An embedding model reads a chunk and returns a vector: a fixed-length list of numbers that stands for the chunk's meaning. The chunk card dissolves into that row of numbers, and the row becomes a single point in a space where each axis is one dimension of meaning. Text is now something a computer can compare numerically.
How AI Answers Questions About Documents It Never Learned