Generative AI can transform your business by streamlining the process of creating text, images, and code. This book will show you how to get in on the action!Generative AI in Action is the comprehensive and concrete guide to generative AI you’ve been searching for. It introduces both AI’s fundamental principles and its practical applications in an enterprise context—from generating text and images for product catalogs and marketing campaigns, to technical reporting, and even writing software. Inside, author Amit Bahree shares his experience leading Generative AI projects at Microsoft for nearly a decade, starting well before the current GPT revolution.Inside Generative AI in Action you will find:A practical overview of of generative AI applicationsArchitectural patterns, integration guidance, and best practices for generative AIThe latest techniques like RAG, prompt engineering, and multi-modalityThe challenges and risks of generative AI like hallucinations and jailbreaksHow to integrate generative AI into your business and IT strategyGenerative AI in Action is full of real-world use cases for generative AI, showing you where and how to start integrating this powerful technology into your products and workflows. You’ll benefit from tried-and-tested implementation advice, as well as application architectures to deploy GenAI in production at enterprise scale.About the technologyIn controlled environments, deep learning systems routinely surpass humans in reading comprehension, image recognition, and language understanding. Large Language Models (LLMs) can deliver similar results in text and image generation and predictive reasoning. Outside the lab, though, generative AI can both impress and fail spectacularly. So how do you get the results you want? Keep reading!About the bookGenerative AI in Action presents concrete examples, insights, and techniques for using LLMs and other modern AI technologies successfully and safely. In it, you’ll find practical approaches for incorporating AI into marketing, software development, business report generation, data storytelling, and other typically-human tasks. You’ll explore the emerging patterns for GenAI apps, master best practices for prompt engineering, and learn how to address hallucination, high operating costs, the rapid pace of change and other common problems.What's insideBest practices for deploying Generative AI appsProduction-quality RAGAdapting GenAI models to your specific domainAbout the readerFor enterprise architects, developers, and data scientists interested in upgrading their architectures with generative AI.About the AuthorAmit Bahree is a Principal Group TPM at Microsoft, where he is part of the engineering team building the next generation of AI products and services for millions of customers using the Azure AI platform. He is also responsible for custom engineering across the platform with key customers, solving complex enterprise scenarios using all forms of AI, including generative AI. Table of ContentsPart 11 Introduction to generative AI2 Introduction to large language models3 Working through an API: Generating text4 From pixels to pictures: Generating images5 What else can AI generate?Part 26 Guide to prompt engineering7 Retrieval-augmented generation: The secret weapon8 Chatting with your data9 Tailoring models with model adaptation and fine-tuningPart 310 Application architecture for generative AI apps11 Scaling up: Best practices for production deployment12 Evaluations and benchmarks13 Guide to ethical GenAI: Principles, practices, and pitfallsA The book’s GitHub repositoryB Responsible AI tools