To make large language models more accurate, you need to power them with your own unique data. But models have a very specific data diet: they only consume vectors, which are a bunch of numbers. Embedding is the process of turning your data (images, text, videos) into vector representations (numbers), and vector databases are specialized places to store these embeddings, and search through + retrieve them when you need them.