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Category: Emerging Concepts
Category: Emerging Concepts
Pruning removes unnecessary connections and parameters from neural networks to make them smaller and faster without significantly hurting performance.
Pruning identifies weights that contribute little to model outputs and removes them. Like trimming dead branches from a tree, it keeps the essential structure while eliminating excess.
Modern techniques can remove 90% or more of parameters with minimal accuracy loss.
Pruning makes AI models practical for deployment on resource-constrained devices. It reduces memory requirements, speeds up inference, and cuts energy consumption.
This technique is crucial for bringing AI to mobile devices and embedded systems.
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