Okay.

"But by training something to be really good at predicting the next word, you're actually forcing it to understand." Well, that, that's com- [chuckles] that's...

It's assuming what he's trying to prove, and the fact that you can predict the next word in a sentence doesn't mean you understand what the words mean.

Uh, it, it's just a fundamental misunderstanding, and the consequence of that is these large language models are really good, or AI in general, really good at finding statistical correlations, finding statistical patterns.

But in terms of separating the wheat from the shaft, separating the ones that are useful from the ones that are just coincidental, temporary correlations, they have no...

There's absolutely no way to do that because, again, they don't understand what the words mean.

So here's, here's an example.

Okay.

Okay.

But by training something to be really good at predicting the next word, you're actually forcing it to understand.

It's assuming what he's trying to prove.

And the fact that you can predict the next word in a sentence doesn't mean you understand what the words mean.

It's just a fundamental misunderstanding.

And the consequence of that is these large language models are really good, or AI in general, really good at finding statistical correlations, finding statistical patterns, but in terms of separating the wheat from the chaff, separating the ones that are useful from the ones that are just coincidental temporary correlations, there's absolutely no way to do that because, again, they don't understand what the words mean.

So here's an example.

Okay.