Embeddings

Pull hard enough on almost any ML design question (recommendations, search, moderation, fraud, RAG) and you hit an embedding. They are the default representation layer of modern ML, and fluency here covers a startling fraction of the interview surface. This page explains what embeddings are, the four ways they get trained, the three ways they get used, and the serving questions interviewers probe.