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Honest question: Given that the only wide consensus of anything approaching general intelligence are humans and that humans are biological systems that have evolved in physical reality, is there any arguments that better efficiency is even possible without relying on leveraging the nature of reality?

For example, analog computers can differentiate near instantly by leveraging the nature of electromagnetism and you can do very basic analogs of complex equations by just connecting containers of water together in certain (very specific) configurations. Are we sure that these optimizations to get us to AGI are possible without abusing the physical nature of the world? This is without even touching the hot mess that is quantum mechanics and its role in chemistry which in turn affects biology. I wouldn't put it past evolution to have stumbled upon some quantum mechanic that allowed for the emergence of general intelligence.

I'm super interested in anything discussing this but have very limited exposure to the literature in this space.




The advantage of artificial intelligence doesnt even need to be energy efficiency. We are pretty good at generating energy, if we had human level AI even if it used an order of magnitude more energy that humans use that would likely still be cheaper than a human.


Inference is already wasteful (compared to humans) but training is absurd. There's strong reason to believe we can do better (even prior to having figured out how).


That would mean with current resources AI can get so much more intelligent than humans, right? Aren't you scared?


That's a potential outcome of any increase in training efficiency.

Which we should expect, even from prior experience with any other AI breakthrough, where first we learn to do it and then we learn to do it efficiently.

E.g. Deep Blue in 1997 was IBM showing off a supercomputer, more than it was any kind of reasonably efficient algorithm, but those came over the next 20-30 years.




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