OpenAI published 722 math manuscripts across 372 result families, all produced by an internal model it has not released. About 300 come with Lean formalizations a machine can check, Crypto Briefing reported, so the rest wait on human reviewers whom one mathematicians' group is urging to stop working with OpenAI.
Perspective Coverage
3 publishers
- Builder
- Builder 30%
- Operator
- Operator 47%
- Investor
- Investor 23%
Reality
- Evidence55
- Adoption20
- Hype gap+35
- Incentives65
- Confidence55
buildConfirmed6 publishers OpenAI posted 372 results from an internal model to GitHub, at about three hours of ChatGPT Pro compute each on average. Finding proofs is now cheap enough that the slow step is mathematicians checking and judging them.
Perspective Coverage
6 publishers
- Builder
- Builder 44%
- Operator
- Operator 31%
- Investor
- Investor 25%
Reality
- Evidence58
- Adoption10
- Hype gap+35
- Incentives72
- Confidence60
OpenAI hands its new math advisory panel a backlog of results from an unreleased model
OpenAI's new mathematicians' panel must first help release scores more results the company says an unreleased model produced. Researchers call the panel a good first step, though many are unsure how much say it will have over how OpenAI announces what its models find.
Reality
- Evidence45
- Adoption
- Not scored
- Hype gap+25
- Incentives65
- Confidence40
Epoch AI enlists mathematicians to pick 50 open problems a computer can check
Epoch AI, which benchmarks AI systems, had mathematicians nominate 50 high-stakes open problems chosen so a computer can check any proposed solution. The rule lets research mathematics be graded as a test of AI, but only problems whose answers a machine can confirm get in.
Reality
- Evidence45
- Adoption
- Not scored
- Hype gap+25
- Incentives60
- Confidence40
Terence Tao names AI's arrival in math research a crisis in the field's values
Scientific American's account from the mathematicians' congress in Philadelphia has a Fields medalist quitting for OpenAI and a Millennium Prize problem falling to an opaque mix of models, with no verification trail reported for either.
Reality
- Evidence30
- Adoption35
- Hype gap+45
- Incentives65
- Confidence35
A prompt to an unreleased Claude lifted the elliptic curve rank record from 29 to 31
Levent Alpoge and Ava Howell used a simple prompt to an internal Claude and got elliptic curves of rank at least 30 and at least 31 in days, in a field where the last single-rank step took more than 18 years.
Reality
- Evidence27
- Adoption14
- Hype gap+40
- Incentives68
- Confidence45
buildConfirmed3 publishers Their joint statement argues that famous open problems were only ever a proxy for understanding, and that benchmarks miss the years of talks and simplifications that follow a proof.
Perspective Coverage
3 publishers
- Builder
- Builder 40%
- Operator
- Operator 43%
- Investor
- Investor 17%
Reality
- Evidence72
- Adoption58
- Hype gap+18
- Incentives68
- Confidence70
OpenAI gave two different answers about Buckmaster's Codex prompts in one week
Tristan Buckmaster told the ABC that the game is up for mathematicians. In the same week, OpenAI described what his Codex prompts did to its models in two incompatible ways, and a customer has no way to pick between them.
Reality
- Evidence34
- Adoption22
- Hype gap+45
- Incentives76
- Confidence42
A mathematician kept a year of unpublished drafts in Codex, then asked whether they had been used for training and got silence on that half of the question, which is the half every enterprise rollout treats as settled.
Reality
- Evidence52
- Adoption30
- Hype gap+32
- Incentives78
- Confidence60
Mathematicians set the verification bar for AI proofs by shipping the Lean file
OpenAI says roughly 10,000 agents produced a Navier-Stokes singularity proof in about 88 hours, but the only proofs an outsider can run belong to two mathematicians who posted Lean formalisations with their preprints.
Reality
- Evidence42
- Adoption22
- Hype gap+45
- Incentives78
- Confidence52