Introduction to Generative AI

inside front cover....2

Introduction to Generative AI....3

Copyright....4

dedication....6

contents....7

front matter....14

foreword....14

preface....16

acknowledgments....18

about this book....19

Who should read this book....20

How this book is organized: A road map....21

liveBook discussion forums....23

Other online resources....24

about the author....24

about the cover illustration....27

1 Large language models: The power of AI....28

Evolution of natural language processing....31

The birth of LLMs: Attention is all you need....36

Explosion of LLMs....41

What are LLMs used for?....42

Language modeling....42

Question answering....44

Coding....46

Content generation....48

Logical reasoning....50

Other natural language tasks....52

Where do LLMs fall short?....53

Training data and bias....54

Limitations in controlling machine outputs....58

Sustainability of LLMs....60

Revolutionizing dialogue: Conversational LLMs....62

OpenAI’s ChatGPT....62

Google’s Bard/LaMDA....64

Microsoft’s Bing AI....66

Meta’s LLaMa/Stanford’s Alpaca....69

Summary....71

2 Training large language models....73

How are LLMs trained?....74

Exploring open web data collection....75

Demystifying autoregression and bidirectional token prediction....78

Fine-tuning LLMs....79

The unexpected: Emergent properties of LLMs....80

Quick study: Learning with few examples....81

Is emergence an illusion?....86

What’s in the training data?....87

Encoding bias....87

Sensitive information....93

Summary....96

3 Data privacy and safety with LLMs....98

Safety-focused improvements for LLM generations....99

Post-processing detection algorithms....101

Content filtering or conditional pre-training....103

Reinforcement learning from human feedback....104

Reinforcement learning from AI feedback....108

Navigating user privacy and commercial risks....111

Inadvertent data leakage....112

Best practices when interacting with chatbots....114

Understanding the rules of the road: Data policies and regulations....116

International standards and data protection laws....116

Are chatbots compliant with GDPR?....121

Privacy regulations in academia....123

Corporate policies....124

Summary....126

4 The evolution of created content....127

The rise of synthetic media....128

Popular techniques for creating synthetic media....130

The good and the bad of synthetic media....133

AI or genuine: Detecting synthetic media....135

Generative AI: Transforming creative workflows....139

Marketing applications....139

Artwork creation....143

Intellectual property in the LLM era....148

Copyright law and fair use....148

Open source and licenses....159

Summary....164

5 Misuse and adversarial attacks....166

Cybersecurity and social engineering....167

Information disorder: Adversarial narratives....185

Political bias and electioneering....197

Why do LLMs hallucinate?....202

Misuse of LLMs in the professional world....212

Summary....220

6 Accelerating productivity: Machine-augmented work....222

Using LLMs in the professional space....223

LLMs assisting doctors with administrative tasks....224

LLMs for legal research, discovery, and documentation....228

LLMs augmenting financial investing and bank customer service....231

LLMs as collaborators in creativity....232

LLMs as a programming sidekick....236

LLMs in daily life....241

Generative AI’s footprint on education....251

Detecting AI-generated text....256

How LLMs affect jobs and the economy....263

Summary....266

7 Making social connections with chatbots....268

Chatbots for social interaction....269

Why humans are turning to chatbots for relationship....278

The loneliness epidemic....279

Emotional attachment theory and chatbots....282

The good and bad of human-chatbot relationships....286

Charting a path for beneficial chatbot interaction....296

Summary....306

8 What’s next for AI and LLMs....307

Where are LLM developments headed?....308

Language: The universal interface....309

LLM agents unlock new possibilities....311

The personalization wave....313

Social and technical risks of LLMs....315

Data inputs and outputs....315

Data privacy....318

Adversarial attacks....319

Misuse....323

How society is affected....324

Using LLMs responsibly: Best practices....326

Curating datasets and standardizing documentation....327

Protecting data privacy....330

Explainability, transparency, and bias....332

Model training strategies for safety....339

Enhanced detection....342

Boundaries for user engagement and metrics....345

Humans in the loop....348

AI regulations: An ethics perspective....350

North America overview....351

EU overview....357

China overview....363

Corporate self-governance....366

Toward an AI governance framework....370

Summary....374

9 Broadening the horizon: Exploratory topics in AI....378

The quest for artificial general intelligence....379

AI sentience and consciousness?....390

How LLMs affect the environment....398

The game changer: Open source community....404

Summary....412

references....415

Chapter 1....419

Chapter 2....428

Chapter 3....433

Chapter 4....441

Chapter 5....451

Chapter 6....462

Chapter 7....471

Chapter 8....479

Chapter 9....488

index....492

inside back cover....505

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.

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.