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About the Author ……………………………………………………………………..xv
Acknowledgments ………………………………………………………………….xvii
Preface ………………………………………………………………………………….xix
Introduction …………………………………………………………………………..xxv
Part I: Introduction …………………………………………………………….1
Chapter 1: Basics of Artificial Intelligence …………………………………….3
Why Does AI Matter? …………………………………………………………………………………4
What Is AI? ………………………………………………………………………………………………4
Machine Learning ………………………………………………………………………………..5
What Is Intelligence? …………………………………………………………………………………6
The Turing Test ……………………………………………………………………………………6
How Machines Learn ………………………………………………………………………………..7
What Is Learning? ………………………………………………………………………………..7
Machine Perception ……………………………………………………………………………..8
Language ……………………………………………………………………………………………9
Topics in Artificial Intelligence ……………………………………………………………………9
Application Areas ……………………………………………………………………………….10
Tools and Techniques …………………………………………………………………………13
Summary ………………………………………………………………………………………………15
Terminology from This Chapter …………………………………………………………………16
Part II: Shopping and Product Discovery ……………………………..19
Chapter 2: Natural Language Processing and Conversational
Shopping …………………………………………………………………………………21
Natural Language Processing …………………………………………………………………..22
ELIZA ………………………………………………………………………………………………..22
Chatbots …………………………………………………………………………………………..23
Specialized Chatbots ………………………………………………………………………….23
Conversational Commerce ……………………………………………………………………….24
Natural Language Queries …………………………………………………………………..24
Shopping and Messaging ……………………………………………………………………25
Personalized Shopping Experiences …………………………………………………….26
Bot-to-Bot Interaction …………………………………………………………………………27
Context-Based Decision Making …………………………………………………………..27
Live Chat …………………………………………………………………………………………..28
How Machines Read ……………………………………………………………………………….29
Tokenization ……………………………………………………………………………………..30
Word Embeddings ……………………………………………………………………………..31
Part-of-Speech Tagging ………………………………………………………………………32
Named Entity Recognition …………………………………………………………………..32
Natural Language Understanding ……………………………………………………………..33
Sentiment Analysis …………………………………………………………………………….33
Relation Extraction …………………………………………………………………………….34
Summary ………………………………………………………………………………………………35
Terminology from This Chapter …………………………………………………………………36
Chapter 3: Computer Vision and Smart Mirrors ……………………………39
Retail Meltdown ……………………………………………………………………………………..40
Smart Mirrors …………………………………………………………………………………………40
Data Collection ………………………………………………………………………………….42
Social Sharing and Checkout ………………………………………………………………42
Implementation …………………………………………………………………………………44
Computer Vision ……………………………………………………………………………………..44
Transformation ………………………………………………………………………………….45
Filtering ……………………………………………………………………………………………46
Feature Extraction ……………………………………………………………………………..47
Image Classification …………………………………………………………………………..50
Beyond Static and 2D Images …………………………………………………………………..50
Summary ………………………………………………………………………………………………50
Terminology from This Chapter …………………………………………………………………51
Chapter 4: Neural Networks and Image Search ……………………………53
Fashion Industry Images ………………………………………………………………………….54
Image Search …………………………………………………………………………………………54
Image Tagging …………………………………………………………………………………..56
Reverse Image Search ………………………………………………………………………..56
Visual Search …………………………………………………………………………………….58
Neural Networks …………………………………………………………………………………….59
Types of Neural Networks ………………………………………………………………………..60
Feed-Forward Neural Networks …………………………………………………………..60
Recurrent Neural Networks …………………………………………………………………62
Convolutional Neural Networks ……………………………………………………………63
Training Neural Networks ……………………………………………………………………64
Training Data …………………………………………………………………………………….65
Standardized Datasets ……………………………………………………………………….65
Adversarial Examples ……………………………………………………………………………..67
Adversarial Image Overlays …………………………………………………………………68
