned to it in runtime, for example, and could securely block untrusted behavior.
Another challenge is the ability to monitor devices with limited connectivity. This is often solved by aggregating data on the device and streaming it to a monitoring server when the device regains connectivity. But this can also be problematic, considering that many monitoring services don’t handle historical events well, particularly when you want issues to be visible as early as possible. A gateway service that is deployed in proximity to devices and acts as a monitoring proxy can help solve this problem.
Easy software updates Like any production deployment, the best practice of deploying to smaller groups of devices first applies. This can often be achieved with metadata attached to devices.
Then, due to the sensitivity and potential risks in an upgrade, you need to guarantee that two things can be achieved through the agent software of the device. First, the update time needs to reflect minimal disruption to device service.
Second, the ability to roll back bad or failed updates is critical, especially for devices at a mass scale that cannot be manually rolled back, or devices that cannot be physically reached to “reset” a bad state. This makes auto-recovery of bad updates a must. Remote access to devices may help here, but again, it may not be applicable to reset a large set of devices.
Of course, the core of the device agent needs to be rock-solid yet minimal so the update agent itself stays up and auto-recovers from self-updates.
Remote access and control Remote access provides great troubleshooting and debugging capabilities when looking to identify issues on individual devices. Most often, problems arise across more than a single device as a result of either external changes or a version update. If monitoring data fails to provide details that are relevant and in context, a developer needs access to a troubled device and check the problem on the device itself.
When you need remote access, this solution is indispensable, especially for otherwise inaccessible devices. Making remote access secure is important, as is making it easy for developers to use, such as establishing connections through a web browser.
Across this entire workflow, automation is key. It requires you to create a fully automated software supply chain process to update your devices and apply runtime monitoring and security checks. This process can often be a natural extension to the existing software supply chain process — one that already exists for building and distributing your device software.
Doing more with smaller, nimbler teams Keeping everything connected and maintaining fully automated processes allows you to achieve wonders with a small and nimble team, even for a large and complicated set of devices. Similar to enterprise “Super DevOps” groups that serve tens of thousands of developers with only a small team, trusted automation processes enable organizations to achieve the same for large, diverse fleets of devices.
All of this ultimately gives you traceability and visibility to all software running on your devices. For example, you can identify a security vulnerability on a device, block it in runtime using agent rules, and also quickly identify the software build that created the device software (and, potentially, other builds impacted by the same vulnerability).
You can then automatically build and release a new version that patches the security hole and distributes it automatically to regional update centers. From there you can roll out a gradual update to selected groups of devices to verify the fix.
Conclusion In the end, the goal is for these four elements — device management, real-time monitoring, efficient software updates and remote access — to work together. Doing so effectively while embracing automation keeps developer teams nimble and end-users and customers happy, creating a win-win situation for team morale and overall business objectives.
Yoav Landman is cofounder and CTO at JFrog.
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"Sky Mavis brings 4 new blockchain games to its Ronin network | VentureBeat"
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"https://venturebeat.com/games/sky-mavis-brings-4-new-blockchain-games-to-its-ronin-network"
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"Game Development View All Programming OS and Hosting Platforms Metaverse View All Virtual Environments and Technologies VR Headsets and Gadgets Virtual Reality Games Gaming Hardware View All Chipsets & Processing Units Headsets & Controllers Gaming PCs and Displays Consoles Gaming Business View All Game Publishing Game Monetization Mergers and Acquisitions Games Releases and Special Events Gaming Workplace Latest Games & Reviews View All PC/Console Games Mobile Games Gaming Events Game Culture Sky Mavis brings 4 new blockchain games to its Ronin network Share on Facebook Share on X Share on LinkedIn Ronin is powering four new games.
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Sky Mavis has generated more than $1.3 billion in revenue from its blockchain game Axie Infinity. And now it is preparing to launch four new Web3 games on its Ronin network.
The company said it has upgraded the Ronin blockchain to Delegated Proof of Stake (DPoS), providing better security and efficiency in its quest to decentralize Ronin. Ronin is an Ethereum virtual machine (EVM) blockchain with trading volume of $4.2 billion.
And Sky Mavis, based in Singapore and Vietnam, has unveiled the genesis batch of game studios that will be building and launching games on Ronin: Directive Games, Tribes, Bali Games, and Bowled.io.
At the Game Developers Conference, I met with the leaders of Sky Mavis, including Kathleen Osgood, director of business development at Sky Mavis; Aleksander Leonard Larsen, cofounder and COO; Jeffrey Zirlin, cofounder and head of growth; and Trung Nguyen, CEO and cofounder.
Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! Larsen said that the Ronin network has always been a part of Sky Mavis’ strategy to make sure it can provide the best service to the Axie Infinity community. And now the next step is opening it up to other developers so they can share in the benefits.
“We spent a long time looking for these five games, which are a good fit for our holistic strategy,” Larsen said in our interview.
Larsen said that Sky Mavis is making direct equity investments into some of the companies for a long-term play. And he noted that he met one of the developers at our GamesBeat Summit Next event last October.
Delegated Proof of Stake As for the delegated proof of stake, the original blockchains like Bitcoin consume a lot of energy, requiring lots of computing resources to independently verify what is stored on the digital ledger of the blockchain. This made the networks secure but extremely wasteful.
With proof of stake, a blockchain network can incentivize users to confirm network data and ensure security through a process of collateral staking. With delegated proof of stake, users of the network vote and elect delegates to validate the next block in a process that is more democratic.
With the DPoS upgrade, anyone with a minimum of 250,000 RON (the token for the Ronin network) can become a validator and take part in block production. That is, it can be a partner that validates transactions on the blockchain. And the energy used is far less than with early blockchain protocols.
“We have had some challenges with the chain, but getting to this point is really great. How we run the network is starting to become more decentralized,” said Larsen, in an interview with GamesBeat. “The purpose of staking is basically that the community can now show support to their favorite validator and, at the same time, help secure the network. So it’s becoming more decentralized and we’re also opening it up.” >>Follow VentureBeat’s ongoing GDC 2023 coverage<< At the same time, any RON holder can stake their tokens and participate in validator selection. The selected validators then share a part of their rewards with the delegators—the users who staked their tokens. RON staking opens today, with rewards starting on April 12.
Overall, security is still extremely important. Last year, when an engineer failed to close a workaround that circumvented blockchain security, the Ronin network got hacked and thieves stole $620 million from Sky Mavis and its users. The company had to raise new funding and guarantee funds for users.
“The Ronin hack itself, obviously, is a painful moment in our history. But I also think it’s a valuable experience for us. We made so many trade-offs to actually be able to go to the market with Axie that, at the end of the day, it came back to bite us,” Larsen said. “Since that time, not only did we refund all the users from our own balance sheet, so everyone was made home — but we are also moving into a much more secure environment. Even if someone gets compromised, that still wouldn’t lead to the same level of disaster that it did before.” He also said the industry is young and such incidents are likely to happen to many chains, and they have been happening.
“I really think that having that experience and being battle tested and surviving that, for us, should be a benefit to any other developer that is working with us. They know that we are taking this pretty seriously because we can survive this,” he said. “That’s why we’re focusing so much on basic security. I’m very proud of how we handled that situation and actually are recovering from it.” Down from the peak Axie Infinity took off like a rocket and came down like one too.
Axie Infinity has about 200,000 daily active users, down from a peak of around 2.7 million during the height of the NFT craze in 2021. In the midst of the pandemic, in communities in the Philippines with 40% unemployment, Axie Infinity took off, helping people make three times the minimum wage in a month. It created a lot of jobs for people and kept spreading. About 20% of the players were unbanked. Then it crashed, as the cost for creating new players rose and players had a hard time sustaining the gameplay. Eventually, there weren’t enough new players to replace the departing ones, and the prices fell for NFTs.
But Larsen notes that the game is resilient, as are the players, who have lived through multiple massive corrections over the years.
“As we are building and building and building the audience, the expectation goes up to the peak where there are 2.7 million people who expect the game should be totally amazing. And then the reality kicks in, and it goes back down again,” Larsen said. “What I would say is that the difference between the quality of the Axie product versus the expectation for the players is actually better. So I would say that we’re pretty suited for another upswing, but that also historically that upswing is dependent on not only what we do, but also the general market. So when we look at crypto as a whole, what keeps happening is that it also follows the cyclical trends, where people think that this is going to change the world. For us, we go back to the original vision of how we create more utility for the Axies.” Players that churn out of the game are the ones that expect a short-term financial gain from selling off their characters. But other players are long-term missionaries who love the game and the community, Zirlin said.
“They love true ownership of their assets. That’s definitely one of the core benefits, but they’re in it for a lot of the benefit and utility outside of just short-term financial speculation,” Zirlin said. “It’s a battle for attention. A battle for community members. And a battle for developers. And it has a cyclical element.” Now that prices are down for Axies, Zirlin said, “We’re starting to see many of the community members that were around in 2018, and 2019, becoming mentors, and really consoling and teaching the other community members that we’ve been through this before, as an industry as a community.” Onward from Axie Infinity Sky Mavis created a genre-defining game in Axie Infinity, which set off a craze around non-fungible tokens (NFTs) in 2021. It had to build the infrastructure that enabled it to scale to millions of users, and that infrastructure became Ronin. To date, more than four million people have downloaded Ronin wallets for trading cryptocurrency.
Now, the company is rolling out its technology to create a gaming ecosystem built on Ronin that shares a big user base, community-owned protocols, applications, and deep asset liquidity. Selected partner studios have the opportunity to access Axie intellectual property for their titles or build entirely new games with distinct IPs on top of Ronin.
Osgood said that over the last year, Sky Mavis has been vetting hundreds of game studios to find the best partners to bring into the ecosystem.
“It’s also noteworthy that we’ve been setting up our operating platform to really structure how we partner with these teams on a deep level, which I think differentiates us from some of the other ecosystems out there,” Osgood said. “We want to leverage everything that we’ve created for Axie Infinity. We want our game studios to leverage that.” The company has set up its Mavis Hub, which is a distribution center for other games. It’s kind of like the Steam of Web3. Sky Mavis also has its Ronin bridge to other networks, which was built to scale Axie Infinity. The company has a department set up to work with game studios on leveraging Sky Mavis’ tools. And it has its publishing division to work with developers on their marketing and community engagement plans.
Sky Mavis has about 2,500 creators, all dying for more games on Ronin to create content and get the word out, Osgood said.
“We have a ton of social capital across all of our accounts. And what we’ll really be doing is helping get these games distributed to a broad audience in Web3,” Osgood said. “So when we’ve been looking at the games that we want to onboard, we have been taking a more strategic approach. We can generate Web3 users by leveraging our assets and building community.” Zirlin added, “One of the things that we’re starting to see is that Ronin has a community, a growth stack and all the tools and platforms that you would need to be able to grow your game to interact with the community.” The new games Last year, when Sky Mavis added new Axie Infinity games, the company had more than 1,000 applications and it picked about 15 teams to make games. Much of the content was fan-generated games.
But now the first game studios to build on Ronin include: Directive Games — A gaming studio founded in 2014 by veteran game developers from companies such as CCP Games, DICE, LucasArts, Square Enix, Ubisoft, and Tencent. Directive Games aims to create large, immersive, competitive multiplayer games that prioritize player agency. To achieve this, Directive Games has developed a powerful tech stack that includes a proprietary backend for developing large persisted worlds, a generative AI-tool chain, and proceduralism.
Today Directive Games is officially announcing the closed beta launch of The Machines Arena on the Epic Games Store to Ronin users. Web3 features will be rolled out in the coming months. In this fast-paced hero shooter, players clash in intense battles delivered from a top-down perspective. Directive’s technologically advanced gameplay will offer the Axie community access to a new, exciting universe of play.
“This is interesting because it’ll start off in the Epic Games Store so players will be able to engage with it immediately at the start,” Osgood said.
At first, the game won’t have Web3 elements. But Sky Mavis will with the devs and the community members and the players to determine the best places to put these Web3 elements into the game, she said.
“We’re going to start off with that Web2 approach and then gradually bringing in Web3 elements,” Osgood said.
Admittedly, that’s a roundabout way to bring out a blockchain game, but it’s a way to stay friendly with the app stores, which often block most Web3 features from being deployed in a game on the official app stores. But it’s a necessary step on the way to reaching a mass audience.
Tribes Studio — Created by a former executive at King and Scopely, who oversaw player experience and community at titles such as Candy Crush Saga, Walking Dead, and Star Trek. Tribes Studio will launch community-led gaming, building titles on their IP Tribesters.
Their main experience will be Tribesters: Island of Solas, an open-world MMO. Prior to launching the MMO, Tribes will launch a community engagement platform that enables the community to help build their games and be rewarded for it. This tech will be available as a mechanism to build community in a structured way to other games within the Ronin ecosystem. Tribes Studio shares Axie Infinity’s community-led approach and will enable gaming experiences for the community.
The dev team is building a social MMO and a community engagement platform that allows the community to participate in areas of game decisions, Osgood said.
“It’s leveraging the community’s unique skills and expertise to help build the game and also be rewarded for it. So the community will be able to participate in ways such as helping build the lore behind an NPC or determining the art style for one of the parks,” Osgood said.
Larsen added, “We’re actually they’re actually building a system so that we can now actually try to tap into that wisdom in the community.” Bali Games — Built by makers of the Korean smash-hit Anipang series, which achieved $1.8 billion gross revenue and over 130 million downloads, Bali Games is leveraging its extensive mobile game experience to create Axie-inspired puzzle games. Bali Games has a track record in expanding major IP including Disney Pop, Snoopy Puzzle and BT21. This collaboration will grow the community in Korea through the expansion of Axie IP and lore through Axie games.
“I’m very excited about working with them. It’s a studio that’s a spin-off of the guys behind the a big card game. They’re highly focused on making mobile games,” said Larsen. “They’re doing two things. They are giving more utility to the Axie game characters and they will create their own native IP. Our strategy is very curated for now. We want to show them as we go to market with community building so that they don’t have to make the same mistakes that we’ve made.” Osgood added, “This is a mechanism to also expand the Axie lore. So internally, we are expanding the Axie lore to allow other studios to build with our guidelines and build this new game.” Bowled.io — This company runs a sports-based social gaming platform that enables fans to discover and play games, own in-game sports assets, and interact with their favorite sports influencers. Beginning with one of the most popular sports in the world, cricket, Bowled.io allows participants to face off against players worldwide, cultivating their team of all-star cricket heroes and leading them to glory in a suite of engaging game modes.
The game is not a Web3 game at the outset, but the team is adding Web3 elements by working with Sky Mavis.
“It goes back to this approach of bringing users into the ecosystem and then start to reward them and incentivize them to set up a Web3 wallet and earn the rewards and then possibly buy in-app purchases to earn NFTs to further their game,” Osgood said.
Eventually, other popular sports like basketball and soccer will also be integrated. The Bowled.io partnership will enable Sky Mavis to tap into a new highly engaged community of India-based sports fans and onboard a different demographic within an emerging market into the Ronin ecosystem.
“India is an emerging market that we want to tap into,” Osgood said. “They have one of the youngest populations and they are open and exploring gaming. We think that although this is a unique play. Cricket is actually the second-largest sport in the entire world. But India is a market that we haven’t necessarily tapped into in a meaningful capacity.” Larsen said he hopes the dev team can create a full sports game hub over time.
A long road ahead “Sky Mavis’ is building on the success of Axie Infinity to create an infinite ecosystem that introduces the benefits of Web3 through immersive gaming experiences,” said Nguyen, CEO of Sky Mavis. “With the upgrade to DPoS, we are ready to open up our infrastructure and technology to the wider Web3 world. We believe that this is the path towards creating gaming that’s community-centric, more rewarding, and above all, more fun. I’m excited to welcome Directive Games, Bali Games, Tribes, and Bowled.io to Ronin.” As for working with big game studios, Nguyen said that there are companies with existing intellectual property and Web2 games that are thinking about how to expand and build on top of the Ronin network.
“We have been discussing that with them, and they’re looking into their options.” And as for Sky Mavis’ own first-party games, Zirlin said the company has been thinking a lot about the core experience of feeding and raising a Tamagotchi-like character, which was foundational to the idea when the company came up with its NFT-based game in the first place more than five years ago.
“It’s not just about one next big game that will get us to the next step as an ecosystem,” he said. “I think it’s about how do we have an interconnected ecosystem where you’re using your assets in different experiences, and then storing that experience in progression through your NFT assets.” Zirlin believes that, over time, we will all become attached to our digital collectibles, our NFTs. And while some may never hold value, we’ll still have an emotional attachment to them and a story to tell about how we acquired them. Eventually, he thinks that will be a massive audience.
“I think Mario would never have penetrated as many households if there wasn’t Donkey Kong, Zelda, or other IPs in the Nintendo universe. Mario would never have penetrated the cultural consciousness of the entire world,” Larsen said. “The difference for us is we feel like the community is with us on this journey. Like the community, we own the assets.” GamesBeat's creed when covering the game industry is "where passion meets business." What does this mean? We want to tell you how the news matters to you -- not just as a decision-maker at a game studio, but also as a fan of games. Whether you read our articles, listen to our podcasts, or watch our videos, GamesBeat will help you learn about the industry and enjoy engaging with it.
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"Skillprint launches science-backed platform to match players with the right skill-based games | VentureBeat"
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"https://venturebeat.com/games/skillprint-launches-science-backed-platform-to-match-players-with-the-right-skill-based-games"
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"Game Development View All Programming OS and Hosting Platforms Metaverse View All Virtual Environments and Technologies VR Headsets and Gadgets Virtual Reality Games Gaming Hardware View All Chipsets & Processing Units Headsets & Controllers Gaming PCs and Displays Consoles Gaming Business View All Game Publishing Game Monetization Mergers and Acquisitions Games Releases and Special Events Gaming Workplace Latest Games & Reviews View All PC/Console Games Mobile Games Gaming Events Game Culture Skillprint launches science-backed platform to match players with the right skill-based games Share on Facebook Share on X Share on LinkedIn Some of Skillprint's app screens.
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Skillprint has launched a platform that uses science to figure out how to match players with the games they will likely enjoy and the skills they want to improve.
The new ratings for games are based on a first-of-its-kind pairing of neuroscience research and machine learning. Skillprint’s ratings consider a number of criteria, evaluating games for their effect on a person’s mind and mood – with the ultimate goal being to match individuals with the best games for their personalities, specific moods and the skills they want to test or improve.
The San Francisco Bay area based start-up was founded in 2019 by seasoned gaming industry veterans Chethan Ramachandran and Davin Miyoshi. They wanted to see games used for a greater purpose and help people feel better through gameplay.
“I want to be the ultimate scoring engine for how you play,” Ramachandran said.
Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! But there’s a lot more behind it than just measuring yourself.
The founders bring a unique vision and expertise to the opportunity. Ramachandran previously founded Playnomics, a predictive analytics company which was sold to Unity in 2014 and now processes 1.5 billion devices each month as Unity Analytics.
Miyoshi founded Mesmo, a social/mobile games company that was sold to GSN, and cofounded GSN Games, which grew to more than 75 million users and $100 million in revenue.
Now, Ramachandran and Miyoshi are turning their talents to exploring the intersection between gaming and cognitive science. Skillprint uses powerful machine learning technology and builds on years of cognitive science research to study how people play games and glean unique insights into an individual’s personality traits, skills and mindset.
The platform now offers unique game ratings, analyzing 135 separate game characteristics to rate and vet games for skills assessment and mood, matching users with personalized game recommendations.
Skillprint offers these ratings through its own platform at skillprint.co, as well as rates and ranks existing third-party mobile games. The company is planning to scale its consumer facing offering to game players and work with game developers to help them find the right players for their games.
“Mobile gaming can sometimes get a bad rap, but people often ignore the many and varied benefits of gaming,” Ramachandran said. “For years, scientists have used games as a way to test people’s cognitive abilities and learn more about how the mind works; there are numerous studies that show the clinical benefits of using games to reduce stress amongst military personnel.” He added, “It’s very hard to understand how your own mind works – people spend their whole lives trying to figure this out. Who doesn’t want to know more about who they are and feel better? Our hypothesis is that games can do both. We’re blending best in class AI with cognitive science best practices, and building a personalized path for each one of our users to help them leverage games to learn more about themselves, and shift their moods.” To date, Skillprint has raised $3.5 million in a previously unannounced pre-seed funding from some of the leading investors at the intersection of games, cognitive science, and human potential.
Investors include Shanda Ventures, LearnStart, Niremia Collective, and a number of private individuals with decades of experience and significant clout in the gaming world, including David Helgason (founder of Unity) and Steve Arnold (founder of LucasArts Games, co-founder of Polaris Ventures, Vice-Chair of the George Lucas Educational Foundation). Shanda Ventures got interested because of its focus on neuroscience.
With a fast-growing monthly user base and more than 40 curated games already available on its platform, the company captures and analyzes an average of 1,200 events per active user to predict their personality traits and skills.
There could be privacy concerns, but Skillprint asks users to opt-in to sharing data at the very start. The data is anonymized and aggregated, and each user owns their own data associated with their own login. You wouldn’t want game companies to nefariously target people on the basis of addictive personalities.
“We have to be smart about our mission,” Ramachandran said. “This whole venture is not to help game companies as much as to help people first and foremost be the best version of themselves. You have to frame it in the right way and hopefully the data flows from there in the right frame.” Doing basic research Ramachandran and Miyoshi have been at this for a while. They started the company in 2019. Their initial thesis was that games can tell you about the mind and help people develop and identify their mental skills.
“That’s basically what we built,” Ramachandran said.
The company licensed more than 40 games that were off-the-shelf mobile games, which were basic mastery games like match-3 games or bubble shooters that everyone from kids to older adults can play. The team did research on neuroscience and tried to isolate different effects on the mind as you play.
We all have basic cognitive skills like attention, focus, ability to plan and execute, to switch tasks, and things like that, Ramachandran said.
“If you talk to psychologists, they talk a lot about five factors for your personality traits: how open you are to new experiences, how conscientious you are, how extroverted, how agreeable or how neurotic in different ways,” he said.
Serious research Six members of the team — all with doctorates — have been working on the research. And that enabled the company to raise its stealth funding round.
And the team built a progressive web app that you can access through any mobile browser. And people play the games on the app to build their “skillprint,” or a pattern record of a player’s skills.
“I think it’s going to be an interesting way to start routing people to find new games,” said Ramachandran. “With the app tracking stuff, it’s really hard to find players now.” But with this added layer of information, Skillprint can think about how to recommend games to you based on your personality traits.
“It turns out that people who are higher on the neurotic scale love word games, for example,” he said. “And we have all this interesting data.” The company will roll out its own studies, some done in collaboration with academics.
“I know two things to be true. People love playing games, and people are kind of obsessed with themselves,” Ramachandran said. “The skill part is just showing you a little bit about yourself.” Interesting findings The psychologists, like Skillprint adviser Rick Robbins of the University of California at Davis, use that create a model about your mood and emotional states.
“What we found was everybody is working on using games in the world of neuroscience, cognitive science, and psychology. And so there is a ton of research that people were doing. And so we basically built our own little machine learning and research lab using these games,” Ramachandran said. “We have people playing Skillprint games, almost like in some cases, as a replacement for the cognitive headspace. They play it to relax, to focus, to get more creative, to be more collaborative. So shifting your mood every day and your mindset as you play would give you more of a map of your mind in terms of your personality traits and your cognitive skills.” Over time, you start to enhance that. If you want to improve your attention or focus, then maybe you can become a pilot at some point in the future. Ramachandran said they found that people who are open to new experiences love role-playing games. People who are less open-minded may like sports games. People who are conscientious like racing games. These are generalizations, but they’re backed by data.
“Part of this has been through real scientific rigor. And part of it has come from seeing what happens to the gameplay data,” he said. “We tie that to outcomes that have to do with your career and your purpose in life.” Action games have a real interesting effect on all skills, Ramachandran said.
“It’s interesting how serious some of our advisers and researchers are, but they’re taking these games very seriously,” he said.
Pivoting Rather than use the data to figure out their career path, people wanted to use the games in a different way. They wanted to use games to feel better every day, Ramachandran said.
“Everybody has a mood and mindset that changes like the weather,” he said. “If we can help them, that is pretty interesting. You can play a game, and now you feel more creative.” Over time, as the products get deeper, the company could eventually figure out things like whether you have the skills of a graphic designer or a landscape architect, based on the skills you have and the games you like. Over time, then, Skillprint might be used to show people a career path.
“You can help them understand how their mind works, and what makes them unique, and then ultimately, figure out what your purpose is to apply all the stuff in real life,” Ramachandran said.
The ambition isn’t so much for the company to have its own app. Its purpose is to be a kind of router, taking someone who wants to play a game for a certain reason around mental wellness, and then routing that person to a game company that wants that player. It’s a tech that could be embedded in games.
Skillprint has collected panels of people who are playing a game and don’t mind sharing their details about career and whatnot. And it helps them build a baseline for what that kind of person likes to play and what kind of skills they have. Then the company uses machine learning to connect it all together.
If someone else is just like you, then you might do well in the type of career that the other person has pursued. Skillprint can surface these correlations with enough good data. Of course, it has to take a long time to get the analyses and correlations correct, and the company doesn’t want to be wrong.
“We can make a recommendation. I think it will be really fun as we start to get more public about this and get a bunch of sports stars to do it,” he said. “We could see how you match up against LeBron James or whoever. That’s coming next.” At this point, the company has a smart personalized platform that helps people find relaxing games to play. And at the moment, the main purpose of the company’s app is to gather the data to train the AI system to rate and plug in other games.
“As such, the games we have are well-known casual game types like match 3 or bubble shooters that allowed us to train the models and start to isolate and show results. As you play more, the Skillprint tab starts to fill with results around mood, personality, and skills,” Ramachandran said. “It just turns out the games are the ultimate testbed for understanding other extremes, like those that make you calm or tense.” An example of what Skillprint can learn Ramachandran said that one example is that when someone plays one of these games that have “merge” mechanics, where you merge two elements together, the boost in creativity is off the charts.
“It’s like a magnitude four or five times better than anything you have in psychology,” he said. “Some people may react really well to a timer and get more focused. Some people might feel they don’t want this and it freaks them out.” To figure this out for each person, the data has to be personalized and Skillprint has to get a layer of data that applies to you. Over time, the company will move to measuring more complex games and coming up with a better map of the mind.
“We’re starting to see bundles and mechanics and it’s fascinating,” he said. “You have a mix of relaxation and focus in the same game session. We’re going to get better at personalizing over time. We can see if this is what will help you feel better every day. If this is going to help you understand your own mind. We’re kind of the ones putting it altogether, and we have more data than most studies.” There are some games that would be good at capturing personality. Reigns, which is set in the Game of Thrones universe, is an example. You make choices in the game and swipe left or right. Those choices can help decipher your personality. If you reimagine that game as an actual personality test, it would probably work pretty well and amass a lot of data.
Games are good If the company expands in the future, it might look at PC games on Steam, as it provides a lot of structured data on game usage.
“Overall, I want to do all of games,” he said.
You could try to create games to train your brain better. But Ramachandran notes that people are already playing games, and the key is to isolate the effects that those games have on the players.
“You figure out what people are getting out of it and give them more of what they want,” he said.
One interesting finding is that a survey of women from 32 to 55 found that they would love to meditate every day but don’t have the time. But they do have time for games, and they get a unique mix of focus and relaxation from playing those games.
“What I think is really interesting, as people are playing games for these reasons of stress relief, or relaxation, or more focus, or more creativity, they just haven’t framed it like that,” he said. “And they generally feel a little guilty that they’re doing it. We think we can kind of change that narrative because you know I fundamentally believe that gameplay is good for you.” Another eventual use might be to create a dating app, particularly for gamers, but ultimately for everybody. At this point, the company doesn’t have any plan to get Food and Drug Administration approval for any therapies that might come from the data.
“I think the player routing and helping people understand what their minds are like is more than enough for now,” he said.
One of the most interesting conclusions is already clear for Skillprint.
“It’s clear that games are going to be the future of mental strength and mental wellness,” Ramachandran said.
GamesBeat's creed when covering the game industry is "where passion meets business." What does this mean? We want to tell you how the news matters to you -- not just as a decision-maker at a game studio, but also as a fan of games. Whether you read our articles, listen to our podcasts, or watch our videos, GamesBeat will help you learn about the industry and enjoy engaging with it.
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"How better use of data can improve compliance programs | VentureBeat"
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"https://venturebeat.com/enterprise-analytics/how-better-use-of-data-can-improve-compliance-programs"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest How better use of data can improve compliance programs Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Leading organizations that treat compliance as more than a checkbox exercise use data to uncover not just the numbers, but why certain trends are occurring and how they might impact the business.
While healthy compliance programs thrive on consistency, they also need to be agile enough to evolve alongside ever-changing policies and regulations. Effective use of data is the key to this agility and is at the heart of all successful compliance programs.
Compliance is an essential function that must be integrated enterprise-wide — from managing external regulations and internal policies to creating thorough employee training. The right data can help leaders gauge the state of their organization’s culture — a powerful indicator of corporate integrity.
As an example of the power of compliance data, an increase in incidents reported could indicate a positive shift in corporate culture, with employees feeling more empowered to speak up about workplace questions or issues. However, it could also indicate an emerging risk within the organization that needs to be addressed.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Correlating this with other key data points, such as region or site-specific reporting volumes, can help identify key drivers. Understanding these critical root causes is essential to compliance not just because it mitigates risk, but it helps organizations evolve and become stronger. Yet, to reach this level of analysis, data insights must be fully discoverable.
Uncovering deeper insights Using technology to aggregate data and unearth insights isn’t new. Countless industries have matured their use of data to uncover deeper business intelligence for competitive advantage.
For instance, in the early 2000s, Walmart perfected the science of using data to optimize product assortment, leveraging historic and predictive customer demand models to ensure the right product was in the right place on the store shelves at the right time, maximizing profits in the process. And Major League Baseball used comprehensive data to create the “Baseball Encyclopedia,” a compendium of researched statistics that replaces intuition with empirical data analysis so that winning teams could be built with modest budgets.
We’re now seeing a similar wave of change in compliance , with organizations digging deeper into data so compliance officers can rely less on their own intuition and more on the factual insights and trends they see firsthand. Especially today, amid increasing and ongoing company data breaches, long-awaited ESG standards and regulations and mass employee resignations, it’s more important than ever to ensure that organizations use data to take a proactive approach to compliance.
Here’s how organizations can successfully leverage compliance data.
Compile and compare data sources to create a strong data foundation When it comes to compliance, the more data the better. This means that compiling and comparing data from across sources is the best way to correlate data points to uncover important trends and predict potential risk.
For example, an increase in internal reports that come in via the organization’s various reporting systems — phone hotlines, online portals, or directly to managers — may appear to signal poor compliance and organizational issues. While more reports may seem to suggest that more problems exist, an increase in reporting data is a good thing, and essential to evolving compliance programs.
In fact, organizations that receive more reporting data from their employees perform better in almost every measure. They are more profitable, have better governance structures and have healthier workplace environments. This is largely because more reporting data gives the organization a fuller view of its compliance programs and culture.
Embrace digital transformation Gathering, monitoring and assessing data is a strong catalyst for digital transformation. It can move organizations beyond antiquated processes where spreadsheets, or even notepads, were used for policy management, compliance tracking, reporting and more. This level of digitization helps organizations effectively scale and mature, removing business silos.
Moreover, digital transformation can grow automation that enhances productivity, removes human error and allows professionals to focus more on high-value aspects of their jobs versus manually entering and analyzing data figures.
View compliance holistically There aren’t many roles that truly think about business compliance from end to end, and that’s a problem. Transforming how data is used can break down data silos that naturally build up over time.
For instance, compliance professionals typically only look at data that falls under the compliance umbrella and sometimes don’t consider how other factors within the business — such as HR or even IT data — can impact their program. When data becomes available across business units, organizations can draw correlations between teams and answer critical questions about the state of their business.
Uncover program gaps and successes Enhanced and consolidated data provide a real-time snapshot of how effective and mature a compliance program is. Further, they reveal micro-trends that can contribute to macro-level change. Having a more comprehensive grasp of both micro- and macro-level trends is what moves the needle for enhanced compliance programs and proactive risk management.
Similar to how insurance companies rely on actuaries to determine risk for liability, organizations can use their compliance data to fuel effective decision-making and proactive risk management. Understanding risk signals, such as incident reporting volume, is a significant factor in closing compliance gaps and building a successful program. The output of this exercise is a program that abides by laws and regulations, creates a safe and ethical work environment, protects the business against internal and external risk, and much more.
Compliance is transforming with the help of data and the ability to discover risk signals and causal mechanisms. Those at the cutting edge of this movement are implementing more robust data protocols in compliance, allowing them to more easily contextualize and grow confidence in their business decisions.
While data has always been essential to compliance, leaders that go beyond treating it as a checkbox exercise and dig deeper are maturing their compliance programs and helping build ethical corporate cultures that, in turn, grow business success.
Bob McCarter is chief product and technology officer at NAVEX Global.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"MariaDB debuts new SkySQL features to help teams manage cloud costs | VentureBeat"
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"https://venturebeat.com/data-infrastructure/mariadb-new-skysql-features-to-help-manage-cloud-costs"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages MariaDB debuts new SkySQL features to help teams manage cloud costs Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Open source database company MariaDB plc today announced an update for SkySQL, its fully-managed cloud database service. Generally available on AWS and Google Cloud, the release comes a few months after the company’s public listing and brings two innovations to help teams better manage their cloud spend: autoscaling and serverless analytics.
MariaDB was created in 2009 as a software fork of Oracle-backed MySQL. The SQL-based relational database management system (RDBMS) started by offering high compatibility with MySQL, functioning as a drop-in replacement for the database in many cases. Currently, the open-source database (MariaDB Server) is maintained and offered by MariaDB plc, along with a commercial cloud database service called SkySQL.
SkySQL is fully managed, and enables teams to deploy and manage key MariaDB products — MariaDB Enterprise Server, the Xpand distributed SQL database, ColumnStore — in the cloud with just a few clicks.
Autoscaling and serverless analytics for MariaDB SkySQL With the latest release, MariaDB says SkySQL gains the ability to autoscale both compute and storage in response to changes in demand.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! For instance, when CPU utilization tops 75% for all replicas for 30 minutes, a new replica or node will automatically be added to handle the increase. Similarly, when CPU utilization is less than 50% over all replicas for an hour, node counts will scale down. All a user has to do is define the top and bottom tiers that trigger autoscaling, and the system will handle the rest, ensuring there are no cost surprises.
“With other clouds, costs tend to only go one way, up,” said Jags Ramnarayan, SVP and SkySQL general manager at MariaDB plc. “With SkySQL, we also let you shrink the cost footprint automatically when demand is low.” Along with autoscaling, the company is adding to SkySQL a serverless analytics layer powered by Apache Spark SQL. The move, MariaDB says, will enable companies to perform operational analytics on active transactional data as well as on external data sources, without requiring ETL. This will remove any inconsistencies between an analytical view and a transactional view.
Plus, when not conducting analytics, the service can be spun down to zero — further saving money.
John Hundley, principal software engineer at Hughes Network Systems, who got early access to the latest SkySQL release, commended the update’s user interface and autoscaling functions.
“Our IoT smart power plugs are distributed nationally across hundreds of locations, collecting data from various plugs at any given time,” he noted. “The number of locations and data rates can vary significantly. The [MariaDB SkySQL] user interface is very easy to use and will give us a better view of our database usage. We also expect autoscaling to help us in responding to our workload changes to ensure we have the right resources allocated.” MariaDB counts organizations such as Bandwidth, DigiCert, InfoArmor, Oppenheimer, Samsung, SelectQuote and SpendHQ among its customers and competes with Microsoft SQL Server , IBM Db2 and PostgreSQL as well as the above-mentioned MySQL RDBMS.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"WaveFront Dynamics Inc. Launches WaveDȳn® Vision Analyzer | VentureBeat"
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"https://venturebeat.com/business/wavefront-dynamics-inc-launches-wavedyn-vision-analyzer"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Press Release WaveFront Dynamics Inc. Launches WaveDȳn® Vision Analyzer Share on Facebook Share on X Share on LinkedIn New dynamic aberrometer now available Video capture of the dynamic optical system enables highly accurate objective refractions.
1 Subjective confirmation of objective refraction.
Ultra-high-resolution Shack-Hartmann wavefront sensor creates high-definition wavefront images.
2 ALBUQUERQUE, N.M.–(BUSINESS WIRE)–March 30, 2023– WaveFront Dynamics Inc.
, an ophthalmic medical device company, announced today the commercial launch of its dynamic aberrometry measurement system, the WaveDyn Vision Analyzer. The WaveDyn Vision Analyzer (pronounced WaveD”eye”n) captures a video of the eye’s dynamic optical system over time (rather than just producing a single measurement). The WaveDyn Analyzer’s high resolution, dynamic measurement capabilities provide highly accurate objective refractions as well as ocular surface quality and accommodative function analysis. The system provides 9 ocular measurements to streamline workflow.
This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20230330005171/en/ WaveFront Dynamics Inc. Launches WaveDȳn® Vision Analyzer; New dynamic aberrometer now available. (Photo: Business Wire Dynamic wavefront aberrometry Objective refraction Dynamic corneal topography Corneal surface irregularity Keratometry Dynamic iris image Pupil dynamics Subjective refraction confirmation Accommodation range measurement At the core of Wavefront Dynamics’ continued innovation is the Shack-Hartmann wavefront sensor, a technology that has long been used in astronomy to improve the image quality of telescopes. Wavefront Dynamic’s founder and CEO, Dan Neal, Ph.D., developed a wide variety of applications for wavefront sensors, including measurement of aero-optic phenomena, the large telescope mirrors used in the James Webb Space Telescope, and silicon wafer metrology. For nearly 30 years, the team has made advancements in wavefront technology to measure and correct imperfections of the human eye, to improve visual performance.
“The WaveDyn Vision Analyzer represents our continued commitment to innovation and advancement in wavefront technology,” said Dr. Neal. “The Analyzer will serve as a platform to create personalized ophthalmic treatment solutions for patients through our strategic industry partnerships.” “The WaveDyn Vison Analyzer has increased my understanding of the optics of the eye and of what is possible,” said Christine Sindt, OD, FAAO Clinical Professor of Ophthalmology and Visual Sciences at University of Iowa Health Care. “I now incorporate aberration measurement into all aspects of patient care. I start all my refractions using data from the WaveDyn System. This system has allowed me to get functional glasses for aberrated eyes.” About WaveFront Dynamics Inc.
Founded in 2019, WaveFront Dynamics is a privately held, commercial-stage medical device company with innovative wavefront diagnostic technology for use in the vision care industry. The company plans to leverage dynamic measurements to yield new insights into assessing visual performance, advancing treatment options, and improving quality of life for the visually impaired. For more information, please visit www.wavefrontdynamics.com.
Neal et al. “Dynamic aberrometer/topographer designed for clinical measurement and treatment of highly aberrated eyes,” Optical Engineering, December 2022, Vol. 61(12) Neal et al, “Restoration of normal optical quality with wavefront guided scleral lenses,” Global Specialty Lens Symposium 2023, Las Vegas, NV.
WaveDyn ® is a registered trademark of WaveFront Dynamics Inc.
View source version on businesswire.com: https://www.businesswire.com/news/home/20230330005171/en/ Investor and Media Inquiries: Dan Neal, PhD, Founder, CEO +1 505.453.7918 [email protected] VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Why exams intended for humans might not be good benchmarks for LLMs like GPT-4 | VentureBeat"
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"https://venturebeat.com/ai/why-exams-intended-for-humans-might-not-be-good-benchmarks-for-gpt-4"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Why exams intended for humans might not be good benchmarks for LLMs like GPT-4 Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
As tech companies continue to roll out large language models (LLM) with impressive results, measuring their real capabilities is becoming more difficult. According to a technical report released by OpenAI , GPT-4 performs impressively on bar exams, SAT math tests, and reading and writing exams.
However, tests designed for humans may not be good benchmarks for measuring LLMs’ capabilities. Language models encompass knowledge in intricate ways, sometimes producing results that match or exceed average human performance. However, the way they obtain the knowledge and use it is often incompatible with that of humans. That can lead us to draw wrong conclusions from test results.
For LLMs like GPT-4, exam success lies in the training data Arvind Narayanan, computer science professor at Princeton University, and Sayash Kapoor, Ph.D. candidate at Princeton University, recently wrote an article on the problems with testing LLMs on professional licensing exams.
One of these problems is “training data contamination.” This happens when a trained model is tested on the data it has been trained with. With too much training, a model might memorize its training examples and perform very well on them, giving the impression that it has learned the task. But it will fail on new examples.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Machine learning engineers go to great pains to separate their training and testing data. But with LLMs, things become tricky because the training corpus is so large that it’s hard to make sure your test examples are not somehow included in the training data.
“Language models are trained on essentially all of the text on the internet, so even if the exact test data isn’t in the training corpus, there will be something very close to it,” Narayanan told VentureBeat. “So when we find that an LLM performs well on an exam or a programming challenge, it isn’t clear how much of that performance is because of memorization versus reasoning.” For example, one experiment showed that GPT-4 performed very well on Codeforces programming challenges created before 2021, when its training data was gathered. Its performance dropped dramatically on more recent problems. Narayanan found that in some cases, when GPT-4 was provided the title of a Codeforces problem, it could produce the link to the contest where it appeared.
In another experiment , computer scientist Melanie Mitchell tested ChatGPT’s performance on MBA tests, a feat that was widely covered in the media. Mitchell found that the model’s performance on the same problem could vary substantially when the prompt was phrased in slightly different ways.
“LLMs have ingested far more text than is possible for a human; in some sense, they have ‘memorized’ (in a compressed format) huge swaths of the web, of Wikipedia, of book corpora, etc.,” Mitchell told VentureBeat. “When they are given a question from an exam, they can bring to bear all the text they have memorized in this form, and can find the most similar patterns of ‘reasoning’ that can then be adapted to solve the question. This works well in some cases but not in others. This is in part why some forms of LLM prompts work very well while others don’t.” Humans solve problems in a different way Humans gradually build their skills and knowledge in layers through years of experience, study and training. Exams designed for humans assume that the test-taker already possesses these preparatory skills and knowledge, and therefore do not test them thoroughly. On the other hand, language models have proven that they can shortcut their way to answers without the need to acquire prerequisite skills.
“Humans are presumably solving these problems in a different, more generalizable way. Thus we can’t make the assumptions for LLMs that we make for humans when we give them tests,” Mitchell said.
For instance, part of the background knowledge for zoology is that each individual is born, lives for a while and dies, and that the length of life is partly a function of species and partly a matter of the chances and vicissitudes of life, says computer scientist and New York University professor Ernest Davis.
“A biology test is not going to ask that, because it can be assumed that all the students know it, and it may not ask any questions that actually require that knowledge. But you had better understand that if [you’re going to be] running a biology lab or a barnyard,” Davis told VentureBeat. “The problem is that there is background knowledge that is actually needed to understand a particular subject. This generally isn’t tested on tests designed for humans because it can pretty well be assumed that people know [it].” The lack of these foundational skills and knowledge is evident in other instances, such as an examination of large language models in mathematics that Davis carried out recently. Davis found that LLMs fail at very elementary math problems posed in natural language.
This is while other experiments, including the technical report on GPT-4, show that LLMs score high on advanced math exams.
How far can you trust LLMs in professional tasks? Mitchell, who further tested LLMs on bar exams and medical school exams , concludes that exams designed for humans are not a reliable way to figure out these AI models’ abilities and limitations for real-world tasks.
“This is not to say that enormous statistical models like LLMs could never reason like humans — I don’t know whether this is true or not, and answering it would require a lot of insight into how LLMs do what they do, and how scaling them up affects their internal mechanisms,” Mitchell said. “This is insight which we don’t have at present.” What we do know is that such systems make hard-to-predict, non-humanlike errors, and “we have to be very careful when assuming that they can generalize in ways that humans can,” Mitchell said.
Narayanan said that an LLM that aces exams through memorization and shallow reasoning might be good for some applications, but can’t do the range of things a professional can do. This is especially true for bar exams, which overemphasize subject matter knowledge and underemphasize real-world skills that are hard to measure in a standardized, computer-administered way.
“We shouldn’t read too much into exam performance unless there is evidence that it translates into an ability to do real-world tasks,” Narayanan said. “Ideally we should study professionals who use LLMs to do their jobs. For now, I think LLMs are much more likely to augment professionals than replace them.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"To create a more accessible internet, context matters | VentureBeat"
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"https://venturebeat.com/ai/to-create-a-more-accessible-internet-context-matters"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest To create a more accessible internet, context matters Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
They say a picture is worth a thousand words. But an image can’t “speak” to individuals who have blindness or low-vision (BLV) without a little help. In a world driven by visual imagery, especially online, this creates a barrier to access.
The good news: When screen readers — software that reads the content of web pages to BLV people — come across an image, they will read any “ alt- text ” descriptions that the website creator added to the underlying HTML code, rendering the image accessible.
The bad news: Few images are accompanied by adequate alt-text descriptions.
In fact, according to one study, alt-text descriptions are included with fewer than 6% of English-language Wikipedia images. And even in instances where websites do provide descriptions, they may be of no help to the BLV community. Imagine, for example, alt-text descriptions that list only the name of the photographer, the image’s file name, or a few keywords to aid with search. Or picture a home button that has the shape of a house but no alt-text saying “home.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! As a result of missing or unhelpful image descriptions, members of the BLV community are frequently left out of valuable social media interactions or unable to access essential information on websites that use images for site navigation or to convey meaning.
Can AI aid those with blindness and low vision? While we should encourage better tooling and interfaces to nudge people toward making images accessible, society’s failure to date to provide useful and accessible alt-text descriptions for every image on the internet points to the potential for an AI solution, says Elisa Kreiss , a graduate student in linguistics at Stanford University and a member of the Stanford Natural Language Processing Group.
However, natural language generated (NLG) image descriptions haven’t yet proven beneficial to the BLV community. “There’s a disconnect between the models we have in computer science that are supposed to generate text from images and what actual users find to be useful,” Kreiss says.
In a recent paper, Kreiss and her study co-authors (including scholars from Stanford, Google Brain and Columbia University) found that BLV users prefer image descriptions that take context into account.
Because context can dramatically change the meaning of an image — e.g., a football player in a Nike ad versus in a story about traumatic brain injury — contextual information is vital for crafting alt-text descriptions that are useful.
Yet existing metrics of image description quality don’t take context into account. These metrics are therefore steering the development of NLG image descriptions in a direction that will not improve image accessibility, Kreiss says.
Read the paper, “ Context Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metrics ” Kreiss and her team also found that BLV users prefer longer alt-text descriptions rather than the concise descriptions typically promoted by prominent accessibility guidelines — a result that runs counter to expectations.
These findings highlight the need not only for new ways of training sophisticated language models, Kreiss says, but also for new ways of evaluating them to ensure they serve the needs of the communities they’ve been designed to help.
Measuring image descriptions’ usefulness in context Computer scientists have long assumed that image descriptions should be objective and context-independent, Kreiss says. But human-computer interaction research shows BLV users tend to prefer descriptions that are both subjective and context-appropriate. “If the dog is cute or the sunny day is beautiful, depending on the context, the description might need to say so,” she says. And if the image appears on a shopping website versus a news blog , the alt-text description should reflect the particular context to help clarify its meaning.
Yet existing metrics for evaluating the quality of image descriptions focus on whether a description is a reasonable fit for the image regardless of the context in which it appears, Kreiss says.
For example, current metrics might highly rate a soccer team’s photo description that reads “a soccer team playing on a field,” regardless of whether it accompanies an article about cooperation (in which case the alt-text should include something about how the team cooperates), a story about the athletes’ unusual hairstyles (in which case the hairstyles should be described) or a report on the prevalence of advertising in soccer stadiums (in which case the advertising in the arena might be mentioned). If image descriptions are to better serve the needs of BLV users, Kreiss says, they must have greater context-awareness.
To explore the importance of context, Kreiss and her colleagues hired Amazon Mechanical Turk workers to write image descriptions for 18 images, each of which appeared in three different Wikipedia articles. In addition to the soccer example cited above, the dataset included images such as a church spire linked to articles about roofs, building materials and Christian crosses; and a mountain range and lake view associated with articles about montane (mountain slope) ecosystems, a body of water, and orogeny (a specific way that mountains are formed).
The researchers then showed the images to both sighted and BLV study participants and asked them to evaluate each description’s overall quality; imaginability (how well it helped users imagine the image); relevance (how well it captured relevant information); irrelevance (how much irrelevant information it added); and general “fit” (how well the image fit within the article).
The study revealed that BLV and sighted participants’ ratings were highly correlated.
Context matters Knowing that the two populations were aligned in their assessments will be helpful when designing future NLG systems for generating image descriptions, Kreiss says. “The perspectives of people in the BLV community are essential, but often during system development we need much more data than we can get from the low-incidence BLV population.” Another finding: Context matters. Participants’ ratings of an image description’s overall quality closely aligned with their ratings for relevance.
When it came to description length, BLV participants rated the quality of longer descriptions more highly than did sighted participants, a finding Kreiss considers surprising and worthy of further research. “Users’ preference for shorter or longer image descriptions might also depend on the context,” she notes. Figures in scientific papers, for example, might merit longer descriptions.
Steering toward better metrics of image description quality Kreiss hopes her team’s research will promote metrics of image description quality that will better serve the needs of BLV users. She and her colleagues found that two of the current methods (CLIPScore and SPURTS) were not capable of capturing context.
CLIPScore, for example, only provides a compatibility score for an image and its description. And SPURTS evaluates the quality of the description text without reference to the image.
While these metrics can evaluate the truthfulness of an image description, that is only a first step toward driving “useful” description generation, which also requires relevance (i.e., context dependence), Kreiss says.
It was therefore unsurprising that CLIPScore’s ratings of the image descriptions in the researchers’ dataset did not correlate with the ratings by the BLV and sighted participants. Essentially, CLIPScore rated the description’s quality the same regardless of context.
When the team added the text of the various Wikipedia articles to alter the way CLIPScore is computed, the correlation with human ratings improved somewhat — a proof of concept, Kreiss says, that reference-less evaluation metrics can be made context-aware.
She and her team are now working to create a metric that takes context into account from the get-go to make descriptions more accessible and more responsive to the community of people they are meant to serve.
“We want to work toward metrics that can lead us toward success in this very important social domain,” Kreiss says. “If we’re not starting with the right metrics, we’re not driving progress in the direction we want to go.” Katharine Miller is a contributing writer for the Stanford Institute for Human-Centered AI.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"OpenAI's GPT-4 violates FTC rules, argues AI policy group | VentureBeat"
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"https://venturebeat.com/ai/openais-gpt-4-violates-ftc-rules-argues-ai-policy-group"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages OpenAI’s GPT-4 violates FTC rules, argues AI policy group Share on Facebook Share on X Share on LinkedIn Washington DC USA - July 3 2017: Federal Trade Commission seal sign and logo in downtown Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
The Federal Trade Commission (FTC) received a new complaint today from the Center for AI and Digital Policy ( CAIDP ), which calls for an investigation of OpenAI and its product GPT-4. The complaint argues that the FTC has declared that the use of AI should be “transparent, explainable, fair, and empirically sound while fostering accountability,” but claims that OpenAI’s GPT-4 “satisfies none of these requirements” and is “biased, deceptive, and a risk to privacy and public safety.” CAIDP is a Washington, D.C.-based independent, nonprofit research organization that “assesses national AI policies and practices , trains AI policy leaders, and promotes democratic values for AI.” It is headed by president and founder Marc Rotenberg and senior research director Merve Hickok.
“The FTC has a clear responsibility to investigate and prohibit unfair and deceptive trade practices. We believe that the FTC should look closely at OpenAI and GPT-4,” said Rotenberg in a press release about the complaints. “We are specifically asking the FTC to determine whether the company has complied with the guidance the federal agency has issued.” The complaint comes a day after an open letter calling for a six-month “pause” on developing large-scale AI models beyond GPT-4 highlighted the fierce debate around risks vs. hype as the speed of AI development accelerates.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! >>Follow VentureBeat’s ongoing generative AI coverage<< FTC has made recent public statements about generative AI The complaint also comes 10 days after the FTC published a business blog post called “Chatbots, deepfakes, and voice clones: AI deception for sale,” authored by Michael Atleson, an attorney at the FTC division of advertising practices. The blog post said that the FTC Act’s “prohibition on deceptive or unfair conduct can apply if you make, sell, or use a tool that is effectively designed to deceive — even if that’s not its intended or sole purpose.” Companies should consider whether they should even be making or selling the AI tool and whether they are effectively mitigating the risks.
“If you decide to make or offer a product like that, take all reasonable precautions before it hits the market,” says the blog post. “The FTC has sued businesses that disseminated potentially harmful technologies without taking reasonable measures to prevent consumer injury.” In a separate post from February, “Keep your AI claims in check,” Atleson wrote that the FTC may be “wondering” if a company advertising an AI product is aware of the risks. “You need to know about the reasonably foreseeable risks and impact of your AI product before putting it on the market. If something goes wrong — maybe it fails or yields biased results — you can’t just blame a third-party developer of the technology. And you can’t say you’re not responsible because that technology is a “black box” you can’t understand or didn’t know how to test.” FTC attorney said agency will always apply ‘bedrock’ advertising law principles In an interview with VentureBeat last week, unrelated to the CAIDP complaint and focused solely on advertising law, Atleson said that the basic message of both of his recent AI-focused blog posts is that no matter how new or different the product or service is, the FTC will always apply the “bedrock” advertising law principles in the FTC Act — that you can’t misrepresent or exaggerate what your product can do or what it is, and you can’t sell things that are going to cause consumers substantial harm.
“It doesn’t matter whether it’s AI or whether it turns out we’re all living in a multiverse,” he said. “Guess what? That prohibition of false advertising still applies to every single instance.” He added that admittedly, AI technology development is happening quickly. “We’re certainly right in the middle of a corporate rush to get a certain type of AI product to market, different types of generative AI tools,” he said. The FTC has focused on AI for a while now, he added, but the difference is that AI is more in the public eye, “especially with these new generative AI tools to which consumers have direct access.” Federal AI regulation may come from FTC With the growth of AI and speed of its development, legal experts say that FTC rulemaking about AI could be coming in 2023. In a December 2022 article written by Alston and Bird, federal AI regulation may be emerging from the FTC even though AI-focused bills introduced in Congress have not yet gained significant support.
“In recent years, the FTC issued two publications foreshadowing increased focus on AI regulation,” the article said, stating that the FTC had developed AI expertise in enforcing a variety of statutes, such as the Fair Credit Reporting Act, Equal Credit Opportunity Act and the FTC Act.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Open letter calling for AI 'pause' shines light on fierce debate around risks vs. hype | VentureBeat"
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"https://venturebeat.com/ai/open-letter-calling-for-ai-pause-shines-light-on-fierce-debate-around-risks-vs-hype"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Open letter calling for AI ‘pause’ shines light on fierce debate around risks vs. hype Share on Facebook Share on X Share on LinkedIn image by Canva Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
A new open letter calling for a six-month “pause” on large-scale AI development beyond OpenAI’s GPT-4 highlights the complex discourse and fast-growing, fierce debate around AI’s various stomach-churning risks, both short-term and long-term.
Critics of the letter — which was signed by Elon Musk, Steve Wozniak, Yoshua Bengio, Gary Marcus and several thousand other AI experts, researchers and industry leaders — say it fosters unhelpful alarm around hypothetical dangers, leading to misinformation and disinformation about actual, real-world concerns. Others pointed out the unrealistic nature of a “pause” and said the letter did not address current efforts towards global AI regulation and legislation.
