Nope. It's an argument from Lyapunov exponents, translated into layman's terms. Edit: I noticed we could be reading this in different directions -- I'm reading

Nope. It's an argument from Lyapunov exponents, translated into layman's terms. Edit: I noticed we could be reading this in different directions -- I'm reading the OP's post as treating LLMs as large Markov-chain-memorizing models, which is where the statistics argument comes into play. Heck, the curse of dimensionality alone makes the memorization aspect of it intractable, so there is a sort of compression, only what kind of compression. I agree that statistically it's going to approach what happens in the real world on the text as things get larger, but simple hallucinated chains of text in an autoregressive matter severely breaks the causal regime. I think that was where I was coming from originally, please do let me know if I've misunderstood, however. Second Edit: w.r.t. to the underlying manifold generalization, yes, this is a natural consequence of the operators used. directly measuring how much it's happening is intractable but by the nature of the system operating under them we are actually somewhere on that compressive spectrum of generalization.