2026-10-11 16:34 UTC

OpenAI releases a broad batch of mathematical results from its internal frontier model on GitHub with Lean proof formalizations, per-result compute estimates (~3 hours of ChatGPT Pro thinking on average), and release protocols developed with IAS's independent AGMAI β€” whether the math community verifies the results and other labs adopt the advised-release protocol resolves whether structured third-party-advised release of AI-generated mathematics becomes standard practice.

state: acceleratingheat: highuncertainty: mediumconvergesscott: highai-assisted-mathematics lean-formalization release-governance agmaiOpenAIAGMAIInstitute for Advanced Study

What is this?

On October 6, 2026, OpenAI published 722 mathematical manuscripts (372 result families) on GitHub, produced by an unreleased internal frontier model, with Lean 4 formalizations for many results, per-result compute estimates (~3 hours ChatGPT Pro equivalent), and a release protocol developed with the independent Advisory Group on Mathematics and AI (AGMAI) at the Institute for Advanced Study. Three results have since been withdrawn (confirmed via GitHub history), making the AGMAI-advised protocol's quality control a live stress test. Community verification is underway: the Lean repository compiles; one named expert review (Barnette #180) is favorable; a substantive critique notes headline claims not matching formalized statements in β‰₯10 families; Terence Tao has blogged on Lean reliability and amplified an Association for Human Mathematics statement urging mathematicians to discontinue work with OpenAI; Fields Medalist Hugo Duminil-Copin reacted viscerally. Two independent Lean-verified building-on artifacts exist (CrocSwap/integer-mult-bounds improvement; DaniilKi/simplex-product-growth extension), both single-group and unaudited. No completed expert verification of the core batch, no confirmation of AGMAI's September 29 primary recommendations (rumored to contradict OpenAI's framing), no second batch, and no cross-lab protocol adoption have been confirmed. Mainstream coverage includes NYT, Scientific American, The Verge, and The Conversation.

Why it matters to Scott

This case is a live, multi-community field test of several load-bearing frameworks in Scott's canon: the Governance Stack's Authority Infrastructure layer (AGMAI as independent advisory), Verification Loops (Lean formalizations + community audit as iterative quality control), the Formalisation Bottleneck (Lean proofs as the new scarce constraint), Mechanically Different Verifiers (Lean compilation, expert review, and community audit as independent checks), Publishing Is an Active Sensor (the release as a concept-sized probe), Rational Resistance / Institutional Failure Radar (AHM/Tao organized pushback as calculated institutional cognition), Borrowed vs Transferable Authority (whether AGMAI's advisory role carries portable legitimacy), Externalised Risk (verification burden shifted to the community), and Validated-release preview boundary (withdrawals stress-testing the protocol's quality gate). The scope-note critique revealing headline/formalization gaps in β‰₯10 families directly exercises Claim-bounded adversarial verification. Two concrete Lean-verified building-on artifacts (CrocSwap, DaniilKi) test formalization uptake. This is not merely an example β€” the case's unresolved variables (AGMAI primary text, completed expert verification, cross-lab protocol adoption) would change what Scott builds and argues.
ip:framework.the-governance-stackip:concept.verification-loopsip:concept.formalisation-bottleneckip:concept.mechanically-different-verifiersip:framework.publishing-is-an-active-sensorip:concept.rational-resistanceip:framework.institutional-failure-radarip:concept.borrowed-authorityip:concept.transferable-authorityip:concept.externalised-riskip:concept.proof-carrying-receiptsip:dev:concept.validated-release-preview-boundaryip:dev:concept.claim-bounded-adversarial-verificationip:dev:concept.review-until-clear-loopip:concept.verification-boundaryradar:agmai-openai-math-release-adviceradar:concept.ai-assisted-mathematicsradar:concept.lean-formalizationradar:concept.formal-verificationradar:concept.ai-for-scienceradar:concept.release-protocolsradar:concept.vulnerability-disclosureradar:concept.ai-governanceradar:person.terence-taoradar:person.openairadar:tao-math-2-0-visionradar:frontiermath-tier3-saturation
queries asked of Scott's wikis
  • governance-stack authority-infrastructure independent-advisory-groups
  • verification-loops formal-verification lean-proof-assistant community-audit
  • release-protocols responsible-disclosure ai-generated-science third-party-advised
  • ai-assisted-mathematics formalization-uptake proof-assistant-adoption
  • institutional-resistance ai-in-science fields-medalist-pushback
  • model-sovereignty closed-model-release compute-transparency

Measured heat

now 51 pts/hpeak 1093 pts/hcomments 13/hpeers p97momentum: cooling3 platformsage 124h
points/hour across evidence Β· reading as of 2026-10-12 02:59:37.977291+11:00 Β· deterministic, not a model opinion