Adversarial Additions ………………………………………………………………………….69
Adversarial Objects ……………………………………………………………………………70
Possible Implications ………………………………………………………………………….70
Summary ………………………………………………………………………………………………71
Terminology from This Chapter …………………………………………………………………71
Chapter 5: Virtual Style Assistants ……………………………………………..75
Virtual Style Assistants ……………………………………………………………………………76
Personal Stylists ………………………………………………………………………………..76
Virtual Assistants ……………………………………………………………………………….77
Voice Interfaces …………………………………………………………………………………77
Features of the Virtual Style Assistant …………………………………………………..78
Existing Examples …………………………………………………………………………………..78
Amazon’s Echo Look …………………………………………………………………………..79
The Hardware ……………………………………………………………………………………80
Image-Based Reviews …………………………………………………………………………….82
The Future of Image-Based Reviews …………………………………………………….82
Artificial General Intelligence ……………………………………………………………………83
Hybrid Intelligence ……………………………………………………………………………..84
Pitfalls of Artificial General Intelligence …………………………………………………84
Dangers of AI …………………………………………………………………………………….84
Summary ………………………………………………………………………………………………85
Terminology from This Chapter …………………………………………………………………86
Part III: Sales …………………………………………………………………..87
Chapter 6: Data Science and Subscription Services ……………………..89
Subscription Models ……………………………………………………………………………….90
Brand Subscriptions …………………………………………………………………………..92
Targeted Subscriptions ……………………………………………………………………….92
User-Selected Subscriptions ……………………………………………………………….92
Consumables Subscriptions ………………………………………………………………..93
Rental Subscriptions ………………………………………………………………………….93
Digital Personalization …………………………………………………………………………….94
Recommendation Engines …………………………………………………………………..95
Data Science …………………………………………………………………………………….97
Summary …………………………………………………………………………………………….104
Terminology from This Chapter ……………………………………………………………….104
Chapter 7: Predictive Analytics and Size Recommendations ………..107
The Fit Problem …………………………………………………………………………………….107
What Are Predictive Analytics? ……………………………………………………………….108
Learning Fit ………………………………………………………………………………………….109
Other Applications for Predictive Analytics ……………………………………………….111
Implementing Predictive Analytics Systems ……………………………………………..111
Data Visualization ………………………………………………………………………………….115
Models ……………………………………………………………………………………………116
Enterprise Tools ……………………………………………………………………………….116
Technology Blogs at Fashion Companies ………………………………………………….117
Data Responsibility ……………………………………………………………………………….118
General Data Protection Regulation …………………………………………………….118
Data and Third-Party Vendors …………………………………………………………….119
Legal ………………………………………………………………………………………………119
Summary …………………………………………………………………………………………….120
Terminology in This Chapter ……………………………………………………………………120
Part IV: Designing …………………………………………………………..123
Chapter 8: Generative Models as Fashion Designers …………………..125
AI Fashion Designer ………………………………………………………………………………125
Artificial Creativity ……………………………………………………………………………126
Mapping Garments onto Images of People …………………………………………..127
Turning Sketches into Color Images ……………………………………………………129
How Generative Models Work …………………………………………………………………129
Limitations ………………………………………………………………………………………131
Why GANs? ……………………………………………………………………………………..131
Implementation Example: AI Fashion Blogger ……………………………………………132
How It Works …………………………………………………………………………………..133
Training GANs ………………………………………………………………………………….134
Improving Results …………………………………………………………………………….136
The Future of GANs ……………………………………………………………………………….137
Summary …………………………………………………………………………………………….137
Terminology from This Chapter ……………………………………………………………….138
Chapter 9: Data Mining and Trend Forecasting …………………………..141
Trend Forecasting …………………………………………………………………………………141
Social Media ………………………………………………………………………………………..142
Social Media Mining …………………………………………………………………………143
What Is Data Mining? …………………………………………………………………………….144
APIs …………………………………………………………………………………………………….145
