←back to thread

277 points simianwords | 1 comments | | HN request time: 0.23s | source
Show context
amelius ◴[] No.45149170[source]
They hallucinate because it's an ill-defined problem with two conflicting usecases:

1. If I tell it the first two lines of a story, I want the LLM to complete the story. This requires hallucination, because it has to make up things. The story has to be original.

2. If I ask it a question, I want it to reply with facts. It should not make up stuff.

LMs were originally designed for (1) because researchers thought that (2) was out of reach. But it turned out that, without any fundamental changes, LMs could do a little bit of (2) and since that discovery things have improved but not to the point that hallucination disappeared or was under control.

replies(10): >>45149354 #>>45149390 #>>45149708 #>>45149889 #>>45149897 #>>45152136 #>>45152227 #>>45152405 #>>45152996 #>>45156457 #
1. hodgehog11 ◴[] No.45149708[source]
I don't agree that it is an ill-defined problem, since we can design separate models to excel in each of these two tasks. For a "factual" LLM, if the output is a verifiable statement, it should be correct. Otherwise it "hallucinates". But since an LLM can't know everything, a better approach is to effectively state its own uncertainty so that it avoids making definitive statements with low confidence.