OpenAI 分享称，其内部智能体系统使用比 GPT-6 Astra 更强的下一代模型，提出对 Navier-Stokes 方程光滑三维流体运动是否会突然失效这一约 90 年未解问题的解，并同时公开证明文稿与 Lean 形式化版本。
原文给出智能体搜索的耗时与 token 消耗，可了解大规模智能体协作做数学研究的具体形态。
MASSIVE: OpenAI's 10,000 AI agents, powered by a model significantly more capable than GPT-6 Astra, solved a math problem unresolved for roughly 90 years.
Looks like, in this new world, the scaling law may be agent count, not model size: enough capable agents can search far more scientific ideas than any human group ever could.
when tens of thousands of strong agents can explore, criticize, and combine ideas, many problems that are "too hard" today may become mostly a compute problem.
For this one, for 90 years, mathematicians could not answer whether smooth 3D fluid flow can suddenly break down. OpenAI's proposed proof says it can.
To find this solution, OpenAI split thousands of agents into groups exploring different ideas, then shared the best findings between them.
The search took 88 hours and used about 130B output tokens across 2.7M messages.
GPT-6 Astra then spent another 17 hours checking and converting the proof into Lean, a system that verifies mathematical proofs.
That Lean version is public, so mathematicians can inspect the argument themselves.
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.在 X 查看被引用的帖子
来源：@rohanpaul_ai · x.com