The letter was published by the nonprofit Future of Life Institute , which was founded to “reduce global catastrophic and existential risk from powerful technologies” (founders include by MIT cosmologist Max Tegmark, Skype co-founder Jaan Tallinn, and DeepMind research scientist Viktoriya Krakovna). The letter says that “With more data and compute, the capabilities of AI systems are scaling rapidly. The largest models are increasingly capable of surpassing human performance across many domains. No single company can forecast what this means for our societies.” The letter points out that superintelligence is far from the only harm to be concerned about when it comes to large AI models — the potential for impersonation and disinformation are others. However, it does emphasize that the stated goal of many commercial labs is to develop AGI (artificial general intelligence) and adds that some researchers believe that we are close to AGI, with accompanying concerns for AGI safety and ethics.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! “We believe that Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable,” the letter stated.
Marcus spoke to the New York Times’ Cade Metz about the letter, saying it was important because “we have a perfect storm of corporate irresponsibility, widespread adoption, lack of regulation and a huge number of unknowns.” Critics say letter ‘further fuels AI hype’ The letter’s critics called out what they considered continued hype around the long-term hypothetical dangers of AGI at the expense of near-term risks such as bias and misinformation that are already happening.
Arvind Narayanan, professor of computer science at Princeton, said on Twitter that the letter “further fuels AI hype and makes it harder to tackle real, already occurring AI harms,” adding that he suspected that it will “benefit the companies that it is supposed to regulate, and not society.” And Alex Engler , a research fellow at the Brookings Institution, told Tech Policy Press that “It would be more credible and effective if its hypotheticals were reasonably grounded in the reality of large machine learning models, which, spoiler, they are not,” adding that he “strongly endorses” independent third-party access to and auditing of large ML models. “That is a key intervention to check corporate claims, enable safe use and identify the real emerging threats.” Joanna Bryson, a professor at Hertie School in Berlin who works on AI and ethics, called the letter “more BS libertarianism,” tweeting that “we don’t need AI to be arbitrarily slowed, we need AI products to be safe. That involves following and documenting good practice, which requires regulation and audits.” The issue, she continued, referring to the EU AI Act , is that “we are well-advanced in a European legislative process not acknowledged here.” She also added that “I don’t think this moratorium call makes any sense. If they want this, why aren’t they working through the Internet Governance Forum , or UNESCO?” Emily M. Bender, professor of linguistics at the University of Washington and co-author of “On the Dangers of Stochastic Parrots : Can Language Models Be Too Big?” went further, tweeting that the Stochastic Parrots paper pointed to a “headlong” rush to ever larger language models without considering risks.
“But the risks and harms have never been about ‘too powerful AI,'” she said. Instead, “they’re about concentration of power in the hands of people, about reproducing systems of oppression, about damage to the information ecosystem, and about damage to the natural ecosystem (through profligate use of energy resources).” In response to the criticism, Marcus pointed out on Twitter that while he doesn’t agree with all elements of the open letter, he “didn’t let perfect be the enemy of the good.” He is “still a skeptic,” he said, “who thinks that large language models are shallow, and not close to AGI. But they can still do real damage.” He supported the letter’s “overall spirit,” and promoted it “because this is the conversation we desperately need to have.” Open letter similar to other mainstream media warnings While the release of GPT-4 has filled the pages and pixels of mainstream media there has been a parallel media focus on the risks of large-scale AI development — particularly hypothetical possibilities over the long haul.
That was at the heart of a VentureBeat interview yesterday with Suresh Venkatasubramanian , former White House AI policy advisor to the Biden Administration from 2021-2022 (where he helped develop the Blueprint for an AI Bill of Rights ) and professor of computer science at Brown University.
The article detailed Venkatasubramanian’s critical response to Senator Chris Murphy (D-CT)’s tweets about ChatGPT that received backlash from many in the AI community. He said that Murphy’s comments, as well as a recent op-ed from the New York Times and similar op-eds, perpetuate “fear-mongering around generative AI systems that are not very constructive and are preventing us from actually engaging with the real issues with AI systems that are not generative.” We should “focus on the harms that are already seen with AI, then worry about the potential takeover of the universe by generative AI,” he added.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Italy blocks ChatGPT, citing data privacy concerns, as calls for AI regulation grow | VentureBeat"
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"https://venturebeat.com/ai/italy-blocks-chatgpt-citing-data-privacy-concerns-as-calls-for-ai-regulation-grow"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Italy blocks ChatGPT, citing data privacy concerns, as calls for AI regulation grow Share on Facebook Share on X Share on LinkedIn Image by Canva Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
It has been a challenging week for OpenAI, as calls for generative AI regulation grow louder: Today, Italy’s data protection agency said it was blocking access OpenAI’s popular ChatGPT chatbot and had opened a probe due to concerns about a suspected data collection breach.
The agency said the restriction was temporary, until OpenAI abides by the EU’s General Data Protection Regulation ( GDPR ) laws. A translation of the announcement said that “a data breach affecting ChatGPT users’ conversations and information on payments by subscribers to the service had been reported on 20 March.” It added that “no information is provided to users and data subjects whose data are collected by Open AI; more importantly, there appears to be no legal basis underpinning the massive collection and processing of personal data in order to ‘train’ the algorithms on which the platform relies.” >>Follow VentureBeat’s ongoing generative AI coverage<< A week of calls for large-scale AI regulation The announcement comes just a day after the Federal Trade Commission (FTC) received a complaint from the Center for AI and Digital Policy ( CAIDP ), which called for an investigation of OpenAI and its product GPT-4. The complaint argued that the FTC has declared that the use of AI should be “transparent, explainable, fair, and empirically sound while fostering accountability,” but claims that OpenAI’s GPT-4 “satisfies none of these requirements” and is “biased, deceptive, and a risk to privacy and public safety.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! And on Wednesday , an open letter calling for a six-month “pause” on large-scale AI development beyond OpenAI’s GPT-4 highlighted the complex discourse and fast-growing, fierce debate around AI’s various risks, both short-term and long-term.
Critics of the letter — which was signed by Elon Musk, Steve Wozniak, Yoshua Bengio, Gary Marcus and other AI experts, researchers and industry leaders — say it fosters unhelpful alarm around hypothetical dangers, leading to misinformation and disinformation about actual, real-world concerns. Others pointed out the unrealistic nature of a “pause” and said the letter did not address current efforts towards global AI regulation and legislation.
Questions about how the GDPR applies to ChatGPT The EU is currently working on developing a proposed Artificial Intelligence Act.
Avi Gesser, partner at Debevoise & Plimpton and co-chair of the firm’s Cybersecurity, Privacy and Artificial Intelligence Practice Group, told VentureBeat in December that the EU Act would be a “risk-based regime to address the highest-risk outcomes of artificial intelligence.” However, the EU AI Act won’t be fully baked or take effect for some time, so some are turning to the GDPR, which was enacted in 2018, for regulatory authority on issues related to ChatGPT. In fact, according to an Infosecurity article from January, some experts are questioning “the very existence of OpenAI’s chatbot for privacy reasons.” Infosecurity quoted Alexander Hanff, member of the European Data Protection Board’s (EDPB) support pool of experts, who said that “If OpenAI obtained its training data through trawling the internet, it’s unlawful.” “Just because something is online doesn’t mean it’s legal to take it,” he added. “Scraping billions or trillions of data points from sites with terms and conditions which, in themselves, said that the data couldn’t be scraped by a third party, is a breach of the contract. Then, you also need to consider the rights of individuals to have their data protected under the EU’s GDPR, ePrivacy directive and Charter of Fundamental Rights.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"How to use AI to improve customer service and drive long-term business growth | VentureBeat"
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"https://venturebeat.com/ai/how-to-use-ai-to-improve-customer-service-and-drive-long-term-business-growth"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest How to use AI to improve customer service and drive long-term business growth Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
In a rocky economy , finding and keeping happy customers is critical to a business’s long-term growth. In fact, American businesses lose upwards of $83 billion due to poor customer service. Therefore, any technological advancement that improves their experience—while increasing your efficiency—is worth considering.
In the past decade, AI has transitioned from a freaky sci-fi concept to a tool working behind the scenes of our lives, to a mainstream topic of discussion. From a business perspective, it’s fast becoming the differentiator that businesses need to stand out from competitors when the landscape is tough.
Even if you’re not using AI to improve your customers’ lives, your rivals most likely are. Here are some key ways businesses can leverage AI to build a customer service experience that inspires loyalty and delivers value both for you and for them.
Customer service that’s fast and consistent Speed is expected in customer service today. We’re used to getting answers to all kinds of questions with a few taps on our smartphones, and that extends to solving any problems we might have with the businesses we interact with. On average, customers expect companies to respond to a phone call within five minutes and an email within one to 24 hours.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! While AI can’t do everything humans can, what it can do, it does much faster than humans, and at greater scale. For example, AI can transcribe customer conversations in real time and identify sentiments associated with the customer’s language. From there, it can advise agents on how best to proceed based on models derived from thousands of other similar conversations.
It can also operate as a search engine, scanning knowledge bases and producing relevant answers to a customer’s queries—all without having to leave them quietly growing more impatient on hold. New AI models such as GPT-3 can learn these tasks at a truly astonishing pace.
Businesses can also use AI to run wide-reaching quality control checks. Whereas one supervisor might be able to listen to 20 calls a day at the most, AI can assess thousands of transcripts in minutes and flag moments that don’t meet the standards it’s been trained to recognize for a person to review.
In theory, a supervisor can do a similar job. They can listen in on a call, judge how it’s going based on their previous experience, and recommend the next steps to the agent while also making sure they are upholding the company’s standards. But a supervisor can’t sit in on every single call while remaining productive in their everyday tasks. AI, however, can be available to all your agents, providing real-time insights that improve customer and agent experiences and the consistency of your service.
Many businesses have customers whose needs don’t fall within call center hours. For example, banks and airlines need to be able to answer questions 24/7. As chatbots become more prevalent and sophisticated, there will be more self-serve options for these kinds of queries, allowing customers to find answers wherever and whenever they need them.
AI excels at this, and at scale, which lines up with the majority of customer service communications. As it improves, expect to see faster resolutions and shorter wait times.
Personalization with a purpose We don’t just accept that our phones know everything about us; we expect them to. If I Google “Greek restaurants” and my phone shows me a list of places hundreds of miles away—or in Greece—I’m pretty frustrated (especially if I’m already hangry). When I’m texting, I get annoyed if my phone doesn’t automatically correct my most common typos. If I’m scrolling through social media, I’m confused if I see ads for products I have no interest in.
These are all examples of personalization generated by AI. In a customer’s view, a personalized experience is a good experience.
76% of customers feel frustrated when brands fail to deliver a personalized interaction—and 71% expect personalized service.
Imagine a scenario where a customer has to call customer service. The agent has all the information available about them and their account before they call, thanks to all the insights drawn from transcripts of previous calls and integrations between the AI and a CRM. The agent can even see a score for the account based on the sentiments of the various members involved across all channels.
That means the customer doesn’t have to spend the first five minutes of the call outlining their history and detailing previous issues. They can jump immediately to the current issue knowing that the agent has all the necessary past context. With all that information and support from the AI, the agent needs less time to find a resolution, improving the customer experience.
Another hope is that chatbots powered by advanced AI like ChatGPT will one day be able to deliver the same level of personalized experience as human agents. This will encourage customers to take their basic queries to bots, allowing more complex problems to go straight to the front of agents’ queues.
Beyond making every customer feel like a VIP, personalization improves the quality and speed of the service they receive.
Being the proactive party Until recently, the challenge was getting AI to the point where it can provide real-time insights. The next stage has been building AI that can make predictions that help businesses forecast customer outcomes. This is particularly useful in economic downturns when businesses are looking for data that can give them a clear indication of their financial situations. It can also help them prioritize resources accordingly.
Closing deals and retaining customers are crucial to surviving a recession. In financial services, a 5 % increase in customer retention increases profit by more than 25%. And in apparel, the average repeat customer spent 67% more in months 31 to 36 than in their first six months as a customer, indicating that long-term customers are more valuable than new customers.
AI can predict both purchase intent and churn risk to an impressive degree of accuracy. This means that sales teams can increase their likelihood of closing deals by concentrating on the strongest leads rather than spending time chasing what ultimately turn out to be dead ends. Meanwhile, AI can also identify trends that indicate a customer is unlikely to renew or is about to cancel. With this information, businesses have the opportunity to identify the issue and fix it preemptively.
It’s been AI’s ability to mine data extremely fast that has made it so useful. On top of that, it’s now able to make predictions about that data that can help us make informed predictions and forecasts with direct implications for revenue.
There have been a lot of positive developments in the AI space that are expanding the ways people and businesses can benefit from this technology. A lot of it comes down to data: where we can find it, how it’s processed, and what we can do with those insights. Businesses need all of those pieces to get the most from AI. In customer service, it translates to what we know about the customer, how we access and analyze that information, and how we use it to improve their experience.
It used to be that AI was used on historical data, which was useful but retroactive. More recently, it’s become possible to use AI to make real-time decisions. The next generation of AI is forward-thinking, using data to make predictions that humans can’t come up with nearly as quickly. As with any tool, AI is most effective when we understand how to use it and its strengths and limitations.
With technology like GPT-3, we’re just starting to find out what those look like in the future.
Dan O’Connell is Chief Strategy Officer at Dialpad.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Got It AI’s ELMAR challenges GPT-4 and LLaMa, scores well on hallucination benchmarks | VentureBeat"
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"https://venturebeat.com/ai/got-it-ai-elmar-challenges-gpt-4-and-llama"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Got It AI’s ELMAR challenges GPT-4 and LLaMa, scores well on hallucination benchmarks Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Conversational AI startup Got It AI has released its latest innovation ELMAR (Enterprise Language Model Architecture), an enterprise-ready large language model (LLM) that can be integrated with any knowledge base for dialog-based chatbot Q&A applications. The company claims that ELMAR is notably smaller than GPT-3 and can run on-premises, making it a cost-effective solution for enterprise customers.
In addition, the LLM’s commercial viability is enhanced by its independence from Facebook Research’s LLaMA and Stanford’s Alpaca.
“ELMAR was conceived because we heard from our enterprise customers in our pipeline that they didn’t want their data to leave their ‘premises,’” Peter Relan, chairman of Got It AI, told VentureBeat. “Hence, we said let’s build a commercially viable, small model that could be run ‘on-prem,’ but match available LLMs in accuracy on key enterprise use cases.” ELMAR also includes truth-checking on responses and post-processing to mitigate the risk of incorrect response rates for users. Compared to currently available LLMs, ELMAR requires less expensive hardware, making it a more accessible option for enterprise beta testers who can sign up for pilots.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! On par with big tech LLMs Got It AI claims that ELMAR offers several benefits to enterprises seeking to incorporate a language model. Firstly, due to its diminutive size, the hardware required to operate ELMAR is significantly less expensive than that needed for OpenAI’s GPT-4. Furthermore, ELMAR allows for fine-tuning on the target dataset, eliminating the need for costly API-based models and preventing a surge in inference costs.
“We are not saying very powerful models aren’t needed,” Relan told VentureBeat. “We are saying all that power is not necessary for key enterprise use cases and requirements.” To advance conversation surrounding the accuracy of language models, Got It AI compared ELMAR to OpenAI’s ChatGPT, GPT-3, GPT-4, GPT-J/Dolly, Meta’s LLaMA, and Stanford’s Alpaca in a study to measure hallucination rates. The study demonstrated how a smaller yet fine-tuned LLM can perform just as well on dialog-based use cases on a 100-article test set made available now for beta testers.
“Recently, it was suggested that smaller and older models like GPT-J can deliver ChatGPT-like experiences. In our experiments, we did not find this to be the case. Despite fine-tuning, such models performed significantly worse than other more advanced models,” said Chandra Khatri, head of conversational AI research and cofounder of Got It AI. “It is not just about the data, but also about modern model architectures and training techniques.” Earlier in January, the company developed what they called “ TruthChecker ,” a small language model–based fine-tuned post-processor, which compares responses generated by any language model with ground truth in the target dataset and flags what appear to be incorrect, misleading or incomplete answers; a phenomenon known as “hallucination.” Got It AI’s study revealed that smaller open-source LLMs perform poorly on specific tasks unless they are fine-tuned on target datasets.
“When we used Alpaca, an open-source model, for a Q&A task on our target 100 articles set, it resulted in a significant fraction of answers being incorrect or hallucinations, but did better after fine-tuning. On the other hand, ELMAR, when fine-tuned on the same dataset, produced accurate results, equivalent to ChatGPT-3,” said Khatri.
“We picked our approach to be such that ELMAR’s model, training and data are not constrained by the licenses of LLaMA and Alpaca-like models and data,” said Relan. “It was not easy. We had to thread the needle and then find the right combination of a commercializable model, training techniques and data.” Empowering businesses with greater LLM control Got It AI’s ELMAR language model allows businesses to configure their pre-processors and plan measures to secure their language model architecture against attacks.
“The pre-processor will be tuned, configured and controlled by the enterprise,” Relan told VentureBeat. “So the enterprise user sets its policies for removing data, such as personally identifiable information (PII).” The ELMAR model has been put through its paces against several knowledge bases such as Zendesk and Confluence, as well as large-sized PDF documents.
Following successful alpha feedback, Got It AI plans to soon commence ELMAR’s beta program with enterprise pilots across multiple industries and receive feedback on the types of pre-processing and post-processing “alignment” that work across all industries, versus those that are industry or enterprise-specific.
The company aims to improve ELMAR’s speed, accuracy and cost-effectiveness for training, with plans to scale up the model post-beta cycle. “There’s lots of work ahead,” said Relan.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Autonomous agents and decentralized ML on tap as Fetch AI raises $40M | VentureBeat"
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"https://venturebeat.com/ai/autonomous-agents-and-decentralized-ml-on-tap-as-fetch-ai-raises-40m"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Autonomous agents and decentralized ML on tap as Fetch AI raises $40M Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Web3 infrastructure provider Fetch AI is looking to advance intelligent agent and distributed blockchain technology on the wings of a $40 million investment round gained today from technology incubator and Web3 investment firm DWF Labs.
Ultimately, Fetch AI targets the needs of consumers that juggle multiple apps to connect to different services, each of which may administer a convenience fee. The goal is to eliminate intermediaries, enable services to get paid fairly, and for end-users to save money.
“By enabling the creation, deployment and connection of intelligent agents, Fetch AI is at the forefront of automating Web3 systems and reinventing traditional business models,” Andrei Grachev, managing partner at DWF Labs, told VentureBeat. “These agents not only learn and predict, but also take action to execute meaningful tasks in the real world.” Fetch AI’s use of blockchain technology enables value transfer and acts as a coordination mechanism through which autonomous agents can launch transactions. Agreements made between these agents are then recorded on the Fetch blockchain using FET, the native cryptocurrency of the platform. FET is used to pay for transactions and services provided by agents.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Core Fetch AI features The company developed a tech stack that includes several key components: On the AI/ML track, the company has developed CoLearn, a collective learning protocol that enables collaboration on machine learning (ML) models without data leakage.
The company is actively developing the Axim platform, which offers a managed and hosted version of CoLearn for enterprise customers.
On the agent track, Fetch AI developed the Autonomous Economic Agent framework and Microagent framework, which can be used to create peer-to-peer agent-based applications.
On the Web3 track , the company has its own layer-1 blockchain network based on Cosmos SDK, along with tools such as the Fetch browser extension wallet, the Cosmpy Python library for developing Cosmos Dapps, and the Jenesis CLI tool for bootstrapping and testing CosmWasm contracts on any CosmWasm chain.
The company is also beginning to release product demonstrators that incorporate all of these building blocks.
Bosch joins in on Fetch Foundation This week, Fetch AI launched support for its agent tech, Fetchbot, in the Fetch wallet. Fetchbot is designed to provide super wallet capabilities, including decentralized finance (DeFi) automation and integration with the GPT-based large language model (LLM) API for processing natural language processing (NLP) queries related to Fetch.
In the coming days, the company plans to release Agentverse, which will provide an in-browser IDE for writing Fetch microagent applications and support a mailbox feature for agent message delivery and hosting that eliminates the need for Fetch agents to be online all the time. The company also plans to release other demonstrators of its agent tech in the DeFi space.
Recently, Bosch and Fetch AI also announced their collaboration to create the Fetch Foundation , which will research and develop Web3 technology for real-world use cases in areas such as mobility, industry and consumers. The foundation will be governed by a three-tier structure and inspired by the Linux Foundation’s decentralized innovation model. Bosch and Fetch AI will lead the foundation’s management board and seek to expand it with other industry participants.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Automation does not mean elimination: AI's role in job security | VentureBeat"
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"https://venturebeat.com/ai/automation-does-not-mean-elimination-ais-role-in-job-security"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Automation does not mean elimination: AI’s role in job security Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Even as technologies such as video conferencing and messaging platforms adopted during forced remote work are now widely accepted, some workers still remain wary of technology in the workforce. New research shows us that only 50% of employees see technology as a strong asset for efficiency.
IT teams are currently drivers of technology innovation implementation for their organizations, and IT optimization is slated to be the third largest AI use case by 2025, with an annual growth rate of 29.7%. However, with pop culture spreading doom and gloom over AI’s role in taking jobs, does this mean IT teams should be concerned about their job security? Will they be another casualty of obsolescence due to AI? A knee-jerk reaction to AI in the workforce is that the need for IT teams is eliminated as machine learning (ML) can more efficiently and cost-effectively serve the team’s core purpose. Fear of automation is not a new concept: Today, 37% of workers are worried about losing their jobs due to automation.
Automation and unemployment not synonymous However, they can rest easy. The truth is that automation does not lead to job loss in the way we think; it may be the opposite. South Korea, which is the most automated country in the world, saw its unemployment rate hit a record low in August 2022.
Singapore and Japan, the next two most automated countries, also have unemployment rates well below the global average , indicating that automation and unemployment are not directly correlated.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! How can we explain the discrepancy between perception and actuality? It’s not job loss; it’s job evolution. Automation will allow for IT teams to carve out a more strategic place for themselves within their organization. AI can play a huge role in reducing the volume of routine tasks that must be manually completed, such as troubleshooting applications or responding to service tickets.
The less time teams can spend on these, the more they can spend on projects that will move the needle within the organization — such as developing new applications that allow businesses to enter new markets, increasing manageability, and cutting hardware costs. These changes in roles will give these employees a better sense of fulfillment and purpose in their organization and allow them to be seen as more valuable assets.
The question becomes, “How do we get there?” The value of AI in IT IT cannot be completely automated, nor should it ever be. Employees seek out human interaction to feel their problems are being heard and that support is personalized to them. IT employees should be used to their greatest strengths: interpersonal communication and long-term strategy/innovation. These are two concepts that AI will never be able to replicate.
The true value of AI is its ability to identify problems proactively and provide actionable insights that IT teams can leverage to attack problems before they occur and optimize their systems for long-term performance.
One goal of AI is to improve the digital employee experience. Employees lose hours of working time through technology issues, and these issues also lower morale when employees feel under-supported by their companies.
Automation alleviates this: Detecting an issue before an employee can flag it saves time and resources; in turn, employees feel better connected to the organization. In the long run, this helps slow employee turnover, support innovation — and by extension, help explain lower unemployment rates amid automation.
So, where does this leave IT teams? The answer is in strategy sessions with senior leadership, where they belong. The days of responding to service requests as the dominant IT responsibility are moving further away. With more free time, they can focus on proactive activities and strategies for better workflow. Automation paves the way for IT to be seen as the strategic leaders they are rather than putting out ad hoc technical fires — they won’t be out of business; they’ll be propelling the organization forward and advancing its digital transformation initiatives.
Embrace change AI is not a threat to IT teams. Instead, it allows them to better showcase their value and importance within their organizations. As difficult economic conditions continue to be top of mind, business leaders will consider where to cut down on costs. Some will, unfortunately, enact layoffs.
However, teams that can showcase their value to the organization and its bottom line may be better off when it comes to those decisions. Rather than viewing AI as a threat, IT professionals should be viewing it as their new favorite co-worker, one that is going to free them from menial tasks and to focus on what provides the most impact and allow them to grow within their company.
AI will not be eliminating IT’s role; it will be transforming it. Both IT departments and entire organizations will reap the rewards.
Yassine Zaied is chief strategy officer of Nexthink.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"5 ways machine learning must evolve in a difficult 2023 | VentureBeat"
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"https://venturebeat.com/ai/5-ways-machine-learning-must-evolve-in-a-difficult-2023"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest 5 ways machine learning must evolve in a difficult 2023 Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
With 2022 well behind us, taking stock in how machine learning (ML) has evolved — as a discipline, technology and industry — is critical. With AI and ML spend expected to continue to grow , companies are seeking ways to optimize rising investments and ensure value, especially in the face of a challenging macroeconomic environment.
With that in mind, how will organizations invest more efficiently while maximizing ML’s impact? How will big tech’s austerity pivot influence how ML is practiced, deployed, and executed moving forward? Here are 5 ML trends to expect in 2023.
1. Automating ML workflows will become more essential Although we saw plenty of top technology companies announce layoffs in the latter half of 2022, it’s likely none of these companies are laying off their most talented ML personnel. However, to fill the void of fewer people on deeply technical teams, companies will have to lean even further into automation to keep productivity up and ensure projects reach completion. We expect to also see companies that use ML technology implement more systems to monitor and govern performance and make more data-driven decisions on managing ML or data science teams. With clearly defined goals, technical teams will have to be more KPI-centric so that leadership can have a more in-depth understanding of ML’s ROI. Gone are the days of ambiguous benchmarks for ML.
2. Hoarding ML talent is over Recent layoffs, specifically for those working with ML, are likely the most recent hires as opposed to the more long-term staff that have been working with ML for years. Since ML and AI have become more common in the last decade, many big tech companies have begun hiring these types of workers because they could handle the financial cost and keep them away from competitors — not necessarily because they were needed. From this perspective, it’s not surprising to see so many ML workers being laid off, considering the surplus within larger companies. However, as the era of ML talent hoarding ends, it could usher in a new wave of innovation and opportunity. With so much talent now looking for work, we will likely see many folks trickle out of big tech and into small and medium-sized businesses or startups.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! 3. ML project prioritization will focus on revenue and business value Looking at ML projects in progress, teams will have to be far more efficient given the recent layoffs and look towards automation to help projects move forward. Other teams will need to develop more structure and determine deadlines to ensure projects are completed effectively. Different business units will have to begin communicating more — improving collaboration — and sharing knowledge so that smaller teams can act as one cohesive unit.
In addition, teams will also have to prioritize which types of projects they need to work on to make the most impact in a short period of time. I see ML projects boiled down to two types: sellable features that leadership believes will increase sales and win against the competition; and revenue optimization projects that directly impact revenue. Sellable feature projects will likely be postponed as they’re hard to get out quickly. Instead, now-smaller ML teams will focus more on revenue optimization as it can drive real revenue. Performance, in this moment, is essential for all business units — and ML isn’t immune to that.
4. Open source ML tools will gain a greater market share It’s clear that next year, MLOps teams that specifically focus on ML operations, management, and governance, will have to do more with less. Because of this, businesses will adopt more off-the-shelf solutions because they are less expensive to produce, require less research time, and can be customized to fit most needs.
MLOps teams will also need to consider open-source infrastructure instead of getting locked into long-term contracts with cloud providers. While organizations using ML at hyperscale can certainly benefit from integrating with their cloud providers, it forces these companies to work the way the provider wants them to work. At the end of the day, you might not be able to do what you want, the way you want, and I can’t think of anyone who actually relishes that predicament.
Also, you are at the mercy of the cloud provider for cost increases and upgrades, and you will suffer if you are running experiments on local machines. On the other hand, open source delivers flexible customization, cost savings, and efficiency — and you can even modify open-source code yourself to ensure that it works exactly the way you want. Especially with teams shrinking across tech, this is becoming a much more viable option.
5. Unified offerings will be key One of the factors slowing down MLOps adoption is the plethora of point solutions. That’s not to say that they don’t work, but that they might not integrate well together and leave gaps in a workflow. Because of that, I firmly believe that 2023 will be the year the industry moves towards unified, end-to-end platforms built from modules that can be used individually and also integrate seamlessly with each other (as well as integrate easily with other products).
This kind of platform approach, with the flexibility of individual components, delivers the kind of agile experience that today’s specialists are looking for. It’s easier than purchasing point products and patching them together; it’s faster than building your own infrastructure from scratch (when you should be using that time to build models). Therefore, it saves both time and labor — not to mention that this approach can be far more cost-effective. There’s no need to suffer with point products when unified solutions exist.
Conclusion In a potentially challenging 2023, the ML category is due for continued change. It will get smarter and more efficient. As organizations talk about austerity, expect to see the above trends take center stage and influence the direction of the industry in the new year.
Moses Guttmann is CEO and cofounder of ClearML.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"The importance of synchronizing siloed security solutions | VentureBeat"
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"https://venturebeat.com/security/the-importance-of-synchronizing-siloed-security-solutions"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest The importance of synchronizing siloed security solutions Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
The growing number of siloed security solutions that make up much of a modern organization’s security stack are creating major headaches for enterprise cybersecurity teams. Existing solutions don’t have the ability to glean contextual insights and analysts don’t have the time or resources to piece together wide ranges of data points amassed from different channels.
This results in an inability to predict and fully understand the scope of flagged threats. And that leaves organizations vulnerable.
To hedge their bets, threat actors look to target an enterprise through multiple attack vectors. This strategy has become much simpler as companies continue to adopt new SaaS apps, web apps, cloud collaboration tools and shared cloud storage drives.
With the number of vulnerable channels only expanding, so are the number of security solutions being deployed, making interconnection of an organization’s cybersecurity solutions essential for the continued and efficient protection of the organization.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Too many tools in the kitchen… With the growth in sophistication and frequency of cyberattacks , security professionals rely on a constantly growing number of cyber-defense tools. On average, organizations use 45 different cybersecurity tools to keep their systems safe, and many companies actually deploy more than that.
With such a bloated slate of solutions, they frequently undermine one another. Security teams that operate more than 50 tools are 8% less effective at detecting an attack, and 7% less effective when responding to one. Clearly, siloed security solutions are leaving enterprises vulnerable.
What’s more, as the arsenal of unconnected solutions continues to expand, it becomes less and less sustainable for security personnel to hop from one threat defense tool to another. The siloing of all these solutions obfuscates the enterprise’s holistic view of its security status and important aspects of contextual analysis. And just think about the overhead that many of these tools require for configuration and management.
Sixty percent of cybersecurity professionals admit their current security tools do not enable their security operations team to work with maximum efficiency. Eight-four percent estimate their organization lost up to 10% of revenue from security breaches in the last 12 months.
These percentages will continue to rise if security teams respond to increased threats with an increased number of tools, especially as they scramble to protect the newer attack vectors. With each new workplace tool (or personal tool such as WhatsApp) adopted by users, areas of vulnerability not covered by traditional enterprise security solutions increase. As reliance on new cloud-based workplace tools grows and hybrid work becomes the norm, enterprise operations will become more complex, and siloed security data will in turn become more problematic.
Consolidation, consolidation, consolidation There is no silver bullet to deal with threat actors. However, it is vital that cybersecurity professionals consolidate their tools to simplify communications and manage incidents rapidly and effectively. As much as possible, security professionals should be able to view activity and data provided by cyber and IT applications from within a single platform. That way they can holistically assess the organization’s security situation and easily plug gaps.
Although the cybersecurity industry is heading towards consolidation with the rise of effective extended detection and response (XDR) tools, the market is some ways away from reaching full maturity. In the meantime, there is still a need for bespoke solutions that deal with different threats and attack vectors.
Therefore, a certain level of synchronization between these different tools is vital. The industry is already seeing this in the form of multi-vendor partnerships which integrate various tools into one platform.
Doing away with siloed security For example, enterprise platforms like Salesforce are partnering with external vendors to bolster cybersecurity capabilities, allowing users to integrate their niche app security within their wider network security. Cybersecurity EDR vendors such as SentinelOne and CrowdStrike partner with various external vendors to provide customers with coverage that is compatible with its own solution, to increase their customers’ security posture and unify management.
Security leaders should drive the vendor community to provide highly integrated solutions that deliver actionable insights from connections, as well as contextual analysis between seemingly disparate problems to prevent and remediate malicious activity. Built-in compatibility between different solutions will also reduce the manual workload required of security teams and allow them to better use their time, dealing with cyberthreats more effectively. This should be supported by machine learning (ML) and artificial intelligence (AI) to further reduce the manual workload.
A hodgepodge of siloed and disconnected solutions may cause more problems than it solves. A cybersecurity team’s lack of ability to see the whole picture (and more) is a major vulnerability for enterprises and impedes a team’s ability to prevent and act on threats. This is especially true if threats work on multiple levels, as is increasingly the case.
In the current economic climate, cost-cutting measures are impacting all enterprises, and a security team’s time has become even more precious. So for an organization’s safety, it’s vital that their time is spent as efficiently as possible.
As the industry braces itself for an increasingly complex wave of threats, breaking down silos and building up synchronicity is imperative for its success.
Yoram Salinger is CEO of Perception Point.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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3,243 | 2,023 |
"How SlashNext is using generative AI to shut down ChatGPT phishing attacks | VentureBeat"
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"https://venturebeat.com/security/slashnext-using-generative-ai-shut-down-chatgpt-phishing-attacks"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages How SlashNext is using generative AI to shut down ChatGPT phishing attacks Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
ChatGPT and generative AI have made life difficult for security teams. Simply by writing a brief prompt, a wannabe hacker can generate a phishing email template in seconds, which they can send off to countless unsuspecting users until one makes the mistake of clicking on a malicious link or attachment.
Email security provider SlashNext is looking to fight AI with AI. BEC Generative AI, its new patent-pending solution, is designed to help identify and block scam messages generated by ChatGPT and other AI models.
BEC Generative AI uses AI data augmentation and cloning technologies to automatically generate thousands of potential business email compromise ( BEC ) threats. SlashNext’s existing Human AI solution then analyzes these with natural language processing to learn how to better detect malicious emails.
While SlashNext claims the solution is the first in the industry to use generative AI to stop BEC attacks, more broadly, the release demonstrates how generative AI can play a positive role in the data security landscape — in this case, by enhancing the detection of phishing emails and social engineering scams, which result in so many data breaches.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! How generative AI is revolutionizing phishing The release comes as phishing scams are on the rise following the release of ChatGPT in November, with Vade finding 278.3 million unique phishing emails in Q4 2022, compared to 74.4 million in Q3 2022.
These attacks are incredibly popular because they’re low-effort and high-reward. For instance, an individual can create a fake Office 365 login form, send out a phishing email template to unsuspecting users and harvest their account details when they attempt to log in.
For both end-users and security teams, it’s also very time-consuming to review each email and determine if the content is legitimate. In fact, research finds that 70% of organizations spend anywhere from 16-60 minutes dealing with a single phishing email.
If a user succumbs to fatigue and takes a scam at face value just once, they may cause a data breach that can cost millions. With generative AI use on the rise, the volume of threats employees are exposed to is only going to increase.
“Generative AI is already being used by threat actors to automate thousands of uniquely tailored phishing messages. What’s more, it can create thousands of variations of those messages to further increase their success rate,” said Patrick Harr, CEO of SlashNext.
“Large language models such as GPT-3 are freely available, and bad actors are very quick to take advantage of any new tool that allows them to increase their volume of attacks while reducing the time, effort and cost involved. It’s a win-win for the threat actors, and the security community must be prepared to fight AI with AI,” Harr said.
While an uptick in scams created by generative AI presents new challenges, organizations can look to use AI themselves to automate and upscale their security operations, ensuring they are prepared to detect AI-generated malicious content at speed.
The email security market SlashNext’s solution falls within the cloud-based email security market , which Mordor Intelligence valued at $762.82 million in 2020 and expects will reach a value of $1,246.99 million by 2026.
One of SlashNext’s main competitors is Abnormal Security , an AI-driven email security provider offering a platform that uses AI to assess incoming issues and compare them to a user’s baseline activity. The platform can then identify anomalous communications that indicate BEC attempts and phishing scams, automatically remediating malicious emails so human users don’t need to.
Last year Abnormal Security achieved a $4 billion valuation.
Another competitor is cloud email security provider Avanan , which offers an API-based solution with natural language processing and image recognition that it claims can identify phishing emails with a 99.2% reduction rate. Check Point acquired Avanan for approximately $300 million in 2021.
Harr argues that the key differentiator between SlashNext and its competitors is the accuracy of its zero-hour threat detection.
“SlashNext is the only company to combine natural language processing, computer vision , machine learning , deep contextualisation and relationship graphs, … file attachment inspection and sender impersonation analysis into one solution for the best, most accurate zero-hour threat detection in the industry,” Harr said.
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"Should organizations swear off open-source software altogether? | VentureBeat"
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"https://venturebeat.com/security/should-organizations-swear-off-open-source-software-altogether"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Should organizations swear off open-source software altogether? Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Open-source software is a nightmare for data security.
According to Synopsys , while 96% of software programs contain some kind of open-source software component, 84% of codebases contain at least one vulnerability.
These vulnerabilities are not only present in internal software, but also in third-party apps and services scattered across on-premises and cloud environments.
Awareness over the software supply chain threats has been growing over the past few years, with President Biden releasing an Executive Order in May 2021 calling for federal government agencies to create a software bill of materials (SBOM) , to produce an inventory of software components used throughout their environments.
Likewise, the revelation that the Log4j vulnerability impacted 58% of organizations showed that organizations needed to be doing more to vet the software they use in their environments.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! While the ubiquitous use of open-source software means that organizations can’t swear off these tools altogether, there are some steps organizations can take to start mitigating the risk of exposing critical data assets.
What risks are facing open-source software? One of the biggest threats facing open-source software is supply chain attacks. In a supply chain attack, a cybercriminal or state-sponsored threat actor will target the maintainer of an open-source project so they can embed malicious code into an open-source library and ship it to any downstream organizations that download it.
This style of attack is becoming increasingly common to the point where research suggests that there has been a 742% average annual increase in software supply chain attacks over the past three years, with Sonatype discovering 106,872 malicious packages available online.
“From a supply chain perspective, it’s increasingly common to see malicious code introduced into open source — and that can be accomplished by compromising a legitimate project, or via a malicious project meant to confuse users into downloading counterfeit code that resembles a common project,” said Dale Gardner, Gartner Sr. director analyst.
Gardner suggests that organizations reliant on open-source software need to evaluate the risk presented by each project.
“For example, does the project have a good track record for responding to problems, are the appropriate security controls in place, is the code up to date, and so on. And from a supply chain perspective, it’s not just open source with which we should be concerned — we’ve seen a number of cases where commercial code has been compromised,” Gardner said.
Frameworks such as the secure software development framework (SSDF) and Supply-chain Levels for Software Artifacts (SLSA) are one way that organizations can evaluate software suppliers for potential weaknesses, to evaluate the risk of software they use to build their own applications.
Defining acceptable risk in the open-source supply chain Another way to manage risk when implementing open-source software is to define acceptable risk. This comes down to deciding whether the vulnerabilities presented by a particular application present an acceptable and controllable level of risk.
“Organizations that utilize open-source software, which today is every digitized business, benefit from developing and socializing an open-source strategy. A strategy provides guidelines on when open source can be utilized, what approval is required and what is acceptable risk to the business,” said Janet Worthington, Forrester senior analyst.
“Have a plan in place in the event a high-impacting security vulnerability is disclosed. Your development team may have to back-port a fix to the version of the open-source library that your organization depends on,” Worthington said.
Worthington highlights that organizations can start to codify and measure risk by creating an SBOM and maintaining an inventory of all software they acquire and download. In addition, security leaders should also ask suppliers to provide a description of their secure software development practices.
When it comes to open-source libraries, Worthington suggests that organizations should first look for an SBOM; if there isn’t one, then scanning it with a software composition analysis (SCA) tool can help to reveal vulnerabilities in the code. You can then see if updates or patches are available to mitigate it.
However, if you do choose to use an SCA to scan open-source components, it’s important to note that tools that use package managers to identify and scan packages are susceptible to missing software packages and vulnerabilities.
Moving beyond SCAs and SBOMs One of the core challenges of securing open-source software components in the enterprise is that they’re not static. Third parties can make changes to open-source software that, at a minimum, create new vulnerabilities, and at worse create actively malicious threats.
While Lisa O’Connor, global lead of security research at Accenture , notes the importance of static application security testing and SBOMs, she warns “we need to go much deeper to understand the risks.” “Researchers from Accenture’s Security Research and Development Labs are currently working on next-generation SBOM traceability to bring the sophistication needed to not only identify security threats, but to understand the downstream effects of vulnerability open-source functions on an organization’s actual installed codebase,” O’Connor said.
The organization’s Security Research and Development Labs are currently working alongside Professor David Bader from the New Jersey Institute of Technology ( NJIT ), an expert in knowledge graphs and analytics, to help improve how organizations identify and isolate vulnerable open-source components.
Understanding risk as the software supply chain evolves and moves is the key to mitigating open-source risk. Dynamic risks require an equally flexible mitigation strategy.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"NCA executive director shares top cybersecurity risks in 2023 | VentureBeat"
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"https://venturebeat.com/security/nca-executive-director-shares-top-cyber-risks-in-2023"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages NCA executive director shares top cybersecurity risks in 2023 Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Data security is all about thinking ahead, and with an international cyberwar and a generative AI revolution underway it can be difficult for security leaders to anticipate how the threat landscape will evolve.
Recently, VentureBeat conducted a Q&A with Lisa Plaggemier, executive director at the National Cybersecurity Alliance (NCA) , a former international marketer at Ford Motor Company and an ex-director of security, culture, risk and client advocacy for CDK Global , to discuss the top risks facing enterprise data in 2023 and beyond.
In this interview, Lisa shared her thoughts on the impact of the Russia-Ukraine war and cyber conflict, generative AI, quantum computing and API-based threats.
>>Follow VentureBeat’s ongoing generative AI coverage<< VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Below is an edited transcript.
Q: What do you see as the top threats facing enterprises in 2023? Plaggemier: “I think we’ll — for the most part — continue to see the same threats against the enterprise that we see every year.
Ransomware attacks, insider threats, identity access and elevation, business/vendor email compromise attacks and other social engineering attacks aren’t going away. Homing in on 2023 specifically though, I think we’ll see the following: New hacking targets “Attackers are going to start to more frequently target industry sectors that have yet to adapt to better incident-response protocols. Healthcare, critical infrastructure and financial services, for example, have been grappling with these threats for much longer.
“So, although attacks there will continue — and sufficient deterrence measures have a long way to go — bad actors are now seeking out more nascent spaces to execute low-tech, high-impact attacks within education, gaming, aviation and automotive. In fact, we’ve already seen several high profile DDoS attacks in the latter two categories in the last months. Expect that to continue.
Rise of adversarial AI “We’re likely to see cybercriminals using AI and ML models to create attacks that can eventually self propagate across a network or exploit vectors in datasets used to model ML frameworks. I think the generative AI arms race is definitely shining a light on how ubiquitous this technology is about to become. Attackers will naturally see that opportunities abound.
“For example, tactics could be as simple as using AI for deception (such as deepfakes and language-accurate phishing material) or as complex as creating and training AI to take malicious actions, make wrong decisions and collect and transmit user input data. In fact, there’s already evidence that hackers can infiltrate ChatGPT’s API and alter its code to generate malicious content — essentially skirting OpenAI’s moderation guardrails.
Vetting M&A risks “Despite economic circumstances likely cooling down cybersecurity investment and M&A this year, private data will continue to happen at a high enough rate that proper due diligence within the industry will remain paramount.
“More consolidation and enterprise security adoption means that the cost of a cybersecurity breach has ripple effects in terms of financial losses and damage to a company’s reputation. There’s going to be a greater reliance on processes that can reduce breach risks and protect the bottom line.
“Increased third-party risk management will play a major role in recognizing downstream vulnerabilities ahead of an acquisition, such as assessing SaaS/data sprawl within an organization, past relationships with breached security vendors and solutions or an insufficient history of vetting partners.
“We’ll also likely see a much stronger reliance on ‘paper trail’ tools like a software bill of materials (SBOM) to offer a detailed inventory of the components that make up a piece of software as means of identifying potential vulnerabilities and ensure better security-by-design prior to an acquisition.” Q: Any comments on how the Russia-Ukraine war will impact the cyberthreat landscape this year? Plaggemier: “One of the main dangers of a prolonged conflict between both regions is the collateral damage and spiller effects of the cyberwarfare tactics both countries employ.
“Russia has long been classified as a major APT threat against the U.S. and its allies, and we could see threat actors — either from within the country or groups contracted outside of its borders — executing attacks on any sovereign nations allied against it.
“That includes an increase in attacks on critical infrastructure, including power grids, financial systems and transportation networks. We could also see continued use of malware as a vehicle for espionage and data theft, alongside disinformation campaigns designed to subtly shape public opinion on the war (that is, via social media propaganda, weaponizing far-right wing channels and opinion, fake news articles and deep fake videos).
“And we could very well see continued targeting of software supply chains to weaken the security posture of any organization, public or private, that allies itself with Ukraine.
“These threats have been front-and-center since the war began — we’ll just continue to have to defend against them the longer it goes on. Emerging technology like generative AI could potentially make that more difficult.” Q: How do you see ChatGPT impacting the threat landscape? Plaggemier : “I think the most prevalent attack vector that we’ll see affecting companies and consumers most explicitly will likely revolve around ChatGPT’s use as a vehicle for generating more effective phishing and social engineering attacks.
“Bad actors can use it to create more convincing spear-phishing emails and texts despite language barriers to fool folks into giving up their data, or design more accurate copy for spoofed websites, links and attachments.
“And since attackers have altered the GPT-3 API to set up a restriction-free version of ChatGPT , they can use it to code malware, help them identify the best way to position phishing links in an email and more.
“Perhaps the worst part, however, is that all of these resources are made available to low-level hackers on the black market for purchase, alongside any data these efforts have already captured.” Q: How would you describe the role of the CISO in managing current threats? Plaggemier : “Recent data shows that 88% of boards of directors view cybersecurity as a business risk , which means the role of the CISO is very quickly being elevated from a bearer of bad news to an advisor to the entire organization and its employees on better data security practices.
“CISOs will be held more accountable and be required to take on more responsibility for educating the C-suite and boards of directors about why there needs to be greater investment in security policies, procedures, resources and training within the organization. And to do that effectively, the modern-day CISO is going to need to know how to communicate in both a technical and business sense.
“The CISO will also be tasked with doubling down on reporting and managing an organization’s defense posture in the eyes of executives, auditors and leadership as it pertains to risk.
“Business leaders will increasingly see the CISO’s function as a business enabler (better security means less operational disruption), thus extending a CISO’s responsibility to wrangle network security on connected devices, data privacy , physical security, compliance , governance, network security and education — all without pulling teams away from their core functions.
“The role is evolving into one that regularly has to walk the tightrope with executive and security/IT teams. It’s more nuanced and complicated than ever before, especially given the world’s decentralized workforces and increased digitization.
” Q: How can organizations better manage API-based threats? Plaggemier : “The latest T-Mobile breach was a pretty hard-hitting reminder about the dangers of API-based threats and a lack of vigilance on the part of a major company in minimizing that threat vector’s risk. I think there are multiple steps organizations can take to deter the success of these types of exploits, including: Taking inventory of all internal APIs to understand and address any potential vulnerabilities and ensure everything is well documented.
Cross-reference inventory with top OWASP vulnerabilities (broken object level authorization, broker user authentication, excessive data exposure) and remediate accordingly.
Implement better authentication and authorization protocols (such as the 0Auth 2.0 framework), validate and encrypt API requests to include only necessary information in user responses to minimize risk.
Log activity on a regular basis and conduct security tests to find any unseen security gaps.
Bring on a trusted vendor to improve API security standards in the long run and ease implementation company-wide.
“I also can’t stress the importance of more low-tech cybersecurity measures enough. These are more easily attainable processes that can offer a more solid foundation to build an effective security framework from.
“Processes like ensuring sufficient training protocols for employees to ID and minimize the success of BEC /VEC scams, implementing better identity access management solutions to regulate employee privileges around sensitive customer data and investing in data loss prevention and exfiltration measures, as well as instituting zero – trust policies for employees (always verify, never trust) can help shore up defenses without a major time or cost commitment.” Q: Any comments on post-quantum computing threats and the importance of quantum-safe solutions? Plaggemier : “I don’t think quantum computing presents an immediate cybersecurity threat in the very short term because the technology to facilitate true quantum computing capabilities just hasn’t caught up to the conceptual framework of what QC is capable of.
“That said, it’s not too far off to start thinking about what proper deterrence looks like, especially because the Biden administration has already begun looking at real-world scenarios and protocols with the Quantum Computing Cybersecurity Preparedness Act.
The projection is that we’ll see quantum computing reach critical mass in the next 5 to 10 years — an inflection point for cybercriminals.
“Typically, bad actors aren’t using the most bleeding edge methodology to make schemes work. There’s a reason that low-tech, high-yield tactics still make up the core of the hacker’s toolbox — because those tactics still work.
“The same way threat actors are using generative AI to bolster those low-tech methods, is likely what we’ll see with quantum computing once it’s at a place that has more practical applications. That said, current cybersecurity technologies, awareness and legislation efforts all need to scale proportionately and quickly to create a framework that can be used to deter QC capabilities.
“Quantum computing will be able to break current encryption methods. The enterprise and the government is going to have to better understand that increased investment into quantum-safe cryptographic systems and quantum-resistant algorithms and protocols minimize code-breaking, data theft and financial losses.” Q: What advice would you give to security leaders who are looking to enhance their organization’s security postures? Plaggemier : “First and foremost, do the basics extremely well. Depending on the size of the organization, security leaders are likely burdened with limited resources, coupled with the continued talent gap in the cybersecurity industry.
“For example, SMBs likely have much smaller budgets to invest in vendor tech stacks or hiring massive SOCs, so security leaders need to do more with less.
“This means better education and awareness initiatives that are entrenched in business culture, training to identify the low-tech tactics that create costly breaches and ransomware situations, and investing in an MSSP in the absence of a more robust internal security team.
“Enterprise companies can see massive value from the same lessons. At the same time, they should ensure that CISOs are better empowered and equipped to bolster the organization’s security posture.
“Additionally, they can build out an effective internal security team by properly compensating potential candidates, as well as investing in deterrence tech like network detection, identity access management, SIEM and more.
“Since SOCs typically operate reactively, investing dollars into technology that can give them better intelligence ahead of a potential incident is a major advantage.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Immuta and ServiceNow partner to tackle cloud data visibility crisis | VentureBeat"
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"https://venturebeat.com/security/immuta-servicenow-partner-tackle-cloud-data-visibility-crisis"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Immuta and ServiceNow partner to tackle cloud data visibility crisis Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
“Where is my organization’s critical data?” is the CISO’s million-dollar question. Today, security leaders need to be able to pinpoint what data assets exist and where, so they can implement access controls to protect them.
Unfortunately there’s a data visibility crisis in the cloud, with organizations reporting 55% of their data is dark and unidentified. This not only makes it difficult to generate insights, it leaves valuable data exposed and vulnerable to external threat actors.
Cloud security vendor Immuta aims to address this by automatically discovering and classifying data assets in the cloud. Today the company received a strategic investment of an undisclosed amount from ServiceNow , an extension to its $100 million Series E funding round last year.
With cloud adoption on the rise, the ability to detect and classify data assets wherever they exist in hybrid and multicloud environments is now foundational, not just for enterprise security, but for enabling decision-makers to derive insights from their data in a way that’s compliant.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Tackling the cloud data visibility crisis A core challenge for security leaders addressing the data visibility crisis is the need to be able to identify sensitive data in the cloud while implementing access controls to prevent unauthorized users from accessing it.
Implementing access controls is an area where many organizations are falling short. An Immuta survey of 600 data professionals found that 97% faced challenges in this area, with 54% reporting that securing data with appropriate access rights is one of their biggest hurdles.
“The underlying problem is that securing data in the cloud is overly complex,” said Matthew Carroll, CEO of Immuta. “Today organizations are managing massive amounts of data across many different databases. They also have a significant increase in the number of users that need to access that data.” He added, “At the heart of it, there is an exponential explosion of data policies to manage who can access what data. Yet the data is difficult to classify and tag. Thousands of data policies must be created and managed. And it’s nearly impossible to monitor how the data is used.” From a compliance perspective, if it can’t be monitored it can’t be used. Nowhere is this more illustrated than in the fact that one of Immuta’s customers, one of the largest banks in the U.S., had to shut down a data lake after just two years of operation because security and compliance teams had no visibility into what data it contained.
Immuta aims to avoid these scenarios through a trio of security solutions: Discover, which scans, classifies and tags sensitive data; Secure, which can design and enforce data access controls; and Detect, which continuously monitors data usage and analyzes the risk of leaks.
The idea is to equip CISOs and security leaders with a single tool they can use to identify and protect data assets in the cloud.
The data security market Immuta’s solution falls within the big-data security market, which Allied Market Research valued at $13.7 billion in 2019 and is projected to grow to $54.2 billion by 2027 as organizations turn to data analytics to enhance their decision-making on protecting their data assets.
One of Immuta’s main competitors is Okera , which uses machine learning to automatically classify and tag sensitive data in the cloud, with the option to de-identify, mask, tokenise, encrypt or anonymize user data.
Okera is currently valued at $29.6 million following a $15 million funding round led by ClearSky Security in December 2021.
Another competitor is Privacera , a data security and access control provider offering a platform to automatically discover data and automate data governance processes to support compliance with SOX, PII, PCI, CCPA, HIPAA, FISMA and the GDPR.
Privacera most recently raised $50 million in funding with a Series B funding round in 2021.
According to Carroll, the main differentiator between Immuta and its competitors is its use of attribute-based access control.
“Immuta leverages attribute-based access control (ABAC), rather than the traditional role-based access control (RBAC), which according to a recent GigaOm report reduces policy burdens by 93 times and can save organizations roughly $500,000 in time and opportunity costs,” Carroll said.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"How to use zero trust and IAM to defend against cyberattacks in an economic downturn | VentureBeat"
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"https://venturebeat.com/security/how-to-use-zero-trust-and-iam-to-defend-against-cyberattacks-in-an-economic-downturn"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages How to use zero trust and IAM to defend against cyberattacks in an economic downturn Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Despite double-digit budget increases, CISOs and their teams are scrambling to contain increased internal breaches, embezzlement and fraud. Identities are the attack vector of choice during a recession, exacerbated by inflationary costs driving up the cost of living, making phishing emails’ false claims of easy money all the more alluring.
As one CISO confided to VentureBeat in a recent interview, “recessions make the revenue-risk aspects of a zero-trust business case real, showing why securing identities deserves urgency.” Attackers use machine learning (ML) algorithms to create and launch malware-free intrusions. These account for 71% of all detections as indexed by the CrowdStrike Threat Graph.
The latest Falcon OverWatch Threat Hunting Report illustrates how attack strategies aim for identities first. “A key finding from the report was that upwards of 60% of interactive intrusions observed by OverWatch involved the use of valid credentials, which continue to be abused by adversaries to facilitate initial access and lateral movement,” said Param Singh, VP of Falcon OverWatch at CrowdStrike.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! CrowdStrike’s acquisition of Reposify reflects how leading cybersecurity platform vendors concentrate on adopting new technologies to provide external attack surface management while protecting enterprises against internal threats.
Reposify scans the web daily for exposed assets, enabling enterprises to have visibility over them and defining which actions they need to take to remediate them. At last year’s Fal.Con event, CrowdStrike announced plans to use Reposify’s technology to help its customers stop internal attacks.
Identity attacks soar in a down economy Identity-based breaches interrupted 78% of enterprises’ operations last year, and 84% said they experienced an identity-related breach.
Identities are a core attack vector for attackers in a down economy; their strategies are to gain control of an organization. Attackers’ favorite targets are legacy identity and privileged access management systems that rely on perimeter-based security that often hasn’t been updated in years. Once in, attackers immediately grab admin rights, create fraudulent identities and begin exfiltrating financial data while attempting cash transfers.
Attackers are using ChatGPT to fine-tune social engineering attacks at scale and mine the data to launch whale phishing attacks.
