Ray scales Python and AI workloads from a laptop to a full cluster, with high-level libraries for distributed training, hyperparameter tuning, and model serving. It's the underlying framework behind a lot of large-scale ML infrastructure, including managed platforms like Anyscale built directly on top of it.
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