> nothing about statistical models are like people.
As if we're not behaving like statistical models. Our decision-making is so fuzzy and probabilistic that trying to get us to stick to fixed sets of rules consistently is one of the things humanity spends the most time inventing systems to try to handle, and keep failing at. We don't even know a consistent way of achieving it for extremely basic things. We can't keep ourselves to rules we set ourselves with any consistency.
I don’t really feel like having the stochastic parrot debate again, but look it up.
We’re more than parrots.
Yes, we're more than parrots, but that does not mean we can be described equally validly as "statistical models". Suggesting something is "just" a statistical model is a statement that is close to semantically void. It tells us near nothing about the computational limits - up or down - of something. Even a very simple system for running a statistical model with a loop around it providing IO can be made Turing complete.
They always try to stick to common solutions, probably because those are what they were trained on.
Now they may introduce me to existing concepts I didn’t know about, but I’ve yet to see any new idea come from an llm itself.
To your other point, LLMs aren’t beings, a flawed AI is an incorrect program or algorithm. Entertaining, maybe, useful in some contexts, sure.
But they’re not beings. nothing about statistical models are like people. I think it’s dangerous to use such fuzzy conflating language with regards to AI.