Companies using generative artificial intelligence tools like ChatGPT could be putting confidential customer information and trade secrets at risk, according to a report from Team8, an Israel-based venture firm. The widespread adoption of new AI chatbots and writing tools could leave companies vulnerable to data leaks and lawsuits, said the report, which was provided to Bloomberg News prior to its release. The fear is that the chatbots could be exploited by hackers to access sensitive corporate information or perform actions against the company. There are also concerns that confidential information fed into the chatbots now could be used by AI companies in the future. Major technology companies including Microsoft and Alphabet are racing to add generative AI capabilities to improve chatbots and search engines, training their models on data scraped from the Internet to give users a one-stop-shop to their queries.

The binding complexes formed by proteins and small molecule ligands are ubiquitous and critical to life. Despite recent advancements in protein structure prediction, existing algorithms are so far unable to systematically predict the binding ligand structures along with their regulatory effects on protein folding. To address this discrepancy, we present NeuralPLexer, a computational approach that can directly predict protein-ligand complex structures solely using protein sequence and ligand molecular graph inputs. NeuralPLexer adopts a deep generative model to sample the 3D structures of the binding complex and their conformational changes at an atomistic resolution. The model is based on a diffusion process that incorporates essential biophysical constraints and a multi-scale geometric deep learning system to iteratively sample residue-level contact maps and all heavy-atom coordinates in a hierarchical manner. NeuralPLexer achieves state-of-the-art performance compared to all existing methods on benchmarks for both protein-ligand blind docking and flexible binding site structure recovery. Moreover, owing to its specificity in sampling both ligand-free-state and ligand-bound-state ensembles, NeuralPLexer consistently outperforms AlphaFold2 in terms of global protein structure accuracy on both representative structure pairs with large conformational changes (average TM-score=0.93) and recently determined ligand-binding proteins (average TM-score=0.89). Case studies reveal that the predicted conformational variations are consistent with structure determination experiments for important targets, including human KRAS$^\textrm{G12C}$, ketol-acid reductoisomerase, and purine GPCRs. Our study suggests that a data-driven approach can capture the structural cooperativity between proteins and small molecules, showing promise in accelerating the design of enzymes, drug molecules, and beyond.

Russell Wald, director of the Stanford Institute for Human-Centered AI, sounds off on'The Story.' OpenAI CEO Sam Altman says the age of the giant artificial intelligence model is already over. "I think we're at the end of the era where it's going to be these, like, giant, giant models," he told an audience at the Massachusetts Institute of Technology over Zoom last week. "We'll make them better in other ways." During the same event, Altman also confirmed that his company is not developing Chat GPT-5. "An earlier version of the letter claimed OpenAI is training GPT-5 right now," he said, referencing a letter from billionaire Elon Musk and Apple co-founder Steve Wozniak.

Two weeks in a row, ChatGPT botched my grocery list. I thought that I had found a really solid, practical use for AI--automating one of my least favorite Sunday chores--but the bot turned out to be pretty darn bad at it. I fed it a link to a recipe for cauliflower shawarma with a spicy sauce and asked it to compile the ingredients in a list. It forgot the pita, so I forgot the pita, and then I had to use tortillas instead. The following week, I gave it a link to a taco recipe.

Digital human avatar technology provider Didimo Inc. is bringing generative artificial intelligence to the world of video game character creation. With today's launch of Popul8, Didimo says, game developers now have a simple way to create hundreds of unique game characters in a fraction of the usual time and cost. Popul8 is a generative AI tool that builds on Didimo's existing avatar creation toolset, accelerating the time it takes for developers to create extremely lifelike, 3D game and metaverse characters with full control over their appearance. Traditionally, it has taken developers countless hours to create realistic-looking characters for their computer games, with painstaking attention to detail a very necessary part of the design process. With Popul8, it becomes possible to design animated and diverse avatars in a matter of minutes. The tool allows for consistent designs, with users able to upload template characters from any game to ensure their new avatars match its aesthetic style.

Is it possible that some of the greatest AI inventions are overlooking something major? In this episode, I dive into what seems to be the missing piece in artificial intelligence and AI research. Listen in to learn how a different approach could bridge the gap between the world of AI and everyday function and usability. "Steve Jobs showed that with Apple. That they were not just science and engineering creations they were theater, they were art.

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"With great power comes great responsibility." You don't have to be a Marvel buff to recognize that quote, popularized by the Spider-Man franchise. And while the sentiment was originally in reference to superhuman speed, strength, agility, and resilience, it's a helpful one to keep in mind when making sense of the rise of generative AI. While the technology itself isn't new, the launch of ChatGPT put it into the hands of 100 million people in the span of just 2 months, something that for many felt like gaining a superpower. But like all superpowers, what matters is what you use them for. Generative AI is no different.

San Francisco-based company Synthesis AI, a frontrunner in the field of synthetic data technologies, unveiled its latest project, Synthesis Labs, on April 18, 2023. This initiative focuses on introducing new generative AI capabilities, with an emphasis on text-to-3D technologies for digital humans. These advancements mark a milestone in the company's journey to support advanced AI applications, making Synthesis AI the first ever to demonstrate text-to-3D digital human synthesis at high-resolution cinematic quality. By merging generative AI with cinematic VFX pipelines, the Synthesis AI platform generates perfectly labeled synthetic data, which can be utilized to train machine learning models. The newest text-to-3D offerings, featured in Synthesis Labs, allow users to experience prompt-based input and editing, making no-code 3D generative AI capabilities accessible to a wide range of users – from computer vision and machine learning experts to non-technical users.

Join top executives in San Francisco on July 11-12, to hear how leaders are integrating and optimizing AI investments for success. In enterprise security, speed is everything. The quicker an analyst can pinpoint legitimate threat signals, the faster they can identify whether there's a breach, and how to respond. As generative AI solutions like GPT develop, human analysts have the potential to supercharge their decision making. Today, cyber intelligence provider Recorded Future announced the release of what it claims is the first AI for threat intelligence.