Databricks outlines fault-tolerant PyTorch training tools for AI Runtime
Databricks says distributed, asynchronous checkpointing and cached data loading can reduce recovery time and GPU idle time during large-scale PyTorch training, while warning that incomplete data-pipeline checkpoints can silently distort resumed jobs.