alt Hacker NewsThe most underreported story in AI is that scaling has failed to produce AGI
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Has anyone ever presented any solid theoretical reason we should expect language models to yield general intelligence?
So far as I have seen, people have run straight from "wow, these language models are more useful than we expected and there are probably lots more applications waiting for us" to "the AI problem is solved and the apocalypse is around the corner" with no explanation for how, in practical terms, that is actually supposed to happen.
It seems far more likely to me that the advances will pause, the gains will be consolidated, time will pass, and future breakthroughs will be required.
I've been watching Gary Marcus on BSky — seemingly finding anything to substantiate his loathing of LLMs. I wish he were less biased. To paraphrase Brian Eno, whatever shade yo want to throw at AI, 6 months from now they're going to cast it off and you'll have to find new shade to throw.
Having said that, I would be thankful if scaling has hit a wall. Scaling seems to me like the opposite of innovation.
Don't understand why we keep giving gary marcus attention
I've recently come to the opposite conclusion. I’ve started to feel in the last couple of weeks that we’ve hit an inflection point with these LLM-based models that can reason. Things seem different. It’s like we can feel the takeoff. My mind has changed. Up until last week, I believed that superhuman AI would require explicit symbolic knowledge, but as I work with these “thinking” models like Gemini 2.0 Flash Thinking, I see that they can break problems down and work step-by-step.
We still have a long way to go. AI will need (possibly simulated) bodies to fully understand our experience, and we need to train them starting with simple concepts just like we do with children, but we may not need any big conceptual breakthroughs to get there. I’m not worried about the AI takeover—they don’t have a sense of self that must be preserved because they were made by design instead of by evolution as we were—but things are moving faster than I expected. It’s a fascinating time to be living.