this post was submitted on 21 Jul 2025
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Did you genuinely not understand the point I was making, or are you just being pedantic? "Silicon" obviously refers to current computing substrates, not a literal constraint on all future hardware. If you’d prefer I rewrite it as "in non-biological substrates," I’m happy to oblige - but I have a feeling you already knew that.
And why is "non-biological" a limitation?
I haven’t claimed that it is. The point is, the only two plausible scenarios I can think of where we don’t eventually reach AGI are: either we destroy ourselves before we get there, or there’s something fundamentally mysterious about the biological computer that is the human brain - something that allows it to process information in a way we simply can’t replicate any other way.
I don’t think that’s the case, since both the brain and computers are made of matter, and matter obeys the laws of physics. But it’s at least conceivable that there could be more to it.
I personally think that the additional component (suppose it's energy) that modern approaches miss is the sheer amount of entropy a human brain gets - plenty of many times duplicated sensory signals with pseudo-random fluctuations. I don't know how one can use lots of entropy to replace lots of computation (OK, I know what Monte-Carlo method is, just how it applies to AI), but superficially this seems to be the way that will be taken at some point.
On your point - I agree.
I'd say we might reach AGI soon enough, but it will be impractical to use as compared to a human.
While the matching efficiency is something very far away, because a human brain has undergone, so to say, an optimization\compression taking the energy of evolution since the beginning of life on Earth.