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WeightBridge first automatically extracts the correspondence between trainer and rollout weight layouts, then plans and executes redundancy-free and load-balanced weight transfer, which reduces average GPU stall time over the state-of-the-art open-source RL framework and achieves high performance in all settings.
The mix of batch and inference workloads in AI data centers creates surprising power dynamics, where smoothing aggregate power demand paradoxically *increases* short-horizon ramping.
