[AnimalMuppet]

Well... ideas are actually encoded (to some degree) in the words in the training data. So when they synthesize new text, they are, to a degree, synthesizing new ideas.

To a degree. The problem is that they don't actually understand the ideas in the training data. (Yeah, you can say we don't know how humans actually understand ideas. True, but not the point. However we understand ideas, LLMs don't do that.) And so they can only synthesize new ideas by rearranging words. This is much less than that human thinking. In particular, it seems that it could only generate ideas that are only new recombinations, not breakthrough ideas.

[Terr_]

> Well... ideas are actually encoded (to some degree) in the words in the training data. So when they synthesize new text, they are, to a degree, synthesizing new ideas.

I don't think that follows: Manipulating a (lossy, imperfect) encoding [0] isn't the same as manipulating the thing it was intended to evoke.

If it is true, then... Well, it's not true in the same way anybody is excited about, because it means "synthesizing new ideas" is something we've been able to do for many decades and which you can easily script up right now at home [1].

[0] https://en.wikipedia.org/wiki/Encoding_(semiotics)

[1] https://benhoyt.com/writings/markov-chain/