Stuart Russell

I think there's some truth to that.

Yeah, I mean, I think the extent to which a human grandmaster can reliably, instantly recognize the right move and instantly recognize the value of a position, I think that's a little bit overrated.

Yeah, so I think what happens is you get a sense that there's some possibility in the position, even if you make a weird looking move, that it opens up some lines of movement.

calculation that otherwise would be definitely bad.

And it's that intuition that there's something here in this position that might yield a win.

And then you follow that, right?

And in some sense, when a chess player is following a line in his or her mind, they're

they're mentally simulating what the other person is going to do, what the opponent is going to do.

And they can do that as long as the moves are kind of forced, right?

As long as there's a, you know, there's a, we call a forcing variation where the opponent doesn't really have much choice how to respond.

And then you see if you can force them into a situation where you win.

You know, we see plenty of mistakes, even in Grandmaster games, where they just miss some simple three, four, five move combination that wasn't particularly apparent in the position, but was still there.

Part of the meta-reasoning capability that it had was based on learning.

And

And you could sit down the next day and you could just feel that it had got a lot smarter.

And all of a sudden you really felt like you were sort of pressed against the wall because it was much more aggressive and was totally unforgiving of any minor mistake that you might make.

And actually it seemed understood the game better.

I think it's definitely an exciting feeling.

You know, this is what made me

work on AI in the first place was as soon as I really understood what a computer was, I wanted to make it smart.