Vector databases are becoming increasingly popular, especially with the increasing popularity of LLMs.
For those new to them, they are a collection of Embeddings, that are vector representations of real-world entities such as text, images, audio, videos and more.
These vector representations help capture the features and semantics of a real-world entity in a continuous vector space.
These vectors can then be used by an ML model for further processing and applications for different ML tasks.
