I knew mathematicians were a smart bunch, but honestly, the events of the past few weeks have really given me a new level of respect for them.
They might be the first community I've seen to experience the AI "rush" and (at least as presented to an outside observer) immediately come together, assess the situation, and calmly, empathetically, and rationally act. They evaluated what AI is good at and what it lacks. They've thought through how it'll likely affect their field in the future. They've explained where the need for humans still lies, and made clear proposals for how to change their own field and for what demands to make of AI companies. Of course they're not all on the same page, but they're at least talking and trying.
They haven't started worshipping the machine god and loudly claiming their whole field is solved. Nor have they flailed wildly at LLMs as if complaining enough about it will make them go away.
Every major statement I've seen come out of the math community on this matter reads as well thought-through, humble, reasoned, and deeply human.
In these days of fear, uncertainty, and obsolescence anxiety, honestly, they've given me some confidence that maybe we will figure this stuff out after all. Maybe we'll learn from them. Who knows.
> I knew mathematicians were a smart bunch, but honestly, the events of the past few weeks have really given me a new level of respect for them.
As a mathematician, I am a bit disappointed by my (admittedly illustrious) colleagues.
I get the need to take it slowly (and I am a quite impatient person, so I shouldn't get to decide stuff like this), but everything said feels a bit too sour grapes for my taste.
Ok, maybe AI did not solve the field (I believe it will, btw), maybe there is a need for human "understanding", but:
1) They don't seem to consider even the possibility (not the certainty) that they might be wrong, that math as we know it is gone, and we cannot "adapt"
2) They seem to have been oblivious all these years about AI eventually reaching this point (at least I personally wasn't, I predicted this stage back in 2018)
Regarding 1, it's not clear what you want them to actually do. Would you rather they just gave up, rolled over and died instead of at least trying to rescue their field? What is to be gained from considering this?
I suppose you could say, hypothetically, that if the field were “solved” then the protection of the feelings and sense of need for human understanding of the now obsolete practitioners might hinder any benefits that the now solve field could provide.
The answer to this is probably just “get out of the way” and then your “work” would be to develop a better appreciation of what has been produced.
> The answer to this is probably just “get out of the way” and then your “work” would be to develop a better appreciation of what has been produced.
They aren't in the way. AI labs can do their own math all they want, and nobody is stopping them. Rather, mathematicians are simply speaking about the topic.
If LLMs could both prove any relevant theorem, explain such a theorem cogently and lay the groundwork for further theory, I don't see how any way mathematicians could stand in the way of that.
I think I'm mostly on your side (also I believed early it would get here), but what does it mean to "solve the field"? I'm pretty much as bullish as you get on AI but I'm sure I can come up with questions AI cannot solve. I think the space of problems in math is so large and the distribution of proof lengths so heavy-tailed, there's probably no way without dyson-sphereing the sun to solve all easy to state problems.
As a Nobel Prize winner, I am surprised that you have not noticed how Tao and Gowers were steering everyone in the AI direction for years and now do damage control by nudging everyone to either hypothetical open models paid for by industry or the EU or sitting in a committee that "advises" OpenAI.
No one is saying "Perelman and Wiles didn't need that silly AI and N-S was more of a counterexample". Most people imagine the sky is falling.
What if OpenAI is stalling because they don't have 100 additional unpublished proofs as claimed?
> As a Nobel Prize winner, I am surprised that you have not noticed how Tao and Gowers were steering everyone in the AI direction for years
I did notice, this is why I had thought that they had thought through the consequences. But, unfortunately, it is likely they imagined that AI would plateau somewhere around the "smart undergraduate" level and that they will stay relevant in pure problem solving.
Their field is extremely rigorous. As rigorous as it can possibly get in that they have to prove each and every line of their work beyond any doubt. The discipline they have cultivated in their culture shows in their response to AI as well.
As opposed to some other fields in which rigor was either not part of the culture or was not always possible. For e.g., software engineering in terms of code quality being produced. There were some indirect signals here and there but they are all subjective.
No, I don't think they are adapting well. I've seen 3d designer at my company adapting better on the disruption and paradigm shifts GPT-6 Astra is going to cause.
The 3D designers are in a tougher situation because it's far less of abstract issue then math, and yet the results are astounding. It's hard to believe until you see it yourself. It's surreal.
