Introduction 1
About This Book 2
Icons Used in This Book 3
Beyond the Book 3
Where to Go from Here 4
Part 1: Introducing AI 5
Chapter 1: Introducing AI 7
Defining the Term AI 7
Discerning intelligence 8
Discovering four ways to define AI 12
Understanding the History of AI 14
Starting with symbolic logic at Dartmouth 15
Continuing with expert systems 16
Overcoming the AI winters 16
Considering AI Uses 17
Avoiding AI Hype 18
Connecting AI to the Underlying Computer 19
Chapter 2: Defining the Role of Data 21
Finding Data Ubiquitous in This Age 22
Understanding Moore’s implications 23
Using data everywhere 24
Putting algorithms into action 25
Using Data Successfully 27
Considering the data sources 27
Obtaining reliable data 28
Making human input more reliable 28
Using automated data collection 30
Manicuring the Data 30
Dealing with missing data 31
Considering data misalignments 32
Separating useful data from other data 32
Considering the Five Mistruths in Data 33
Commission 33
Omission 34
Perspective 34
Bias 35
Frame of reference 36
Defining the Limits of Data Acquisition 37
Chapter 3: Considering the Use of Algorithms 39
Understanding the Role of Algorithms 40
Understanding what algorithm means 40
Starting from planning and branching 41
Playing adversarial games 44
Using local search and heuristics 46
Discovering the Learning Machine 49
Leveraging expert systems 50
Introducing machine learning 52
Touching new heights 53
Chapter 4: Pioneering Specialized Hardware 55
Relying on Standard Hardware 56
Understanding the standard hardware 56
Describing standard hardware deficiencies 57
Using GPUs 59
Considering the Von Neumann bottleneck 60
Defining the GPU 61
Considering why GPUs work well 62
Creating a Specialized Processing Environment 62
Increasing Hardware Capabilities 63
Adding Specialized Sensors 64
Devising Methods to Interact with the Environment 65
Part 2: Considering the Uses of AI in Society 67
Chapter 5: Seeing AI Uses in Computer Applications 69
Introducing Common Application Types 70
Using AI in typical applications 70
Realizing AI‘s wide range of fields 71
Considering the Chinese Room argument 72
Seeing How AI Makes Applications Friendlier 73
Performing Corrections Automatically 74
Considering the kinds of corrections 74
Seeing the benefits of automatic corrections 75
Understanding why automated corrections don’t work 75
Making Suggestions 76
Getting suggestions based on past actions 76
Getting suggestions based on groups 77
Obtaining the wrong suggestions 77
Considering AI-based Errors 78
Chapter 6: Automating Common Processes 81
Developing Solutions for Boredom 82
Making tasks more interesting 82
Helping humans work more efficiently 83
Understanding how AI reduces boredom 84
Considering how AI can’t reduce boredom 84
Working in Industrial Settings 85
Developing various levels of automation 85
Using more than just robots 86
Relying on automation alone 87
Creating a Safe Environment 88
Considering the role of boredom in accidents 88
Seeing AI in avoiding safety issues 88
Understanding that AI can’t eliminate safety issues 89
Chapter 7: Using AI to Address Medical Needs 91
Implementing Portable Patient Monitoring 92
Wearing helpful monitors 92
Relying on critical wearable monitors 93
Using movable monitors 94
Making Humans More Capable 95
Using games for therapy 95
Considering the use of exoskeletons 97
Addressing Special Needs 99
Considering the software-based solutions 100
Relying on hardware augmentation 100
Seeing AI in prosthetics 101
Completing Analysis in New Ways 101
Devising New Surgical Techniques 102
Making surgical suggestions 102
Assisting a surgeon 103
Replacing the surgeon with monitoring 104
Performing Tasks Using Automation 105
Working with medical records 105
Predicting the future 106
Making procedures safer 106
Creating better medications 107
Combining Robots and Medical Professionals 108
Chapter 8: Relying on AI to Improve Human Interaction 109
Developing New Ways to Communicate 110
Creating new alphabets 111
Automating language translation 111
Incorporating body language 113
Exchanging Ideas 114
Creating connections 114
Augmenting communication 115
Defining trends 115
Using Multimedia 116
Embellishing Human Sensory Perception 117
Shifting data spectrum 117
Augmenting human senses 118
Part 3: Working with Software-Based AI Applications 119
Chapter 9: Performing Data Analysis for AI 121
Defining Data Analysis 122
Understanding why analysis is important 124
Reconsidering the value of data 125
Defining Machine Learning 126
Understanding how machine learning works 127
Understanding the benefits of machine learning 129
