So then you agree with the OP that an LLM is not intelligent in the same way that Google Maps is not intelligent? That seems to be where your argument leads but you're replying in a way that makes me think you are disagreeing with the op.
If you're comparing the output of an LLM to a lexicon, you're agreeing with the person you originally replied to. He's arguing that an LLM is incapable of being true or false because of the manner in which its utterances are created, i.e. not by a mind.
This would be unlike a human, who can be right or wrong independently of an utterance, because they have a mind and beliefs.
And of course a thing in and of itself, be it an apple, a dog or an LLM, can’t be true or false.
That classical or quantum mechanics are at all useful depends on the truthfulness of their propositions. If we cared about the process then we let the non-intuitive nature of quantum mechanics enter into the judgement of the usefulness of the science.
The better question to ask is if a tool, be it a book, a thermometer, or an LLM are useful. Error rates affect utility which means that distinctions between correct and incorrect signals are more important than attempts to define arbitrary labels for the tools themselves.
You’re attempting to discount a tool based on everything other than the utility.
Though in this case I'm not even sure what the comment they're supposedly disagreeing with is even claiming. Is it even claiming anything?
Disagree! :)
> Though in this case I'm not even sure what the comment they're supposedly disagreeing with is even claiming. Is it even claiming anything?
It's offering support for the claim that LLMs hallucinate 100% of the time, even when their hallucinations happen to be true.
Well this makes the term "hallucinate" completely useless for any sort of distinction. The word then becomes nothing more than a disparaging term for an LLM.
For example, does this distinction affect the assessed truthfulness of a signal?
Does process affect the artfulness of a painting? “My five year old could draw that?”
I think that's taking things a bit too far though. You can define hallucination in a more useful way. For instance you can say 'hallucination' is when the information in the input doesn't make it to the output. It is possible to make this precise, but it might be impractically hard to measure it.
An extreme version would be a En->FR translation model that translates every sentence into 'omelette du fromage'. Even if it's right the input didn't actually affect the output one bit so it's a hallucination. Compared to a model that actually changes the output when the input changes it's clearly worse.
Conceivably you could check if the probability of a sentence actually decreases if the input changes (which it should if it's based on the input), but given the nonsense models generate at a temperature of 1 I don't quite trust them to assign meaningful probabilities to anything.