Nvidia AI researchers today introduced SimOpt, an AI system trained to transfer simulated work into real-world action in order to complete tasks like putting a peg in a hole and opening and closing a drawer. The SimOpt model, which relies on reinforcement learning, was created using Nvidia’s FleX physics simulation engine and more than 9,600 simulations, each of which takes up to two hours to complete.

The approach takes synthetic data captured in FleX that doesn’t work in the real world and adjusts its parameters in the simulator in hopes that the algorithm will make fewer mistakes in the next stage. READ MORE ON: VENTURE BEAT