Comment by qnleigh

5 days ago

> It doesn't discern between them, just looks for the best statistical fit

Of course at the lowest level, LLMs are trained on next-token prediction, and on the surface, that looks like a statistics problem. But this is an incredibly reductionist viewpoint and I don't see how it makes any empirically testable predictions about their limits. LLMs 'learned' a lot of math and science in this way.

> "truly novel" and "solving unsolved math problem"

OK again if novelty lies on a continuum, where do you draw the line? And why is it correct to draw it there and not somewhere else? It seems like you are just naming exceptionally hard research problems.

>LLMs 'learned' a lot of math and science in this way.

Did they? Or is it begging the question?

  • This is why I put 'learned' in quotes. They started from a state of not being able to solve algebra problems or produce basic steps of scientific reasoning to being able to. Operationally, that is what I mean by learning and they unambiguously do it.