🔗 Scalar and binary quantization for pgvector vector search and storage

While many AI/ML embedding models generate vectors that provide large amounts of information by using high dimensionality, this can come at the cost of using more memory for searches and more overall storage. Both of these can have an impact on the cost and performance of a system that’s storing vectors, including when using PostgreSQL with the pgvector for these use cases.