This book explores the critical role of vector databases in enhancing generative AI applications. It begins by explaining how vector databases store and index high-dimensional data, crucial for tasks like natural language processing, image recognition, and recommendation systems. The book dives into practical implementations, demonstrating how vector search engines can optimize large language models, semantic search, and AI-based content generation. Readers will learn about common vector database architectures, indexing techniques, and optimization strategies for handling vast AI-generated data. Real-world case studies illustrate how organizations leverage vector databases to improve AI workflows, from search engines to recommendation systems. The book is aimed at developers, data engineers, and AI enthusiasts looking to harness the power of vector databases in generative AI applications.
