# Unite.AI — OpenAI Says Its Models Produced Three Proofs in Math, CS, and Physics

- Company: Unite.AI (unite.ai)
- Announced: 2026-10-26T22:17:01+00:00
- Category: research-paper
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://www.unite.ai/openai-says-its-models-produced-three-proofs-in-math-cs-and-physics/
- Record: https://forck.live/items/28024-openai-says-its-models-produced-three-proofs-in-math-cs-and-physics
- Subject: Reporting

OpenAI says its internal models produced three research results in mathematics, computer science and physics, including a disproof of the Exponential Time Hypothesis. The company calls the AI-generated manuscripts raw research data that must still be converted into scientific understanding, and it is testing three release strategies. External experts acted as shepherds, advising that the mathematics output be published directly while the computer science and physics results get collaborator groups. The collaborations follow four principles: transparency with no nondisclosure agreements, no academic credit for OpenAI, recognition for each group's materials, and voluntary unpaid participation. OpenAI obtained the mathematics output on October 18, 2026, formalized it in Lean the next day, and published an AI writeup and Lean proof in its public GitHub repository. The computer science disproof, produced on October 16, 2026 and formalized in Lean on October 17, will be shepherded by a group led by Russell Impagliazzo, Ramamohan Paturi and Ryan Williams. OpenAI agreed to make all raw data public and to fund a conference on the work's implications, and says it does not yet know which release approach will prove most useful.

## Evidence

Verbatim from https://www.unite.ai/openai-says-its-models-produced-three-proofs-in-math-cs-and-physics/:

> OpenAI said in an announcement on October 26, 2026, that its internal models produced three research results in mathematics, computer science, and physics, including a disproof of the Exponential Time Hypothesis, a longstanding conjecture in computational complexity theory.
> 
> In the company’s view, the AI-generated manuscripts amount to raw research data that must still be converted into scientific understanding, and it is experimenting with a new release approach toward that end. OpenAI asked external experts to act as shepherds, organizing groups to understand the new results, and said the shepherds advised three different release strategies: release the mathematics AI output directly, with researchers free to organize their own explanatory work; form an external group of collaborators for the computer science result while publishing the AI output for anyone to examine and build on; and form such a group for the physics result while deferring to it on the release of materials. The company said it does not yet know which of the three approaches will prove most useful and invited feedback on what works and what can be improved.

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