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Training inner loop Utilizing Ray to speed up ML dataset experiments Figure 5: Ray managing CPU and GPU workload within one cluster With Ray, ML engineers start their development process by spinning up a dedicated, heterogeneous Ray Cluster that manages both CPU and GPU resources. This process is