Comment by anal_reactor 3 hours ago
There's this huge wave of "don't anthropomorphize AI" but LLMs are much easier to understand when you think of them in terms of human psychology rather than a program. Again and again, HackerNews is shocked that AI displays human-like behavior, and then chooses not to see that.
It reminds me of the start of Ubik[1], where one of the protagonists has to argue with their subscription-based apartment door. Given also the theme of AI allucinations, that book has become even more prescient than when it was written.
This comparison is extremely silly. LLMs solve reliably entire classes of problems that are impossible to solve otherwise. For example, show me Russian <-> Japanese translation software that doesn't use AI and comes anywhere close to the performance and reliability of LLMs. "Please close the castle when leaving the office". "I got my wisdom carrot extracted". "He's pregnant." This was the level of machine translation from English before AI, from Japanese it was usually pure garbage.
> LLMs solve reliably entire classes of problems that are impossible to solve otherwise.
Is it really ok to have to negotiate with a toaster if it additionally works as a piano and a phone? I think not. The first step is admitting there is obviously a problem, afterwards you can think of ways to adapt.
FTR, I'm very much in favor of AI, but my enthusiasm especially for LLMs isn't unconditional. If this kind of madness is really the price of working with it in the current form, then we probably need to consider pivoting towards smaller purpose-built LMs and abandoning the "do everything" approach.
>LLMs solve reliably entire classes of problems that are impossible to solve otherwise
Great! Agreed! So we're going to restrict LLMs to those classes of problems, right? And not invest trillions of dollars into the infrastructure, because these fields are only billion dollar problems. Right? Right!?
Remember: a phone is a phone, you're not supposed to browse the internet on it.
> LLMs are much easier to understand when you think of them in terms of human psychology
Are they? You can reasonably expect from a human that they will learn from their mistake, and be genuinely sorry about it which will motivate them to not repeat the same mistake in the future. You can't have the same expectation from an LLM.
The only thing you should expect from an LLM is that its output is non-deterministic. You can expect the same from a human, of course, but you can fire a human if they keep making (the same) mistake(s).
I'm genuinely wondering if your parent comment is correct and the only reason we don't see the behaviour you describe, IE, learning and growth is because of how we do context windows, they're functionally equivalent to someone who has short term memory loss, think Drew Barrymore's character or one of the people in that facility she ends up in in the film 50 first dates.
Their internal state moves them to a place where they "really intend" to help or change their behaviour, a lot of what I see is really consistent with that, and then they just, forget.
One day you wake up, and find that you now need to negotiate with your toaster. Flatter it maybe. Lie to it about the urgency of your task to overcome some new emotional inertia that it has suddenly developed.
Only toast can save us now, you yell into the toaster, just to get on with your day. You complain about this odd new state of things to your coworkers and peers, who like yourself are in fact expert toaster-engineers. This is fine they say, this is good.
Toasters need not reliably make toast, they say with a chuckle, it's very old fashioned to think this way. Your new toaster is a good toaster, not some badly misbehaving mechanism. A good, fine, completely normal toaster. Pay it compliments, they say, ask it nicely. Just explain in simple terms why you deserve to have toast, and if from time to time you still don't get any, then where's the harm in this? It's really much better than it was before