attention — The mechanism that lets a model weigh which earlier words matter for the word it's currently processing — the core operation of a transformer.
transformer — The neural network architecture behind modern AI models, built on attention — letting every word directly consider every other word in parallel.
LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
Why it matters
Every model you use descends from this architecture, and reading it is how the rest of the stack stops being magic: attentionThe mechanism that lets a model weigh which earlier words matter for the word it's currently processing — the core operation of a transformer.Full definition → heads, positional encoding, the encoder-decoder split, and why removing recurrence is what made training parallel enough to scale at all.
