The bear case for AGI
I thought this was a thoughtful response:
At a higher level, I guess I’d say there’s a sort of refusal to think carefully about what models are or are not useful for in a rigorous way which I find personally quite annoying, and instead a reliance on some nebulous notion of being “AGI pilled” as a replacement for serious thought. I think people are very quick to anthropomorphize LLM intelligence because humans communicate through words and we infer the intelligence of human counterparties through comprehension of their language, but this leads them to wrong conclusions; for example if we observe that a new model proved some incredible mathematical theorem, some will say, “well, don’t we have AGI now, huh?” But to me, it’s actually more like, “well, given how hard it would have been for a human to do these mathematics, and given the limited economic effect of LLMs upon the world so far, isn’t it actually a negative datapoint vis-a-vis the generality of LLM intelligence?”
Andrew Ho @andrewho03 · September 3, 2026 ↗Not really observations that others before me haven’t made, but: - Despite the seemingly magical nature of LLMs, reflection over a >3 month timescale suggests my total productivity hasn’t increased by over 100%, or perhaps even by over 50%, and a lot of time is actually wasted…
As always, thoughtful response from Philippe Lemoine:
Philippe Lemoine @phl43 · September 4, 2026 ↗This is a good post and I think people should take seriously the points it raises and think more about them. I would just like to make additional comments on the observation that LLM intelligence seems very different from human intelligence, because it's something I have been…