#attention

A from-scratch tour of what's actually inside an LLM: how a transformer turns tokens into predictions, what Query, Key, and Value really mean, and how generating text one token at a time builds the KV cache — the growing pool of memory that makes inference so expensive.

The word "mask" means at least four unrelated things in deep learning — what a token can see, what counts toward the loss, what is hidden to create a task, and what is randomly dropped. One field guide to all of them, with why each exists and what breaks without it.