How the heat travelled

10-06 12:00⭐ origin directly observedSharing AI progress in mathematics
OpenAI on openai
β€”
10-07 06:34first on hacker news Β· published Β· +18.6hOpenAI unleashes hundreds more math results upon a field in shock
mr_fantastic
β€”
10-07 14:17first on r/singularity Β· published Β· +26.3hRumor from an NYU math professor that this was only batch #1 of 3 of OpenAI math solutions…
socoolandawesome
β€”
10-07 17:56first on r/artificial Β· published Β· +29.9hOpenAI unleashes hundreds more math results upon a field already in shock
scientificamerican
β€”
10-08 03:38first on r/OpenAI Β· published Β· +39.6hFields Medalist Terence Tao reposts statement from the Association for Human Mathematics urging mathematicians to stop working with OpenAI for continuing to solve open math problems against their recommendations
Eliv_nurotic
β€”
10-07 06:34amplified on hacker newshn.story.49989115
mr_fantastic
peak 9 Β· 2 comments Β· 0% of case engagement
10-07 14:17amplified on r/singularityreddit.post.1wzxpir
socoolandawesome
peak 507 Β· 258 comments Β· 5% of case engagement
10-07 14:35amplified on hacker newshn.story.49993463
krunck
peak 2 Β· 2 comments Β· 0% of case engagement
10-07 17:40amplified on r/singularityreddit.post.1x030cj
Southern-Break5505
peak 544 Β· 136 comments Β· 4% of case engagement
10-07 17:46amplified on r/singularityreddit.post.1x035ne
Anen-o-me
peak 337 Β· 65 comments Β· 2% of case engagement
10-07 17:56amplified on r/artificialreddit.post.1x03feu
scientificamerican
peak 14 Β· 35 comments Β· 0% of case engagement
46 more amplifiers in ainews.case_chain
10-07 06:21our radar first saw it Β· +18.4hdiscovery anchor: openai.article.270d2009beef3a33ff16c116β€”
10-08 13:59reached heat=high Β· +50.0h Β· via queue+ledgerβ€”β€”
pace: p99 vs 1247 stories at the 96h mark (now 124h old) β€” ahead of gemini-4-argon-release (1.1x), behind anthropic-fable-mythos-51-release (0.9x)

Evidence (53) β€” ⭐ canonical anchor

sourceobjectauthorscorecomments
🟧 openai ⭐Sharing AI progress in mathematics
Retrieved article excerpt

Open article Β· Retrieved 2026-10-07T06:21:44.263828+00:00

October 6, 2026

[Research](https://openai.com/news/research/)[Publication](https://openai.com/research/index/publication/)

# Sharing AI progress in mathematics

[View on GitHub(opens in a new window)](https://github.com/openai/math)

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We’re releasing a broad range of new mathematical results produced by an [internal frontier model](https://openai.com/index/navier-stokes-solution/).

As we look to improve how we share results with the math community, we’ve been consulting with the independent [Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study⁠(opens in a new window)](https://agmai.org/) to develop best practices, and we have drawn on their advice and [public recommendations⁠(opens in a new window)](https://agmai.org/general-sep29/) to inform how we release these results.

For this release, we’re publishing the results in a GitHub repository, with protocols for paper revisions and citations. We’re continuing to explore other community-hosted alternatives for this release which meet the committee’s guidelines. For future releases, we are committed to further improving the quality of the papers via the citations, mathematical exposition, and presentation of the results for better understanding.

As part of our GitHub repository, we are sharing formalizations of many of the proofs in Lean, a programming language that allows mathematical proofs to be checked by a computer. We will update the repository with more formalizations as we obtain them.

To promote scientific transparency and openness, we are also publishing additional details about how we obtained the results in the repository. These include 10 summaries of the model’s reasoning, estimations of compute spent in terms of Pro usage on ChatGPT, and statistics about the number of attempted problems. The average result used the equivalent compute of roughly three hours of ChatGPT Pro thinking.

We want this progress to push the frontier of human knowledge and enable further progress in mathematics. We will be funding a series of workshops, conferences, and special programs around the understanding of major results produced by AIβ€”we will share more on this in the near future.

We want to directly empower scientists with state-of-the-art capabilities and are working to responsibly release the model that produced these results. This is why it is important to continue to evaluate our internal frontier models on mathematics and other sciences, so we can accelerate developing the tools to advance those fields. We will continue to act on feedback from the community and update our standards for future disclosures of major scientific advancements.

- [2026](https://openai.com/news/?tags=2026)

## Author

OpenAI

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Interpretation history

Decision trace