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Scientists See Advances in Deep Learning, a Part of Artificial Intelligence

Stashed in: Turing, GPU, Machine Learning, Artificial Intelligence

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“We decided early on not to make money out of this, but just to sort of spread it to infect everybody,” he said. “These companies are terribly pleased with this.”

Referring to the rapid deep-learning advances made possible by greater computing power, and especially the rise of graphics processors, he added:

“The point about this approach is that it scales beautifully. Basically you just need to keep making it bigger and faster, and it will get better. There’s no looking back now.”

They're still a long way from anything Turing-able:

This summer, Jeff Dean, a Google technical fellow, and Andrew Y. Ng, a Stanford computer scientist, programmed a cluster of 16,000 computers to train itself to automatically recognize images in a library of 14 million pictures of 20,000 different objects. Although the accuracy rate was low — 15.8 percent — the system did 70 percent better than the most advanced previous one.

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