Teaching Machines to Understand Us

The first time Yann LeCun revolutionized artificial intelligence, it was a false dawn. It was 1995, and for almost a decade, the young Frenchman had been dedicated to what many computer scientists considered a bad idea: that crudely mimicking certain features of the brain was the best way to bring about intelligent machines. But LeCun had shown that this approach could produce something strikingly smart—and useful. Working at Bell Labs, he made software that roughly simulated neurons and learned to read handwritten text by looking at many different examples. Bell Labs’ corporate parent, AT&T, used it to sell the first machines capable of reading the handwriting on checks and written forms. To LeCun and a few fellow believers in artificial neural networks, it seemed to mark the beginning of an era in which machines could learn many other skills previously limited to humans. It wasn’t.

That's how the fantastic featured story by Tom Simonite begins in the latest issue of MIT Technology Review. It is definitely worth the read. 

/Source

Antonio Ortiz

Antonio Ortiz has always been an autodidact with an eclectic array of interests. Fascinated with technology, advertising and culture he has forged a career that combines them all. In 1991 Antonio developed one of the very first websites to market the arts. It was text based, only available to computer scientists, and increased attendance to the Rutgers Arts Center where he had truly begun his professional career. Since then Antonio has been an early adopter and innovator merging technology and marketing with his passion for art, culture and entertainment. For a more in-depth look at those passions, visit SmarterCreativity.com.