Stephen Wolfram

Yes, right.

And in fact, I kind of gave the, I had this quote from Hal to explain, you know, it's as the Hal states in the movie, you know, it's the Hal 9000 is, you know, the thing was just a rhetorical device because I'm realizing, oh my gosh, you know, this chat GPT,

could have easily fooled me.

I mean, it did this amazing thing of knowing this thing about the movie and being able to turn that into the notes of the song, except it's the wrong song.

And Hal, in the movie, Hal says, I think it's something like, no 9,000 series computer has ever been found to make an error

We are, for all practical purposes, perfect and incapable of error.

And I thought that was kind of a charming sort of quote from Hal to make in connection with what ChatGPT had done in that case.

The interesting thing is about the LLMs, like you said, that they are very willing to admit their error.

Well, yes.

I mean, that's a question of the RLH, the Reinforcement Learning Human Feedback thing.

Oh, right.

That's, you know, an LLM.

The really remarkable thing about ChatGPT is, you know, I had been following what was happening with large language models, and I played with them a whole bunch, and they were kind of like, eh, you know, kind of like what you would expect based on sort of statistical continuation of language.

It's interesting, but it's not breakout exciting.

And then I think the kind of reinforcement, the human feedback reinforcement learning, you know, in making ChatGPT try and do the things that humans really wanted to do, that broke through, that kind of reached this threshold where the thing really is interesting to us humans.

And by the way, it's interesting to see how, you know, you change the temperature or something like that, the thing goes bonkers.

And it no longer is interesting to humans.

It's producing garbage.

Yeah.

And it's kind of right.