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Generative AI in Action
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
• 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 technology
In 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 book
Generative 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 inside
• Best practices for deploying Generative AI apps
• Production-quality RAG
• Adapting GenAI models to your specific domain
About the reader
For enterprise architects, developers, and data scientists interested in upgrading their architectures with generative AI.
About the author
Amit Bahree is Principal Group Product Manager for the Azure AI engineering team at Microsoft.
The technical editor on this book was Wee Hyong Tok.
Table of Contents
Part 1
1 Introduction to generative AI
2 Introduction to large language models
3 Working through an Generating text
4 From pixels to Generating images
5 What else can AI generate?
Part 2
6 Guide to prompt engineering
7 Retrieval-aug
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
• 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 technology
In 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 book
Generative 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 inside
• Best practices for deploying Generative AI apps
• Production-quality RAG
• Adapting GenAI models to your specific domain
About the reader
For enterprise architects, developers, and data scientists interested in upgrading their architectures with generative AI.
About the author
Amit Bahree is Principal Group Product Manager for the Azure AI engineering team at Microsoft.
The technical editor on this book was Wee Hyong Tok.
Table of Contents
Part 1
1 Introduction to generative AI
2 Introduction to large language models
3 Working through an Generating text
4 From pixels to Generating images
5 What else can AI generate?
Part 2
6 Guide to prompt engineering
7 Retrieval-aug
464 pages, Paperback
Published October 29, 2024
15 people are currently reading
27 people want to read
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Displaying 1 - 4 of 4 reviews
December 24, 2024
Going with a higher rating based on "how much I recommend" vs "how much did this book help me"
If you're just getting started with Generative AI this book is an excellent read.
If you're not a beginner, it's still worth your time, but I give it a 3 if you have experience with Generative AI.
If you're just getting started with Generative AI this book is an excellent read.
If you're not a beginner, it's still worth your time, but I give it a 3 if you have experience with Generative AI.
June 14, 2025
left at the part 3, as further than that is not relevant for me right now.
May 1, 2025
The book covers a good range of topics and seems largely accurate, but it's full of slop like the below (chosen by opening the book on a random page, so it's not even particularly cherry-picked). The writing may well be entirely human, but many passages read as if they were written by GPT-4. Given that better models now exist, you'll probably get more up-to-date information with less bloat if you just feed the table of contents into a frontier model and ask it to walk you through each of the areas.
While RAG is still in its early stages of development, it holds the potential to transform
the landscape of text generation models. RAG can be harnessed to produce more
comprehensive, varied, and factual text generation models for many applications.
This section delves into the myriad of benefits that enterprises can gain.
RAG’s ability to draw data from external resources in real-time is a game changer
for sectors that require up-to-the-minute data, such as finance, healthcare, or news.
Whether tracking market dynamics, updating healthcare records, or breaking news,
RAG guarantees the inclusion of the latest information. This ensures that the output
is consistently relevant and current.
June 14, 2025
Lots of things to learn. Good book for beginner to start working on GenAI tech.
Some things were repetitive. Book could be a bit shorter.
Some things were repetitive. Book could be a bit shorter.
Displaying 1 - 4 of 4 reviews