
OpenAI shares model results on the Kakeya conjecture, Exponential Time Hypothesis, and quantum chromodynamics—and how researchers can verify and build on them.
OpenAI announced three new scientific discoveries in mathematics, computer science, and physics that were produced by AI systems. The findings concern wave behavior in harmonic analysis, computational complexity theory, and quantum field theory. Rather than releasing these results directly, OpenAI is experimenting with involving external academic experts as "shepherds" to help interpret and explain the discoveries to the broader research community, with different release strategies for each result based on expert recommendations. The approach is designed to convert raw AI-generated research into scientific understanding while maintaining transparency, independence, and proper academic credit for the experts involved in explaining the work.
Want to go deeper than the news? Explore live, cohort-based AI courses taught by practitioners.
Browse AI courses on Maven
Less than a month after its mass release of hundreds of manuscripts that it said contained solutions to long-standing mathematics questions, OpenAI is back with three more "major" discoveries in math, computer science, and physics. What's different this time is the choice to have external experts that OpenAI describes as "shepherds" guiding the results in computer science and physics, while for the math problem it says that they advised it to release the AI output for researche

Nace AI has released Drex for Search, which brings its Drex decision models to document search. Drex for Search is a retrieval layer that helps people and agents find evidence. Coding agents such as Claude Code, Codex, Cursor and OpenCode call it through CLI, SDKs, MCP or REST. In Nace’s evaluation, it scores 92.05% on BrowseComp-Plus with GPT-5, using 12.6 search calls per question. TL;DR Size: a hosted search system built to search over 1M+ files. It pairs with an answering model

Anthropic's Claude independently designed protein binders targeting deadly scorpion neurotoxins. Out of more than 318,000 designs, 211 were tested in the lab. Seventeen met the criteria, and the two strongest bind extremely tightly to Cn2, a toxin from a Mexican scorpion. Whether they actually work as antivenom remains an open question. The article Claude Science tackles deadly scorpion stings by designing protein binders from scratch appeared first on The Decoder.
Also reported by The Verge

Microsoft AI chief Mustafa Suleyman. | Getty Images For years, AI leaders have touted healthcare as one of the clearest examples of where their technology will improve lives. Now "it is finally here," Microsoft AI CEO Mustafa Suleyman tells The Verge. The company claims to have developed an AI-powered tool it says can diagnose conditions up to four times more accurately than human doctors. The findings, published Thursday in one of the world's most prestigious journals, Science,

Microsoft’s new AI diagnostic system beat generalist doctors on hard cases, according to a study in Science. But most of the improvement seems to come from the AI models underneath, not from Microsoft’s system itself.

Inception says Mercury 3 is the most capable diffusion language model released so far. The company claims it runs four to eight times faster than GPT-6 Luna and Claude Haiku 5.5 and beats both in eight of 12 benchmarks. There are no independent tests yet. The article Inception's Mercury 3 diffusion model claims to beat GPT-6 Luna and Claude Haiku 5.5 at a fraction of the wait appeared first on The Decoder.