01 · Understand the idea
In simple words
Imagine placing ideas on a map so that related ideas are often near one another. Embeddings are numeric representations that make this kind of comparison possible. A search system may connect “affordable laptop” with “budget computer” without an exact word match. The map is learned and imperfect; nearby items are not necessarily interchangeable.
Two useful terms
Vector: a list of numbers. Similarity: a measure used to compare two representations.
Build your understanding
An embedding maps an input to a numeric vector. Similarity can help retrieve related passages even when they use different words. The usefulness of distance depends on the embedding model, task and data. Similarity scores are ranking signals, not probabilities that a claim is true.
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