In plain English
An embedding is a list of numbers that represents the meaning of a piece of data, such as a word, sentence, or image, as a point in a high-dimensional space. Items with similar meaning end up close together, and unrelated items end up far apart. This geometric layout is what lets software compare meaning rather than just matching exact words.
Why it matters
Embeddings are the quiet engine behind semantic search, recommendations, and retrieval-augmented generation. They let systems find things by meaning, not just keywords.
A worked example
The embeddings for 'doctor' and 'physician' sit close together, so a search for one can surface results about the other even with no shared words.
Common confusion
An embedding is not the original text or image. It is a numerical fingerprint of meaning, and you usually keep the source content stored separately.