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What you’re doing is the classic No True Scotsman fallacy. “Isn’t real” is a tell for that. It’s the same as saying it’s not a “true” intelligence. Define wha

by antonvs 4mo ago

What you’re doing is the classic No True Scotsman fallacy. “Isn’t real” is a tell for that. It’s the same as saying it’s not a “true” intelligence. Define what you mean by “true”, then. But for me, what I’m interested in is functional capability, not some mysterious ineffable quality that only humans can have. And in terms of functional capability, current models are certainly better at software development than you are. You’re just in denial.

anon373839 4mo ago
Perhaps I was unclear: the part that isn't real is the generalization. The models appear to generalize because they're fitted to so many discrete tasks that it almost doesn't appear to matter. But then it leaks, and the failure modes reveal no coherent model or process that generated the failure. The labs only have one answer for this, which is more duct tape. > current models are certainly better at software development than you are. You’re just in denial. I have no ego in this. It could be true. Wikipedia is also "smarter" than I am; it "knows" so many more concepts than I could ever. But regardless, I think the state of slopcoded messes like Claude Code shows that the models are missing something.
- abalashov 4mo ago
  Although I agree with you, in fairness, there are some lively controversies in the world of cognitive science and philosophy of mind about whether this meaningfully differs from human thinking at sufficient scale. The general idea is that the building blocks of "coherent models" and "processes" within the churning of the human intellect are also, in so many words, prior art and existing concepts, and so, while the human mind is not a text model, a sufficiently large and sensorily multimodal neural net would not be too different. Neural nets are, after all, inspired by what we understand of human cognition -- they'd say.

by antonvs 4mo ago

anon373839 4mo ago

Perhaps I was unclear: the part that isn't real is the generalization. The models appear to generalize because they're fitted to so many discrete tasks that it almost doesn't appear to matter. But then it leaks, and the failure modes reveal no coherent model or process that generated the failure. The labs only have one answer for this, which is more duct tape. > current models are certainly better at software development than you are. You’re just in denial. I have no ego in this. It could be true. Wikipedia is also "smarter" than I am; it "knows" so many more concepts than I could ever. But regardless, I think the state of slopcoded messes like Claude Code shows that the models are missing something.

abalashov 4mo ago
Although I agree with you, in fairness, there are some lively controversies in the world of cognitive science and philosophy of mind about whether this meaningfully differs from human thinking at sufficient scale. The general idea is that the building blocks of "coherent models" and "processes" within the churning of the human intellect are also, in so many words, prior art and existing concepts, and so, while the human mind is not a text model, a sufficiently large and sensorily multimodal neural net would not be too different. Neural nets are, after all, inspired by what we understand of human cognition -- they'd say.