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 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.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

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

像ChatGPT這樣的生成式AI工具真是令人驚嘆，但它們的使用將如何影響我們的社會呢？這本書介紹了這個改變世界的技術以及您使用生成式AI的安全和有效策略。

《生成式AI入門》以易於理解的語言向您介紹生成式AI的原理和目的。在這本易讀的介紹中，您將學到：

- 大型語言模型（LLM）的工作原理
- 如何將生成式AI整合到個人和專業工作流程中
- 平衡創新和責任
- 生成式AI周圍的社會、法律和政策環境
- 生成式AI的社會影響
- AI的未來發展方向

任何使用ChatGPT僅僅幾分鐘的人都可以感受到它與其他聊天機器人或問答工具的真正不同之處。《生成式AI入門》將引導您從第一次令人驚嘆的互動開始，了解這些強大工具如何改變您的個人和專業生活。在這本書中，您將獲得關於生成式AI基礎的實用指南，幫助您了解這些模型能夠做到什麼（以及不能做到什麼），以及如何最大程度地利用它們。

Sahar Massachi為本書撰寫了前言。

購買印刷版書籍將包含Manning Publications提供的PDF、Kindle和ePub格式的免費電子書。

關於技術：

像ChatGPT、Bing和Bard這樣的生成式AI工具已經永久改變了我們的工作、學習和溝通方式。這本令人愉快的書以平易近人、不使用行話的英語向您展示生成式AI的工作原理，並提供您使用它的安全和有效策略的見解。

關於本書：

《生成式AI入門》指導您了解生成式AI技術的好處、風險和限制。您將了解AI模型的學習和思考方式，探索創建文本和圖形的最佳實踐，並考慮AI對社會、經濟和法律的影響。在此過程中，您將學習應對濫用和安全威脅的策略，並練習獲得準確回答的技巧。

內容概要：

- 大型語言模型的工作原理
- 將生成式AI融入日常工作
- 平衡創新和責任

關於讀者：

適合對生成式AI感興趣的任何人，無需技術經驗。

關於作者：

Numa Dhamani是一位在技術和社會交叉領域工作的自然語言處理專家。

Maggie Engler是一位工程師和研究人員，目前致力於大型語言模型的安全性。

本書的技術編輯是Maris Sekar。

目錄：

1. 大型語言模型：AI的力量
2. 大型語言模型的訓練
3. LLM的數據隱私和安全性
4. 創建內容的演變
5. 濫用和對抗性攻擊
6. 提高生產力：機器輔助工作
7. 通過聊天機器人建立社交聯繫
8. AI和LLM的未來展望
9. 擴大視野：AI中的探索性主題

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.

Maggie Engler is an engineer and researcher currently working on safety for large language models. She focuses on applying data science and machine learning to abuses in the online ecosystem, and is a domain expert in cybersecurity and trust and safety. Maggie is also an adjunct instructor at the University of Texas at Austin School of Information.

Numa Dhamani 是一位自然語言處理專家，擁有資訊戰、安全和隱私領域的專業知識。她曾為財富500強公司和社交媒體平台開發過機器學習系統，同時也為初創企業和非營利組織提供過相關服務。Numa曾為公司和組織提供過諮詢，擔任過美國國防部研究計劃的首席調查員，並為多個國際同行評審期刊做出了貢獻。

Maggie Engler 是一位工程師和研究員，目前致力於大型語言模型的安全性工作。她專注於將數據科學和機器學習應用於網絡生態系統中的濫用行為，同時也是網絡安全和信任與安全領域的專家。Maggie還是德克薩斯大學奧斯汀分校資訊學院的兼職講師。