UC Berkeley postdoctoral researcher Dr. Danyal Fer and his fellow researchers hope to advance the state of the art of robotic surgery. Automated robots in testing situations can meet or exceed a human in dexterity, precision and speed, according to a new research paper from the Berkeley team. The Berkeley team decided to build a new neural network that analyzed the robot's mistakes and learned how much precision it was losing with each passing day. "It learns how the robot's joints evolve over time," said Brijen Thananjeyan, a doctoral student on the team.