←back to thread

277 points simianwords | 1 comments | | HN request time: 0s | source
Show context
rhubarbtree ◴[] No.45152883[source]
I find this rather oddly phrased.

LLMs hallucinate because they are language models. They are stochastic models of language. They model language, not truth.

If the “truthy” responses are common in their training set for a given prompt, you might be more likely to get something useful as output. Feels like we fell into that idea and said - ok this is useful as an information retrieval tool. And now we use RL to reinforce that useful behaviour. But still, it’s a (biased) language model.

I don’t think that’s how humans work. There’s more to it. We need a model of language, but it’s not sufficient to explain our mental mechanisms. We have other ways of thinking than generating language fragments.

Trying to eliminate cases where a stochastic model the size of an LLM gives “undesirable” or “untrue” responses seems rather odd.

replies(9): >>45152948 #>>45153052 #>>45153156 #>>45153672 #>>45153695 #>>45153785 #>>45154058 #>>45154227 #>>45156698 #
1. asats ◴[] No.45154058[source]
Exactly. I always found it strange when people assume that "hallucinations" are just some sort of a bug in the system, as if by you tweaking some code or training modality will produce an oracle of absolute truth incapable of making mistakes.