The brain architecture is not the end-all of computing. For example weather prediction is just about fast math, a brain like architecture is useless here.
Human brains, if you ignore brains of mammals larger than us, are the most complex "computers" we know of. And they are much more efficient at that and their assembly doesn't require huge buildings full of machines that cost billions of dollars.
Their existence means it's possible to reach such efficiency at manufacturing and heat dissipation. It means further progress, like the one we had until now, is possible. It seems that we currently are several orders of magnitude away from what human brains achieve.
Of course human flight doesn't use flapping wings nor do computers have to work 100% like brains. But they should at least be as efficient until we give up and say "no improvements are possible".
So maybe one day we will build computers based on organic chemistry. If they are cheaper and more efficient and work as well as silicon based computers, there is certainly a case to build them.
But just to humor you, today's best processors have a transistor density of roughly 25M transistors per mm^2. The human brain has a neuron density of 14K neurons per mm^3. And of course, the human brain has a volume 250x the average desktop processor.
Should we measure CMOS and silicon's overall usefulness as a medium of CPU design based on the performance of a Z80?
Not to mention the same issue with time needed for new algorithms/software to be generated, run, and limitations/difficulties on interfaces.
They're different systems, optimised for different things.
CPUs look superior if you ignore the problems using/requiring the huge benefits of biological and analogue systems the brain has, and the brain generally looks superior if you forget time, logic and deductive system implementations, inspection, standardisation, commoditization, etc.
obviously that's extremely simplified, but that's what one can fit in a HN post.
that also doesn't mean we can't learn and gain benefits for both by taking inspiration from the other, but like most things in life its far more complex than one outperforming the other or the two even being directly analogous.
(Against merely “average” human performance, a π0 would beat the entire planet by a factor of six).
Wiring up some neurons to perform binary arithmetic could be much more efficient. But there was never an evolutionary reason to do so.
It's more like this: http://dwarffortresswiki.org/index.php/User:BaronW#The_Almig... . Not just horrendously inefficient, but also highly at odds with what the brain is designed to do.
Of course, in terms of raw speed, my laptop can learn to read handwritten digits from only the examples in the SciKit-learn python module in 0.225 seconds [1], a bit less than the time it takes a human visual system to go from “some photons have hit the retina” to “there is a thought now, and that thought is ‘three’.” — the architecture of the AI is nowhere near as example-efficient as the architecture of a human brain, and it is only winning by the absurd performance difference of the hardware [2].
[1] https://kitsunesoftware.wordpress.com/2018/03/16/speed-of-ma...
[2] https://kitsunesoftware.wordpress.com/2017/11/26/you-wont-be...