Terence Tao

and not add all these extra features, but just have something of the same sort of level of functionality, then actually it doesn't save that much, to be honest.

So it's made the papers sort of richer and broader, but not necessarily deeper.

Yeah, so intelligence is famously hard to define.

It's one of these things that you kind of know it when you see it.

But when I talk to someone, and we're trying to collaboratively solve a math problem together,

There's this conversation where neither of us knows how to solve the problem initially, but one of us has some idea and it looks promising.

And so then we have some sort of prototype strategy and then we test it and then it doesn't work, but then we modify it.

And there's some adaptivity and continuing improvement of the idea over time.

And eventually, we've mapped out what doesn't work, what does work, and we can kind of see a path forward.

But it's evolving with our discussion.

And this is not quite what the AI is.

The AI can kind of mimic this a little bit.

So to go back to this analogy of these jumping robots, so they can jump and fail and jump and fail and jump and fail.

But what they can't do is they kind of jump a little bit.

And they reach some handhold.

But then they sort of stay there.

And then they pull other people up.

And then they try to just jump from there.

There isn't this cumulative process which is sort of built up interactively.

It seems to be a lot more trial and error and just repetition brute force, which it scales and it can work amazingly well in certain contexts.