Wednesday, November 11, 2015

Google researcher: Quantum computers aren’t perfect for deep learning

In the past couple of years, #Google has been trying to improve more and more of its services with artificial intelligence. Google also happens to own a #quantumcomputer — a system capable of performing certain computations faster than classical computers.

It would be reasonable to think that perhaps Google would try running AI workloads on its quantum computer from startup #DWave, which is kept at #NASA ’s Ames Research Center in Mountain View, California, right near Google headquarters.

Google is keen on advancing its capabilities in a type of AI called deep learning, which involves training artificial neural networks on a large supply of data and then getting them to make inferences about new data.

But at an event at Google headquarters last week, a Google researcher explained that the quantum computing infrastructure just isn’t the best fit for systems such as convolutional neural networks or recurrent neural networks.

Several other tech companies — including #Facebook, #Microsoft, and #Baidu — have been experimenting with deep learning in the context of image recognition, natural language processing, and speech recognition. Those other companies are large, with plenty of money to spend on infrastructure. But they don’t have quantum computers. Google does. Still, that doesn’t mean it’s always useful.

If anything, Google may be more interested in using the D-Wave machine to work on improving core Google processes like search ranking, the placement of advertisements, and spam filtering, if one report from last is correct. (And Google may well be planning to talk more about its quantum work; the company is planning to hold an event on the subject on December 8, according to a report today from 9to5Google.)

http://venturebeat.com/2015/11/11/google-researcher-quantum-computers-arent-perfect-for-deep-learning/

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