Distributed Training Pipeline

High-performance computing made training times comparable to real-world data-collection times. The distributed architecture was central because computation could keep pace with data collection and deployment. The learned dynamics model generated large-scale parallel synthetic rollouts for policy optimization. Training used a distributed real-world pipeline involving the robot, a local workstation, an HPC cluster, and a JAX/BRAX implementation.