OpenAI says its AI disproved the Exponential Time Hypothesis; outside experts will check

OpenAI is claiming three scientific results at once and asking outsiders to check them. In a post dated Oct. 26, 2026, the company said its internal models produced new proofs in harmonic analysis, complexity theory and quantum field theory, and called the manuscripts "a form of raw research data."

The three claims

• Computer science: "Surprisingly, our system has recently proved that the ETH is false, a result that was subsequently verified in Lean," OpenAI wrote. The ETH has been used in hundreds of papers to derive hardness results, according to the company.
• Math: a proof of Sogge's 1991 local smoothing conjecture in every dimension, which OpenAI says also resolves the Kakeya and Stein restriction conjectures in all dimensions.
• Physics: a rigorous existence proof for certain four-dimensional interacting quantum field theories, including quantum chromodynamics (QCD). It includes the existence part of the Yang–Mills Millennium Prize problem; The Decoder notes OpenAI says it solved only the existence part, not the mass gap.

Who checks the work

The ETH result will be verified and shepherded by Russell Impagliazzo and Ramamohan Paturi of UC San Diego, who proposed the hypothesis with Francis Zane, and Ryan Williams of MIT. At the group's request, OpenAI published the natural-language proof and Lean proof in its GitHub repository and committed to fund a conference on the implications.

"We are working to verify and examine their proof and determine if it holds up," Williams told Al Jazeera. In an open letter, the three made clear their involvement is not an endorsement of the claim, The Decoder reported.

A physics group led by David Gross, who shared the 2004 Nobel Prize in Physics, with Michael Douglas, Arthur Jaffe, Igor Klebanov and Nikita Nekrasov, has decided to hold off on releasing the AI-produced artifacts and write up the result itself.

Limits

Lean checks whether a proof establishes the statement as written in Lean; experts still have to decide whether that statement captures the intended problem, The Decoder noted. OpenAI said turning the ETH result into practical improvements "will require significant further research," and that it does not seek academic credit for the discoveries.