Dex-Net 2.0 robot uses deep-learning to grasp objects

Researchers at UC Berkeley have developed a robot that can pick up awkward and unusually shaped objects. The robot learned how to grasp different objects by studying a virtual library of 10,000 3D objects and suitable grasps. When a new object is placed in front of the bot, its deep-learning system quickly figures out what grasp the arm should use. When the robot was unsure of how to grasp an object, it poked it to figure out how to better grasp it. Deep-learning software tries to mimic the activity in layers of neurons in the neocortex, which makes up 80 percent of the brain and is where thinking occurs.