28th July 2023
You can think of the attention mechanism as a matchmaking service for words. Each word makes a checklist (called a query vector) describing the characteristics of words it is looking for. Each word also makes a checklist (called a key vector) describing its own characteristics. The network compares each key vector to each query vector (by computing a dot product) to find the words that are the best match. Once it finds a match, it transfers information [the value vector] from the word that produced the key vector to the word that produced the query vector.
Recent articles
- OpenAI DevDay 2026 live blog - 29th September 2026
- 2026 in LLMs (so far) - 27th September 2026
- Claude Opus 5.5, GPT-6 Sol, GPT-6 Luna, and a new price war - 22nd September 2026