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Achieve near-instant (<50ms) service downtime when dynamically reconfiguring LLM inference pipelines across heterogeneous GPUs in serverless environments.
Circuit cutting introduces substantial end-to-end overheads in quantum neural network training, with reconstruction dominating per-query time, but surprisingly, test accuracy and robustness can be preserved or even improved.
