[patagurbon]

That Erdos problem solution is believed by quite a few to be a previous result found in the literature, just used in a slightly different way. It also seems not a lack of progress but simply no one cared to give it a go.

That’s a really fantastic capability, but not super surprising.

[bakkoting]

You're thinking of a previous report from a month ago, #897 or #481, or the one from two weeks ago, #728. There's a new one from a week ago, #205, which is genuinely novel, although it is still a relatively "shallow" result.

Terence Tao maintains a list [1] of AI attempts (successful and otherwise). #205 is currently the only success in section 1, the "full solution for which subsequent literature review did not find new relevant prior partial or full solutions" section - but it is in that section.

As to speed, as far as I know the recent results are all due to GPT 5.2, which is barely a month old, or Aristotle, which is a system built on top of some frontier LLMs and which has only been accessible to the public for a month or two. I have seen multiple mathematicians report that GPT-5.2 is a major improvement in proof-writing, e.g. [2]

[1] https://github.com/teorth/erdosproblems/wiki/AI-contribution...

[2] https://x.com/AcerFur/status/1999314476320063546

[utopiah]

Thanks for the wiki link, very interesting, in particular

- the long tail aspect of the problem space ; 'a "long tail" of under-explored problems at the other, many of which are "low hanging fruit" that are very suitable for being attacked by current AI tools'

- the expertise requirement, literature review but also 'Do I understand what the key ideas of the solution are, and how the hypotheses are utilized to reach the conclusion?' so basically one must already be an expert (or able to become one) to actually use this kind of tooling

and finally the outcomes which taking into consider the previous 2 points makes it very different from what most people would assume as "AI contributions".