Getting stuff wrong is key to smarter artificial intelligence

NEURAL networks, like the ones grabbing headlines for winning boardgames or driving cars, depend on huge amounts of computing hardware. That in turn means a colossal amount of power: the next wave may consume millions of watts each. That’s one reason why some suggest we rethink what we want computers to be. Reducing the precision with which they analyse problems, and putting up with the odd “error”, can cut zeroes off their energy consumption (see To make computers better, let them get sloppy). And it has precedent in the human brain – an unrivalled piece of hardware using electrical fluctuations and requiring a million times less power than a computer. Introducing error will also make computers better at handling the real world. Neural networks, loosely modelled on the brain, capture…

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