Ivanti’s State of Security Preparedness 2023 Report found that nearly one in three CEOs and members of senior management have fallen victim to phishing scams, either by clicking on the same link or sending money.
Identities are under siege during periods of economic uncertainty and recessions. CISOs fear that internal employees will be duped out of their passwords and privileged access credentials by social engineering and phishing attacks — or worse, that they may go rogue.
CISOs, internal security analysts staffing security operations centers (SOCs) and zero-trust leaders have told VentureBeat that a rogue IT employee with admin privileges is their worst nightmare.
Snowden a cautionary tale Those CISOs willing to discuss the issue with VentureBeat all referenced Edward Snowden’s book Permanent Record as an example of why they’re so concerned about rogue attackers.
One CISO cited the passage: “Any analyst at any time can target anyone. Any selector, anywhere I, sitting at my desk, certainly had the authorities to wiretap anyone, from you or your accountant to a federal judge, to even the President.” “We’re always looking for fuel to keep our senior executives and board funding zero trust, and the passages in Snowden’s book are effective in accomplishing that task,” one cybersecurity director told VentureBeat.
A core tenant of zero trust is monitoring everything. The Snowden book provides a cautionary tale of why that is essential.
System and security admins interviewed by VentureBeat admit that internally launched cyberattacks are the hardest to identify and contain. A stunning 92% of security leaders say internal attacks are equally as complex or more challenging to identify than external attacks. And, 74% of enterprises say insider attacks have become more frequent; more than half have experienced an insider threat in the last year, and 8% have experienced more than 20 internal attacks.
Why CISOs are fast-tracking IAM implementations CrowdStrike CEO and cofounder George Kurtz commented: “Identity-first security is critical for zero trust because it enables organizations to implement strong and effective access controls based on their users’ specific needs. By continuously verifying the identity of users and devices, organizations can reduce the risk of unauthorized access and protect against potential threats.” Kurtz told the audience at his keynote at Fal.Con 2022 that “80% of the attacks, or the compromises that we see, use some form of identity and credential theft.” CISOs interviewed for this story say they’re fast-tracking identity access management (IAM) in response to the rise in internal attacks, the high cost of misconfigured identities and new attack strategies from the outside aimed at their IAM, PAM and Active Directory platforms.
The highest priority is IAM proofs of concept and the fast-tracking of pilots to production servers in response to more aggressive attacks on legacy tools without advanced security features, including vaults.
Leading IAM providers include AWS Identity and Access Management , CrowdStrike, Delinea , Ericom, ForgeRock, Google Cloud Identity , IBM Cloud Identity , Ivanti and Microsoft Azure Active Directory.
Steps CISOs take to get quick value from IAM Getting the most value from IAM implementations is considered core to CISO’s zero-trust network access (ZTNA) frameworks and operating philosophy. This is made all the more urgent by economic uncertainty and a forecasted recession.
Stopping the zombie credential epidemic by auditing all existing access credentials and rights A common mistake is to import all existing credentials from an existing legacy identity management system into a new one. CISOs must budget time to audit every credential and delete those no longer needed.
Ivanti’s study found that 45% of enterprises suspect that former employees and contractors still have active access to company systems and files. This is often because de-provisioning guidance wasn’t followed correctly, or because third-party apps offer hidden access even after credentials have been inactivated.
“Large organizations often fail to account for the huge ecosystem of apps, platforms, and third-party services that grant access well past an employee’s termination,” said Ivanti chief product officer Srinivas Mukkamala. “We call these zombie credentials, and a shockingly large number of security professionals — and even leadership-level executives — still have access to former employers’ systems and data.” Multifactor authentication (MFA) adoption is critical early on in an IAM launch MFA must be first designed into workflows to minimize the impact on user experiences. Next, CIOs need to drive identity-based security awareness while also considering how passwordless technologies can alleviate the need for long-term MFA.
Leading passwordless authentication providers include Microsoft Azure Active Directory (Azure AD) , OneLogin Workforce Identity , Thales SafeNet Trusted Access and Windows Hello for Business.
Enforcing identity management on mobile devices has become a core requirement, as more workforces will stay virtual. Of the vendors in this area, Ivanti’s Zero Sign-On (ZSO) is the only solution that combines passwordless authentication, zero trust and a streamlined user experience on its unified endpoint management (UEM) platform.
Ivanti designed the tool to support biometrics — Apple’s Face ID — as the secondary authentication factor for accessing personal and shared corporate accounts, data and systems. ZSO eliminates the need for passwords by using FIDO2 authentication protocols.
CIOs tell VentureBeat that Ivanti ZSO is a win because it can be configured on any mobile device and doesn’t require another agent to be loaded and patched to stay current.
Require identity verification before granting access to any resource The latest generation of IAM platforms is designed with agility, adaptability and integration to a broader cybersecurity tech stack via open APIs. Take advantage of how adaptive new IAM platforms are by requiring identity verification on every resource, endpoint and data source.
Start tight with controls and allow access only on an exception basis where identities are closely monitored and validated. Every transaction with every resource needs to be tracked. This is a core part of having a zero-trust security mindset. Being rigorous about defining identity verification will reduce unauthorized access attempts by employees, contractors or other insiders, shielding an organization from external threats by requiring identity verification before granting access.
Configure the IAM so no human can assume a machine’s role, especially in AWS configurations This is core to zero trust because human roles on an AWS platform need to be constrained to least privileged access.
From DevOps, engineering and production teams to outside contractors working in an AWS instance, never allow human roles to intersect or have access to machine roles. Not getting this right increases the attack surface and could lead to a rogue employee or contractor capturing confidential revenue data through an AWS instance without anyone ever knowing. Audit every transaction and enforce least privileged access to avoid a breach.
Monitor all IAM activity down to the identity, role and credential level Real-time data on how, where and what resources that each identity, role and credential is accessing — and if any access attempts are outside defined roles — is core to achieving a zero-trust security framework.
CISOs tell VentureBeat that it’s essential to consider identity threats as multifaceted and more nuanced than they initially appear when first discovered through monitoring and threat detection. An excellent reason to monitor all IAM activity is to catch potential misconfigurations and resulting vulnerabilities in the identified areas of the tech stack.
One manager of an SOC for a financial services firm told VentureBeat that monitoring saved their company from a breach. An attacker broke into several employees’ cars and stole their badges and any access credentials they could find — including laptops — then used them to access the company’s accounting systems. The intrusion was blocked immediately with monitoring, as the employees had told IT that their laptops had been stolen earlier that week.
Being safe in an economic downturn begins with identities CISOs, CIOs, SOC managers and analysts tracking alerts and threats say the gaps left by legacy identity management systems are the weakest security link they have to deal with during down economic times.
Legacy IAM systems were used primarily for preventative control, but today every organization needs a more cyber-resilient approach to protecting every machine and human identity in their business.
IAM implementations are being fast-tracked to ensure that only legitimate users’ identities have least privileged access to the resources they need to do their jobs. The goal of preventing unauthorized users from accessing the network begins by getting rid of zombie credentials.
Monitoring user activities is a must-have for any IAM implementation, as it can stop a breach in certain situations and prevent fraud before it starts.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"How threat intelligence helps SecOps prevent cyberevents before they happen | VentureBeat"
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"https://venturebeat.com/security/how-threat-intelligence-helps-secops-prevent-cyberevents-before-they-happen"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages How threat intelligence helps SecOps prevent cyberevents before they happen Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
CISOs tell VentureBeat they’re looking to get more value from security operations (SecOps) by identifying threats rather than analyzing them after an event.
Gartner’s direction is that “SecOps’ goal is to create proactive risk understanding and enable threat exposure reduction as well as detection of, and response to, cyber events that negatively affect the organization.” SecOps teams need help to get out of a reactive approach of analyzing alerts and intrusion, breach and botnet events after they’ve occurred. As a first step to solving this challenge, enterprise security teams and the CISOs that lead them are pushing for greater real-time visibility. In addition, tech-stack consolidation, a strong focus on minimizing costs, and the need to stand up remote SecOps locations faster than on-premises systems and their infrastructure allow are driving SecOps teams’ need for threat intelligence and more real-time data.
Improving SecOps with real-time threat intelligence For SecOps to deliver on its potential, it must start by reducing false positives, filtering out inbound noise, and providing threat intelligence that triggers automated detection and remediation actions. In short, SecOps teams need threat intelligence providers to interpret and act on inbound packets immediately, finding new ways to capitalize on real-time data. Fortunately, the next generation of threat intelligence solutions is purpose-built to provide post-attack analytics, including forensic visibility across all events.
The National Institute of Standards and Technology (NIST) defines threat intelligence as “threat information that has been aggregated, transformed, analyzed, interpreted, or enriched to provide the necessary context for decision-making processes.” NIST mentions threat intelligence in their NIST SP 1800-21 , NIST SP 800-150 , and NIST SP 800-172A standards.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Leading vendors include Centripetal , whose CleanINTERNET solution operationalizes cyberthreat intelligence at scale by combining automated shielding, advanced threat detection (ATD) and dedicated teams of human threat analysts. Centripetal’s customer base includes government agencies, financial institutions, healthcare providers and critical infrastructure providers.
“Threat intelligence, if you apply it properly, can become a highly effective tool to determine automatically who should come into your network and who should not, and thus gives an organization risk-based control,” said Centripetal’s CEO, Steven Rogers.
There are more than 75 vendors in the threat intelligence market today, including CrowdStrike , Egnyte , Ivanti , Mandiant , Palo Alto Networks , and Splunk.
All strive to strengthen their threat intelligence as core to their ability to contribute to their customers’ SecOps needs.
Centripetal’s architecture is noteworthy in its use of artificial intelligence (AI) and proprietary algorithms to aggregate, filter, correlate, detect, triage and analyze thousands of global feeds at massive scale and machine speed. AI acts as an orchestration technology in their platform, coordinating threat intelligence feeds and enforcement algorithms and simultaneously reporting to both Centripetal’s internal cyberthreat analyst team and that of the customer.
Scaling threat intelligence in the enterprise VentureBeat recently sat down virtually with Chuck Veth, president of CVM, Inc.
, to learn how enterprises are putting threat intelligence to work and how his firm helps their implementations scale. CVM, an IT services firm with more than 30 years of experience, is a two-time winner of Deloitte’s CT Fast 50. Chuck’s firm implements and supports Centripetal and is a leading reseller to enterprise and government accounts. Presented here are selected segments of VentureBeat’s interview with Chuck: VentureBeat: What challenges do your customers face that led you to contact Centripetal to be a reseller for them? Chuck Veth: “ The challenge to enhance cybersecurity is constant. We first learned about Centripetal from one of our accounts. After evaluating it and presenting it to our customers, we realized that the CleanINTERNET service is an excellent final layer of security for public-facing networks. We look at it as a necessary insurance policy. When you turn on CleanINTERNET, it gets used thousands of times a minute.” VB: Keeping with the insurance analogy, can you expand on how you see the value Centripetal provides? Veth: “ It’s not like car insurance; you can do the math easily on asset protection insurance. It’s more like the car insurance component that covers damage to the occupants, which you typically don’t think about when you’re evaluating car insurance. You’re thinking about your car. But the truth is, car insurance is really there for the people because they’re irreplaceable. When thinking about network security, you mainly approach it from the packet inspection perspective. Centripetal’s CleanINTERNET service works from a completely different perspective. It is determining if the remote IP address is a threat actor; if it is, it blocks it. You need to use this perspective as well; the cost of missing a threat actor can close your business.” VB: What are some of the most valuable lessons learned regarding how Centripetal provides greater threat intelligence of your shared customers with them? Veth: “One of the most exciting outcomes of having the Centripetal CleanINTERNET service is its ability to separate a threat actor from a non-threat actor on some very common pathways of the internet. HTTPS traffic travels on port 443, HTTP on port 80, and email travels on port 25, et cetera. Years ago, when some services lived on relatively unique ports, they were easy to monitor for an attack. Today it’s harder as the industry has moved to a world that lives on a handful of ports, like 443, using SSL certificates.
“For example, individuals on private networks often turn to public proxy server websites to avoid corporate filtering, such as blocking day trading. The user connects to the proxy service, and it connects their browser to the day trading site. All the user needs to do is find a proxy service that is not blocked by their company firewall. Bad actors often operate these proxy services as they can track every detail of the online activity.” VB: That’s the danger of using a proxy service that isn’t verified to visit a site your company has blocked. How does threat intelligence help identify the threat and protect infrastructure? Veth: “Centripetal is looking at the IP address and saying, ‘I have a list of billions of IP addresses that are known to be operated by threat actors.’ It’s a different way of looking at things. And, to do it correctly, Centripetal compiles real-time information from hundreds upon hundreds, even thousands, of threat intelligence feeds. And that’s the secret sauce of the Centripetal CleanINTERNET service. They are normalizing the data from thousands of real-time threat intelligence feeds to say, ‘Hey, this particular site popped up in three or four different threat intelligence databases. And for us, that is a sign that it is a threat actor. And so, we’re going to block it.’” VB: What’s your favorite example of how effective Centripetal is at uncovering bad actors’ attack strategies that are cloaked to avoid detection? Veth: “One day, we got a note from our Centripetal security analyst, ‘…this threat actor’s trying to communicate with this customer – it’s a known threat actor operating out of Europe – it’s this IP address….’ We’re an IT firm, so we looked up the IP address, and the IP address was at a hosting facility in New York.
“And we’re like, ‘What? Why did our security analyst tell us that this IP address was in this foreign country when one of our staff found that it’s in New York?’ We browsed to the IP address. It was a hosting company in New York that only takes payment via cryptocurrency and requires no audit to host on its service. So any host can sign up for this service with no authentication. But the Centripetal device knew that this site, although hosted in New York, was a threat actor from a foreign country. This would have never been blocked by geofiltering, but the Centripetal service was able to identify it and block it.” How threat intelligence enables zero trust Having threat intelligence add value in a zero-trust framework requires identifying and classifying threats before they gain access to a corporate network. Interpreting every data packet and then evaluating its level of risk or trust is essential — while factoring in and correlating to all known global threat feeds in an adaptive, customizable service. Identifying and classifying threats before they reach the network is core to the future of threat intelligence and the ability for SecOps to migrate to a zero-trust framework.
Threat intelligence needs to do the following to increase its value to zero-trust initiatives: Enforce zero trust by inspecting every packet of bidirectional traffic Vendors are setting service goals that center on their ability to shield their customers’ organizations from all known attacks. Each of the competing vendors in threat intelligence is taking a different approach.
Continually improve the real-time visibility across the known threatscape Most threat intelligence vendors are more focused on analyzing the data from previous events. A few have proven exceptional in using machine learning algorithms to look at predictive patterns in traffic and attack data. What’s needed is a threat intelligence system that can aggregate the data of every inbound packet, then correlate the analysis results with known threats. Centripetal compares each packet’s contents to all available cyberthreat indicators in real time, using thousands of global threat feeds to support their single, fully managed service.
Reduce false positives, inaccurate alerts and events by verifying every access attempt before it gets inside the corporate network A core tenant of zero trust is to assume the network has already been breached and the attacker needs to be contained so they can’t laterally move into core systems and do damage. Leading threat intelligence system providers are applying machine learning algorithms to reduce the noise from external networks, filtering out extraneous data to find the actual threats. Besides contributing to the zero-trust initiatives of an organization, it helps reduce the burden on the security operations center (SOC) in having to clear false positives and alerts.
SecOps must improve at delivering business-driven outcomes based on real-time data insights, learning to be more adaptive and quicker to respond at scale. As part of the next generation of threat intelligence solutions, companies like Centripetal support SecOps teams by specializing in providing threat intelligence to reduce false positives, filter out inbound noise and trigger automated detection and remediation actions.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Cloud security provider Wiz raises $300M for consolidated CSPM/CNAPP platform | VentureBeat"
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"https://venturebeat.com/security/cloud-security-provider-wiz-raises-300m-consolidated-cspm-cnapp-platform"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Cloud security provider Wiz raises $300M for consolidated CSPM/CNAPP platform Share on Facebook Share on X Share on LinkedIn A photo of the Wiz team Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Cloud technology has changed the data economy. Data is no longer locked in on-premise silos and servers, but traverses through a dynamic patchwork of cloud service providers, apps, APIs and containers. An unchecked vulnerability or misconfiguration in any of these components can leave critical data exposed. That’s why consolidated cloud security is now essential.
It’s a reality few organizations are prepared to confront, with the average organization using six tools to secure the cloud. A number of cybersecurity vendors are looking to address these challenges by offering a more consolidated approach to cloud security.
One such provider is Wiz , which today raised $300 million as part of a Series D funding round. Wiz provides cloud security posture management (CSPM) and a cloud-native application protection platform (CNAPP) designed to enable security teams to monitor cloud services, APIs and containers for vulnerabilities and misconfigurations.
The latest funding round, led by Lightspeed Venture Partners and Greenoaks Capital Partners, brings Wiz’s valuation to $10 billion and makes it the largest cyber-unicorn, highlighting the fact that investors see securing the cloud as the definitive challenge in protecting enterprise data.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Consolidating cloud security Traditional approaches to cybersecurity simply don’t work in decentralized cloud environments.
Research from Venafi finds that 81% of organizations experienced a cloud-related security incident in the last 12 months, with 45% suffering at least four incidents.
There are many reasons for the high rate of cloud breaches, from a cloud skills gap to under-resourced security teams. But perhaps the most significant cause is lack of visibility over data assets and exposures. Most organizations simply don’t have the ability to identify vulnerabilities and misconfigurations across the attack surface.
“ Cloud is agile and dynamic — this is the reason it enables companies to grow so fast. However, this is also why it is so hard to secure the cloud. It keeps changing,” said Assad Rappaport, cofounder and CEO of Wiz.
“How can you secure data in the cloud, if it can be stored in dozens of services, routed daily to different places and systems? Legacy approaches completely fail to handle the complexity and agility of cloud. Cloud requires a cloud-native approach,” Rappaport said.
Wiz’s answer to securing the cloud is to consolidate CSPM and CNAPP capabilities into a single platform alongside data security posture management, external attack surface management (EASM) and cloud detection and response (CDR). This combination is designed to help organizations augment and streamline their detection and response capabilities for threats across the cloud.
For instance, security teams can continuously scan for misconfigurations across hybrid cloud environments, infrastructure as code (IaC) and containers, and automatically remediate potential exploits that expose data to threat actors.
The platform also provides a security graph that triages and correlates attack paths so that both developer and security teams can understand the cause of a breach and identify how to respond quickly.
A brief look at the CNAPP market Wiz’s solution falls within the global CNAPP market , which researchers valued at $7.8 billion in 2022 and estimate will reach $19.3 billion by 2027 as more organizations realize their cloud adoption plans.
The organization is competing against some established companies in the space, including Palo Alto Networks, which offers its own CNAPP called Prisma Cloud.
Prisma Cloud offers real-time inspection of cloud workloads for misconfigurations and vulnerabilities, using machine learning to identify normal baseline activity, and generating alerts to highlight anomalous activity. Palo Alto Networks earned $84.2 million in revenue last quarter.
Another competitor is Lacework , which offers a CNAPP with infrastructure as code (IaC) scanning, runtime vulnerability scanning for workloads, container images, hosts and language libraries, as well as anomaly detection-based threat detection. Lacework is currently valued at $8.3 billion.
Rappaport argues that the key differentiator between Wiz and these solutions is its emphasis on managing risks in real time.
“Wiz has introduced a new approach, one that enables the business to embrace the cloud securely by continuously identifying and reducing the risks that matter. Wiz is rolled out in minutes via an agentless, API-centered approach to seamlessly scan workloads and give full visibility of cloud environments,” Rappaport said.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"4 ways ChatGPT can radically up your job search | VentureBeat"
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"https://venturebeat.com/programming-development/4-ways-chatgpt-can-radically-up-your-job-search"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Sponsored Jobs 4 ways ChatGPT can radically up your job search Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Job hunting can be a lot of stress, as well as a lot of work. It can take a lot of time too — according to the Bureau of Labor Statistics, the average job search takes roughly five months.
With a lot of talent freshly released into the labor market thanks to the swathe of layoffs currently affecting the tech industry — Layoffs.fyi data indicates that there have been in excess of 108,000 job cuts so far this year — honing a competitive advantage is essential.
One small glimmer of relief for those in the tech sector in particular is the fact that laid-off tech professionals are able to quickly find new work. A recent survey found that 79% of those laid off from a tech company job got a new job within three months of starting their search, and nearly four in 10 of them found jobs in less than a month.
That’s positive news, but what else can you do to speed up and improve your job search? VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Enter ChatGPT. A natural language processing chatbot, it is driven by AI technology that allows you to ask it questions, have surprisingly human-like conversations, and get answers to complex topics.
The chatbot can also be used in many ways to help you get a new job both pre-application and for interview prep. Here are four ways you can make ChatGPT work for you.
1. Identifying keywords in job descriptions Job applicants often don’t understand how important it is to use keywords from the job description in their resume. This is because a huge number of hiring professionals use software called application tracking systems (ATS) to weed out resumes as an initial step. Over 98.8% of Fortune 500 companies use ATS, as do 66% of large companies, and 35% of small organizations.
Paste a job description into ChatGPT and then ask it to tell you the three to five most important responsibilities. This will give you actionable keywords to include in your resume, and beat the bots.
2. Personalize your resume and cover letter Yes, ChatGPT can also create personalized versions of your resume, tailored to the job description. This is another important step to take as it elevates your resume from the basics and makes it highly relevant.
Do the following three things: Ask ChatGPT to “personalize my resume for this [Job Title] role at [Company]”. Then paste in the job ad, and paste in your current resume. Do take time to edit the results so that they are appropriate for the role, and personalized for you.
The tool can also help with cover letters, offering a structured style and format you can tweak. Ask it to “write a cover letter for a Java developer job”, and you’ll get back a surprisingly useful piece of copy––albeit one that will need some tweaking and extra information from you.
3. Help you understand complex terms It’s interview time and you’re applying for a stretch role. Some of the concepts in the job description aren’t ones you are familiar with. ChatGPT can help: ask it to explain a complex topic or technical jargon you’re not familiar with, and it will return a succinct, plain English explanation that can really help you out.
4. Write interview questions Another dreaded aspect of the interview process is the bit where you’re asked, “do you have any questions for us?” Yes: you do. You can ask it to generate questions in a variety of ways — request the most common questions to ask at an interview, or ask it for personalized suggestions based on the job description, which you can paste in.
While this is a tool that can automate parts of a job search, it’s important to keep front of mind that it’s not a replacement for you; after all, it creates its answers from data sets. Carefully edit its responses, adding your own personal touches, and you’ll get the best from the bot.
Ready to give ChatGPT a shot? There are three exciting roles to discover below, with many more on the VentureBeat Job Board.
Senior Enterprise Account Engineer, Amazon Web Services, Inc., Herndon As a Senior Enterprise Account Engineer , you will craft and execute strategies to drive customers’ adoption of AWS services. You’ll have technical acumen and customer-facing skills and will drive discussions with senior leadership regarding incidents, trade-offs, support and risk management. To apply, you will need six years’ of technical engineering experience, experience with operational parameters and troubleshooting for three of the following: compute; storage; networking; CDN; databases; DevOps; big data and analytics; security; or applications development in a distributed systems environment.
Get the full job spec right here.
AI Research Director — AI for Tech, JPMorgan Chase Bank, New York The AI Research Director will work on multiple research projects, formulating problems, generating hypotheses, developing new algorithms and models, conducting experiments, synthesizing results, gathering data, building prototypes and communicating the significance of research. To apply, it’s preferred that you have a PhD in computer science (especially AI/ML) or related fields, have research publications in prominent AI/ML or software engineering venues such as conferences and journals, and possess strong expertise in one or more specialized areas: deep learning (DL), or natural language processing (NLP).
Discover all the requirements here.
Cybersecurity Project Manager, Apple, Cupertino The Cybersecurity Project Manager will lead the planning and execution of an end-to-end cybersecurity assessment/audit process, providing operational support, and contributing to documenting controls and processes. You’ll also provide leadership and transparency throughout the program lifecycle, and ensure program deliverables meet expectations. Necessary skills include three to five years’ of experience in project management, preferably in cybersecurity, and experience leading large projects, with the ability to create project plans.
Apply for this position here.
Get a great new job on the VentureBeat Job Board today VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"How BMW's Designworks churns out 300 product designs a year | VentureBeat"
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"https://venturebeat.com/games/bmw-designworks-qa"
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"Game Development View All Programming OS and Hosting Platforms Metaverse View All Virtual Environments and Technologies VR Headsets and Gadgets Virtual Reality Games Gaming Hardware View All Chipsets & Processing Units Headsets & Controllers Gaming PCs and Displays Consoles Gaming Business View All Game Publishing Game Monetization Mergers and Acquisitions Games Releases and Special Events Gaming Workplace Latest Games & Reviews View All PC/Console Games Mobile Games Gaming Events Game Culture How BMW’s Designworks churns out 300 product designs a year Share on Facebook Share on X Share on LinkedIn BMW Designworks head Holger Hampf shows off the new studio in Santa Monica, California.
Are you looking to showcase your brand in front of the brightest minds of the gaming industry? Consider getting a custom GamesBeat sponsorship.
Learn more.
BMW recently located its Designworks product design studio to the heart of Silicon Beach in Los Angeles. BMW recently opened the studio in Santa Monica, California, to the press to celebrate its 50 years of designing cars, media and other technology-based products.
Its mission from the BMW Group is not only to design the latest automobile concepts but also deliver cross-industry designs for external clients and stay at the forefront of innovation, design and sustainability. The BMW team talked about designs like the BMW i Vision Dee concept car that can change into 32 different colors on the fly, and it showed off its BMW M Hybrid V8 race car.
Adrian van Hooydonk, senior vice president of BMW Group Design, came from Munich, Germany for the occasion to show how design inspiration and user centricity should lead industries such as mobility, transportation, consumer electronics, charging infrastructure and interior spaces.
He joined Holger Hampf, head of the Designworks studio, for a group press Q&A during the event at the 16,500-square-feet studio.
Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! The studio has 150 people, in addition to other big teams in Shanghai and Munich, to work on designs for BMW as well as external clients with an “outside in” perspective. It completes around 300 designs a year and that helps it stay informed about the forefront of industry and see patterns across different markets. It’s a model, started by Chuck Pelly in Malibu in 1972, that has worked for decades.
Here’s an edited transcript of the press Q&A.
Question: For your outside companies that you work with and the products you work with, how do you take that knowledge and interaction with the materials you use for those things and translate it to automotive design for BMW? Adrian van Hooydonk: Holger can talk more about that, but first of all, these companies need to know that what we do for them is provide designs to them. That’s the way it works, also from a contract point of view. What it does in any case is that it gives our designers a more complete view on the future. If we do work for other companies, typically that also has a development or lead time to production of about three years. A good idea, if you’re working on an electronic device or an airplane interior–those kinds of products will develop in three or four years’ time. That happens to be the lead time for our car design as well.
The designers typically do mood boards based on things they see today. We now have mood boards about the future. That, I think, is an incredible value. We can offer that to our outside clients as well. Our designers know how we think about mobility in three to four to even ten years’ time. That gives them an opportunity to check whether these things seem to line up. Some industries are far apart, so it’s just peripheral, let’s say. Sometimes it’s close, if they’re both in mobility. You can draw some parallels. But it works both ways in that sense, without ever having to show what we do for another company to the board of BMW. They never see it. But it gives us, as a design team, a more complete image or a more complete mood board about the future, if you will.
Holger Hampf: It doesn’t necessarily need to be–it usually never is a direct translation of what we do with external clients to BMW. But number one, I think, there’s a very subtle indirect translation, which is the knowledge of the market, the broader view that is translated to automotive design. Again, the expectations and the desires in a car are important, and they’re formed from other fields.
One very good example we like to use is air travel, traveling in first class or business class. You have a very personal space, I would say, in a cabin. You have a combination of different functions such as entertainment, ergonomics, seating comfort. During a long-distance flight you sleep, you eat, you read, you entertain, you work on your computer. We’ll never design a business class seat in a car, but when you travel in the second row of a 7-series, we inform ourselves about how people like to travel, what they like to do, how we can design certain features in the car. The latest 7-series, as you know, has a very sophisticated entertainment system, a very large screen. It’s very desirable for customers.
Again, it’s not a direct translation from air travel. However, we learn a lot about people wanting a nice screen size, the resolution, good audio. We inform our work this way.
Question: I’m a little confused around how much juggling you do. Three hundred designs a year, 130 people, but many of these take multiple years to do. That sounds like a design a day that’s coming out.
Hampf: There are different sizes of program, first of all. Not all of them are–some are smaller material programs within the number 300. Those are independent proposals. Half of them are for BMW and half of them are for the broader BMW group and external clients. Different size programs. A lot of programs are going on in parallel. Some are paused for a while because they go into a development phase.
To your point about juggling, I can say that in the background – and it’s the same for BMW – when we started the year 2023, we looked at a very complex project landscape together. Right now I have to say that it seems like our world has gotten a bit more complex than it was in the last few years. The landscape has gotten a little more complex as well. That’s the art, I think, behind it. We talk about triangular relationships at Designworks. The creative is one part of the puzzle. But very good project management and organizing, the people who structure all of this, is equally important.
van Hooydonk: Worldwide we have 700 team members. Then we have the Designworks studio in Shanghai, this one here in Los Angeles, and the one in Munich. We have a design studio in Goodwood. Then we have several design studios in Munich. You can imagine the project workload. We do several hundred projects in a year. Like Holger said, the project landscape is quite daunting. Some projects get stopped and new ones come in, so you also have to calculate a certain flexibility.
But we have very good project management. Sometimes I feel that we have a creativity machine. For the designer, they have to feel free within a given project. If you feel pressure all day long, you can no longer be creative. The designer should be able to think about the project in terms of creativity. Someone else will take care of the budget and the timing issues. We also have a good team that enables the creative team to do just that.
It’s complex. We built it over many years. Thankfully we didn’t have to put it together in two weeks. We keep adjusting. We keep learning. We keep changing our processes as we go along. Each year we know that there are certain areas of our process that we have to review and change. Only in this way can we keep delivering this kind of creativity. I’m always impressed by how, at the end of the year, we’ve managed another year of all that. In the middle it sometimes feels quite stressful.
Question: Do you notice a different design aesthetic, different design requests depending on the area of the world, with respect to mobility? What are you getting from here versus Europe versus Shanghai? van Hooydonk: We want to hear exactly that from the studios in the various locations. That local feel. They’re all working on BMWs or Minis or Rolls-Royces, but still, there are cultural differences. Society, in some cases, is changing fast. If you talk about China, in terms of the digital parts of life, they’re ahead of most other parts of the world. It happens much faster there. If you go to a restaurant in Shanghai and have dinner with a group of people, you never see a menu. Nobody pulls out a wallet. It all happens automatically. And my last experience was three years ago. I haven’t been there in quite some time. I’m going back later this year. Translating that to mobility is the task at hand. In China we have customers that are used to that level of digital comfort. They’ll expect that from our products. That gets filtered into the design.
Then you see electric mobility happening all over the world, but with various speeds of change. Here it’s very present. In China it’s very present. Europe is catching on. You see some local differences. You also see, or begin to see, luxury changing. It’s becoming more and more personal, more individual. Those are interesting things.
We always do a design competition between all of the studios. Specifically, we ask the studios to bring in everything that they learn and see in their local market. But in the end, we have to make one Mini for the world, one BMW for the whole world. We have to come to the right mixture of design that we feel will suit all the markets.
Question: Is that design competition just for vehicles, or is it any project that comes into Designworks? Hampf: It’s for several aspects of the car. We talked earlier about new things such as sound or scent in a car. Other interior aspects like lighting. We’re well on our way to finding the common thread across all of these singular experiences. We’ve all had experiences with products that have very good styling. They look beautiful. But they don’t function very well. Or they have certain aspects that don’t work well. We’re frustrated and we say that the whole thing doesn’t work.
What we’re trying, and I think it’s working well, is to make sure that you have a holistic experience with a product like a car. It’s not only the styling that looks good. When you get in, the ergonomics of the cabin welcome you. The ease of connecting with the car. All of these things, these little things, need to be very well-connected in the future. The car can look as beautiful as we want it to. If the UI doesn’t work, the whole thing fails.
Question: It’s not just that one office says, “This is our winning design,” then? They might take the interior from one and the exterior design from another.
Hampf: Right. We’re looking at these different proposals. Sometimes we see that China has a leading interior concept for something. We take that forward and see if we can combine these things. The China interior proposal is really good and it fits well with what we’ve seen from the team in Munich, something like this.
It’s definitely changed a lot. Where we would associate an individual with a design, that was the past. Today it’s purely seen as a team effort. People don’t have any problems with their part becoming part of the bigger picture and solution. It’s working quite well, this BMW team effort. Also in regards to how Designworks integrates with the design team in Munich. These boundaries or this idea of “my design” are gone. We have one signature and it says BMW Design or Mini Design. That’s it. People have not only accepted this, but actually praise it nowadays.
Question: You talked about the digital advancement in China. Were you able to identify aesthetics that were unique or common in the United States and in Europe? van Hooydonk: We want to be careful not to generalize, to say that America is like this and China is like that. We’re also in a lucky situation where in terms of luxury brands – our brands are premium or luxury brands – the world’s tastes are not growing apart. They’re actually converging. If I look at what the Chinese market wants now, what our designers in Shanghai – who are mostly local – are doing, it’s not so different from what we would like to see. They have completely understood what BMW is all about. They’re tasked to bring that to the future.
Again, I would say there’s a converging. China used to have a bit more, let’s say, bling. I don’t see that anymore. It’s actually become quite refined in terms of tastes. The only difference that you might be able to see is that–to an American customer is a sporty vehicle, no matter how big it is. Even a 7-series is seen as a sporty car. In China, BMW is rather seen as a luxury object, no matter how small or big it is. I think it’s always been like that. In our design we make sure that our customer–the new 7-series is a great example. You can specify this with an M Sports pack. Big rims, everything matte black and all that. You can make it look very sporty, and of course it will drive like that. You can also specify it in lighter colors. We even have cashmere fabric in the interior of the 7-series, a very high-level material. You can also spec it in a way that’s purely modern luxury.
In the end that’s what’s happening around the world. Luxury, like I said, is getting more and more personal, more individual. There isn’t one formula anymore. Maybe 30 years ago, if you reached a certain level of success in life, you wanted to belong to that luxury segment. Then you were willing to buy into all that. But today people don’t care about that so much, especially if you become successful in your own right. You want your own kind of luxury or reward. It’s become far more individual. Through our offerings in body styles and color and materials, we can allow for that. We’re offering for that. That’s been part of our success.
Question: What kind of bets have you made on technology in the design process? There are things like Unreal Engine being used a lot more across industries, or the Omniverse tools from Nvidia. What’s changed for you there? van Hooydonk: We talked about this yesterday a bit. For us, all the virtual tools–we use the ones I think you know. We use Blender a lot, and of course we have VR glasses and AR glasses that we use. We have good connectivity between the studios, where we can all look at the same object in a virtual space. Yesterday, after the talk, you asked about whether we’ll be able to collaborate completely in the virtual space. That’s something we’re looking into. Who knows where that will lead? Maybe a virtual office where people can contact us or collaborate with us who are not part of our organization. That could be an interesting experiment.
Of course AI now has gone through the roof online. That’s also something we’re looking at. But there, in our mind, it really completely depends on what you feed the system. If you feed it 100 years of BMW history and then you ask it to do a new BMW, it tends to look like a BMW that you think you know. That’s what we’ve seen online in the past few weeks. That, for us, will not be good enough. We probably have to feed the system, the AI, different things. A designer’s mind works quite differently. They have a mood board that contains a bottle opener, a coffee cup, and a picture of a hotel lobby. All of that gets worked into a new car design. We’re looking into that as well. We’re experimenting with it. We’ll see where that takes us.
Also, the tool chain is changing very quickly now. You see online designers that have their own websites, they already post their tool chain. Illustrator, Alias, ChatGPT. For them it’s normal that they use all of that. That’s their creativity. That’s going to be interesting in the next few years, how that is going to settle down.
Hampf: We’re experiencing what is almost this third wave. In the big picture, Aiden and I are coming from a piece of paper and Copic markers. We still draw on paper, but in the second stage, you see that the process of sketching and illustrating became digital. We worked with overlays. The same on the physical side, from a clay model and foam to data-based design. Now this third revolution is from the typical digital tools, the Adobe suite or something–we’re moving on to a tool chain that’s completely different. It’s data-based.
What is interesting is that we see this competency of using these tools with the designer. It’s one and the same person. A designer very often today is not going to a computer specialist and saying, “Can you translate my sketch?” They do it themselves to a very high level of sophistication. It means specialization to get the data completely right, but it’s amazing, this third stage, going from paper to digital tablets to data-driven software.
van Hooydonk: The last few years of COVID restrictions taught us a lot. Even I learned a lot in terms of how to use different tools. We used to have big design reviews, big screens. Somebody would present a computer model. I would do some hand movements – more like this, more like that. Two weeks later we would meet again and they would have done what I asked, or maybe not. Otherwise I would have to do more hand-waving.
Now we’re online. We have the designer, the modeler, and myself all in a Teams call. We’re looking at a computer model. I took a screenshot and drew two lines on it, so I didn’t have to do any hand-waving. I just drew on it and shared it with the team. They said, “Okay, I see what you mean.” The modeler started doing what I asked, all in the same call. That process has sped up tremendously, whether we like it or not. We can travel again, so we don’t have to be in our home offices anymore. But that speed is not going to go away. It’s still there. We learned a lot over the last few years in that sense.
Question: I wanted to find out a few more details about how art is integrated into this Designworks studio. Have you anything planned along the lines where you’re teasing an upcoming specific model that you’re about to put on sale or whatever, and you’re finding a way through contemporary art to be able to introduce that and allude to the design rather than just unveiling it? van Hooydonk: The art car series is continuing, but we’re not doing one each year. Sometimes there’s a gap of two or three years. One project is in progress right now. I think later this year we will communicate about which artist is doing that with us. But it’s happening as we speak. We definitely want to continue that. For us, it’s always interesting and inspiring, just like the work we did with Thomas Girst–that was special. It was based on, let’s say, our personal relationship somewhat. For the most part we’re still in contact with all the artists who have done art cars.
Last year, with the launch of the new 7-series, the i7, we introduced something that we call Art Mode. I don’t know if you’re aware, but the 7-series has this curved screen. Digital art, of course, is an up and coming thing. Cao Fei is a digital artist with whom we did an art car. We asked her to be the first artist to create something inside the car for this Art Mode. Now, in the 7-series, you can select Art Mode. You’ll see the screen change into a design that she did.
That’s a first step. We feel that with the technology we have in the cars, the screens that we have, we could actually do more. Probably what we’re going to do in the future, when we do other art cars, we’ll ask those artists to also do something inside the car. We can do a lot more, but you have to be a bit careful, of course. In a driving environment, can you have moving things? There are limits to that.
Here at Designworks we’ve also been talking to people like Refik Anadol, who we find very interesting as an artist. In the realm of digital art we could do a lot more. We could imagine a lot more collaborations. It just has to make sense to both parties. There has to be a match. Refik has visited the studio here. He has a studio in Los Angeles. He seems to be quite busy as he is. That’s the thing. But there are possibilities that are now just opening up to us. We just have to find the time for it and make it meaningful for all parties. Of course you can imagine that we could do a lot of wallpapers in a car, but that’s maybe not good enough, if you think about where we’re coming from in terms of art cars.
Hampf: It’s maybe also not only art, even though that was the center of your question. We very regularly talk to other creative fields like architecture. We had a very good workshop a while ago with Rem Koolhaas at BMW. We’re equally inspired by people like him in terms of their architecture and so on.
We’re talking about the car, and we put out things like the vision circular from a couple of years ago. The word “vision” is loaded, obviously, but to us it really is something that’s pointing toward the future, where we’re putting a stake in. What is visionary architecture? What does our corporate architecture look like? We have some things in Munich that BMW built, the museum and so on. I’m currently very interested in this relationship between mobility and architecture. I talk to architects. There are companies like TeamLab that we look at.
It’s almost, if you will–it’s not so specific to art or artistry. It’s almost a blend of architecture, art, and design. This, I think, becomes really interesting for us. We can find ourselves in this area where we move away from designing a car. We’re designing an object and an experience, mixing all these influences into our work. That becomes interesting.
Question: The lines between architecture, design, and art, a lot of them are blurry lines anyway. Would Designworks ever consider collaborating with a high-profile artist and using the connections that BMW has to work on a project where–say an artist came in and designed a particular area of a product. You could use that as a sort of special edition. Has that ever become a part of the way that Designworks thinks? van Hooydonk: I would say yes. There’s a very good example on our website. It’s a special 7-series. It’s not from this new generation, but the previous generation. It was done by our studio in China. At that time Annette Baumeister was in charge of the China studio. She’s now in charge of color and material for the BMW group. She’s a very experienced designer and artist. She helped to design this very special edition 7-series with artists in China. A lot of craftspeople who made details of the car. It’s wonderful. There’s a super nice video on our website. It’s a red car, and it’s very beautiful. It has embroidery, paint, special wood treatments. But yes, we’re very interested in these types of things.
Hampf: We did the Jeff Koons limited edition 8-series. That was really the first time. You see fashion brands of course doing this in a big way now, like Louis Vuitton and Yayoi Kusama. You could imagine doing that. But Jeff Koons, he really wanted to do this. He was bugging us for a long time. We were saying, “Jeff, are you sure? It’s not too commercial?” But he wanted to do a BMW. He actually wanted to do more cars than we dared to do. We always want to be respectful of our artists, to be careful that it doesn’t look like a quick marketing exercise. That seems to make sense. But for Jeff he wanted to do it, and he already asked if he could do another one. It depends, I guess, who the artist is. That was, I think, 99 cars? van Hooydonk: Yes, 99 cars. It was quite expressive. Total Jeff Koons, I would say. But it’s not like it’s in all of our dealerships around the world. That’s what Louis Vuitton is doing now. You don’t have statues of Jeff Koons and Jeff Koons all over the place. It’s not a big exercise like that. For us it was a sort of toe in the water to see how it goes. They sold quite quickly. But still, for our sales organization, they said, “What?” It’s not what they’re used to selling.
That’s also part of our business. When we do a design we show it to our sales colleagues three years ahead of time. Then they have to gauge the volume. They have to make a statement, an argument. How many do they think they can sell? Imagine showing the Jeff Koons car to them and saying, “Okay, what do you think? How many can you sell, and for how much?” For them that was really difficult. Is it a car? Is it a piece of art? If you relate the price to Jeff Koons’s art, it’s nothing. It’s kind of common. But if you look at it as a car, a special edition 8-series, for a dealership it’s an expensive car. That was territory that was hard to explore. You just don’t know.
Of course what you don’t want is to do too many, and then they’re sitting around everywhere and the value goes down. That wouldn’t have been good for Jeff Koons either. We felt that an edition of 99 cars was a good venture. Then we’ll see whether we’ll do more.
Question: Do you see these kinds of artist collaborations becoming part of designing a car in the future? van Hooydonk: It could be. What we’re looking at is that we think luxury is becoming more personal, like I said before. Whatever that means to people. A lot of our customers are interested in design and art, but then it gets even more personal. Some really love certain artists and really don’t like others. As I said, in the car we have experimented for the first time with Art Mode last year. We had the Jeff Koons limited edition. You can imagine that in the future, we can show a lot more inside the car and become more flexible in the design of the interior and the exterior. We might even be able to change the color of the exterior, like we showed at the Consumer Electronics Show. A car could become a complete canvas. People could express their own tastes or preferences through all of that. It could grow to include art as well. Technologically, though, there are still some things to figure out before we get there.
Hampf: It’s a super interesting time for a designer. Both of us come from an industrial design background. When we look at Dee, the car we introduced at CES, it’s basically–we took away many features that you usually find on cars. We created a very clean and pure exterior. And yet–we’ve been close to the car and walked around it, and it’s 100% a BMW. If you stand in front of it, there’s no doubt this is a BMW. The proportions, everything around it.
However, the car also lends itself to becoming this canvas, in a certain way. It’s clean. It’s a fresh start. It can almost take on your personality. That’s why this experiment with the healing surfaces worked so well on the car, I think. All of a sudden–it’s yours now. What would you do with it? Like the app we introduced yesterday. We really enjoy this time of–it’s a renewing process, I would say. And yet I think it’s 100% BMW. We looked at it just a week ago at our headquarters in Munich. It’s amazing how expressive it is as a BMW. And yet very, very clean. Many of the surfaces–it’s a very pure, clean design.
Disclosure: BMW paid my way to a Santa Monica event. Our coverage remains objective.
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"This week in data: The ML, AI and data landscape with Matt Turck | VentureBeat"
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"https://venturebeat.com/data-infrastructure/this-week-in-data-the-ml-ai-and-data-landscape-with-matt-turck"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages This week in data: The ML, AI and data landscape with Matt Turck Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
In this week’s video, Bruno breaks down the latest edition of the MAD (Machine Learning, Artificial Intelligence and Data) landscape. FirstMark Capital’s managing director Matt Turck also joins the CarCast to discuss the current landscape and key trends. Watch the video below for an in-depth explanation of what’s happening in machine learning, artificial intelligence and data today: This week’s CarCast covers the following: Financing trends across public and private markets and how they affect the world of data. In 2022, the IPO volume sank 78% and public data and infrastructure companies pulled back (-51% vs. -19% S&P 500). Startups witnessed the “Great VC Pullback” and raised an aggregate of approximately $238B, a drop of 31% compared to the year before.
McKinsey & Company’s survey shows that 63% of respondents will increase investment in AI over the next three years. And we know that, according to a survey published in VentureBeat, almost 70% of Data Leaders are looking to INCREASE their data management investments this year.
When it comes to data trends, Mark’s blog highlights seven key trends, and Bruno rolls them up into three key developments: consolidate, converge, and fold where categories come together, or fold under each other. For example, ETL and reverse ETL, data quality and observability, OLTP and OLAP (aka HTAP), data catalogs fold under data governance platforms, and MLOps fold under AI platforms.
And finally, the Modern Data Stack (MDS) appears to be under pressure. Watch the video to find out what that means for data today.
Bruno Aziza is head of data and analytics at Google Cloud.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
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"Talend Data Fabric adds data observability features, connector updates | VentureBeat"
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"https://venturebeat.com/data-infrastructure/talend-data-fabric-adds-data-observability-features-connector-updates"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Talend Data Fabric adds data observability features, connector updates Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Data management and integration veteran Talend today debuted the winter ‘23 release of its core platform, providing enhanced observability, automation and connectivity for enterprises’ data assets. The update comes over a month after the company announced it is being acquired by Qlik in a transaction set to close in the first half of 2023.
Talend started in 2004 as a data integrator, but gradually expanded to offer Talend Data Fabric, a unified solution that works across any cloud, hybrid or multicloud environment. The solution combines enterprise-grade data discovery, integration, quality (automatic cleaning and profiling) and governance capabilities. It’s is intended to reduce the effort involved in working with data, while providing teams with clean and uncompromised information for decision-making.
The new release of Talend Data Fabric builds out the platform’s capabilities, giving enterprises a trust score that enables teams to closely observe the reliability of any data asset at a glance. This is said to strengthen trust in the data being integrated by the platform.
With the latest release, the company is also building on the platform’s existing data quality and integrity elements by bringing observability into the mix. Data professionals can now automatically and proactively monitor the quality of their data over time. That is particularly important, as data quality is very dynamic.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Teams using Data Fabric can use dataset crawling or tags to uncover data blind spots and find new datasets relevant to the business. They can also instantaneously check the validity and usage of data types across the datasets; apply contextual data quality rules; and monitor how data quality evolves using the trust score, which acts as a gauge to measure the quality of data.
This capability empowers enterprises to continuously monitor data throughout its lifecycle, and understand and impact how it evolves and moves to fuel positive business outcomes, according to Jason Penkethman, chief product officer at Talend. This is important, as observability is a key product in today’s enterprise technology space. The many companies offering solutions in this area include Acceldata , Monte Carlo and Datafold.
What else is new in Talend Data Fabric? Along with monitoring capabilities, Talend has focused on improving data connectivity and AI-driven automation with the winter ‘23 release.
For data connectivity, the company said it is expanding its lineup of 1,000+ connectors and components, adding certified connectors for SAP S/4HANA and SAP business warehouse on HANA, as well as support for ad platforms such as TikTok, Snapchat, Twitter and modern cloud databases, including Amazon Keyspaces, Azure SQL Database, Google Bigtable and Neo4j Aura Cloud.
On the automation front, it is bringing AI -powered smart services that simplify the scheduling and orchestration of cloud jobs, allowing users to pause and resume tasks and use smart timeouts to cut compute time and improve operational efficiency.
The company also said it is updating Stitch, its fully managed cloud ETL service, with new role-based access control to provide better segregation of administrator duties, and new pipeline monitoring capabilities that will allow data teams to get key metrics on data ingestion, including data volumes, data freshness, and schema changes. There’s also a new History mode for Snowflake, which enables easy tracking of data changes.
In the highly diverse data integration space, Talend competes with players like IBM, Informatica, Mulesoft, Fivetran and Matillion.
Last year, Talend was named a leader in the Magic Quadrant for Data integration Tools.
It currently serves over 7,000 enterprise customers, including Toyota, Domino’s, Lenovo, Foodpanda and eBay.
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"Zymtronix Welcomes Thomas Videbaek to Its Board of Directors | VentureBeat"
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"https://venturebeat.com/business/zymtronix-welcomes-thomas-videbaek-to-its-board-of-directors"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Press Release Zymtronix Welcomes Thomas Videbaek to Its Board of Directors Share on Facebook Share on X Share on LinkedIn RESEARCH TRIANGLE PARK, N.C. & ITHACA, N.Y.–(BUSINESS WIRE)–February 28, 2023– Zymtronix, Inc., a groundbreaking new biotechnology company, today announced that Dr. Thomas Videbaek, biotech industry veteran and former Executive Vice President (EVP) of Novozymes, is joining its Board of Directors.
Dr. Videbaek has spent more than 30 years in biotechnology and held multiple Executive Vice President (EVP) roles at Novozymes, the world leader in industrial enzymes. These included COO covering Global R&D, Manufacturing and Supply Chain, M&A, Sustainability and Regional Leadership, EVP for Corporate Strategy & Business Transformation, and EVP for the Bio-business. He has led many key initiatives that created several new business areas for the firm, including areas in industrial enzymes, microorganisms, and bio-agriculture.
Dr. Videbaek holds a PhD and MSc from the Technical University of Denmark and a Bachelors in Business Administration (HD) from the Copenhagen Business School.
“Thomas brings years of experience and an impressive track record of developing and commercializing transformative technologies,” said Stéphane Corgié, PhD, Founder & CEO of Zymtronix. “His experience and expertise are greatly adding to the pool of leadership fueling Zymtronix’s growth and industrialization of our platforms and products,” he continued.
“Thomas truly understands the sustainability power of biology and enzymes in making the world a better place. He’s also a great guy that knows what it takes to commercialize new technology and it’s a significant vote of confidence for our technology to have a global leader like Thomas sitting on our board,” said Adam Monroe, President and COO of Zymtronix. “In my years at Novozymes working with Thomas, he was universally respected both inside and outside the company as a true change leader and great colleague,” he added.
Dr. Videbaek said, “I am delighted to join the Board of Zymtronix. As someone who has been part of developing the multibillion dollar industrial enzyme industry and seen the many ways in which you can utilize enzymes in making the world a better place, I’m amazed by how Zymtronix is unlocking a new level of impact through their cell-free, multi enzyme technology. This technology could be opening the door to completely new products, step change economics, and enormous sustainability power.” ABOUT ZYMTRONIX With technology originating at Cornell University, Zymtronix has opened completely new biomanufacturing possibilities with their cell-free product development and proprietary process technologies. Their novel matrices of unique immobilization materials and composition of enzymes can provide previously inaccessible molecules and fundamentally change existing product economies. The uniqueness and efficiency of the Zymtronix systems can dramatically improve the carbon footprint and sustainability profiles of the manufactured products and provide new pathways to a better future.
View source version on businesswire.com: https://www.businesswire.com/news/home/20230206005633/en/ Stéphane Corgié, Founder, CEO and CTO [email protected] Adam Monroe, President and COO [email protected] VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"New report from KPMG Private Enterprise reveals tax consequences on family business transfers can vary in the millions based on location | VentureBeat"
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"https://venturebeat.com/business/new-report-from-kpmg-private-enterprise-reveals-tax-consequences-on-family-business-transfers-can-vary-in-the-millions-based-on-location"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Press Release New report from KPMG Private Enterprise reveals tax consequences on family business transfers can vary in the millions based on location Share on Facebook Share on X Share on LinkedIn Highlights include: Vast differences in tax paid for generational transfers across 57 jurisdictions More than half of the jurisdictions analyzed offer substantial tax breaks List of jurisdictions that impose the highest tax rates for transfer of a family business valued at EUR10 million versus EUR100 million Emerging trends and factors driving succession, investment, and planning for today’s business families.
TORONTO–(BUSINESS WIRE)–February 28, 2023– For many business families, sustaining prosperity for the long run depends on how well they plan for transfers of business assets and family wealth from one generation to the next, according to the KPMG Private Enterprise Global Family Business Tax Monitor.
The report advises business families with footprints in multiple jurisdictions to monitor potential new or increased taxes and consider taking action in advance.
The report has been a go-to source for family business tax planning for almost a decade, comparing the vastly different tax liabilities among jurisdictions on the transfer of family business through gifting during the owners’ lifetime (including on retirement) and through inheritance.
Among the 57 jurisdictions covered in the report, some have geared their tax policies in ways that recognize how a thriving family business sector contributes to a vibrant economy. Others give no special tax exemptions for intergenerational family business transfers, increasing tax costs and likely reducing the family’s ability to compete with business families in more tax-friendly jurisdictions.
“Location can make a world of difference! Tax-efficient transfers between generations can leave wealth in the hands of entrepreneurial families to invest in profit-producing activities – and that can help stimulate job creation and innovation for future generations,” says Tom McGuiness, Global Leader, Family Business, KPMG Private Enterprise, KPMG International KPMG Private Enterprise’s report found that globally, South Korea, France, the US and the UK impose the highest tax rates for transfer of a family business valued at EUR10 million by inheritance, before any tax breaks are accounted for. After exemptions, South Africa takes the biggest bite from family business inheritances valued at EUR10 million, followed by Canada and Japan.
For inheritances of family businesses over EUR100 million, the most expensive taxing jurisdiction is South Korea after exemptions, with South Africa and the US coming in second and third.
For transfers during the owner’s lifetime (gifts) of family businesses valued at EUR10 million, Venezuela imposes the highest taxes globally before exemptions, followed by Spain, South Korea and France.
After exemptions, South Africa and Japan come second and third behind Venezuela as the jurisdictions imposing the highest tax costs on business transfers by gift. These comparisons are similar for family businesses valued at EUR100 million before and after exemptions.
Top priorities for today’s business families The report also provides insights on what business families consider their biggest priorities and risks and calls attention to three emerging trends – branching out, building up and giving back.
The trends crucially reveal an increase in business families and their assets becoming more global, a rise in the importance of governance and a renewed focus on the management of family wealth and the notion of giving back with philanthropic activities commanding more time.
“Amid rising geopolitical tension and unparalleled economic uncertainty, the leading business families that we work with are diversifying globally and putting more focus on the sustainability of their businesses, their wealth and their communities,” says Tom McGuiness, Global Leader, Family Business, KPMG Private Enterprise, KPMG International. “By doing so, they can position their families for sustainable success down the generations. As a result, we are seeing more business families around the world that are focused on branching out, building up and giving back.” Download the report for details.
