An AI system solves a widely known open mathematics problem that multiple leading human mathematicians had been unable to resolve after significant effort
Mathematician Timothy Gowers called it one of AI's firsts in the field.
A great example of our field shifting from Benchmaxxing to _Benchmaking_. Only novel results and artifacts count.
If you are a mathematician, then you may want to make sure you are sitting down before reading further.
A respectable milestone in AI for Math. Congrats to everyone involved!
If you are a mathematician, then you may want to make sure you are sitting down before reading further.
Dites-moi, où et en quel pays are the stochastic parrots now?
If you are a mathematician, then you may want to make sure you are sitting down before reading further.
@ChrSzegedy @StatsLime What is really interesting though about these models whether their jaggedness will go away. At the moment, my personal experience is very random.
The next in a series of firsts for AI and mathematics!
If you are a mathematician, then you may want to make sure you are sitting down before reading further.
"AI generating new knowledge and accelerating science will change the trajectory of humanity."
Welcome to the era of Knowledge Accelerationism.
interesting to think of the space of possibilities in the mathematical and physical sciences where humans are amazing at building out entire fields of theory, study, and understanding around but really really bad at the mechanical grunt work
I think we are in the process of discovering that humans are bad at mathematics. A gibbon would scoff at an Olympic climber; the human body is not optimized for climbing. We're getting mounting evidence that our brain may be far from optimal for advanced math. No disrespect to mathematicians. I was a two-time IMO silver medalist; I'm just smart enough to appreciate that some people are much, much smarter. But it's starting to look like math is somewhere on the midpoint of Moravec’s paradox; between chess (computers surpassed us some time back) and cooking (probably many years to go, for general capabilities). It's fairly hard for us, and so it looks like computers are going to surpass us. AI math still has important weaknesses. For instance, AI systems have not yet shown any ability to identify interesting research directions, or develop new concepts on which further work can build. But they are starting to look superhuman in some respects. And once AI *starts* to become superhuman in some domain, we all know what happens next.
example: there’s a big difference between the knowledge work of llms doing coding projects that take a few hours-days mostly autonomously w/ minimal guidance from me vs taking alex radford’s pre-1931 llm and having it recreate 80 years of fundamental computer science theory
interesting to think of the space of possibilities in the mathematical and physical sciences where humans are amazing at building out entire fields of theory, study, and understanding around but really really bad at the mechanical grunt work
@roydanroy So I think it's both quite impressive (because I think this problem is cool) and in a way also not so impressive.
@roydanroy Combinatorialists and incidence / discrete geometry experts wouldn't have any Algebraic number theory chops. AI models can pattern match wherever they want. Erdos also believing that the conjecture was true biased folk. The LM could run amok in either direction.