How Deep Learning Architectures Evolved — From DNNs to Transformers

Deep learning architectures are not random model names. DNN, CNN, RNN, and Transformer each appeared because data has different structure. Images need spatial patterns. Sequences need order. Modern AI needs scalable attention. That is the big picture. Core Idea Deep learning architectures evolve around one question: What structure does the data have? A basic DNN learns layered representations. A CNN is better for spatial data like images. An RNN is built for sequential data. A Transformer uses a