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Huyen C: AI Engineering

AI Engineering

Building Applications with Foundation Models

Retrieval-Augmented Generation (RAG) represents the cutting edge of AI innovation, bridging the gap between large language models (LLMs) and real-world knowledge. This book provides the definitive roadmap for building, optimizing, and deploying enterprise-grade RAG systems that deliver measurable business value.
This comprehensive guide takes you beyond basic concepts to advanced implementation strategies, covering everything from architectural patterns to production deployment. You'll explore proven techniques for document processing, vector optimization, retrieval enhancement, and system scaling, supported by real-world case studies from leading organizations.
Key Learning Objectives

<li>Design and implement production-ready RAG architectures for diverse enterprise use cases

</li><li>Master advanced retrieval strategies including graph-based approaches and agentic systems

</li><li>Optimize performance through sophisticated chunking, embedding, and vector database techniques

</li><li>Navigate the integration of RAG with modern LLMs and generative AI frameworks

</li><li>Implement robust evaluation frameworks and quality assurance processes

</li><li>Deploy scalable solutions with proper security, privacy, and governance controls




Real-World Applications

</li><li>Intelligent document analysis and knowledge extraction

</li><li>Code generation and technical documentation systems

</li><li>Customer support automation and decision support tools

</li><li>Regulatory compliance and risk management solutions




Whether you're an AI engineer scaling existing systems or a technical leader planning next-generation capabilities, this book provides the expertise needed to succeed in the rapidly evolving landscape of enterprise AI.

What You Will Learn

</li><li>Architecture Mastery: Design scalable RAG systems from prototype to enterprise production

</li><li>Advanced Retrieval: Implement sophisticated strategies, including graph-based and multi-modal approaches

</li><li>Performance Optimization: Fine-tune embedding models, vector databases, and retrieval algorithms for maximum efficiency

</li><li>LLM Integration: Seamlessly combine RAG with state-of-the-art language models and generative AI frameworks

</li><li>Production Excellence: Deploy robust systems with monitoring, evaluation, and continuous improvement processes

</li><li>Industry Applications: Apply RAG solutions across diverse enterprise sectors and use cases




 

Who This Book Is For
Primary audience: Senior AI/ML engineers, data scientists, and technical architects building production AI systems; secondary audience: Engineering managers, technical leads, and AI researchers working with large-scale language models and information retrieval systems
Prerequisites: Intermediate Python programming, basic understanding of machine learning concepts, and familiarity with natural language processing fundamentals

 


</li>

Retrieval-Augmented Generation (RAG) represents the cutting edge of AI innovation, bridging the gap between large language models (LLMs) and real-world knowledge. This book provides the definitive roadmap for building, optimizing, and deploying enterprise-grade RAG systems that deliver measurable business value.This comprehensive guide takes you beyond basic concepts to advanced implementation strategies, covering everything from architectural patterns to production deployment. You'll explore proven techniques for document processing, vector optimization, retrieval enhancement, and system scaling, supported by real-world case studies from leading organizations.Key Learning Objectives<ul><li>Design and implement production-ready RAG architectures for diverse enterprise use cases</li><li>Master advanced retrieval strategies including graph-based approaches and agentic systems</li><li>Optimize performance through sophisticated chunking, embedding, and vector database techniques</li><li>Navigate the integration of RAG with modern LLMs and generative AI frameworks</li><li>Implement robust evaluation frameworks and quality assurance processes</li><li>Deploy scalable solutions with proper security, privacy, and governance controls</li></ul>Real-World Applications<ul><li>Intelligent document analysis and knowledge extraction</li><li>Code generation and technical documentation systems</li><li>Customer support automation and decision support tools</li><li>Regulatory compliance and risk management solutions</li></ul>Whether you're an AI engineer scaling existing systems or a technical leader planning next-generation capabilities, this book provides the expertise needed to succeed in the rapidly evolving landscape of enterprise AI.What You Will Learn<ul><li>Architecture Mastery: Design scalable RAG systems from prototype to enterprise production</li><li>Advanced Retrieval: Implement sophisticated strategies, including graph-based and multi-modal approaches</li><li>Performance Optimization: Fine-tune embedding models, vector databases, and retrieval algorithms for maximum efficiency</li><li>LLM Integration: Seamlessly combine RAG with state-of-the-art language models and generative AI frameworks</li><li>Production Excellence: Deploy robust systems with monitoring, evaluation, and continuous improvement processes</li><li>Industry Applications: Apply RAG solutions across diverse enterprise sectors and use cases</li></ul>&nbsp;Who This Book Is ForPrimary audience: Senior AI/ML engineers, data scientists, and technical architects building production AI systems; secondary audience: Engineering managers, technical leads, and AI researchers working with large-scale language models and information retrieval systemsPrerequisites: Intermediate Python programming, basic understanding of machine learning concepts, and familiarity with natural language processing fundamentals&nbsp;&nbsp;

Advanced Techniques and Production-Ready Solutions for Enterprise AI

Mastering Retrieval-Augmented Generation

The Complete Step-By-Step Guide to Managing Product Development Using Agile Framework

