'Deep learning' clusters crack coding problems their top engineers can't
by By Jack Clark, The Register
Analysis Google no longer understands how its "deep learning" decision-making computer systems have made themselves so good at recognizing things in photos.
This means the internet giant may need fewer experts in future as it can instead rely on its semi-autonomous, semi-smart machines to solve problems all on their own.
The claims were made at the Machine Learning Conference in San Francisco on Friday by Google software engineer Quoc V. Le in a talk in which he outlined some of the ways the content-slurper is putting "deep learning" systems to work. (You find out more about machine learning, a computer science research topic, here [PDF].)
"Deep learning" involves large clusters of computers ingesting and automatically classifying data, such as things in pictures. Google uses the technology for services such as Android's voice-controlled search, image recognition, and Google translate.
The ad-slinger's deep learning experiments caused a stir in June 2012 when a front-page New York Times article revealed that after Google fed its "DistBelief" technology with millions of YouTube videos, the software had learned to recognize the key features of cats.
A feline detector may sound trivial, but it's the sort of digital brain-power needed to identify house numbers for Street View photos, individual faces on websites, or, say, < skynet disclaimer > if Google ever needs to identify rebel human forces creeping through the smoking ruins of a bombed-out Silicon Valley < /skynet >.
--more at The Register--
*Thanks for the link, Gary
by By Jack Clark, The Register
Analysis Google no longer understands how its "deep learning" decision-making computer systems have made themselves so good at recognizing things in photos.
This means the internet giant may need fewer experts in future as it can instead rely on its semi-autonomous, semi-smart machines to solve problems all on their own.
The claims were made at the Machine Learning Conference in San Francisco on Friday by Google software engineer Quoc V. Le in a talk in which he outlined some of the ways the content-slurper is putting "deep learning" systems to work. (You find out more about machine learning, a computer science research topic, here [PDF].)
"Deep learning" involves large clusters of computers ingesting and automatically classifying data, such as things in pictures. Google uses the technology for services such as Android's voice-controlled search, image recognition, and Google translate.
The ad-slinger's deep learning experiments caused a stir in June 2012 when a front-page New York Times article revealed that after Google fed its "DistBelief" technology with millions of YouTube videos, the software had learned to recognize the key features of cats.
A feline detector may sound trivial, but it's the sort of digital brain-power needed to identify house numbers for Street View photos, individual faces on websites, or, say, < skynet disclaimer > if Google ever needs to identify rebel human forces creeping through the smoking ruins of a bombed-out Silicon Valley < /skynet >.
--more at The Register--
*Thanks for the link, Gary
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