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In this presentation we describe four applications of Isaac Gym at the Intelligent Autonomous Manipulation Lab: performing large-scale experiments, learning to sense contacts on robot arms, learning dynamics models and directly planning with deep reinforcement learning in Isaac Gym. We discuss how Isaac Gym's parallel simulations leads to efficient data collection, enabling these applications and faster research cycles.