Show HN: PostgreSQL for AI – A book on pgvector, RAG, and in-database ML (book.zeybek.dev)

A new book titled "PostgreSQL for AI" has been announced, focusing on leveraging PostgreSQL's pgvector for AI applications. It presents a comprehensive guide on implementing in-database machine learning (ML) capabilities, featuring techniques like hybrid search, embedded generation, and real-time AI pipelines. The book uses practical examples, including an AI-powered recommendation system, to teach readers how to integrate AI functions into their existing PostgreSQL databases without requiring external infrastructure, ensuring ease of use and minimal vendor lock-in. This resource is significant for the AI/ML community as it positions PostgreSQL not just as a data storage solution but as a robust AI platform. The book covers key technical aspects such as creating advanced indexing with HNSW, implementing retrieval-augmented generation (RAG) for contextual AI responses, and utilizing features like materialized views and continuous aggregates for efficient data processing. By bridging SQL and AI practices, this guide simplifies the process for individuals familiar with ML but new to database management, making it a crucial tool for anyone looking to enhance their applications with AI capabilities.