“We all know that OpenAI is not doing this “for the good of science”. These pdfs are exhaust fumes from their internal benchmarking effort.”

Not to toot my own horn but she's making exactly my point. The companies are producing normal bad work. Expert academics can do the same with available tools

In this interview Strogatz manages to reinforce plenty of the worst cliches about mathematicians: they're all men, Erdős was completely unable to live a normal life and popped amphetamines all the time, Perelman never cut his fingernails, etc. He analogizes the pleasure of solving math problems to masturbation. And the strange part: he seems to think this is all most charming. It's part of…

In a general-public piece, I discuss how ideas can go from a conversation with an AI tool to a mathematical proof.

It leads me to wonder, how much plagiarism is there in the mathematical genius of bi AI?

This was just the same when OpenAI just slung a zip file with "proofs" that they hadn't verified. Many mathematicians hated it since making proof is about further the field through collaboration and building on already existing paper. What OpenAI did was just to shoot an shotgun through a wall.

This touches on something I have been thinking about. #Mathsky

I don't think we will ever get a 'community' answer to genAI in mathematics. For the simple reason that the community is too big (mathematics is one of the largest fields of science), the answers will be context- (and country) dependent

Here is one practical thing that many places have done for years: you only get to attach 3 papers, those are the only ones that will be looked at by the committee.

The game theory changes, because suddenly any additional low effort papers become uncounted wasted effort. You encourage strong work

The power lies with department hiring committees. When you fail to announce what you look for, that is creating the uncertainty for junior folks

I'm tentatively understanding the news about LLMs offering barely comprehensible solutions to hundreds of hard maths problems in the following way. #Maths is symbol manipulation according to set rules. You can do this task by training an LLM on a lot of maths writing. You don't actually have to understand maths to do maths, as long as you stick to the symbol manipulation rules. Nor does an LLM und…

Oh God, this is getting even worse: apparently the "source" of the claim that AI might have broken classical cryptography is the fact that some numbers are skipped in the OpenAI math dump. You know, that same dump that doesn't even have formal verification on more than half of the results and […]

Here's how Radchenko and Wheeler wrote about Imran Zaidi's LLM-generated proof: "While the proof seemed correct, it was not presented in a format that was easy or fun to check. We were left with three choices: do nothing, continue working at our pace and ignore LLM assisted proofs, or make our own LLM assisted proof. The first option was unacceptable based on the importance of the pro…

https://arxiv.org/abs/2610.08144 is interesting read about the navier stokes #math #ai result. I guess it must be relevant to the recent math dump

Seeing this metaphor of 'conjecture as lighthouse' a lot lately. I don't like it, I thought lighthouses are a thing you should avoid (at risk of sinking and drowning). Can any lighthouse expert weigh in on this?

Many have posted the news story below. I have three responses.

(1) I am not a fan of offloading human cognition onto genAI.

(2) But I think the research article in question has, potentially, some serious problems.

(3) If we are going to critique AI, it MSUT be on the basis of solid evidence.

I mean, this will all have to be done outside the auspices of OpenAI, because OpenAI clearly does not care.

But if mathematicians could self-organize and distribute the task of digging through the results, akin to something like the Polymath project, this could have a worthwhile outcome.

Oh look, AI guys dumping a whole bunch of slop on someone who's expected to check if it's right

Is it a math proof or a retro decomp, surprise surprise it's actually your whole work inbox

My mathematical studies are far remote in time, but I still remember that a "proof" which can not be checked isn't a proof.

My take is that sorting through and vetting the OpenAI dump should be considered important, publishable, career-advancing work.

Ideally the tasks could be distributed in a an organized way to those who are interested and could benefit from the recognition.

Technically you get the answer, but that’s not the point.

Quotes that bother me below.

The big one is that they won’t release the prompts. They want it to look like they presented the problem and got the proof but clearly something else is happening here.

Someone told me today that OpenAI “solved math” and mathematicians are freaking out because there’s no point in doing math anymore. And then I saw that some mathematicians have already looked at some of those results and found new, more elegant proofs or have improved the bounds in some of the results. OpenAI didn’t “solve” anything. Because math is more art than it is science. It can’t be “solved…

The problem with big names praising "breakthroughs" by OpenAI is that it gives OpenAI a pass on mostly sloppy and sometimes incorrect proofs, treating them as "machine things" that we should accept as a "small price". Would love to see them read the proofs and then write their understandings.

I know it is so important to keep saying this and yet I remain baffled that people COULD EVEN THINK THAT genAI HAS THESE THINGS.

Formal verification of AI agents, whether super-intelligent or not, has been proposed as a wayto AI safety. This cannot address that AI agents are being asked to make synthetic truth statements most of the time. We have no logical theory of the world that can verify "there is a duck in this photo."

The "inadequacy of translation" problem with @openai-m.extwitter.link 's claim to have settled the Navier-Stokes finite-time blow up problem is related, in Quine's mind, to the analytic/synthetic truth distinction that makes formal verification of experts a fool's errand for AI safety.

But mathematicians reading these proofs seem to often have a hard time, meaning that they're not great at aligning the formal stuff with our intuitions (yet). I'd also take this as a little evidence arxiv.org/abs/2610.08144

Holy shit! OpenAI solved the unit addition conjecture! I've been pondering over this question for 30 years and now they come up wth this and just tell me they solved it? My entire math career is ruined! #Math #AI

Not to mention that you can go over someone's proof and verify it step by step and yet completely fail to understand it. A proof that a statement is correct can work for someone as a certificate, yet still fail its most crucial goal.

OpenAI withdraws three algebraic geometry manuscripts from its math repository, with about 42% of headline results now machine-checked in the Lean proof assistant

i’d love to spend a billion tokens asking frontier models which millennium prize question they think is the easiest

it is on going. i mean they retracted 3 and then i heard the hodge proof had a sign error. a fucking sign error! i don't trust the model to be doing formalization well enough for this whole thing not to be a flop. i think the low-level and some mid-tier results will survive but the big ones will

Anyway the thing I'm wondering why most is that apparently with the openAI math proof dump they fed in 8,000 questions and a bit less than 800 got a proof. So for that ~90%, what did it do? That they're not also posting their failures isn't very academically rigorous of u.

Mathematician: Who at OpenAI can I contact about you using my results without credit?

OpenAI: No one

Oh, they can certainly use this to advance their subject. I think there’s a subtlety here.

The advancement does not begin, in their mind, until humans understand it. The mere production of a proof is meaningless unless or until it is understood.

OpenAI has fired three safety researchers, alleging they mishandled confidential information. (...) I was pushed out of OpenAI in August after ~5 years as a researcher. No foul play in my case, but working on formal math & verification in Lean at OpenAI was career suicide. (...) Oleg Mürk

When do we get our first GPT-stated Millennium Prize problem?

Do undergraduates study lean on a #math degree these days. I would like to see an text at that level

I suggest that the right attitude to take toward the OpenAI math release is to imagine we have discovered a notebook full of results from a deceased mathematician. Our job is to make sense of the notebook.

One very specific lie is that the OpenAI proof of finite time blowup for Navier-Stokes was stolen from Tristan Buckmaster (in the process of his collaboration with Alpöge). In fact, Buckmaster has never claimed to have a proof of Navier-Stokes, and the most extreme possibility Buckmaster…

that the IAS in Princeton legitimizes now this Open AI trash is just another proof how right wing and anti-emancipative this institute is. Founded by Oppenheimer, they were always WHITE, had fascist, reduced conceptions of math and were all around real douchebags www.ias.edu/math/people/...

Do we still need mathematicians?