Jacob Tsimerman, who just won the Fields Medal last month, announced at the awards ceremony that he will soon join OpenAI to conduct AI safety research.
Further reading: Fearing AI extinction, Fields Medal winner takes leave to go to OpenAI! Aiming to tame AI with mathematics
In early August, he and OpenAI research scientist Sébastien Bubeck convened a closed-door summit of about 40 mathematicians at the headquarters in San Francisco. The title of one presentation was 'The End of Mathematics.'
OpenAI research scientist Sébastien Bubeck
The presenter, University of Toronto professor Daniel Litt, said:
It's possible we are ultimately headed towards a world without high-quality mathematical research, where human mathematical expertise has completely vanished.
He believes the extreme outcome is unlikely, but mathematicians must take action.
MIT mathematician Drew Sutherland put it more directly and starkly:
Perhaps we are just the canary in the coal mine; mathematicians are the first to suffer.
Mathematics is chosen as AI's testing ground because it serves as a proxy indicator for high-level intellectual activity—what can be done in mathematics will eventually be replicated in other fields.
AI is Starting to 'Do Math' in Bulk
The direct background for this summit is the intensive release of results.
In May, a yet-to-be-released model from OpenAI disproved the unit distance conjecture.
Further reading: OpenAI completely stuns the mathematics world, cracking an 80-year-old core conjecture! Fields Medal winner exclaims he couldn't sit still
This old problem concerning 'the arrangement of points on an infinite plane' had remained unsolved for years. The AI used a known but difficult-to-manipulate technique from algebraic number theory, effectively crossing subfields to apply tools.
Tsimerman's assessment at the time was that he would 'accept without hesitation' this result in any journal.
This is viewed by many mathematicians as AI's first major mathematical breakthrough.
Subsequently, results have poured out one after another.
In August, OpenAI announced ten AI-generated discoveries in mathematics and computer science at once, covering multiple subfields that typically take years to master.
Further reading: Sudden! OpenAI's next-generation AI conquers 10 Fields Medal-level problems
Anthropic has also been busy.
Anthropic employee Levent Alpöge used Claude to assist in constructing a pair of orthogonal vectors on a 668-dimensional hypercube.
Mathematicians have long believed such a construction existed, but no one had actually built it.
Alpöge announced the result by posting on X: a 24,000-character thread consisting entirely of plus and minus signs.
https://x.com/__alpoge__/status/2087504785952182273
Traditional mathematical research follows a fixed pipeline: seminar discussions, circulation among peers, posting on the preprint server arXiv, and finally publication in a journal after peer review.
AI-generated results are bypassing this pipeline.
Dmitry Rybin, an entrepreneur based in Shenzhen, asked ChatGPT to 'make a breakthrough' to disprove a network flow hypothesis. Every time the model failed, he encouraged it to continue, acting as an AI cheerleader.
ChatGPT eventually provided a counterexample. After verifying it, Rybin posted a tweet. At the time, he was watching a movie with friends.
https://x.com/DmitryRybin1/status/2079904005652893709
Further reading: GPT-5.6 disproves a 30-year-old graph theory conjecture! Peking University alumnus solves 6 problems in 5 days
Mathematician David Bessis raised doubts about this:
You post on Twitter saying you proved a big problem while cooking pasta? Of course it will go viral.
The question is, what happens after it goes viral? Who organizes this pile of things, who figures out what's really going on?
Last week, Anthropic also announced that one of its employees had their internal version of Claude 'give it a serious try' on the Riemann hypothesis.
The Riemann hypothesis has remained unsolved for over a hundred years, with a $1 million prize offered for its solution.
Under repeated prompts like 'continue' and 'think again,' the model produced new discoveries on a related problem.
Further reading: Sudden, Claude sets a new record on the Riemann hypothesis!
3000 People Signed a Petition, Then What?
The reaction from the mathematics community is divided.
In June, an open letter titled 'The Leiden Declaration' was released, signed by over 3,000 mathematicians.
Further reading: Setting rules for AI! Mathematicians panic as AI just solves an 80-year-old math problem
The letter calls on researchers to use AI tools responsibly, ensuring results are verified and citations are proper.
Another group of mathematicians has gone further, advocating for a complete rejection of AI and AI companies to preserve humanity's place in mathematics.
Northwestern University mathematics professor Bryna Kra attended the summit and is also one of the 16 initiators of the Leiden Declaration.
She said:
The core of mathematics is understanding results, not just proving them.
A proof that is not understood does not become part of the literature.
AI can prove theorems, but can it explain how it proved them?
Harvard University mathematician Melanie Matchett Wood helped write the human-readable version of the proof for OpenAI's unit distance conjecture result.
She found that top AI models share a common flaw in explanation: they elaborate extensively on simple parts but gloss over the difficult parts.
She said:
Top AI models are not yet capable of identifying the truly difficult parts of an argument and explaining them clearly.
German mathematician Andreas Thom offered a more precise distinction.
One of the ten new results announced by OpenAI was a new construction related to 'non-sofic groups,' filling a gap between two papers by Thom and his collaborator Gábor Kun in 2016 and 2019.
The two subsequently published a follow-up paper, simplifying and extending the AI's discovery.
Thom said:
The AI is solving problems in a very intelligent, substantial way.
But new concepts only emerged after human involvement in the proof process; that's not something AI has achieved on its own yet.
Faced with this division, summit organizer Bubeck described four possible futures after the meeting:
Mathematics becomes like software engineering, with AI helping hundreds of people collaborate to tackle the same problem;
Becomes like physics, relying on massive computing power and AI models as substitutes for particle accelerators;
Becomes museum curation, with AI responsible for production and humans responsible for selection and interpretation;
Or mathematicians collectively transition to working on AI safety.
Bubeck said:
We must put people, put mathematicians, first.
Mathematics only makes sense when mathematicians learn something from it.
'A civilization without people is meaningless.'
But the 40 attendees did not reach a consensus.
Tsimerman said:
There is no conclusion yet on what the mathematics community wants.
The purpose of this meeting was more to start a conversation than to make a specific decision.
He himself has not officially started at OpenAI.
The fact that a Fields Medal winner chooses to go to an AI company to do safety research is itself a microcosm of the mathematics community's predicament.
As for what he does next, the next signal may be more noteworthy than the presentations at this summit.
References:
https://www.washingtonpost.com/technology/2026/08/19/mathematicians-ask-whats-left-humans-when-ai-can-do-math-research/
This article is from the WeChat public account "New Zhiyuan", author: ASI启示录, editor: Marco
