Description AI is rapidly permeating every facet of our lives, fine-tuning the quality of our existence and shaping a better future. Organizations are improving their business performance by leveraging AI in their digital transformation initiatives. At the heart of this fervent global wave are the data scientists, the data engineers, the AI architects and developers, who are infusing AI into applications to solve real-world problems. This book begins with an understanding of AI, subsequently showing how to apply AI to solve real-world challenges. Each chapter provides several illustrations, code examples, and hands-on exercises to augment further understanding of the technical concepts, preparing the readers to implement right from the very first chapter. The readers also learn how to make their AI-based solutions robust and enterprise-ready. Though the concepts are explained with Java and AI tools in Azure, this could be well applied using other programming languages and other similar cloud environments. This book will help Java developers and architects quickly ramp up on AI and use the necessary tools to build AI-enabled applications. AI technology stakeholders, administrators, and enthusiasts will learn and understand the concepts and how these are being applied in the real-world. What you will learn Implement language, vision, and speech using cognitive AI. Develop text, vector, semantic, and multimodal search capabilities. Master generative and document AI for multimodal processing. Build multimodal chatbots to handle real-time AI conversations. Orchestrate multi-agent systems using Semantic Kernel and MCP. Leverage Azure AI, Microsoft Fabric, and AI Foundry. Operationalize and secure real-world enterprise AI use cases. Who this book is for This book is for Java developers, architects, cloud AI engineers, data scientists, IT administrators, stakeholders, and AI enthusiasts who want to build, design, deploy, and manage AI-enabled applications. It assumes a basic understanding of AI concepts, Azure cloud computing, and Java programming. Table of Contents 1. Introduction to AI 2. AI in the Cloud 3. Data in AI 4. Language, Vision, Speech 5. Search 6. Generative AI services 7. Document AI 8. Conversational AI 9. AI Agents 10. Security 11. Production 12. Use Cases and Applications
