Edge AI inference brings machine learning models directly to user devices and edge servers, eliminating cloud roundtrips and enabling real-time predictions. Techniques like quantization, pruning, and framework optimization (TensorFlow Lite, ONNX) make sophisticated AI models deployable on resource-constrained hardware.

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