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What, Erdős problems? It's hard to see how anyone except mathematicians, and then again only a few communities of mathematicians, especially care about those. Remember back in the day when Deep Mind made AlphaGo? That made huge waves for two reasons: one, it was very well understood by AI researchers that beating expert humans at Go was very hard; and, two, that Go is a game of great cultural significance to literally billions of people outside of academia, albeit mainly in SE Asia. Now, Erdős? I'm a computer scientist and I had to look up the planar unit distance problem when I heard about it because I had no idea what that was. Because it never comes up in the literature I read. I'm not saying it's not interesting, but it does seem a bit... random? That they started with Erdős problems? I'd have gone for a Millennium Prize problem, first. P vs NP, Riemann, Navier Stokes, those are heavy-weight results that would establish AI as the de facto approach to mathematics for the foreseeable future. Even I would find it hard to raise an objection (imagine that). Erdős can take a number, compared to all that. I'm not saying they're choosing problems at random, mind. But it does seem like we're only seeing the tip of the iceberg, with respect to what the AI companies are doing internally. That shouldn't be a surprise. That's exactly how research works in general, both in academia and in industry. There is a clear survivorship bias and we only ever get to see the positive results, never the negative ones. >> The 2 most notable/interesting solutions have come from Open AI directly, but most of the 'LLM solves open problem' category didn't and has come from 3rd parties doing their own thing with publicly available models. I don't see why one would assume they're running models on hundreds of problems. Actually, that's a good point but it's in support of my contention. If there are random people in the community running LLMs on their own, favourite, maths problems, we should be seeing many more of those solved and much more often, provided LLMs were really as good at maths as OpenAI et al want them to be. There must be literally thousands of mathematicians trying to use LLMs to solve this or that problem that is famous in their community. Where are all those spectacular results? Or, to abuse Fermi's question, where is everybody? |
Erdős problems vary enormously in difficulty and significance. The fact that a problem is obscure to non-mathematicians does not make its solution unimportant. There are also many major open problems in computer science that most laypeople have never heard of.
>That they started with Erdős problems? I'd have gone for a Millennium Prize problem, first. P vs NP, Riemann, Navier Stokes, those are heavy-weight results that would establish AI as the de facto approach to mathematics for the foreseeable future.
Solving the biggest, most famous open problems would "establish AI as the de facto approach to mathematics for the foreseeable future"? It would do a lot more than that.
>That's exactly how research works in general, both in academia and in industry.
Then what exactly is the objection? Research normally produces many failures and incremental results before a major success. Do you apply this survivorship-bias criticism to every published mathematical result, or only when a machine contributed to it?
>Actually, that's a good point but it's in support of my contention.
If they're running as many problems as constantly as you imagine then they did not miss all that. So either they're just not sharing it us which contends with your "desperate to demonstrate mathematical competence" or they have their eyes on a more curated set.
>Or, to abuse Fermi's question, where is everybody?
If we had as many verified alien encounters as LLM contributions to open problems, nobody would be invoking the Fermi Paradox. Where is everyone? Right here.