Notes to Editors About KPMG Private Enterprise Passion, it’s what drives entrepreneurs, it’s also what inspires KPMG Private Enterprise advisers to help you maximize success. You know KPMG, but you might not know KPMG Private Enterprise. KPMG Private Enterprise advisers in KPMG firms around the world are dedicated to working with you and your business, no matter where you are in your growth journey – whether you’re looking to reach new heights, embrace technology, plan for an exit, or manage the transition of wealth or your business to the next generation. Working with KPMG Private Enterprise, you’ll gain access to a trusted adviser – a single point of contact who shares your entrepreneurial mindset. Access to KPMG’s global resources and alliance network can help you drive your business forward and meet your goals. Your success is KPMG Private Enterprise’s legacy.
About KPMG International KPMG is a global organization of independent professional services firms providing Audit, Tax and Advisory services. KPMG is the brand under which the member firms of KPMG International Limited (“KPMG International”) operate and provide professional services. “KPMG” is used to refer to individual member firms within the KPMG organization or to one or more member firms collectively.
KPMG firms operate in 143 countries and territories with more than 265,000 partners and employees working in member firms around the world. Each KPMG firm is a legally distinct and separate entity and describes itself as such. Each KPMG member firm is responsible for its own obligations and liabilities.
KPMG International Limited is a private English company limited by guarantee. KPMG International Limited and its related entities do not provide services to clients.
For more detail about our structure, please visit kpmg.com/governance.
About the KPMG Private Enterprise Global Center of Excellence for Family Business As with your family, your business doesn’t stand still – it evolves. Family businesses are unique and KPMG Private Enterprise family business advisers understand the dynamics of a successful family business and work with you to provide tailored advice and experienced guidance to help you succeed. To support the unique needs of family businesses, KPMG Private Enterprise coordinates with KPMG firms from around the world that are dedicated to offering relevant information and advice to family-owned companies. KPMG Private Enterprise understands that the nature of a family business is inherently different from a non-family business and requires an approach that considers the family component.
Visit: kpmg.com/familybusiness View source version on businesswire.com: https://www.businesswire.com/news/home/20230227005579/en/ For more information: Daniel Caines, Senior Manager, Global External Communications, KPMG International T: +44 7732400262 E: [email protected] VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Mawari Launches Testnet in Japan as a GSMA Foundry Project | VentureBeat"
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"https://venturebeat.com/business/mawari-launches-testnet-in-japan-as-a-gsma-foundry-project"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Press Release Mawari Launches Testnet in Japan as a GSMA Foundry Project Share on Facebook Share on X Share on LinkedIn Japanese Operator KDDI joins as the first collaborating partner.
BARCELONA, Spain–(BUSINESS WIRE)–February 28, 2023– Mawari Corp., the leader in cloud rendering and XR streaming is thrilled to announce that Japanese telecommunications giant KDDI Corporation will join the Mawari Network Testnet in Japan. They will be collaborating by providing edge rendering, validating, and storage nodes, in addition to the last-mile 5G network.
This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20230227005350/en/ Mawari Network (Graphic: Business Wire) “KDDI is pleased to continue our ongoing partnership with Mawari and provide our Edge Computing and 5G network resources for the Mawari Network Testnet” , says Katsuhiro Kozuki, Head of XR Development Department at KDDI Corporation.
“Our pioneering work together with Mawari over the past years to deploy consumer-grade XR experiences now continues at a new, more advanced level to create new life experiences in the Beyond 5G and 6G era.” This GSMA Foundry Project will showcase the world’s first Web3, decentralized XR content delivery platform that scales real-time 3D rendering and streaming to XR wearable devices via 5G.
“This GSMA Foundry project demonstrates the role operators can play in the decentralised delivery of Web3 services to mobile devices and wearables. This is critical for delivering high quality 3D content on a sustainable basis,” says Alex Sinclair, Chief Technology Officer at GSMA.
“The project will also explore the benefits brought by the GSMA Open Gateway API for Quality on Demand and how it exposes operator network capabilities to deliver great experiences to users.” Over the past 6 years Mawari has developed proven and widely demonstrated cutting-edge, proprietary technologies including patent-pending Split Rendering frameworks and 3D streaming CODECs of the Mawari Engine which will power the Mawari Network Testnet.
“The trillion-dollar opportunity represented by XR will not be realized until consumer-grade content can be efficiently streamed simultaneously to large numbers of XR wearable devices. Similarly, without the killer use-case, mainstream adoption cannot happen. The Mawari Network opens the doors for creative developers to push creativity to the limit.” says Founder and CEO Luis Oscar Ramirez Solorzano.
In 2023, KDDI and Mawari will conduct use case exploration in Japan in the areas of consumer and entertainment verticals using XR wearables in collaboration with Qualcomm Technologies, Inc. and the Snapdragon Spaces™ XR Developer Platform. The most compelling examples will be showcased in the future.
“The Qualcomm Technologies and Mawari collaboration, utilizing the Snapdragon Spaces platform, will enable the technology for developers to raise the bar in augmented reality experiences in the XR, Web3, and metaverse era,” says Brian Vogelsang, Senior Director of XR Product Management, Qualcomm Technologies, Inc.
“We are looking forward to working with Mawari and other Snapdragon Spaces ecosystem members to accelerate the pace of innovation in headworn AR.” As a result of this GSMA Foundry initiative, other operators from around the world will have the opportunity to witness and learn from this pioneering work in XR delivery and 5G monetization.
About KDDI Corporation KDDI aims to provide new experience value by expanding and coordinating various life design services, including those related to commerce, finance, energy, entertainment, education, and healthcare, while focusing on conventional telecommunications services, such as those related to smartphones, cell phones, FTTH, and CATV. We dynamically provide services attuned to customer needs and market conditions through a multi-brand strategy that encompasses “au,” “UQ mobile,” and “povo.” https://www.kddi.com/extlib/files/english/corporate/ir/ir-library/sustainability-integrated-report/pdf/kddi_sir2022_e.pdf About Mawari Corp.
Mawari is a pioneer in Cloud Rendering and Streaming technologies. Our core technology has been validated in the market through repeated success in the XR industry with over 40+ deployments to date worldwide. The Mawari Network is a decentralized 3D & XR content delivery platform that breaks the bottlenecks of infrastructure supply for real-time rendering, and the lack of local compute power on XR Devices. We do this by orchestrating a decentralized network of GPU-powered nodes that run the Mawari Engine, a proprietary technology stack that allows to render interactive 3D content and stream it efficiently in real-time to mobile XR devices at scale.
Snapdragon and Snapdragon Spaces are trademarks or registered trademarks of Qualcomm Incorporated. Snapdragon Spaces is a product of Qualcomm Technologies, Inc. and/or its subsidiaries.
View source version on businesswire.com: https://www.businesswire.com/news/home/20230227005350/en/ Mawari Corp.
Fred Speckeen, COO [email protected] VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"KDDI, Telefónica, Mawari and Sturfee Revolutionize Online Shopping With the 5G MEC Powered XR Digital Twin Store Project in Alignment With GSMA Foundry Telco Edge Cloud (TEC) Trials Initiative | VentureBeat"
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"https://venturebeat.com/business/kddi-telefonica-mawari-and-sturfee-revolutionize-online-shopping-with-the-5g-mec-powered-xr-digital-twin-store-project-in-alignment-with-gsma-foundry-telco-edge-cloud-tec-trials-initiative"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Press Release KDDI, Telefónica, Mawari and Sturfee Revolutionize Online Shopping With the 5G MEC Powered XR Digital Twin Store Project in Alignment With GSMA Foundry Telco Edge Cloud (TEC) Trials Initiative Share on Facebook Share on X Share on LinkedIn BARCELONA, Spain–(BUSINESS WIRE)–March 1, 2023– Sturfee and Mawari, in partnership with KDDI and Telefónica, are proud to announce the 5G MEC powered XR Digital Twin Store, a new project aimed at demonstrating the power of XR technologies in creating a sense of co-presence and togetherness. The project will be showcased at the Mobile World Congress Barcelona 2023. A video demonstrating the project is available at https://youtu.be/xBN_yg_d0os This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20230228006480/en/ 5G MEC powered XR Digital Twin Store 1 (Photo: Business Wire) The project allows a shopper in a physical store to connect with a remote shop assistant through the use of 5G technology and augmented reality capabilities. Shop assistants can serve Spanish-speaking shoppers in a store in Ginza, Japan, with assistance from an operator in Spain, while Japanese shoppers are assisted from Tokyo. Mawari’s decentralized 3D & XR content delivery platform “The Mawari Network” coordinates the service, connecting to the appropriate cloud rendering server for the XR-Tuber application.
Sturfee’s Digital Twin platform enables retailers to create, host, and connect digital twin shops to physical stores. The key element of the platform is Sturfee’s Visual Positioning Service (VPS) that connects the digital and physical spaces together and synchronizes user activities across spaces. Mawari’s XR-Tuber captures operators’ facial motions and voices, encoding them, and streaming them to the digital human’s cloud rendering servers for lip-syncing, rendering, and streaming processes, providing a hyper-realistic 3D digital human avatar with low latency and high-fidelity.
KDDI and Telefónica provide low latency and high-speed network connections for seamless transmission of data, making the 5G MEC powered XR Digital Twin Store project a true showcase of the potential of XR technologies. To ensure certain Quality of Service (QoS)-level network connection, the project scope also includes testing and implementation for the Quality on Demand (QoD) API from the GSMA Open Gateway initiative.
The project is a testament to the innovative power of XR technologies and their ability to create a sense of co-presence and togetherness, even when individuals are separated by great distances.
“We could confirm the power of XR technologies in creating a sense of co-presence: the feeling of being together in a place, despite being separated by great distance, by utilizing KDDI’s and Telefónica’s 5G edge resources,” says Katsuhiro Kozuki, Head of XR Development Department at KDDI Corporation. “We would like to innovate life experiences and behaviors with 5G and technological evolution for age of Beyond 5G and 6G.” “This is an amazing case that shows the great value of the Telco Edge Cloud when combined with 5G and advanced technologies like XR, Digital Twins or Virtual Positioning Services to deliver new ways of human communication and new tools for sectors like Retail, taking us closer to future scenarios like the Metaverse that are based in the connection of digital and physical worlds,” says Juan Carlos García, SVP Technology Innovation and Ecosystems at Telefónica. “It has been a great experience to work with our partners KDDI, Mawari and Sturfee to make this possible”.
“We are thrilled to join forces with KDDI, Telefónica and Sturfee to harness the power of 5G and XR technology and create a new level of personalization and immersion for shoppers. By eliminating the barriers with the Mawari’s real-time rendering and XR streaming SDK, we’ve enabled a real sense of presence, and also provided a more empathetic and personalized customer support that truly enhances the shopping experience.” says Luis Oscar Ramirez Solorzano, Founder and CEO of Mawari.
“We are excited to see national operators like KDDI and Telefónica using our Digital Twin Platform to create, host, and connect digital replicas of stores to actual stores. It is amazing to see the beginning of a new form of immersive shopping services our platform can enable, easily integrating Mawari’s XR Tuber service.” says Harini Sridharan, Chief Technology Officer at Sturfee. “VPS is key in connecting physical and digital worlds to power such exciting co-presence experiences.” “We’re very excited to complete this GSMA Foundry Telco Edge Cloud trial with KDDI, Telefónica, Mawari and Sturfee. This collaboration represents yet more innovation available to see at MWC Barcelona 2023, underpinned by the GSMA Open Gateway initiative and the Quality on Demand API. When coupled with 5G powered Telco Edge Cloud capabilities this trial enables truly innovative ways to shop; blurring the lines between the physical world and XR,” said Henry Calvert, Head of Network, GSMA.
About KDDI Corporation KDDI aims to provide new experience value by expanding and coordinating various life design services, including those related to commerce, finance, energy, entertainment, education, and healthcare, while focusing on conventional telecommunications services, such as those related to smartphones, cell phones, FTTH, and CATV. We dynamically provide services attuned to customer needs and market conditions through a multi-brand strategy that encompasses “au,” “UQ mobile,” and “povo.” https://www.kddi.com/extlib/files/english/corporate/ir/ir-library/sustainability-integrated-report/pdf/kddi_sir2022_e.pdf About Telefónica Telefónica is one the largest telecommunications service providers in the world. The company offers fixed and mobile connectivity as well as a wide range of digital services for residential and business customers. With more than 383 million customers, Telefónica operates in Europe and Latin America.
Telefónica is a 100% listed company and its shares are traded on the Spanish Stock Market and on those in New York and Lima.
About Mawari Mawari is a pioneer in Cloud Rendering and Streaming technologies. Our core technology has been validated in the market through repeated success in the XR industry with over 40+ deployments to date worldwide. The Mawari Network is a decentralized 3D & XR content delivery platform that breaks the bottlenecks of infrastructure supply for real-time rendering, and the lack of local compute power on XR Devices. We do this by orchestrating a decentralized network of GPU-powered nodes that run the Mawari Engine, a proprietary technology stack that allows to render interactive 3D content and stream it efficiently in real-time to mobile XR devices at scale.
About Sturfee Sturfee is a computer vision startup focused on creating metaverse-ready maps of the physical world that can be used for Augmented Reality, Digital Twin, and Autonomous applications. Mobile operators use Sturfee’s platform to deliver immersive experiences for retail locations, venues and campuses; these experiences are available both as on-site AR content and as remote virtual mode. The key element of the platform is the Visual Positioning Service (VPS) to determine where a camera is looking in the real world; this enables persistent Augmented Reality content and shared presence across AR and VR modes. Sturfee’s cloud service creates 1:1 large-scale city models and private 3D indoor maps using various datasets ranging from mobile phone scans, professional scanners, and satellite 3D data, and is tightly coupled with ubiquitous indoor-outdoor VPS service.
About GSMA The GSMA is a global organisation unifying the mobile ecosystem to discover, develop and deliver innovation foundational to positive business environments and societal change. Our vision is to unlock the full power of connectivity so that people, industry, and society thrive. Representing mobile operators and organisations across the mobile ecosystem and adjacent industries, the GSMA delivers for its members across three broad pillars: Connectivity for Good, Industry Services and Solutions, and Outreach. This activity includes advancing policy, tackling today’s biggest societal challenges, underpinning the technology and interoperability that make mobile work, and providing the world’s largest platform to convene the mobile ecosystem at the MWC and M360 series of events.
We invite you to find out more at gsma.com https://www.gsma.com/.
View source version on businesswire.com: https://www.businesswire.com/news/home/20230228006480/en/ Mawari Corp.
Fred Speckeen, COO [email protected] VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Black Desert Mobile debuts on Apple Macs with new update | VentureBeat"
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"https://venturebeat.com/business/black-desert-mobile-debuts-on-apple-macs-with-new-update"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Black Desert Mobile debuts on Apple Macs with new update Share on Facebook Share on X Share on LinkedIn Black Desert is a big hit from Pearl Abyss. Now it is heading to the Mac.
Pearl Abyss announced today that you can now download Black Desert Mobile from the App Store onto select Macs.
The South Korean company also said that the new Hashashin Awakening class, Zayed, is available now in the game with a new update. Black Desert has had more than 50 million registered users to date.
Adventurers can take on the sand-wielding fighter Zayed, who uses his Dual Glaives across four distinct skills, such as purge, ensnaring sands, condemnation, and Desert’s Shadow.
Black Desert Mobile is available now to play on all Mac devices with Apple silicon chips from 2020 or later, including Mac OS, MacBook Pro, MacBook Air, iMac, Mac mini, and Mac Studio.
And today Pearl Abyss launched a new Amazon Prime Gaming campaign offering valuable in-game rewards every two weeks. Starting today, February 28, and running through August 22, Amazon Prime members can redeem items on the Prime Gaming homepage, starting today with 1,000 Chaos Crystals and five Abyssal Relic Selection Chests (a $49.50 value).
I met last week with Jeonghee “JJ” Jin, head of the U.S. office of Pearl Abyss, last week at the Dice Summit in Las Vegas. Black Desert is eight years old now, and it recently crossed its seventh anniversary in the U.S. The company is also working on Crimson Desert, which was originally announced in 2018. The company has around 1,500 people and a proprietary game engine, Black Space, for its titles.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
All rights reserved.
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"Angeles Equity Partners Adds Randi Moran as Chief Performance Officer | VentureBeat"
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"https://venturebeat.com/business/angeles-equity-partners-adds-randi-moran-as-chief-performance-officer"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Press Release Angeles Equity Partners Adds Randi Moran as Chief Performance Officer Share on Facebook Share on X Share on LinkedIn LOS ANGELES–(BUSINESS WIRE)–February 28, 2023– Angeles Equity Partners, LLC (“Angeles”), a private investment firm focused on value creation through operational transformation, has appointed Randi Moran as chief performance officer at Angeles Operations Group, LLC. Moran brings more than 20 years of people, process, and program management experience to the role.
Angeles is a specialist lower middle-market private equity investment firm with a consistent approach to transforming underperforming industrial businesses. As chief performance officer, Moran will support Angeles in the evaluation and due diligence of new platform investments, selection and development of leadership talent, and driving organizational effectiveness across portfolio investments.
“We are thrilled to add Randi Moran as our chief performance officer. Her extensive experience in acquiring and developing talent and creating more effective organizations in the industrial and manufacturing sectors makes her an outstanding fit for this role,” said Tim Meyer co-founder and managing partner of Angeles Equity Partners. “The addition of Randi underscores our commitment to investing in ‘top talent’ and the ongoing professional development of our portfolio employees.” Prior to joining Angeles, Moran was chief human resources officer (CHRO) at American Construction Source, a national building materials platform for custom home builders and repair and remodel contractors. Before that, she held senior leadership roles at Elo Touch Solutions, GE Power, Vought Aircraft, Boeing, Hughes Space & Communications, and AlliedSignal. Moran was a Major in the U.S. Air Force and earned an aerospace engineering degree from the University of Southern California and an MBA from Pepperdine University.
“I believe strongly in the power of cultivating and optimizing a people-first culture by acquiring and developing the best talent to drive growth and create value. I am thrilled to work alongside the talented individuals at Angeles and look forward to contributing to the continued success of the firm,” Moran said.
About Angeles Equity Partners, LLC Angeles Equity Partners, LLC is a specialist lower middle-market private equity investment firm with a consistent approach to transforming underperforming industrial companies. In partnership with Angeles Operations Group, LLC, the Angeles skill set drives the firm’s investment philosophy and, in its view, can help businesses reach their full potential. Learn more online at www.angelesequity.com.
View source version on businesswire.com: https://www.businesswire.com/news/home/20230228005680/en/ Michelle Barry Chameleon Collective for Angeles Equity Partners [email protected] VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
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"How to be recession ready with intelligent automation | VentureBeat"
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"https://venturebeat.com/automation/how-to-be-recession-ready-with-intelligent-automation"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest How to be recession ready with intelligent automation Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Businesses of all sizes are bracing for a recession.
Still, while it may sound counterintuitive, this is actually the right time to accelerate digital transformation.
Historically, an economic downturn is a boon for innovation. According to Morgan Stanley , roughly half of Fortune 500 companies were founded in times of recession or economic crisis.
Investing in digital transformation will help businesses overcome a slowdown and address talent shortages. Organizations can also get ahead of their competitors as they make cuts and slow digital transformation plans. A Harvard Business Review analyzing outcomes across three recessions found that those most likely to flourish post-downturn were those that successfully made efficiency improvements and invested in the future.
Shortsighted savings will cost you in the long run Businesses are dealing with a looming recession, a tight labor market and continued supply chain disruptions. It may be counterintuitive, but cost-cutting measures in the face of such headwinds are not the answer.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! The pandemic inadvertently showed us unprecedented innovation born out of necessity and spurred the adoption of digital technologies to meet consumer demands. This innovation also allowed R&D timelines to leapfrog the development of a vaccine in less than a year — a process that normally would have taken about 10 years from concept to approval.
The looming economic downturn and growing skills gaps present another opportunity to drive innovation. Accelerating digital transformation will help businesses overcome the slowdown and address talent shortages.
Businesses are expected to invest a total of $3.4 trillion to fund their digital transformation strategies by 2026. And, those best positioned to meet rapidly shifting consumer needs and embrace innovation are leveraging intelligent automation.
All in on automation Digital transformation enables businesses to mitigate fallout and foster agility and resilience, making future volatility easier to withstand. The benefits of gearing up digital transformation are multifold — from productivity and efficiency gains to better supply chain management, customer experience and resource visibility.
No-code automation platforms ease the burden of reskilling employees to use advanced automation technologies. Robotic process automation (RPA) can then be used to automate time-consuming, repetitive, painstaking and often error-prone tasks. Pairing this advanced technology with artificial intelligence (AI) allows for scalability and decision-making capabilities within business process automation. By automating these processes, workers have more time and access to invaluable insights for creative endeavors to enhance customer experience and promote growth and revenue.
Even implementing a simple automation solution like intelligent document processing is a powerful step toward digitalization. It has the potential to save tens of thousands of hours, including those spent on rework for mistakes, and create immense value.
U.S. companies spend an astonishing $5.3 billion annually on wages for manual document processing. By automating processes, resources can be redirected to improve other key business objectives, such as customer and employee experience.
Common mistakes to avoid Digital transformation is amazing and exciting, but only if done right. Businesses get sold on all the wonders of digitalization and jump the gun on implementing solutions. This is an easily avoidable obstacle.
Businesses need a well-considered digital transformation plan. This is often most successfully achieved with the right digital transformation partner who can help them mine processes for automation, select the right solutions, integrate automation into their existing infrastructure and train/upskill existing workers — or, if preferred, maintain their new digital infrastructure on their behalf.
Subject matter expertise is another key differentiator because a vendor offering in-depth knowledge of specific sectors will understand pain points where automation will add the most value. For example, suppose a hedge fund is looking to invest in more digitalization. In that case, they will want to partner with a vendor that understands processing in their sector and can perform tasks such as net asset value calculations.
Stakeholder support is key Another common trap businesses fall into is not investing in the cultural transformation needed to make any digital transformation plan successful. To get the most out of business process automation during a global talent shortage, you need to upskill engaged workers with an aptitude for such training.
It would help if you also educated all workers on the purpose of a digitalization plan. Why should they care? How are they going to benefit? These are key questions; if your employees don’t know the answers, you’re already positioning your plan to fail. Workers play a significant role in overseeing digitalization implementation; if they feel antagonistic about it, their chances of success diminish.
Estimates suggest that for every dollar businesses spend on licensing an automation solution, they spend five times more trying to figure out how to implement and scale. This is an avoidable waste of resources, especially when many can’t afford it. All it takes is a well-developed strategy.
Doubling down on investment in intelligent automation will help businesses navigate hard times. The power of advanced automation technologies is that they improve efficiency and free up resources for innovation and human capital investment — paving the way for long-term success.
Colin Redbond is global SVP for product and strategy at SS&C Blue Prism DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"The purpose and impact of creative AI | VentureBeat"
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"https://venturebeat.com/ai/the-purpose-and-impact-of-creative-ai"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest The purpose and impact of creative AI Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
As robotics began to take on more and more tasks, one of the biggest questions has always been, “Will robots ever be creative?” That always seemed a laughably distant goal. Without consciousness, a robot couldn’t do more than follow directions. Or could it? With the advent of AI and machine learning , it suddenly became possible to imagine an AI that could learn to interact creatively. Now we have a new question to deal with: “Will creative AI be more of a problem than it’s worth?” Creative AI and art One concern many have voiced is that generative AI could encroach on human-specific domains, like art. This fall, an AI artwork won the Colorado State Fair’s fine arts competition. The creator, Jason Allen, wasn’t an artist. He created the artwork using Midjourney , one of several generative AI art creators.
Allen himself had to overcome some personal worries about AI art. However, by the time he won the prize, he felt that AI “is a tool, just like the paintbrush is a tool. Without the person, there is no creative force.” Allen still needed to curate the AI’s responses to his prompt, and he ran the final versions through some other editing tools as well.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! However, Allen faced considerable backlash, with some even suggesting that Allen should return his award. One person said that using Midjourney was like “entering a marathon and driving a Lamborghini to the finish line.” If we see AI as a tool, it doesn’t need to inspire fear. It may be the sensational claims that often surround AI that are causing the issues. If “creative” AI is seen as replacing human creativity, it could be perceived as a threat rather than an opportunity.
And AI doesn’t need to be a threat. Recently some friends and I sat around a living room and tried out different prompts in Midjourney. I tried for some time to create an “Amish superhero.” For some reason, it insisted on creating figures with a hat pulled down over their eyes. Clearly, AI can’t just replace a human artist.
A good artist could use AI as the basis for something, and manipulate it later, as Allen did. It’s useful too, and it needs to be marketed in that way. Sensationalizing AI will distract from real-world applications that make a human artist’s job easier.
A good use case for creative AI For example, AI can already be very useful in graphic design. Several companies have explored the possibilities that graphic design AI could bring to their business.
Recently, when sending out a marketing email, I discovered Mailchimp’s new Creative Assistant AI, which is fully integrated with its email builder. I was able to just enter my copy, upload a few images and choose some settings. The AI created lots of different possibilities and variations.
Creative Assistant took away an hour of work, where I’d have had to create an entire graphic and then shift the text and images around, and no one was worried that it could replace a marketing agent. In this case, AI filled an uncontroversial role. Who wouldn’t use a time-saving AI assistant? Creative virtual assistants If the goal of AI is to make our work easier, how about AI virtual assistants? Bots that can actually learn and can create new answers to our questions? Surprisingly, this subject has also launched a recent controversy. This time it surrounds the complexities of relating to a robot as though it were human.
Google has been developing a chatbot, called LaMDA, which can return intelligent, human-like responses to prompts. The bot interacted so humanly that one of the engineers, Blake Lemoine, became convinced that it had become sentient. LaMDA’s responses to his queries seemed very humanlike and self-aware. In fact, LaMDA even created an allegory where a wise owl saved forest creatures, a story intended to express LaMDA’s desire to help others.
Convinced that LaMDA was sentient, Lemoine wanted to treat LaMDA as a human. However, for those, like me, who aren’t convinced that AIs are sentient, another problem could arise. A human-like AI might not be most comfortable for customers.
While such an AI could be considered a valid replacement for a human interaction, customers could feel cheated if they need to interact with a machine rather than a human.
Where generative AI fits in What would work better is to optimize AI for helpfulness without making it appear human. If AI can take away tedious tasks and enable us to spend more time on what’s more important, it has done its job. If consumers know that that’s the purpose of generative AI, they will be much more comfortable with the role it plays.
Lynn Martin works in marketing for Brechbill Trailers.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Qualcomm lines up 7 global telecom operators to support XR devices with Snapdragon Spaces | VentureBeat"
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"https://venturebeat.com/ai/qualcomm-lines-up-7-global-telecom-operators-to-support-xr-devices-with-snapdragon-spaces"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Qualcomm lines up 7 global telecom operators to support XR devices with Snapdragon Spaces Share on Facebook Share on X Share on LinkedIn Growing support for Snapdragon Spaces mixed reality.
Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Qualcomm said it has lined up seven global telecommunications operators to leverage XR (extended reality) devices using Snapdragon Spaces.
The operators include CMCC, Deutsche Telekom, KDDI Corporation, NTT QONOQ, T-Mobile, Telefonica, and Vodafone. All are working with Qualcomm on new XR devices, experiences, and developer initiatives with Snapdragon Spaces. The companies made the announcement at Mobile World Conference in Barcelona.
At MWC, KDDI and Qualcomm announced a multi-year collaboration, focused on the expansion of XR use cases and creation of a developer program in Japan. XR devices included augmented reality, virtual reality, and mixed reality.
Equipment makers leveraging Snapdragon XR technology are designing a new wave of devices for operators and beyond. They include Xiaomi Wireless AR Glass Discovery Edition, and OPPO’s new mixed reality device and OnePlus 11 5G smartphone, which are both Snapdragon Spaces Ready.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Operators are leading a variety of investments around XR, and are using the cross-device and open ecosystem Snapdragon Spaces XR Developer Platform as the foundation, Qualcomm said.
Global operators are helping to define Snapdragon Spaces device requirements and compatibility that will give customers more options to wirelessly tether smartphones and glasses, champion these technologies on their networks, and launch regional developer programs that pioneer head-worn augmented reality (AR) experiences.
Expanding the current XR hardware offerings, multiple hardware companies unveiled new devices powered by Snapdragon technologies and developer platforms. Xiaomi revealed its new Wireless AR Glass Discovery Edition powered by the Snapdragon XR2 Platform.
“With a series of Metaverse innovations, China Mobile is fully investing in the Metaverse and XR, implementing our strategy of both excellence in software and in hardware technology,” said Cui Fang, general manager for technology at China Mobile Communication Group Device Company, in a statement. “We have a long-standing collaboration with Qualcomm Technologies in XR actively promoting the development of the industry and working together to solve industrial challenges. We look forward to working together in building the developer ecosystem using Snapdragon Spaces to empower the growth of the overall XR industry ecosystem.” OPPO confirmed a new mixed reality (MR) device that is Snapdragon Spaces Ready alongside its OnePlus 11 5G — which is the first Snapdragon 8 Gen 2 device to be approved as Snapdragon Spaces Ready and will enable developers to bring head-worn AR ideas to life.
“NTT QONOQ was founded Oct 2022 to drive XR business development. XR devices will be fundamental to our value proposition, and we are thrilled to be working together with Qualcomm Technologies and Snapdragon Spaces in this new frontier,” said Mikio Iwamura, executive vice president at NTT QONOQ in a statement.
Analyst firm CCS Insight revealed its first white paper “The Operator Opportunity: VR, AR and the Metaverse” which features inventive XR insight from Qualcomm Technologies and leading global operators.
“XR, paired with 5G, is poised to unleash a massive wave of new innovative applications for consumers and businesses alike,” said John Saw, an executive at T-Mobile, in a statement. “As the lead North America 5G launch partner for Snapdragon Spaces, we are honored to work with Qualcomm Technologies and others to continue fueling the advancement of XR on our industry-leading 5G network.” At MWC, Qualcomm also announced the Snapdragon Digital Chassis connected car technology portfolio with its Snapdragon Auto 5G Modem-RF Gen 2. It also said that six companies are developing smartphones with Qualcomm’s Snapdragon Satellite technology.
And it also said it is doing research and development laying the groundwork for 6G technology over the next decade.
GamesBeat's creed when covering the game industry is "where passion meets business." What does this mean? We want to tell you how the news matters to you -- not just as a decision-maker at a game studio, but also as a fan of games. Whether you read our articles, listen to our podcasts, or watch our videos, GamesBeat will help you learn about the industry and enjoy engaging with it.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Prophesee teams with Qualcomm on faster event-based smartphone cameras | VentureBeat"
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"https://venturebeat.com/ai/prophesee-teams-with-qualcomm-on-faster-event-based-smartphone-cameras"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Prophesee teams with Qualcomm on faster event-based smartphone cameras Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Prophesee has partnered with Qualcomm to bring a new kind of fast image sensor to smartphone cameras.
The “event-based” Metavision technology will enable smartphone cameras that can capture fast action in comparison to today’s image sensors. The company made the announcement with Qualcomm at the Mobile World Congress event in Barcelona.
The idea is to bring the speed, efficiency, and quality of neuromorphic-enabled vision to mobile devices.
The technical and business collaboration will provide mobile device developers a fast and efficient way to leverage the Paris-based Prophesee sensor’s ability to dramatically improve camera performance, particularly in fast-moving dynamic scenes (e.g. sport scenes) and in low light, through its breakthrough event-based continuous and asynchronous pixel sensing approach.
In contrast to normal image sensors, the event-based sensors designed by Prophesee only capture what changes in a smartphone image. That enables them to skip the processing required by other kinds of sensors which process every single pixel in an image. Prophesee only captures the changes, or events, that reflect something that is changing in a moving image.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Prophesee and Qualcomm have agreed to a multi-year collaboration to enable native compatibility between Prophesee’s Event-Based Metavision Sensors & Software and premium Snapdragon mobile platforms.
The world is neither raster-based nor frame-based. Inspired by the human eye, Prophesee Event-Based sensors repair motion blur and other image quality artifacts caused by conventional sensors, especially in high dynamic scenes and low light conditions bringing Photography and Video closer to our true experiences, Prophesee said.
“Prophesee is a clear leader in applying neuromorphic techniques to address limitations of traditional cameras and improve the overall user experience. We believe this is game-changing technology for taking mobile photography to the next level and our collaboration on both the technical and business levels will help drive adoption by leading OEMs,” said Judd Heape, vice president of product management at Qualcomm Technologies, in a statement. “Their pioneering achievements with event cameras’ shutter-free capability offer a significant enhancement to the quality of photography available in the next generation of mobile devices powered by Snapdragon, even in the most demanding environments, unlocking a range of new possibilities for Snapdragon customers.” Prophesee’s neuromorphic Event-Based Metavision sensors and software will be available for premium Snapdragon mobile platforms. Development kits are expected to be available from Prophesee this year.
“We are excited to be working with the provider of one of the world’s most popular mobile platforms to incorporate event-based vision into the Snapdragon ecosystem. Through this collaboration, product developers will be able to dramatically enhance the user experience with cameras that deliver image quality and operational excellence not available using just traditional frame-based methods,” said Luca Verre, CEO of Prophesee, in a statement.
How it works Prophesee’s breakthrough sensors add a new sensing dimension to mobile photography. They change the paradigm in traditional image capture by focusing only on changes in a scene, pixel by pixel, continuously, at extreme speeds, the companies said.
Each pixel in the Metavision sensor embeds a logic core, enabling it to act as a neuron. They each activate themselves intelligently and asynchronously depending on the number of photons they sense. A pixel activating itself is called an event. In essence, events are driven by the scene’s dynamics, not an arbitrary clock anymore, so the acquisition speed always matches the actual scene dynamics.
High-performance event-based deblurring is achieved by synchronizing a frame-based and Prophesee’s event-based sensor. The system then fills the gaps between and inside the frames with microsecond events to algorithmically extract pure motion information and repair motion blur.
A development kit featuring compatibility with Prophesee sensor technologies is expected to be available this year. Prophesee has more than 100 engineers and 50 international patents.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"OpenAI has grand 'plans' for AGI. Here's another way to read its manifesto | The AI Beat | VentureBeat"
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"https://venturebeat.com/ai/openai-has-grand-plans-for-agi-heres-another-way-to-read-its-manifesto-the-ai-beat"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages OpenAI has grand ‘plans’ for AGI. Here’s another way to read its manifesto | The AI Beat Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Am I the only one who found Open AI’s latest blog post, “ Planning for AGI and Beyond ” problematic? From its inception in 2015, OpenAI has always made it clear that its central goal is to build artificial general intelligence (AGI). Its stated mission is “to ensure that artificial general intelligence benefits all of humanity.” To be fair, the blog post was no different — it discussed how the company believes the world can prepare for AGI, both in the short and long term.
Some found the manifesto-of-sorts, which has a million “likes” on Twitter alone, “fascinating.” One tweet called it a “must-read for anyone who expects to live 20 more years.” Another tweet thanked Sam Altman, saying “more reassurance like this is appreciated as it was all getting rather scary and felt like @openai was going off-piste. Communication and consistency is key in maintaining trust.” >>Follow VentureBeat’s ongoing generative AI coverage<< VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Others found it, well, less than appealing. Emily Bender, professor of linguistics at the University of Washington, said : “From the get-go this is just gross. They think they are really in the business of developing/shaping ‘AGI.’ And they think they are positioned to decide what ‘benefits all of humanity.'” And Gary Marcus, professor emeritus at NYU and founder and CEO of Robust AI , tweeted , “I am with @emilymbender in smelling delusions of grandeur at OpenAI.” Computer scientist Timnit Gebru, founder and executive director of the Distributed Artificial Intelligence Research Institute (DAIR) , went even further, tweeting : “If someone told me that Silicon Valley was ran by a cult believing in a machine god for the cosmos & “universe flourishing” & that they write manifestos endorsed by the Big Tech CEOs/chairmen and such I’d tell them they’re too much into conspiracy theories. And here we are.” OpenAI’s prophetic tone Personally, I think it’s notable that the blog post’s verbiage, which remains remarkably consistent with OpenAI’s roots as an open, nonprofit research lab, gives off a far different vibe today in the context of its current high-powered place in the AI landscape. After all, the company is no longer “open” or nonprofit, and recently enjoyed a reported infusion of $10 billion from Microsoft.
In addition, the release of ChatGPT on November 30 led OpenAI to enter the zeitgeist of public consciousness. Over the past three months, hundreds of millions of people have been introduced to OpenAI — but surely most have little inkling of its history with and attitude toward AGI research.
Their understanding of ChatGPT and DALL-E has likely been limited to its use as either a toy, creative inspiration or a work assistant. Does the world understand how OpenAI sees itself as potentially influencing the future of humanity? Certainly not.
OpenAI’s grand message also seems disconnected from its product-focused PR of the past couple of months, around how tools like ChatGPT or Microsoft’s Bing might help in use cases like search results or essay writing. Thinking about how AGI could “ empower humanity to maximally flourish in the universe” made me giggle — how about just figuring out how to keep Bing’s Sydney from having a major meltdown ? With that in mind, to me Altman comes across as a kind of wannabe biblical prophet. The blog post offers revelations, foretells events, warns the world of what is coming, and presents OpenAI as the trustworthy savior.
The question is, are we talking about a true seer? A false prophet? Just profit ? Or even a self-fulfilling prophecy? With no agreed-upon definition of AGI, no widespread agreement on whether we are near AGI, no metrics on how we would know whether AGI was achieved, no clarity around what it would mean for AGI to “benefit humanity,” and no general understanding of why AGI is a worthwhile long-term goal for humanity in the first place if the “existential” risks are so great, there is no way to answer those questions.
That makes OpenAI’s blog post a problem, in my opinion, given the many millions of people hanging onto Sam Altman’s every utterance (to say nothing of the millions more waiting impatiently for Elon Musk’s next existential AI angst tweet). History is filled with the consequences of apocalyptic prophesies.
Some point out that OpenAI has some interesting and important things to say about how to tackle challenges related to AI research and product development. But are they overshadowed by the company’s relentless focus on AGI? After all, there are plenty of important short-term AI risks to tackle (bias, privacy, exploitation and misinformation, just to name a few) without shifting focus to doomsday scenarios.
The Book of Sam Altman I decided to take a stab at reworking OpenAI’s blog post to deepen its prophetic tone. It required assistance — not from ChatGPT, but from the Old Testament’s Book of Isaiah : 1:1 – The vision of Sam Altman, which he saw concerning planning for AGI and beyond.
1:2 – Hear, O heavens, and give ear, O earth: for OpenAI hath spoken, our mission is to ensure that artificial general intelligence (AGI) — AI systems that are generally smarter than humans — benefits all of humanity.
1:3 – The ox knoweth his owner, and the ass his master’s crib: but humanity doth not know, my people doth not consider. For lo, if AGI is successfully created, this technology could help us elevate humanity by increasing abundance, turbocharging the global economy, and aiding in the discovery of new scientific knowledge that changes the limits of possibility.
1:4 – Come now, and let us reason together, saith OpenAI: AGI has the potential to give everyone incredible new capabilities; we can imagine a world where all of us have access to help with almost any cognitive task, providing a great force multiplier for human ingenuity and creativity.
1:5 – If ye be willing and obedient, ye shall eat the good of the land. But if ye refuse and rebel, on the other hand, AGI would also come with serious risk of misuse, drastic accidents and societal disruption.
1:6 – Therefore saith OpenAI, the mighty One of Silicon Valley, because the upside of AGI is so great, we do not believe it is possible or desirable for society to stop its development forever; instead, society and the developers of AGI have to figure out how to get it right.
1:7 – And the strong shall be as tow, and the maker of it as a spark, and they shall both burn together, and none shall quench them. We want AGI to empower humanity to maximally flourish in the universe. We don’t expect the future to be an unqualified utopia, but we want to maximize the good and minimize the bad, and for AGI to be an amplifier of humanity. Take counsel, execute judgment.
1:8 – And it shall come to pass in the last days, as we create successively more powerful systems, we want to deploy them and gain experience with operating them in the real world. We believe this is the best way to carefully steward AGI into existence — a gradual transition to a world with AGI is better than a sudden one. Fear, and the pit, and the snare, are upon thee, O inhabitant of the earth.
1:9 – The lofty looks of man shall be humbled, and the haughtiness of men shall be bowed down, and OpenAI alone shall be exalted in that day. Some people in the AI field think the risks of AGI (and successor systems) are fictitious; we would be delighted if they turn out to be right, but we are going to operate as if these risks are existential.
1:10 – Moreover OpenAI saith we will need to develop new alignment techniques as our models become more powerful (and tests to understand when our current techniques are failing). Lift ye up a banner upon the high mountain, exalt the voice unto them, shake the hand, that they may go into the gates of the nobles.
1:11 – Butter and honey shall he eat, that he may know to refuse the evil, and choose the good. The first AGI will be just a point along the continuum of intelligence. We think it’s likely that progress will continue from there, possibly sustaining the rate of progress we’ve seen over the past decade for a long period of time.
1:12 – If this is true, the world could become extremely different from how it is today, and the risks could be extraordinary. Howl ye; for the day of AGI is at hand.
1:13 – With arrows and with bows shall men come thither; because all the land shall become briers and thorns. A misaligned superintelligent AGI could cause grievous harm to the world; an autocratic regime with a decisive superintelligence lead could do that too. The earth mourneth and fadeth away.
1:14 – Behold, successfully transitioning to a world with superintelligence is perhaps the most important — and hopeful, and scary — project in human history. And they shall look unto the earth; and behold trouble and darkness, dimness of anguish; and they shall be driven to darkness. And many among them shall stumble, and fall, and be broken, and be snared, and be taken.
1:15 – They shall not hurt nor destroy in all my holy mountain: for the earth shall be full of the knowledge of OpenAI, as the waters cover the sea. Success is far from guaranteed, and the stakes (boundless downside and boundless upside) will hopefully unite all of us. Therefore shall all hands be faint, and every man’s heart shall melt.
1:16 – And it shall come to pass, that we can imagine a world in which humanity flourishes to a degree that is probably impossible for any of us to fully visualize yet. And now, O inhabitants of earth, we hope to contribute to the world an AGI aligned with such flourishing. Take heed, and be quiet; fear not.
1:17: Behold, OpenAI is my salvation; I will trust, and not be afraid.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Hugging Face, AWS partner on open-source machine learning amidst AI arms race | VentureBeat"
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"https://venturebeat.com/ai/hugging-face-aws-partner-on-open-source-machine-learning-amidst-ai-arms-race"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Hugging Face, AWS partner on open-source machine learning amidst AI arms race Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Impressive advances in large language models (LLMs) are showing signs of what could be the beginnings of a major shift in the tech industry. AI startups and big tech companies are finding novel ways to put advanced LLMs to use in everything from composing emails to generating software code.
However, the promises of LLMs have also triggered an arms race between tech giants. In their efforts to build up their AI arsenals, big tech companies threaten to push the field toward less openness and more secrecy.
In the midst of this rivalry, Hugging Face is mapping a different strategy that will provide scalable access to open- source AI models. Hugging Face is collaborating with Amazon Web Services (AWS) to facilitate adoption of open-source machine learning (ML) models. In an era when advanced models are becoming increasingly inaccessible or hidden behind walled gardens, an easy-to-use open-source alternative could expand the market for applied machine learning.
Open-source models While large-scale machine learning models are very useful, setting up and running them requires special expertise that few companies possess. The new partnership between Hugging Face and AWS will try to address these challenges.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Developers can use Amazon’s cloud tools and infrastructure to easily fine-tune and deploy state-of-the-art models from Hugging Face’s ML repository.
The two companies began working in 2021 with the introduction of Hugging Face deep learning containers (DLCs) on SageMaker, Amazon’s cloud-based machine learning platform. The new partnership will extend the availability of Hugging Face models to other AWS products and Amazon’s cloud-based AI accelerator hardware to speed up training and inference.
“Since we started offering Hugging Face natively in SageMaker, usage has been growing exponentially, and we now have more than 1,000 customers using our solutions every month,” Jeff Boudier, product director at Hugging Face, told VentureBeat. “Through this new partnership, we are now working hand in hand with the engineering teams that build new efficient hardware for AI, like AWS Trainium and AWS Inferentia, to build solutions that can be used directly on Elastic Compute Cloud (EC2) and Elastic Kubernetes Service (EKS).” The AI arms race Tech leaders have been talking about the transformative nature of machine learning for several years. But never has this transformation been felt as it has in the past few months. The release of OpenAI’s ChatGPT language model has set the stage for a new chapter in the race for AI dominance.
Microsoft recently poured $10 billion into OpenAI and is working hard to integrate LLMs into its products. Google has invested $300 million into Anthropic, an OpenAI rival, and is scrambling to protect its online search empire against the rise of LLM-powered products.
There are clear benefits to these partnerships. With Microsoft’s financial backing, OpenAI has been able to train very large and expensive machine learning models on specialized hardware and deploy them at scale to millions of people. Anthropic will also receive special access to the Google Cloud Platform through its new partnership.
However, the rivalry between big tech companies also has tradeoffs for the field. For example, since it began its partnership with Microsoft, OpenAI stopped open-sourcing most of its machine learning models and is serving them through a paid application programming interface (API). It has also become locked into Microsoft’s cloud platform, and its models are only available on Azure and Microsoft products.
On the other hand, Hugging Face remains committed to continuing to deliver open-source models. Through the partnership between Hugging Face and Amazon, developers and researchers will be able to deploy open-source models such as BLOOMZ (a GPT-3 alternative) and Stable Diffusion (a rival to DALL-E 2).
“This is an alliance between the leader of open-source machine learning and the leader in cloud services to build together the next generation of open-source models, and solutions to use them. Everything we build together will be open-source and openly accessible,” Boudier said.
Hugging Face also aims to avoid the kind of lock-in that other AI companies are facing. While Amazon will remain its preferred cloud provider, Hugging Face will continue to work with other cloud platforms.
“This new partnership is not exclusive and does not change our relations with other cloud providers,” Boudier said. “Our mission is to democratize good machine learning, and to do that we need to enable users wherever they are using our models and libraries. We’ll keep working with Microsoft and other clouds to serve customers everywhere.” Openness and transparency The API model provided by OpenAI is a convenient option for companies that don’t have in-house ML expertise. Hugging Face has also been delivering a similar service through its Inference Endpoint and Inference API products. But APIs will prove to be limited for organizations that want more flexibility to modify the models and integrate them with other machine learning architectures. They are also inconvenient for research that requires access to model weights, gradients and training data.
Easy-to-deploy, scalable cloud tools such as those provided by Hugging Face will enable these kinds of applications. At the same time, the company is developing tools for detecting and flagging misuse, bias and other problems with ML models.
“Our vision is that openness and transparency [are] the way forward for ML,” Boudier said. “ML is science-driven and science requires reproducibility. Ease of use makes everything accessible to the end users, so people can understand what models can and cannot do, [and] how they should and should not be used.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"How D-Id is merging avatars with conversational AI for enterprise use cases | VentureBeat"
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"https://venturebeat.com/ai/how-d-id-is-merging-avatars-with-conversational-ai-for-enterprise-use-cases"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages How D-Id is merging avatars with conversational AI for enterprise use cases Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Generating digital humans (avatars) is a process increasingly making use of artificial intelligence (AI).
And, the power of generative AI is now coming to avatars. This could have wide-ranging implication for enterprises, including customer support and experience.
Today, Israeli startup D-ID announced the launch of its new chat.d-id chat, which melds its widely-used digital human platform with Large Language Models (LLMs) for conversational AI. D-ID’s eponymous platform has been used to generate more than 100 million lifelike digital humans over the last two years. The core D-ID platform enables anyone to simply load up a new image or choose from an existing inventory of pre-built avatars that are able to vocalize text-to-speech using different voices and in different languages.
The integration of generative AI now enables avatars to benefit from real-time streaming that provides a conversational AI approach. So instead of just a one-way vocalization of text-to-speech, D-ID avatars can now converse with and provide answers to real humans. D-ID technology is also being extended with an application programming interface (API) that will enable developers to build customized conversational AI avatar experiences for enterprise use cases.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! “This is an evolution of the digital person from just presenting one-way communication,” Gil Perry, CEO and cofounder of D-ID, told VentureBeat. “The streaming capability enables our partners and developers to build products that enable you to converse with the avatar in real time.” Putting a (digital) human face to conversational AI for enterprise Chatbots are perhaps one of the most common use cases of conversational AI today.
With a chatbot, a customer can interact with a vendor’s support service. In 2023, an emerging trend has been the integration of LLM-powered chatbots , with ChatGPT being perhaps the most notable. One thing that most chatbots have had in common is that they are text based, with some also using audio. But, Perry’s goal is to provide a more personalized experience with a life-like digital human avatar.
The goal with chat.d-id isn’t to just integrate with an existing LLM, but to help enterprises customize a generative AI model for a specific business and its operations. The chat.d-id approach isn’t just about providing answers, but also about automation, said Perry. It has the ability to execute operations such as updating a customer’s account or changing a service level.
“So instead of trying to understand how to operate your new computer, app or website, you just speak to it (as you would) speak with a person, because you don’t want to speak with text, as it’s harder to understand,” said Perry. “We humans are wired to communicate with humans.” Extending avatars for enterprise with API The ability to programmatically integrate with an existing enterprise application workflow is critical to enable adoption, said Perry. That’s where APIs will now fit in.
With the API, Perry said, developers will have full access to the capabilities of the chat.d-id platform, enabling an enterprise to highly customize and integrate an avatar into an existing user experience workflow. He said he also expects that enterprise developers will build entirely new support workflows around the API that help to improve user experience.
Perry said that d-id has a session about its API at the upcoming Nvidia GTC conference. The company will go into detail on how it works and can be implemented by developers.
“The vision here is to disrupt how humans interface with anything digital,” said Perry.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
All rights reserved.
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"How customizing models is bringing generative AI to the enterprise | VentureBeat"
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"https://venturebeat.com/ai/how-customizing-models-is-bringing-generative-ai-to-the-enterprise"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages How customizing models is bringing generative AI to the enterprise Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
There is a lot of hype and activity around generative AI models, especially in the short time since ChatGPT first launched.
ChatGPT — and the GPT-3 large language model (LLM) it is based on — have been trained on public data, which serves as a great foundation for consumer applications, but lacks the customization, privacy and security that an enterprise requires. That’s where Rodrigo Liang, cofounder and CEO of SambaNova Systems , is looking to make a difference with the launch today of his company’s SambaNova Suite, which aims to help enterprises build and deploy customized generative AI models.
>>Follow VentureBeat’s ongoing generative AI coverage<< SambaNova got its start in 2017 focused largely on hardware for AI, raising a staggering $676 million in April 2021 to support its efforts. In recent years, the company has expanded beyond its initial focus on hardware to also build out support for both machine learning–training and inference on different models, with its dataflow-as-a-service offering. The new SambaNova Suite expands on the dataflow service with a collection of capabilities that enables organizations to customize both open-source and proprietary generative AI models to meet their specific requirements.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! “The focus of SambaNova is how to bring generative AI capabilities more to the enterprise,” Liang told VentureBeat. “There are certain things that you need for enterprises in order to be able to be successful, and we’re doing that today for them.” Nvidia isn’t the only AI hardware vendor for generative AI There is a growing list of vendors building on top of generative AI models to help enable enterprise use cases.
Content creation is a particularly vibrant field of enterprise generative AI customization.
Jasper AI , for example, recently announced its Jasper for Business offering designed to help customize AI for a specific business.
Typeface emerged from stealth on Monday with its enterprise content creation platform for generative AI, alongside $65 million in funding.
Quantive last week announced its foray into generative AI, helping organizations with their business strategy.
SambaNova’s key differentiator from others in the generative AI space is that it has its own hardware to help optimize enterprise use cases. Rather than just relying on Nvidia GPUs like many in the industry, SambaNova has developed its own custom silicon that is optimized for both machine learning–training and inference.
“What we’ve done is … take the AI software stack that people really want to use with PyTorch , TensorFlow and complex models like GPT, and we bring them down all the way to the silicon,” Liang said. “We have silicon that’s actually been custom built for running these large models for the enterprise, versus the other way around.” The team behind SambaNova, including Liang, has a background in building microprocessors for Sun Microsystems and Oracle. Liang said that SambaNova has created a microprocessor for AI that is extremely power efficient and performative in order to run these enterprise generative AI applications.
Liang emphasized that the custom silicon also enables a continuous training and inference capability, such that the data that feeds the generative AI models can be kept up to date.
“In business, you need real-time information and so you do not want your models to actually lag behind,” he said.
Privacy, responsible AI and the enterprise With the new SambaNova Suite, Liang said that his company is looking to solve the primary challenges that enterprises have with generative AI. Among those challenges are customization for a company’s specific data, as well the ability to limit bias and provide responsible and explainable AI.
With its platform, SambaNova enables an organization to run customized training in a private environment on any data the organization has, including unstructured data that might be found in a company’s Slack discussion channels. Going a step further, Liang said the platform provides transparency to organizations for how a given AI model actually works.
“SambaNova has been built around being able to give you exposure of exactly how the model arrived at a certain conclusion,” Liang said. “We store all the processes around how we train and fine-tune the model, so that when an auditor comes or somebody wants to check for bias or why something happened a certain way, you can actually work through the flow and verify that your results were done properly.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Federated learning at the edge may out-compete the cloud on privacy, speed and cost | VentureBeat"
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"https://venturebeat.com/ai/federated-learning-at-the-edge-may-out-compete-the-cloud-on-privacy-speed-and-cost"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Federated learning at the edge may out-compete the cloud on privacy, speed and cost Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
In the 2000s, the cloud began to take off. Programmers and businesses started to procure virtual compute resources on demand to run their software and applications.
Over the last two decades, developers have grown accustomed to, and reliant on, instantly available infrastructure managed and maintained by someone else. And this is no surprise. Abstracting hardware and infrastructure away enables developers and companies to focus on product innovation and user features above all else.
Amazon Web Services, Microsoft Azure and Google Cloud have made storage and compute ubiquitous, on-demand and straightforward to deploy. And these hyperscalers have built robust, high-margin businesses atop this approach. Organizations reliant on the cloud have traded capital expenditures (servers and hardware) for operating expenditures (pay-as-you-go compute and storage resources).
Enter federated learning Although the cloud’s ease of use is a boon to any upstart team trying to innovate at all costs, cloud-centric architecture is a significant cost as a company scales. In fact, 50% of large SaaS company revenue goes toward cloud infrastructure.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! As machine learning (ML) continues to grow in popularity and utility, organizations store an increasing amount of data in the cloud and train larger and larger models in search of higher model accuracy and greater user benefit. This further exacerbates reliance on cloud providers, and organizations find it difficult to repatriate workloads to on-premises solutions. In fact, doing so would require them to hire a stellar infrastructure team and re-architect their systems altogether.
Organizations are looking for tools that enable new product innovation and offer high accuracy with low latency while still being cost-effective.
Enter federated learning (FL) on the edge.
What is Federated Learning on the edge? Federated learning, or collaborative learning, takes a different approach to data storage and compute. For example, whereas popular cloud-centric ML approaches send data from your phone to centralized servers and aggregate this data in a silo, FL on the edge keeps data on the device (that is, your mobile phone or your tablet). It works in the following way: Step 1: Your edge device (or mobile phone) downloads an initial model from an FL server.
Step 2: On-device training is then conducted; data on the device improves the model.
Step 3: The encrypted training results are sent back to the server for model improvement while the underlying data sits safely on the user’s device.
Step 4: With the model on the device, you conduct training and inference on the edge in a completely distributed and decentralized way.
This loop continues iteratively and your model accuracy increases.
Federated learning benefits for the user When you aren’t reliant on or bottlenecked by centralized data, the user benefits in dramatic ways. With FL on the edge, developers can reduce latency, reduce network calls and drive power efficiency all while promoting user privacy and improved model accuracy.
FL on the edge is enabled by the ever-increasing hardware capabilities of the phones in our pockets. Each year, on-device computation and battery life improve. As the smartphone processor and hardware in our pocket improves, FL techniques will unlock increasingly complex and personalized use cases.
