MIT Technology Review:  Fanuc’s robot uses a technique known as deep reinforcement learning to train itself, over time, how to learn a new task. It tries picking up objects while capturing video footage of the process. Each time it succeeds or fails, it remembers how the object looked, knowledge that is used to refine a deep learning model, or a large neural network, that controls its action. Deep learning has proved to be a powerful approach in pattern recognition over the past few years.

“After eight hours or so it gets to 90 percent accuracy or above, which is almost the same as if an expert were to program it,” explains Shohei Hido, chief research officer at Preferred Networks, a Tokyo-based company specializing in machine learning. “It works overnight; the next morning it is tuned.”... (full story)