How Transformer Architecture Works — Encoder, Decoder, Tokens, and Context (opens in new tab)

Transformers changed NLP because they stopped treating text as a simple left-to-right chain. Instead of reading one token at a time, they compare tokens directly. That shift made modern language models faster, more scalable, and better at understanding context. Core Idea A Transformer is a sequence-to-sequence architecture. It maps an input sequence to an output sequence. For example: English sentence → Korean sentence Question → Answer Document → Summary But the key idea is not “replace one ...