I don't really get it, seems like a gate keeping exercise for the academic community.
Of course OpenAI and others will hype any LLM led/assisted research results, and the media will find juicy headlines to write about it. But in the end they are publishing findings, and the academic community can gauge the developments and decide what they want to do with them. To me that seems like research working as expected.
The purpose is obvious - AI companies are using math to as a PR tool to demonstrate that AI is more capable than humans. This devalues math and mathematicians. There is even a relevant announcement from today, where OpenAI announced they solve 100 open math problems, without even bothering to state what they are.
However, even if they are successful in removing math from the PR toolkit of AI companies, I can’t see it more than a short term band aid. If AI progression continues, the announcements will just transition from big flashy one, to a kid using Claude on their laptop.
I don’t have a solution here, and I’m worried it’s coming to all human fields. So it’s more of an ability to observe what might happen to all of us.
> There is even a relevant announcement from today, where OpenAI announced they solve 100 open math problems, without even bothering to state what they are.
This group has been formed to tell OpenAI whether or not (and if yes how) they should release those 100+ problems.
IMO “AI companies are using math to as a PR tool” is not quite it; they are using math problems as a benchmark to evaluate their AIs, but after the prior blowback from the mathematical community, they are happy to sit on the results until the community (this group) tells them how to publish the results.
And as you say, even if they don't publish the results eventually anyone will be able to do this when this model is released, so it's just a matter of time.
> I don’t have a solution here, and I’m worried it’s coming to all human fields. So it’s more of an ability to observe what might happen to all of us.
You can also look (as I did back in 2018 when contemplating the end of math) at how chess or Go players adapted mentally to the idea that whatever they may do, a machine could do it better (Lee Sedol famously quit Go).
These math problems don't exist in a vacuum. It's not like mathematicians are doing mathematics just for the funsies.
Calling it a publicity stunt is an interesting way of framing ground breaking discoveries. The beneficiaries down stream of these discoveries could not care less how they were found.
> It's not like mathematicians are doing mathematics just for the funsies.
Someone please correct me...
I thought mathematicians did mathematics specifically for the funsies. It's a hell of a challenging endeavor that's not particularly well compensated. Maybe to some it's a calling moreso than funsies, but it's still overwhelmingly intrinsic motivation no?
Interestingly, all mathematicians could stop work today and every one of the field's previously accomplished works continues to remain accomplished. Math needs no KOTL rotation.
> If I thought this was a good thing to do, this would be a great group of people to do it. But I have immediate misgivings. OpenAI has had some very bad publicity, and so they are trying to exploit the trust and respect that these mathematicians command. It is unrealistic to think that this group can change the way OpenAI does business; I don’t need to tell you all the objections that people have raised to that. Is it a good idea to help their crisis management?
(FRS, UCLA professor of algebraic geometry and topology, with work influenced by the Hodge conjecture, one of the remaining Millennium Prize problems).
I really wish the models were smart enough to "tail their own logs" and tell us whose work/papers/chats were the catalyst for these math insights. What makes their "internal" model so much better at math? Must be trained on a whole lot of honesty.
Why aren't they consulting the younger mathematicians whom this actually affects?
Anyways, this is overblown. Let me know when AI swarms can create a research program or library from scratch. We're really missing long term planning and abstraction creation in these things.
I knew mathematicians were a smart bunch, but honestly, the events of the past few weeks have really given me a new level of respect for them.
They might be the first community I've seen to experience the AI "rush" and (at least as presented to an outside observer) immediately come together, assess the situation, and calmly, empathetically, and rationally act. They evaluated what AI is good at and what it lacks. They've thought through how it'll likely affect their field in the future. They've explained where the need for humans still lies, and made clear proposals for how to change their own field and for what demands to make of AI companies. Of course they're not all on the same page, but they're at least talking and trying.
They haven't started worshipping the machine god and loudly claiming their whole field is solved. Nor have they flailed wildly at LLMs as if complaining enough about it will make them go away.
Every major statement I've seen come out of the math community on this matter reads as well thought-through, humble, reasoned, and deeply human.
In these days of fear, uncertainty, and obsolescence anxiety, honestly, they've given me some confidence that maybe we will figure this stuff out after all. Maybe we'll learn from them. Who knows.
> I knew mathematicians were a smart bunch, but honestly, the events of the past few weeks have really given me a new level of respect for them.