Scrum

A critical introduction to the psychiatric technologies of the future Artificial intelligence (AI) promises to transform nearly every area of modern life, and psychiatry is no exception. The field faces the mounting crisises in diagnostic inaccuracy, treatment stagnation, and persistent failures in suicide prevention, while traditional approaches struggle to keep pace with patient needs. AI and neuroscience offer a new path forward, pointing toward a future where mental health care is grounded in objective data, individualized predictions, and biologically informed treatments. Decoding Despair provides a cutting-edge look at these emerging scientific possibilities and the long-standing norms they may replace. Beginning with an examination of psychiatry's current challenges, it moves toward a present where AI-powered tools are beginning to reshape diagnostics, treatment selection, and drug development. The book offers readers a deeper understanding of mental health as both a scientific field and a lived human experience, while igniting an essential conversation about the transformative potential of precision psychiatry and technology. Decoding Despair readers will also find: <ul> <li>Exploration of the patient's journey from first symptoms to being prescribed medication</li> <li>Deep dive into the healthcare system and an understanding of the connections between stakeholders</li> <li>Clear explanations of how AI models work and how they can be practically applied to solving issues in mental health</li> <li>Deep introduction into the world of data and the different models of data acquisition necessary for building AI solutions</li> <li>Analysis of the potential innovations that could come first and the conditions necessary for them to occur</li> </ul> &nbsp; Decoding Despair is ideal for professionals and innovators building the future of psychiatry-as well as anyone seeking to understand their own mental health and the technological breakthroughs poised to reshape this critical field of care.

How AI is Reshaping Psychiatry

Decoding Despair

Revolution of AI and Machine Learning for Design and Automation

Recursions

A Media Theory of Machine Learning

Errant Intelligence

Inventory Optimization

This book serves as an essential guide for both beginners and advanced learners in the field of inventory control and supply chain management. It meticulously presents the fundamental terminologies, models, and theories necessary for understanding and mastering these subjects. What sets this book apart is its incorporation of modern, updated methods rooted in probability theory and fuzzy logic, offering readers a deeper insight into the complexities of inventory and supply chain issues. Instead of focusing solely on contemporary advancements, this book explores a wide range of inventory and supply chain problems, utilizing fuzzy logic to provide innovative solutions. It thoroughly integrates the latest developments in the field, ensuring readers are equipped with the most current knowledge. Ideal for beginners, professionals, and researchers alike, this book offers a comprehensive, up-to-date resource for tackling inventory and supply chain challenges effectively.

Innovative Approaches to Inventory Control and Supply Chain Management

This innovative textbook edited by international experts in technology law and policy provides a comprehensive and accessible guide into the fast-evolving landscape of technology law and policy in the UK and the EU. The recent wave of regulatory reforms adopted by UK and EU regulators increases the complexity of Internet law as it had developed in the past decades. Recognising the ever-growing importance of artificial intelligence in today's public discourse, the textbook extends beyond traditional legal sectoral frameworks, and explores the intersection of law, technology, and public policy to describe and critically reflect on current and emerging issues in the modern information society. This exploration follows thematic areas of interest, such as adtech, privacy by design, predictive policing, and social media, while also providing accessible historical overviews of how policy has developed in specific fields including platform liability, copyright, or data protection, and case studies on key topics. The companion website provides multimedia resources to delve deeper into specific topics; introductory materials for readers that are unfamiliar with the EU legal system; and teaching resources. Law, Policy, and the Internet is an essential resource for anyone seeking to navigate the complexities of internet regulation in an era of exponential technological change.

Law, Policy, and the Internet

A roadmap for business leaders to unlock the full potential of data, machine learning, and artificial intelligenceMore than 90 percent of businesses surveyed say they want to capitalize on data--but two-thirds admit to feeling stuck. What these leaders do not realize is that to succeed at becoming a data-driven business requires developing a nuanced understanding of why data holds such transformative power, what a data-inspired culture looks like, and how to get there.Data Inspired shows that the secret isn't to be more data-driven--it is to become data-inspired. This book reveals the crucial strategic distinction between using data to optimize existing operations and using them as a catalyst for deep transformation and innovation. Wernicke argues that this success hinges less on technology and more on reshaping an organization's culture and decision-making habits. And with the book's proven principles, real-world examples, and comprehensive toolbox of methods for building a culture of evidence-based inquiry, readers will learn that success means far more than just adding more data to a business: it is about creating a thoroughly data-inspired organization with innovative work methods, new structures, and unmatched efficiency.Data Inspired will help business leaders, managers, and data professionals move beyond incremental improvements to achieve lasting, powerful change.

