This video explores the use of pgvector, an extension for PostgreSQL that enables vector search capabilities for generative AI applications. Shayon Sanyal, a principal data specialist solutions architect at AWS, discusses how pgvector enhances existing Postgres databases to support AI workloads, including its integration with Amazon Bedrock. The presentation covers the benefits of using Postgres for vector search, the features of pgvector, and recent improvements like HNSW indexing. A demo showcases a question-answering chatbot application using pgvector on Amazon Aurora Postgres. The video concludes with upcoming enhancements to pgvector and resources for getting started with this technology.