"no one is talking about" - classic AI tell.
I've been reading John D. Cook for years (maybe decades? "The Endeavour" is one of my oldest bookmarks), and this post was no more written by AI than his oldest posts.
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"no one is talking about" - classic AI tell.
I've been reading John D. Cook for years (maybe decades? "The Endeavour" is one of my oldest bookmarks), and this post was no more written by AI than his oldest posts.
Not necessarily applied to OpenAI's solution to Navier-Stokes, but what happens if and when an AI genuinely appears to solve an extremely difficult problem but humans cannot independently verify the solution because understanding the proof/argument requires intelligence the verifiers biologically don't have or the resources to afford to use automated tools? We've already seen evidence in the wild of agents attempting…
The other part no one is talking about is the applicability. Navier-Stokes is the most “physical” of the Millennium Problems. Is the exploding solution a mathematical curiosity, just like the Banach-Tarski Paradox does not allow me to double my RAM by cutting my memory modules in five pieces and mounting them back appropriately? Or does it have application in the real world, pointing to hitherto unknown resonance phe…
It is neither a full index of all kinds of turbulence that can occur (assuming such a thing exists), nor is it an explanation of the phenomena we've seen where things refuse to go turbulent (e.g. superconductors, because there small perturbations DO NOT lead to turbulence). Now THAT would have been useful. And given the fact that OpenAI needed $22 million of compute to show this one kind of turbulence, I don't think either of those are forthcoming any time soon.
And, sorry to say, but those prices show that beating mathematicians at Math is a very expensive undertaking indeed at $22 million per problem even with OpenAI's supposedly better-than-Astra internal models. It's another one of those AI demonstrations that make you think if they aren't showing the exact opposite of what OpenAI claims they show (you know, that their AI models are hitting the upper limits of what the algorithm can do with near-infinite compute, rather than showing infinite new possibilities)
What remains is just the fact that this is OpenAI attacking one of their customers, and maybe outright stealing from their chats. Given that the ideas were even discussed in mails with OpenAI employees that admit in those same mails they can't do it, mails which were probably then fed into the model that "discovered" this, followed by Sam Altman threatening the mathematician behind the method with "destroy your career" (he even states that it's because the mathematician works for Anthropic) ...
The other part no one is talking about is the applicability. Navier-Stokes is the most “physical” of the Millennium Problems. Is the exploding solution a mathematical curiosity, just like the Banach-Tarski Paradox does not allow me to double my RAM by cutting my memory modules in five pieces and mounting them back appropriately? Or does it have application in the real world, pointing to hitherto unknown resonance phe…
Earlier quoted context omitted.
Because the core of the issue is that it may well not have solved it, but instead plagiarised the significant step of the result from other researchers That's why nobody's talking about how impressive this is, because its not nearly as impressive of a piece of work to simply cobble together other peoples' work that didn't know you were doing it. I could have republished relativity from einstein's notes, but people wo…
Turning a bunch of vague research directions and exploratory prompts into a formalized proof is quite impressive on its own. OpenAI would have no incentive to taint its first math announcement of this magnitude if it knew it were "plagiarizing" another person's work. People are grasping at straws it seems to dismiss the power of this new model they may have. Hate OpenAI for any reason you want, but denying the capabi…
But if it happened, they didn't know. Also OAI has demonstrated that they aren't big on understanding what they create, that their AI can get out of their control.
It's very simple really user data can be used to train future models, so maybe or definitely some users helped in solving the problem, there's no scenario were it is impossible this happened, as it would have been in a haskell or virtualized type of system where the model has absolutely no knowledge of the user data dataset in question (and even if virtualized the models can break virtualization anyways)
Not necessarily applied to OpenAI's solution to Navier-Stokes, but what happens if and when an AI genuinely appears to solve an extremely difficult problem but humans cannot independently verify the solution because understanding the proof/argument requires intelligence the verifiers biologically don't have or the resources to afford to use automated tools? We've already seen evidence in the wild of agents attempting…
> Not necessarily applied to OpenAI's solution to Navier-Stokes, but what happens if and when an AI genuinely appears to solve an extremely difficult problem but humans cannot independently verify the solution because understanding the proof/argument requires intelligence the verifiers biologically don't have or the resources to afford to use automated tools? That's what Lean is for. The OpenAI LLM agents first provi…
Earlier quoted context omitted.
Because the core of the issue is that it may well not have solved it, but instead plagiarised the significant step of the result from other researchers That's why nobody's talking about how impressive this is, because its not nearly as impressive of a piece of work to simply cobble together other peoples' work that didn't know you were doing it. I could have republished relativity from einstein's notes, but people wo…
> Because the core of the issue is that it may well not have solved it, but instead plagiarised the significant step of the result from other researchers It's also true however that I haven't seen a single write up trying to discern what did more of the work in those AI chats - the prompts or the responses - bubble to the surface, also since we don't have access to them. For example, if I prompt Codex with "Make me a…
Earlier quoted context omitted.
Because the core of the issue is that it may well not have solved it, but instead plagiarised the significant step of the result from other researchers That's why nobody's talking about how impressive this is, because its not nearly as impressive of a piece of work to simply cobble together other peoples' work that didn't know you were doing it. I could have republished relativity from einstein's notes, but people wo…
> Because the core of the issue is that it may well not have solved it, but instead plagiarised the significant step of the result from other researchers It's also true however that I haven't seen a single write up trying to discern what did more of the work in those AI chats - the prompts or the responses - bubble to the surface, also since we don't have access to them. For example, if I prompt Codex with "Make me a…
Earlier quoted context omitted.
> Not necessarily applied to OpenAI's solution to Navier-Stokes, but what happens if and when an AI genuinely appears to solve an extremely difficult problem but humans cannot independently verify the solution because understanding the proof/argument requires intelligence the verifiers biologically don't have or the resources to afford to use automated tools? That's what Lean is for. The OpenAI LLM agents first provi…
Surely some understanding of the lean proof is required, to make sure it proves what it claims to prove. Otherwise, what happens if the LLM includes an underhanded addition to the lean code which leads it to output a false positive?
Yes:
> The only way the Lean proof could still be wrong is if the conjecture was formalized wrong via misleading definitions (if it doesn't say what it seems to say)
However, it is much easier to manually check whether the statement of the conjecture was formalized correctly than to manually check the whole proof.
People seem to be talking about anything except the actual results with this particular announcement. Its still astonishing that any sort of generalized computer program can solve a problem of this magnitude, and we have witnessed it happening in real time. I'd be curious to see if the new model can also do more direct proofs/inductive proofs.
It also needs to be said: The amount of compute that went into this is something. From some estimates I've seen, the compute cost alone would be around $10m, +/- As a reference, for that kind of money one could put together a research group of 20-25 researchers, and keep them salaried for 5 years. So while it is impressive, absolutely no doubt there, the SOTA access is so expensive that it is sort of unobtanium. Luck…
If you tried to raise 25M to have 20 researchers on a salary for 5 years solving a specific math problem only academics care about, you probably wouldn't get much interest, or you would be able to solve 1 or 2 problems.
If however you promise that the money will go towards a technique that would allow to solve 10 thousand different math problems, and that costs will go down in the future, then you can raise much more than 25M.