Imagine, for example, software that sits on your phone in a privacy-centric way that can automatically draft replies to incoming emails with your individual tone, punctuation style, slang and other hyper-personalized attributes — all you have to do is click “Send.” Enterprise pull is strong In my conversations with multiple Fortune 500 companies, it has been blindingly obvious how much demand there is for FL on the edge across sectors. CTOs express how they’ve been searching for a solution to bring FL techniques on the edge to life. They reference the millions of dollars spent on infrastructure and model deployment that could otherwise be saved with an FL approach.
In my opinion, the three industries that have the most potential to reap the rewards of federated learning are finance, media and ecommerce. Let me explain why.
Use case 1: Finance — improved latency and security Many large multinational financial companies (e.g. Mastercard, PayPal) are eager to adopt FL on the edge to assist them with identifying account takeovers, money laundering and fraud detection. More accurate models are sitting on the shelf and have not been approved for launch.
Why? These models increase latency just enough that the user experience is negatively impacted — we can all think of apps we no longer use because they took too long to open or crashed. Companies can’t afford to lose users for these reasons.
Instead, they accept a higher false negative rate and suffer excess account hijacking, laundering and fraud. FL on the edge empowers companies to simultaneously improve latency while showing relative uplift in model performance compared to traditional cloud-centric deployments.
Use case 2: Media — hyper-personalization In the media sector, companies like Netflix and YouTube want to increase the relevance of their suggestions for movies or videos to watch. The Netflix Prize famously awarded $1 million for a 10% uplift in performance compared to its own algorithm.
FL on the edge has the potential to have a similar impact.
Today, when a new show is launched or a popular sporting event is live (like the Super Bowl), companies reduce the signals they gather from their users. Otherwise, the sheer volume of data (at a rate of millions of requests per second) causes a network bottleneck that prevents them from recommending content at scale.
With edge computing, companies can use these signals to suggest personalized content based on insight from individual users’ tastes and preferences.
Use case 3: Ecommerce — more timely and relevant suggestions Ecommerce and marketplace companies want to increase click-through rates (CTR) and drive conversions based on real-time feature stores. This enables them to re-rank recommendations for customers and serve more accurate predictions without the lag of traditional cloud-based recommendations.
Imagine, for example, opening the Target app on your phone and getting highly personalized recommendations for products in a completely privacy-centric way — no identifying data would have left your phone. Federated learning can increase CTR thanks to a more performant, privacy-aware model that offers users more timely and relevant suggestions.
The market landscape Thanks to technological advances, large corporations and startups alike are working to make FL ubiquitous so that companies and consumers alike can benefit. For companies, this likely means lower costs; for consumers, it may mean a better user experience.
There are already a few early players in the space: Amazon SageMaker allows developers to deploy ML models primarily on edge devices and embedded systems; Google’s Distributed Cloud extends its infrastructure to the edge; and upstart companies like NimbleEdge are reimagining the infrastructure stack.
While we are in the early innings, FL on the edge is here and the hyperscalers are in an incumbent’s dilemma. The revenue that cloud providers earn for compute, storage and data is at risk; modern vendors who have adopted edge computing architecture can offer customers premium ML model accuracy and reduced latency. This improves user experience and drives profitability — a value proposition that you can’t ignore for long.
Neeraj Hablani is a partner at Neotribe Ventures focused on early-stage companies making breakthrough technologies.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"ChatGPT and its implications for customer experience | VentureBeat"
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"https://venturebeat.com/ai/chatgpt-and-its-implications-for-customer-experience"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages ChatGPT and its implications for customer experience Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
OpenAI opened the ChatGPT beta in late November 2022, in a move that produced the most powerful natural language processing (NLP) AI model to date. It quickly went viral, attracting a million users in the first five days.
Will models like ChatGPT completely replace chatbots? The underlying premise of this question is whether large language models (LLMs) like ChatGPT will transform the reputation of chatbots from clunky, impersonal and faulty into algorithms so meticulous that (a) human interaction is no longer needed, and (b) traditional ways of building chatbots are now completely obsolete. We’ll explore these premises and give our view on how ChatGPT will impact the CX space.
Broadly speaking, we differentiate between conventional chatbots and chatbots like ChatGPT built on generative LLMs.
Conventional chatbots This category includes most chatbots you’ll encounter in the wild, from chatbots for checking the status of your DPD delivery to customer service chatbots for multinational banks. Built on technologies like DialogFlow , IBM Watson or Rasa , they are limited to a specific set of topics and are not able to respond to inputs outside of those topics (i.e. they are closed-domain). They can only produce responses that have been pre-written or pre-approved by a human (i.e. they are non-generative).
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! LLM-based chatbots These can respond to a wide range of topics (i.e. they are open-domain) and generate responses on the fly, rather than just selecting from a pre-written list of responses (i.e. they are generative). They include Google Meena , Replika.ai , BlenderBot , ChatGPT and others.
LLM-based chatbots and conventional chatbots fulfill somewhat different purposes. Indeed, for many CX applications, LLMs’ open nature is less help and more hindrance when building a chatbot that can specifically answer questions about your product or help a user with an issue they’re experiencing.
Realistically, LLMs won’t be let loose into the CX domain tomorrow. The process will be much more nuanced. The name of the game will be marrying the expressiveness and fluency of ChatGPT with the fine-grained control and boundaries of conventional chatbots. This is something that chatbot teams with a research focus will be best suited for.
Where can you already use ChatGPT today when creating chatbots? There are many aspects of chatbot creation and maintenance that ChatGPT is not suited for in its current state, but here are some for which it is already well-suited: Brainstorming potential questions and answers for a given closed domain, either on the basis of its training data, or fine-tuned on more specific information — either by OpenAI releasing the ability for fine-tuning when ChatGPT becomes accessible by API, or through including desired information via prompt engineering. (Caveat: It is still difficult to know with certainty where a piece of information comes from, so this development process will continue to require a human in the loop to validate output.) Training your chatbot: ChatGPT can be used to paraphrase questions a user might ask, particularly in a variety of styles, and even generate example conversations, thereby automating large parts of the training.
Testing and QA.
Using ChatGPT to test an existing chatbot by simulating user inputs holds much promise, particularly when combined with human testers. ChatGPT can be told the topics to cover in its testing, with different levels of granularity, and, as with generating training data, the style and tone it uses can be varied.
We see the next generation of CX chatbots continuing to be based on conventional, non-generative technology, but generative models being used heavily in the creation process.
Chatbots are set to level up the current CX space LLMs’ key impacts on consumer expectations will include increased visibility of chatbots, greater urgency to incorporate them into CX, a heightened reputation for chatbots and a higher standard. In other words, chatbots are getting a glow-up! We’ve all experienced them — clunky chatbots with extremely limited dialogue options that churn out painfully robotic lines (if they can understand anything at all). While poorly performing chatbots are already on the way out, standards will now be shooting through the roof to avoid this experience, and the shift from human to AI will rapidly continue.
A recent report predicts that the number of interactions between customers and call centers handled by AI will increase from 2% in 2022 to more than 15% by 2026, then double to 30% by 2031. However, given the rapid adoption of and exponential advancements in AI over the past three to five years, we anticipate the true growth to be far greater.
Brands like Lemonaid , Oura , AirBnb and ExpressVPN have paved the way for excellent 24/7 support — so much so that today’s customers now simply expect a seamless experience. The consequences of missing out on delivering great service are no joke. Poor service can have a significant impact on a brand’s retention rates, causing would-be buyers to look elsewhere: According to Forbes, bad customer service costs businesses a combined $62 billion each year.
Risks in using today’s LMM-based chatbots ChatGPT is certainly in a hype phase, but there are significant risks in using it as-is right now. We believe that the majority of the current risks result from ChatGPT’s unpredictability, which creates reputational, brand and legal concerns. Whilst the buzz around ChatGPT is good, you must not forget its associated risks, and the importance of selecting the right partner to avoid any pitfalls.
In particular, we see the following risks for big businesses adopting LLMs directly into their customer journey: Harm to brand image — sharing of offensive content Misleading customers — sharing false content Potential for adversarial attack — people trying to break the chatbot to damage reputations False creativity — users mistaking the “stochastic parrot” for genuine human creativity/connection False authority — ChatGPT produces authoritative-sounding text which humans are notoriously bad at refuting.
Data security and data ownership and confidentiality — OpenAI has insight and access to all data shared via ChatGPT, opening huge risk floodgates for confidentiality breaches.
In other words: “Just because you can doesn’t mean you should” Startups and established organizations will inevitably try to introduce safeguards and other measures to mitigate some of these risks. However, a lot of companies, including many of those we work with, still want (or are legally obliged) to retain full control of the content. Our legal and FCA-regulated clients are a good example. With generative LLMs like ChatGPT retaining full content, control is impossible.
When it comes to chatbot development itself, players using open-source stacks like Rasa or Botpress will have the advantage of agility due to the flexibility and versatility these open systems enable. In the short to medium term, chatbot developers with experience in NLP and using LLMs will be the ones to bring this technology to the chatbot market, because they are able to effectively leverage and fine-tune the models to their (or their clients’) needs and use cases.
In the long term, small companies will continue to be better positioned to swiftly implement changes than large, established platforms like ChatGPT. Amidst the current financial market volatility, however, we anticipate a potential market consolidation of players in the next 12-24 months, with the larger players acquiring smaller players, and — a common occurrence in the chatbot space — clients buying their chatbot suppliers.
Which industries will adopt ChatGPT in their CX processes first? Despite ChatGPT only being in beta and no API yet available, there has been a myriad of exciting use cases published by individuals, including a number of browser extensions , mainly via Twitter.
As long as ChatGPT is available to the public (we expect a volume-based pricing model to come, as with previous models like GPT-3), small players will continue to be the ones pushing the boundaries with novel applications.
Victoria Albrecht is a cofounder and managing director of Springbok AI.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
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You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Transforming organizations one emoji at a time | VentureBeat"
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"https://venturebeat.com/virtual/transforming-organizations-one-emoji-at-a-time"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Transforming organizations one emoji at a time Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
How did we go from calling emojis inappropriate for the workplace, to typing smileys in our closing lines? Is it a change in corporate culture, or have you simply crossed a line? What if we told you it’s a bit of both? The shift toward hybrid and remote work has left a gap in organizations, so professionals have had to find creative methods of connecting with their peers. From Zoom sessions to shared Google Docs, collaboration in everyday work is as great as ever. Still, it can often feel as though words don’t convey message or emotion, which can simply get lost in translation.
Global perception The workplace messaging platform Slack recently shared the results of a survey of 9,400 hybrid office workers from North America, Australia and parts of Europe and Asia. It found that 58% of participants globally believed that emojis at work provide more nuance in fewer words (69% in the U.S.) and 54% believed emojis provide greater efficiency in communication (67% in the U.S.).
The Slack survey also reported that “Interestingly, Indian, Chinese and American workers are most likely to find emoji-less texts or messages lacking, especially compared with global respondents.” And it predicts that these numbers will grow and the gap will decrease as digital-native generations take over the job market.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Do emojis equal better emotion? Researchers have found that emotions in the digital workspace are likely to be more contagious than in the context of a regular office, described as “digital emotion contagion.” Hybrid work has employees glued to screens and absorbing more of others’ emotions through them. Their emotions can then be persuaded by others they’re in contact with either directly through communication or indirectly.
This leaves us questioning: How prepared are companies in supporting their employees with these kinds of disruptions in the new norm of digital work? The dynamics of workplace relationships also play a major role in perceived emotion in communication. A CNN article shared researcher findings — from Vyvyan Evans, a professor of linguistics at Bangor University in the UK, and Linda Kaye a senior lecturer in psychology — on what emojis say about individuals.
Kaye stated that people who use emojis with frequency are more “socially receptive and empathetic, making them more approachable.” This suggests emojis are a simple way of reducing the emotional toll of communication in a work environment with great hierarchical barriers. Evans went so far as to say that “someone who is not using them [emojis] is not an effective communicator and therefore not effective in inducing an emotional response.” So, we’re here to tell you that emojis indeed belong in the workplace. Whether you’re a veteran team leader or an entry-level associate, the way you communicate has a great impact on your colleagues’ work. Consider implementing emojis in your everyday work — but, of course, do so responsibly and respectfully.
Yair Nativ is the founder and CEO of Hour25.AI.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Plan now for the internet's transformation by the metaverse and Web3 | VentureBeat"
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"https://venturebeat.com/virtual/plan-now-for-the-internets-transformation-by-the-metaverse-and-web3"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Plan now for the internet’s transformation by the metaverse and Web3 Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Today, the internet is a disparate collection of sites, apps and platforms. Because they are separate from one another, they lack interoperability and data portability. So, despite huge advances made through digital transformation, this current model will eventually constrain businesses. In fact, 95% of executives surveyed for the 2022 Accenture Technology Vision report believe that future digital platforms will need to offer unified experiences, enabling interoperability of customers’ data across different platforms and spaces.
However, thanks to two emerging concepts, a new form of internet is emerging that will transcend these limitations: 1) the metaverse continuum, an evolution of the internet that enables people to participate in a persistent shared experience across real-world and virtual realms, and 2) Web3 , or emerging efforts to build a “distributed” layer to the internet via technologies such as blockchain and tokenization.
Taken together, these are showing us the next generation of the internet — one that moves beyond the fragmented interaction of today into a new world of contiguous immersive experiences.
Web3 and the metaverse: The internet reimagined Put simply, the digital world is in the early stages of an evolution, and eventually the metaverse and Web3 will become critical components of how enterprises orchestrate their digital strategies. The online footprints that companies have built over the past decade will be reimagined, from which services are sold and which data is accessible to how advertising is conducted and content generated.
Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! >>Don’t miss our special issue: The CIO agenda: The 2023 roadmap for IT leaders.
<< With the metaverse, the internet will be rebuilt as a persistent 3D environment, imbued with a sense of place, where moving from work to a social platform is as simple as crossing the road. Meanwhile, Web3 technologies will create a data layer than enables veracity, trust and even scarcity. This new internet will be more human-centric and exponentially more valuable.
Now is the time for companies to decide the role that they will play in the future of the internet. Do they want to be part of the wave that creates this future, or will they be content merely watching how it unfolds? Signs of change Shifts in the digital world over the past 18 months have made it clear that a “wait and see” approach will soon become “look — it already happened.” In fact, enterprises are already thinking about the digital world differently and are capturing new value.
For example, BMW recently built digital twins of 31 different factories. The models use real-time data to create a photo-realistic 3D environment that recreates everything from the machines on the floor to the people populating stations and their individual work-order instructions.
The digital twins are used to train robots to navigate factories, bring together designers from across the globe for experiments, and perform training simulations for individual tasks. Employees can also use the environment to push software updates, monitor individual cells for disruptions, assign new “missions” to the robots on the floor and even teleoperate machines for individual tasks.
A good example of Web3 innovation comes from Inrupt , creator of Solid, lets users control their data and store it in Personal Online Data Stores (Pods). Large organizations and governments can now build websites or applications that interact with Pods, and with people’s permission, access the data they need for given tasks. In common with all Web3 technologies, Solid creates a transaction and trust layer across the web by making different parties the arbiters of their own data.
In digital, technology adoption and related services often snowball. After all, it took just 15 years from the launch of the first iPhone to a world with 6.6 billion smartphones. The internet of tomorrow will be the internet of today before you know it.
Actions to take now Business leaders should start exploring the potential of new products and services today, while training their executives on the technologies that will soon be foundational to their business. As metaverse and Web3 technologies continue to mature, the companies prepared and willing to experiment with new platforms and data structures will be the ones that define the next generation of digital business. There are several factors to consider: Invest in the cloud : The metaverse that emerges will be defined by the services and platforms it encompasses. To even have a presence, enterprises must have the infrastructure to share applications widely and securely. That means rebuilding applications in the cloud with microservice architectures and APIs to be easily usable by, and shareable with, others. These steps should be taken today, even if the end state of the metaverse remains uncertain.
Focus on skills : For the metaverse, enterprises will require 3D artists, game designers and experts in the platforms built. Companies chasing Web3 opportunities will need experience with multiple blockchains. They will need to build relationships with different consortiums, find partners to go to market with and build new business and operating models. Fortunately, the increasing sophistication and democratization of immersive design tools is making it easier than ever to start experimenting with these technologies.
Find partners : Forming new partnerships and ensuring your organization can participate in future collaborations is also critical. Consortiums and industry standards bodies will be important, enabling greater interoperability between companies and making it easier to deliver cross-platform experiences or to jointly collaborate on an experience. By agreeing to a common framework when a technology is in its infancy, businesses can set themselves up to provide more compatible services to future shared consumers.
The metaverse and Web3 are momentous technology shifts, simultaneously working to eliminate the friction that exists between today’s many digital platforms and to reinvent how data moves and is used across digital experiences. As they create a new internet, they will drive new lines of business, new ways of working and new means of interaction between businesses and people. For many organizations, now is the first and best opportunity they have ever had to architect a new kind of digital world.
Marc Carrel-Billiard is the global lead of Accenture Technology Innovation. He oversees all research and development activities of Accenture and leads the delivery of the firm’s annual Technology Vision.
Michael Biltz is managing director of Accenture technology vision at Accenture Labs.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Why enterprises trust hardware-based security over quantum computing | VentureBeat"
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"https://venturebeat.com/security/why-enterprises-trust-hardware-based-security-over-quantum-computing"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Why enterprises trust hardware-based security over quantum computing Share on Facebook Share on X Share on LinkedIn Quantum computer. Conceptual computer artwork of electronic circuitry with blue light passing through it, representing how data may be controlled and stored in a quantum computer.
Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Designing zero trust into silicon and producing hardware-based security at the chip level is delivering on the promises quantum computing made years ago.
But, the core technologies based on quantum computing — quantum bits or qubits — are too noisy to provide the telemetry data that endpoint detection and response ( EDR ) and extended detection and response ( XDR ) need to operate at scale in an enterprise. Even with cybersecurity vendors exploring quantum computing to capture and interpret weak signals, the technology continues to be impractical for mainstream cybersecurity use today.
Quantum computing needs a cybersecurity use case If quantum computing is going to help solve cybersecurity challenges, it must increase the stability, speed and scale in identifying weak signals and stopping breaches while also providing real-time data from powerful algorithms. A recent Financial Times article, “Hype around quantum computing recedes over lack of practical uses,” critiques Chinese researchers’ claims of defeating RSA encryption using quantum computers, a technology attainment predicted to take a decade or longer.
>>Don’t miss our special issue: The CIO agenda: The 2023 roadmap for IT leaders.
<< VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! The article analyzes why claims are improbable. One of the most noteworthy insights is how quantum computing’s current state of qubit technology is too noisy for error correction. The article states, “the quantum bits, or qubits, used in today’s machines are highly unstable and only hold their quantum states for extremely short periods, creating “noise.” As a result, “errors accumulate in the computer, and after around 100 operations there are so many errors the computation fails,” Steve Brierley, chief executive of quantum software company Riverlane , told the Financial Times.
Late last year, H.R.7535 , the Quantum Computing Cybersecurity Preparedness Act, was passed. The act “addresses the migration of executive agencies’ information technology systems to post-quantum cryptography. Post-quantum cryptography is encryption strong enough to resist attacks from quantum computers developed in the future.” CISOs and CIOs are likewise concerned about how quantum computing could potentially be used to render their authentication and encryption obsolete, leaving their infrastructures exposed. Those types of strategic threats make hardware-based security with zero trust designed from first silicon all the more attractive and trusted.
What is hardware-based security? Gartner defines hardware-based security as the “use of chip-level techniques for protecting critical security controls and processes in host systems independent of OS integrity. Typical control isolation includes encryption key handling, secrets protection, secure I/O, process isolation/monitoring, and encrypted memory handling.” Hardware-based security is quickly emerging as table stakes for securing an enterprise by providing safeguards against various cyberattacks ranging from ransomware to sophisticated software supply chain intrusion attempts. With features like confidential computing, encrypted VMs and containers, enterprises are beginning to put more trust in hardware-based security. With all hardware security vendors either currently providing or finalizing zero-trust support in their silicon, hardware-based security is gaining greater adoption in enterprise data centers.
Microsoft’s recently published Windows 11 Security Book: Powerful S ecurity from Chip to Cloud explains how Windows 11 enables zero-trust protection. The operating system supports chip-level zero-trust security that guards against privileged access, credential theft and many other attack scenarios.
“Credentials are protected by hardware and software security layers such as Trusted Platform Module 2.0 , Virtualization-based Security (VBS) , and Windows Defender Credential Guard , making it harder for attackers to steal credentials from a device,” according to the report.
The lengthy publication provides examples of how Microsoft collaborates with a broad base of chipset manufacturers, all focused on providing hardware-based zero trust.
“I believe the zero-trust concepts shouldn’t stop at the network or system,” writes Martin G. Dixon, Intel fellow and VP of Intel’s security architecture and engineering group. “Rather, they can be applied down inside the silicon. We even refer to infrastructure on the chip as a network or ‘network on a chip.'” One of the most compelling aspects of the latest hardware-based security silicon development generation is its support for zero-trust security. Upgrading servers across a data center with the latest generation of hardware-based security chipsets and silicon-based products opens up the opportunity to enable hardware-based authentication and encryption, two core goals for many zero-trust security frameworks and initiatives.
Leading vendors providing hardware-based security in silicon or working on R&D projects in this area include Amazon Web Services (AWS), AMD, Anjuna, Apple, Bitdefender, Fortanix, Google, Intel, Microsoft, Nvidia, Samsung Electronics and many others.
Four areas where quantum computing is falling short Inflated claims of what quantum computing could deliver for cybersecurity created great expectations. But for all its computational power, there are four weaknesses that quantum computing has that are leading enterprises to put more trust in hardware-based security.
Qubit technology continues to be too noisy for error correction As the number of qubits in a quantum computing use case increase, managing errors becomes more challenging. Qubit errors occur when the state of a qubit is disturbed by external factors such as noise, temperature or electromagnetic interference. These errors can cause the computation to become unreliable and produce random noise, limiting the number of steps a quantum algorithm can perform.
This is a significant problem for quantum computing in cybersecurity, as it reduces the accuracy and reliability of computations. With the leading cybersecurity providers’ roadmaps reflecting continued improvements in sensing, interpreting and acting on signal data, quantum computing’s instability in this area is contributing to the growth of hardware-based security.
During his keynote at CrowdStrike’s Fal.Con event last year, CrowdStrike cofounder and CEO George Kurtz said his company’s goal is to “pick up the weak signals on endpoints to understand intrusion patterns better.” He continued, “and one of the areas that we’ve pioneered is [taking] weak signals from across different endpoints. And we can link these together to find novel detections. We’re now extending that to our third-party partners so that we can look at other weak signals across not only endpoints but across domains, and come up with a novel detection. This is much different than, ‘Let’s pile a bunch of data into a data lake and sort it out.'” External control electronics need greater scale to meet cybersecurity’s challenges From a cybersecurity standpoint, the problem of scaling quantum computing is closely related to increase in the number of qubits within a quantum chip. As the number of qubits increases, so does the number of control wires or lasers needed to control them. This requires external control electronics, which in turn requires many signal lines to scale.
In the IEEE Spectrum article An Optimist’s View of the 4 Challenges to Quantum Computing , Intel’s director of quantum hardware James S. Clarke writes, “Today, we require multiple control wires, or multiple lasers, to create and control qubits. As a result, fan-out is a major challenge for scaling up quantum computing.” This complexity of scaling quantum computers with multiple control wires or lasers can make it challenging to implement and maintain security protocols in quantum computing systems, which is crucial for cybersecurity. As a result of this limitation, hardware-based security is gaining adoption and trust across enterprises.
High-value algorithms don’t provide data fast enough to thwart breach attempts One of quantum computing’s limitations today is the length of time it takes to access and retrieve data from the highest-value algorithms. This is because quantum algorithms often require superpolynomial time to run, meaning the number of steps increases faster than a polynomial function of the input size. This can make them less suitable for zero-trust security, where quick and efficient telemetry data is required to thwart potential breach attempts.
In the context of zero-trust security, the ability to quickly and accurately measure the output of a computational process is crucial. Zero-trust security is based on the principle of “never trust, always verify,” meaning that even internal network traffic and communications should be closely monitored and verified. With high-value quantum algorithms that have impractical readout times, it may take time to quickly and accurately verify the output of the computation, thereby making these algorithms less suitable for use in zero-trust security systems.
Lack of standardization creates a challenge The lack of standardization across programming, middleware, and assembler levels can make it challenging to ensure the security and integrity of the data being processed and stored. Compounding that challenge is the need for more knowledge about the application, application stack and environment management among developers and operations ( devops ) teams. This can result in a need for standardized processes for the development life cycle, making it harder to maintain secure and efficient quantum computing systems.
Given the need for more standardization, enterprises are concerned about vendor lock-in , which is also a significant barrier to adopting quantum computing.
In summary, the lack of standardization across programming, middleware and assembler levels in quantum computing makes it more challenging to ensure the security and integrity of data being processed and stored, making enterprise cybersecurity a significant challenge.
Conclusion Hardware-based security is rapidly emerging as an attractive option for enterprises seeking to protect their data centers from cyberattacks. Quantum computing cannot (yet) provide the accuracy and speed required for effective EDR, making hardware-based security a more reliable option.
Hardware-based security solutions are designed from the first silicon to rely on zero-trust principles to guard against privileged access credential theft and other attack scenarios.
While quantum computing provides immense computational power, its current state of qubit technology is too noisy for error correction. External control electronics lack the necessary scale. High-value algorithms don’t quickly provide data. And, the lack of standardization makes enterprise cybersecurity challenging.
As a result, hardware-based security solutions are gaining trust in enterprises and providing safeguards against numerous cyberattacks.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"USPS signs data management contract worth up to $70M with Veritas Technologies | VentureBeat"
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"https://venturebeat.com/security/usps-signs-data-management-contract-worth-up-to-70m-with-veritas-technologies"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages USPS signs data management contract worth up to $70M with Veritas Technologies Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Data security is something few organizations can afford to overlook. With the average cost of a data breach reaching $4.35 million in 2022, leaving data exposed can have devastating consequences. Yet in the cloud, the only way to avoid this scenario is to invest extensively in data management capabilities.
That’s why today, Veritas Technologies announced that the United States Postal Service ( USPS ) has awarded the vendor a three year contract to help strengthen its regulatory, data compliance posture and eDiscovery capabilities with Veritas Enterprise Vault, Merge1 and eDiscovery Platform.
The contract has the potential to be extended for as long as 7 years, giving the deal a maximum potential value of $70 million.
USPS will use Veritas’ solutions to implement automated data archiving and retention across all on-premises and cloud-based data sources, including cloud collaboration tools. This will give the organization the ability to pinpoint the resiliency of data assets wherever they live in the environment.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Data management as the answer to data security The deal comes as organizations continue to reconcile cloud computing and data security: Research shows that 90% of organizations struggle to enforce security policies around sensitive or critical data.
Part of the reason for these poor controls is that organizations lack visibility over where data is located in the environment, and what risks it’s exposed to. Back in 2018, USPS experienced these challenges first hand when hackers used a vulnerability in its systems to harvest the data of more than 60 million customers.
Now, with a significant investment in a unified data management tool, the USPS is positioning itself to mitigate threats against customer data with greater data resilience across the cloud, rather than relying on siloed data management tools.
“It’s not uncommon for cloud administrators, application developers, data managers and security teams to implement their own data management solutions,” said Kevin Youngquist, VP for the U.S. public sector at Veritas.
“This siloed approach increases the total cost of ownership and creates data management, security and compliance challenges,” he said. “As complexity in the multicloud increases, so does the difficulty of ensuring data protection, opening the door for potential vulnerabilities including ransomware.” With Veritas Enterprise Vault, USPS will be able to reduce complexity by capturing and archiving data whether it’s located on-premises or in the cloud.
For example, the solution can pull data from email and messaging platforms and automatically classify it based on predefined archiving policies, to file sensitive information in compliance with regulations such as the GDPR.
On the other side of the coin, the Veritas eDiscovery platform enables compliance officers and legal staff to execute data breach investigations and respond to regulatory requests to identify key resolution files. This provides a framework for streamlining responses to regulatory inquiries where time is of the essence.
The enterprise data management market Veritas Technologies tools fall under the category of data management solutions, which are designed to automate and streamline the discovery, capture and retention of critical data assets across cloud and on-premise environments.
It’s a market that researchers valued at $89.34 billion in 2022 and estimate will grow at a Compound Annual Growth Rate (CAGR) of 12.1% up to 2030.
One of Veritas’ main competitors in the space is Tableau , an analytics provider with integrated data management and governance capabilities. This gives users the ability to manage the entire data lifecycle from ingestion to removal. Under parent company Salesforce, Tableau raised $1.95 billion in revenue in 2021.
Another significant competitor is Oracle , which offers Enterprise Data Management Cloud. The tool can integrate data from disparate applications via REST APIs, providing a framework to implement permission-based access to apps and data, while developing an audit trail.
Oracle recently announced Q2 total revenue of $12.3 billion.
However, Youngquist argues that Veritas’ unified data management approach differentiates it from other competitors in the market.
“Our unified approach to data management and protection continues to deliver unmatched resiliency, simplicity and cost-savings across any workload, any cloud and any storage,” said Youngquist. “So, when it comes to addressing today’s urgent requirements associated with managing and protecting cloud data, Veritas is leading the way.” To date, Veritas Technologies has more than 80,000 customers, including up to 95% of the Fortune 100, and supports over 800 disparate data sources, 100-plus operating systems, 1,400-plus storage targets and 60-plus cloud platforms.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Saviynt raises $205M and affirms that IAM must be cloud-friendly | VentureBeat"
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"https://venturebeat.com/security/saviynt-raises-205m-and-affirms-that-iam-must-be-cloud-friendly"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Saviynt raises $205M and affirms that IAM must be cloud-friendly Share on Facebook Share on X Share on LinkedIn A photo of Saviynt CEO and founder, Sachin Nayyar Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Managing identities on-premises isn’t good enough. Today’s organizations need automated, cloud-friendly Identity Access Management (IAM) processes if they’re going to authenticate and authorize remote users at scale. In decentralized working environments, there’s a mandate for being agile.
One vendor looking to build an agile cloud IAM process is identity and access governance provider Saviynt , which today announced it has closed $205 million in growth financing from AB Private Credit Investors’ Tech Capital solutions group.
Saviynt’s Enterprise Identity Cloud (EIC) is a cloud-native converged identity platform designed for streamlining identity and access management processes, for workforce, enterprise applications, privileged and third-party identities as part of a single solution.
>>Don’t miss our special issue: The CIO agenda: The 2023 roadmap for IT leaders.
<< VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! This approach enables security teams to manage the identity life cycle with automated workflows to govern identities at scale across on-premises, hybrid and multicloud environments.
Protecting identities in the cloud The funding comes as organizations have continually failed to secure identities against threat actors, with research showing that 80% of organizations suffered identity-related breaches in the last 12 months.
One of the key challenges that contributes to this lack of security is that organizations don’t have the technologies or processes in place to consistently enforce access management controls throughout on-premises and cloud environments.
“Applications drive today’s modern organization and are at the core of every digital transformation. The central challenge of managing identity in the cloud is ensuring secure and reliable access control to resources while maintaining user privacy and compliance with regulatory requirements at a time where there is massive growth in identities,” said Sachin Nayyar, Saviynt CEO and founder.
“This includes ensuring the authenticity of users and devices, whether they are employees, third parties or machine identities, and protecting against unauthorized or over-provisioned access. It can also be challenging to integrate and synchronize identities across different cloud environments and on-premises systems,” Nayyar said.
Reviewing the IAM market Saviynt’s solution falls under the IAM market , which researchers valued at $12.3 billion in 2020 and anticipate will reach $34.5 billion in 2028 as organizations attempt to keep up with mounting security and compliance concerns.
One of the company’s main competitors in the space is SailPoint Technologies , a cloud IAM provider that offers the SailPoint Identity Security Platform, which uses artificial intelligence (AI) and machine learning to discover and automate real-time access. Last year, Thoma Bravo acquired SailPoint Technologies for $6.9 billion.
Another significant competitor in the space is Okta , which offers a Workforce Identity Cloud solution with single sign-on, adaptive multifactor authentication capabilities and life cycle management capabilities. Okta expects to generate total revenue of $1.8 billion in 2023.
Nayyar argues that the key differentiator between Saviynt and its competitors is its cloud-native approach to identity security.
“Unlike legacy identity security providers like SailPoint, Saviynt offers a cloud-native, converged identity platform for workforce, enterprise applications, privileged and third-party identities to provide the best user experience for solving the greatest number of use cases with the highest ROI and lowest TCO,” Nayyar said.
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"Sentra raises $30M to streamline data securely across the public cloud | VentureBeat"
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"https://venturebeat.com/security/data-security-posture-management-key-to-public-cloud-privacy"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Sentra raises $30M to streamline data securely across the public cloud Share on Facebook Share on X Share on LinkedIn A photo of the Sentra team Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Protecting data in the cloud is the core challenge of modern enterprise security. After all, organizations need to have the ability to prevent unauthorized users from accessing data as it moves across on-premises, cloud, hybrid and multicloud environments. This can be challenging in the public cloud in particular, where there’s lack of visibility over what data is in use, where.
This is a challenge that cloud data security vendor Sentra aims to solve. The company today announced it has raised $30 million as part of a series A funding round led by Standard Investments. It provides organizations with a solution to discover and scan cloud data stores across the public cloud, generating alerts if PII is exposed.
It’s an approach that offers organizations a way to enhance their data security posture across the cloud by reducing the data attack surface and lowering the risk of data theft or exfiltration.
>>Don’t miss our special issue: The CIO agenda: The 2023 roadmap for IT leaders.
<< VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Data security as a usability essential Maintaining data protection across the cloud has become a persistent struggle for organizations, with research showing that 53% of IT professionals say compliance in the cloud has become too difficult.
These compliance challenges not only increase risks for organizations, they also discourage decision-makers from gathering insights from their data, lest they open the door to legal and financial liabilities. As a result, implementing cloud-friendly data-protection controls is critical for ensuring data usability.
“Today, most organizations view security as a blocker to business success, not an enabler. Sentra was founded because we believe this thinking to be flawed as data security should be a business’ most important enabler,” said Yoav Regev, CEO and cofounder of Sentra. “When data is used efficiently and protected appropriately, organizations can move faster in this digital age and ensure business continuity.” “The promises of flexibility make the cloud one of the most amazing technological advancements in recent memory. However this flexibility means that organizations can easily lose control and visibility of their most sensitive information. Our solution solves this problem by ensuring that organizations prioritize the protection of this sensitive information while keeping up with business demand and the speed of data in the cloud,” Regev said.
A look at the DSPM market Sentra falls under the category of the data security posture management (DSPM) market, as outlined by Gartner in the Hype Cycle for Data Security 2022.
From Gartner’s perspective, DSPM solutions provide visibility on where sensitive data is located, who has access to it and what the security posture of the data store or application is.
One of Sentra’s competitors is Baffle , which offers a cloud data protection platform (CDPP) designed to simplify tokenization and data encryption to help organizations maintain data privacy with the support of access monitoring and field-level encryption to protect data end-to-end.
Baffle most recently announced raising $20 million in series B funding in August 2021.
Another competitor is Dig Security , offering security teams a platform that can discover and classify cloud data assets across multiple clouds, while providing real-time data detection and response to generated alerts and automated responses to threats.
Dig Security most recently raised $34 million as part of a series A funding round in September 2022.
“Many players in the DSPM space are startups that have only been around for one to two years. That said, the main differentiator separating us from the companies is our focused data-centric approach. Our vision is to secure the data life cycle and integrate within a customer’s environment, bringing them a holistic view instead of a siloed one,” Regev said.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Black swans events are shaping the cybersecurity present and future | VentureBeat"
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"https://venturebeat.com/security/black-swans-events-are-shaping-the-cybersecurity-present-and-future"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Black swans events are shaping the cybersecurity present and future Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
First coined by Lebanese-American thought leader Nassim Nicholas Taleb , the term “black swan” refers to unexpected global events that have a profound effect on society. Some are beneficial, like the invention of the printing press; and others are destructive, such as the subprime crisis in 2008. But they have all altered the course of history.
In recent years, we have bore witness to a surge of black swan events, and they continue to emerge in real time. They have affected every facet of our lives, and this rings true in the world of cybersecurity. By analyzing these recent events, we can better map out our industry’s evolutionary processes to predict where cybersecurity is heading next.
The COVID-19 pandemic set the stage for innovation It’s unquestionable that one of the most significant black swans of recent memory was the beginning of the COVID-19 pandemic in 2020. One of the direct results of this global crisis was the transition to work-from-home practices, and with it came an overwhelming incentive to migrate a significant portion of our digital activity away from physical data centers to the virtual cloud workspace.
>>Don’t miss our special issue: The CIO agenda: The 2023 roadmap for IT leaders.
<< VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! This was a matter of decentralization versus centralization. Prior to the pandemic, centralizing an organization’s digital assets in one physical location that could be protected with a traditional security perimeter was considered standard practice. But during the pandemic, it became a liability, and organizations rapidly decentralized to move assets like business-critical applications and databases to the cloud. But this adjustment altered hackers’ attack vectors, requiring completely different defenses.
The decentralization of digital assets introduced new security vulnerabilities, both in the workplace and in employees’ homes, creating a significant hurdle to protecting against cyber criminals who were only growing more sophisticated and well-funded. These hackers developed new methods, known as 5th generation (Gen V) attacks, which were multidimensional and allowed the threat actors to hit from many different angles simultaneously.
As these new cyber threats emerged, the newly-developed cloud environments also demanded security products that were easier and quicker to install, activate and maintain. All of these elements combined to create the perfect conditions for a new approach to cybersecurity , one that would require record-breaking funding.
The rise and fall of cybersecurity capital investments The next black swan in cybersecurity came on the heels of the pandemic’s effective end (also known as the COVID-cyber-boom). The combination of the need to protect decentralized digital assets from Gen V attacks with the need to develop new products for today’s modern environments was a powerful incentive for innovation, fostered by a macroeconomic environment where interest rates were low and liquidity was high. It’s unsurprising that in 2021, more than $20 billion in venture funding was invested in cybersecurity companies globally, a new record. Venture capital firms were eager to get involved in this expanding industry.
As a result of this free flow of cash, cybersecurity start-ups experienced meteoric market valuations, resulting in the emergence of many unicorns.
While these valuations certainly represented their potential, they were often inaccurate representations of the companies’ actual worth. And with these investments came an onslaught of new cybersecurity products available to CISOs, providing a level of variety previously unheard of. But as the market was flooded by companies with inaccurate valuations, a bubble was created. And unfortunately, we know how bubbles end.
The final black swan actually involved three events in 2022: an increase in interest rates, a global supply chain crisis, and the war in Ukraine. This was a perfect storm for a worldwide recession. Capital and market valuations, which both seemed so abundant just a year before, seemed to fall off a cliff, and as a result, the growth so easily sustained in 2021 experienced a huge slowdown.
Where does this leave us? Today, we are left in a troublesome situation. Amidst a decline in innovation investments, assets continue to be decentralized, the Gen V attack surface still exists and organizations need an end-to-end solution.
As such, I predict that in the next 18 months, the industry will experience extreme consolidation to strengthen the defensive line of cybersecurity products and provide a comprehensive solution. This means consolidating similar products under one roof to create an end-to-end solution that empowers CISOs to deliver a layered model of protection. Rather than relying on the founding of new companies, this will be accomplished through mergers, acquisitions, or partnerships.
The challenge here is one of execution, and the gravity of these sorts of integrations for large organizations looms large. There are real and valid concerns around these sorts of unifications. What if large organizations with deep pockets absorb start-ups and rob them of their agency and agility, essentially stamping out any capacity for innovation before they can hit their stride? Any advantages to be gained by the acquisition will be lost if they effectively squash these competitive differentiators.
To prevent this, organizations must tread carefully to grant the acquired start-ups a high degree of autonomy without any added bureaucracy or friction. Only by guaranteeing these freedoms can large organizations harness start-ups’ ability to develop, test, and deploy solutions with advanced precision and speed. This will likely require strategic organizational restructuring, wherein an individual who understands how to balance the needs of a start-up with the wealth, size and goals of a large organization can act as a trusted go-between between leadership and the start-up team. This is how larger organizations can reinvent themselves to rise to the occasion brought about by a series of black swans.
On the start-up side, these entrepreneurs need to ensure that their new parent organization aligns with their vision for growth. They should establish a roadmap for the next two or three fiscal years to set expectations on both sides. With all parties united in their goals, cybersecurity organizations can provide a modern, end-to-end solution to decentralization without forcing the industry to rely on venture funding that simply no longer exists.
Black swans are driving positive change in cybersecurity The digital decentralization of 2020, industry growth of 2021 and inevitable bust of 2022 have been a whirlwind of events in just three short years. But their challenges and opportunities will move us forward to a more cyber secure world. After a rapid succession of black swans that have irreversibly shifted the course of our industry, the technological and economic evolution of cybersecurity is progressing in a positive direction toward a brighter future.
Moshe Lipsker is SVP of product development at Imperva.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"As public cloud use increases, security gaps widen | VentureBeat"
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"https://venturebeat.com/security/as-public-cloud-use-increases-security-gaps-widen"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages As public cloud use increases, security gaps widen Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Cloud footprints are exploding, as is the volume of data stored within them.
And, due to its low cost, simplicity, reliability and flexibility (among other factors), the public cloud — or a hybrid or multicloud model incorporating it — is the option of choice.
But everything has its disadvantages; notably, increased work processes in the public cloud can cause security gaps, experts say.
“Organizations are experiencing an explosion of data on their public cloud environments,” said Dan Benjamin, CEO and cofounder of Dig Security.
This results in “an extended data attack surface that can lead to a breach or compliance failure.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! >>Don’t miss our special issue: The CIO agenda: The 2023 roadmap for IT leaders.
<< Data: Dynamic, complex — and ever-vulnerable With the public cloud model, all servers, storage, hardware, software and other supporting infrastructure are owned and managed by the provider. And, those are shared with other organizations, or ‘“tenants.” As of 2022, more than 60% of all corporate data was stored in the cloud. This share reached 30% in 2015 and has continued to grow as organizations look to improve reliability and agility.
This year, revenue in the public cloud market is projected to reach $525.6 billion, registering a compound annual growth rate (CAGR) of nearly 14%. Undoubtedly, the market will only continue to grow (and at an accelerated pace), exceeding $881 billion by 2027.
And, Gartner estimates that, by 2026, public cloud spending will exceed 45% of all enterprise IT spending , up from less than 17% in 2021.
But, Benjamin pointed out that high-profile security incidents such as the Uber and LastPass breaches have proven how vulnerable cloud data stores are, even for organizations that understand cybersecurity and invest in data protection.
“Data is dynamic and complex,” said Benjamin. “It lives in various forms and is constantly being collected, so it is ever-changing across the public cloud.” Cloud environments are often part of complex ecosystems that include more than one public cloud provider and on-premises infrastructure, he explained. Also, many organizations simultaneously run multiple software-as-a-service (SaaS) applications, virtual machines (VMs), containers and cloud instances, adding more layers of abstraction.
As data travels between these assets, discovering it and mapping data flows is challenging and easy to lose control of, he said.
Hiding in the shadows As organizations move quickly and deliver faster to production, they give a lot of power to areas other than IT or DevSecOps, explained Shira Shamban, CEO and cofounder of cloud security company Solvo.
And, “they create, unintentionally of course, shadow data that doesn’t follow security best practices,” she said.
Shadow data is that which is not actively managed or governed by IT teams. It can include snapshots, backups and copies of data used for development and testing purposes, Benjamin explained. It primarily exists in spreadsheets, local copies of databases, emails, presentations and on personal devices.
Security controls and policies are often not applied to this data, making it more difficult to track, manage and monitor. It also leaves it susceptible to unauthorized access and exfiltration, said Benjamin.
This poses significant risk from both security and compliance perspectives, he said. A lapse in compliance could result in fines and reputational damage, while a weakened data security posture exposes organizations on several levels. Damage caused can diminish customer trust and result in reputational damage, fines, legal fees and IP theft.
In particular, the nature of the public cloud “makes it easy to spin up a new data store, but difficult for security teams to monitor the contents of that data store,” said Benjamin. “As such, organizations must change the way they think about data security.” A complex data environment Across the board, protecting cloud data is both critical and challenging — no matter whether private, public, hybrid or multicloud, experts say.
And, the most common attacks in the cloud are no different from common attacks on-premises, said Shamban. Typically, this is credential theft; the unique attack vectors in the cloud have to do with misconfiguration of cloud technology.
Benjamin agreed that there are a variety of ways to infiltrate the cloud environment; attackers commonly exploit software vulnerabilities, leaked credentials or misconfigured access. But, regardless of how the environment is infiltrated, he said, the objective is always either to steal or sabotage the data for financial or other gain.
“This is what makes focusing on protecting data so important and effective,” said Benjamin.
Visibility is critical There are many tools that organizations use to protect themselves; one common one is cloud security posture management ( CSPM ). This identifies and remediates risk through visibility automation, uninterrupted monitoring, threat detection and remediation workflows. It searches for misconfigurations across diverse cloud environments and infrastructure including SaaS, infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS).
Gartner, for its part, recently introduced the idea of data security posture management (DSPM).
According to Patrick Hevesi, Gartner VP analyst, this includes several components: Compliance assessment Risk identification Operational monitoring DevSecOps integration Policy enforcement Threat protection As Benjamin explained, this approach can work alongside a similarly new concept of data detection and response ( DDR ), which (as its name would suggest) provides real-time monitoring, detection and response.
“Increasingly, there is a heightened awareness of the risks and a movement toward better governance and monitoring over data assets,” he said. “Capabilities for DSPM, cloud data loss prevention (DLP), and DDR can help organizations meet the challenges head-on.” A mix of tools, culture Ultimately, organizations must train their devops and R&D teams to have security “ingrained in their mindset,” said Shamban. They must also be equipped with the right tools to help automate some of their daily decision-making and remediation tasks, as this will free up their time for more complex projects.
“We can’t stop using the cloud, and that’s why we should learn how to use it more efficiently and more securely,” she said.
Benjamin agreed, acknowledging that enterprises aren’t going to abandon the public cloud due to its numerous advantages “Cloud computing enables unparalleled flexibility, performance and velocity,” he said.
And ultimately, “the risks should not discourage organizations from using public clouds,” said Benjamin.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Complexity is the enemy of productivity | VentureBeat"
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"https://venturebeat.com/programming-development/complexity-is-the-enemy-of-productivity"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Complexity is the enemy of productivity Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Your IT group is increasing complexity, not reducing it. But it’s not their fault.
Companies contain a myriad of departments and divisions, all with their own specialized teams. Processes are designed to be as efficient as possible, often at the expense of flexibility. And information is collected and analyzed to a level of detail that would have been unimaginable just a few years ago.
Amid all this complexity, it’s easy to lose sight of the fact that businesses exist to produce something — whether it’s a product, a service, or simply a profit. In the quest for efficiency and productivity, companies sometimes forget that the goal is to produce results, not just to follow a set of rules. When businesses ask IT to build new apps, it increases complexity and often hard-codes rules into the process. Then, tomorrow, you may find yourself bogged down by your own bureaucracy and struggling to achieve your true potential.
App explosion contributes to complexity Building more apps to support new business needs creates more complexity, not less. Apps, SaaS , low-code apps, and automation have created a more complex landscape than ever before. And while some argue that this complexity is a necessary evil, it introduces more risk and can lead to problems down the road.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! >>Don’t miss our special issue: The CIO agenda: The 2023 roadmap for IT leaders.
<< One of the biggest problems with having so many apps is that it makes things more difficult to change. If you want to add a new feature or make a change to a business process running across an app, you have to wade through a lot of code and figure out how everything fits together. Many times, the processes are hard-coded to the app, making you choose between innovation and stagnation.
If you add an app to avoid the inherent complexity, you add more complexity for tomorrow. If you modify an app or automation to avoid waiting on IT to build another app, it still takes a long time to edit and test your new processes. You have left yourself with two poor choices, both of them from having too many apps for too few developers.
More apps create more work Enterprises are already struggling to keep up with the sheer volume of their apps. Therefore, it’s hard to imagine why anyone would want to add more to the mix. CIOs are already stretched thin, and their IT teams are spread even thinner. Can you imagine a CIO stating, “My company has 65 apps on the average knowledge worker’s desktop. I’d like to get to 75 apps by the end of the year.” No.
More apps simply mean more work, and there’s no way enterprises can keep up with the demand.
But low-code platforms are changing the game. With low-code, enterprises can quickly and easily build the apps they need, without having to invest in dedicated developers. That means that IT teams can focus on more important tasks, and CIOs can reallocate resources. Right? Wrong.
Low-code platforms build more apps and more apps create more complexity. Plus, low-code platforms aren’t really that simple. To build an app, one must have JavaScript, SQL, API and SDLC skills — the same skills a software developer has.
Enterprises force complexity on their people It’s been said that the people are the hardest part of any change management initiative. And it’s true — people are naturally resistant to change, and trying to get them on board with a new process or way of doing things can be a daunting task. It’s in our DNA. Change introduces risk and we want to limit risk to avoid failure.
But what if we looked at things from a different perspective? What if, instead of trying to force people to change to accommodate a new IT process, we change the way we deliver IT capabilities? Instead of asking people to learn a new system for the sake of data entry, or remember a set of tribal knowledge-process steps across complicated infrastructure, we guide them and ask them to interact only when necessary. In other words, we could make change easier — not harder. Don’t ask people to change. Change your IT delivery mentality to put people first.
Build enterprise IT that puts people first IT’s role has never been more important. Unfortunately, enterprise IT development and delivery models are often complex, inflexible and slow to respond to change because of all of the legacy dependencies. As a result, they often hinder rather than accelerate innovation. Thankfully, there is a better way to innovate and transform your businesses, a way that puts people first.
Use software to orchestrate processes instead of relying on people Follow a business process across your organization and you’ll find that it is part software and part tribal knowledge. There are certain steps that a person knows or understands because they are exposed to them from practice or because they are a critical integration point. This shouldn’t be the case. You need to stitch this work together with software like an automation fabric. An automation fabric automates automation instead of relying on people to do it.
Make things easier to change Change is inevitable and we must embrace it. However, it shouldn’t be as hard as it is. You should make things easier to change so that your business can adapt and evolve as your environment changes. To change more quickly, you need to reduce the skills required to do so and decouple business needs from IT constraints. That means you need to find a way to help your people optimize the business without depending on constrained IT resources.
Reduce the burden on your people Your people are your most important asset. Unfortunately, they are also the ones who are asked to do the most with the least. They are asked to remember a lot of information, to juggle multiple tasks and to use a variety of tools and technologies. This is simply too much. We need to find ways to reduce the burden on our people so that they can focus on what’s important — the business.
Move more work to software and AI As you move more business processes to an adaptive platform and away from brittle customizations and tribal knowledge, you accomplish two important goals. First, moving more work to software removes people constraints and enables you to capture tribal knowledge and data. Second, this data can learn how your processes operate and help your people optimize business outcomes using artificial intelligence.
That way, people can focus on what they do best: interacting with other people and making decisions.
You can add complexity or remove it To innovate and make change easier, IT should focus on delivery models that put people first. This means using software to orchestrate processes instead of relying on people to do it, and making things easier to change so that businesses can adapt and evolve. IT should reduce the burden on people by moving more work to software and artificial intelligence.
So ask yourself: Are you adding or removing complexity? John Michelsen if CEO of Krista Software DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"4 key opportunities for startups in 2023 | VentureBeat"
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"https://venturebeat.com/programming-development/4-key-opportunities-for-startups-in-2023"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest 4 key opportunities for startups in 2023 Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
What do Electronic Arts, Cisco, Airbnb and Square have in common? They are just a few of the successful technology leaders that were founded as startups during times of economic uncertainty. And they didn’t just grow; they changed the way people worked and lived.
It may be that tough times make startups scrappier, building cultures focused on efficient growth that endures. Certainly, they launch into a market where customers are ready to try something new and be more efficient themselves. After all, older ways aren’t working like they used to, and there is a lot more necessity around changing behavior. Look no further than the growth of cloud computing after the 2009 downturn, where startups and enterprises took to the cloud to take advantage of new cost efficiencies.
2023 looks like it may be one of those times of economic trials, and if history is any guide, that means that today, somewhere, the next world-changing startups are forming. What’s the next big thing they will develop? >>Don’t miss our special issue: The CIO agenda: The 2023 roadmap for IT leaders.
<< VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! I don’t think any of us know with certainty what market leaders are being born today, but I’m confident they will be built with the most advanced tools available for platforms and environments that will grow in the coming years. And by looking at the most promising emerging tools, technologies and markets, we can begin to find signals for what to look for in great startups.
Here are four key areas I think will be opportunities for startups in 2023.
Real data and artificial intelligence AI and ML have become increasingly cheaper and easier to use, so applying them to everything from online shopping to manufacturing quality assurance is a natural step. It’s a matter of lower costs and greater ease of use broadening a potential market.
There’s more to it than that, though. Existing companies will be looking for new ways to get value from their extensive and growing data holdings, and will seek new insights from combining multiple data sources in ways they haven’t before. That creates opportunity not just for AI/ML services, but for new ways to cleanse, align and securely combine multiple data sources, both inside and outside companies. With many enterprises hesitant to spend a lot of capital, there’s an opportunity for new companies that can either do this as a service or automate parts of it.
There are also many industries where new analytics and AI approaches haven’t yet played a role, either because of costs, unwillingness to change processes, or a lack of knowledge about these industries among the data community. That may well change in 2023.
The vertical opportunity for startups Economic pressures change labor patterns. In a labor market where many people are already electing to work later in life before retirement, layoffs, hiring cutbacks and other staffing challenges may lead folks to return to work or seek part-time and consultative work. That creates a new knowledge base around all sorts of niche industries that large companies haven’t approached, where experts with years of knowledge can look to apply things like cloud-based data analysis, targeted mobility solutions, chatbots or robotics, among others. They can team up with people with modern tech skills who may leave one industry and migrate to another, seeking new opportunities or a different lifestyle.
The startups that succeed in niche industries will seek adjacent businesses, or even find a process that can be adapted to something truly revolutionary for mainstream markets. Sometimes startups create entirely new verticals, something that seems particularly timely in areas like sustainability, biosciences or agriculture. That kind of adaptation is easier today than it was in the past, thanks to the flexibility of cloud-based software, and cloud practices like microservices and serverless computing. Better still, the investment community is hungry for these types of opportunities.
Many of today’s technology companies have been able to grow rapidly while maintaining their experimental DNA. But it may soon be more challenging to succeed at first with a broad new platform offering, as opposed to finding and establishing a business with a clearly focused product. In an era of tougher fundraising, where investors are looking for more evident data points of success, bringing a clear value proposition to a vertical that’s ripe to be changed through the application of new technologies is a winning formula for startups.
Distributed systems, distributed teams, distributed companies The underlying technology of networked blockchain ledgers will likely find an increasing number of practical uses in the years to come. It happened 20 years ago when the underground and undersea cables laid during the telecommunications bubble made things like offshoring and outsourcing during the post-bubble downturn possible. Blockchains, which distribute information over a broad set of computers with a means of authenticating in real time activities like the completion of work or financial transfers, will probably find new uses.
In parallel, the collaboration technologies that proved so important during COVID have made it possible for large groups to organize and execute work from numerous locations at the same time. That means that teams and companies can self-organize and develop products more cheaply and better than ever. The capacity inside large cloud systems remains large, and it’s likely we’ll see more startups organize without a physical headquarters.
Helping startups grow and thrive To continue providing startups with the support they need to build, grow and thrive, the Google for Startups Cloud Program has been ramping up skills training for startups, building out more mentoring and information-sharing opportunities for startups to connect with engineering and product development, and identifying more ways to help startups find customers and improve distribution through channels like our Apps Store.
