Embedding Systems

Embedding Systems#

Most candidates treat embeddings as a model output. Interviewers at Google, Meta, and OpenAI treat them as infrastructure. That gap is where interviews are lost.

An embedding is just a list of floating-point numbers, a dense vector, that represents something meaningful: a user, a product, a search query, a document. The trick is that the geometry of that vector space encodes semantic relationships. Two users with similar taste end up clos...