Challenging Conventions: A Breakthrough Transformer Architecture Without Normalization Layers

In the field of deep learning, normalization layers are considered an indispensable component of modern neural networks. Recently, research led by Meta FAIR research scientist Zhuang Liu, titled "Transformer without Normalization Layers", has garnered significant attention. This research not only introduces a new technique called Dynamic Tanh (DyT), but also demonstrates the effectiveness of Transformer architectures even without traditional normalization layers.