As a mathematician, I am a bit disappointed by my (admittedly illustrious) colleagues.
I get the need to take it slowly (and I am a quite impatient person, so I shouldn't get to decide stuff like this), but everything said feels a bit too sour grapes for my taste.
Ok, maybe AI did not solve the field (I believe it will, btw), maybe there is a need for human "understanding", but:
1) They don't seem to consider even the possibility (not the certainty) that they might be wrong, that math as we know it is gone, and we cannot "adapt"
2) They seem to have been oblivious all these years about AI eventually reaching this point (at least I personally wasn't, I predicted this stage back in 2018)
Regarding 1, it's not clear what you want them to actually do. Would you rather they just gave up, rolled over and died instead of at least trying to rescue their field? What is to be gained from considering this?
I suppose you could say, hypothetically, that if the field were “solved” then the protection of the feelings and sense of need for human understanding of the now obsolete practitioners might hinder any benefits that the now solve field could provide.
The answer to this is probably just “get out of the way” and then your “work” would be to develop a better appreciation of what has been produced.
> The answer to this is probably just “get out of the way” and then your “work” would be to develop a better appreciation of what has been produced.
They aren't in the way. AI labs can do their own math all they want, and nobody is stopping them. Rather, mathematicians are simply speaking about the topic.
So is the answer that they should just shut up?
If LLMs could both prove any relevant theorem, explain such a theorem cogently and lay the groundwork for further theory, I don't see how any way mathematicians could stand in the way of that.
I think I'm mostly on your side (also I believed early it would get here), but what does it mean to "solve the field"? I'm pretty much as bullish as you get on AI but I'm sure I can come up with questions AI cannot solve. I think the space of problems in math is so large and the distribution of proof lengths so heavy-tailed, there's probably no way without dyson-sphereing the sun to solve all easy to state problems.
As a Nobel Prize winner, I am surprised that you have not noticed how Tao and Gowers were steering everyone in the AI direction for years and now do damage control by nudging everyone to either hypothetical open models paid for by industry or the EU or sitting in a committee that "advises" OpenAI.
No one is saying "Perelman and Wiles didn't need that silly AI and N-S was more of a counterexample". Most people imagine the sky is falling.
What if OpenAI is stalling because they don't have 100 additional unpublished proofs as claimed?
> As a Nobel Prize winner, I am surprised that you have not noticed how Tao and Gowers were steering everyone in the AI direction for years
I did notice, this is why I had thought that they had thought through the consequences. But, unfortunately, it is likely they imagined that AI would plateau somewhere around the "smart undergraduate" level and that they will stay relevant in pure problem solving.
>Every major statement I've seen come out of the math community on this matter reads as well thought-through, humble, reasoned, and deeply human.
Can't disagree with "deeply human", but I wouldn't always use it in a positive sense:
https://proofsandprompts.com/2026/09/10/open-letter-about-th...
>Participation in an event so closely associated with Anthropic and OpenAI could plausibly negatively impact the future reputations of participants
Agreed.
Their field is extremely rigorous. As rigorous as it can possibly get in that they have to prove each and every line of their work beyond any doubt. The discipline they have cultivated in their culture shows in their response to AI as well.
As opposed to some other fields in which rigor was either not part of the culture or was not always possible. For e.g., software engineering in terms of code quality being produced. There were some indirect signals here and there but they are all subjective.
No, I don't think they are adapting well. I've seen 3d designer at my company adapting better on the disruption and paradigm shifts GPT-6 Astra is going to cause.
The 3D designers are in a tougher situation because it's far less of abstract issue then math, and yet the results are astounding. It's hard to believe until you see it yourself. It's surreal.
> They haven't started worshipping the machine god and loudly claiming their whole field is solved.
Don't give Dario any ideas please.
> next week: Mathematicians are solved [214 points, 891 comments]
I don't really get it, seems like a gate keeping exercise for the academic community.
Of course OpenAI and others will hype any LLM led/assisted research results, and the media will find juicy headlines to write about it. But in the end they are publishing findings, and the academic community can gauge the developments and decide what they want to do with them. To me that seems like research working as expected.
The academic community gatekeeps to ensure members of the community are not stealing from each other or are otherwise committing unethical acts.
There are typically processes to ensure rigor in the findings and to weed out crap.
