This robot arm's AI thinks like we do about how to grab something

Robots are great at doing things they've been shown how to do, but when presented with a novel problem, such as an unfamiliar shape that needs to be gripped, they tend to choke. AI is helping there in the form of systems like Dex-Net, which uses deep learning to let a robotic arm improvise an effective grip for objects it's never seen before. The basic idea behind the system is rather like how we figure out how to pick things up. You see an object, understand its shape and compare it to other objects you've picked up in the past, then use that information to choose the best way to grab it. Dex-Net doesn't have the advantage of being a living person with eyes and a memory, so its creators gave it more than six million artificial 3D representations of objects and had it work out the best way, theoretically, to pick up each.