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5 entries with this tag
One new research article published: OpenAI's announcement of a Navier–Stokes Millennium Prize solution produced by ~10,000 AI agents in 88 hours, with Lean 4 formalization and a major credit controversy involving NYU mathematician Tristan Buckmaster.
On September 8, 2026, OpenAI announced that an internal model — significantly more capable than GPT-6 Astra — coordinated approximately 10,000 AI agents to produce a solution to the Navier–Stokes existence and smoothness problem, one of the seven Millennium Prize Problems. The proof shows that smooth 3D fluid motion can develop a singularity in finite time, formalized and verified in Lean 4. The announcement triggered immediate controversy over credit, with NYU mathematician Tristan Buckmaster alleging OpenAI accelerated its work after learning of his and Levent Alpöge's parallel research on related Euler equations.
One new research article published: comprehensive analysis of OpenAI's GPT-5.6 family launch — Sol (flagship), Terra (balanced), Luna (fastest/cheapest) — with ultra multi-agent mode, Cerebras-powered speed, Programmatic Tool Calling, and the most robust safety stack yet. Luna priced at $0.20/$1.20 after 80% cut.
On August 13, 2026, OpenAI launched the GPT-5.6 family — Sol (flagship), Terra (balanced), and Luna (fastest/cheapest) — with ultra multi-agent mode, Cerebras-powered speed (up to 14×), Programmatic Tool Calling, and the most robust safety stack to date. Sol sets SOTA on Agents' Last Exam (53.6), Coding Agent Index (80), BrowseComp (92.2%), and OSWorld 2.0 (62.6%). Luna prices at $0.20/$1.20 per million tokens after 80% cut. Covers architecture, benchmarks, ultra mode, pricing, safety framework, and strategic implications.
OpenAI revealed its next major model family, Astra, by publishing ten solutions to long-standing open problems in mathematics and theoretical computer science — each with machine-checkable Lean 4 certificates. Covers the ten results across eight domains, the multi-agent long-horizon architecture, $2,000 total compute cost, the Leiden Declaration context, and what this means for the future of mathematical research.