Google Puts Souped-Up Neural Networks To Work

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."

Comments

Second best option.

[Rockoon]

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.

Re:Second best option.

[jkflying]

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.