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Introduction to Generative AI
Generative AI tools like ChatGPT are amazing—but how will their use impact our society? This book introduces the world-transforming technology and the strategies you need to use generative AI safely and effectively.
Introduction to Generative AI gives you the hows-and-whys of generative AI in accessible language. In this easy-to-read introduction, you’ll
How large language models (LLMs) work How to integrate generative AI into your personal and professional workflows Balancing innovation and responsibility The social, legal, and policy landscape around generative AI Societal impacts of generative AI Where AI is going
Anyone who uses ChatGPT for even a few minutes can tell that it’s truly different from other chatbots or question-and-answer tools. Introduction to Generative AI guides you from that first eye-opening interaction to how these powerful tools can transform your personal and professional life. In it, you’ll get no-nonsense guidance on generative AI fundamentals to help you understand what these models are (and aren’t) capable of, and how you can use them to your greatest advantage.
Foreword by Sahar Massachi.
About the technology
Generative AI tools like ChatGPT, Bing, and Bard have permanently transformed the way we work, learn, and communicate. This delightful book shows you exactly how Generative AI works in plain, jargon-free English, along with the insights you’ll need to use it safely and effectively.
About the book
Introduction to Generative AI guides you through benefits, risks, and limitations of Generative AI technology. You’ll discover how AI models learn and think, explore best practices for creating text and graphics, and consider the impact of AI on society, the economy, and the law. Along the way, you’ll practice strategies for getting accurate responses and even understand how to handle misuse and security threats.
What's inside
How large language models work Integrate Generative AI into your daily work Balance innovation and responsibility
About the reader
For anyone interested in Generative AI. No technical experience required.
About the author
Numa Dhamani is a natural language processing expert working at the intersection of technology and society. Maggie Engler is an engineer and researcher currently working on safety for large language models.
The technical editor on this book was Maris Sekar.
Table of Contents
1 Large language The power of AI Evolution of natural language processing
2 Training large language models
3 Data privacy and safety with LLMs
4 The evolution of created content
5 Misuse and adversarial attacks
6 Accelerating Machine-augmented work
7 Making social connections with chatbots
8 What’s next for AI and LLMs
9 Broadening the Exploratory topics in AI
Introduction to Generative AI gives you the hows-and-whys of generative AI in accessible language. In this easy-to-read introduction, you’ll
How large language models (LLMs) work How to integrate generative AI into your personal and professional workflows Balancing innovation and responsibility The social, legal, and policy landscape around generative AI Societal impacts of generative AI Where AI is going
Anyone who uses ChatGPT for even a few minutes can tell that it’s truly different from other chatbots or question-and-answer tools. Introduction to Generative AI guides you from that first eye-opening interaction to how these powerful tools can transform your personal and professional life. In it, you’ll get no-nonsense guidance on generative AI fundamentals to help you understand what these models are (and aren’t) capable of, and how you can use them to your greatest advantage.
Foreword by Sahar Massachi.
About the technology
Generative AI tools like ChatGPT, Bing, and Bard have permanently transformed the way we work, learn, and communicate. This delightful book shows you exactly how Generative AI works in plain, jargon-free English, along with the insights you’ll need to use it safely and effectively.
About the book
Introduction to Generative AI guides you through benefits, risks, and limitations of Generative AI technology. You’ll discover how AI models learn and think, explore best practices for creating text and graphics, and consider the impact of AI on society, the economy, and the law. Along the way, you’ll practice strategies for getting accurate responses and even understand how to handle misuse and security threats.
What's inside
How large language models work Integrate Generative AI into your daily work Balance innovation and responsibility
About the reader
For anyone interested in Generative AI. No technical experience required.
About the author
Numa Dhamani is a natural language processing expert working at the intersection of technology and society. Maggie Engler is an engineer and researcher currently working on safety for large language models.
The technical editor on this book was Maris Sekar.
Table of Contents
1 Large language The power of AI Evolution of natural language processing
2 Training large language models
3 Data privacy and safety with LLMs
4 The evolution of created content
5 Misuse and adversarial attacks
6 Accelerating Machine-augmented work
7 Making social connections with chatbots
8 What’s next for AI and LLMs
9 Broadening the Exploratory topics in AI
457 pages, Kindle Edition
Published March 5, 2024
30 people are currently reading
31 people want to read
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Displaying 1 - 9 of 9 reviews
March 9, 2024
I was expecting a technical book, but it is instead a cliché-riddled account of the supposed impacts of the technology, including woke-minded account of social issues and mischaracterization of some people's views.
