As a senior at the University of Minnesota, Jeff Dean built an artificial brain. Kinda. Using what was considered a supercomputer at the time, he mimicked the networks of neurons inside your head, creating a system that could analyze information—and even learn. The trouble was it didn’t work that well. Those computers didn’t provide enough juice. They couldn’t juggle enough data. "We just trained it on toy problems," he says of this neural network. "The computational power wasn’t all that great."
But this was 25 years ago, before Dean went to Google and changed the very nature of computational power.
As one of Google’s earliest engineers, Dean helped create the fundamental computing systems that underpin the company’s vast online empire, systems that span tens of thousands of machines. This work gave him celebrity-like status among Silicon Valley engineers—people recognize him as he walks through the Google cafeteria. Now, armed with those massively distributed systems and the ideas that drive them, he has returned to the world of neural networks. And this time, these artificial brains work remarkably well.
From Wired
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