RAG-Driven Generative AI, 2E by Denis Rothman (.PDF)
File Size: 12.5 MB
RAG-Driven Generative AI: Build MAS-RAG with DualRAG, GraphRAG, multimodal video pipelines, and Oracle Database 23ai, 2nd Edition by Denis Rothman
Requirements: .PDF reader, 12.5 MB | True PDF
Overview: Building MAS-RAG (multi-agent AI systems for RAG) that reason over real-world data using hybrid retrieval and scalable architectures for production use. Stop moving your data to the AI. This second edition defines a revolutionary architectural shift: bringing the AI to the data. By using Oracle Database 23ai as a converged engine in this book, you will architect Sovereign AI systems that eliminate the fragmentation, latency, and massive security risks inherent in traditional data extraction. You’ll work with DualRAG, synchronizing unstructured vector semantics with the deterministic truth of structured SQL, Graph, and Spatial retrieval. This allows your systems to reason over verified corporate data rather than probabilistic guesses, reducing hallucinations at the source. Moving beyond simple pipelines, you’ll also build MAS-RAG (multi-agent systems for RAG), where autonomous agents coordinate across hybrid retrieval workflows, multimodal video pipelines, and graph-based knowledge structures. This book is for AI engineers, ML engineers, data scientists, and MLOps professionals who want to build production-ready generative AI systems grounded in enterprise data. It will also benefit solutions architects, database engineers, and software developers looking to integrate large language models with structured and unstructured data sources using modern retrieval architectures. Readers should be comfortable with Python and have a basic understanding of Machine Learning concepts. Prior experience with generative AI or vector databases will help you get the most out of this book.
Genre: Non-Fiction > Tech & Devices
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