Mohlo by se vám také líbit

Více informací o knize Retrieval-Augmented Generation for AI

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 47 bodů

Anotace knihy

Retrieval-Augmented Generation for AI: Build Reliable, Up-to-Date LLMs with Real-World Knowledge

Are you tired of AI models that hallucinate, fail to cite sources, or fall behind on the latest knowledge? In a world where accuracy, transparency, and trust are non-negotiable, the standard approach to language models just isn't enough.

Retrieval-Augmented Generation for AI: Build Reliable, Up-to-Date LLMs with Real-World Knowledge delivers a proven framework for engineers, architects, and leaders who need answers they can trust. This comprehensive guide is the essential resource for building AI solutions that stay current, grounded, and auditable-no matter how fast the information landscape changes.

Whether you're modernizing enterprise search, deploying an intelligent chatbot, or powering a next-generation virtual assistant, this book shows you step-by-step how to connect language models with dynamic, high-quality data. Discover practical strategies for seamless retrieval, powerful prompt engineering, and context integration-backed by real code, robust patterns, and production-tested tools like LangChain, LlamaIndex, Pinecone, and Haystack.

Inside, you'll master:

• End-to-end RAG system design-architecture, workflow, and best practices for reliability and scale

• Building high-performance knowledge bases from structured, semi-structured, and unstructured sources

• Embedding model selection, hybrid search, and retrieval optimization for fast, relevant answers

• Advanced prompt engineering, context management, and real-world handling of long documents

• Deploying, monitoring, and scaling with confidence, including security, privacy, and compliance essentials

• Proven techniques for bias reduction, fairness, and transparent source attribution

• Operational checklists, troubleshooting guides, and hands-on case studies for immediate results

Ready to deliver AI that stays accurate, up-to-date, and worthy of user trust? This is the definitive handbook for anyone serious about retrieval-augmented generation. Stop relying on guesswork and take control of your language model's output-get the clarity, performance, and transparency your users demand.

Parametry knihy

• Plný název: Retrieval-Augmented Generation for AI
• Podnázev: Build Reliable, Up-to-Date LLMs with Real-World Knowledge
• Autor: William L. Younker
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 228
• EAN: 9798265291004
• ID: 50537252
• Nakladatelství: Independently published
• Hmotnost: 405 g
• Rozměry: 254 × 178 × 12 mm
• Datum vydání: 14. September 2025

---

---

---