> Think how we can build construction equipment thousands times stronger than any animal's muscle. And yet the mantis shrimp can throw a punch faster than a bu

> Think how we can build construction equipment thousands times stronger than any animal's muscle. And yet the mantis shrimp can throw a punch faster than a bullet. Nature does not optimize for the same things we do. Animals did not evolve muscles as strong as some of our construction equipment, but it is hard to know whether this is because evolution is limited, or because that capability was not helpful enough to compensate for the extra fuel requirements. > Even with same algorithms, performance of digital intelligence will be orders of magnitude higher simply because of speed and memory capacity. Maybe. But I think you (and others) have misplaced confidence in the superiority of our technology. Power consumption of a circuit is proportional to frequency. We have computing units that can work at GHz rates, sure, but you can't exactly cram 80 billions of these into a cubic foot unless you're planning to melt them into plasma. So we don't. Current approaches must multiplex millions of "neurons" through the same computing units, leading to effective firing rates that are not wildly different from biological neurons. If we were to switch to a different approach where each "neuron" is independent, I expect the communication speed to plummet simply because of practical considerations about energy consumption and heat dissipation. Beyond that, I would argue that our paradigm of hardware design rests on many intentional decisions that are structurally suboptimal for intelligence, and that this is a graver problem than the brain's own inefficiencies. Take the ability that you mention to read one's own implementation and back up one's brain. This is intentional in our design. But this is not free! Unfettered read access to one's brain is a heavy internal communication requirement when you compare it to simple local communication between units, and it is naive to think it would not have a negative impact on performance. AI that can copy itself has a lower performance ceiling than a system that does not have this requirement. That's physics. In any case, the point I'm trying to make is not about humans vs AI, it is about intelligence in general. I suspect that intelligence is excellent at simple optimization, but that it is not very good at complex optimization, and thus for any intelligence there may be a point where it starts to underperform relative to e.g. evolution.