This misses that key point that all this prediction can give rise to what looks like astonishing human-level creativity and across many genres. The last decade and half have shown us that with enough data we can pick out patterns well enough to be able to "categorize". But to create, that seemed like a whole another human level outside the realm of mere prediction. Turns out it isn't. What exactly allows LLMs to have this capacity for flexible mimicry? I mean, I can ask it to generate a rap battle between Eminem and Daniel Dennett about consciousness and it can do it very decently.

https://twitter.com/SaiDrGaddam/status/1625750884541169666

That just seems like it shouldn't be so "effortless". What is in here that makes it possible?

edit: OK, the article (which is a wonderful introduction, dont want to seem dismissive) does sort of address this but is buried

"We can think of the construction of computational language—and semantic grammar—as representing a kind of ultimate compression in representing things. Because it allows us to talk about the essence of what’s possible, without, for example, dealing with all the “turns of phrase” that exist in ordinary human language. And we can view the great strength of ChatGPT as being something a bit similar: because it too has in a sense “drilled through” to the point where it can “put language together in a semantically meaningful way” without concern for different possible turns of phrase."

That for me is the real fascinating question. What's allowing LLMs to tap into this semantic grammar and do it so flexibly?