Ray's Serve, Data, and Train libraries now abstract TPU complexities for distributed AI workloads. Serve handles multi-host model scheduling, Data removes data-loading bottlenecks, and Train streamlines cross-slice coordination.#AI #AutomationSource: Google Developers AIhttps://developers.googleblog.com/run-ray-on-tpu-part-2-ray-ai-libraries/
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