WE ARE ALL DESIGNIST:

Though he catches flak for it, Garrett Kenyon, a physicist at Los Alamos National Laboratory, calls artificial intelligence (AI) "overhyped." The algorithms that underlie everything from Alexa's voice recognition to credit card fraud detection typically owe their skills to deep learning, in which the software learns to perform specific tasks by churning through vast databases of examples. These programs, Kenyon points out, don't organize and process information the way human brains do, and they fall short when it comes to the versatile smarts needed for fully autonomous robots, for example. "We have a lot of fabulous devices out there that are incredibly useful," Kenyon says. "But I would not call any of that particularly intelligent."

Kenyon and many others see hope for smarter computers in an upstart technology called neuromorphic computing. In place of standard computing architecture, which processes information linearly, neuromorphic chips emulate the way our brains process information, with myriad digital neurons working in parallel to send electrical impulses, or spikes, to networks of other neurons.

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