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Taschenbuch. Zustand: Neu. Neuware - Build a private, production-ready AI chatbot from the ground up-without surrendering control of your data. \*Build Your Own AI Chatbot\* is a practical, implementation-focused guide to creating retrieval-augmented generation (RAG) applications with PostgreSQL, pgvector, Python, and FastAPI. Designed for developers, technology professionals, students, and educators, the book moves beyond basic chatbot demonstrations to explain how reliable RAG systems are architected, secured, tested, evaluated, and deployed. Readers begin by building a working local chatbot and then progressively strengthen every layer of the system. The book covers document ingestion, source tracking, semantic chunking, embedding generation, vector indexing, similarity search, hybrid retrieval, reranking, evidence selection, prompt assembly, citation validation, and grounded response generation. It also addresses the challenges that frequently separate experimental projects from dependable applications, including hallucinations, insufficient evidence, prompt injection, tenant isolation, data retention, observability, performance, and recovery. The hands-on examples use Python and FastAPI for application services, PostgreSQL and pgvector for durable vector storage, and a provider-neutral model interface that supports local, private deployment. Practical code snippets throughout the chapters demonstrate how the individual components fit together while preserving clear security and authorization boundaries. This expanded textbook edition includes: \* 12 detailed chapters covering the complete RAG lifecycle\* A working chatbot quickstart\* 24 cumulative, hands-on implementation labs\* Complete lab solutions collected in the back of the book\* 120 end-of-chapter questions with a comprehensive answer key\* Troubleshooting guidance, a technical glossary, and real-world RAG recipes>Whether you are creating an internal knowledge assistant, a secure enterprise chatbot, an educational project, or your first AI-powered application, \*Build Your Own AI Chatbot\* provides the technical foundation and practical direction needed to transform a promising prototype into a private, powerful, and trustworthy RAG system. …

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Taschenbuch. Zustand: Neu. Neuware - AI can make a company faster. But can it also make the company forget how to think As organizations embed artificial intelligence into customer service, forecasting, software development, security, operations, and decision making, corporate intelligence does not simply disappear. It moves from employees into workflows, from workflows into models, and from the organization into vendors and technology platforms. The danger begins when leaders can no longer locate the knowledge, judgment, memory, or authority their companies depend upon. In \*Where Did the Company's Intelligence Go \*, Richard Lightcap, Ph.D., examines real world examples from Morgan Stanley, Klarna, Amazon, Boston Consulting Group, Zillow, Air Canada, Microsoft, IBM, Moderna, JPMorgan Chase, and Walmart. These cases reveal what happens when AI augments expertise, automates it, obscures it, or carries it beyond the organization's direct control. The book exposes the hidden intelligence deficit that can emerge through employee deskilling, weakened apprenticeship, institutional memory without understanding, vendor dependence, and accountability without meaningful authority. More importantly, it gives leaders practical frameworks for tracing where intelligence has moved, distinguishing productivity from genuine organizational intelligence, preserving critical expertise, designing effective human authority, evaluating AI vendors, and measuring whether automation is making the company more capable or merely more dependent. For executives, board members, technology leaders, cybersecurity and risk professionals, educators, and anyone responsible for the future of work, this book asks the question every organization adopting AI must be prepared to answer: After the transformation is complete, will your company still know how to think.…

PAP. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Zustand: new. Paperback. Build a private, production-ready AI chatbot from the ground up-without surrendering control of your data. *Build Your Own AI Chatbot* is a practical, implementation-focused guide to creating retrieval-augmented generation (RAG) applications with PostgreSQL, pgvector, Python, and FastAPI. Designed for developers, technology professionals, students, and educators, the book moves beyond basic chatbot demonstrations to explain how reliable RAG systems are architected, secured, tested, evaluated, and deployed. Readers begin by building a working local chatbot and then progressively strengthen every layer of the system. The book covers document ingestion, source tracking, semantic chunking, embedding generation, vector indexing, similarity search, hybrid retrieval, reranking, evidence selection, prompt assembly, citation validation, and grounded response generation. It also addresses the challenges that frequently separate experimental projects from dependable applications, including hallucinations, insufficient evidence, prompt injection, tenant isolation, data retention, observability, performance, and recovery. The hands-on examples use Python and FastAPI for application services, PostgreSQL and pgvector for durable vector storage, and a provider-neutral model interface that supports local, private deployment. Practical code snippets throughout the chapters demonstrate how the individual components fit together while preserving clear security and authorization boundaries. This expanded textbook edition includes: * 12 detailed chapters covering the complete RAG lifecycle* A working chatbot quickstart* 24 cumulative, hands-on implementation labs* Complete lab solutions collected in the back of the book* 120 end-of-chapter questions with a comprehensive answer key* Troubleshooting guidance, a technical glossary, and real-world RAG recipes* Deployment, evaluation, security, and operational checklists Whether you are creating an internal knowledge assistant, a secure enterprise chatbot, an educational project, or your first AI-powered application, *Build Your Own AI Chatbot* provides the technical foundation and practical direction needed to transform a promising prototype into a private, powerful, and trustworthy RAG system. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

Paperback. Zustand: New.

Paperback. Zustand: New.

PAP. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Zustand: new. Paperback. AI can make a company faster. But can it also make the company forget how to think? As organizations embed artificial intelligence into customer service, forecasting, software development, security, operations, and decision making, corporate intelligence does not simply disappear. It moves from employees into workflows, from workflows into models, and from the organization into vendors and technology platforms. The danger begins when leaders can no longer locate the knowledge, judgment, memory, or authority their companies depend upon. In *Where Did the Company's Intelligence Go?*, Richard Lightcap, Ph.D., examines real world examples from Morgan Stanley, Klarna, Amazon, Boston Consulting Group, Zillow, Air Canada, Microsoft, IBM, Moderna, JPMorgan Chase, and Walmart. These cases reveal what happens when AI augments expertise, automates it, obscures it, or carries it beyond the organization's direct control. The book exposes the hidden intelligence deficit that can emerge through employee deskilling, weakened apprenticeship, institutional memory without understanding, vendor dependence, and accountability without meaningful authority. More importantly, it gives leaders practical frameworks for tracing where intelligence has moved, distinguishing productivity from genuine organizational intelligence, preserving critical expertise, designing effective human authority, evaluating AI vendors, and measuring whether automation is making the company more capable or merely more dependent. For executives, board members, technology leaders, cybersecurity and risk professionals, educators, and anyone responsible for the future of work, this book asks the question every organization adopting AI must be prepared to answer: After the transformation is complete, will your company still know how to think? This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…