Comment by f_klem
8 hours ago
Agreed, formatting was kind of f, but there is no need to be rude.
I wasn't saying there was any difference. All I'm saying is that the claimings the AI research field does are based on false assumptions. And from false assumptions, you cannot reach a proper conclusion.
Whether an AI system can reason and think like if it where a human being, or not, I don't care. I'm fine with either: it is just technological advance. But making claims based on false assumptions, and then being fooled by how 'wonderful' or 'spectacular' the results are, is, at least, naive.
> Nothing but human insecurity, in my eyes. There was never a principled difference. Just a way to operationalize some "I'm unique and special and better than a matrix math machine" vibes.
This is just something I don't get. People ignorant of technique are insecure and afraid. People that know how technology works, and thus investigate and know how it works fundamentally*, were never afraid or insecure.
A lot of people who "know how technology works" just went looking for copium, and found some. Now, they "know" a comforting lie - something like "it's just next token prediction".
Very comforting, that, but actively harmful to understanding.
The understanding starts with: we don't actually know how LLMs do what they do. They're more grown than designed. And it only gets worse from there. Very little comfort to be found in modern AI.
There are two things here: one is how an LLM is fundamentally structured and designed, the other is how an LLM distributes and 'lays out' the relationship between inputs and outputs through layers and weights.
We might not know how the actual distribution works, but we do know how it i s fundamentally structured and designed -- because we did it. We also know that there is something like a representation system inside them. And we also know that human beings do not hold 'internal representations' like any AI system needs to. So there isn't any 'intrinsically magical' in modern AI systems.