adaptive computing for AI

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Adaptive computing for AI refers to systems that dynamically adjust their processing power and architecture based on the specific demands of machine learning tasks. Instead of relying on fixed hardware, these systems optimize performance and efficiency by matching resources to workload needs in real time, whether it's training deep neural networks or running inference on edge devices. This flexibility helps speed up AI workloads while reducing energy use and latency.