We've been following Dex-Net's progress towards universal grasping for several years now, and today in a paper in Science Robotics, UC Berkeley is presenting Dex-Net 4.0. The new and exciting bit about this latest version of Dex-Net is that it's able to successfully grasp 95 percent of unseen objects at a rate of 300 per hour, thanks to some added ambidexterity that lets the robot dynamically choose between two different kinds of grippers. For some context, humans are able to pick objects like these nearly twice as fast, between 400 and 600 picks per hour. And my guess would be that human success rates are as close to 100 percent as you can reasonably expect, perhaps achieving 100 percent if you allow for multiple tries to pick the same object. We set a very, very high bar for the machines.