Web Scraping ………………………………………………………………………………….147
Web Crawlers ………………………………………………………………………………….148
Data Warehousing …………………………………………………………………………………149
Summary …………………………………………………………………………………………….150
Terminology from This Chapter ……………………………………………………………….151
Part V: Supply Chain ……………………………………………………….153
Chapter 10: Deep Learning and Demand Forecasting ………………….155
What Is Demand Forecasting? ………………………………………………………………..156
Forecasting Methods …………………………………………………………………………….156
Fashion’s Challenges in Forecasting ………………………………………………………..157
Overproduction ………………………………………………………………………………..157
Fast and Short Seasons …………………………………………………………………….157
Consumer Behavior ………………………………………………………………………….158
Nonforecasting Solutions ……………………………………………………………………….158
Price Prediction ……………………………………………………………………………….158
Deep Learning ………………………………………………………………………………………159
What Is Deep Learning? ……………………………………………………………………160
Deep Learning for Demand Forecasting ………………………………………………161
Techniques for Smaller Datasets …………………………………………………………….161
Transfer Learning …………………………………………………………………………….162
Other Forecasting Models …………………………………………………………………163
Summary …………………………………………………………………………………………….165
Terminology from This Chapter ……………………………………………………………….166
Chapter 11: Robotics and Manufacturing …………………………………..167
Robots in Popular Culture ………………………………………………………………………167
Robots and Women …………………………………………………………………………..168
What Is a Robot? …………………………………………………………………………………..170
Types of Robots …………………………………………………………………………………….170
Industrial Robots ……………………………………………………………………………..171
Articulated Robots ……………………………………………………………………………171
End Effectors …………………………………………………………………………………..172
Sewing Robots ……………………………………………………………………………………..173
Advantages of Robotics in Sewing ……………………………………………………..175
Designing for Robots ………………………………………………………………………..176
Automation and Robotics ……………………………………………………………………….176
Questions of Responsible Automation …………………………………………………177
Supply-Chain Robotics …………………………………………………………………………..177
Lights-Out Manufacturing …………………………………………………………………178
Summary …………………………………………………………………………………………….178
Terminology from This Chapter ……………………………………………………………….179
Part VI: Future ………………………………………………………………..183
Chapter 12: Democratization and Impacts of AI ………………………….185
Lowering the Barrier to Entry ………………………………………………………………….186
Simplified Interfaces ……………………………………………………………………………..186
Developer Tools ……………………………………………………………………………….187
Access to Data ……………………………………………………………………………………..187
Open Source ………………………………………………………………………………………..188
Specialized Hardware ……………………………………………………………………………189
GPUs and TPUs ………………………………………………………………………………..189
Cloud Services …………………………………………………………………………………190
Tutorials and Online Courses ………………………………………………………………….191
Impact on Jobs …………………………………………………………………………………….191
Ethics and the Future …………………………………………………………………………….192
Race and Gender ……………………………………………………………………………..193
The Partnership on AI ……………………………………………………………………….193
Summary …………………………………………………………………………………………….194
Terminology from This Chapter ……………………………………………………………….194
Bibliography ………………………………………………………………………….197
General References ……………………………………………………………………………….197
Adversarial Examples ……………………………………………………………………………199
Chatbots, Virtual Style Assistants …………………………………………………………….199
Computer Vision, Visual Search ……………………………………………………………….201
Data, Data Mining ………………………………………………………………………………….202
Demand Forecasting ……………………………………………………………………………..202
Ethics ………………………………………………………………………………………………….203
Generative Models ………………………………………………………………………………..203
Natural Language Processing …………………………………………………………………206
Neural Networks …………………………………………………………………………………..207
Predictive Analytics, Recommendation Engines ………………………………………..208
Robotics, Impact …………………………………………………………………………………..210
Specialized Hardware ……………………………………………………………………………210
Projects, Companies ……………………………………………………………………………..211
Index …………………………………………………………………………………….213