Self-Attention and Positional Encoding: How Transformer Architecture Powers Generative AI
Self-attention and positional encoding are the core innovations behind Transformer models that power modern generative AI. They enable machines to understand context, word order, and long-range relationships in text-making chatbots, code assistants, and content generators possible.
