The State of Simulation for Physical AI: An Overview
Hugging Face
Simulation has become essential for training physical AI systems and robots, enabling developers to generate large amounts of training data cost-effectively rather than relying solely on real-world interaction. Multiple GPU-accelerated simulation engines now exist for different use cases, including MuJoCo, Isaac Sim, Isaac Lab, and Newton, each optimized for specific robotics tasks like reinforcement learning, synthetic data generation, or photorealistic rendering. This shift has created a layered infrastructure ecosystem where different tools specialize and interoperate, making high-quality simulated robot experience foundational to modern embodied AI development.