ML framework adds L0 regularization capability to train sparse neural networks

AI Impact Summary

A new capability in the ML framework allows training sparse neural networks using L0 regularization, pushing weights exactly to zero. This can reduce model size and potentially speed up inference when the deployed runtime supports sparse tensors or pruning-friendly kernels. Teams will need to tune L0 lambda and consider how sparsity affects optimizer state, checkpoint compatibility, and serving pipelines; if hardware and software support sparse formats, latency and memory footprint improve, otherwise gains may be limited.