Geoffrey Hinton

It plays chess the same way a talented person plays chess, it's just better.

So it plays chess the way Mikael Thal played chess, where he makes sort of brilliant sacrifices where it's not clear what's going on until a few moves later when you're done for.

And it does that without doing huge searches, because it has very good chess intuitions.

So you might ask, since it got much better than us at Go and chess, could the same thing happen with language?

Now, at present, the way it's learning from us is just like when the Go programs mimic the moves of experts.

The way it learns language is it looks at documents written by people and tries to predict the next word in the document.

That's very much like trying to predict the next move made by a Go expert.

And you'll never get much better than the Go experts like that.

So is there another way it could kind of learn language or learn from language?

And there is.

So with AlphaGo, it played against itself, and then it got much better.

And with language, now that they can do reasoning,

A neural net could take some of the things it believes and now do some reasoning and say, look, if I believe these things, then with a bit of reasoning, I should also believe that thing.

But I don't believe that thing.

So there's something wrong somewhere.

There's an inconsistency between my beliefs and I need to fix it.

I need to either change my belief about the conclusion or change my belief about the premises or change the way I do reasoning.

But there's something wrong that I can learn from.

Are we talking about experiences here?

So this will be a neural net that just takes the beliefs it has in language, expressed in language, and does reasoning on them to derive new beliefs, just like the good old-fashioned symbolic AI people wanted to do.