Researchers introduce NeRD, a neural robot dynamics model that replaces traditional simulator components to achieve unprecedented generalization across tasks and environments. This breakthrough enables stable, thousand-step predictions, in-sim policy training, and real-world fine-tuning, effectively bridging the sim-to-real gap for articulated robots.