Embeddings turn text, images, users, products, or other entities into arrays of numbers that models can compare efficiently. Similar items usually end up near each other, which is why embeddings are useful for search, recommendation, ranking, and clustering.
In many blog examples, embeddings are the bridge between messy human language and a system that can perform fast similarity lookup.
