adaptive computing for AI

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Adaptive computing for AI refers to systems that dynamically adjust their hardware and software resources based on the specific demands of machine learning workloads. Instead of relying on fixed architectures, these systems optimize performance and efficiency by tailoring computation, memory, and power use in real time. This flexibility allows faster training, better inference, and lower energy costs across diverse AI applications, from edge devices to data centers.