A new PostgreSQL extension called `pgvector` has been released in Supabase, allowing developers to store and query vector embeddings within their database. This enables efficient storage and search of large amounts of data, such as text or image embeddings, using a scalable and flexible solution. The `pgvector` extension introduces a new data type called `vector`, which can be used to store and query vector data in PostgreSQL. It also provides three new operators for calculating similarity between vectors: `<->` (Euclidean distance), `<#>` (negative inner product), and `<=>` (cosine distance). The extension is designed to work with the Supabase platform, which provides a set of tools and services for building and deploying AI applications. With `pgvector`, developers can build scalable and efficient search functions that can be integrated with their products, making it easier to find relevant data and improve user experience.