Comment by ben_w

> There is no thinking. No comprehension. No decisions.

Re-reading my own comment, I am unclear why you think it necessary to say those specific examples — my descriptions were "results, made, disagree, right/wrong, struggle": tools make things, have results; engines struggle; search engines can be right or wrong; words can be disagreed with regardless of authorship.

While I am curious what it would mean for a system to "think" or "comprehend", every time I have looked at such discussions I have been disappointed that it's pre-paradigmatic. The closest we have is examples such as Turing 1950[0] saying essentially (to paraphrase) "if it quacks like a duck, it's a duck" vs. Searle 1980[1] which says, to quote the abstract itself, "no program by itself is sufficient for thinking".

> I guess my point is, when you use LLMs for tasks, you're getting whatever other humans have said.

All of maths can be derived from the axioms of maths. All chess moves derive from the rules of the game. This kind of process has a lot of legs, regardless of if you want to think of the models as "thinking" or not.

Me? I don't worry too much if they can actually think, not because there's no important philosophical questions about what that even means, but because other things have a more immediate impact: even if they are "just" a better search engine, they're a mechanism that somehow managed to squeeze almost all of the important technical info on the internet into something that fits into RAM on a top-end laptop.

The models may indeed be cargo-cult golems — I'd assume that by default, there's so much we don't yet know — but whatever is or isn't going on inside, they still do a good job of quacking like a duck.

[0] Turing, A. M. (1950). Computing machinery and intelligence. Mind, 59, 433–460. https://doi.org/10.1093/mind/LIX.236.433

[1] Searle, J. R. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3(3), 417–424. https://doi.org/10.1017/S0140525X00005756