Comment by xg15
4 days ago
> which in no way challenge the established view that these bots are next-token predictors.
I mean, of course they are, that's literally what the inference loop does. You can look at the source of your favorite model runner and you'll see exactly that.
What I find misleading about this term is that it focuses attention on the "next token" part and glosses over the "prediction" part as some sort of unspecified "statistical algorithm" - even though this is where most of the work happens and where the interesting questions are.
I've seen nothing to suggest it misleads anyone else.
There are other next token prediction algorithms such as markov chains or HMMs that also "fit the same interface", but are vastly simpler than what LLMs use.
I've seen various posters talk about "stochastic parrots" or about how LLMs were just "using very simple word statistics" to get their results, which sounded to me very much as if they thought of LLMs simply as glorified markov chains. I would consider that a big misunderstanding.
No misunderstanding at all.
"In machine learning, the term stochastic parrot is a metaphor that frames large language models as systems that statistically mimic text without real understanding." https://en.wikipedia.org/wiki/Stochastic_parrot
"Large Language Models as Markov Chains" https://arxiv.org/abs/2410.02724