Francois Chollet

But it comes up quite a bit on the internet.

So they've basically memorized it.

And what's really interesting is that they can do it for a transposition length of like three or five, because there are very, very common numbers in examples provided on the internet.

But if you try to do it with an arbitrary number, like nine, it's going to fail.

because it does not encode the generalized form of the algorithm, but only specific cases.

It has memorized specific cases of the algorithm, right?

And if it could actually synthesize on the fly the Solver algorithm, then the value of n would not matter at all, because it does not increase the problem complexity.

I think this is true of humans as well, where, what was the study that- Humans use memorization pattern matching all the time, of course, but humans are not limited to memorization pattern matching.

They have this very unique ability to adapt to new situations on the fly.

This is exactly what enables you to navigate

every new day in your life.

Chess memorization.

I would assume that it has simply mined from its extremely extensive, unimaginably vast training data.

It has mined the required template and then it's just reusing it.

We know that LLMs have a very poor ability to synthesize new program templates like this on the fly or even adapt existing ones.

They're very much limited to fetching.

Forget about Google software developers.

Every human, every day of their lives is full of novel things that they've not been prepared for.

You cannot navigate your life based on memorization alone.

It's impossible.