Superconducting neurons could match the power efficiency of the brain
The human brain is by far the most impressive computing device known to science. The brain operates at a clock speed of just a few hertz, snail-like in comparison to modern microprocessors that run at gigahertz speeds.
But it gets its power by carrying out many calculations at the same time—a billion billion calculations per second. This parallelism allows it to solve problems with ease that conventional computers have yet to tackle: driving, walking, conversing, and so on.
More impressive still is that it does all this powered by little more than a bowl of porridge. By contrast, the world’s most powerful supercomputers use more power than large towns.
That’s why computer scientists want to copy the computing performance of the human brain using neural networks as computational workhorses.
That’s easier said than done. Ordinary chips can be programmed to behave like neural networks, but this is computationally demanding and energy draining.
