Isbn: 9783112226773 - rag artificial intelligence: retrieval-augmented generation in generative ai (de gruyter textbook) (13 resultados)

Paperback or Softback. Condición: New. Rag Artificial Intelligence: Retrieval-Augmented Generation in Generative AI. Book.

Condición: New.

Taschenbuch. Condición: Neu. Neuware -This book provides a deep dive into the foundations of RAG, covering transformer architectures, vector similarity search, and the integration of retrieval techniques into generative models. Readers will learn to implement RAG using open-source tools, explore real-world applications in chatbots, legal and medical document retrieval, and AI-assisted research, and address challenges like bias and misinformation. 390 pp. Englisch.…

Taschenbuch. Condición: Neu. Neuware -This book provides a deep dive into the foundations of RAG, covering transformer architectures, vector similarity search, and the integration of retrieval techniques into generative models. Readers will learn to implement RAG using open-source tools, explore real-world applications in chatbots, legal and medical document retrieval, and AI-assisted research, and address challenges like bias and misinformation. 390 pp. Englisch.…

Perfect Paperback. Condición: Brand New. 596 pages. 6.69x2.00x9.45 inches. In Stock.

Condición: New. Saloni Garg is a Senior Machine Learning Engineer based in Mountain View, California. With deep expertise in scalable ML systems and infrastructure, she has made impactful contributions to open-source projects including Ray and PyTorch. A passionate tech.

Taschenbuch. Condición: Neu. Neuware -Generative AI has transformed industries, enabling the creation of human-like text, images, and code. However, traditional generative models often suffer from inaccuracies and hallucinations due to their reliance on pre-trained data. Retrieval-Augmented Generation (RAG) addresses this limitation by integrating retrieval mechanisms, enhancing the quality, accuracy, and relevance of generated content.Beyond the foundational aspects, this book delves into the core mechanisms that make RAG more effective than traditional generative models. It covers advanced embedding techniques for efficient knowledge retrieval, vector database optimization, and fine-tuning transformer models to dynamically fetch and incorporate external knowledge into generated responses. Readers will also explore dense retrieval methods, indexing strategies, and real-time query optimization to enhance generative model performance.Additionally, the book explores the synergy between RAG and Large Language Models (LLMs), discussing how hybrid architectures can be designed for improved accuracy, lower computational costs, and reduced model hallucinations. Through case studies and hands-on examples, readers will gain practical insights into deploying RAG-based AI systems at scale, optimizing inference speeds, and ensuring data relevance in diverse application domains. The final chapters will present emerging trends in retrieval-based architectures, multimodal AI integration, and the potential role of RAG in decentralized and federated learning environments.Walter de Gruyter GmbH, Genthiner Straße 13, 10785 Berlin 390 pp. Englisch.…

Taschenbuch. Condición: Neu. RAG Artificial Intelligence | Retrieval-Augmented Generation in Generative AI | Saloni Garg (u. a.) | Taschenbuch | De Gruyter Textbook | XIV | Englisch | 2026 | Walter de Gruyter | EAN 9783112226773 | Verantwortliche Person für die EU: Walter de Gruyter GmbH, De Gruyter GmbH, Genthiner Str. 13, 10785 Berlin, productsafety[at]degruyterbrill[dot]com | Anbieter: preigu.…

Taschenbuch. Condición: Neu. Neuware - This book provides a deep dive into the foundations of RAG, covering transformer architectures, vector similarity search, and the integration of retrieval techniques into generative models. Readers will learn to implement RAG using open-source tools, explore real-world applications in chatbots, legal and medical document retrieval, and AI-assisted research, and address challenges like bias and misinformation.…

Condición: Hervorragend. Zustand: Hervorragend | Seiten: 390 | Sprache: Englisch | Produktart: Bücher | Generative AI has transformed industries, enabling the creation of human-like text, images, and code. However, traditional generative models often suffer from inaccuracies and hallucinations due to their reliance on pre-trained data. Retrieval-Augmented Generation (RAG) addresses this limitation by integrating retrieval mechanisms, enhancing the quality, accuracy, and relevance of generated content.Beyond the foundational aspects, this book delves into the core mechanisms that make RAG more effective than traditional generative models. It covers advanced embedding techniques for efficient knowledge retrieval, vector database optimization, and fine-tuning transformer models to dynamically fetch and incorporate external knowledge into generated responses. Readers will also explore dense retrieval methods, indexing strategies, and real-time query optimization to enhance generative model performance.Additionally, the book explores the synergy between RAG and Large Language Models (LLMs), discussing how hybrid architectures can be designed for improved accuracy, lower computational costs, and reduced model hallucinations. Through case studies and hands-on examples, readers will gain practical insights into deploying RAG-based AI systems at scale, optimizing inference speeds, and ensuring data relevance in diverse application domains. The final chapters will present emerging trends in retrieval-based architectures, multimodal AI integration, and the potential role of RAG in decentralized and federated learning environments.…

Paperback. Condición: new. Paperback. This book provides a deep dive into the foundations of RAG, covering transformer architectures, vector similarity search, and the integration of retrieval techniques into generative models. Readers will learn to implement RAG using open-source tools, explore real-world applications in chatbots, legal and medical document retrieval, and AI-assisted research, and address challenges like bias and misinformation. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condición: new. Paperback. This book provides a deep dive into the foundations of RAG, covering transformer architectures, vector similarity search, and the integration of retrieval techniques into generative models. Readers will learn to implement RAG using open-source tools, explore real-world applications in chatbots, legal and medical document retrieval, and AI-assisted research, and address challenges like bias and misinformation. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Paperback. Condición: new. Paperback. This book provides a deep dive into the foundations of RAG, covering transformer architectures, vector similarity search, and the integration of retrieval techniques into generative models. Readers will learn to implement RAG using open-source tools, explore real-world applications in chatbots, legal and medical document retrieval, and AI-assisted research, and address challenges like bias and misinformation. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…