"Advances in an artificial intelligence technology that can recognize patterns offer the possibility of machines that perform human activities like seeing, listening and thinking. ... But what is new in recent months is the growing speed and accuracy of deep-learning programs, often called artificial neural networks or just 'neural nets' for their resemblance to the neural connections in the brain. 'There has been a number of stunning new results with deep-learning methods,' said Yann LeCun, a computer scientist at New York University who did pioneering research in handwriting recognition at Bell Laboratories. 'The kind of jump we are seeing in the accuracy of these systems is very rare indeed.' Artificial intelligence researchers are acutely aware of the dangers of being overly optimistic. ... But recent achievements have impressed a wide spectrum of computer experts. In October, for example, a team of graduate students studying with the University of Toronto computer scientist Geoffrey E. Hinton won the top prize in a contest sponsored by Merck to design software to help find molecules that might lead to new drugs. From a data set describing the chemical structure of 15 different molecules, they used deep-learning software to determine which molecule was most likely to be an effective drug agent."
Source: http://rss.slashdot.org/~r/Slashdot/slashdotScience/~3/4F-srHjSa0I/story01.htm
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