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Comment by ngruhn | Hacker News Reader

> or posting arXiv does not count

The Poincaré conjecture guy also broke that rule. They wanted to give him the prize anyway but he refused. OpenAI announced they would also not claim the prize.

Looks like no one wants this prize lol

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Perelman posted to arXiv in 2002/3.

The prize was offered to him in 2010, after multiple others had digested his work and published elsewhere.

But if I remember correctly, he gained recognition for his achievement rather quickly after posting.

You might be right. At this rate, if AI solves the remaining five problems, we're heading towards a hilarious situation where all the Millennium Problems are solved, but nobody wants to claim the prize money.

I did and was intending to claim the prize, that is why I worked with GPT-4 and GPT-5 to program the algorithms that lead to the breakthrough. You think NS is a surprise? Wait until you see that my NS counterexample was based on my RH disproof.

That’s a big if. In the maths community, there has been a feeling that Navier-Stokes was close to being solved for a while now. I don’t know of anyone credible who feels that way about the Riemann hypothesis.

Here’s what Terrence Tao had to say about it https://youtu.be/vuT-2_e4NHg

Edit to add: The fun part about the RH since people mentioned lean in a sibling thread is that in lean’s mathlib4 there is verified statement of the Riemann Hypothesis with a comment that says something like “instantiating an object of this type will lead to a prize of a million dollars”

It's really not that big. Yeah Navier-Stokes was easier than Riemann but that's not really the issue.

AI has and will improve at a much greater rate than human mathematicians. So it's really a question of if AI gets good enough to tackle it before any human does. It doesn't look like humans will be solving it anytime soon but where will AI be in 2 years ?

Hell, it looks like at least one other result will be announced soon too.

Has and will. Are you going to back that assertion up at all, or just repeat it like that other viral thought-terminating cliche: ‘this is the worst the models will ever be’?

Yes. This is the worst the models will ever be. Perhaps you should start paying attention to that now.

No it isn't. Best and worst and ill-defined anyway but the chess ELO score of various LLMs has fluctuated up and down, it's not been montonically increasing. What is the best answer to "how do I make cocaine"? The models are getting larger, with more compute and RAM backing them, but that doesn't automatically make them better if you don't define how you're measuring better-ness.

None of the frontier labs care about Chess as it's already a solved problem. If they did, the models would be much better. It's really not that hard. Google has a paper on grandmaster level chess without search from transformers.

Better obviously means better, like how they became better than they were 6 months and a year ago.

I would describe better as how much of my work I can delegate to the agent. Right now I'm delegating much more to Astra high than 6 months ago to Opus 4.6. Every dev has this feeling, it's weird to even argue what a better model/harness means.

Chess is not solved in any meaningful sense of the term. Computers have been better than humans since the 90s, but better chess programs are released all the time.

It's solved in that we have had grossly superhuman capabilities for some time. It's not interesting for frontier labs. I suspect you understand this and the greater point so why be needlessly pedantic ?

"Better" is not one dimensional across all use cases even if model capabilities are improving in aggregate.

e.g. If someone said "this is the worst they'll ever be" in response to some writing with obvious LLM cliches in 2024, I'm not convinced that prediction was actually correct.

The focus of OpenAI/Anthropic pivoted aggressively to the agentic performance arms race instead of making a more human sounding chatbot so regressions in writing ability aren't really a concern anymore if agentic benchmarks improve.

The first time I heard a recommendation to use Claude was specifically because it sounded much more "human" and natural than ChatGPT. Fast forward to now and idiosyncratic Claude-isms repeated every other sentence and its convoluted verbosity has become a widely mocked meme.

Right but we're talking about a single subject here - mathematics that labs are incentivized to keep improving for some time.

>e.g. If someone said "this is the worst they'll ever be" in response to some writing with obvious LLM cliches in 2024, I'm not convinced that prediction was actually correct.

2024 creative writing prose was...the last few versions have stalled, but I think they're still better than 2024.

Sorry, but I doubt you have anything interesting to contribute and probably have no expertise in mathematics. I’d rather hear from those who do.

The thing about mathematics is that it can be arbitrarily hard, including impossible to prove a given theorem.

I don’t know the details of RH, it might very well be solved soon, but it could also be impossible or just so difficult that even orders of magnitude more intelligent AI can’t solve it even.

If it is impossible to prove, it might be possible to prove that it is impossible to prove, or that itself might be difficult or impossible…

I mean if it's impossible to prove then the bet is still valid right ? The Clay institute won't be giving out any prize still in that case.

TBF a company the size of openai claiming a prize of this sort would be a pretty bad look. If they did accept it I expect they would inevitably redirect it to charity for PR reasons.

I'm surprised perelman turned it down though. Seems straightforward enough to offer half of it to the other guy if you feel strongly about it.

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