Let mathematicians do the AI-supported research on their own incentive at their own pace? What leaves a bad taste is that OpenAI doesn’t do this because they care about the actual math. Especially when they are leaving the necessary work of properly verifying, understanding, and writing up in an intelligible manner the proofs, up to the math community.

People would be more sympathetic if this was an alien race sharing their math results in not-quite-intelligible-to-us papers, because there at least we could assume that the aliens cared about the math and did their best to transmit their understanding to us.

1) is probably phrased wrongly. I think it isn't even research for the AI labs, it's just an inevitable byproduct of how they train and verify their models. That goes perhaps to the heart of how the mathematicians feel about it: what they thought was a crowning achievement of the human intellect is now a byproduct of a mechanical-industrial process. But that also means the AI labs can't just stop, because they need ever harder puzzles to be part of the training.

> People still play chess and go and StarCraft

Those are activities where repeating the same experience yourself is still enjoyable, kind of like you might eat today even though you already ate yesterday.

Finding mathematical proofs is probably more like seeing the ending to a mystery novel. Once the ending has been spoiled for you, it's really hard for you to enjoy it the same way, and it might be more fun to move on to a different mystery.

Chess and StarCraft are games. For many other intellectual activities, part of the satisfaction comes from contributing something meaningful to a collective effort. If a machine can do that orders of magnitude faster, for many people these activities become effectively pointless.

> People still play chess and go and StarCraft. People do what people want to do.

Poor analogy. Because math is one of those job-hobby type hybrids where the job may be enjoyable but you still need the academic infrastructure to do it on a modern level, both because you need funding and you need others to motivate you to keep to a certain standard.

Job-hobby hybrids like this are not the same as running and Starcraft where you can do it by yourself and still reap a lot of benefit from it in the same way. Hobbyists might still do math but if it were just up to the hobbyists, we wouldn't have the level of discovery we have today.

> People still play chess and go and StarCraft

but very few get paid to do that

Have you not already heard others make this analogy a million times by now? It seems like I read it multiple times a day at this point.

Mathematics can be enjoyed recreationally as a puzzle like any other, but it isn’t just an arbitrary puzzle. It’s a science where one discovers truth and seeks an understanding of, and dreams up, new phenomena. It’s not chess, or go, or StarCraft. There’s no fixed rule set and the goal isn’t to ‘win’ or beat your opponents.

Let’s stop repeating this nonsense as if it’s a profound observation.

All the “it’s not clear if there will be fewer jobs in the future” rhetoric is frankly mind boggling. It’s pretty clear the goal of LLMs in a capital sense is to reduce operational budgets as much as possible. If it doesn’t happen naturally it will happen by execs forcing that decision.

I don't really understand these takes if we speak of the long-term. You're speaking of a world where there'd be widespread access to high quality cognitive work for a price approaching $0. The possibilities this would open are endless. We need to ensure that we don't neglect our own personal development, and fall into the sci-fi trope of an ignorant civilization relying on an machine built by their ancestors, but I don't think that's much of a practical concern.

In the short-run I think concern is much more merited because it will obviously cause some instability as the economy settles into a new equilibrium, but that's always the case with any sort of revolutionary technology. And this would almost certainly just be short-term stuff. As the value of one thing goes down, the value of other things would go up, and new things would emerge.

AI has to come for politicians, CEOs, executive leadership and management in all kinds of organizations first.

We can find a robot that will play golf instead of CEOs.

AI can generate keynotes and meet with other AI agents, pat itself on the back for success stories and give itself promotions and empire building.

"a set of some of humanity's brightest struggling to comprehend the emergence of such an incomprehensibly creative and powerful intelligence"

Where do you get this from? There is exactly one comment that even mentions creativity, and none of them speak about intelligence. All seem to agree it's slop.

> To be fair, my first reaction was almost boredom. Yes, the AI has “proved” (really? Are we sure? Can we even understand what is written there?) a bunch of interesting results in my field. Not even a Millennium Problem. Pff. [..] If a paper or thesis is so badly written that I cannot get past the first page without considerable effort, I reject it and ask for a new, readable version. With these AI-generated papers, I feel that we, as a community, are not applying the same standards of quality and rigour. They can simply release multiple 100+ page papers claiming to have solved this or that problem, often with redundant arguments, unclear logical structure, multiple dead ends, and strange or unsettling terminology — in other words, slop.