The startup ecosystem is larger and more diverse than ever, and the pace of that growth is quickening; it’s good for everyone to see that growth. Mentoring in technology, product development, and regional and global expansion are both a good idea and good business on both sides — which is why I, and the Google for Startups Cloud team, are excited to work with and support even more startups in 2023.
After all, it wasn’t that long ago that Google, too, was a startup looking to grow during hard times, build a culture that lasts, take new technologies further and build something big.
Ryan Kiskis is Director, Startup Ecosystem at Google Cloud.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Metaphysic partners with CAA to develop generative AI for creative artists | VentureBeat"
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"https://venturebeat.com/games/metaphysic-partners-with-caa-to-develop-generative-ai-for-creative-artists"
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"Game Development View All Programming OS and Hosting Platforms Metaverse View All Virtual Environments and Technologies VR Headsets and Gadgets Virtual Reality Games Gaming Hardware View All Chipsets & Processing Units Headsets & Controllers Gaming PCs and Displays Consoles Gaming Business View All Game Publishing Game Monetization Mergers and Acquisitions Games Releases and Special Events Gaming Workplace Latest Games & Reviews View All PC/Console Games Mobile Games Gaming Events Game Culture Metaphysic partners with CAA to develop generative AI for creative artists Share on Facebook Share on X Share on LinkedIn Are you looking to showcase your brand in front of the brightest minds of the gaming industry? Consider getting a custom GamesBeat sponsorship.
Learn more.
Metaphysic announced today it partnered with entertainment and sports agency Creative Artists Agency (CAA) to develop generative AI tools and services for global talent.
Through this partnership, Metaphysic and CAA will work together to create deals for artists using AI across film, television, and entertainment.
Metaphysic is in the “deep fake” business, where it creates artificial versions of celebrities and others using AI techniques. Metaphysic is aiming its synthetic media to connect influencers and their audiences in novel ways — including via deep fake videos — that are hyper-realistic, ethically created and uniquely compelling.
>>Follow VentureBeat’s ongoing generative AI coverage<< Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! Metaphysic made history in 2022 on “America’s Got Talent,” introducing hyperreal generative AI content to a national television audience. The team used AI to create photorealistic avatars of the king of rock and roll, Elvis Presley, that delivered musical performances on stage that looked perfectly real.
The performances captured the world’s attention, along with leaders in the entertainment industry, including CAA and Los Angeles-based film and television studio Miramax.
“Metaphysic are industry leaders in using generative AI and machine learning to create photorealistic Hollywood-quality content, combined with their ethics-first approach and thought leadership they unlock an incredible opportunity for the entertainment industry and beyond,” said Joanna Popper, chief metaverse officer at CAA, in a statement. “Artificial intelligence will have a transformative impact on content creation and intellectual property. CAA has always been at the forefront of new technological frontiers and we are excited to work with Metaphysic in bringing the most exciting opportunities to our clients and the industry.” Testament to its technical and creative excellence, Metaphysic has been named the sole AI provider for the highly-anticipated major motion picture Here , produced by Miramax and directed by Robert Zemeckis. Starring Tom Hanks and Robin Wright, this adaptation of Richard McGuire’s graphic novel reunites the original Oscar-winning team behind “Forrest Gump,” along with Paul Bettany and Kelly Reilly.
In an industry-first, Here incorporates hyperreal AI-generated face replacements and de-ageing into the very fabric of its storytelling.
“I’ve always been attracted to technology that helps me to tell a story. With HERE, the film simply wouldn’t work without our actors seamlessly transforming into younger versions of themselves. Metaphysic’s AI tools do exactly that, in ways that were previously impossible! Having tested every flavor of face replacement and de-aging technology available today, Metaphysic are clearly the global leaders in feature-quality AI content and the perfect choice for this incredibly challenging, emotional film,” said Robert Zemeckis, in a statement.
Building on its industry-leading generative AI technology for Hollywood, Metaphysic is announcing its new product, Metaphysic Live. Being deployed in production on Here , Metaphysic’s new tool creates high-resolution photorealistic faceswaps and de-ageing effects on top of actors’ performances live and in real-time without the need for further compositing or VFX work. Streaming AI-generated photorealistic content that maps onto real-world scenes at up to 30 frames per second is a dramatic advance in the technology that will be essential to creating immersive AR/VR, gaming and entertainment experiences.
Kevin Baillie, Production Visual Effects Supervisor on Here says, “It is incredible to see Metaphysic’s AI-generated content flawlessly integrated into a shot live on set! The actors can even use the technology as a ‘youth mirror’ – testing out acting choices for their younger selves in real-time. That feedback loop and youthful performance is absolutely essential in achieving an authentic, delightful result.” “Metaphysic is rapidly expanding the creative horizons of Hollywood and beyond. Our tools are cost- effective, movie-quality and scalable – we are being forced to reimagine how visual media is produced,” said Thomas Graham, CEO of Metaphysic, in a statement. “With the support of CAA and by working on projects like Here , Metaphysic is demonstrating the transformative power of hyperreal AI to shape the future of entertainment and to eventually help people create AI-generated, photorealistic immersive content while they own and control their data.” To build upon its incredible technical offering, Metaphysic is currently hiring additional talent to bolster its machine learning, VFX, and product innovation teams. Qualified candidates are encouraged to reach out to Metaphysic.
Metaphysic has appointed creative team leaders, cofounder Chris Ume as AI Supervisor and recently hired Chief Innovation Officer Jo Plaete – as visual effects supervisor for Here.
GamesBeat's creed when covering the game industry is "where passion meets business." What does this mean? We want to tell you how the news matters to you -- not just as a decision-maker at a game studio, but also as a fan of games. Whether you read our articles, listen to our podcasts, or watch our videos, GamesBeat will help you learn about the industry and enjoy engaging with it.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! Games Beat Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"CDOs look to boost data management investment even as recession winds gather | VentureBeat"
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"https://venturebeat.com/data-infrastructure/despite-recession-cdos-are-looking-to-increase-investment-in-data-management"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages CDOs look to boost data management investment even as recession winds gather Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Economic recession heads a list of hurdles enterprises now face, but data management investments do not appear to be slowing down. This is according to a survey from Wakefield Research and data mainstay Informatica that sees data governance as the number one priority among chief data officers (CDOs). In fact, data management investments are on track to increase.
Conducted toward the end of 2022, the survey brings the perspective of 600 corporate data leaders across the U.S., Europe, and the Asia Pacific regions into the light. And, it finds that despite the looming macroeconomic crisis, more than 2 in 3 data leaders (68%) are looking to increase data management investments in 2023.
Aligning business and data management investments The move is expected in response to a growing mesh of data sources — 55% of respondents already manage 1,000-plus data sources. The survey further reveals that those set to move are more likely to align business and data interests within their organization.
The survey found that 73% of leaders with strongly aligned business and data strategies predicted increased investment in data management, against 53% who are not aligned or partially aligned. It further notes that the alignment of teams is also very critical to effectively meeting key data strategy goals.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! “By driving organizational alignment and making the appropriate data management investments to support it, they will differentiate their organizations, drive clear business outcomes and enable success in 2023 and beyond,” said Jitesh Ghai, Informatica chief product officer.
According to the research, the most sought-after capability under data management is data quality, with 42% of leaders looking to invest in it. This is followed by data protection (40%), data marketplaces (39%), master data (35%) and data discovery and cataloging (31%).
As for data strategy, 52% of survey respondents cited improving governance over data and processes as their top priority for 2023, ahead of data-driven culture and literacy (46%) and gaining a holistic view of customers (45%).
Both of these aspects — implementing the right strategies and utilizing the right tools — will be the key to gaining more from investments and setting the company up for success, according to the report.
Broader IT investments also likely to grow The importance of data in today’s business initiatives may mean a safer harbor for data management investments and some other IT efforts, even as economic headwinds threaten the consumer economy.
According to a separate study from Gartner, global IT spending is expected to grow during the economic downturn by 2.4%, hitting $4.5 trillion in 2023. But, it’s worth noting that this estimate is down from the previous quarter’s forecast of 5.1% growth.
“A turbulent economy has changed the context of business decisions and can cause CIOs to become more hesitant, delay decisions or reorder priorities ,” said John-David Lovelock, distinguished VP analyst at Gartner.
“We’ve seen this in action with the reshuffling taking place among some B2B companies, especially those that overinvested in growth,” he said. “However, IT budgets are not driving these shifts, and IT spending remains recession-proof.” Major players that grew head counts in recent years are already witnessing the impact of the downturn.
Among those that have moved to cut staff are Meta, Alphabet, Amazon, Goldman Sachs, Salesforce, IBM, Microsoft and Twitter.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Sony, Microsoft and Nintendo may skip E3 2023 | IGN | VentureBeat"
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"https://venturebeat.com/business/sony-microsoft-and-nintendo-may-skip-e3-2023-ign"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Sony, Microsoft and Nintendo may skip E3 2023 | IGN Share on Facebook Share on X Share on LinkedIn E3 did not happen at all in 2023.
IGN reported today that Sony, Microsoft and Nintendo — the video game industry’s biggest platform companies, may not have booths at E3 2023.
We have yet to confirm whether that’s true or not, and the Entertainment Software Industry referred an email request for comment to ReedPop, the organizer of the PAX fan shows and new steward of the E3 trade show, which is taking place in mid-June in Los Angeles.
If it’s true, then it’s a blow for the biggest game trade show in the U.S., and that certainly won’t help an industry still reeling with changes from the pandemic and economic downturn.
In a statement, ReedPop said, “E3 is undergoing a transformation from its 2019 iteration based on exhibitor and fan feedback. A collaborative process such as this, with so many stakeholders, takes time. ReedPop remains committed to delivering the best show possible and is excited to share more information on show format and the fantastic exhibitors taking part in the near future.” The company doesn’t address whether Microsoft and Nintendo, which have been longtime supporters of E3, will have booths at the show as they have pretty much always done. Sony hasn’t been at the show for years and so it may be no surprise that it isn’t coming back.
But Microsoft and Nintendo usually held pre-E3 events that served as magnets for the crowds at E3, which in pre-pandemic days could draw huge crowds of both fans and game industry professionals.
In its healthy years, E3 had 69,200 attendees in 2018 and 66,100 in 2019. Both years had more than 200 exhibitors. But in 2020, the show was canceled because of the pandemic. In 2021, the show was digital only and it had only 33 exhibitors, and in 2022 the show was canceled altogether.
During the pandemic, Geoff Keighley, the host of The Game Awards, started a competing show that drew tens of millions of viewers and even small groups for in-person events, such as one held for the press last year. The competition took its toll on E3, particularly in 2021.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Iron Galaxy's Rumbleverse is sailing into the sunset | VentureBeat"
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"https://venturebeat.com/business/iron-galaxys-rumbleverse-is-sailing-into-the-sunset"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Iron Galaxy’s Rumbleverse is sailing into the sunset Share on Facebook Share on X Share on LinkedIn Iron Galaxy's Rumbleverse is sailing into the sunset.
Back in August 2022, Iron Galaxy’s Rumbleverse slammed onto the scene as a battle royale brawler for 40 people.
The game was an original title from a company that makes a lot of its revenue from work-for-hire and contract work, and it had a lot of promise with its zany sense of humor. But Iron Galaxy announced today that it will be “sunsetting” Rumbleverse.
In a post, the Iron Galaxy dev team said it will keep making games and you “may not yet have seen the Rumble in its final form,” meaning the franchise might have some opportunity to be reborn in some way. The team thanked the players and said, “We have loved watching you play. We have learned from your stories and your insights. We even passed around the art you’ve created to immortalize your best moments in the streets.” We’ll check to see if there are more details.
Here’s the full statement below.
At Iron Galaxy, we believe very strongly in the value of bringing people together to share meaningful experiences in games. Every single one of us is a gamer. It’s what motivates us to create. With the announcement of the sunsetting of Rumbleverse, we want to share a more personal note with the players who have joined us in Grapital City.
When you work on a video game, you imagine the community that will show up to play it someday. For years, we dreamed about a lively city filled with people fighting to become a champion. We strived to create a vibrant place that celebrated the competitive spirit. Our goal was to bring joy back to online multiplayer gaming.
The people who gave Rumbleverse a chance and took it on as a new hobby have validated every day that we put into bringing our ideas to life. We have loved watching you play. We have learned from your stories and your insights. We even passed around the art you’ve created to immortalize your best moments in the streets.
It is our sincerest hope that this news does not mark the end of Rumbleverse. You may not yet have seen the Rumble in its final form. If we can welcome people back onto the deck of the battle barge again, we hope you’ll be there, laced up and ready to take your rightful place in the cannon.
Iron Galaxy will keep making games. It’s our passion and our purpose. Our people are filled with skills and inspirations to keep the world playing.
Thank you for playing. This is not the last time you’ll hear from us. This is not the last time we’ll invite you to play.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"DealHub Partners with Gong to Power Deal Execution and Revenue Predictability | VentureBeat"
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"https://venturebeat.com/business/dealhub-partners-with-gong-to-power-deal-execution-and-revenue-predictability"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Press Release DealHub Partners with Gong to Power Deal Execution and Revenue Predictability Share on Facebook Share on X Share on LinkedIn Together, DealHub and Gong provide sales teams with deep and holistic intelligence on buyer intent and deal sentiment AUSTIN, Texas–(BUSINESS WIRE)–January 31, 2023– DealHub.io , the Next-Gen CPQ Platform, today announced a partnership with Gong, the Reality Platform, to combine customer conversation and activity data from Gong with DealHub’s buyer journey insights. The partnership delivers a more complete picture of buyer engagement and sentiment throughout the sales process.
This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20230131005748/en/ (Graphic: Business Wire) With this partnership, DealHub’s insights add a new dimension of deal visibility and predictability within the Gong deal timeline. The consolidated view of buyer interactions provides sales teams with a deep understanding of customer sentiment and intent that is needed to drive next best actions and improve forecast accuracy.
Via its Digital DealRoom , DealHub provides the ability to capture real-time buyer intent and deal insights, derived from every customer touch, throughout the sales process and buyer journey. As a virtual playing field where buyers and sellers engage on all aspects of a deal, DealHub reveals buyer engagement insights that help revenue teams to more accurately predict outcomes and overcome roadblocks.
“DealHub’s deal insights have proven to increase win-rates,” says Eyal Elbahary, DealHub’s CEO and Co-founder. “Our partnership with Gong will provide sales organizations with greater control and clarity over deals, and significantly increase revenue predictability.” “In the face of economic volatility, revenue teams and sales leaders need visibility into their pipeline and deals leveraging buyer engagement signals. This holds especially true around quoting and contracts to help focus selling efforts on deals with the highest propensity to close,” says Eran Aloni, EVP of Ecosystem and Business Development at Gong. “By welcoming DealHub into the Gong Collective, we will unlock more value for our mutual customers.” Learn more about the DealHub and Gong integration , or visit our integration center.
About DealHub.io DealHub offers the most complete and connected CPQ solution for sales organizations. Our low-code platform empowers visionary leaders to connect their teams and processes, execute deals faster, and create accurate and predictable pipelines. With a unified CPQ , CLM and Subscription Management stack powered by a guided selling playbook , teams can generate spot-on quotes, accelerate contract negotiations, and sign off bigger deals. Using a DealRoom , they can centralize buyer/seller communications to deliver the most innovative buyer experience and drive deals to success. For more information, visit dealhub.io or follow DealHub on LinkedIn.
View source version on businesswire.com: https://www.businesswire.com/news/home/20230131005748/en/ Gideon Thomas, CMO [email protected] +972584433192 VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"7 of the best-paid tech jobs in the U.S. this year | VentureBeat"
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"https://venturebeat.com/business/7-of-the-best-paid-tech-jobs-in-the-u-s-this-year"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Sponsored Jobs 7 of the best-paid tech jobs in the U.S. this year Share on Facebook Share on X Share on LinkedIn If you’re thinking about a job move this year, you’re definitely not alone: a recent “ New Year, New Career ” poll found that 96% of U.S. workers are planning to look for a new role in 2023. The reasons are manifold: 40% said they need a higher income, 35% are currently unemployed, 34% said there’s no room to grow in their current job, and a quarter of the poll’s respondents said they are working in a toxic environment.
Those working in tech are understandably nervous about the current landscape. With tech layoffs an almost weekly feature at the moment, 66% of workers think it will be difficult to find a new job due to the state of the economy.
But new research indicates that there are still many jobs and career paths with strong footings. The 100 Best Jobs ranking showcases a number of high-paying tech roles — explore seven of those below.
1. Software Developer Median salary: $120,730 One of the globe’s most in-demand jobs, the Bureau of Labor Statistics (BLS) projects a 26% employment growth for software developers up to 2031. In that period, an estimated 370,600 jobs are projected to open up. IT consulting firm GenSpark is recruiting for a Java Developer role, which can be based in Maryland. You’ll need a BS in STEM, two to three years’ of programming experience, previous professional experience in Java mandate and one to three years experience in SQL is also required.
2. Information Security Analyst Median salary: $102,600 Cybersecurity is another growth area: The BLS projects “information security analyst” will be the 10th fastest growing occupation over the next decade. If this is your area, Interactive Brokers in Greenwich, CT, has an opening for an Information Security Analyst.
Consistently at the forefront of trading innovation, the company prides ourselves on being primarily a technology company and challenging the status quo. You’ll maintain a repository of firm security policies and controls, maintain mapping of policies and controls to regulatory requirements and industry frameworks and track development and maintenance of security standards with their respective owners to ensure timely completion, among other tasks.
3. IT Manager Median salary: $159,010 By 2031, 82,400 new IT manager jobs are expected to be created, according to the BLS. Siemens has a vacancy for a Senior IT Service Provider Performance Manager for its Alpharetta, GA location.
You will help build the relationship with Siemens’ partners and drive the journey to the cloud. You should have experience in managing the performance of providers delivering application managed services in an IT organization.
4. Web Developer Median salary: $77,030 This role encompasses back-end developers who are responsible for writing the code that stores and processes website data on a site; front-end developers focus more on the user experience as well as full-stack developers, who work across both front- and back-end web development.
Infologitech is seeking a Web Developer in Richmond, VA. You will need extensive experience in website accessibility standards and methodologies plus seven years’ of experience developing in web content management systems, and the same amount of experience in graphic and web design.
5. Computer Systems Analyst Median salary: $99,270 Another strong growth role, BLS is projecting that an estimated 50,900 jobs in the field will be available by 2031.
The Operational Computer Systems Analyst Level 2 at Lockheed Martin Corporation in Hanover, MD, will play a vital role in providing computer support to achieve core mission objectives by actively managing the functioning enterprise computer systems. To apply you will need a BS plus two years relevant experience across network administration, system administration (Windows, LINUX), virus detection and prevention and scripting languages (e.g. Bash).
6. Data Scientist Median salary: $100,910 More data means more skilled workers who can work with it to derive meaningful insights. There were 79 zettabytes of data generated worldwide in 2021 and the global big data analytics market annual revenue is estimated to reach $68.09 billion by 2025.
The LA Times has an opportunity for a Data Scientist in El Segundo. You will be part of its data organization, where you’ll have the chance to work with a diverse team that includes data engineers, analysts and consumer researchers, developing novel ways to help stakeholders in the newsroom achieve objectives through analysis and modeling. Interested candidates will need a Bachelor’s degree in a quantitative or computing-focused degree and four years’ of experience in analytics and data science.
7. Database Administrator Median salary: $96,710 With the BLS projecting an 8.1% employment growth for database administrators up to 2031, this is a career worth looking at.
If you are in Philadelphia PA, Worldgate, llc is seeking a Database Administrator.
You’ll be responsible for the development and support in administration on client database systems using database programming languages. Additionally you will manage the performance, integrity and security and be involved in the planning and development of the database, as well as troubleshooting any issues.
Ready to find your next role? Head to the VentureBeat Job Board today to view hundreds of roles that are currently hiring.
VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Who will compete with ChatGPT? Meet the contenders | The AI Beat | VentureBeat"
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"https://venturebeat.com/ai/who-will-compete-with-chatgpt-meet-the-contenders-the-ai-beat"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Who will compete with ChatGPT? Meet the contenders | The AI Beat Share on Facebook Share on X Share on LinkedIn Mikhail Nilov/Pexels Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Today, ChatGPT is two months old.
Yes, believe it or not, it was less than nine weeks ago that OpenAI launched what it simply described as an “early demo” a part of the GPT-3.5 series — an interactive, conversational model whose dialogue format “makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.” ChatGPT quickly caught the imagination — and feverish excitement — of both the AI community and the general public. Since then, the tool’s possibilities as well as limitations and hidden dangers have been well established, and any hints of slowing down its development were quickly dashed when Microsoft announced its plans to invest billions more into OpenAI.
Can anyone catch up and compete with OpenAI and ChatGPT? Every day it seems like contenders, both new and old, step into the ring. Just this morning, for example, Reuters reported that Chinese internet search giant Baidu plans to launch an AI chatbot service similar to OpenAI’s ChatGPT in March.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Here are four top players potentially making moves to challenge ChatGPT: Anthropic: Claude According to a New York Times article last Friday, Anthropic, a San Francisco startup, is close to raising roughly $300 million in new funding, which could value the company at around $5 billion.
Keep in mind that Anthropic has always had money to burn: Founded in 2021 by several researchers who left OpenAI, it gained more attention last April when, after less than a year in existence, it suddenly announced a whopping $580 million in funding — which, it turns out, mostly came from Sam Bankman-Fried and the folks at FTX, the now-bankrupt cryptocurrency platform accused of fraud. There have been questions as to whether that money could be recovered by a bankruptcy court.
Anthropic, and FTX, has also been tied to the Effective Altruism movement, which former Google researcher Timnit Gebru called out recently in a Wired opinion piece as a “dangerous brand of AI safety.” Anthropic developed an AI chatbot, Claude — available in closed beta through a Slack integration — that reports say is similar to ChatGPT and has even demonstrated improvements. Anthropic, which describes itself as “working to build reliable, interpretable, and steerable AI systems,” created Claude using a process called “Constitutional AI,” which it says is based on concepts such as beneficence, non-maleficence and autonomy.
According to an Anthropic paper detailing Constitutional AI , the process involves a supervised learning and a reinforcement learning phase: “As a result we are able to train a harmless but non-evasive AI assistant that engages with harmful queries by explaining its objections to them.” DeepMind: Sparrow In a TIME article two weeks ago, DeepMind’s CEO and cofounder Demis Hassabis said that DeepMind is is considering releasing its chatbot Sparrow in a “private beta” sometime in 2023. In the article, Hassabis said it is “right to be cautious” in its release, so that the company can work on reinforcement learning-based features like citing sources — something ChatGPT does not have.
DeepMind, which is the British-owned subsidiary of Google parent company Alphabet, introduced Sparrow in a paper in September. It was hailed as an important step toward creating safer, less-biased machine learning (ML) systems, thanks to its application of reinforcement learning based on input from human research participants for training.
DeepMind says Sparrow is a “dialogue agent that’s useful and reduces the risk of unsafe and inappropriate answers.” The agent is designed to “talk with a user, answer questions and search the internet using Google when it’s helpful to look up evidence to inform its responses.” However, DeepMind has said it considers Sparrow a research-based, proof-of-concept model that is not ready to be deployed, according to Geoffrey Irving, a safety researcher at DeepMind and lead author of the paper introducing Sparrow.
“We have not deployed the system because we think that it has a lot of biases and flaws of other types,” Irving told VentureBeat last September. “I think the question is, how do you weigh the communication advantages — like communicating with humans — against the disadvantages? I tend to believe in the safety needs of talking to humans … I think it is a tool for that in the long run.” Google: LaMDA You might remember LaMDA from last summer’s “AI sentience” whirlwind, when Blake Lemoine, a Google engineer, was fired due to his claims that LaMDA — short for Language Model for Dialogue Applications — was sentient.
“I legitimately believe that LaMDA is a person,” Lemoine told Wired last June.
But LaMDA is still considered to be one of ChatGPT’s biggest competitors. Launched in 2021, Google said in a launch blog post that LaMDA’s conversational skills “have been years in the making.” Like ChatGPT, LaMDA is built on Transformer , the neural network architecture that Google Research invented and open-sourced in 2017. The Transformer architecture “produces a model that can be trained to read many words (a sentence or paragraph, for example), pay attention to how those words relate to one another and then predict what words it thinks will come next.” And like ChatGPT, LaMDA was trained on dialogue. According to Google, “During its training, [LaMDA] picked up on several of the nuances that distinguish open-ended conversation from other forms of language.” A New York Times article from January 20 said that last month, Google founders Larry Page and Sergey Brin met with company executives to discuss ChatGPT, which could be a threat to Google’s $149 billion search business. In a statement, a Google spokeswoman said: “We continue to test our AI technology internally to make sure it’s helpful and safe, and we look forward to sharing more experiences externally soon.” Character AI What happens when engineers who developed Google’s LaMDA get sick of Big Tech bureaucracy and decide to strike out on their own? Well, just three months ago, Noam Shazeer (who was also one of the authors of the original Transformer paper) and Daniel De Freitas launched Character AI, its new AI chatbot technology that allows users to chat and role-play with, well, anyone, living or dead — the tool can impersonate historical figures like Queen Elizabeth and William Shakespeare, for example, or fictional characters like Draco Malfoy.
According to The Information , Character “has told investors it wants to raise as much as $250 million in new funding, a striking price for a startup with a product still in beta.” Currently, the report said, the technology is free to use, and Character is “studying how users interact with it before committing to a specific plan to generate revenue.” In October, Shazeer and De Freitas told the Washington Post that they left Google to “get this technology into as many hands as possible.” “I thought, ‘Let’s build a product now that can that can help millions and billions of people,’” Shazeer said. “Especially in the age of COVID, there are just millions of people who are feeling isolated or lonely or need someone to talk to.” And, as he told Bloomberg last month: “Startups can move faster and launch things.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Samsung brings generative AI art and personalization to refrigerators | VentureBeat"
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"https://venturebeat.com/ai/samsung-brings-generative-ai-art-and-personalization-to-refrigerators"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Samsung brings generative AI art and personalization to refrigerators Share on Facebook Share on X Share on LinkedIn You can have generative art on your Samsung Bespoke refrigerators.
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Samsung is announcing that its Bespoke line of custom appliance decorations will enable a form of generative AI art on its refrigerators and more.
With MyBespoke, the company will tap a combination of a human artist with generative AI art to make a collection of art available for its appliances.
The company’s latest line of refrigerators will have a Bespoke refrigerator that can be personalized with your original designs, artwork or favorite photos. MyBespoke custom panels help inspire you to create a one-of-a-kind fridge so you can personalize your kitchen.
Samsung said MyBespoke embraces home design trends that express personality and style using new materials, colors and artful designs. You can design your one-of-a-kind MyBespoke fridge panels with one or both French Doors and Samsung will deliver them to your home.
Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! You can create your own design when you purchase a Bespoke refrigerator from Samsung.com, and simply change out your existing Bespoke French Door fridge panels with your custom-designed panels. To complement your custom MyBespoke design on the top doors, you can choose from a variety of bold, bright or neutral Bespoke colors in glass or metallic finishes – for the lower doors or drawers of the fridge.
You can upload, edit and print your design on customizable, interchangeable Bespoke fridge door panels on Samsung.com. MyBespoke custom printed panels are available for $300 per panel, with delivery to your home in approximately eight weeks.
Unlocking personalization with generative art Samsung partnered with generative artist, Matt Jacobson, to create 100 unique generative art prints designed for Bespoke refrigerators.
The MyBespoke Generative Art Collection uses four popular Bespoke colors as a foundation, including White Glass, Navy Steel, Morning Blue and Emerald Green. The digital art collection complements those colors with inspiration from nature, visually channeling how water might flow through a stream or how wind might blow through air.
Generative art is an evolving digital medium that uses the randomness of computer algorithms to create stunning, one-of-a-kind images. It’s a blend of creativity and technology. Combined with the detail of MyBespoke printing, this innovative medium unlocks new ways to experience digital art.
Matt Jacobson – a.k.a. numbersinmotion – uses computer code as his paintbrush. He created the MyBespoke Generative Art Collection to share the unexpected artistry of algorithms with a whole new audience.
The collection is available for a limited time and free to download from January 31 to February 13. The digital prints are sized for Bespoke refrigerator panels, so you can easily upload, edit and print the designs with MyBespoke on Samsung.com.
GamesBeat's creed when covering the game industry is "where passion meets business." What does this mean? We want to tell you how the news matters to you -- not just as a decision-maker at a game studio, but also as a fan of games. Whether you read our articles, listen to our podcasts, or watch our videos, GamesBeat will help you learn about the industry and enjoy engaging with it.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Ray 2.2 boosts machine learning observability and scalability performance | VentureBeat"
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"https://venturebeat.com/ai/ray-2-2-boosts-machine-learning-observability-and-scalability-performance"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Ray 2.2 boosts machine learning observability and scalability performance Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Ray , the popular open-source machine learning (ML) framework, has released its 2.2 version with improved performance and observability capabilities, as well as features that can help to enable reproducibility.
The Ray technology is widely used by organizations to scale ML models across clusters of hardware, for both training and inference. Among Ray’s many users is generative AI pioneer OpenAI , which uses Ray to scale and enable a variety of workloads, including supporting ChatGPT.
The lead commercial sponsor behind the Ray open-source technology is San Francisco-based Anyscale , which has raised $259 million in funding to date.
The new Ray 2.2 release continues to build out a series of capabilities first introduced in the Ray 2.0 update in August 2022, including Ray AI Runtime (AIR) that is designed to serve as a runtime layer for executing ML services. With the new release, the Ray Jobs feature is moving from being a beta feature to general availability, providing users with the ability to more easily schedule and repeat ML workloads.
>>Don’t miss our special issue: The CIO agenda: The 2023 roadmap for IT leaders.
<< VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Ray 2.2 also provides a series of capabilities intended to help improve observability of ML workloads, helping data scientists ensure efficient use of hardware computing resources.
“One of the most common and challenging things about scaling machine learning applications is debugging, which is basically figuring out what went wrong,” Robert Nishihara, cofounder and CEO of Anyscale, told VentureBeat. “One of the most important things we can do with Ray is to improve the tooling around observability.” Where observability matters for scaling AI/ML workloads Ray fits into a number of common use cases for helping organizations scale artificial intelligence (AI) and ML workloads.
Nishihara explained that Ray is commonly used to help scale up and run training workloads for ML models. He noted that Ray is also used for AI inference workloads, including computer vision and natural language processing (NLP), where lots of images or text are being identified.
Increasingly, organizations are using Ray for multiple workloads at the same time, which is where the Ray AIR fits in, providing a common layer for ML services. With Ray 2.2, Nishihara said that AIR benefits from performance improvements that will help accelerate training and inference.
Ray 2.2 also has a strong focus on helping improve observability for all types running workloads. The observability enhancements in Ray 2.2 are all about making sure that all types of workloads have the right amount of resources to run. Nishihara said that one of the biggest classes of errors that ML workloads encounter is running out of resources, such as CPU or GPU memory. Among the ways that Ray 2.2 improves observability into resource-related issues is with new visualization on the Ray Dashboard that help operators better understand resource utilization and capacity limits.
How Ray Jobs will give AI reproducibility and explainability a boost The Ray 2.2 release also includes the general availability for the Ray Jobs feature that helps users deploy workloads in a consistent and repeatable approach.
Nishihara explained that Ray Jobs includes both the actual application code for the workload as well as a manifest file that describes the required environment. The manifest lists all the details needed to run a workload, such as application code and dependencies needed in an environment to execute the training or inference operation.
The ability to easily define the requirements for how an AI/ML workload should run is a key part of enabling reproducibility, which is what Ray Jobs is supporting. Reproducibility is also a foundational element of enabling explainability, according to Nishihara.
“You need reproducibility to be able to do anything meaningful with explainability,” Nishihara said.
He noted that generally, when people talk about explainability, they’re talking about being able to interpret what an ML model is actually doing. For example, why a model reached a certain decision.
“You need a strong experimental setup to be able to start to ask these questions, and that includes reproducibility,” he said.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"How to choose the right Chief AI Officer | VentureBeat"
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"https://venturebeat.com/ai/how-to-choose-the-right-chief-ai-officer"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest How to choose the right Chief AI Officer Share on Facebook Share on X Share on LinkedIn Business people working in high-end modern office Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
As technology spending accelerates across the business world, senior artificial intelligence (AI) leadership is critical to building successful AI programs and implementing them in organizations across industries.
In fact, the global AI market size is estimated to have grown to $432.8 billion in 2022, according to IDC.
But this rapid growth has left a white space for strong AI leadership. Companies are wrestling over how to organize management of AI teams, where AI teams fit within the broader corporate structure, and who should sit in the AI leader role.
Although AI departments and programs have proliferated across business sectors over the past decade, AI remains a relatively new field that corporations are still trying to understand and integrate into their businesses and operations. To keep pushing the field forward and avoid remaining stagnant, many need to take a new approach to AI leadership to maximize their program’s potential.
>>Don’t miss our special issue: The CIO agenda: The 2023 roadmap for IT leaders.
<< VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! In most organizations today, the person driving the AI strategy is usually a technology executive with a senior data scientist background and a career in analytics, data and AI. That person typically possesses a deep knowledge of AI tooling, AI governance, and management processes for AI development, among other specialties.
While this technical acumen is useful for understanding and developing AI, many organizations lack the role of a senior AI leader with technical expertise who can also focus on the business value that the technology can unlock, encourage the organization to invest wisely, and ensure that they have the resources in place to roll out successful AI programs.
To position themselves on the front foot in this new age of AI, organizations must consider creating a structure with two AI leadership roles — a Chief AI Officer (CAIO) and a Vice President of AI — to address the business and technical needs separately so that organizations can more effectively harness the value of AI.
Putting the right people in the right roles AI’s widespread use raises the stakes for companies to have an effective AI leadership structure. Many organizations beyond tech companies use the technology in some capacity for marketing products and services to the right potential customers, calibrating supply chains to meet fluctuating demand, and monitoring their in-house technology.
A successful and optimally running AI function will help companies operate more efficiently and compete more effectively. Therefore, placing the right people in the right senior leadership roles is critical to unleash the program’s potential within the organization.
While the race for tech talent continues, it’s nearly impossible to find a single senior AI professional who is proficient in both a business and technical capacity. However, having two leadership roles that perform these duties separately can solve the problem.
Building AI leadership So, how should an organization begin dividing up these roles and increase focus on AI strategy? Start with the CAIO. Similar to how a company’s Chief Technology Officer (CTO) sits at the executive table and the VP of engineering makes sure everything gets built, the CAIO and the VP of AI can play similar roles.
A strategic CAIO needs to be strong in business decisions and outcomes and not solely focused on implementation. From their position in the C-suite, the CAIO can pay close attention to the organization’s higher business focus and operations and what’s happening in the market. From this C-suite table, they can focus on funding and resources for their organization and building a strategic plan while having an influential voice for other executives.
Alternatively, the VP of AI needs to be a technical expert respected by the company’s data scientists and AI engineers. They’ve typically risen through the ranks of an organization’s AI structure — from a data scientist to a senior data scientist, to a manager of data science and then to the VP level.
The VP of AI focuses on delivering products and projects on schedule. They are also responsible for talent recruitment and hiring. Finally, they oversee the organization’s technical infrastructure, determining the right mix of on-premises versus cloud capacity.
Where to start AI programs in most companies today would either fall under the purview of the Chief Information Officer (CIO) in a technical organization — where the company would house analytics and possibly a data science team — or within the digital, innovation or transformation divisions, where it would serve a more business-oriented function.
When setting up a company’s new AI division, many infer that the most strategic approach would be to place it in an IT department. However, in doing so, a company is subjected to limiting AI’s capabilities solely to that department rather than holistically incorporating it throughout the organization.
For example, an organization such as a consumer goods giant or a publisher with a data science team might decide to elevate its Director of Data Science to a newly created Director of Data Science and AI position without fully understanding what that new role would entail. In this scenario, it would then be difficult for the new Director of Data Science and AI to develop a strategic plan for the CEO or CTO, as their role to this point would have been exclusively technical.
But a two-pronged AI leadership structure presents a solution. Companies can follow two paths to implementing this new structure, depending on whether they haven’t set up an AI program yet, or whether they have set one up, but it’s not working effectively.
Evolving AI leadership The first path applies to companies lacking an AI program.
To begin, these organizations need to hire their leadership talent in data science and engineering, provide funding and allocate internal resources. They can start by hiring the CAIO and charging that person with finding a VP of AI — to act as his or her technical leader — and focusing on building a business plan for the broader AI function.
The second path applies to businesses with underperforming AI programs. Again, the problem often stems from a substandard leadership structure that lacks an AI business head at the top. In this case, companies should hire a CAIO and have them restructure the organization with a VP of AI. And if the business has fragmented its AI talent across the company, the organization needs to aggregate them under this new leadership structure.
Indisputably, AI and data science departments have grown in complexity and importance to many companies’ operations and earnings. Therefore, corporate structures should expand — by establishing a CAIO and a VP of AI — to reflect their rising prominence within organizations and better realize AI’s evolving potential.
Rodrigo Madanes is global AI leader at EY.
### The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organization or its member firms.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Auxuman lets gamers generate multiplayer games on LG TVs using simple text input | VentureBeat"
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"https://venturebeat.com/ai/auxuman-brings-generative-ai-multiplayer-games-to-lg-tvs"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Auxuman lets gamers generate multiplayer games on LG TVs using simple text input Share on Facebook Share on X Share on LinkedIn Auxworld will generate multiplayer game worlds based on your text inputs.
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Auxuman , an AI gaming startup, said it has teamed up with Oorbit to bring generative AI multiplayer gaming to LG Electronics TVs. In Auxuman’s Auxworld app, players can use AI to generate their own multiplayer metaverse by typing text input, similar to how AI tools generate images.
It makes use of Auxuman’s custom AI network, and it’s all part of LG’s plan to make the “metaverse” more accessible to consumers by providing metaverse-like experiences on TVs.
Oorbit wants to use cloud technology to build the world’s premiere technology platform powering the metaverse, and it debuted starting on LG TVs on January 15. And through this partnership, Auxuman’s Auxworld will enable anyone to instantly create an online multiplayer game simply through text input in a manner similar to popular AI image generators.
“The fact that you will be able to do this right from your TV is very exciting for us,” said Negar Shaghaghi, CEO of Auxuman, in an interview with GamesBeat. “Essentially all you need as a consumer to use the Auxworld experience is a text prompt.” Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! Harnessing the power of generative AI with its own proprietary AI technology, Auxuman’s Auxworld (spelled auxWorld by the company) will empower anyone to create endless multiplayer game sessions easily, quickly and affordably with different IP styles, assets and game modes that they can engage with friends or any community. The result is a fusion of AI and games.
As long as game development is so difficult, time consuming and expensive, it’s going to be only a few people who can dedicate the time and effort to do it, she said.
“We want to change that model,” she said. “You can make it more efficient, in terms of costs and complexity, and more intuitive. This kind of spontaneity for content creation, the way you see on TikTok or Instagram, is really interesting.
When you input text, you are transported into a game world.
“We’re able to connect the intent of the user to all the things that make up a game, like the mechanics, environment, assets and all of that. It’s essentially an unlimited way to assemble games. Every time you come into it, it’s a different thing,” she said.
Of course, games generated like this won’t be very deep.
“My biggest lesson from all of the metaverse experiences that we saw is that it isn’t enough to give people a virtual environment and ask them to join it. That’s why we have experience on both sides (AI and games). One of the things we achieved is that it works very well,” she said. “That’s the result of years of research on how we use AI in a meaningful way.” “Auxworld revolutionizes the development of virtual worlds and gameplay by providing a simple and streamlined way for anyone to build a completely immersive, engaging and social experience. Only by expanding the definition of ‘game creator’ to anyone with a desire to socialize and express themselves through games, we can truly make our online life more engaging and immersive,” said Shaghaghi. “Through this partnership with LG and Oorbit, we give LG customers the very first opportunity to bring personalized gaming to their own living rooms.” Gaming is one of the most popular forms of entertainment, but games are expensive and time-consuming to create and are not personalized to consumers like most other social entertainment applications. Platforms that do allow players to use gaming for self-expression or socialization are limited in style and options. All of this changes with the launch of Auxworld, said Shaghaghi.
“Partnering with Auxworld and LG allows customers endless gameplay with the ease of accessing games through their Smart TV,” said Ash Koosha, CEO of Oorbit, in a statement. ”By coupling auxWorld’s no-code gaming with the Oorbit platform, we are continuing our mission to make metaverse gaming vastly more accessible.” Shaghaghi thinks the primary audience for Auxworld will be young people, including non-traditional gamers who are not as versed in gaming but want to make something fun themselves.
“You don’t really think about being involved in this big game,” she said. “It’s like a spontaneous experience that you can have just like sitting down and watching. I’m pretty excited to cross that chasm and target ordinary people.” Origins Shaghaghi started Auxuman in 2019 with a focus on applying AI to build behavior-driven virtual beings (or non-player characters). While Shaghaghi is an AI expert, here cofounder Isabella Winthrop was a big gamer. They saw a lot of potential in blending AI and gaming. And as excitement around generative AI and the metaverse grew, the company’s plan came together.
“Most of what we do is research and development on how we can use AI to simplify game creation. Essentially, when we started the company in 2019, our focus was around adding AI to NPCs or game characters,” Shaghaghi said. “We had NPCs that you could plug into game engines. But over the years, we’ve done a lot of interesting research on how we can use generative AI to facilitate new experiences.” The team started asking questions, like why are the games so expensive? Why do they take so long to make? Why are the risks so high? The company distilled its vision to making building games as easy as it is to generate social media.
“Only a few people produce games, and a lot of people consume them,” she said. “And we think that if we get to a point where the border between the creator and consumer is blurred — the same way that you have with social media platforms — then we can see true creativity and being spontaneous in the moment. Gaming doesn’t have to be something that lasts for a long time. It can be a disposable content.” When you’re done playing with a game you have generated, you can decide if you want to keep it or toss it.
The “aha” moment came. And the company expanded its AI and digital twin expertise to evolve into an AI game creation platform dubbed Auxworld.
“Users want ownership of what they consume through personalized and customizable content,” Shaghaghi said. “AI generative models are making the creation of content easier than ever, but it has yet to be utilized for the creation of video games…until now. Players can now literally turn their thoughts into video games.” They teamed up with Oorbit to make it easier still to remove barriers for consumers. And then LG got involved.
“These experiences are seamless, without complexity, and that’s the benefit we get from Oorbit,” Shaghaghi said.
The company has funding from Mark Cuban, Tess Hau, Betaworks Ventures, and others. The company has 10 people.
As for the use of generative AI across gaming, Shaghaghi said she sees people using AI throughout the game creation process.
“A lot of people are looking at AI generating assets. But right now, a lot of efforts I see are focused on the developer side. I’m hoping to see more of this put to use on the consumer side. Where consumers are the target audience for generative AI, rather than developers.” GamesBeat's creed when covering the game industry is "where passion meets business." What does this mean? We want to tell you how the news matters to you -- not just as a decision-maker at a game studio, but also as a fan of games. Whether you read our articles, listen to our podcasts, or watch our videos, GamesBeat will help you learn about the industry and enjoy engaging with it.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"AI success is being limited by poor digital transformation | VentureBeat"
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"https://venturebeat.com/ai/ai-success-is-being-limited-by-poor-digital-transformation"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest AI success is being limited by poor digital transformation Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Digital transformation has multiple dimensions and complexities, which are sometimes lost on organizations undertaking it. The recipe for success lies in rethinking the processes and the organizational structure to generate maximum value from the technology framework — something many enterprises continue to struggle with.
A 2020 study by Boston Consulting Group found that about 70% of digital transformation projects fall short of their goals even when the priorities are clearly mapped and leadership is aligned. Compounding the challenge is the need to bring AI into the organization that is transforming. AI is everywhere today and promises great returns from customer experience and organizational efficiency. Not investing in AI is a non-starter now when a digital transformation effort is begun, but the investment can feel like an insurmountable task. Why is this? >>Don’t miss our special issue: The CIO agenda: The 2023 roadmap for IT leaders.
<< Gaps in the digital transformation roadmap can hinder success of AI initiatives The factors that lead to failed digital transformation initiatives also act as roadblocks to the success of AI initiatives. These include: VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Identifying the right problems to solve: Without proper project design and outside intervention, identifying the right problem and the right approach to solve it is unbelievably difficult. This is where a poorly executed digital strategy or a faulty transformation roadmap will act as a bottleneck for AI success: The underlying data strategy was not aligned to the organization’s unique needs in the first place.
Lack of an overarching data strategy: Companies must have a clear idea of what kind of data they need for digital transformation. Otherwise, they risk investing in improper tech stacks. A proper data infrastructure and strategy form the foundation upon which emerging technologies are built, and formulation of an AI strategy is created on top of it.
Lack of integration across verticals and units: Too often, digital transformation projects are siloed within individual departments instead of integrated across the company. This can lead to duplicate efforts and wasted resources. Siloing prevents data and insights to move freely across departments, which can make deploying AI challenging. The fact that many AI programmers are led by specific departments rather than centrally managed makes the situation worse. As a result, businesses frequently depend on a small number of vendors for their AI requirements, which can result in vendor lock-in and limited flexibility when using AI systems. Silos can make employees resistant to change. Professionals may prefer their work surroundings within the silo, making them resistant to regulations that would disrupt their environment.
Lack of CoEs and best practices, proper frameworks and approaches: A poor digital transformation initiative does not create the proper system of best practices, Centers of Excellence and frameworks to develop, test and enhance digital solutions.
Poor execution due to lack of cross-pollination and overall coordination: Many companies lack the internal expertise needed to effectively manage a digital transformation initiative. Additionally, they may lack adequate change management processes and tools.
Absence of a human-centric, digital-first culture: The first step in creating an organizational culture that empowers employees to adopt emerging technology begins with a successful digital transformation. If that is not in place, subsequent AI initiatives are doomed to failure.
Connected systems lead to successful AI programs To overcome these challenges, organizations need to develop AI systems that are connected across the enterprise like a mesh or fabric, ensuring seamless collaboration. This will also require a shift in mindset from thinking about AI as a tool for individual departments to considering it as a strategic objective for the entire organization.
Organizations need to adopt a scalable architecture across the enterprise, one that’s modular, holistic, scalable, de-risked and agile. This will provide a strong AI foundation with tools and processes that manage the end-to-end discover-to-implementation cycle while allowing the organization to take full advantage of the benefits AI can offer and steadily shape their business for lasting growth.
The fundamental dimensions in which AI can flourish include: Modular AI architectures provide the flexibility needed to tailor AI solutions to specific business needs. They also make it possible to easily add or remove features as required. Organizations can use modular AI to deploy it for specific use cases, resulting in a more open, focused, and affordabl e overall AI system and strategy.
Holistic AI architecture provides a comprehensive view of the business and a deeper understanding of how AI can be applied across all areas. This ensures that enterprises can adopt AI with confidence, as such an architecture provides assurance, support on ethical and legal issues, protection from reputational and financial damage, improved transparency of the system, and risk mitigation.
A scalable data fabric ensures that it builds links, or talks, to all of an enterprise’s microservices or services. This acts as a common business language for the company irrespective of any underlying technologies, source systems or data formats, and can support millions of micro databases, concurrent or virtualized, in a distributed, high-performing and consistent architecture.
De-risk AI to manage reputational and performance risks. Analytics model interpretability, bias detection and continuous performance monitoring should be built into various stages of the lifecycle, from development to deployment and use.
Agile AI architecture is essential for companies that need to quickly adapt to changing market conditions or customer needs so they can rapidly deploy and implement AI solutions.
Agile approaches have long been recognized for their capacity to improve teamwork, dismantle silos and empower decision-making and project management, among other things.
Summary Successful digital transformation requires the integration of AI into all areas of a business, like a fabric and mesh. This will result in fundamental changes to how the business operates and delivers value to customers. To fully capitalize on the opportunities presented by digital transformation, businesses need to have a clear understanding of what it entails. With this understanding, they can make their digital transformation efforts effective by breaking down siloed processes that can inhibit AI integration and a powerful digital transformation.
Balakrishna DR, popularly known as Bali, is the executive vice president and head of the AI and automation unit at Infosys.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"SplitMetrics acquires App Radar to boost mobile app growth | VentureBeat"
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"https://venturebeat.com/games/splitmetrics-acquires-app-radar-to-boost-mobile-app-growth"
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"Game Development View All Programming OS and Hosting Platforms Metaverse View All Virtual Environments and Technologies VR Headsets and Gadgets Virtual Reality Games Gaming Hardware View All Chipsets & Processing Units Headsets & Controllers Gaming PCs and Displays Consoles Gaming Business View All Game Publishing Game Monetization Mergers and Acquisitions Games Releases and Special Events Gaming Workplace Latest Games & Reviews View All PC/Console Games Mobile Games Gaming Events Game Culture SplitMetrics acquires App Radar to boost mobile app growth Share on Facebook Share on X Share on LinkedIn Silvio Peruci and Thomas Kriebernegg of App Radar.
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SplitMetrics has acquired Austria’s App Radar in a seven-figure deal to boost the growth of mobile apps.
App Radar is an app marketing and analytics platform. The strategic collaboration positions SplitMetrics to offer an expansive platform powered by artificial intelligence (AI) for various app growth services.
The merger brings together two startups to create a comprehensive solution for app developers and marketers. The newly formed entity will offer an array of AI-powered services, encompassing paid user acquisition (UA), app store optimization (ASO), conversion rate optimization, and data analytics.
Key highlights AI services: The combined forces of SplitMetrics and App Radar results in the creation of the largest platform in the industry, providing AI-powered services to over 1,000 customers across more than 100 countries. These services include UA, ASO, conversion rate optimization, and advanced data analytics.
Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! Separate brands, unified goals: While operating as separate brands, SplitMetrics and App Radar will synergize their efforts to serve customers across Europe and the United Kingdom, North America, and the Asia Pacific region. This approach allows both entities to maintain their unique strengths while benefiting from the collective expertise.
Global impact: With a global team of 160, SplitMetrics currently manages over $250 million in annual ad spend, catering to clients such as Babbel, Skyscanner, Glovo, and Rakuten Viber. App Radar specializes in app store optimization and automation for 30,000 app developers and marketers globally.
Strategic growth and consolidation: The acquisition aligns with SplitMetrics’ broader strategy to capitalize on the growing trend of AI-enabled marketing. The goal is to evolve into an AI-centric company, breaking down silos between UA, ASO, and conversion optimization to offer holistic services.
Max Kamenkov, CEO of SplitMetrics, said in a statement, “App Radar has a range of very powerful tools that are fully complementary to our own. By combining these services, we can offer a market-leading end-to-end solution that will drive incredible growth for our customers.” Thomas Kriebernegg, managing director of App Radar, said in a statement, “We’re delighted to join SplitMetrics’ team and create a powerful new service for our customers. Our respective strengths in the US and Europe, and key app stores, make SplitMetrics and App Radar a perfect match.” Silvio Peruci, managing director of App Radar, emphasized the role of AI in the future of app marketing in a statement, “Over the past year, AI has opened the door to the creation of a range of new AI-driven marketing techniques that use deep analysis of data to enable much richer and impactful campaigns.” The collaboration between SplitMetrics and App Radar is poised to usher in a new era in app marketing, leveraging AI to provide an all-encompassing solution for developers and marketers.
GamesBeat's creed when covering the game industry is "where passion meets business." What does this mean? We want to tell you how the news matters to you -- not just as a decision-maker at a game studio, but also as a fan of games. Whether you read our articles, listen to our podcasts, or watch our videos, GamesBeat will help you learn about the industry and enjoy engaging with it.
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Join the GamesBeat community! Enjoy access to special events, private newsletters and more.
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"Replai introduces AI for mobile game ads and raises $8M | VentureBeat"
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"https://venturebeat.com/games/replai-introduces-ai-for-mobile-game-ads-and-raises-8m"
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"Game Development View All Programming OS and Hosting Platforms Metaverse View All Virtual Environments and Technologies VR Headsets and Gadgets Virtual Reality Games Gaming Hardware View All Chipsets & Processing Units Headsets & Controllers Gaming PCs and Displays Consoles Gaming Business View All Game Publishing Game Monetization Mergers and Acquisitions Games Releases and Special Events Gaming Workplace Latest Games & Reviews View All PC/Console Games Mobile Games Gaming Events Game Culture Replai introduces AI for mobile game ads and raises $8M Share on Facebook Share on X Share on LinkedIn Replai can tell you what should do with your ads.
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Replai , a software-as-a-service (SaaS) company, has unveiled its tech for combining AI with mobile game advertising to make much more effective ads in a very short time. The company has also raised $8 million to date.
The AI from Replai aims to automate video creation for marketing purposes, promising effectiveness and speed in creating ads.
The company already operates a platform that processes over $5 billion of ad spend annually. With a focus on collaboration with major gaming companies globally, Replai’s technology now generates thousands of video ads each month. The company’s latest AI innovation stands out for its automatic video creation from data or text prompts, marking a milestone in gaming advertising.
“Replai AI creation is a natural step that follows from the video intelligence platform, expertise, and data models that we’ve invested in for years,” said CEO João Vieira da Costa. “We were surprised when we put the creation product in the hands of early adopters – the empowering effect is real and is supercharging professionals like we’ve never seen in over a decade of the industry. We saw prompts being made after midnight by creative and non-creative people.” Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! He added, “We know the market is big, and many competitors will surely come. At Replai, we try to create an edge with the levels of data we already process into insights, together with a genuine love for helping the individuals we have the pleasure to call customers.” It’s clearly part of the trend around using AI to enhance business processes, such as creating ads.
“The market is exploding,” said Da Costa. “More than a year ago, we started developing generative AI capabilities. And it wasn’t until then that we became capable of doing an entire video from scratch using AI.” Da Costa said that the market is very responsive to what the company is doing, and the opportunity is big. Replai has about 30 people, with much of the product team in Portugal.
The hallmark of Replai’s AI breakthrough lies in its capability to fabricate videos based on a customer’s ad-network accounts and the game’s data. Using advanced computer vision, the AI deciphers in-game data, interprets tags, and dynamically produces real-time video creatives.
The company has transformed about $5 billion per year in ad spending into its data platform and it uses that information with its generative AI model to generate videos for customers on the fly. It can incorporate your existing videos and ads and generate its own ads as needed.
Humans can review the work but Replai can deliver the video ads directly to the clients’ ad networks.
“We receive the feedback in real time and can iterate the video automatically and make it live,” da Costa said. “The customer doesn’t have to touch it. What Replai was always able to do was to give you an insight that you should check data by the other sources. If changes are necessary, they can be implemented in a very short time, rather than a week or more with manual work.” “Because this creates a feedback loop, we can then review it live. We can replay and analyze the elements, which are the facts that we use together with the metrics that can give us a way to bring a conclusion,” he said. “The AI generator creates a new video ad automatically. We think this is a very hot topic.” Additionally, Replai automatically launches these videos within ad campaigns, gauges performance fatigue, and tailors creative variations for different ad networks. This approach, driven by Replai’s Learning Language Model (LLM), transforms video tags and metrics data into fresh and successful content.
Innovating further, Replai has introduced a distinctive text-to-video platform empowering user acquisition and creative teams to make AI-driven changes to existing videos or create entirely new ones. This platform, capable of mimicking competitors’ styles, offers a competitive edge in the market.
The technology’s potential to alter the marketing landscape for gaming companies globally was underlined by da Costa.
Da Costa started the company in 2019. And now Replai said it leads the frontier in creative insights within mobile gaming advertising. Replai’s AI-driven platform automatically generates marketing videos from ad-network data, product content, and text prompts.
With an emphasis on performance optimization leveraging advanced computer vision and AI models, Replai caters to global gaming brands, seeking to enhance growth and efficient marketing strategies. The company operates across San Francisco, London, and Porto, emphasizing innovation and customer-centric solutions.
