Well OpenAI wants to maintain its edge and solving a Millennium problem is of course fantastic PR, and given that Anthropic seems to be working on that it’s not hard to imagine they wanted to be first. I don’t get how people buy into that whole “oh we heard models can solve Millennium prize problems now so we thought why not give it a go…” story - it’s a bit funny. This whole AI bubble is about hype and solving such problems is probably one of the best ways to keep this hype up so you can safely assume both OpenAI and Anthropic are using significant resources on these areas.
The Navier–Stokes Millennium Prize Problem
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Re: The Navier–Stokes Millennium Prize Problem
#72LLM’s seem very good at solving mathematical problems of which there is an enormous amount of exisiting work/attempts in their training data. This is an amazing capability, but does not convince me that these models are «thinking» or «reasoning» in the way a human does. A human mathematician could in theory categorize/discover an entirely new field of mathematics tomorrow, based purely on their «human intelligence»,…
A lot of what humans do is combining old ideas.
And an LLM could in theory also stumble upon entirely new ideas: there's randomness in how they generate their reasoning and answers after all.
I suspect that we are seeing a lot of advances coming from the combination of existing but somewhat obscure knowledge coming from LLMs at the moment, because LLMs are really good at this. At least compared to humans.
Even before our AI friends became good, they were already known for having read approximately every paper and every textbook published in any language. You only need to increase intelligence a fairly small amount from there to get to something like the 'convex hull' of human knowledge.
Compare https://slatestarcodex.com/2016/11/17/the-alzheimer-photo/
The gist is that basically whenever anyone comes up with a new method you get a big burst of activity of picking up all the now lower hanging fruit, that was previously out of reach.
Re: The Navier–Stokes Millennium Prize Problem
#73>While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models. What do you mean, as OpenAI employee, you cannot tell that his work has entered the training data ? But also correct me if I'm wrong, if the two mathematician were really close to finish this problem, and their conversation were used by OpenAI, shouldn't the Agent have succeeded way faster/e…
I’m not a mathematician so take this with a grain of salt. Apparently terry tao commented that the approach used for the Euler paper can “probably” be used for solving NS but it’s still technically challenging and can probably be done with an LLM with a lot of compute. To me the crux of the issue is whether the insight were stolen so that the problem becomes something that is in the domain of LLMs. This is much different than LLMs coming up with the insight. OpenAI wants everyone to think the LLM came up with the insight and solved the thing by itself even though they have perhaps an army of researchers.
Re: The Navier–Stokes Millennium Prize Problem
#74Earlier quoted context omitted.
He is in the HN ingroup of whenever he posts a blog, a prominent HN mod or poster with 1 billion karma will inevitably post it, and so it goes. It's sort of like the music industry.
Does poster karma boost the post in any way?
I don't believe HN boosts their algo but I think people recognize posters like celebs. I recognize tosh, simonw, etc.
Also it's an easy way to farm karma. The pelican guy posted a pelican, let's upvote it? It's at least a bit of psychosis / mass effect in this.
For what it's worth, I like the pelicans but just making an observation
Re: The Navier–Stokes Millennium Prize Problem
#75I run a small SaaS[1], like so many others, that uses AI to generate and optimize SQL. Getting this to perform optimally has been a lot of work and now I wonder if OpenAI is outright stealing this knowledge, which without a doubt is highly valuable to them. [1]: https://www.sqlai.ai
It's extremely unlikely that there is anything interesting or novel in the optimisation of a small SaaS SQL
Re: The Navier–Stokes Millennium Prize Problem
#76My take home from this entire drama is that one should not use LLM services for confidential or proprietary information as they all seem to be run by assholes. And you’re sending them everything you are doing. Would you send your lab notebook to an asshole? Hell no. I say that as a mathematician (on paper) who perhaps surprisingly doesn’t give a crap about the problem itself.
Their privacy policy for normie subscribers says in plain English they use your Personal Data for research. I think it’s pretty unreasonable to use the service and expect otherwise.
I think those are pretty unreasonable terms and it’s sad that you’re defending them.
Does google docs own the content of docs you make with it? Does Apple claim ownership of discoveries made using their tools?
Re: The Navier–Stokes Millennium Prize Problem
#77I think this drama was blown up a bit out of proportion. The entire discourse I am seeing online seems to revolve around this: > While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models I mean... yeah? What do you expect? What else can they say? How could you prove a negative in this case? I do not want to comment on specific OAI employee chat messa…
I can give you some context.
1. Terence Tao's mastodon explains the way this problem was solved does not in itself contribute much. LLMs (and in this case) produce massive, often unintelligible proofs that do not further understanding. It is often that in pursuit of solving these problems, many other discoveries are made.
2. There is a more serious question about scooping. If OAI is using chat data from researchers to make discoveries, essentially every researcher who chats with an LLM can get scooped. You could be 80% of your way to solving a problem, and LLM could solve the remaining 20%, and get all the credit. Years of your work could be scooped in an instant. If you're a PhD student, this is even worse. Here it's a world famous problem. But imagine you're a PhD student, working on your small but extremely career/progression critical problem, and you get scooped by an AI you talk to. No one is even going to care.
Re: The Navier–Stokes Millennium Prize Problem
#78Occam's Razor says: "They heard this problem is solved or about to be solved amongst the rest of the other problems. They prioritized this and put substantial compute with their newest model and solved it." I know everyone loves juicy rumors, theories etc. but honestly that is the simplest and most plausible explanation given the state of AI improvement now. Obviously spending 15 million on a problem is not a slam du…
Why is that simple or plausible? Why is simpler or more plausible than lifting an almost-finished solution from a researcher's account?
Re: The Navier–Stokes Millennium Prize Problem
#79> The discovery is somewhat overshadowed by accusations of skulduggery from Tristan Buckmaster [...]
I think you should not say that. Buckmaster did only state his version of events and was very clear on that he did not make any accusations at all.
To quote from his statement pdf:
> I am not accusing anyone of anything.
Re: The Navier–Stokes Millennium Prize Problem
#80Earlier quoted context omitted.
If that is the case, why on earth would you use it in any professional setting?
Depends on your profession? I sometimes work on open source code as part of my professional duties. Nothing that goes on there is necessary to keep private.
Vulnerabilities, responsible disclosure etc?