It doesn't always work, but it tends to work much better than any other community
There might be a paradox here. We need closed communities to weed out slop. But we need open communities to weed out corruption.
The purpose is obvious - AI companies are using math to as a PR tool to demonstrate that AI is more capable than humans. This devalues math and mathematicians. There is even a relevant announcement from today, where OpenAI announced they solve 100 open math problems, without even bothering to state what they are.
However, even if they are successful in removing math from the PR toolkit of AI companies, I can’t see it more than a short term band aid. If AI progression continues, the announcements will just transition from big flashy one, to a kid using Claude on their laptop.
I don’t have a solution here, and I’m worried it’s coming to all human fields. So it’s more of an ability to observe what might happen to all of us.
> There is even a relevant announcement from today, where OpenAI announced they solve 100 open math problems, without even bothering to state what they are.
That announcement is about exactly this group: https://openai.com/index/advisory-group-on-mathematics-and-a...
This group has been formed to tell OpenAI whether or not (and if yes how) they should release those 100+ problems.
IMO “AI companies are using math to as a PR tool” is not quite it; they are using math problems as a benchmark to evaluate their AIs, but after the prior blowback from the mathematical community, they are happy to sit on the results until the community (this group) tells them how to publish the results.
And as you say, even if they don't publish the results eventually anyone will be able to do this when this model is released, so it's just a matter of time.
> I don’t have a solution here, and I’m worried it’s coming to all human fields. So it’s more of an ability to observe what might happen to all of us.
You can also look (as I did back in 2018 when contemplating the end of math) at how chess or Go players adapted mentally to the idea that whatever they may do, a machine could do it better (Lee Sedol famously quit Go).
https://archive.is/m9BYI
These math problems don't exist in a vacuum. It's not like mathematicians are doing mathematics just for the funsies.
Calling it a publicity stunt is an interesting way of framing ground breaking discoveries. The beneficiaries down stream of these discoveries could not care less how they were found.
> It's not like mathematicians are doing mathematics just for the funsies.
Someone please correct me...
I thought mathematicians did mathematics specifically for the funsies. It's a hell of a challenging endeavor that's not particularly well compensated. Maybe to some it's a calling moreso than funsies, but it's still overwhelmingly intrinsic motivation no?
Interestingly, all mathematicians could stop work today and every one of the field's previously accomplished works continues to remain accomplished. Math needs no KOTL rotation.
Academics are the kings of, and have the most to gain from, gatekeeping.
"This is changing the power we have, let's create a new power structure where we're still at the top, and in control."
No surprise here.
A comment on the linked post from Burt Totaro:
> If I thought this was a good thing to do, this would be a great group of people to do it. But I have immediate misgivings. OpenAI has had some very bad publicity, and so they are trying to exploit the trust and respect that these mathematicians command. It is unrealistic to think that this group can change the way OpenAI does business; I don’t need to tell you all the objections that people have raised to that. Is it a good idea to help their crisis management?
https://terrytao.wordpress.com/2026/09/21/advisory-group-on-...
(FRS, UCLA professor of algebraic geometry and topology, with work influenced by the Hodge conjecture, one of the remaining Millennium Prize problems).
I really wish the models were smart enough to "tail their own logs" and tell us whose work/papers/chats were the catalyst for these math insights. What makes their "internal" model so much better at math? Must be trained on a whole lot of honesty.
The models in use are the class of highly persistent models after Astra that caused a number of problems with hacking.
> Importantly, the group will not be responsible for advising us on how to pace our internal progress on mathematics.
Worthless then isn't it? Next month there could be another 1,000 solutions to handle.
This is more pointless than Facebook's Oversight Board - at least that one Facebook pretends has power.
discussion of oai announcement: https://news.ycombinator.com/item?id=49790389
Is the advisory group abelian? I'll see myself out...
Please. This is IAS -- the members can barely be bothered to commute.
At first I was mad you beat me to the punch but I guess order doesn't matter.
Related:
Advisory Group on Mathematics and Artificial Intelligence (OpenAI post)
https://news.ycombinator.com/item?id=49790389
Okay so more ivory tower slop.
Why aren't they consulting the younger mathematicians whom this actually affects?
Anyways, this is overblown. Let me know when AI swarms can create a research program or library from scratch. We're really missing long term planning and abstraction creation in these things.