Dactyl works by training the robot hand in a simulation and then transferring the knowledge gained there to the real world.
Simulated learning is becoming widespread in AI, withDactyl representing a milestone in terms of how well it’s been able to execute the task its trained for in reality.
The result is a robot hand that can complete many tasks, efficiently, using a range of movements, without them having to be individually programmed by a human.
“We’re working on teaching robots to solve a wide variety of tasks, without having to programme them for any one specific task,” said Alex Ray, a machine learning engineer at OpenAI.
“The system runs on a human-like robot hand and we used reinforcement learning and simulation to teach the robot how to solve tasks in the real world.”