Comment by michaelt

I think very few people on this forum believe LLMs are correct in a systematic way, but a lot of people seem to think there's something more than predicting words from other words.

Modern machine learning models contain a lot of inscrutable inner layers, with far too many billions of parameters for any human to comprehend, so we can only speculate about what's going on. A lot of people think that, in order to be so good at generating text, there must be a bunch of understanding of the world in those inner layers.

If a model can write convincingly about a soccer game, producing output that's consistent with the rules, the normal flow of the game and the passage of time - to a lot of people, that implies the inner layers 'understand' soccer.

And anyone who noodled around with the text prediction models of a few decades ago, like Markov chains, Bayesian text processing, sentiment detection and things like that can see that LLMs are massively, massively better than the output from the traditional ways of predicting the next word.