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Staged Embarrassment Learning (SEL) is a bio-inspired framework for efficient Deep Learning. Inspired by a child’s rapid correction after a mistake, SEL uses dynamic gradient sparsity to focus compute on high-loss "embarrassing" samples . It achieves up to 99% FLOPs reduction, making it ideal for Edge AI.