Terence Tao

We don't know which ones are tall, which ones are short.

And so we try to light some candles and make some maps.

And slowly, we kind of figure out some of them are climbable.

Some of them, we can identify some partial crack in the wall that you can reach first.

And then these AI tools, they're kind of like these jumping machines that can kind of jump, you know, two meters in the air, you know, higher than any human.

And sometimes they jump in the wrong direction and sometimes they crash, but sometimes they can reach the tops of the lowest walls that we couldn't reach before.

And so we basically set them loose in this mountain range, hopping around.

And then there was this exciting period where they could actually find all the low ones and they could reach them.

But then there's been no... I mean, maybe if the next time there's a big advance in the models, then they will try it again and maybe a few more will be...

will be breached but it's a different style of doing mathematics than sort of the you know so normally we would hill climb and you know we would we would make little markers and try to identify partial things and

These tools, they either succeed or they fail.

And they've been really bad at creating sort of partial progress or identifying intermediate stages that you should focus on first.

Again, going back to this previous discussion, we don't have a way of evaluating partial progress.

The same way you can evaluate a one-shot success or failure of solving a problem.

I agree.

So they excel at breadth, and humans excel at depth, and human experts, at least.

So I think they're very complementary.

But our current way of doing math and science is focused on depth because that's where the human expertise is because humans can't do breadth.

But yeah, so we have to redesign the way we do science to take full advantage of this breadth capability that we now have.

So as I said, we should have a lot more effort in creating very broad classes of problems to work on rather than one or two really deep, important problems.