> However, communications quickly became contentious. According to Buckmaster, OpenAI offered to give him sole authorship on the Navier-Stokes solution—but only if Alpöge’s name was removed from the work and if the write-up would acknowledge the problem had been resolved by an internal OpenAI model. Buckmaster refused, in part because he was troubled by the question of what OpenAI's system had actually seen. For example, Buckmaster said the company did not initially give him a clear answer about whether its agents had access to the pair's logs on Codex (which is an OpenAI product).
> OpenAI executives have denied that any employee or AI agent saw the pair’s work before the researchers released it publicly on 7 September. But there still remains a separate question: Could the pair's work have reached OpenAI's models through its training data?
> OpenAI’s blog announcing the Navier-Stokes solution does not dismiss the possibility: “While unlikely, we cannot rule out that de-identified data derived from [Buckmaster and Alpöge’s] usage of our products helped improve our models .”
So, this company wants everyone and every organization on Earth to use their software, and reserve the right to then tell anyone how the resulting work can be published and credited?
Real solid business model there, how could it ever fail?
Regardless of what you think of the priority dispute issue discussed on sibling threads, I’m highly skeptical of the closing quote that this Navier Stokes result means that the same approach of casually spending a few million on agentic computation is going to solve end to end materials design or drug development.
Those problems can’t be formally verified with an automated theorem prover. We have a lot of physics based simulation tools, but they tend to focus on small subsets of the full design problem and they make limiting approximations because otherwise they’d be too computationally expensive, or we just don’t have the right data to parameterize them beyond describing qualitative behavior. Agents are helping accelerate research in these fields but I think it’s mostly a different class of problem that’s a lot harder to specify and verify
"Breakthrough" to me would be like Isaac Newton inventing calculus to calculate pi. This feels more like $12MM in tokens was spent to add another digit to pi using the old way.
I think it was a pretty questionable thing to do by trying to front-run these researchers even if they didn’t make use of their techniques. The fact that they may have inadvertently “borrowed” their work via training data makes it much worse.
OpenAI’s behavior here — even if you only consider there side of the story — was (at best) in bad taste.
And according to that team OpenAI only started asking their own model these questions after those submissions had occurred. So OpenAI had these critical clues and info before they started. If OpenAI did or did not use that to produce their own “proof” is an open question, but OpenAI hasn’t definitely denied it.
Are you asking if it uses additional axioms of `sorry` in the proof? It's easy to check that it doesn't by compiling it and telling lean to list the axioms.
Personally this is a watershed moment for researchers and grad students I know. All of them are close sourcing WIP repos, not putting their progress in LLMs, or have lab level initiatives to self host models.
I'm a mathematician. I have a lot of trepidation about these tools and what they mean for the future of the profession.
That said... most of us are not working on problems as famous as Navier-Stokes. Even if OpenAI could scoop me based on my back-and-forth with ChatGPT, which I presume they could if they threw $15 million worth of compute at it, I highly doubt they'd bother.
But consider they could decide that they want to scoop more regular research work too. Even if you opted out in the ToS, you'd have to file a massive lawsuit just to enforce it. And the actual fine would be inconsequential to OpenAI.
I think going forward, any researcher should consider anything submitted to an LLM to be copied.
If you mean move to products with ZDR policies, OK, very fair and I agree. If you're talking the equivalent of carpenters should give up pneumatic air guns because hammers are more authentic, then that's silly. These are tools, and like any tool how effective they are can come down to how well you use them.
Should they give up pneumatic air guns if the company that supplies then can then control what you build with them, how you build with them, and secretly copies all your designs for their own use. Sure its a good tool, but its also becoming a trap.
They represent different AI usage patterns. OpenAI wants everyone to believe that it was done with a practically autonomous network of thousands of agents with little to no human intervention for 88 hours, while the Buckmaster/Alpöge were using AI in a more guided way for months. If OpenAI actually used anything from Buckmaster/Alpöge work they would be misleading the public.
> OpenAI, meanwhile, says its experience with Navier-Stokes could open the door to solving puzzles with more practical relevance. “We are now able to spend millions of dollars on a problem that we really care about and that really matters: developing new materials, finding cures to diseases,” Bubeck said. “All of those things that we have been talking about for a long time—now they seem to be at our fingertips.”
Eh? There's no connection at all between the Navier-Stokes work and those things.
He may be hinting that solving these complex mathematical problems will boost OpenAI clients' confidence and encourage them to spend millions of dollars on solving other complex problems.
> However, communications quickly became contentious. According to Buckmaster, OpenAI offered to give him sole authorship on the Navier-Stokes solution—but only if Alpöge’s name was removed from the work and if the write-up would acknowledge the problem had been resolved by an internal OpenAI model. Buckmaster refused, in part because he was troubled by the question of what OpenAI's system had actually seen. For example, Buckmaster said the company did not initially give him a clear answer about whether its agents had access to the pair's logs on Codex (which is an OpenAI product).
> OpenAI executives have denied that any employee or AI agent saw the pair’s work before the researchers released it publicly on 7 September. But there still remains a separate question: Could the pair's work have reached OpenAI's models through its training data?
> OpenAI’s blog announcing the Navier-Stokes solution does not dismiss the possibility: “While unlikely, we cannot rule out that de-identified data derived from [Buckmaster and Alpöge’s] usage of our products helped improve our models .”
Real solid business model there, how could it ever fail?
Well yeah, if you use the free product they train on your data, ... I thought this was widely understood?
> I pay for the tools my group uses out of my own research funds, including footing a large bill to OpenAI.
[0] https://cims.nyu.edu/~tristanb/statement.pdf
This is blatant scientific misconduct.
Those problems can’t be formally verified with an automated theorem prover. We have a lot of physics based simulation tools, but they tend to focus on small subsets of the full design problem and they make limiting approximations because otherwise they’d be too computationally expensive, or we just don’t have the right data to parameterize them beyond describing qualitative behavior. Agents are helping accelerate research in these fields but I think it’s mostly a different class of problem that’s a lot harder to specify and verify
Quanta Magazine article that also discusses some of the controversy: https://www.quantamagazine.org/ai-has-solved-one-of-maths-1-...
Seven, not six. One is solved already, but is still a millennium problem.
OpenAI’s behavior here — even if you only consider there side of the story — was (at best) in bad taste.
And the AI company for making the search program that searched through the data and found the solution.
That said... most of us are not working on problems as famous as Navier-Stokes. Even if OpenAI could scoop me based on my back-and-forth with ChatGPT, which I presume they could if they threw $15 million worth of compute at it, I highly doubt they'd bother.
I think going forward, any researcher should consider anything submitted to an LLM to be copied.
Eh? There's no connection at all between the Navier-Stokes work and those things.
Navier Stokes is a test of how high the intelligence is.