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Since DALL-E was released into public beta last month, many companies have begun integrating its use in various situations across the artificial intelligence (AI) landscape. Tome, the platform for storytelling and ideas, announced this week that its interactive slideshow functionality is now supported by DALL-E technology. Users can apply DALL-E to help them with presentation images to accurately convey what they imagine. Tome says it’s also working with GPT-3 to add more AI functionality to its platform in the near future.
Also on the scale of generative AI, Microsoft revealed this week that the Bonsai project’s reinforcement learning will be powered by d-Matrix DIMC technology. The goal is to speed up AI reasoning. For context, using generative AI to model transformers is critical to its functionality, but also a resource-intensive process. Inference systems in artificial intelligence help in prediction and building results from the model. Microsoft’s move to speed up the process will help increase efficiency and deploy generative AI models.
Nvidia also made great strides this week with the announcement of developments aimed at improving the Omniverse, extending scientific applications to higher performance computing platforms. The company said this would allow digital twins to collect data that currently exists across various applications, models, and user experiences. It’s a step toward developing digital twins from passive modeling to actively shaping the world,” said Dion Harris, principal product manager for accelerated computing.
Meanwhile, this week’s Intel news focused on shaping the world in a different way: eliminating deepfakes. The company introduced a new tool dubbed FakeCatcher, which it claims has an accuracy rate of 96% and works by analyzing “blood flow” from a photo or video and returning results in real time.
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Not surprisingly, along with the advent of new technologies such as deepfakes and new strides in artificial intelligence, has necessitated the need for increased security across sectors. In a VentureBeat special report on zero-trust security released this week, our writers highlight how security is tested and why a no-trust approach is the future. Part of the insight also examines the ways in which some organizations get mistrust wrong, including failing to understand what mistrust is at its core and how to properly apply it.
Here are more of the top 5 tech stories of the week:
- The new DALL-E integration adds generative AI to next-level chips
Tome announced OpenAI’s DALL-E-powered interactive slide options. The company, which calls itself “the new form of storytelling for work and ideas that matter,” says it was a natural fit to add an AI generic dimension to the decks.
“Making this part of the storytelling creation experience really felt natural,” Tome CEO Keith Pearce told VentureBeat. “It felt so much more powerful than looking for a stock photo or clip art — it kind of gives us a first look at what storytelling can look like.”
- Nvidia Omniverse to support Scientific Digital Twins
Nvidia announced several significant developments and partnerships to extend the Omniverse into scientific applications on top of high-performance computer (HPC) systems.
This will support scientific digital twins that combine existing data silos across different applications, models, tools, and user experiences.
- Why don’t companies get trust wrong?
The truth about zero confidence adoption is that it is a journey, not a destination. There is no quick fix for implementing no trust because it is a security methodology designed to be applied consistently throughout the environment to control user access.
One of the most important reasons companies lack zero trust is not only about understanding what zero trust means, but also knowing how to apply it, and what products can apply zero trust.
- New partnership with Microsoft accelerates generative development of AIMicrosoft and d-Matrix announced that Microsoft Project Bonsai’s reinforcement learning will be supported on d-Matrix DIMC technology, which the two vendors hope will provide significant acceleration of AI inference.
“Project Bonsai is a platform that enables our version of deep reinforcement learning and we call it machine learning,” Kingsuk Maitra, Principal Artificial Intelligence Engineer at Microsoft, told VentureBeat.
- Intel unveils real-time deepfake detector, claims 96% accuracy rate
On Monday, Intel introduced FakeCatcher, which it says is the first real-time detector for deepfakes — artificial media in which a person in an existing photo or video is replaced with the appearance of another person.
Intel claims the product has a 96% accuracy rate and works by analyzing the exact “blood flow” in video pixels to return results in milliseconds.
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