It was a waste of time for me.
It was a waste of time for me.
Read
June 18, 2025textual descriptions of the variants and social impacts of generative AI
May 11, 2025
This is a decent book on AI. It explains the terms conversational, generative, and agentic AI. It talks about the technology behind AI. It discusses privacy, ethical, security, and legal concerns in and around AI. What I've learnt is that Gen AI is just an accelerator of the race for more data and better models. It has also given access to SMB's and mid-sized businesses to join the race and do high-quality content creation at much lower costs, similar to the advantage of cloud technology.
April 2, 2024
Numa and Maggie’s Introduction to Generative AI is a refreshing antidote to the prevailing attitude of ChatGPT as a magical genie or some sort of doomsday device [1]. Their deep dive in the topic shows generative AI as a mirror to our society, warts and all.
The first few chapters of the book cover how these models are constructed and why bias, stereotyping, and discrimination is found in these systems. The very qualities that make generative AI seem so wondrous unfortunately also make it inherit some of the worst traits on the internet (think reddit but like ALL of it). Additionally, the explanation of why these models seem to be skilled at tasks they were not trained for is crucial for understanding why so many people have invested in AI.
It then transitions into how you should be using these systems and the potential data privacy concerns. The book then delves into my favorite chapter of how Generative AI systems can be compromised or used to spread disinformation. Once again, the building blocks of AI technology make it especially vulnerable to attacks by bad actors.
The breadth of this book is quite extensive. It’s filled to the brim with useful websites and references as well as anecdotes, legal frameworks, hacking, AI relationships, Lazarus movie stars, and more. There are sections on utopian societies and how you should use ChatGPT today to get the best results (chapter 3 should be required reading for everyone).
As someone who uses ChatGPT and Gemini quite frequently but has felt a sense of unease around AI, this book has made me feel excited about the benefits of AI and tentatively hopeful we will be able to deal with some of it’s challenges.
Numa and Maggie make sure to frame Generative AI in a global context which is much appreciated and sadly rare for most books about technology. If we believe in an equitable future then we have to include everyone who is using it. The book ends on a philosophical note showing the connection between some leading thinkers on AI and their concerning connection to eugenics. The people that are affected by Artificial Intelligence should be both considered and involved in it’s production, regulation, and not just it’s consumption.
Numa and Maggie have done something rare for technologists. Not only have they written a book about an emerging technology but they have picked a side and a blueprint on how the future of AI should be regulated (both societally and legally) to reduce bias, protect privacy, and generally be helpful to people today. This is not just an introduction to Generative AI, it is a treatise on ethics and in a way is asking one of the oldest questions there is, how should we treat one another and who should we care about? As we delve deeper into artificial intelligence, it will ask us to reexamine our humanity, hopefully we come out with a passing grade.
Note: I came out of this book very curious about how AI models would react differently in non-English dominant training sets. Would a AI bot only trained in Arabic poetry or Chinese Literature gave us very different answers (translation issues notwithstanding)?
References:
[1] Will A.I. Become the New McKinsey?
https://www.newyorker.com/science/ann...
To be clear this article is talking about why A.I. is not a genie and this line of reasoning is dangerous and misguided.
[2] But what is a neural network? | Chapter 1, Deep learning
https://www.youtube.com/watch?v=aircA...
I’d advise watching this video while reading the first few chapters of the book. It helped me visualize the idea of a neural network.
The first few chapters of the book cover how these models are constructed and why bias, stereotyping, and discrimination is found in these systems. The very qualities that make generative AI seem so wondrous unfortunately also make it inherit some of the worst traits on the internet (think reddit but like ALL of it). Additionally, the explanation of why these models seem to be skilled at tasks they were not trained for is crucial for understanding why so many people have invested in AI.
It then transitions into how you should be using these systems and the potential data privacy concerns. The book then delves into my favorite chapter of how Generative AI systems can be compromised or used to spread disinformation. Once again, the building blocks of AI technology make it especially vulnerable to attacks by bad actors.
The breadth of this book is quite extensive. It’s filled to the brim with useful websites and references as well as anecdotes, legal frameworks, hacking, AI relationships, Lazarus movie stars, and more. There are sections on utopian societies and how you should use ChatGPT today to get the best results (chapter 3 should be required reading for everyone).