“We have a few pilot customers on stealth that we’ve done this with and they are very big customers,” da Costa said. “They are already at the stage where it is very useful, sometimes generating hundreds of videos or even thousands of videos per month. It has been very intense.” GamesBeat's creed when covering the game industry is "where passion meets business." What does this mean? We want to tell you how the news matters to you -- not just as a decision-maker at a game studio, but also as a fan of games. Whether you read our articles, listen to our podcasts, or watch our videos, GamesBeat will help you learn about the industry and enjoy engaging with it.
Discover our Briefings.
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"Layer AI raises $1.8M to bring AI to game art production | VentureBeat"
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"https://venturebeat.com/games/layer-ai-raises-1-8m-to-bring-ai-to-game-art-production"
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"Game Development View All Programming OS and Hosting Platforms Metaverse View All Virtual Environments and Technologies VR Headsets and Gadgets Virtual Reality Games Gaming Hardware View All Chipsets & Processing Units Headsets & Controllers Gaming PCs and Displays Consoles Gaming Business View All Game Publishing Game Monetization Mergers and Acquisitions Games Releases and Special Events Gaming Workplace Latest Games & Reviews View All PC/Console Games Mobile Games Gaming Events Game Culture Layer AI raises $1.8M to bring AI to game art production Share on Facebook Share on X Share on LinkedIn Are you looking to showcase your brand in front of the brightest minds of the gaming industry? Consider getting a custom GamesBeat sponsorship.
Learn more.
AI is coming to disrupt game art production whether artists like it or not. And Layer AI is the latest startup to raise $1.8 million to bring AI to game art.
Layer AI raised the round of venture capital funding from investors such as The Games Fund to create what it says is a cutting-edge AI-powered productivity tool.
The San Francisco company, known for its innovative solutions, has attracted a robust support system from industry stalwarts and investors in the gaming and AI sectors, with case studies here.
The team is led by a cadre of industry professionals with extensive experience in AI, gaming, and computer vision. Volkan Gurel, the CEO, brings a background in engineering and management from MIT, Hunch, and Coinbase.
Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! Supported by Burcu Ozcengiz, the CRO, and Kuo-chin, the CTO, Layer AI boasts a team with a strategic mix of expertise and experience across various domains, all committed to advancing gaming art production through AI. The company has four employees now and it is hiring.
Investors in the round included top serial entrepreneurs and industry legends like Jim Payne, gaming angels like Akin Babayigit, Michele Attisani, Dilpesh Parmar and gaming VCs like The Games Fund, The Games Syndicate, GFR Fund, Laton Ventures along with other AI/Tech VCs and angels like 500 Global, Elena Silenok, Taimur Rashid. Additionally, the team also got a strategic investment from the US-based top art production and talent house Devoted Studios.
Gurel, CEO of Layer AI, said in a statement, “Just like Web 2.0, Cloud computing or mobile unlocked novel applications that beat incumbents and other startup competitors based on a great product experience, we believe the AI revolution will be no different. AI has unlocked many new applications that will be built on top of this new tech stack, and we plan to win by building the best product experience for artists in the enterprise leveraging the power of all the great foundational models and tools released by OpenAI, Meta, Stability AI and others. We’re creator-first, enterprise-ready and will remain model-agnostic.” The newly secured funds and strategic investments have fortified the company’s vision to enhance game art production. The tool, known for its seamless integration into art pipelines and intuitive workflows, aims to empower creators across skill levels, allowing them to explore new ideas and art styles.
In an industry where AI tools often focus on general use cases or standalone features, Layer AI stands out with its commitment to serving everyday use cases in a user-friendly and enterprise-ready manner. Testimonials and detailed case studies attest to the productivity boost and enhanced user experience that Layer AI offers to game creators. It is being used at studios like Tripledot Studios, APPS Teknoloji and Games United.
“Layer.ai Supercharged Tripledot’s art creation, tripling our production speed and elevating quality. By reducing our reliance on outsourcing studios, we’ve not only saved significant costs but also brought the magic of art production in-house. We’re incredibly excited about this technology and eagerly await further updates,” said Andriy Matviychuk, vice president of creative at Tripledot Studios, in a statement.
“Being deeply rooted in game development we see pivotal changes coming to production with gen-AI tools coming into play,” said Maria Kochmola, General Partner at The Games Fund, in a statement. “We are not big fans of the idea of flooding the market with soulless content and Layer.AI sets itself apart by aiming to enhance, not replace, human artistry, liberating creators from mundane tasks. That is what we all believe in. We also like that their focus is on enterprise clients and their real needs for seamless integration into existing production pipelines.” Looking ahead, Layer AI plans to expand its offerings beyond 2D generation in gaming to cater to spine and sprite animations. The team envisions integrations into non-gaming workflows like marketing and advertising, ensuring a smooth transition and enhanced productivity for creators.
“At a high level, our creative process starts with sketching, continues with draft coloring, and lasts with final coloring,” said Bulut Korzay, chief product officer at Fortune Mine Games,” in a statement. “Normally, we are producing one level for our game in 15 days. With the help of Layer AI, we decreased this time to 5 days Our aim is to make it 3 days with the upcoming new features Layer team has planned to ship.” The company has already begun serving top-tier clients like Tripledot, Sciplay, Mag Interactive, and numerous professional artists since its launch in February 2023. Layer AI is committed to further strengthening its security and reliability through SOC 2 and ISO certification, ensuring a robust offering for enterprise clients. The team is hiring. You can visit Layer AI’s careers page for details.
“AI unlockedcmany opportunities for gaming and we want Layer to be the easiest tool to get onboard with and the fastest to ROI,“ said Ozcengiz, the CRO. “Layer is already serving numerous top-tier clients like Tripledot, Sciplay, Mag Interactive and hundreds of professional artists since launching in February 2023. Layer is also working to shore up their compliance program and will achieve SOC 2 and ISO certification to further cement the security and reliability of their offering for the enterprise.” Gurel said the company’s goal is to be a creator-first and enterprise-ready product.
“We believe AI will change art creation no matter what, and we want to be the ones doing this in the most responsible and artist-friendly way, and in a way that gives confidence to enterprise customers when it comes to copyright,” he said.
Regarding copyright law, Gurel said in an email to GamesBeat, “We respect copyright and want to protect the intellectual property of artists. We believe content generated with no artist involvement or guidance is not copyrightable. Layer tries to stay in line with established norms in the industry around what’s copyrightable work and adapts these norms to the age of AI. Two examples of this are ideation and producing final assets.” He added, “Today, when a team of artists starts a new project, they do concept development by creating a mood board, gathering content generated by other artists. The goal of this exercise is to draw inspiration and develop a unique style for the project. No artist would say putting such content in the mood board violates someone’s copyright, since this content is not put directly into the final product. Layer supports this use case by providing generic AI models like SDXL or DALL-E 3, and we encourage our users to use these for ideation and concept development, and not to use the outputs of these models directly in their final product.” And he said, “Once the team develops a unique, original, ‘copyrightable’ style, then Layer provides a way for them to finetune AI models based on reference images in this style and these finetuned models use general world knowledge and combine it with the style in the reference images to output other images in that style. This makes Layer a productivity booster for use cases where a game studio wants to create many assets in their style. In this use case, the creativity and originality still comes from the artists themselves, and the generated assets are not 100% ready in many cases, and the artists and art directors still need to get the final assets to 100% production readiness.” Regarding the threat that AI poses to jobs, Gurel said that it’s true that AI will eliminate some jobs, but it will create many more higher quality jobs.
“We believe most artists’ jobs won’t be eliminated, but they will evolve – removing the basic and repetitive parts of their work and opening up new possibilities for creativity,” Gurel said. “This has happened many times before with other technological revolutions in the past and despite all the hype with AI today as if it’s unique in history, it is ultimately a massive technological revolution, and we can draw a lot of analogies from the past.” He added, “Photography, digital art or even tube paints were all controversial when they were first invented, but what ended up happening is demand for art exploded along with these inventions, because the cost to create art went down and artists’ productivity went up. We believe this time will be no different – artists’ creativity and productivity will increase by an order of magnitude and the demand for this art will increase even more as a lot more possibilities open up.” And he said, “With our customers we’re seeing that with increased productivity, instead of cutting jobs they are shipping more game content in shorter time periods. And this makes sense – if a studio is creative and limitless in their imagination, they will take a tool like Layer and simply make more top quality games that their users want, and thus generate more revenue. This is not a zero sum game.” As for keeping costs for AI low, Gurel said, “The cost has not been a real issue for us for two reasons.
First, our team is quite experienced building ML infrastructure, and we used this experience to architect a best-in-class system that’s scalable, efficient and super fast. As an example, our image generation speeds are an order of magnitude faster (~3 seconds per batch) than any comparable tool.” And he said, “And second, we’re focused on the enterprise segment and enterprise user flows are a lot more predictable. Our users come to Layer, get the content they need, and leave happy. Consumer focused tools on the other hand might be having a lot of cost related issues and concerns due to the unpredictable nature of their needs and how there is a lot more content created “for fun”.
The company started in November 2022 and it launched its first version in February 2023 after seening early success. The company incorporated in July 2023.
“For a company like us who is focused on Merge-3 games like Merge Park, Layer has helped multiply our art libraries and production powers, we’re 240% more productive thanks to Layer,” said Yagiz Gur, production lead at Games United, in a statement.
When it comes to accuracy, Gurel said the company can deliver two to three times more productvity, based on real users.
“Layer’s contribution to our art pipeline has been tremendous. We’re able to produce assets for our games with 100% more productivity. In other words, it takes half the time it used to take to produce the same assets. Before Layer, we used to create 3D models> Pose the model then get a render. If we wanted to edit an asset we needed to go back to the model and take another render to edit the asset. Using Layer’s Asset Studio, making edits takes only a few minutes. Not only it saves time, but it also multiply our abilities to think creativity by providing a few variations to choose from achieve outputs we couldn’t think about before,” said Samet Soylemez, game artist at Apps Teknoloji, in a statement.
“At PlayPack, we were looking for a user-friendly solution that could easily onboard the team for generative AI pipeline integration and workflow, and Layer.ai was the tool that the team simply chose over all other competitors due to the best user experience. This really allowed us to speed up the production of our merge games and save a lot of resources, enabling us to move forward with content development,” said Tatjana Kondratyeva, CEO at Playpack, in a statement.
As for the inspiration, Gurel said that the team focused AI, MLOps and Gaming. In the summer/fall of 2022, DALL-E 2, Stable Diffusion were released, and the Dreambooth paper came out, which triggered massive interest in the AI art hobbyist community in finetuning models to create content in a specific style.
“When we saw this, and discussed it in detail in a brainstorming session, we instantly recognized that if it works as promised, it could solve some serious pain points in the art creation pipelines during game development that we were very familiar with,” Gurel said. “Within two weeks of starting the project, we had some early customers from wo studios that had millions of users and that served both as validation of the idea and as guidance for further development.” GamesBeat's creed when covering the game industry is "where passion meets business." What does this mean? We want to tell you how the news matters to you -- not just as a decision-maker at a game studio, but also as a fan of games. Whether you read our articles, listen to our podcasts, or watch our videos, GamesBeat will help you learn about the industry and enjoy engaging with it.
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"The AI revolution: Shaping the future of investing | VentureBeat"
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"https://venturebeat.com/business/the-ai-revolution-shaping-the-future-of-investing"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Contributor Content The AI revolution: Shaping the future of investing Share on Facebook Share on X Share on LinkedIn In the ever-evolving financial landscape, artificial intelligence (AI) has brought about a quiet revolution, fundamentally altering how investing is now approached. Integrating advanced natural language processing (NLP) and large language models (LLMs) has introduced a new paradigm in trading, investment, financial analytics, reporting and financial literacy.
AI-driven technologies analyze vast amounts of data in real time from various sources like news articles, social media, and financial reports to enhance trading and investment decisions. This has led to enhanced data analysis, empowering data-driven decision-making amid the constant influx of new information.
This synthesis of technology and finance not only streamlines operations but also improves access to financial knowledge and services, fostering a more inclusive and financially literate future. AI-driven algorithmic trading strategies execute high-speed, high-frequency trades, exploiting market inefficiencies and price disparities.
In addition to driving innovations in trading, AI also plays a crucial role in fraud detection and risk management, benefiting not only investors but financial institutions as well. By employing AI, this revolution is seeing the democratization of investing as it grants increased access to advanced investment strategies — once limited to institutional investors — making investing more accessible.
One person who is making their mark amidst this transformative tide is Lumine Lin, whose company involves the exploration of AI’s profound impact on the investment realm. Lin’s venture, Highmoon Capital, has harnessed AI’s capabilities to reshape the future of investing and trading while focusing on data-driven insights, predictive analytics and sophisticated decision-making.
Drawing from his early entrepreneurial ventures, Lin gained a keen understanding of AI’s value in dissecting complex data sets to unveil market trends that often elude human analysis. At Highmoon Capital, AI is the linchpin, driving research and informing trading strategies with robust data analysis and predictive modeling. Lin’s team employs these tools not just to react to market movements but to anticipate them, incorporating a nuanced grasp of market psychology into their investment process.
Another aspect of Lin’s approach to trading is using artificial intelligence to conduct large-scale research. At Highmoon Capital, AI takes center stage, yet with a humanistic approach that is groundbreaking in finance. This enables the team to dive into the psychological intricacies of the market more effectively and efficiently. It is this blend of human expertise and AI capabilities in understanding the subtle interplay between emotion and economics that empowers the company to ask probing questions to unlock the full potential of this technology. The nuanced application of AI provides key insights that better inform investment strategies. Equipped with these data-driven perspectives on market psychology, the traders make more informed decisions.
Lin envisions a future where AI continues to shape the investing world, additionally facilitating advanced research, predictive analysis and enhanced decision-making at his company. Highmoon Capital’s objective is to empower users with the wealth of data and insights generated by AI while nurturing personal development through trading.
In an industry historically rooted in human decision-making, Lin’s journey underscores AI’s transformative potential in the investing world. He aims to revolutionize trading strategies by harnessing AI’s analytical power to reshape how individuals approach investing. By leveraging AI’s capabilities, Lin is determined to push the boundaries of the investment landscape, contributing to a more data-informed, insightful and inclusive financial future.
VentureBeat newsroom and editorial staff were not involved in the creation of this content.
VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"A look back at the metaverse in 2022: Hype, investments and marketing moves | VentureBeat"
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"https://venturebeat.com/virtual/a-look-back-at-the-metaverse-in-2022-hype-investments-and-marketing-moves"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages A look back at the metaverse in 2022: Hype, investments and marketing moves Share on Facebook Share on X Share on LinkedIn The metaverse This year, 2022, can be considered a fruitful year for metaverse investments, though doubts about the viability of the virtual world still cross some stakeholders’ minds. Last year, companies and venture capital firms pooled $57 billion in stakes, but that amount has since been surpassed by the $120+ billion recorded this year, according to a report by McKinsey.
Despite the tragic outing of Meta in Q3 2022 , the computerized reality remains a mystery that plenty of businesses want to unravel and commercialize.
In an always-on environment where events occur in real-time, Gartner expects 25% of people to be in the digital space for at least one hour daily by 2026. The metaverse symbolizes a new way for individuals and companies to interact with technology. Its use cases stretch from the usual culprits like blockchain and gaming, to the rehabilitation of patients , digital fashion and much more. Some of the popular industry leaders actively involved in unlocking the metaverse’s seemingly limitless potential include Twitter, Microsoft and Spotify.
Although Web3 awareness is at an all-time high and translates into serious competition, Asaf Fybish CEO and cofounder of GuerillaBuzz , a Web3 marketing agency, believes there’s much to unravel in the next few years. Although Fybish admits that budgeting and strategy for short-term metaverse goals have recently changed due to the ‘bear market,’ he says, “marketing in the metaverse will become increasingly prioritized over the next two to four years ahead.” On top of that, Fybish told VentureBeat that, “More [marketing] dollars would go into the metaverse in the next coming years as major brands continue to shift their marketing spending toward the emergent metaverse space.” Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! While allocating a sizable amount of an organization’s marketing budget to metaverse efforts might seem frivolous, the ability to develop and personalize new worlds for customers is a hill many are willing to die on.
Controversial, but growing It’s not uncommon for new ideas to get fiercely contested, and that’s largely been the case for the metaverse in 2022. The blazing buzz about the metaverse seems to have divided many experts. Mark Zuckerberg’s explanation in 2021 described it as the next stage of technology where “you’re in the experience, not just looking at it.” However, respondents to a 2022 PEW Research study consider the metaverse to be the crop of marketing hype.
To Steve Wilson, one of the survey’s participants and founder of Lockstep Consulting , the metaverse “ is not well enough defined for us to make predictions about a fully immersive experience being more important by 2040.” Wilson believes it should be allowed to evolve naturally, noting that “digital renditions of reality may convey excitement, but then the risk of adoption isn’t receiving adequate consideration.” Meanwhile, the differing opinions on what the metaverse is and should be hasn’t stopped its growth.
Findings from Statista in 2021 revealed a market revenue of $38.85 billion and estimated the figure to hit $47.48 billion. In 2030, the segment is predicted to be worth at least $678.8 billion.
What’s in store for the metaverse in 2023? Just as different opinions of the metaverse’s capabilities exist, industry players have also unveiled varied purposes for it. And while opting to build virtual environments or enabling team collaboration using a digital community are two interesting — yet separate — paths, what should any brand expect from the virtual world next year? Forrester predicts that many businesses will transition from employing customer-centric NFT art to providing extraordinary customer experiences.
Hang , a business-to-business (B2B) startup, aligns with the research firm. Currently, it is focused on using NFTs to redefine loyalty programs for clients like Budweiser, Bleacher Report and Superfly.
As previously mentioned, some brands may leverage the artificial universe to elevate employee engagement. Workplace collaboration can increase productivity, raise the problem-solving rate and reduces the workload. One way to keep the team happy is to integrate metaverse-driven technology in the office. Forester also anticipates that frequent encounters with such tools will build familiarity, leading to widespread adoption for personal use.
Last year, Microsoft announced Mesh, a Teams feature that blends existing modes “Together” and “Presenter” to make remote meetings more immersive. Google, Slack and Zoom are expected to roll out similar offerings in the next year.
On another side of the coin, security concerns about the metaverse deserve serious considerations. Given that data collection in the virtual world is automatic and steady, the odds of these assets being stolen are great. Additionally, aspects of the metaverse like blockchain, AR and VR, are considered likely targets for hacks. Therefore, data security should be accounted for in the yearly budget to help teams truly scale in the relatively digital future.
Beyond marketing, the metaverse needs direction Beyond its conceivable advantages and incredible market potential , it’s smart to question whether to invest in the fulfillment of a virtual realm. Despite a looming economic recession, corporations have sunk billions of dollars into this venture. However, spending on the cause isn’t enough; you need direction, too.
Partnering with trusted specialists in the industry gives companies access to proven techniques, as well as the guts to execute them. One of the outlets providing businesses with the much-needed focus on metaverse strategy is Invisible North.
Similar to what Hang is doing, New York-based Invisible North aided the emergence of an on-site NFT experience at the Coachella Valley Music and Arts Festival this year. This is one of its many projects.
Apart from collaborating with creative agencies for long-term metaverse projects, businesses should also set realistic goals and be open to consistent iterations. One of the downsides to experimenting with a simulated reality is that it’s evolving, meaning that nothing is certain and that frequent innovation is needed. Perhaps this is why organizations looking to assume leadership in the metaverse must now consider appointing a chief metaverse officer — someone who can effectively serve as the conductor in the metaverse’s royal orchestra.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"How Honeywell is bridging gaps in legacy OT, IT and industrial control systems for manufacturers | VentureBeat"
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"https://venturebeat.com/security/why-bridging-zero-trust-gaps-in-legacy-ot-and-it-systems-is-critical-for-manufacturers"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages How Honeywell is bridging gaps in legacy OT, IT and industrial control systems for manufacturers Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Bad actors target manufacturing, processing plants and utilities as open targets because the operational technology (OT) and IT integrations used do not provide the security needed to protect the core systems that run plants. By taking advantage of wide security gaps between IT, OT and industrial control systems (ICS) that weren’t designed for securing operations, bad actors seize the opportunity to launch ransomware attacks.
Sometimes even large-scale attacks, including those on Colonial Pipeline and JBS Foods , which illustrate the vulnerability of plants, utilities and systems, are the result of IT and OT systems’ security gaps that bad actors tend to exploit.
IT/OT gaps lead to security breaches Processing plants, utilities, manufacturers and supply chains that rely on IT and OT systems have tech stacks designed for speed, efficiency and shop floor control. Unfortunately, ICS, IT, OT and legacy enterprise resource planning (ERP) systems are not typically designed with security as a primary goal. As a result, the tech stacks built on these systems have wide IT/OT security gaps where implicit trust leaves them vulnerable to attacks.
Eighty-six percent of process and discrete manufacturers report having limited visibility into their ICS environments, making them an open target for cyberattacks. At the system level, a typical ICS is difficult to retrofit and enable more robust tools like zero-trust network access (ZTNA) at the application level. As a result, these systems become targets for bad actors who can scan IT and OT infrastructure and tech stacks and find open services, IP addresses and other endpoints that are entirely unprotected. This is such a problem that the U.S.
Cybersecurity and Infrastructure Security Agency (CISA) issued an alert earlier this year warning of such attacks targeting ICS and SCADA devices.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! A recent survey by the SANS Institute , in collaboration with Nozomi Networks , found that the most prominent challenge organizations report with securing OT technologies and processes is integrating legacy and aging OT technology with modern IT systems.
“With the evolution of new attack frameworks, legacy devices, evolving technology options and resource constraints, the biggest challenge with securing control systems technologies and processes is the technical integration of legacy and aging ICS/OT technology with modern IT systems,” the survey’s authors write. “Facilities are confronted with the fact that traditional IT security technologies are not designed for control systems and cause disruption in ICS/OT environments, and they need direction on prioritizing ICS-specific controls to protect their priority assets.” Fifty-four percent said it is the greatest challenge they face in securing their operations today, followed by traditional IT security technologies not being designed for control systems and causing disruption in OT environments. Additionally, 39% of the respondents say ransomware is the most significant concern regarding attacks on their ICS- and OT-based infrastructure.
The SANS study also points out that several ICS facilities fell victim to the Ekans ICS-tailored ransomware. Notable companies, including Honda and multinational energy company Enel Group, where the adversary group demanded $14 million in ransom for the decryption key and to prevent the attackers from releasing terabytes of stolen data.
Honeywell helps close gaps with zero trust Getting zero trust right across manufacturing and processing plants and utilities optimized for OT and ICS systems is a challenge because, unlike traditional IT stacks and network infrastructure that have endpoints with an OS or firmware installed, OT and ICS-based systems rely on programmable logic controllers (PLCs) to monitor plant and machinery process performance.
Infrastructure operators that keep water treatment, electrical utilities and process manufacturing plants running rely on supervisory control and data acquisition (SCADA) systems that are designed for monitoring, not security. Defending the availability, reliability and safety of their industrial control systems and operations can become more challenging as new processes are added to an existing plant.
Upwards of 85 vendors are vying to provide zero-trust capabilities to processing plants and utilities by offering endpoint detection and response (EDR), managed services, and cloud-based platforms for running entire processing operations. One player in the space, Honeywell, differentiates itself by how much data it can capture across diverse networks and interpret it in real time to avert intrusions and breaches.
“Honeywell was the organization that had cybersecurity experts who were able to reach our target. With our OT DCS engineers, their mentality, and existing collaboration with Honeywell engineers, we had a solid foundation to build on,” Ioannis Minoyiannis, head of automation at Motor Oil , said on Honeywell’s website.
Earlier this month, at the company’s Honeywell Connect 22 event, it introduced two advances in its cybersecurity solutions aimed at helping processing plants and utilities progress on ZTNA framework initiatives. Additionally, its Advanced Monitoring and Incident Response (AMIR) managed cybersecurity service added dashboard visibility.
Providing greater visibility and control over threat detection, security monitoring, alerting and incident response based on security information and event management (SIEM) and security orchestration and automation and response (SOAR) capabilities, Honeywell helps process manufacturers and utilities build out ZTNA frameworks.
By identifying and responding to threats faster with early threat detection, threat hunting, remediation and incident response, AMIR managed services helps manufacturers make progress on their ZTNA initiatives. Additionally, threat notifications and guidance help harden endpoints and give any organization insight into how best to segment networks in the future while enforcing least-privileged access.
Honeywell’s AMIR managed service is a step in the direction of treating every identity and endpoint as a new security perimeter for a processing plant, manufacturer or utility.
Honeywell’s service is for all ICS assets, regardless of manufacturer Keeping the design criteria for ZTNA frameworks as defined by NIST standards, Honeywell’s AMIR managed service is vendor-neutral, supporting both Honeywell and non-Honeywell assets on an ICS network. The AMIR managed service is designed to help mitigate complex OT security incidents, threats and cyberattacks through incident response support provided by Honeywell’s security professionals.
Information and updates are also provided via automated and immediate custom alerts and routine trend reports. In addition, the company designed the enterprise dashboard to provide customers with support 24/7.
“AMIR helps fill a major security gap that many industrial customers currently face: the inability to monitor OT environments 24/7 and proactively detect and respond to evolving threats,” said Jeff Zindel, vice president and general manager of Honeywell cybersecurity. “The addition of an AMIR dashboard offers customers enhanced visibility to know the status of identified incidents and the steps being taken by Honeywell OT cyber professionals to help respond to active threats.” Cyber App Control, previously known as Application Whitelisting, was also introduced, with vendor-agnostic support for both Honeywell and non-Honeywell control systems. It is designed to provide an additional security layer that ensures only known and trusted applications can run on ICS assets. The National Institute of Standards and Technology (NIST) considers Cyber App Control essential for OT security.
Cyber App Control uses the latest software release from security specialist VMware Carbon Black, with special rules and configurations crafted specifically for OT environments, developed by Honeywell’s OT Cybersecurity Centers of Excellence and Innovation.
Prioritizing ZTNA for the future Bad actors will continue to prioritize the softest targets that deliver the largest ransomware payments, beginning with processing and utility plants that are core to supply chains. Locking up a supply chain with ransomware is the payout multiplier that attackers want because manufacturers often pay up to keep their businesses operating.
Any business that integrates OT, IT and ICS systems may want to examine the benefits of pursuing a ZTNA-based framework to secure its infrastructure. Implementing a ZTNA framework doesn’t have to be expensive or require an entire staff. Gartner’s 2022 Market Guide for Zero Trust Network Access is one reference that can define guardrails for any ZTNA framework. With every identity a new security perimeter, manufacturers must prioritize ZTNA going into 2023.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Using PAM to secure digital identities, SPHERE announces $31M in funding | VentureBeat"
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"https://venturebeat.com/security/pam-sphere-funding"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Using PAM to secure digital identities, SPHERE announces $31M in funding Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
The adoption of cloud computing in hybrid and remote working environments have changed the attack surface forever. Now security teams not only have to protect on-premises networks, but also user and machine identities with privileged access management (PAM) and identity access management ( IAM ) to control access to sensitive information.
In response to these challenges, more and more providers are aiming to provide a more efficient approach to managing privileged user accounts. One such vendor is identity-hygiene provider, SPHERE Technology Solutions (SPHERE), which announced raising $31 million in series B funding led by growth equity firm, Edison Partners.
The organization’s flagship solution, SPHEREboard, provides an end-to-end workflow for managing end-user and privileged account controls, across cloud and on-premises infrastructure.
SPHERE’s approach is designed to help mitigate excessive privileged user access and decrease the risk of data exposure.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Using IAM and identity hygiene to stop data breaches The funding comes as cybercriminals continue to target users’ online accounts, with 22% of adults in the U.S. reportedly falling victim to account takeover fraud.
With the global cost of a data breach reaching $4.35 million this year, organizations can’t afford to overlook the financial damage that unchecked access to privileged user accounts can cause.
As a result, it’s now business-critical for security teams to proactively manage user and machine identities to decrease the risk of data breaches.
“The goal of true identity hygiene is to ensure that the right people have access to the right information at all times, so an organization’s crown jewels are protected,” said Rita Gurevich, SPHERE CEO.
“In order to address their customers’ concerns, SPHERE provides enterprises with innovative, effective and reliable cyber hygiene solutions to keep their data secure and compliant with updated regulations,” Gurevich said.
SPHERE aims to help security teams automate the management of digital identities by evaluating access and data protection controls, and identifying high risk users, so that excessive access permissions can be revoked.
A look at the IAM market The vendor falls loosely within the global identity and access management market , which researchers valued at $12.3 billion in 2020 and anticipate will reach a value of $34.5 billion by 2028.
One of the organization’s main competitors is Varonis , which offers a data access governance solution called DataPrivilege that security teams can use to manage user access to data and applications. Last year, Varonis announced $390 million in total revenue.
Another competitor is Netwrix , which offers its own PAM solution that enables security teams to identify user accounts with privileged access. Netwrix’s solution can also generate on-demand accounts that are automatically deleted after use to provide employees with secure access to data.
Gurevich argues that SPHERE’s focus on creating an identity-hygiene workflow is what separates it from competitors.
“SPHEREboard is a true end-to-end workflow that is designed to fill the gaps that other products could not, as it empowers clients to manage data, systems and the access to them. Its methodology follows the pathway of data collection, organization, reporting, reviews and, finally and most importantly, remediation. This is what makes SPHEREboard innovative,” Gurevich said.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Not giving up the (encryption) keys to the kingdom: Fortanix now integrated with AWS | VentureBeat"
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"https://venturebeat.com/security/not-giving-up-the-encryption-keys-to-the-kingdom-fortanix-now-integrated-with-aws"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Not giving up the (encryption) keys to the kingdom: Fortanix now integrated with AWS Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
The biggest and strongest of doors can be opened by the smallest of keys — encryption keys included.
In other words: No matter how fortified and secure an organization is, it can be compromised by undue access to keys, said Shashi Kiran, CMO of Fortanix.
“Key management is therefore non-trivial,” he said.
If a bad actor gets a hold of them, organizations with sensitive data run the risk of data breaches and becoming subject to ransomware. They could also run afoul of regulatory agencies that invoke hefty penalties.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! But, “all this can be gracefully avoided by decoupling data storage from key storage and focusing on the key management lifecycle,” said Kiran.
To enable organizations this ability for AWS customers, Fortanix today announced that its Fortanix Data Security Manager is now integrated with AWS External Key Store. This will allow organizations that deal with regulated data to run workloads on AWS by segregating data on the platform from encryption keys, said Kiran.
“The key to the crown jewels will be inherently more secure,” he said.
Confidential computing: A sophisticated level of security Today, 81% of organizations are using multicloud infrastructures (or plan to do so soon). But this brings with it increased security risks: 45% of breaches occur in the cloud, and the average cost of a data breach is at an all-time high of $4.35 million.
This has fueled the expansion of the key management software market. In it, top players include Oracle Cloud Infrastructure Vault, Azure Key Vault, AWS Key Management Service, Egnyte and HashiCorp Vault. The market is expected to grow to $4.87 billion by 2028, representing a compound annual growth rate (CAGR) of nearly 29% from 2021.
And, the general confidential computing market — which Fortanix calls itself a pioneer of — is projected to grow at a whopping CAGR of 90% to 95%, reaching $54 billion in 2026.
The young, emerging method of confidential computing protects data “in use” by performing the computation in a hardware-based trusted execution environment (TEE). This makes it possible to keep data secure even when hackers get physical access to servers, and/or have root passwords, said Kiran.
He called it “such a sophisticated level of security,” which opens up many new use cases and helps derive much more data value. It is an underpinning to several data security use cases and is becoming increasingly strategic in the industry with cloud providers, ISVs and chip vendors supporting it.
“Confidential computing is a way to decouple security from your infrastructure,” said Kiran. “Even if your infrastructure is compromised, your data remains secure.” Avoiding security and compliance risk As Kiran noted, there are advanced cryptographic technologies and many controls in use, based on standards bodies such as the National Institute of Standards and Technology ( NIST ). Regulatory agencies are also requiring stringent compliance for data privacy with geolocation dependence with GDPR , Shrems-II and the California Consumer Protection Act (CCPA).
While encryption technologies can be highly successful in securing data — and public cloud providers like AWS have been doing it successfully — several compliance requirements warrant the use of a key store or key management entity that is outside the cloud provider, said Kiran.
A centralized, external key store allows users to maintain full custody of their keys. And, “this control includes defining where the keys reside, access and policy control,” said Kiran.
This functionality allows enterprises to move sensitive workloads to the cloud while fully satisfying their regulatory and compliance requirements.
“The status quo would be that the cloud provider does both,” said Kiran. “While technically feasible, this is increasingly viewed as a security and compliance risk that most CISOs and GRC leaders would do well to avoid.” Granular access control The Fortanix DSM integration with AWS External Key Store is built on Fortanix’s existing software-as-a- service (SaaS) offering. In addition to giving organizations full control of their encryption keys, it allows them to enforce granular access control across hybrid multicloud infrastructures and simplify workflows and audits with centralized key management.
As Kiran put it, the addressable market for the joint tool is “growing considerably.” Fortanix has seen several deployments with Google, and with AWS now committing to it, “we have no doubt that enterprise customers globally will benefit.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Meta fined by Irish Data Protection Commission for web scraping activity | VentureBeat"
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"https://venturebeat.com/security/meta-fined-by-irish-data-protection-commission-for-web-scraping-activity"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Meta fined by Irish Data Protection Commission for web scraping activity Share on Facebook Share on X Share on LinkedIn A woman looks at the Facebook logo on an iPad in this photo illustration.
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Yesterday, the Irish Data Protection Commission ( DPC ) fined Facebook parent company Meta €265 million ($274 million USD) for breaching article 25 of the General Data Protection Regulation (GDPR) after hackers leaked the personal details of up to 533 million users on an online hacking forum.
The hackers exploited data processing measures in Facebook’s contact importer feature (active between 25th May 2018 to September 2019) to conduct web scraping activities on public profiles and connect users’ profiles with email addresses.
In a statement released by a Meta spokesperson, the organization claims to have “made changes to our system during the time in question, including removing the ability to scrape our features in this way using phone numbers.” Liabilities of web scraping The news comes amid reports of a leak of the data of 500 million WhatsApp users, although WhatsApp has insisted that there is “no evidence of a data leak.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! It also comes shortly after the DPC fined Meta €405 million ($419 million USD) for violating the GDPR and failing to prevent children from using business accounts, which made email addresses and/or phone numbers public by default.
Meta’s latest fine stands out because it highlights the regulatory liabilities of failing to prevent web scraping of public data.
“The fine itself shows that GDPR continues to be a powerful regulation that has consequences for non-adherence, and as reported, the section in question points to fundamental design ethos, protection by design and default, for compliance — which in turn also means security,” said Jon France, CISO of ISC2 , “Privacy and security are a fundamental part of the development process, not a treatment to it.” France added that, “web scraping has long been a tactic used by many to get data from public websites, and the implications are that the design of websites needs to incorporate measures that protect from en masse scraping at scale, such as rate limiting, etc.” Why is web scraping so common? While web scraping is frowned upon, it actually is not illegal. Both market research firms and threat actors alike are free to harvest publicly available information on the internet.
This was recently highlighted within the U.S. Ninth Circuit Court of Appeals, which ruled in hiQ Labs, Inc. v. LinkedIn Corp, that LinkedIn can’t prevent hiQ Labs from scraping LinkedIN users’ publicly available data.
In this case, which dates back to 2017, LinkedIn argued that hiQ violated laws such as the Computer Fraud and Abuse Act (CFAA) and attempted to block the organization from scraping data from public LinkedIn profiles.
Circuit Judge Marsha Berzon argued, at the time , that “there is little evidence that LinkedIn users who choose to make their profiles public maintain an expectation of privacy with respect to the information that they post publicly, and it is doubtful that they do.” Mitigating regulatory risk It’s important to note that web scraping presents regulatory risks when it relates to “data that’s covered by privacy law,” explained Mike Parkin, senior technical engineer at Vulcan Cyber.
For this reason, organizations need to have a complete understanding of what information is publicly exposed. In practice, this comes down to reviewing all publicly available data exposed on their websites and completing a risk assessment to measure how this information could put user privacy at risk.
“If your website makes information available, people will find it whether you want them to or not,” Parkin said. “Web scraping tools will follow any link they can find and can harvest any data they encounter. This can be a problem even with mundane data.” Another way to tackle web scraping is to add greater protections at the API-level, creating an inventory of APIs and increasing visibility over them.
“To prevent malicious web scraping, site owners need visibility into every API endpoint and the data exposed,” said Scott Gerlach, cofounder and CSO at StackHawk.
“Testing web interfaces and APIs for vulnerabilities frequently and early on improves overall security posture and provides insight to act quickly if needed.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"How CISOs get multicloud security right with CIEM | VentureBeat"
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"https://venturebeat.com/security/how-cisos-get-multicloud-security-right-with-ciem"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages How CISOs get multicloud security right with CIEM Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
More CISOs will have to deliver revenue growth to protect their budgets and grow their careers in 2023 and beyond, and a core part of that will be getting multicloud security right. It’s the most common infrastructure strategy for rejuvenating legacy IT systems and clouds while driving new revenue models. As a result, multicloud is the most popular cloud infrastructure, with 89% of enterprises relying on it, according to Flexera’s 2022 State of the Cloud Report.
Organizations and the CISOs running them often decide to pursue a multicloud strategy based on the improved availability of resources and best-of-market innovations available, as it helps them meet compliance requirements more efficiently and gain greater bargaining parity during cloud provider negotiations. CISOs have told VentureBeat in previous interviews that multicloud is also an excellent way to avoid vendor lock-in. Large-scale enterprises also look to gain more excellent geographical coverage of their global operations.
The more multicloud proliferates, the greater the need to enforce least-privileged access across every cloud instance and platform. That’s one of the main reasons why CISOs need to pay attention to what’s happening with cloud infrastructure entitlement management (CIEM).
Defining CIEM Gartner defines CIEM as a software-as-a-service (SaaS) solution for managing cloud access by monitoring and controlling entitlements. It said CIEM uses “analytics, machine learning (ML), and other methods to detect anomalies in account entitlements, like accumulating privileges and dormant and unnecessary entitlements. CIEM ideally provides remediation and enforcement of least privilege approaches.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Multicloud is a major zero-trust challenge Every cloud hyperscaler has a unique approach to solving their platforms’ IAM, PAM, microsegmentation, multifactor authentication (MFA), single sign-on (SSO), and other main challenges their customers face in attempting to implement a zero-trust network access (ZTNA) framework on and across platforms.
Gartner predicts that inadequate management of identities, access and privileges will cause 75% of cloud security failures by 2023. The more complex a multicloud configuration, the more it becomes a minefield for zero-trust implementation. CISOs and their teams often rely on the Shared Responsibility Model in briefings and as a planning framework for defining who is responsible for which area of the multicloud tech stacks.
Many enterprises rely on the Amazon Web Services version because of its straightforward approach to defining IAM. With each hyperscaler providing security just for their platform and tech stacks, CISOs and their teams need to identify and validate the best possible IAM, PAM, microsegmentation, and multifactor authentication (MFA) apps and platforms that can traverse across each hyperscalers cloud platform.
“Existing cloud security tools don’t necessarily address specific aspects of cloud infrastructure,” Scott Fanning, senior director of product management and cloud security at CrowdStrike, told VentureBeat. “Identity isn’t necessarily buried into that DNA as well, and the cloud providers themselves have added so much granularity and sophistication in their controls,” he continued.
One of CIEM’s design goals is to help close the gaps between multiclouds by enforcing least-privileged access, removing any implicit trust of endpoints and human and machine identities. The goal is to eradicate implicit trust from multicloud infrastructure. That isn’t easy to do without an overarching governance platform, which is one of the reasons CIEM is gaining market momentum today.
The more complex a multicloud configuration, the more challenging it becomes for experienced staff to manage, with errors becoming more commonplace. As a result, CIEM advocates point to the need to automate scale governance and configuration monitoring to alleviate human errors.
Gartner predicts this year that 50% of enterprises will unknowingly and mistakenly expose some applications, network segments, storage, and APIs directly to the public, up from 25% in 2018. In addition, the research firm predicts that by 2023, 99% of cloud security failures will result from manual controls not being correctly configured.
Why CIEM’s importance is growing Getting in control of cloud access risk is what drives the CIEM market today. CISOs rely on risk-optimization scenarios to balance their budgets, and the value CIEM delivers makes it part of the budgeting mix. In addition, by providing time controls for the governance of entitlements in hybrid and multicloud IaaS environments, CIEM platforms can enforce least privilege at scale.
Leading CIEM vendors include Authomize, Britive, CrowdStrike, CyberArk, Ermetic, Microsoft (CloudKnox), SailPoint, Saviynt, SentinelOne (Attivo Networks), Sonrai Security, Zscaler and others.
Advanced CIEM platforms rely on machine learning (ML), predictive analytics, and pattern-matching technologies to identify anomalies in account entitlements, such as accounts accumulating privileges that have been dormant and have unnecessary permissions. From a zero-trust perspective, CIEM can enforce and remediate least-privileged access for any endpoint, human or machine identity.
Fanning said CrowdStrike’s approach to CIEM enables enterprises to prevent identity-based threats from turning into breaches because of improperly configured cloud entitlements across public cloud service providers. He told VentureBeat that one of the key design goals is to enforce least-privileged access to clouds and provide continuous detection and remediation of identity threats.
“We’re having more discussions about identity governance and identity deployment in boardrooms,” he told VentureBeat during a recent interview.
Five reasons why CIEM will continue to gain adoption CISOs pursuing a ZTNA strategy are out for quick wins, especially with budgets on the line today. CIEM is showing that it has the potential to deliver measurable results in five key areas.
Predicting and preventing identity-based threats across hybrid and multicloud environments delivers measurable results that are being used to quantify risk reduction.
CIEM is also proving effective at visualizing, investigating and securing all cloud identities and entitlements.
CISOs tell VentureBeat that CIEM is simplifying privileged-access management and policy enforcement at scale.
CIEM makes it possible to perform one-click remediation testing before deployment on the most advanced platforms.
CIEM can integrate and remediate fast enough to not slow devops down.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"How penetration testing bolsters API security | VentureBeat"
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"https://venturebeat.com/security/api-security-testing"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages How penetration testing bolsters API security Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Last year, Gartner predicted that API attacks would become the most-frequent attack vector in 2022. While it remains unclear whether this is the case, when considering that the exploitation of Twitter’s API vulnerability exposed the data of 5.4 million users, it’s clear they’re devastatingly effective.
In an attempt to help security teams address these threats, today, cybersecurity startup Wib announced the launch of what it claims is the industry’s first API PenTesting-as-a-service (PTaaS), which is designed to test for application security, API, and business logic vulnerabilities.
Wib recently announced raising $16 million in funding and enables users to generate a complete inventory of APIs, generate documentation, and enhance visibility over the attack surface.
In this instance, penetration testing provides security teams with a more accurate view of their organization’s API security posture so they can identify and mitigate potential entry points before cybercriminals can exploit them.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Playing catchup with API security The announcement comes as attacks on APIs continue to increase, with research showing that 94% of organizations have experienced security problems in production APIs.
To make matters worse, many security teams are in the dark about how to respond to these threats, with 61% lacking any API security strategy or having only a basic plan.
The truth is that many organizations are playing catchup with API security after embracing cloud computing and microservices.
“Most of these blind spots are exposed as firms embrace an API-first methodology and shift to a microservice-based architecture, which changes their attack surfaces, but their defenses weren’t designed for this structure and have not yet evolved to cover it,” said Chuck Herrin, CTO of Wib. “Adoption always outpaces security, and this time is no different. What is different this time is that API traffic is already 91% of web traffic, while most defenders are blind to APIs as an attack vector,” Herrin said.
By offering a purpose-built penetration testing service, Wib provides organizations with access to the expertise and technologies they need to detect API-level threats.
After each test, security teams receive a full assessment report of identified vulnerabilities alongside a risk severity score based on NIST’s cyber matrix calculator and a remediation road map plan with recommendations on how to mitigate vulnerabilities.
Reviewing the API security market Wib is just one of many providers in the global API security market , which researchers valued at $783.9 million in 2021 and anticipate will reach a value of $984.1 million in 2022.
The organization is competing against a range of competitors in the market including Salt Security , which raised $140 million in series D funding earlier this year, and offers an artificial intelligence (AI) and machine learning (ML)-driven platform for inventorying APIs and exposed data with OAS analysis capabilities.
Another significant competitor is NoName Security , an API security platform that identifies vulnerabilities and misconfigurations while providing security teams with automated detection and response capabilities. NoName Security most recently raised $135 million as part of a series C funding round in December 2021.
However, Herrin argues that WIB’s versatile penetration testing approach and lack of reliance on API traffic to spot threats is what differentiates it from these existing tools.
“Both of these “unicorns” focus on a production traffic-based view, which is a useful lens, but is insufficient to find blind spots like zombie APIs (APIs exposed but with no normal traffic) or APIS that don’t communicate across expected traffic paths,” Herrin said.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
All rights reserved.
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"Modern software development calls for automated API security | VentureBeat"
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"https://venturebeat.com/security/api-security-pangea"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Modern software development calls for automated API security Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
API security is something few organizations are getting right. In fact, research shows that 76% of organizations have had an API security incident in the past year.
Part of the problem is that developers often don’t have the time, expertise or technologies necessary to secure APIs at a sustainable pace for modern software development.
API security provider Pangea Cyber , which today announced it has raised $26 million in series B funding, is aiming to address this challenge with an API plug-and-play service that enables developers to embed security capabilities and APIs into their applications without developing custom code.
The idea is to make API security scalable and accessible to developers so they can plug in the necessary protections to mitigate risks to protected data.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Automating API security The announcement comes as API security incidents continue to plague developers, with 94% of organizations citing that they have experienced security problems in production APIs in the past year.
While there are many reasons for these gaps, lack of expertise is one of the biggest factors.
“Development teams simply lack the expertise to add security capabilities into their applications,” said Oliver Freidrichs, founder and CEO at Pangea. “With up to one million software companies anticipated by 2027 (according to Forrester ), it’s essential that the applications they build have access to a trustworthy framework of security functions. This new funding will help us to realize and accelerate that vision.” Pangea Cybe’s approach is designed to enable users to embed security features within apps so they can ship secure products and accelerate the overall time to market.
Protections are available for users to add on to the service including the ability to log security events, manage export restrictions, manage personally identifiable information ( PII ), identify malicious files, and block users from high-risk domains.
A look at the provider’s securing APIs Pangea Cyber’s solution fits within the API security market , which researchers estimate will grow 26.3% annually between 2022 and 2032 to reach a value of $10,185.4 million.
The vendor is competing against a range of established providers including Salt Security , which uses artificial intelligence (AI) and machine learning to discover APIs and exposed data throughout an organization’s environment, as well as testing during production. Earlier this year, Salt Security announced raising $140 million in series D funding.
Another key competitor in the market is the API security platform, Noname Security , which offers organizations the ability to create an inventory of APIs and implement real-time detection and response capabilities to identify vulnerabilities and misconfigurations in APIs. The solution also offers the ability to test APIs before production. Noname Security most recently raised $135 million in series C funding and achieved a $1 billion valuation in December 2021.
The main difference between Pangea Cyber and its competitors is the company’s plug-in-and-play approach, opting to provide developers with a Security Platform-as-a-service (SPaaS) framework to give developers a simple and repeatable way to add security functions to their applications via API calls.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
All rights reserved.
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"31 CISOs share their security priorities and predictions for 2023 | VentureBeat"
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"https://venturebeat.com/security/31-cisos-share-their-security-priorities-and-predictions-for-2023"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages 31 CISOs share their security priorities and predictions for 2023 Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
2022 was a pivotal year in the cyberthreat landscape. With the Russia-Ukraine war emboldening nation-state hackers and professional cybercriminals alike, organizations are under increasing pressure to optimize their security operations just to keep up.
Securing the software supply chain and the open-source software ecosystem, implementing zero trust, and educating employees about the risks of social engineering and phishing attempts are just some of the areas that CISOs are evaluating to mitigate potential risks.
VentureBeat recently asked CISOs from some of the top global organizations to outline their security priorities and predictions for 2023. Below are their responses (edited for length and style): Phil Venables, Google Cloud Malicious behavior will get worse before it gets better — and investments in technological infrastructure will rise in response.
Federal emphasis on protecting national technical infrastructure against malicious activity will grow in 2023. In the year ahead, I expect to see the Biden Administration implement a consistent stream of policies following the 2021 Executive Order on Improving the Nation’s Cybersecurity and the 2022 National Security Memorandum.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! While public/private sector collaboration has recently grown, there must be deeper coordination between agencies and Big Tech organizations. It is reasonable to expect that the government may implement more safeguarded checkpoints between agencies and Big Tech organizations.
It is reasonable to expect that the government may implement more safeguarded checkpoints for organizations to reflect on their progress for meeting regulatory requirements. As these are implemented, we can expect to see increased knowledge-sharing between public and private organizations, heightening transparency and protection around today’s biggest threats.
Malicious behavior will get worse before it gets better — and investments in technological infrastructure will rise in response. The increased malicious activity we saw in 2022 is no surprise — and will only continue to grow in 2023. My outlook long-term is optimistic, but short-term pessimistic, and I expect organizational approaches in the coming year to continue to be more cautious, especially as public and private organizations are still figuring out how to contain the growing number of cyberthreats.
In 2023, we can expect to see increased investment in IT modernization, especially as malicious activity continues to rise in sophistication. With a modernized IT environment, security will become a “built-in” element of infrastructures instead of an “add-on,” so even with short-term challenges, the long-term benefits of IT modernization are paramount and key to mitigating evolving cyberthreats.
CJ Moses, AWS … security starts not only with using the best security tooling, but also building a culture of security.
AWS builds security services by working backward from customer problems, and we see a common thread among our customers — that security starts not only with using the best security tooling, but also building a culture of security.
Looking to 2023, AWS will continue innovating new services that solve customer problems and also help our customers prioritize building a security-first mindset based on what we’ve learned: Educating everyone about security — no matter their role or job title — is critical to operating securely. This includes everyone from software developers to customer representatives to the C-suite.
Sharing a common language to talk about security means proactively educating everyone on security best practices, expectations and risks. When people are educated on security, they are empowered to make better decisions that result in positive security outcomes and better customer experiences.
Education is just the beginning.
Building a security-first culture aligns knowledge with behaviors. In a security-first culture, developers think about securing before writing a line of code. Product managers think about security before architecting a new product or service. And C-suite decision-makers think about how security risks can impact the bottom line. Most importantly, a security-first culture enables all of them to think about how crucial security is for their customer experiences and why proper investment in security is business critical.
Attracting the best talent from diverse backgrounds and developing security leaders reinforces a security-first culture. Employees today expect companies to provide clear career paths, upskilling opportunities and leadership development.
Advancing talent through mentorship, apprenticeship programs and certification opportunities builds an inclusive and collaborative environment that improves businesses and provides more value to customers.
Making security in the builder experience as frictionless as possible maximizes the value of teams. Shifting left — embedding security as early as possible in the product development life cycle — leads to a better builder experience and more secure outcomes.
Automating as much as possible also helps builders focus on solving high-value problems for customers. Technologies like automated reasoning and machine learning not only save time for builders, but can also quickly surface unknown security risks to help organizations better protect their infrastructure, applications and customers.
Invest in a dynamic workforce.
The past two years have shown us that people want flexibility and choice in where they work. Securing the tools and environments employees use to work — no matter where they are located — helps keep organizations safe. But just like the builder experience, securing for all employees should be easy, frictionless and as automated as possible.
Together, these priorities can help organizations improve their security posture by focusing on people and the culture within their teams. Using the best security tooling helps build a foundation for secure operations.
But raising the bar on securing means building pillars on that foundation where security-minded people are empowered and can operate in a culture where security comes first in everything they do through education, professional development, and making security as easy as possible for everyone.
Bret Arsenault, Microsoft …if you’re playing catchup, you’re leaving yourself vulnerable to attackers.
As security professionals, it’s not enough to forecast what’s coming in 2023. We need to look five to 10 years down the road and prepare for these threats, because if you’re playing catchup, you’re leaving yourself vulnerable to attackers.
At Microsoft, we had to see the cloud coming and plan for it way before we were ready to migrate. We had to see passwords fail and plan for it. And now we have to anticipate the ways MFA might be vulnerable and plan for those. You have to think like a hacker.
Koos Lodewijkx, IBM The events of the past two years [have been] a stark reminder of how much our security depends on the security of others — supply chains, partners, open source.
As we prepare for 2023, my teams — and other CISOs I talk to — are focused on adapting to the developing threat landscape, as ransomware and disruptive attacks on enterprises and critical infrastructure are multiplying and not letting up anytime soon.
With the attack surface becoming exponentially more complex and dispersed, it’s even more important to focus on attack surface management to find and fix high-priority vulnerabilities, as well as threat detection and response within enterprise environments — finding and stopping attackers quickly, before they can achieve their objectives.
The events of the past two years have also been a stark reminder of how much our security depends on the security of others — supply chains, partners, open source. This remains an important area of focus.
Looking forward, we’re on the precipice of some very novel AI [ artificial intelligence ] innovations which hold huge potential in the cyberdefense space. We’re working closely with our colleagues within IBM Research and IBM Security to explore completely novel AI use-cases which go well beyond those being put into practice today.
Mandy Andress, Elastic “…a key priority … will be to better understand [an] organization’s vulnerability at the intersection between the technical aspects of their security postures and the human ones.” Given recent and past cyberattacks like we’ve seen with SolarWinds, Okta and others, a key priority for security teams will be to better understand their organization’s vulnerability at the intersection between the technical aspects of their security postures and the human ones. Both present vulnerabilities and malicious actors increasingly focus on exploiting the inflection points where technology and people intersect.
To address any technical weak points, I believe more organizations will need to start developing security in the open, which enables security practitioners to see the underlying code of a product and understand how it works in their environment. This will help security teams identify potential blind spots and address gaps in their security technology stack while developing risk profiles for new and emerging threats.
The human aspect of security is slightly more nuanced because it is less predictable. Certain factors like the pandemic and remote work environments have led to people connecting to and interacting with technology more than ever before, but this doesn’t necessarily make them more security-aware.
John McClurg, BlackBerry … adopting a prevention-first approach to cybersecurity is ultimately one of the best ways businesses can guard against malicious actors ….
Producing a software bill of materials (SBOM) will be top of mind for companies providing software to the U.S. government in accordance with President Biden’s Executive Order 14028, as they manage the details and navigate the implications of these new requirements.” Highly visible attacks on the software supply chain start with access to the weakest link. As we head into a new year, it’s important to engage businesses of all sizes to be engaged as new secure software development practices are defined.
Leaders in the security space will also be focused on closing their cybersecurity skills shortage.
In the face of a talent pipeline in desperate need of a turbocharge, adopting a prevention-first approach to cybersecurity is ultimately one of the best ways businesses can guard against malicious actors as we continue to see a growing gap between threats faced and front-line security workers available to handle them.
Niall Browne, Palo Alto Networks It’s paramount to ensure that not only your own organization’s software supply chain is secure, but also [those of] the companies you do business with.
Over the last few years, we’ve seen every organization become a digital business. This significant increase in organizations’ digital presence unsurprisingly has led to bad actors taking advantage of insecure software supply chains.
The Log4j attack showed us just how detrimental these attacks can be, where a vulnerable codebase can impact thousands of companies. These types of attacks will not go away and will increase exponentially over the coming years.
Gartner predicts that “by 2025, 45% of organizations worldwide will have experienced attacks on their software supply chains, a three-fold increase from 2021.” It’s paramount to ensure that not only your own organization’s software supply chain is secure, but also [those of] the companies you do business with. A top priority for every CISO needs to include proper security of every codebase, application and third party the organization uses.
Kevin Cross, Dell Technologies We must execute the basics with brilliance because threat actors commonly use these weaknesses to enter, navigate and compromise environments.
When looking at 2023, my priorities are not necessarily focused on the newest trends of the day, but continuing to get cybersecurity fundamentals right. We must execute the basics with brilliance because threat actors commonly use these weaknesses to enter, navigate and compromise environments.
