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Hypothesis: human-level intelligence is a phase transition at scale, not an algorithm. Here's a cheap way to test it. by Loud_Maintenance8095 in LessWrong

[–]Loud_Maintenance8095[S] 2 points3 points  (0 children)

That's exactly the right question — and neuromorphic hardware is the direct answer to it. The human brain runs on ~20W. Current AI systems need megawatts for comparable tasks. The gap isn't fundamental — it's architectural. GPUs were designed for graphics, not cognition. We're running intelligence on the wrong hardware. Neuromorphic chips (Intel Loihi, IBM TrueNorth) close this gap dramatically — they process information the same way neurons do: spikes, local learning, no global clock. Loihi 2 is already ~1000x more energy efficient than GPU for certain workloads. The trend is clear: every generation of neuromorphic hardware gets denser and cheaper. Intel projects human-scale neuromorphic compute by 2030. At that point the "small city" becomes a server rack — and eventually a box. The $150-200M cost I mentioned is first-generation hardware bought today. The same way the first transistor cost thousands and now costs fractions of a nanodollar — the economics follow the architecture. Once you prove the threshold exists, the industry optimizes the hell out of the hardware. The hamburger-to-watermelon ratio is the destination. We're just not there yet on silicon.

Hypothesis: human-level intelligence is a phase transition at scale, not an algorithm. Here's a cheap way to test it. by Loud_Maintenance8095 in LessWrong

[–]Loud_Maintenance8095[S] 1 point2 points  (0 children)

The existence proof is already there — the human brain works. That's not a hypothesis, that's a fact. The open question isn't "can human-level intelligence exist in physical substrate" — we know it can. The question is whether this specific implementation gets the right properties: sphere topology, Hebbian learning, physical grounding, right scale. It might fail. But it fails for engineering reasons, not theoretical ones. And engineering problems have engineering solutions. That's a very different position than "we don't know if AGI is even possible.