What are embeddings?
Also: Vector embeddings, semantic vectors
Embeddings are lists of numbers that represent the meaning of a text, so that texts with similar meaning sit close together. Retrieval systems use them to find passages related to a question even when the exact words differ. This is why clear topic coverage matters more than repeating a keyword.
What it means in practice
A page about "customer support software for small teams" can match a question phrased as "helpdesk tool for a five-person company". Write naturally and cover the concept with its synonyms and related details.
Example: a question about "cheap accounting tool for solo founders" can retrieve a page titled "bookkeeping software for freelancers".