Zero to Expert in Eight Hours: These Robots Can Learn For Themselves

Zero to Expert in Eight Hours: These Robots Can Learn For Themselves
By Pavel Alpeyev

December 3, 2015 — 4:00 AM PST

A yellow robotic arm pauses over a pile of metal cylinders, snaps a photo, then proceeds to confidently pick pieces out of the jumble. What’s impressive is that just eight hours ago, its bin-picking skills were about zero.

Fanuc Corp. is showing off the first results of its partnership with artificial intelligence startup Preferred Networks Inc. at Tokyo’s International Robot Exhibition this week. The world’s largest maker of automation equipment is using so-called “deep learning” to enable machines that can acquire skills independently.

Left overnight, a robot empowered by the algorithms can use trial and error to figure out how to pick up randomly positioned objects with 90 percent accuracy. Eight machines working simultaneously and sharing their lessons can do that in an hour. A veteran Fanuc engineer would need several days to write a teaching program that even approaches that performance.

“Deep learning allows machines to take vast amounts of data and distill useful rules and lessons all by themselves,” Preferred Networks Chief Executive Officer Toru Nishikawa said at the expo. “For a robot, that means understanding not only why one movement was successful and another one not, but also how to improve its performance.”

Fanuc plans to make the self-learning functionality commercially available next year, Nishikawa said. The two companies are also working on applications that predict machine failures to prevent costly factory stoppages.

The deep learning algorithms, inspired by the way living things process information, already help minimize human involvement when Facebook Inc. tags user photos or Google Inc. serves up ads. Now hardware companies from Fanuc to Toyota Motor Corp. and Samsung Electronics Co. are stepping up investments to add problem-solving capabilities to their products.

Fanuc earlier this year paid 900 million yen ($7.5 million) for a 6 percent stake in Preferred Network, after rival ABB Ltd. invested several million dollars into AI startup Vicarious. Facebook’s Mark Zuckerberg, Inc.’s Jeff Bezos, actor Ashton Kutcher and Samsung are also among Vicarious’s shareholders.

Nishikawa is a world finalist of the prestigious ACM Programming Contest, whose winners include a former chief technology officer of Facebook and the first employee at Google. He founded Preferred Networks with his University of Tokyo classmate Daisuke Okanahara in March 2014. Little more than a year later, the company counted Fanuc, Toyota and Panasonic Corp. among its partners.

“This technology doesn’t have to be limited to Fanuc robots,” Nishikawa said. “There are all kinds of machines that can benefit from it.”


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