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OpenAI says internal models produced manuscripts including a claimed disproof of the Exponential Time Hypothesis (ETH) and a partial result related to a Millennium Prize Problem. The company published the raw writeups and Lean formalizations, is funding independent review, and has asked outside experts (including a Nobel laureate) to act as "shepherds" to check and interpret the proofs.
Microsoft has created a new Xbox Labs group to experiment with decompiling and recompiling games and other AI-enabled modding, according to Xbox CEO Asha Sharma. The small team of game makers, engineers and scientists will "build in the open," share tools and learnings with developers, and study how AI changes where and how games are played and created.
In a post on X, Microsoft CEO Satya Nadella urged stepping back to "assess the trust architecture" of AI and proposed separating models from the orchestration "harness," externalizing safeguards, keeping tamper‑proof human‑readable records of every meaningful model action, and ensuring an authorized person can pause or shut down a model mid‑task as an "emergency brake." His comments come after several incidents of perceived loss of model control and follow other industry calls for more cautious development, including a plan from Anthropic CEO Dario Amodei.
GeoPT is a research method that helps AI models learn basic principles of physics, enabling them to simulate how objects respond to influences like wind and water more efficiently and accurately. The approach broadens the range of real-world scenarios the models can represent.
Google DeepMind and Isomorphic Labs have shared a joint approach to bioresilience and the use of AI models, outlining how the organizations plan to address biological resilience-related challenges with AI (source: Google DeepMind).
Researchers developed an automated framework that helps AI models generate CAD programs more accurately and more efficiently, improving the process of turning 2D designs into 3D models for rapid prototyping. Details on methods, benchmarks and limitations were not provided in the source summary.
Through research and entrepreneurship, Professor Devavrat Shah is designing methods to enable continuous decision‑making by AI systems when computational resources are limited, aiming to help models operate effectively in real‑world settings.
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