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Comment by NitpickLawyer

21 hours ago

Terrence Tao, in a recent podcast, said that he's very interested in "working along side these tools". He sees the best use in the near future as "explorers of human set vision" in a way. (i.e. set some ideas/parameters and let the LLMs explore and do parallel search / proof / etc)

Your comparison with chess engines is pretty spot-on, that's how the best of the best chess players do prep nowadays. Gone are the multi person expert teams that analysed positions and offered advice. They now have analysts that use supercomputers to search through bajillions of positions and extract the best ideas, and distill them to their players.

The key distinction is that chess players compete against each other, whereas mathematicians engage in a dialogue with mathematics itself.

> They now have analysts that use supercomputers to search through bajillions of positions and extract the best ideas, and distill

I was recently researching AI's for this, seems it would be a huge unlock for some parts of science where this is the case too like chess

Similar to https://en.wikipedia.org/wiki/Advanced_chess

The Wikipedia doesn't have much info on the results, but from other reading I got the impression that the combination produced results stronger than any individual human or computer player.

  • My understanding is that they did, but don't any more; it's no longer true that humans understand enough things about chess better than computers for the human/computer collaboration to contribute anything over just using the computer.

    I don't think the interval between "computers are almost as strong as humans" and "computers are so much stronger than humans that there's no way for even the strongest humans to contribute anything that improves the computer's play" was very long. We'll see whether mathematics is any different...