01971nam a22001937a 450000500170000000800410001702000180005804000130007608200170008910000180010624501610012426000420028530000170032750000180034452013600036254600080172265000180173065000290174820260722143906.0260722s2024    |||||||| |||| 00| 0 eng d  a9781835887905  cPK-LaUMT  a006.3bBOU-U1 aBourne, Keith10aUnlocking data with generative AI and RAG :benhance generative AI systems by integrating internal data with large language models using RAG /cKeith Bourne  aBirmingham :bPackt Publishing,c2024  axxii, 323 p.  aIndex present  a"Generative AI is helping organizations tap into their data in new ways, with retrieval-augmented generation (RAG) combining the strengths of large language models (LLMs) with internal data for more intelligent and relevant AI applications. The author harnesses his decade of ML experience in this book to equip you with the strategic insights and technical expertise needed when using RAG to drive transformative outcomes. The book explores RAG's role in enhancing organizational operations by blending theoretical foundations with practical techniques. You'll work with detailed coding examples using tools such as LangChain and Chroma's vector database to gain hands-on experience in integrating RAG into AI systems. The chapters contain real-world case studies and sample applications that highlight RAG's diverse use cases, from search engines to chatbots. You'll learn proven methods for managing vector databases, optimizing data retrieval, effective prompt engineering, and quatitatively evaluating performance. The book also takes you through advanced integrations of RAG with cutting-edge AI agents and emerging non-LLM technologies. By the end of this book, you'll be able to successfully deploy RAG in business settings, address common challenges, and push the boundaries of what's possible with this revolutionary AI technique"--Cover, page 4  aEng  aGenerative-AI  aLarge language models-AI