121–130 of 136 posts
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It's because anthropic vibemathed it. I forgot the name but some other guy is working on a handwritten version of it and I bet it'll be more than just 1 magnitude faster.
They could probably vibe-optimize it if they cared. What would happen if they give an equivalent agent swarm the proof and a target to reduce runtime .
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> From some estimates I've seen, the compute cost alone would be around $10m, +/- At market prices. All the estimates I've seen are based on OpenAI API costs. It doesn't mean that's what they paid, or how they paid for it. But yes, the surprising willingness of humans to solve hard problems in exchange for food and board is underrated.
Given that they all the bit AI players are still loosing money, it follows that their total costs are _higher_ that their API pricing would imply.
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…
My understanding of the result that was found is that the blowup doesn't happen in the real world, and only happens in an NS simulation. The bottom line is that NS is insufficient to model the real world, because in this case the real world is more stable than the model. [Take this with a grain of salt, I barely knew of NS before a couple days ago]
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There's a large difference between "wrong for the given definitions" and "right in that context, but wrong for other definitions" though.
I think I am make a much more basic point than what you're talking about but then again I am not sure what you're tying to say here...
Your comment may have other points it makes too, the above is just clarifying the type of mathematical limbo GP is discussing with the abc conjecture is not related to the type of mathematical limbo you're discussing.
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.
> People seem to be talking about anything except the actual results with this particular announcement. To be fair, most people have a fairly good handle on "Does opting out my prompts from training runs actually work?", but not on Navier-Stokes. They discuss what more immediately affects them.
It's kinda funny to realize that Lean is apparently so slow that for Fermat's Last Theorem proof verification runs only 1 order of magnitude faster than agents could generate the Lean code (15h verification with 230GB of RAM vs 11 days to generate it). To what extent can you optimize Lean? It has to be simple enough to be auditable, does that mean you cannot use opaque optimizations to make it run faster?
[Talk] 10 years of superlinear slowness in Coq (2022)
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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…
It's kinda funny to realize that Lean is apparently so slow that for Fermat's Last Theorem proof verification runs only 1 order of magnitude faster than agents could generate the Lean code (15h verification with 230GB of RAM vs 11 days to generate it). To what extent can you optimize Lean? It has to be simple enough to be auditable, does that mean you cannot use opaque optimizations to make it run faster?
"I have discovered a truly marvelous proof of this, which my memory is too small to contain..."
It's kinda funny to realize that Lean is apparently so slow that for Fermat's Last Theorem proof verification runs only 1 order of magnitude faster than agents could generate the Lean code (15h verification with 230GB of RAM vs 11 days to generate it). To what extent can you optimize Lean? It has to be simple enough to be auditable, does that mean you cannot use opaque optimizations to make it run faster?
> 230 GB of RAM "I have discovered a truly marvelous proof of this, which my memory is too small to contain..."
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…
That people still think OpenAI has, in the Year of Our Lord 2026, any integrity left is baffling.