• Rioting Pacifist@lemmy.world
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    17 hours ago

    Specifically LLMs fail at multiple of the axioms that underpin the “theory” of signularity

    • Fail - Recursive self-improvement is possible - LLMs aren’t being coded, beyond specific fields like image generation and programming, it’s not really clear how an LLM would improve itself in a general sense.
    • Fail? - Moore’s Law (or its generalization) - it seems like we are hitting the limits of fitting more chips into a processor and LLMs are not going to solve that
    • Fail - Human cognition is near the threshold for AI being able to self-improve - they really seem to be showing something AI researchers have known for a while - people are dumb and anthropomorphize anything the moment it can pretend to talk to you
    • Fail - Greater intelligence reliably translates into greater real-world capability - I think tech CEOs are doing a great job of demonstrating that this isn’t true - so the idea that a supersmart general AI would run the world rather than be stuck generating deep fake porn of children isn’t necessarily true.
    • Fail? - There is no fundamental ceiling on intelligence - it seems like each itteration of LLMs is returning a smaller improvement than the last, which to my simple meat bag brain implies there is a ceiling on the intelligence of LLMs - I don’t know if this points to some fundamental limit of intelligence but at least with LLMs it seems like they have an asymptotic limit.
    • kkj@lemmy.dbzer0.com
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      16 hours ago

      In regards to the last point, asymptotic functions certainly look like that, but so do logs with a base greater than 1 and powers with an exponent between 0 and 1 exclusive, and both of those do eventually go to infinity. Now, most concepts of the singularity have development accelerating, not decelerating, so this still doesn’t qualify, but it could technically keep increasing without limit.