Sean Carroll

Thank you very much.

about simple problems adding medium-sized numbers together.

Other kinds of number-based problems they're not very good at.

Counting the number of Rs in the word strawberry.

Random numbers.

If you ask an LLM to generate a million random integers between 0 and 100 and then made a plot of the frequencies, it would not look uniform.

Of course, these are all things that human beings are also intrinsically not very good at.

But part of you thinks, come on, it's a computer.

It should be able to do simple arithmetic problems.

And of course, the answer is there's no real mystery here.

The computer on which the LLM is running has no problem doing arithmetic.

But you're not talking to the computer.

You're talking to a program.

and the program might not be set up to do those kinds of things.

And again, it's exactly like humans.

It's almost like you tried really hard to make a program that sounded human, and in the course of doing that, it lost the ability to do arithmetic, which is kind of interesting when you think about it.

But it's also a reminder that when you say thought or thinking, you're not really referring to a single thing.

The ability to add numbers together and the ability to carry on a conversation, those are two very different abilities.

And you might optimize for one over the other in building a program or evolving an organism through natural selection.

Nevertheless, we do sort of aim at a sort of standard set of standards for thinking correctly, right?