The human brain, it turns out, is even more efficient than previous estimates:
Fifty-seven years ago, Nobel laureates Alan Hodgkin and Andrew Huxley came up with a model to calculate the power behind electrochemical currents in neurons–a great step forward in understanding how the brain worked and how it divvied up resources. The only problem was that their subject was not a person, or even a rodent, but a giant squid. Today, researchers announced that they have found a more accurate model for mammal brains, which elevates some of their transactions to three times more efficient than that of the squid-based equations.
This computational efficiency is the single most astonishing fact of the mammalian brain. Here you are, reading these words, daydreaming about lunch, processing the richness of reality, thinking about tomorrow, and your brain requires less energy than a low wattage lightbulb. Evolution is an impressive engineer.
One way to think about this efficiency is to compare the performance of Deep Blue, that IBM chess supercomputer, to its human opponents. While Deep Blue is capable of analyzing over 200 million possible chess moves per second – it wins through sheer computational force – chess grandmasters like Gary Kasparov can only consciously evaluate about five moves per second. From the perspective of processing speed, humans are at a severe disadvantage. We’re an Atari surrounded by X-Box 360s.
But here’s the surprising fact: Deep Blue can still only win about half the time. Although their biological computers seem woefully outclassed, grandmasters can still use wit and guile and learned intelligence to beat the silicon mainframe. Even more impressive is the relative energy efficiency of these two machines. Just look at Deep Blue: when the machine is operating at full speed it’s a fire hazard, and requires specialized heat-dissipating equipment to keep it cool. Meanwhile, people like Kasparov barely break a sweat.