Comment by Sprotch
2 days ago
Thanks - that makes sense. On that basis the article’s thesis is totally wrong - it would be like a computer program rating its ability based on how well it predicts moves played by grandmasters in the past. It’s not inventing new moves.
I wouldn't necessarily say that. Anybody who's playing a chess game is predicting their next move, whether or not they're inventing new moves.
LLMs are not simple things like a Markov model, there's a lot going on in there, it's not deterministic, and it's completely capable of creating entire new styles of play based on complex interactions of internal states.
> LLMs are not simple things like a Markov model
"Large Language Models as Markov Chains" https://www.alphaxiv.org/pdf/2410.02724
Argh, what I wrote was obviously wrong. What I meant was to refer to the simple n-state Markov models as used past decades.
Anything that's sequential, like language is, will exhibit Markovian properties, and be somewhat a "Markov" model.
Markov chains are a different concept than a Markov model, but I do agree that, technically, an LLM is a Markov model, just with an internal state space that is nothing like what is usually meant when ML people refer to Markov models.