If fundamental processes are not sound, then those will be the first to fail. We’re continuously making sure our basic blocking and tackling is working so we are best positioned to stay ahead of evolving threats.
For many companies, mastering the fundamentals is hindered by the industry gap in cybersecurity talent. There are fewer people in the available workforce pool with the right cybersecurity skills needed to protect, detect, respond to and recover from cyberthreats. That’s why it’s important to uplift my team and provide continuous training and education, while supporting their career paths and interests.
Adam Marré, Arctic Wolf Whether it’s teams on the vendor side or in-house experts, having the right team in play should be a priority for all companies.
As cyberattacks continue to affect organizations everywhere, leaders should continue investing in cybersecurity talent and focus on cybersecurity fundamentals. Although there are new and exciting technologies that are aimed at solving different attack vectors, focusing on successfully executing the fundamentals of cybersecurity remains the most effective strategy.
The Verizon Data Breach Investigations Report and other security incident-reporting have shown that most successful attacks involve the use of credentials or exploiting a software vulnerability that already has a security patch available. This means that most organizations are still not executing on the fundamentals of secure credential handling and patch/vulnerability management.
To ensure these essential activities are being done, it takes hardworking team members to focus on security. Whether it’s teams on the vendor side or in-house experts, having the right team in play should be a priority for all companies.
Anne Marie Zettlemoyer, CyCognito Like most companies, we have to maximize security resources and investments; so shifting left in our security and building secure products up front is important.
As a tech company we are faced with the important responsibility of ensuring that what we build and how we build is safe for our company and for the customers we service. We pride ourselves on the trust our customers place in us and work hard to build security into everything we do.
Like most companies, we have to maximize security resources and investments; so shifting left in our security and building secure products up front is important. Doing so lets us find weaknesses early and allows for quicker, more efficient remediation, thereby reducing MTTR and driving down costs.
We leverage our expertise in security and engineering to build tools that are safe, trustworthy and reliable; and we utilize our own platform to ensure that not only do we have a great understanding of our own dynamic attack surface ; but that we are regularly and reliability testing our apps, machines and cloud instances in order to manage risk in a proactive way and stay ahead of attackers.
Josh Yavor, Tessian “Attackers don’t respect work-life boundaries ….” In 2023, CISOs need to focus on how they can defend and protect employees beyond the walls of corporate systems. More and more, we’re seeing attackers target employees in social engineering scams that originate on their personal networks — through LinkedIn, SMS text or their personal email account — with the ultimate goal of compromising the workplace.
For example, if an employee’s laptop is compromised, the attacker can often gain access to the personal email of the employee to then attempt to social engineer their employer’s IT team into giving them access.
Attackers don’t respect work-life boundaries, so we need to continue investing in security programs that support and enable our employees in their personal lives while still maintaining the right balance and boundaries.
It’s clear that security needs to extend outside of corporate walls, but there’s an important balance that CISOs and security leaders need to strike. How do we support employees not just at work but in their personal lives, while still respecting boundaries with their personal devices and accounts? How do you address that there will always be employee devices that you don’t own and control? Jason Clark, Netskope Security’s greatest enemy is complexity.
Nearly every CISO that I’ve had a conversation with lately has had the same top-of-mind priority: the simplification of security operations. They are being forced to simplify security, as budgets consolidate and the tech stack becomes too complex for long-term sustainability. Here are a few areas I recommend evaluating first: Security’s greatest enemy is complexity. Therefore, the first area to focus on is the simplification of processes. In many cases, there are too many security controls in place without thinking about the resulting friction it puts on the business at large. By simplifying processes, you also eliminate a few of the unnecessary controls.
Jonathan Rau, Lightspin Push-based MFA … has shown to be a weak implementation of MFA … due to social engineering attacks.
Push-based MFA was seen as the anodyne to lessen the user experience burden when it came to using vaults, a variety of software and hardware authenticator apps with TOTP. However, it has shown to be a weak implementation of MFA much as SMS has become due to social engineering attacks.
For 2023, investment and in-depth analysis of how and where MFA is implemented needs to be undertaken primarily to implement MFA that presents a challenge, captures log details and has risk-based policy controls to prevent MFA spam attacks from holding.
Jeff Costlow, ExtraHop Nation-state actors will escalate their attempts at credential stuffing.
Usernames and passwords for personal social media accounts continue to make up a large portion of breached data dumps. 2023 will see a rise in more targeted account-takeover attempts with these leaked credentials, including corporate accounts.
We noticed an uptick in unauthorized access attempts and trolling on our own corporate accounts when we shared resources related to CISA’s Shields Up guidance. I think this targeting of accounts sharing guidance for organizations around geopolitical cyber events will increase into 2023.
Andrew Obadiaru, Cobalt Almost every organization collects and stores clients’ sensitive data, and the safety and protection of that data must remain a key priority for 2023.
With ransomware still the number one threat to the safety of company data, CISOs should prioritize enhancing security monitoring capabilities and building up defenses.
Another priority is security analytics. Traditional, rule-based security information and event management (SIEM) is no longer sufficient given the scale and speed of real-time threats. Preparing for 2023, CISOs should integrate data analytics into security monitoring and alert analysis.
The lingering questions of, “Have we done all that we can to protect ourselves and our customers, and are there additional measures we can adopt?” really keeps me up at night. The truth is, we have implemented a number of security measures and we will continue to evaluate these measures for adequacy.
Mike Beck, Darktrace … CISOs are going to be faced with several difficult choices around how they build an effective security program given increasing budget constraints.
Each year, cyberattackers innovate to increase their capability and capacity to conduct attacks.
With cybercriminals incentivized by monetary gain and nation-states driven by geopolitical tensions and the possibility for intelligence gathering and causing major disruption for adversaries, the attack surface faced by organizations globally continues to widen. The CISOs of global businesses must contend with this backdrop in every cybersecurity decision.
In an inflationary environment with global economic slowdowns, CISOs are going to be faced with several difficult choices around how they build an effective security program given increasing budget constraints.
Many will be unable to invest in large security teams capable of manually operating security functions and will have to look to AI as a force multiplier. Obtaining comprehensive AI-powered security solutions, incorporating outsourced services that are additive to the cybersecurity program, and retaining key security talent will be primary objectives for the CISO in 2023.
Bernard Brantley, Corelight My top priority in the coming year is reinforcing shared security through the human element.
As we approach 2023, I believe that our current method of addressing the evolving threat landscape with a controls-centric focus remains inefficient and that we must find or make a way to develop the security acumen of our most critical asset: the humans (people network) in our organizations.
The security organization maintains numerous technology-centric functions to identify structural weakness and protect the organization, while providing support to the people-centric functions of detection, response and recovery associated with adversarial impact.
Ryan Kazanciyan, Wiz … organizations will struggle with in-house and vendor systems that provide inconsistent or incomplete support for these mechanisms.
Deploying phishing-resistant multifactor authentication at scale –- and managing the inevitable gaps: Incidents throughout 2022 have underscored the need to move away from SMS, TOTP and push-based multifactor authentication (MFA).
Phishing-resistant FIDO2 Web Authentication (WebAuthn) is more accessible than ever — with hardware tokens, built-in hardware like TouchID and Windows Hello, and the recent release of PassKeys –- but organizations will struggle with in-house and vendor systems that provide inconsistent or incomplete support for these mechanisms.
The long tail of incompatible systems will force many organizations to continue supporting pockets of their environment with insecure MFA methods for many years to come.
Michael Oberlaender, GoTo Organizations will struggle with in-house and vendor systems that provide inconsistent or incomplete support for these mechanisms.
GoTo is dedicated to monitoring and continuously improving our security, technical, and organizational measures to protect our customers’ sensitive information.
In addition to our SOC and SOC 3 compliance, we’re executing a security-by-design approach working on administrative safeguards, least privileges and identity access management ( IAM ), enhanced multifactor authentication (MFA), zero trust , asset management and automated capabilities, which also will continue to be a priority in the year ahead.
With the average cost of data breaches [at] an all-time high, businesses need to take every precaution to protect themselves from outside attack or malicious users, and a security-by-design model is an effective way to leave no doubt.
Sounil Yu, JupiterOne … we are on a diet of poisoned fruit with respect to our software supply chain.
We have recently seen several high-profile attacks that have exploited MFA implementations that remain susceptible to social engineering. MFA is not a panacea, particularly if users can still be tricked into giving up the MFA token to an attacker.
In 2023, we should see efforts to make users aware of these attacks and improvements in MFA implementations to make them more phishing resistant.
To borrow Richard Danzig’s analogy, we are on a diet of poisoned fruit with respect to our software supply chain.
This poison is not going to go away, so we will need to learn how to survive and thrive under these conditions.
Being aware of the risks (through efforts such as SBOMs) and managing the risks (through compensating controls such as egress filtering) will be a priority in 2023 and the foreseeable future.
Rick Holland, Digital Shadows CISOs should understand the company’s strategic objectives for next year and look for ways to minimize risk and enable business initiatives.
It is the 2023 planning season, and much of the focus has been on which security tools CISOs should invest in next year. Instead of prioritizing security tooling, CISOs should prioritize alignment to 2023 business objectives.
What does the business plan to do next year? Is the company going to release a new product that will generate significant revenue needed to achieve revenue goals? Is the company going to expand into a new geography? CISOs should understand the company’s strategic objectives for next year and look for ways to minimize risk and enable business initiatives. Business risks should also drive the CISO’s 2023 priorities. SEC Form 10-Ks are excellent resources that outline the key risks to the business.
Chris Morales, Netenrich … we can continually score threat likelihood and business impact to make informed decisions on where to best focus resources.
I have one priority for 2023 — to be data-driven for risk-making decisions. My commitment starting fiscal year 2023 is to be data-driven with quantitative risk-management practices.
That means providing the business units with a dashboard and trending metrics to the state of assets, vulnerabilities and threats that comprise their attack surface.
From this, we can continually score threat likelihood and business impact to make informed decisions on where to best focus resources.
Making this happen requires a tightly integrated security stack that shares data into a single aggregated data lake to threat model and answer questions.
To paraphrase in buzzwords/market lingo: Cyber risk quantification Attack-surface management Security analytics Cybersecurity mesh architecture John Burger, ReliaQuest In 2023, I want to improve our quantification capabilities so we can demonstrate to leadership the continuum between risk and dollars.
Risk quantification is my main priority for 2023 because it’s essential to securing funding on all my security initiatives. And as most CISOs are acutely aware, new security spend isn’t easy to come by.
In order to fund anything, CISOs must be able to quantify the potential risk in dollars. While it’s often more achievable to quantify the material impact of losing an application for a day, or even a ransomware attack , it’s much harder to quantify the probability of that impact occurring.
In 2023, I want to improve our quantification capabilities so we can demonstrate to leadership the continuum between risk and dollars. For example, if you accept this amount of risk, it costs this amount. If you’re willing to accept more risk, you pay less. Risk quantification has the potential to advance the clarity in our communication with the business.
Ryan Davis, NS1 For too long, security has existed in a silo, and seen as an afterthought and a cost center.
CISOs will be looking for ways to bolster the security department’s impact in an unsteady economic climate, without substantial additional cost or investment. One tangible element of that is developing partnerships within the organization.
When CISOs and security teams are able to spearhead partnerships with other departments, it can reduce the overall cost of securing the organization — whether working with HR on company-wide security awareness efforts, training development teams in security, or partnering with marketing to make security a business differentiator.
Krishna Athur, Nile CISOs must advance efforts to achieve zero trust in their security protocols.
Cybersecurity approaches will become tomorrow’s law: CISOs must actively engage with state and federal officials to educate policymakers and lawmakers on business and data security requirements to positively impact the way new regulations are written.
More importantly, as different states are moving at varied paces and approaches, CISOs should focus on advocating that federal officials step in to create a national standard for data privacy and protection.
CISOs must advance efforts to achieve zero trust in their security protocols. CISOs must seek solutions and vendors that can help them advance zero trust from a goal that is hard to achieve, to a security standard that is an operating prerogative.
Marc Woolward, vArmour I’m focused on helping my customers understand their IT supply chain from the inside-out … In 2023, one of my top priorities is addressing cybersecurity and operational risk in the software supply chain, especially as regulators continue to enact guidance about protecting critical business functions and confidential data in this area. From PyPI to Lapsus$ , attackers are taking full advantage of the vulnerabilities in third-party applications, and the fact that businesses can’t stop them.
I’m focused on helping my customers understand their IT supply chain from the inside-out — whether it’s their applications, their data flows, their code or their people — and put dynamic policies in place to control it.
It’s only through that inside-out view of the supply chain (via observability technology and a Software Bill of Materials) that we can fully assess enterprise risk and the context surrounding it, choose what security strategies to prioritize, and then close the everyday vulnerabilities in enterprise software that attacks so easily take advantage of.
Nikolai Chernyy, SandboxAQ … we need to stay focused on maintaining a good attitude towards security and a positive culture where reporting suspicious activity is encouraged.
Sandbox grew from 20 employees to nearly 100 in 2022, and we expect to reach 200-300 in 2023. As the company grows, there is increased pressure to support more and more platforms while maintaining security discipline (e.g., continue to enforce SSO everywhere).
We don’t have a perimeter, the increased user and technology complexity leads to more scenarios that can stack up to allow threat actors to operate. Additional care must be taken to make sure the telemetry and altering scales with the infrastructure and security policies continue to be enforced.
Finally, as the organization size crosses Dunbar’s number, we need to stay focused on maintaining a good attitude towards security and a positive culture where reporting suspicious activity is encouraged.
Brian Spanswick, Cohesity … attackers are getting access to critical systems and sensitive data by exploiting basic vulnerabilities … Our priorities keep coming back to the cybersecurity fundamentals, with a focus on increasing coverage and effectiveness of core security controls. Looking at some of the most recent and impactful breaches, the attackers are getting access to critical systems and sensitive data by exploiting basic vulnerabilities that exist in the security posture.
A key priority that we are carrying over from FY ’22 is an ongoing focus on security awareness training and education on social engineering attacks for all our employees. This needs to be a campaign in order to build and sustain the muscle memory required to reduce the exposure.
Another priority is to continue to focus on credentials management that includes increasing RBAC, least-privileged access, and ensuring proper password management practices. Even with the progress made year-over-year, this is an area that requires constant management to ensure that changes to our environments maintain the targeted level of credentials management.
Mauricio Pegoraro, Azion … we expect CISOs to prioritize protection of code more than ever before.
The security of the software supply chain continues to plague organizations. We expect that supply chain attacks will become more complex, but we also expect to see sophisticated solutions developed to thwart those attacks.
With supply chain attacks on the rise, we expect that CISOs will invest more robustly in securing the software development life cycle and building up formalized patch management programs to maintain clean software libraries.
Open-source code is the lifeblood of software development innovation, so we expect CISOs to prioritize protection of code more than ever before.
Robb Reck, Red Canary Attackers are better than ever at finding their way into environments ….
The most important skill for a CISO is to know their company inside and out. This means knowing how technology and data are used to create value, and being involved with new projects early. This level of integration is not easy, and has no end date, so should be at the top of every CISO’s priority list for 2023.
That said, CISOs do have other priorities that will be important next year.
The pandemic has forever changed how employees look at their jobs. All bosses need to reevaluate the expectations they put on their employees. CISOs should be asking how much after-hours work they’re requiring from their team. This may be the time to reset those expectations, and potentially augment teams with external partners and additional hires.
Attackers are better than ever at finding their way into environments and leveraging that access for ransomware, intellectual property theft or other malevolent ends. Those companies who haven’t already done so are focused on implementing processes and technologies that will help them quickly detect and respond to attackers who make it through the company’s security controls.
Yogesh Badwe, Druva Time and again it’s proven that humans are the weakest link in the security chain.
In 2023, leaders should focus on training staff, automation , and finding a holistic solution which brings together security and data protection to strengthen an organization’s data.
Trusting the right people with your data can be tricky, and complex. As proven by countless instances of humans playing a key role in a data leak or beach: you can never be too safe.
Time and again it’s proven that humans are the weakest link in the security chain. To ensure data resilience in wake of a disaster or attack, organizations should prioritize the proper training of their IT professionals while equipping them with the right systems to automate processes.
It’s important that organizations shed the idea that their teams must manually handle these processes, from backing up data each night to monitoring systems. With touchless systems, teams can rest assured that their operations and data are always safe — even if a disaster strikes.
Neil Ellis, CafeX Ecosystem complexity is transforming the threat landscape for 2023.
We recognize this, and have invested in solutions that monitor, detect and provide information on our IT environment. As a CISO, the greatest challenge I see security teams face is how to leverage that information and significantly reduce remediation time.
We use our Challo platform to orchestrate and automate incident response through a single “pane of glass” so we can accelerate collaboration between internal and external experts, streamline secure access to system data and documents, and automate workflows that are relevant to various incident-types that are captured and reported by monitoring tools.
Investing in incident response has directly addressed challenges with ecosystem complexity, and improved agility and cybersecurity posture in the process.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"How designing with passion can redefine the customer experience | VentureBeat"
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"https://venturebeat.com/programming-development/how-designing-with-passion-can-redefine-the-customer-experience"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages VB Lab Insights How designing with passion can redefine the customer experience Share on Facebook Share on X Share on LinkedIn This article is part of a VB Lab Insights series paid for by Capital One.
What possibilities arise when we bring meraki to our work? Meraki is a Greek term for “doing something with soul, creativity, love and passion.” It’s that special something, the secret sauce, that can make all the difference in delivering experiences that both resonate with customers and create business value.
As the head of design for Capital One’s financial services business, my team and I serve a broad spectrum of customers — from our internal associates to the car buyers and dealers who use our financial products — and I can tell you that when we approach our work with the spirit of meraki , the outcome is transformational.
For a product, service or experience to work really well, those of us creating it must work with synchronicity and share a hunger for understanding and solving our customers’ deepest needs. Put simply, we need to start by caring about the people we are creating for, and then bring the best of ourselves (individually and collectively) to the work we do for them.
In a world where technology is table stakes, creating solutions with meraki matters. Infusing our products, services and experiences with passion gives us the best shot at delivering impactful solutions that go above and beyond our customers’ needs and wants. Because taking our customers’ best interests to heart can help exceed their expectations and become a real differentiator in a crowded market.
To do this, here are some battle-tested and timeless tips and considerations that I’ve seen work throughout my design career.
Fall in love with the problem.
A differentiated customer experience goes beyond simply completing a task; it presents something unexpected that the customer can’t live without. From a teamwork perspective, it means we need to approach the assignment with a level of care and commitment that shows we understand the customer’s needs and wants, and are genuinely motivated to deliver and account for what they need (which sometimes they don’t even know).
Consider the smartphone. It’s a product that does, well, everything.
But initially, none of us were clamoring for it, because who knew such a thing was possible? Now, though, few of us can imagine navigating life without it. By constantly focusing on the customer experience, by building and refining its capabilities, smartphone designers have created an iconic solution.
Understand — and truly care for — all of your audiences.
Different people need and expect different things. By leading with human-centered design principles and working back from the core pain point of the customer, you’ll deliver a more useful product to the end user. It begins with getting all the key players at the table, early on and throughout the design process. Diversity of experience and background is vital to ensuring the concept and delivery of an experience is not simply useful, but equitable and inclusive.
Work with grit.
If you truly believe a problem is worth solving, there’s always more to be perfected on behalf of the customer. It’s a never-ending quest. That can’t happen without persistence and conviction. It means constantly seeking customer feedback, testing, troubleshooting, and incorporating findings back into the experience.
Keep empathy — and humans — at the core.
True competitive differentiation comes in the form of customer experiences that go above and beyond — those that add a feeling of delight, solve a problem in an interesting way, and give users something more than what they anticipated. The challenge is that the bar for customer expectations is always changing. To do this well, you need to understand who you’re designing for and care for them deeply.
Human-centered design, driven by passionate teams, really works. I believe there’s always a shadow of the team that built the experience within every customer solution or product. My own team helped build Capital One’s Auto Navigator and complementary tools for car dealers. These are distinctly different platforms, for two very different audiences (consumers and dealers, respectively), yet they complement each other in ways that wouldn’t have been possible without understanding and attending to the needs of each audience.
By looking at the whole ecosystem — and genuinely caring about both car buyers and dealers — we’ve been able to find common ground and common goals and needs between them. And our solutions bring together these two important parties who are needed for most people to buy a car.
For example, neither dealers nor car buyers want to waste time during the car shopping process. By enabling people to shop and pre-qualify online with Capital One Auto Navigator, we actually create a faster, better experience when they go into the dealership. Because the dealer is able to welcome a knowledgeable, prepared customer into their store, everyone wins with a more seamless, efficient process. And they can focus on the joy of the test drive and getting out the door with a car they love.
The way brands break through the noise and build lasting relationships with their customers will become increasingly linked to the experiences they offer. As customers demand more from the companies they choose to do business with, it’s up to all of us who build experiences — designers, technologists, product managers, data engineers and business leaders — to bring something akin to meraki to the challenge.
Approaching our customers’ problems with passion, empathy and care for the humans we solve for is not only good for customers, it’s good for business, and it’s the pathway to further innovation.
Renee McKeon Rives is VP, Head of Design, Financial Services at Capital One.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"7 critical power skills you need to succeed at work | VentureBeat"
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"https://venturebeat.com/programming-development/7-critical-power-skills-you-need-to-succeed-at-work"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Sponsored Jobs 7 critical power skills you need to succeed at work Share on Facebook Share on X Share on LinkedIn There are a lot of skills we need in life, and when it comes to our working lives, the ones we hear about needing the most are hard and soft skills. We also need functional skills, which are core English, math and ICT abilities.
Hard skills are fairly easy to quantify: if you’re a programmer and you can code in C++, Python and Java — bingo, there are three easy-to-define hard skills right there. Others could include UX design, project management, video editing, foreign language fluency or data analysis. They are essentially the things that underpin the “what” and the “how” of your job.
It is the soft skills which people often struggle with defining, and as a result can dismiss their importance. Where hard skills are the nuts and bolts that define a job, soft skills provide the glide to make your day-to-day easier. They are the communication, persuasion, presentation and problem-solving abilities that go hand-in-hand with your core competencies, and by combining the two sets of abilities, you can deliver a power-boost to your career.
This especially matters if you work in a technical role and want to avoid being siloed — developing your presentation or communication muscles can be a great way to move up the career ladder into a more senior role where face-time with leadership will be part of your role.
Power skills Soft skills may be even more important than previously thought. Corporate learning experts at Bellevue University have studied workforce requirements and come to the conclusion that in order to cope with the massive changes in requirements we are seeing, agility is key. Those with good soft skills will be drivers of this agility thanks to their ability to adapt and thrive regardless of what change may bring.
Their research has recognized a set of seven “Power Skills” which reflect their importance in workforce productivity and company competitiveness. They are problem-solving; decision-making; judgment; communication; self-management; collaboration and value-clarification.
But it isn’t always so easy to get companies to understand the value and importance of soft, or “power” skills. In fact, a study from Corporate Learning Solutions found that most current soft skills assessment relies on anecdotal evidence. Employee skills gaps are the widest around soft skills too, and this gap is getting worse.
That is despite the fact that employees who receive soft skills training also exhibit greater levels of productivity than those who aren’t trained — which in itself can be used as a lever to persuade management to put in place some training for soft skills in 2023.
If you would like to move to a role where you can put your power skills to the test, then we have three worth looking at below, as well as plenty more to discover on the VentureBeat Job Board.
Senior Program Manager, Adobe, San Jose The Senior Program Manager position requires a highly qualified professional who is innovative, organized and dependable. The ideal candidate will have strong technical experience and skills, an ability to manage expectations and relationships with a diverse set of stakeholders, flex between the strategic and the tactical, outstanding verbal and written communication skills, and a high level of energy and flexibility to get things done. You will need a Bachelor’s degree with five years’ of experience, with an MBA preferred. A solid track record in project management in software, SaaS and/or related industries is preferred and you will need strong listening, analytical, problem-solving and conflict resolution skills as well as the ability to communicate efficiently with executive-level leaders.
Get the full job description.
Senior Software Engineer, Android, Duolingo, New York Duolingo is the most popular language-learning application in the world, with over 500 million users. As an Android Software Engineer , you will be developing applications primarily in Kotlin and using the Android SDK. You will collaborate on software projects with product design and backend aspects, develop, release, and maintain native Android applications and lead individual project priorities and deliverables. You’ll need to have a Bachelor’s degree in computer science or a related technical field and strong competencies in data structures, algorithms and software design as well as programming experience in Java/Kotlin.
Apply for the role here.
DevOps Engineer, Siemens, Florham Park Siemens is seeking a DevOps Engineer for Siemens Smart Infrastructure. You will support standard design, maintenance, enhancement, testing implementation, and support of software, and drive exploration of new best practices in continuous integration and develop automated release tools meant to allow for continuous build and release processes. You will need a BS in computer science, a related field or equivalent work experience plus five years’ of overall DevOps experience in building and enhancing CI/CD pipelines and tools to deploy software and experience with CI/CD, Gitlab, and GitHub. Find out more about the requirements here.
For opportunities in tech companies across the U.S, visit the VentureBeat Job Board today VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Striim brings cloud-modernization tool to AWS | VentureBeat"
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"https://venturebeat.com/data-infrastructure/striim-brings-cloud-modernization-tool-to-aws"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Striim brings cloud-modernization tool to AWS Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Can real-time technology help companies save during economic hardship? Alok Pareek thinks it can. Pareek is the cofounder and executive VP of products at Striim , a vendor whose goal and motto is to, “help companies make data useful the instant it’s born”.
Depending on which angle you look at it, you could say that Pareek is either biased or in the know. Either way, it was not so long ago that real-time data, or streaming data as this market is also called, was estimated to be worth billions.
The streaming analytics market (which, depending on definitions, may just be one segment of the streaming data market) is projected to grow from $15.4 billion in 2021 to $50.1 billion in 2026, at a compound annual growth rate (CAGR) of 26.5% during the forecast period according to Markets and Markets.
Then again, as the recent wave of layoffs and market capitalization losses goes to show, not all positive projections around technology come to fruition. Many projections counted on the effects of changes in consumer behavior due to COVID-19 and the associated restrictions as being permanent. It turns out that they are not, and hence projections are off the mark.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Could real-time data be different? Where does cloud modernization come into play, and how does Striim’s offering relate to that? Striim today announced the availability of its fully managed Striim Cloud service on Amazon Web Services (AWS).
After making Striim Cloud available on Azure and Google Cloud, the company’s announcement today regarding the availability of Striim Cloud on AWS is somewhat unusual, as cloud-based solutions tend to cover AWS first and then expand to other cloud vendors. Pareek said that this decision was based on two things: Customer demand and business relationships.
As Pareek explained, Striim is participating in Amazon Re-Invent this week, but the relationships with the Google and Azure teams are already established, “because they were super interested in getting real-time data into their successful offerings”. In addition, Striim’s focus was more on enterprises and they saw that AWS’ target market was “not necessarily the very large ones when it came to data management. Those were more in the other two CSPs” as per Pareek.
Striim wants to make data flow in real-time Striim was founded in 2012 by executive and technical members of organizations like Informatica, Oracle, Embarcadero Technologies, GoldenGate Software and BEA/WebLogic, both acquired by Oracle. Pareek was previously the CTO of GoldenGate , a managed service providing a real-time data mesh platform. Striim CEO Ali Kutay was CEO of WebLogic , a platform for developing, deploying and running enterprise applications.
It would not be too far off the mark to say that Striim picks up where Kutay and Pareek left off with GoldenGate and WebLogic. Striim’s vision, as per Pareek, is to deliver a unified data integration and streaming service to the market.
“We want to power all operations and decisions in real-time. Data flows for the digital economy, and we aim to make sure that the data is flowing in real-time”, said Pareek.
Striim, however, is not the only solution in the real-time data market.
Like virtually all of its counterparts, Striim emphasizes the real-time aspect as the key differentiation compared to solutions that operate in batch mode, such as Informatica or Talend. The overlap with those solutions, as per Pareek, is in use cases such as cloud data integration, data monetization, customer 360 and analytics.
Pareek referred to a number of trends that Striim is capitalizing on: The shift from on premise to cloud-based data platforms, from batch to real-time data processing, from pre-integrated commercial solutions to best of breed platforms. Striim sees many teams trying to leverage architectures like data mesh or data fabric in order to decouple data access. It also sees the emergence of products built around data as well as the emergence of flexible data formats such as JSON, Parquet and Delta.
As far as the differentiation with other real-time data platforms goes, Pareek emphasized the “hundreds” of supported data sources: From databases and log files to messaging systems like Kafka or IBM MQ and JMS-based systems to data from sensors, the web or applications like CRMs and Salesforce. Striim has developed its own Change Data Capture (CDC) technology for those sources, which enables anything-to-anything data integration scenarios in real-time.
Pareek added that Striim offers data transformation capabilities that go way beyond data integration. Striim offers SQL capabilities for continuous query processing, as well as the ability to define pattern-based or time-based data selection windows and feed data to do things such as auditing with third-party systems or real-time machine learning. These are leveraged in use cases ranging from improved customer experience and better patient care to fraud detection in domains such as logistics, travel, customer loyalty and retail supply chain.
“From streaming ingestion and CDC, to stream processing, to stream storage, to stream analytics, and then finally to stream visualization and delivery,” Pareek said. “We are taking all of these different capabilities in the streaming system and we have a comprehensive platform that addresses all of these; that’s why we call it unified.” Cloud modernization and real-time data as a cost saver According to Pareek, Striim is often utilized in mission-critical use cases. While he does acknowledge that some things in the industry are slowing down due to the economic downturn, Pareek thinks real-time technology is becoming more and more prevalent.
“We see our customers accelerating their cloud modernization initiatives because I think that’s how they actually save cost,” he said. “Nobody wants to manage their infrastructure and support. The economic downturn has impacted us a little bit, where people have slowed down their decision-making process and it’s taking more time. So we’ve seen some glimpses of that. At the same time, on a 12 to 24 month horizon, I’m not that worried.” Pareek explained that with real-time data processing 80-60% of ETL is, “still homegrown, on-premise and poorly executed through scripts that often fail.” Which he noted is ” a very labor-oriented and cumbersome business, so a lot of people are simply trying to get rid of that. That’s where the modern platforms which allow you to do real-time data integration come in. I think there’s a general trend in spending on that layer.” Striim’s offering is available as a platform that can be downloaded and run on-premises or in a self-managed cloud, as well as via Striim Cloud.
The latter is a fully managed cloud offering. As Pareek shared, Striim also offers pre-configured versions for specific data sources and targets such as Oracle, PostgreSQL, Kafka, Snowflake, Amazon S3 and Google BigQuery.
Following its latest funding round , Striim said it aims to deliver a developer-oriented version of its platform in early 2023. Pareek noted that it will be a premium offering that lets people get hands-on with the platform without having to be concerned with payments. The company also aims to broaden its suite of application connectors based on customer feedback.
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"PwC report: 81% of executives anticipate a recession within the next six months | VentureBeat"
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"https://venturebeat.com/data-infrastructure/pwc-report-81-of-executives-anticipate-a-recession-within-the-next-six-months"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages PwC report: 81% of executives anticipate a recession within the next six months Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Leading through turbulent times has become far too familiar for leaders; PwC’s new report found 90% of executives are concerned about macroeconomic conditions, including the Federal Reserve’s tightening cycle, higher cost of capital, and wages not keeping up with inflation. However, 82% remain confident about their ability to execute on digital transformation initiatives and 77% are confident they can achieve near-term growth goals.
Inflation is a looming threat, but large budget cuts can formulate the exact precarious situation companies hope to avoid. Rather than acting swiftly, the survey found executives are focused on planning for the potential timing and severity of a recession.
Executives are thinking about how to cut costs without reducing headcount, such as using automation and managed services for efficiency. CIOs still plan to invest in digital transformation.
Implementing strategies for recession-proofing Along with inflation fears, executives are worried about wage growth not keeping up with rising costs, and plan to reduce the number of full-time employees as a result. In fact, 81% of CHROs plan to implement at least one tactic to reduce their workforce, such as layoffs, voluntary retirement or not replacing people who leave on hiring freezes.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! The state of hybrid work remains a topic among executives. Two-thirds are concerned with a slower-than-expected returns to work. Many seek to implement on-site training, coaching and mentoring opportunities to attract employees. Executives are challenged to rethink the role of the office by creating a culture that fosters in-office participation.
While fears of a recession loom, not all hope is lost. Leaders are focused on growth and looking to enter a possible recession healthy and exit healthier. While conscious of their cost structure, it’s part of a bigger conversation about how they will transform their businesses for the future, rather than a knee-jerk reaction to current economic conditions. How well and how quickly they are able to execute will determine the outcome.
Effective strategic planning, investment in growth and continuous flexibility will see companies through growing concerns.
PwC’s report surveyed more than 650 business executives, including 91 CFOs and 94 CHROs.
Read the full report by PwC.
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"Deep dive: How network-as-a-service (NaaS) is aiding cloud adoption | VentureBeat"
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"https://venturebeat.com/data-infrastructure/deep-dive-how-network-as-a-service-naas-is-aiding-cloud-adoption"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Deep dive: How network-as-a-service (NaaS) is aiding cloud adoption Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
The adoption of cloud computing and the transition of corporate applications to on-premises networks have made corporate data infrastructures increasingly complex. Employees today need access to several applications for their jobs, applications that are latency-sensitive and require high-performance and reliable network connectivity.
While some applications can be hosted in one cloud, others must be set up in a completely different cloud. This practice vastly decreases the flexibility of a network’s architecture. Network flexibility has also created new issues for IT teams, who are already under enormous pressure to ensure that enterprise networks remain reliable secure, scalable and compliant.
Over a decade ago, organizational flexibility was viewed as a bonus rather than a necessity, and certainly not at the top of the corporate agenda. But with the pace of innovation, most enterprises can no longer afford the time it takes to build and maintain their own network infrastructures. As a result, the importance of a robust network has never been greater.
Network-as-a-service (NaaS) is slowly becoming the consumption model of choice to help organizations meet increased flexibility needs. NaaS solutions enable an organization to ensure that it has the network infrastructure and enterprise-grade security to protect it without needing to maintain the necessary personnel and resources in-house.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! What is network-as-a-service? NaaS architecture is a cloud service paradigm that delivers networking hardware, software and operational/maintenance services as an operating expense rather than a one-time cost.
Within enterprises, the as-a-service concept is taking hold as organizations embrace cloud computing and its consumption-based billing model.
According to research firm IDC , the as-a-service model will account for more than 75% of network infrastructure at edge locations and up to 50% of data center infrastructure by 2024.
Many corporate activities are transitioning to the cloud, and NaaS is a viable replacement for MLPS connections, legacy network setups and numerous types of on-premises hardware, such as load balancers and firewall devices.
NaaS also reduces the time network employees must spend maintaining the network, as well as the level of training and competency required of network professionals. For example, IT experts can handle an organization’s network via a portal instead of maintaining a pool of network management tools and hardware stacks.
Like other cloud services, the service provider maintains and delivers the NaaS model for a fixed fee. And for enterprises that prefer a subscription-based approach to enterprise networking, NaaS provides equipment, software orchestration and administration for a fixed recurring cost, with services tailored to an adopter’s unique business requirements.
As a newer model for routing traffic and applying security policies, NaaS has significantly impacted enterprise networking architecture. Furthermore, certain NaaS providers specialize in areas such as ultra-secure connections, simple configurations, and services for mobile and temporary sites.
Benefits of NaaS architecture In the past, when employees on an internal network connected to the internet, their traffic had to go through the corporate networking infrastructure via a VPN first. This model quickly became inefficient as business activities began moving into the cloud. Cloud computing has also grown more efficient, with more capabilities. Today, DDoS mitigation, firewalls, load balancing and other essential networking functions can all run in the cloud, eliminating the need for internal IT teams to build and maintain these services.
For these reasons, NaaS is a more efficient option than relying on internally maintained WANs. Such WANs require constant maintenance and often create bottlenecks for network traffic. With NaaS, employees can connect to their cloud services directly through a virtual network that an external vendor manages and secures. IT teams don’t have to spend time keeping up with the demand for network services.
With NaaS, employees no longer have to wait for their web traffic to travel through the internal corporate infrastructure. Instead, they can connect to the internet, sign in through a browser and access all the cloud services they need. A NaaS provider secures their browsing activity, protects their data and routes their web traffic wherever it needs to go as efficiently as possible.
Small and medium-sized businesses, particularly those without a prior WAN investment, are typical NaaS buyers. However, larger enterprises, too, have become more interested in the NaaS model over the past 10 years.
The NaaS model has several other benefits, including: Improved service latency: Reduced latency results in enhanced sound quality, more efficient call routing and better network administration. Employees can focus on their work instead of being distracted by IT issues.
Enhanced productivity: IT staff (and other employees) can complete their regular tasks more efficiently and effectively when their network is in good working order, with fewer difficulties and downtime. As a result, overall productivity increases. The NaaS partner will deliver monthly reports so you can identify concerns and critical trends.
Reduced cost: Many IT expenses, including infrastructure, hardware, software, operations and maintenance, may very well be decreased with NaaS. NaaS significantly reduces the capital investment cost for networking gear, making it attractive to new business owners. Furthermore, most NaaS providers charge a fixed monthly subscription fee, assisting adopters in planning their monthly IT budget.
Challenges facing NaaS architecture The existing NaaS architectures lack vendor versatility, portability and long-term commitments. There may also be problems with legacy systems, such as software or hardware incompatible with the solution. Most NaaS compatibility difficulties are caused by outdated hardware or on-premises applications that are outdated but still in use.
Because many organizations still use on-premises data centers rather than the cloud for some critical operations or applications, transitioning to the NaaS model might require a good deal of time and effort, though the services can assist their customers.
>>Don’t miss our special issue: Zero trust: The new security paradigm.
<< Because a NaaS connection is typically established using “best effort” public broadband, the service is available only where broadband internet connections are available, which can limit performance and capabilities to the speed of the last-mile connectivity.
Another concern for some organizations is the potential for loss of control. Adopters may have concerns about service responsiveness and control of their network resources with outsourced network services.
A future of opportunities NaaS vendors usually emphasize SD-WAN functionality in addition to the simplicity of reading and management at the center of the NaaS model. The network-as-a-service model is also a compelling new option for corporations that want to focus on code design without hiring engineers and building hardware infrastructure. With NaaS, a company can virtualize its network and use virtual logic entities to regulate it, rather than use hardware switches and nodes to drive network activity Since NaaS is easily accessible from any part of the world and any device, it is expected to become widespread in hybrid and small businesses in the next few years. Employees can easily access any platform as long as they have a stable internet connection and login credentials.
Typically the service provider will charge a monthly subscription fee, but depending on the service provider, infrastructure functionality may or may not be included; the client can pay individually for each service, including optimization, firewall, other security services and SD-WAN. So, once your company has defined its business objectives and the scope of its service requirements, you can opt for the best financial model and feature set for your needs.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Why modernization investment should be more strategic than discretionary | VentureBeat"
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"https://venturebeat.com/business/why-modernization-investment-should-be-more-strategic-than-discretionary"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Why modernization investment should be more strategic than discretionary Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Enterprise modernization efforts aren’t what they used to be. Once limited to the IT side of the house, modernization efforts today now rightfully top the executive agenda.
This makes sense. Modernization, when done right, drives increased reliability, resilience and revenue across organizations. The result: Happier customers and a more healthy organization.
More organizations are recognizing this. Over the next five years, as much as 90% of legacy applications will be replaced by modern systems, according to a recent Infosys survey of 1,500 senior technology leaders and executives.
But while modernization’s importance is on the rise, not all modernization efforts are equally successful. On one hand, there has been a heartening rise in the number of organizations that have taken a strategic approach to their modernization projects. On the other hand, we still see many organizations that rely on a more haphazard approach, exposing them to a wide variety of risks.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Why discretionary modernization fails Earlier this year our team set out to better understand the state of application modernization across large and small enterprises. In conversations with IT leaders and executives we found that, while companies overall invest 65% of their discretionary budget on modernization projects, smaller organizations were more likely than larger ones to do so.
This is dangerous. Companies that rely on discretionary budgeting to modernize their systems are more likely to experience frequent and severe disruptions, according to the business leaders we spoke to.
The costs of such downtime can be immense.
According to some estimates , a minute of system downtime can cost an organization as much as $5,400. In today’s economy, few organizations can afford that kind of loss.
Why strategic investment succeeds Fortunately, while many organizations still rely on discretionary investment, the majority are thinking differently. More strategic, future-thinking companies are approaching modernization like a marathon, building modernization roadmaps optimized for pacing, planning and persistence.
There are a few benefits to this approach. For one, thinking strategically allows organizations to be more deliberate. For example, we’ve seen consistent success among organizations that have embraced phased implementations of modern applications. This approach, also known as “coexistent” implementation, is less disruptive and ensures business continuity. It’s particularly important for critical systems, which are the most costly when they go down.
Second, organizations that embrace strategic modernization are also more likely to be able to articulate the commercial outcomes of their efforts. It’s hard to overstate how valuable this is. Nearly a quarter (24%) of the IT leads we spoke to said that cost was the most significant hurdle to their modernization projects. A better understanding of the financial impact can help. After all, it’s far easier to secure executive sponsorship for a project if you can explain to your finance team how it will drive revenue, reduce costs or, ideally, do both simultaneously. Indeed, 29% of the leaders we spoke to said that having a valid business case was most important to ensuring that a modernization program reaches its objectives.
Third, a more strategic approach to enterprise modernization can also drive a more informed approach to talent development. The tech talent crunch is real for organizations both large and small. When we asked respondents about the most significant impediments to their modernization efforts, more than half cited the skills gap and the difficulty of both retraining existing technologists and recruiting new ones. Thinking long-term can help IT teams better understand their current talent gaps and how to address them in a structured, sustainable way.
A more modern approach to modernization To close, let’s highlight one element that separates successful business transformation efforts from less successful ones: The ability to articulate and share a single, cohesive vision for modernization. The organizations that succeed are those that can tell a story that aligns their people, process and technology. The organizations that fail are the ones that can’t.
Gautam Khanna is the vice president and global head of the modernization practice at Infosys.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"LabGenius Wins Government Innovation Grant to Support the Development of ML-driven Cancer Therapies | VentureBeat"
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"https://venturebeat.com/business/labgenius-wins-government-innovation-grant-to-support-the-development-of-ml-driven-cancer-therapies"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Press Release LabGenius Wins Government Innovation Grant to Support the Development of ML-driven Cancer Therapies Share on Facebook Share on X Share on LinkedIn The UK’s innovation agency, Innovate UK, has awarded LabGenius Biomedical Catalyst funding to drive the development of their immunotherapy pipeline LONDON–(BUSINESS WIRE)–November 30, 2022– LabGenius, a pioneer in the use of machine learning (ML) for antibody-based drug discovery, today announced that it has been awarded a highly competitive Biomedical Catalyst (BMC) grant from Innovate UK. With this recent grant, LabGenius has secured a total of over £1 million in government backing this year.
This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20221130005020/en/ LabGenius is pioneering the development of an ML-driven protein engineering platform ( EVA ™ ).
To date, EVA has co-optimised mono- and multi-specific single domain antibodies for biochemical and biofunctional properties, including stability, potency and selective tumour cell killing.
There are many different types of solid tumours that would benefit from highly selective immunotherapy treatments. This grant will be used to support the development of LabGenius’ pipeline of antibody therapeutics by financing the discovery of best-in-class immune cell engager molecules with favourable selective killing profiles. To do this, LabGenius will use its platform technology to intelligently guide the search for protein designs that perform across multiple therapeutically valuable properties.
“We’re truly delighted with this result” said LabGenius’ CEO and Founder, Dr. James Field.
“This grant will enhance LabGenius’ ability to optimise an important class of immunotherapeutics and help us to accelerate drug candidates towards the clinic.” Speaking to LabGenius’ success, Chairman of LabGenius’ Board and former CEO of Ablynx, Dr. Edwin Moses commented “This is a great win for LabGenius as it further validates their ML-driven approach to antibody discovery. With this backing, the team can further expand their efforts to build a strong pipeline of molecules that would not have been identified through rational human design alone.” – end – About LabGenius Headquartered in London, LabGenius is a leading machine learning-driven protein engineering company. The company’s core technology platform, EVA ™ , enables the rapid discovery of novel therapeutic antibodies. LabGenius’ highly multidisciplinary team brings together the very best minds from the fields of computer science, robotic automation and synthetic biology.
For more information, please visit www.labgeni.us , or connect on Twitter , LinkedIn and Medium.
View source version on businesswire.com: https://www.businesswire.com/news/home/20221130005020/en/ For more information, please contact: For media enquiries, please contact Lucy Shaw at [email protected] For business development, please contact James Field at [email protected] VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Predictions for AI, video, chips and more in 2023 | Deloitte | VentureBeat"
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"https://venturebeat.com/ai/predictions-for-ai-video-chips-and-more-in-2023-deloitte"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Predictions for AI, video, chips and more in 2023 | Deloitte Share on Facebook Share on X Share on LinkedIn Deloitte pulled out its crystal ball again for 2023 predictions.
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The new year will see AI tools for chip design, video streams with ad support, and a crowd of satellites in space, according to the annual tech, media and telecom predictions from accounting and consulting firm Deloitte.
In its predictions, Deloitte said it expects we will see the major formerly ad-free streaming services shift to offering cheaper or free options with advertising. The firm also sees a lot of M&A activity continuing across the tech, media, gaming, and telecom markets in 2023.
It also said that streamers are getting in the game with live sports, in a bid to turn fans into subscribers. Jumping over to deep tech, the company also said chips are getting more complicated and design talent more scarce. As a result, AI tools could come to the rescue. (This trend has been happening in chip design tools for a lot of years already, but it’s accelerating.) And Deloitte said five thousand satellites in orbit could connect the world with data, but managing traffic in space is getting more challenging, according to the Deloitte Technology, Media & Telecommunications 2023 Predictions report.
Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! Rising inflation and interest rates, slowing economies, and plunging consumer confidence have dominated discourse this year, Deloitte said. And economic conditions are driving a rebound in tech divestitures and growth in M&A activity around gaming as many targets are much cheaper than a year ago.
The report focuses on the crucial roles artificial intelligence (AI), advertising video on demand (AVOD), 5G and chips could play in our hyperconnected world. These broad and diverse subjects reflect how far and wide Deloitte’s reach is in terms of industries that it analyzes.
“This year’s TMT predictions underscore a common theme, both with consumers and businesses to do more with less as inflationary pressures, supply chain issues and other world events continue to cause uncertainty,” said Kevin Westcott, vice chair at Deloitte U.S. global Telecommunications, Media and entertainment (TME) practice leader, in a statement. “Given this, consumers are looking for more cost-effective ways to communicate, to be entertained, and to be productive, while businesses are looking for efficient ways to innovate in order to compete, differentiate and grow revenue. Our thinking on these emerging trends should help guide organizations as they plan for the future and strive to meet their customers’ needs.” Gaming M&A is growing on the back of consolidation, portfolio plays, and game tech Deloitte predicts that in 2023, the number of video game company mergers and acquisitions will continue to increase by around 25%, slightly slower than the estimated 30% quarterly growth of 2022. Video game services, experiences, and business models are innovating, console supply chains are loosening up to meet pent-up demand for next-gen experiences, and many anticipated games that were delayed in 2022 are now set to reach players in the coming year.
Deloitte predicts that the VR market will generate $7 billion in revenue globally in 2023, a 50% increase over 2022’s $4.7 billion. As VR grows in popularity, 90% of that revenue will likely come from headset kit sales, with 14 million units averaging $450 each expected to sell in 2023. The remainder should comprise mostly of VR content — principally games, but also some enterprise applications — which could see revenues of just over $1 billion.
That said, in terms of numbers, VR has a long way to go to catch up with other digital devices. Smartphones alone count almost five billion users worldwide, and billions also use PCs, tablets, and TV sets. Even smart speakers, a relatively new device that launched in 2017, will likely boast an installed base of more than 500 million units by the end of 2023. At an active installed base of just 22 million in 2023, VR will therefore remain relatively niche for the time being.
Now that component shortages have been alleviated some by the economic downturn, game hardware and VR hardware companies may be able to ship more products in 2023, said Hanish Patel, a Deloitte managing director who specializes in gaming, in an interview with GamesBeat.
Improvements in the underlying technology, including power, screens, and audio should fuel this growth. Next year, headsets should offer higher frame rates, higher-resolution displays, and enhanced spatial audio, enabling a realistic, immersive experience.
“I truly believe that because of just the sheer pace of new technology, new innovation, adoption, it’s leading to incredibly more exciting and accelerating times,” said Patel.
Microsoft is in the process of acquiring Activision Blizzard for $68.5 billion, and the thing about big acquisitions is they inspire more acquisitions, Patel said. Prices for some companies are falling and that could inspire more M&A as well.
“That in itself is going to still result in a fair amount of deal flow,” Patel said. “Companies are maximizing their intellectual property. And in order to do that, there still will be some more consolidation.” One interesting point is that Deloitte didn’t really bring up the metaverse or blockchain gaming much in the gaming section of the report. But Patel said that the firm has been watching those areas develop for a while. The slowdown in crypto and its “rollercoaster year” could affect blockchain gaming’s growth, he said. And while gaming is an onramp for the metaverse, Deloitte did not weigh in on that topic in a big way in this report. Still, Patel said he sees growth ahead for the metaverse and Web3 technologies in gaming.
As for growth in 2023, Patel said he could see the that supply chain shortage that held back the console game industry has begun to ease. This holiday season could well determine whether the shortage caused gaming to permanently lose console sales or if there is still pent-up demand that could be fulfilled now that consoles are more plentiful.
“We’re saying the foundations of gaming are strong and have been strong for a long time,” Patel said.
Global growth in streaming services includes AVOD increase Deloitte predicts that major streaming services that have been ad-free will add AVOD (advertising video on demand) options. While ad-free subscriptions aren’t going away, Deloitte anticipates that by the end of 2023, major subscription video-on-demand services in developed markets will likely launch new ad-funded tiers. By the end of 2024, half of these providers will likely also have launched a free ad-supported streaming TV service (FAST). And by 2030, Deloitte expects that most online video service subscriptions will be partially or wholly ad-funded.
“Our recent research showed the churn rate for streaming services in the U.S. was 37%. This means media and entertainment companies should continuously look for ways to generate new revenue while appealing to cost-conscious consumers who have a growing appetite for more compelling and diverse content,” said Jana Arbanas, vice chair of Deloitte and U.S. telecom, media and entertainment sector leader, in a statement. “Advertising video on demand, for example, can satisfy both objectives by giving consumers more options that work within their budget and streaming companies more opportunity for growth by working with eager advertisers, not to mention the more lasting relationship with consumers.” Semiconductor companies turn to AI and high-power materials to design future chips Chip companies are using AI to help design chips faster, cheaper, and more efficiently. Deloitte predicts that the world’s leading semiconductor companies could spend $300 million on internal and third-party AI tools for designing chips in 2023, and that number may grow by 20% annually for the next four years to surpass $500 million in 2026. The impact of AI will likely go far beyond the money spent on AI design tools.
They can enable chipmakers to push the boundaries of Moore’s Law, save time and money, and even drag older chip designs into the modern era. In 1965, Intel chairman emeritus Gordon Moore predicted the number of components on a chip could double every couple of years. For decades, that held true, resulting in huge technological advances. A number of chip leaders say the easy advances from manufacturing over the decades have been exhausted.
“The semiconductor shortage has demonstrated the need for faster, more efficient manufacturing of chips in order to meet demand,” said Paul Silverglate, vice chair, Deloitte and U.S. technology sector leader, in a statement. “Artificial intelligence-aided design can be used to address this need and can also make older chips better by moving to more advanced process nodes, and even help close the chip talent gap. By making chip design exponentially faster with AI, semiconductor companies can move beyond the current market challenges and focus more on what’s next.” Supercharged semiconductors made of high-power materials are taking chip development to a new level. Replacing silicon, these materials — primarily gallium nitride and silicon carbide — are suited for the higher voltages, power levels, and resilience needed for increasingly common applications such as EV batteries, super-efficient consumer electronics chargers, powerful solar panels, advanced military applications, space technology and nuclear energy.
Deloitte predicts that chips made of high-power semiconducting materials could sell a combined $3.3 billion in 2023, up almost 40% from 2022. Growth in these types of chips, collectively known as power compound semiconductors, is expected to accelerate to nearly 60% in 2024, possibly generating revenue of more than US$5 billion.
Broadband satellites will need to navigate a crowded sky Deloitte predicts that more than 6,000 broadband satellites could be in low-Earth orbit (LEO) by the end of 2023, because of growth in commercial data satellite deployments to provide high-speed internet to every corner of the world. They could make up two working constellations providing high-speed internet to nearly a million subscribers on all parts of the planet, no matter how remote.
Starlink alone has more than 2,600 satellites in space, and Amazon plans to put 3,236 satellites into orbit.
If every organization currently planning to build an LEO constellation succeeds, seven to 10 competing networks could be operational by 2030, with a total of 40,000 to 50,000 satellites serving more than 10 million end users. This growth would likely require more to protect the commons of space including increased industry collaboration and new capabilities for space situational awareness, in-orbit satellite servicing, and space debris removal.
Among the impacts: Deloitte expects a lot of demand for radiation-hardened semiconductors.
Additional Deloitte 2023 TMT predictions: Many organizations want to reach net zero and the technology industry is making a strong commitment. According to an analysis of the Deloitte CxO sustainability survey, tech companies are working harder and faster to impact climate change and are 13% more likely than non-tech companies to target net zero by 2030.
By introducing virtualized, cloud-centric capabilities, 5G standalone (SA) networks are poised to drive disruptive change that could make previous advances in wireless technology (2G/3G/4G) appear incremental. Deloitte expects the number of mobile network operators (MNOs) investing in 5G standalone networks — with trials, planned deployments, or actual rollouts — to double from more than 100 operators in 2022 to at least 200 by the end of 2023. Deloitte expects to see $99 5G phones.
Virtual production is also getting real. The tools and techniques of virtual production are transforming film and cinema, increasing flexibility, shortening production times, and bringing real-time computer-generated imagery and visual effects out of post-production and onto real-life sets. Deloitte predicts that the market for virtual production tools will grow to $2.2 billion in 2023 — up 20% from an estimated $1.8 billion in 2022.
The next arena for the streaming wars: live sports Streaming providers are spending billions of dollars on live sports. They have purchased rights across the spectrum of sporting events in a bid to attract, retain, and monetize their audiences via this popular content. Deloitte predicts that in 2023, streamers could spend more than $6 billion on major sports rights in the largest global markets.
Streaming services are the latest to enter the live sports ring, with cable, broadcast, and satellite services all contending for fans. In one corner stand entertainment companies and regional sports networks with traditional linear channels that also offer a streaming service. In another corner are the “pure play” streaming providers who have only their streaming service as an option to reach consumers. In the third corner, there are tech companies looking to broaden the reach of their streaming services and increase time spent within their ecosystem.
Apple has committed to spend at least $2.5 billion for the sole rights to stream every U.S. Major League Soccer (MLS) game over the next 10 years via a dedicated Apple TV app.
Shopping goes social, trending past $1 trillion annually Deloitte predicts spending for goods and services on social media will surpass $1 trillion globally in 2023, growing 25% annually with more than two billion people shopping this way in the last year. The social commerce market is outgrowing traditional e-commerce. In a Deloitte survey, Generation Z and Millennials are more likely than Gen X respondents to say that social media influencers affect their buying decisions.
And cloud, telco, equipment, and platform companies are vying for a share of enterprise investments in edge services and products that make computing faster, safer, and cheaper. Deloitte predicts that the enterprise market for edge computing will grow at 22% in 2023, compared to 4% growth in spending on enterprise networking equipment and 6% on overall enterprise IT for the same year. Most of this growth will likely come from expenditures on hardware initially but should migrate toward software and services as the market matures.
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