OpenAI hands math, complexity and physics results to outside groups to check

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OpenAI announced that it would hand a set of mathematics, computational complexity and physics results produced by its internal models to outside research groups to be checked — it said it had proved Sogge's 1991 local smoothing conjecture in all dimensions, settling the Kakeya conjecture and the Stein restriction conjecture along with it (result Oct 18, 2026; formalized in Lean the next day); that it had shown the Exponential Time Hypothesis (ETH) to be false (result Oct 16, 2026; formalized in Lean the next day); and that it had proved the existence of four-dimensional interacting quantum field theories including gauge fields and fermions, which covers the existence of quantum chromodynamics and of pure Yang-Mills theory (Yang-Mills generated Sep 9, 2026, quantum chromodynamics Sep 18, 2026; formalized Oct 16, 2026). The complexity group is led by Russell Impagliazzo, Ramamohan Paturi and Ryan Williams and the physics group by David Gross, Michael Douglas, Arthur Jaffe, Igor Klebanov and Nikita Nekrasov; participants are not asked to sign non-disclosure agreements and are not paid.

Why it matters

It put results produced by AI out as research raw material rather than as papers, and tested a way of releasing them that leaves the work of understanding and checking them to academics outside the company. It said it had applied a different release strategy to each of the three results — for the mathematics, only the material released; for the computational complexity, release and a research group in parallel; for the physics, the decision on release delegated to the research group — to see which is useful. The claim that the Exponential Time Hypothesis is false unsettles the premise on which hundreds of conditional hardness results rest, and the existence of Yang-Mills theory is part of one of the Clay Mathematics Institute's Millennium Prize Problems. All of it, though, is company-reported and independent review has not begun — a Lean formalization is a machine check of a proof's logic, not a guarantee that the problem was set up correctly. It gave $5 million to the Simons Foundation to cover the cost of review workshops and conferences.

Source — Primary sources first; secondary reports are labelled “Press”

Officialopenai.comhttps://openai.com/index/building-scientific-understanding-with-academic-communities/

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