this post was submitted on 13 Nov 2024
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Even Zuckerberg admits that trying to scale LLMs larger doesn’t work because the energy and compute requirements go up exponentially. There must exist a different architecture that is more efficient, since the meat computers in our skulls are hella efficient in comparison.
Once we figure that architecture out though, it’s very likely we will be able to surpass biological efficiency like we have in many industries.
That's a bad analogy. We weren't able to surpass biological efficiency in industry sector because we figured out human anatomy and how to improve it. It's simply alternative ways to produce force like electricity and motors which had absolutely no relation to how muscles works.
I imagine it would be the same for computers, simply another, better method to achieve something but it's so uncertain that it's barely worth discussing about.
Of course! It’s not like animals have jet engines!
Human brains are merely the proof that such energy efficiencies are possible for intelligence. It’s likely we can match or go far beyond that, probably not by emulating biology directly. (Though we certainly may use it as inspiration while we figure out the underlying principles.)
With current stat prediction models?