Distributed training

Distributed training is training a machine learning model across many GPUs or machines at once, splitting the data, the model or both, to handle larger models and finish training faster.

Distributed training sits in the Foundations part of the Agentik {OS} glossary, which defines the words used to build and run AI agent systems.