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Google Puts Souped-Up Neural Networks To Work

Posted by timothy on from the our-menu-options-have-recently-changed dept.

holy_calamity writes "A machine learning breakthrough from Google researchers that grabbed headlines this summer is now being put to work improving the company's products. The company revealed in June that it had built neural networks that run on 16,000 processors simultaneously, enough power that they could learn to recognize cats just by watching YouTube. Those neural nets have now made Google's speech recognition for U.S. English 25 percent better, and are set to be used in other products, such as image search."

4 of 95 comments (clear)

  1. Re:Face recognition by StripedCow · · Score: 5, Funny

    How long until Google starts using this for face recognition?

    That totally does not bother me. These methods are easily defeated by Burqa technology, invented by Muslims ages ago.

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    If Pandora's box is destined to be opened, *I* want to be the one to open it.
  2. Second best option. by Rockoon · · Score: 5, Interesting

    In AI circles, a popular saying is that Neural Networks are always the second best way to solve a problem. Its what you use when you don't want to (or don't know how to) implement a more specific approach.

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    "His name was James Damore."
    1. Re:Second best option. by jkflying · · Score: 5, Interesting

      Neural networks don't work as well as some specific algorithms for specific problems, but they are great generalists, so you can throw a NN at almost any problem and get at least OK results. Just like humans vs. machines, we have machines that can do things faster than us, more accurate than us, and more reliably than us, but they can't also run around a field and kick a ball and climb a tree and swim.

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      Help I am stuck in a signature factory!
  3. 90% accuracy by Anonymous Coward · · Score: 5, Funny

    In today's news, google announced that a new algorithm has achieved a 90% success rate in identifying video's containing cats on youtube. The algo shouts "cats" every time a video is started, and since 90% of youtube video's contain cats, the algorithm has obtained a success rate of 9 in 10.