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.
The main issue is that the death of moore's law somehow implies that there won't be any progress in chip manufacturing and we'll always use the computing technology we have now because at some point you reach sizes of single atoms. But this is wrong as we don't need node shrinks, we need different improvements. And human brains are the proof that they are physically possible.
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".
It's possible with organic chemistry, but what about inorganic chemistry? It's possible with carbon based chemistry, but what about silicon-based chemistry? I'm not convinced that it's impossible to build a human-mind-level consciousness in silicon, but I'm skeptical.
Human brains actually move real stuff around for their computation [1]. Like are like abacusses or some complex clock. Silicon based computers move electrons around which are much smaller and have much less weight. However, you might be right that silicon based computers won't allow further improvements.
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.
The fact that the brain exists says absolutely nothing about the future of chip manufacturing. It is on a completely different plane than Moore's law: neurons are only as small as .004mm at minimum. What you're suggesting isn't an improvement, it's starting over completely from scratch.
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.
yeah, after nanometers we've still got picometers, femtometers, attometers, angstrom, fermi ... lots of room before we hit planck! intel, get your shit together!
Human brains are the most efficient at some problems. This is trivial to demonstrate: try multiplying two 10 digit numbers in your head. Now pick up a calculator and do the same in a fraction of time, using a fraction of power, and with perfect accuracy.
Computers are better than humans at some problems but I'd argue that this is because they can use their available computational powress much better than human brains can, even if it's much less. Computers are still much worse at driving cars for example and their power consumption is a real problem. If you could have done more computations for the same power budget, or with a power budget of tens of kilowatts, the problem might be solvable.
Depends on the brain doesn't it? Kim Peek and Srinivasa Ramanujan would indicate there is no fundamental limitation to the architecture of the human brain that prevents "fast math".
Should we measure CMOS and silicon's overall usefulness as a medium of CPU design based on the performance of a Z80?
I think you may have underestimated quite how fast computers are at maths. A $5 Raspberry Pi Zero, at 24 gigaflops, beats the combined performance of every American (continent, not country) combined, even if those humans were all calculating at the speed of the current world record holder, Takahiro Asano, who correctly added 15 sets of 3-digit numbers in 1.68 seconds.
(Against merely “average” human performance, a π0 would beat the entire planet by a factor of six).
I wonder whether a human calculating a math problems is not unlike a computer simulating another computer. Observing the hand-eye coordination of top athletes, it's pretty clear that our brains do some amazing computations, and fast. In fractions of a second, we can turn a pattern of photons into concepts, discover relationships between those concepts, track changes over time, and project all of that out some distance into the future. In other words, aren't most of our computational capabilities buried in the unconscious mind?
That might be a better way of making my own point than what I actually wrote. You’re right, explicit conscious maths isn’t what our brain architecture evolved for.
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].
That’s because humans have to decode written or verbal instructions, process them in a network that actually understands the concepts behind counting, numbers etc, and then translate the results into written or verbal language.
Wiring up some neurons to perform binary arithmetic could be much more efficient. But there was never an evolutionary reason to do so.
the latency for operations in/ out of the brain is just incomparable between biological systems and cpus.
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.
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".