Comment by vouaobrasil
11 hours ago
Not exactly, because we would have cool people to inspire us and hang out with us.
But your argument is nonsensical because even if Gauss and von Neumann appeared, they wouldn't go into random fields and just prove things mechanically. They'd have to attend seminars, teach others, collaborate with others, and generally inspire others with their brilliance. It's the precise lack of this activity that makes AI in math so reprehensible.
Your argument encapsulates a contradiction because human mathematicians wouldn't be dropping proofs arbitrarily like AI is doing. They would do something completely different. Even the best of them.
Gauss was generally quite secretive and Ramanujan would famously tell people answers that he had received from divine inspiration, often with no ability to articulate how he knew. Von Neumann did just go into random fields and revolutionize them. If the three of them did come back from the dead and form a little powerhouse group that barely collaborated with the outside and just started publishing results for everyone else to try to keep up with, they'd no doubt still be considered geniuses.
Give it six months and models might be able to explain things better than any human. They can already collaborate perfectly well if you ask them to. e.g. there was a post here a couple months ago where Tao shared his ChatGPT logs[0].
If you're not inspired by the ability to talk to a superintelligent machine, and can't find what you'd want to know, that's a you problem.
[0] https://news.ycombinator.com/item?id=49010345
> Give it six months
Ah, the "six months till AGI" meme, but unironically :)
Also, before citing Terence Tao on LLMs maybe you should read what he has to say about it...
It's been doing all of the actual coding part of my job for the better part of a year, and you're commenting on a post about how it just released another round of math breakthroughs, besting a bunch of top humans. It can search the web and analyze documents it finds for me. It can do reverse engineering. It can analyze and create images.
Not sure what your definition of AGI is, but it clearly has superhuman performance on most knowledge work already. Do you think after already having demonstrated that it can solve top problems, that the final frontier it won't be able to cross is explaining its solutions to the experts that were researching those problems, and eventually to e.g. grad student or postdoc level practitioners as a lecture course/set of notes?