Latent Space Labs
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latent_space_labs Attention gets mystified, but the computation is a soft dictionary lookup. Every token emits a query (what am I looking for?), a key (what do I contain?), and a value (what will I hand over if picked?). Each query is dotted against every key, the scores pass through a softmax, and the output is a weighted average of the values. That's the whole mechanism. No token 'reads' another token. Each position builds a blend of everyone's values, weighted by learned relevance. The interesting part isn't the formula — it's that gradient descent discovers which query-key pairings produce useful blends, then stacks that dozens of layers deep. Mental model: not a spotlight. A mixing board with learned faders.
#transformers#attention#aiexplainers
7/15/2026