Manning Publications, 2024. — 464 p. — ISBN 978-1633436947.
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 applications.
Architectural patterns, integration guidance, and best practices for generative AI.
The latest techniques like RAG, prompt engineering, and multi-modality.
The challenges and risks of generative AI like hallucinations and jailbreaks.
How to integrate generative AI into your business and IT strategy.
Generative 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 apps.
Production-quality RAG.
Adapting GenAI models to your specific domain.
About the readerFor enterprise architects, developers, and data scientists interested in upgrading their architectures with generative
Table of ContentsPart 1Introduction to generative AI
Introduction to large language models
Working through an API: Generating text
From pixels to pictures: Generating images
What else can AI generate?
Part 2Guide to prompt engineering
Retrieval-augmented generation: The secret weapon
Chatting with your data
Tailoring models with model adaptation and fine-tuning
Part 3Application architecture for generative AI apps
Scaling up: Best practices for production deployment
Evaluations and benchmarks
Guide to ethical GenAI: Principles, practices, and pitfalls
A The book’s GitHub repository
B Responsible AI tools