[p1necone]

> Aside from the possibility of "emerging intelligence", I don't think this is the way to the AGI.

My intuition is that this is the only way to create AGI. I don't think anyone is ever going to carefully intentionally construct an AGI, it's almost certainly going to emerge from something conceptually fairly simple.

I don't think it's impossible that our own brains are also basically just a big statistical prediction model too. Maybe AGI just requires our models to be 10/100/1000x as good. Or our training data needs to be broader in a qualitative way rather than a quantitative way that we haven't quite worked out yet.

[ducktective]

Can you prove Fermat last theorem via giving a high parameter LLM a very large amount of mathematical knowledge?

[317070]

Yes.

I would even be surprised if in 10 years an AI wouldn't be able to decide on the Riemann hypothesis given enough compute.

The rate of progress made in the last 10 years has been enormous, but blanks in comparison to the acceleration of the last year. Unless there are yet unknown limits to our current methods, there does not seem anything to stop us from building machines that outperform the field of human mathematics.

I could sketch you a couple of paths there if we manage to leverage current LLM to become self-improving. But even if we don't manage to do that, there are paths to leverage LLM's to solve mathematics. I can outline truly remarkable approaches, which this comment is too small to contain.