OpenAI presented research in which a human-like robot hand solved a Rubik's Cube. The neural networks were trained entirely in simulation, using the same reinforcement learning code as OpenAI Five together with a new technique called Automatic Domain Randomization (ADR), and coped with perturbations never seen in training. The work showed that reinforcement learning can tackle physical-world tasks requiring high dexterity.