in terms of communication utility, it's also a very accurate term.
when WE hallucinate, it's because our internal predictive models are flying off the rails filling in the blanks based on assumptions rather than referencing concrete sensory information and generating results that conflict with reality.
when AIs hallucinate, it's due to its predictive model generating results that do not align with reality because it instead flew off the rails presuming what was calculated to be likely to exist rather than referencing positively certain information.
it's the same song, but played on a different instrument.
when WE hallucinate, it's because our internal predictive models are flying off the rails filling in the blanks based on assumptions rather than referencing concrete sensory information and generating results that conflict with reality.
Is it really? You make it sound like this is a proven fact.
Now that's just not fair. I don't think any of us have a problem with handicapped cows getting the special help they need, be it a wheelchair or a prosthetic arm.
Thanks for the unprompted mansplanation bro, but I was specifically refering to the comment that replied "JuSt lIkE hUmAn BrAin", to "they generate data based on other data"
That's crazy, because they weren't even talking about keyboard autofill, so why'd you even bring that up? How can you imply my comment is irrelevant when it's a direct response to your initial irrelevant comment?
Nice hijacking of the term mansplaining, btw. Super cool of you.
Fine, I'll play along, chew it up for you, since you've been so helpful and mansplained that a keyboard is different than LLM:
My comment was responding to anthropomorphization of software. Someone said it's not human because it just generates output based on input. Someone else said "just like human brain", I said yes, but also just like a keyboard, alluding to the false equivalence.
Oh man, I'm excited for you. Today is the day you learn words can have two meanings! Wait until you see what the rest of the dictionary contains. It is crazy! But not actually crazy, because dictionaries don't have brains.
No fucking shit it’s an anthropomorphization, nothing that can be hosted on GitHub has true human qualities…
The point is that everyone knows what it means within that context of AI, and using other terminology would only serve to obfuscate your message such that the average person couldn’t understand it as easily.
Non-living things also don’t have “behavior” (“the way in which someone conducts oneself or behaves”, but—hey look! People started anthropomorphizing things so much that it got added to the dictionary! (“the way in which something functions or operates”.)
It may not be ideal, and convince some people that LLMs are more human-like than they really are, but the one thing you haven’t done is suggest an alternative that would convey its meaning as effectively to the masses.
Which is okay. I learn new things every day. I just find funny the fact that the other commenter is so fixated on the idea of "it can't be real because I never heard of it."
An anthropomorphic model of the software, wherein you can articulate things like "the software is making up packages", or "the software mistakenly thinks these packages ought to exist", is the right level of abstraction for usefully reasoning about software like this. Using that model, you can make predictions about what will happen when you run the software, and you can take actions that will lead to the outcomes you want occurring more often when you run the software.
If you try to explain what is going on without these concepts, you're left saying something like "the wrong token is being sampled because the probability of the right one is too low because of several thousand neural network weights being slightly off of where they would have to be to make the right one come out consistently". Which is true, but not useful.
The anthropomorphic approach suggests stuff like "yell at the software in all caps to only use python packages that really exist", and that sort of approach has been found to be effective in practice.