lhd1

Is this a major concern? I can imagine them selling the excess compute to other LLM providers just as SpaceX did with Anthropic.

Whether you think they have a future or not does not change fact that they currently are wildly unprofitable.

>internet thing wasn’t going anywhere.

This is conflating the utility of the technology with the economics behind it. Few people claim LLMs are useless. It's a question of figuring out a viable business model.

It would help if this was also written up in the conventional way as a scientific paper (Intro, methods, conclusions, etc). These discursive blog posts are getting exhausting.

Are you suggesting that Tao, whose banner image on his blog is a quote from On Proof and Progress, has not read Thurston's essay?

it's a lot of style over substance

I wonder - was there really no other people they could have given it to? The detection of gravitational waves was split between a theorist, experimentalist and a person who had a big hand in shepherding the project along. Could not the same have been done here?

there are so many extraordinary things about von Neumann that there seems little need to write a fictionalized account of his life. How is the reader to know what is real and what is fiction?

Much of Susskind's papers are like that. A few simple equations motivated by dimensional analysis, a couple of Penrose diagrams, and the rest speculation and insight.

lo and behold, a 1000 word sample comes back in Pangram as AI generated. This should not be worth anyone's time (and maybe you have spent more time on your comment than the author did in their blogpost).

>Mathematics is probably the same way. There's a short-term rush when you pull the lever, but there's less desire to get invested in what comes out.

Perhaps it will take until the next generation to come along to really embrace the new AI-assisted way of doing mathematics. The current generation has too many reservations.

It would be good if someone made a list of allresults obtained with AI so far just to see what kinds of problems AI excels at. Are there any that aren't of the existence-proof type?

Reductively, math can be said to be either problem solving or theory building - it seems the latter is a much harder thing to do right now.

This is also what I've been thinking. The result itself is amazing but it's not like this was completely unexpected. There has been a huge amount of progress on the problem in the last 10 years without which it seems unlikely today's full resolution would have been possible. It is not clear what strategy was taken but it sounds like it borrowed heavily from the two spanish mathematicians. Experts will scrutinize the proof and it will be interesting to see if anything truly original or unexpected was done, outside of known techniques, a move 37.

So what do you think his contribution was? His preprint record shows no research on fluids - and the statement says that the first LLM-generated proof Tristan received from Levent was 'the most horrendous I have ever read.' Levent is out for mathematical scalps whether it is in his field of expertise or not, and he has the resources to do it. And I am not saying he is not a very clever person, but the idea that you can bring yourself up to the forefront of research in PDEs, in particular NS, and contribute new ideas in less than a year is implausible.