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Scientists See Promise in Deep-Learning Programs


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Microsoft's Richard F. Rashid

A voice recognition program translated a speech given by Richard F. Rashid, Microsoft's top scientist, into Mandarin Chinese.

Credit: Hao Zhang / The New York Times

Deep-learning technology, an artificial intelligence technique inspired by theories about how the brain recognizes patterns, has recently grown in speed and accuracy. "There has been a number of stunning new results with deep-learning methods," says New York University computer scientist Yann LeCun. "The kind of jump we are seeing in the accuracy of these systems is very rare indeed."

For example, in October a group of University of Toronto researchers developed software to help find molecules that could lead to new medical drugs. The technique uses deep-learning software to determine which molecule is the most likely to be an effective drug agent. The software won the top prize in a contest sponsored by Merck. "This is a really breathtaking result because it is the first time that deep learning won, and more significantly it won on a data set that it wouldn't have been expected to win at," says Kaggle CEO Anthony Goldbloom. Advanced pattern-recognition technologies also can be used in marketing and law enforcement applications.

Deep-learning systems recently have outperformed humans in certain limited recognition tests, and have been trained to recognize images in a database of German traffic signs.

From The New York Times
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Abstracts Copyright © 2012 Information Inc., Bethesda, Maryland, USA


 

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