> if we don't do something NOW

We are doing something now. We're making it so the AI does it all better, so we don't have to do it anymore. Gotta break a few eggs to make an omelet, but it's going to be a delicious fucking omelet when it's ready. I don't understand why people are pushing back so hard on making the world a better place. I personally can't wait until it's clankers all the way down.

why assume that because LLMs are strong in a narrow set of fields it will be strong in everything? we don't make that assumption about other forms of intelligence. i.e nobody thinks Stockfish is good at product management, and people generally don't think that a genius composer will be equally good at botany.

But they aren't more successful. They can solve this because of standing on a huge body of work made by working mathematicians. Without it AI would get nowhere. Now AI are burning the minds that fed it for short term gain.

A bit part of it is that no one human mathematical genius can hold all of math in their mind at once. The surface area is enormous. Humans specialize. The model has the luxury of finding obvious interactions in widely disconnected fields that no human would have found.

I was really quite surprised that they'd parade around 722 manuscripts with only less than half (or really, close to only a third) of it being machine-checked. It's genuinely equivalent to the overconfident and blind drive-by PRs in software that people here should be well familiar with, and those are not exactly the hallmark of quality usually. Quite the curiously dangerous game to play when you're trying to scoop an entire field of study on an industrial scale as powerplay.

Part of it is probably because we've already been through this? The SWE field has seen exactly these reactions over the past 4+ years.

Some people saw "the spark" before LLMs were mainstream. We had code autocomplete models based on GPT2 that ran on your machine and provided line-based autocomplete. Then we had gpt3.5 (chatgpt launch) where it almost looked like it could write python, then we had gpt4 and saw the first glimpses of actual code writing, then opus4 / gpt5, and today we have sol/fable etc. At every step we had people in this field write the same kinds of takes. And at every step the tech evolved, improved, and got better. To a point where the vast majority learned to accept it, and the denialists (there are still some) are now in a minority.

And the acceptance phase was not "we are now useless as SWE", nor was it "hah, it's only for the juniors, we are safe. It was, mainly, "we can now work at a higher level of abstraction, and use our experience to guide these tools and work faster / broader / deeper in a topic. Basically understand the tools, learn their pros and cons, and adapt at using them.

Also part of it could be that the message seems to complain about the situation without providing alternatives. What are the alternatives? What are they proposing? "Please don't do this" does seem like gate keeping if you don't offer an alternative. What exactly do they want these labs to do? Don't try to solve the problems? (stop the count?) Don't publish the results? It's not clear to me.

I guess a lot of people are unclear on the messaging. Is this purely ideological, or is it something more? (It doesn't help that AHM also has a section where they highlight their members who pledge to do research "without AI assistance". Whatever that means. Yeah, that's cute, but can signal denial, which again we've already seen in SWE, and hopefully most people have dismissed it already) Are these statements part of the 7 stages of grief, or is there more? When taken at face value, the statements seem rushed, unprepared and "in denial". At least when compared to writing on the same topic from other people in the field (Tao et all).

> "hey, please don't do this, it's seriously hampering our work in this field"

I don't think that that's really a fair summary of the linked article though. By my reading, I'd say that a quarter of the responses were overall positive on the announcement, a quarter were overall negative, and the rest were mixed/neutral. I agree that there are many mathematicians saying something similar to "please don't do this", but that's not a consensus (or even a plurality) view.

(I agree with your broader point though, that lots of the other replies to this article are way too dismissive of mathematicians' concerns.)

OpenAI dropped a slop bomb on mathematics the same way people will drop slop bombs in codebases and the people here are saying “well drop everything and review it of course!”

I think it’s very reasonable to expect the people that are dropping this on other people for review to have reviewed it first, closely, made adjustments, etc, the same way I do before dumping my Claude/ChatGPT assisted PRs onto other people.

The reviewers shouldn’t be exerting more effort than the person that set the prompt.

>they're vastly underestimating what AI will be able to deliver in years to come

Will it be able to, though?

Don't rub it in; they're depressed enough as it is!

Please explain 2 things:

1. "...these open problems were curated in order to organize a field around, most to all of them only have/had value in so far as they promoted study of the subject" - I don't understand, how were the open problems curated? Do you mean that mathematicians put a lot of work into coming up with the problems and now all that work is somehow worthless now?

2. "OpenAI is functionally reducing the communities ability to ask real questions." How? Let's assume all the remaining proofs are correct (big assumption): how does resolving conjectures reduce the ability to pose new problems? This only makes sense to me if the assumption is that there are a relatively small number of possible problems to solve and so it's like a game that's coming to an end with no more interesting areas to explore. Surely math is bigger than these?

they would be treated the same: "we dont have time for your slop questions and conjectures, they do not even come from a place of struggle and curiosity, we will not engage with your PR attempts, we already have problems to solve and things to think about for the next 200 years"