New 'Deep Learning' Technique Lets Robots Learn Through Trial-and-Error

jan_jes writes: UC Berkeley researchers turned to a branch of artificial intelligence known as deep learning for developing algorithms that enable robots to learn motor tasks through trial and error. It's a process that more closely approximates the way humans learn, marking a major milestone in the field of artificial intelligence. Their demonstration robot completes tasks such as "putting a clothes hanger on a rack, assembling a toy plane, screwing a cap on a water bottle, and more" without pre-programmed details about its surroundings. The challenge of putting robots into real-life settings (e.g. homes or offices) is that those environments are constantly changing. The robot must be able to perceive and adapt to its surroundings, so this type of learning is an important step.

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[Ol Olsoc]

But can't we get people to mod down the now incessent "Why is this news" or "Why is this on Slashdot?" Posts?

They are becoming the 2015 equivalent of "Frist Post, or "Welcome from the Golden Girls".