Comment by tptacek
12 hours ago
What does this matter? You can build a working coding agent for yourself extremely quickly; it's remarkably straightforward to do (more people should). But look underneath all the "sprawling tools": the LLM itself is a sprawling maze of matrices. It's all sprawling, it's all crazy, and it's insane what they're capable of doing.
Again if you want to say they're limited in some way, I'm all ears, I'm sure they are. But none of that has anything to do with "statistical text generation". Apparently, a huge chunk of all knowledge work is "statistical text generation". I choose to draw from that the conclusion that the "text generation" part of this is not interesting.
Well, hang on a second - it sounds like you may actually disagree with the user who created this thread. That user claims that these systems exhibit “real intelligence”, and success on this Erdos problem is proof.
You seem to be making the claim that LLMs are statistical text generators, but statistical text generation is good enough to succeed in certain cases. Those are different arguments. What do you actually believe? Are we even in disagreement?
I don't have any opinion about "real intelligence" or not. I'm not a P(doom)er, I don't think we're on the bring of ascending as a species. But I'm also allergic to arguments like "they're just statistical text generators", because that truly does not capture what these things do or what their capabilities are.
(The clearer way for me to have said this is that I don't care whether they're According-to-Hoyle "intelligent", and that controversy isn't what motivated me to comment).
"But I'm also allergic to arguments like "they're just statistical text generators", because that truly does not capture what these things do or what their capabilities are."
Umm, why doesn't it capture it? Why can't a statistical text generator do amazing things without _actually_ being intelligent (I'm thinking agency here)? I think it's important to remind ourselves, these things do not reflect or understand what they're outputting. That is 100% evident with the continuing issues with them outputting nonsense along with their apparently insightful output. The article itself said the output was poor but the student noticed something about it that sparked an idea and he followed that lead.
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Just to clarify because I’m not sure I understand:
So you agree that LLMs are in fact statistical text generators but you don’t like people use that fact in arguments about the capabilities of the things?
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He does say that LLMs are just a part of the models used these days.