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Microchips that Mimic the Human Brain Could Make AI More Energy Efficient


Collections of Intel Loihi computer chips, such as those seen here, are poised to speed up artificial intelligence.

Credit: Tim Herman/Intel Corporation

Artificial intelligence (AI) makes video games more realistic and helps your phone recognize your voice—but the power-hungry programs slurp up energy big time. However, the next generation of AI may be 1000 times more energy efficient, thanks to computer chips that work like the human brain. A new study shows such neuromorphic chips can run AI algorithms using just a fraction of the energy consumed by ordinary chips.

"This is an impressive piece of work," says Steve Furber, a computer scientist at the University of Manchester. Such advances, he says, could lead to huge leaps in performance in complex software that, say, translates languages or pilots driverless cars.

An AI program generally excels at finding certain desired patterns in a data set, and one of the most complicated things it does is keep bits of the pattern straight as it pieces together the whole thing. Consider how a computer might recognize an image. First, it spots the well-defined edges of that image. Then, it must remember these edges—and all subsequent parts of the image—as it forms the final picture.

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