Exactly! All LLMs do is “hallucinate”. Sometimes the output happens to be right, same as a broken clock.
Just like every other form of ML we've come up with, LLMs are imperfect. They get things wrong. This is more of an indictment of yeeting a pure AI chat interface in front of a consumer than it is an indictment of the underlying technology itself. LLMs are incredibly good at doing some things. They are less good at other things.
There are ways to use them effectively, and there are bad ways to use them. Just like every other tool.
There's no shortcut to figuring out what the truth of what a new technology is actually useful for. It's very rarely the case that either "everything" or "nothing" is the truth.
It's not about it being perfect or not. It's about how they come about with the responses they do.
>Very few people seem to go around talking about how their binary classifier is always hallucinating, but just sometimes happens to be right.
Yeah, but no one is anthropomorphizing binary classifiers.