As someone who uses ChatGPT and Gemini quite frequently but has felt a sense of unease around AI, this book has made me feel excited about the benefits of AI and tentatively hopeful we will be able to deal with some of it’s challenges.
Numa and Maggie make sure to frame Generative AI in a global context which is much appreciated and sadly rare for most books about technology. If we believe in an equitable future then we have to include everyone who is using it. The book ends on a philosophical note showing the connection between some leading thinkers on AI and their concerning connection to eugenics. The people that are affected by Artificial Intelligence should be both considered and involved in it’s production, regulation, and not just it’s consumption.
Numa and Maggie have done something rare for technologists. Not only have they written a book about an emerging technology but they have picked a side and a blueprint on how the future of AI should be regulated (both societally and legally) to reduce bias, protect privacy, and generally be helpful to people today. This is not just an introduction to Generative AI, it is a treatise on ethics and in a way is asking one of the oldest questions there is, how should we treat one another and who should we care about? As we delve deeper into artificial intelligence, it will ask us to reexamine our humanity, hopefully we come out with a passing grade.
Note: I came out of this book very curious about how AI models would react differently in non-English dominant training sets. Would a AI bot only trained in Arabic poetry or Chinese Literature gave us very different answers (translation issues notwithstanding)?
References:
[1] Will A.I. Become the New McKinsey?
https://www.newyorker.com/science/ann...
To be clear this article is talking about why A.I. is not a genie and this line of reasoning is dangerous and misguided.
[2] But what is a neural network? | Chapter 1, Deep learning
https://www.youtube.com/watch?v=aircA...
I’d advise watching this video while reading the first few chapters of the book. It helped me visualize the idea of a neural network.
March 4, 2024
It's a comprehensive, up to date, hands on, easy to follow book explaining "Gen AI" (and the history of AI) with its latest LLMs, use cases, caveats, society, security and the future.
The topics, diagrams and summaries are thoughtful and aid in reinforcing your understanding of the text.
I enjoyed reading it in chapter sequence continuously learning about the current AI systems that are capable of generating content in response to "prompts".
The assumed (non technical) reader will come away with more than enough knowledge and vocabulary ( whence 5 stars ) to start their journey in safely using Generative AI as another software tool for creating content, problem solving, chat responses, documents, designs, synthetic data, video, images and many other artifacts the Human can imagine.
The topics, diagrams and summaries are thoughtful and aid in reinforcing your understanding of the text.
I enjoyed reading it in chapter sequence continuously learning about the current AI systems that are capable of generating content in response to "prompts".
The assumed (non technical) reader will come away with more than enough knowledge and vocabulary ( whence 5 stars ) to start their journey in safely using Generative AI as another software tool for creating content, problem solving, chat responses, documents, designs, synthetic data, video, images and many other artifacts the Human can imagine.
February 18, 2024
📕 Why (Not) to read this book (Target Audience)
Looks at AI beyond the hype.
👀 How this book changed my daily live (Takeaways)
SYNTHETIC MEDIA or, more specifically, AI-generated media, is an umbrella term for content that has been created or altered with the help of AI, which spans text, image, video, voice, and data.
Pablo Picasso, one of the most renowned painters of the 20th century, allegedly said, “Good artists copy; great artists steal”
⁉ Spoiler Alerts (Highlights)
LLMs often encode and amplify stereotypical and derogatory associations; they also contain sensitive data, including personally identifiable information (PII).
Looks at AI beyond the hype.
👀 How this book changed my daily live (Takeaways)
SYNTHETIC MEDIA or, more specifically, AI-generated media, is an umbrella term for content that has been created or altered with the help of AI, which spans text, image, video, voice, and data.
Pablo Picasso, one of the most renowned painters of the 20th century, allegedly said, “Good artists copy; great artists steal”
⁉ Spoiler Alerts (Highlights)
LLMs often encode and amplify stereotypical and derogatory associations; they also contain sensitive data, including personally identifiable information (PII).
January 1, 2024
I opted for the audiobook rendition of this book. It offers an effortlessly engaging experience, presenting a comprehensive overview without delving into intricate technicalities. I would confidently recommend it as a valuable reference guide.
May 12, 2024
It is one of the best books to introduce non tech people to the world of LLM.
Every detail, pro&cons, all are discussed in detail.
Every detail, pro&cons, all are discussed in detail.
March 3, 2025
I went through the audio book. It's very good. But the problem is many times they refer to figures in the printed book which is a challenge. E.g. Please check diagram 3.1.
Displaying 1 - 9 of 9 reviews