Building for Physical AI on Crusoe Cloud

Physical AI demands a fundamentally different infrastructure. It repeatedly ingests petabytes of synchronized sensor data every epoch, combines training with synthetic generation and simulation, and operates within a continuous closed loop. Systems built for standard text and image models stall as soon as your strategy relies on large-scale synthetic data generation.

This whitepaper explores key physical AI deployment scenarios. It details how Crusoe supports these workloads across a unified platform, covering data processing, synthetic data generation, and model training to fine-tuning, inference, and operations in Crusoe Cloud and at the edge using Crusoe Spark and Crusoe Edge Zones.