Dynamic Tanh: Turing Award Winner Yann LeCun’s Latest Work in Rethinking Layer Normalization

The introduction of Dynamic Tanh (DyT) by Yann LeCun, Kaiming He, and team is shaking up a foundational assumption in deep learning—namely, that normalization layers are essential. DyT’s stateless, element-wise design mimics the most useful behavior of normalization (nonlinear squashing of outliers) without the costly computation of statistics across batches or tokens.

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