關於這本電子書
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 learn:
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
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 models: 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 productivity: Machine-augmented work
7 Making social connections with chatbots
8 What’s next for AI and LLMs
9 Broadening the horizon: 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 learn:
- 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 models: 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 productivity: Machine-augmented work
7 Making social connections with chatbots
8 What’s next for AI and LLMs
9 Broadening the horizon: Exploratory topics in AI
關於作者
Numa Dhamani is a natural language processing expert with domain expertise in information warfare, security, and privacy. She has developed machine learning systems for Fortune 500 companies and social media platforms, as well as for startups and nonprofits. Numa has advised companies and organizations, served as the Principal Investigator on the United States Department of Defense’s research programs, and contributed to multiple international peer-reviewed journals.
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