Building an Organizational Culture of Inquiry for Lasting Transformation

Data Inspired

In today's AI landscape, success depends not just on prompting large language models but on orchestrating them into intelligent systems that are scalable, compliant, and cost-effective. GenAI on Google Cloud is your hands-on guide to bridging that gap. Whether you're an ML engineer or an enterprise leader, this book offers a practical game plan for taking agentic systems from prototype to production. Written by practitioners with deep experience in AgentOps, data engineering, and GenAI infrastructure, this guide takes you through real-world workflows from data prep and deployment to orchestration and integration. With concrete examples, field-tested frameworks, and honest insights, you'll learn how to build agentic systems that deliver measurable business value. <ul><li>Bridge the production gap that stalls 90% of vertical AI initiatives using systematic deployment frameworks</li> <li>Navigate AgentOps complexities through practical guidance on orchestration, evaluation, and responsible AI practices</li> <li>Build robust multimodal systems for text, images, and video using proven agent architectures</li> <li>Optimize for scale with strategies for cost management, performance tuning, and production monitoring</li></ul>

Enterprise Generative AI Systems and Agents

Genai on Google Cloud

THE AGI CHRONICLES is not a futurist manifesto, an academic chin-stroker, a corporate biography, or a self-help manual. It's the inside story of the birth of AGI, as told by the people who are bringing it into existence, or trying to stop it from coming into existence, and who are grappling with the consequences before anyone else.Building Artificial General Intelligence - a machine that is as smart or smarter than humans, at everything our brains can do - has been the goal for the world's biggest technology companies for about the last decade, and it is probably the most consequential technological project in history.&nbsp;Only a few hundred people are fully awake to what's actually happening on the AI frontier, or how short the timelines are. Powerful AI will reshape society -&nbsp;and most governments and big corporations already view this conclusion as obvious, as evidenced by the trillions of dollars they're spending to get there first.&nbsp;New York Times&nbsp;journalist Kevin Roose may be the only person who can tell this story. He has put his life on hold, gone to the heart of the action, interviewed those who have been involved in building this technology, digging up secrets and putting together the first major behind-the-scenes account of this race.And the people building powerful AI are much, much weirder than you'd think. If you dig beneath the corporate veneers, the AI scene here is full of messianic claims, cult-like dynamics, and a degree of belief in the inevitability and imminence of powerful AI that can strike the uninitiated as genuinely insane.This is gripping, characterful, first draft of history that reads like a non-fiction thriller, for readers of THE BIG SHORT, CARELESS PEOPLE and AMERICAN PROMETHEUS. It's the book that people will turn to one hundred years from now as a defining account of the moment our species was changed for ever.

The AGI Chronicles

Artificial intelligence is rapidly transforming the insurance sector. This book explores how industry practitioners are already implementing AI and how its role will continue to develop. Covering foundational concepts, real-world use cases and strategic and regulatory considerations, it provides a comprehensive, practice-oriented perspective: How can an AI unit be established? What role does AI play in underwriting, brokerage, and back-office operations? And how is it transforming the customer experience?
Leading experts from across the entire spectrum of the industry share their insights. 

The book examines the gap between AI's theoretical potential and its practical implementation, presenting a structured overview of current use cases, opportunities, and risks. It offers a clear understanding of how AI is shaping the insurance industry today - and how it is set to transform it in the years to come.

Insider Perspectives on Opportunities, Risks, and Practical Applications of AI

Artificial Intelligence in the Insurance Industry

A NEW YORK TIMES BESTSELLER 'Extraordinary... beautifully written, clear-eyed and engaged in the deepest ethical questions of our day' Rory Stewart 'Mallaby has done full justice to his kaleidoscopically interesting subject ... expertly structured and vividly reported, the book presents the most insightful portrait of Hassabis to date' Financial Times A revelatory portrait of the visionary behind Google DeepMind, the race to control the future - and what it means to win Even in a tech world crowded with visionary leaders, Demis Hassabis is recognized as a special case. Born to working class, immigrant parents in North London, a chess prodigy by five and wizard coder in his teens, he turned down a seven-figure job offer from a video-game studio to study science at Cambridge. Long before the current obsession with AI, he founded the path-breaking company DeepMind in order to pursue a single, audacious goal: the dream of artificial superintelligence, which would solve humanity's hardest problems, change life and work as we know it, and perhaps even unlock the deepest mysteries of the Universe. For his scientific achievements, he won a Nobel Prize in 2024, and his company, now Google DeepMind, is considered the tech giant's engine room. For the past three years, Sebastian Mallaby has had unprecedented access to Hassabis and DeepMind, conducting hundreds of hours of interviews with him and his inner circle as well as detractors and rivals at other companies. The result is a revelation-packed portrait of a singular mind and a historic reckoning with the AI revolution, a shift potentially more significant than any since the dawn of complex thought 70,000 years ago. As Mallaby chronicles, DeepMind is locked in an arms race with Silicon Valley competitors to build artificial general intelligence, and thereby become the keeper of humanity's future. Yet this is not a Silicon Valley story. Hassabis has remained in Britain, and unlike his rivals, his aims are not wealth and power but scientific enlightenment. Like them, however, he is haunted by the memory of Robert Oppenheimer, the creator of the atom bomb. He aims to control the technology, but the technology may ultimately control him - and humanity writ large.

Demis Hassabis, DeepMind and the Quest for Superintelligence

The Infinity Machine

AI Engineering

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