Being useful; being mundane 130
Specifying the limits of machine learning 131
Considering How to Learn from Data 132
Supervised learning 133
Unsupervised learning 134
Reinforcement learning 134
Chapter 10: Employing Machine Learning in AI 135
Taking Many Different Roads to Learning 136
Discovering five main approaches to AI learning 136
Delving into the three most promising AI learning approaches 139
Awaiting the next breakthrough 140
Exploring the Truth in Probabilities 140
Determining what probabilities can do 141
Considering prior knowledge 143
Envisioning the world as a graph 146
Growing Trees that Can Classify 150
Predicting outcomes by splitting data 150
Making decisions based on trees 152
Pruning overgrown trees 154
Chapter 11: Improving AI with Deep Learning 155
Shaping Neural Networks Similar to the Human Brain 156
Introducing the neuron 156
Starting with the miraculous perceptron 156
Mimicking the Learning Brain 159
Considering simple neural networks 159
Figuring out the secret is in the weights 160
Understanding the role of backpropagation 161
Introducing Deep Learning 161
Explaining the difference in deep learning 163
Finding even smarter solutions 164
Detecting Edges and Shapes from Images 167
Starting with character recognition 167
Explaining how convolutions work 168
Advancing using image challenges 170
Learning to Imitate Art and Life 171
Memorizing sequences that matter 171
Discovering the magic of AI conversations 172
Making an AI compete against another AI 174
Part 4: Working With AI in Hardware Applications 179
Chapter 12: Developing Robots 181
Defining Robot Roles 182
Overcoming the sci-fi view of robots 183
Knowing why it’s hard to be a humanoid 186
Working with robots 188
Assembling a Basic Robot 191
Considering the components 191
Sensing the world 192
Controlling a robot 193
Chapter 13: Flying with Drones 195
Acknowledging the State of the Art 196
Flying unmanned to missions 196
Meeting the quadcopter 197
Defining Uses for Drones 199
Seeing drones in nonmilitary roles 200
Powering up drones using AI 202
Understanding regulatory issues 205
Chapter 14: Utilizing the AI-Driven Car 207
Getting a Short History 208
Understanding the Future of Mobility 209
Climbing the six levels of autonomy 209
Rethinking the role of cars in our lives 210
Getting into a Self-Driving Car 214
Putting all the tech together 215
Letting AI into the scene 216
Understanding it is not just AI 217
Overcoming Uncertainty of Perceptions 218
Introducing the car’s senses 219
Putting together what you perceive 221
Part 5: Considering the Future of AI 223
Chapter 15: Understanding the Nonstarter Application 225
Using AI Where It Won’t Work 226
Defining the limits of AI 226
Applying AI incorrectly 229
Entering a world of unrealistic expectations 229
Considering the Effects of AI Winters 230
Understanding the AI winter 231
Defining the causes of the AI winter 231
Rebuilding expectations with new goals 233
Creating Solutions in Search of a Problem 234
Defining a gizmo 235
Avoiding the infomercial 235
Understanding when humans do it better 236
Looking for the simple solution 237
Chapter 16: Seeing AI in Space 239
Observing the Universe 240
Seeing clearly for the first time 240
Finding new places to go 241
Considering the evolution of the universe 242
Creating new scientific principles 242
Performing Space Mining 243
Harvesting water 245
Obtaining rare earths and other metals 245
Finding new elements 247
Enhancing communication 247
Exploring New Places 248
Starting with the probe 248
Relying on robotic missions 249
Adding the human element 251
Building Structures in Space 252
Taking your first space vacation 252
Performing scientific investigation 253
Industrializing space 253
Using space for storage 254
Chapter 17: Adding New Human Occupations 255
Living and Working in Space 256
Creating Cities in Hostile Environments 257
Building cities in the ocean 258
Creating space-based habitats 259
Constructing moon-based resources 260
Making Humans More Efficient 261
Fixing Problems on a Planetary Scale 263
Contemplating how the world works 264
Locating potential sources of problems 265
Defining potential solutions 266
Seeing the effects of the solutions 267
Trying again 267
Part 6: The Part of Tens 269
Chapter 18: Ten AI-Safe Occupations 271
Performing Human Interaction 272
Teaching children 272
Nursing 272
Addressing personal needs 273
Solving developmental issues 273
Creating New Things 274
Inventing 274
Being artistic 275
Imagining the unreal 275
Making Intuitive Decisions 276
Investigating crime 276
Monitoring situations in real time 276
Separating fact from fiction 277
Chapter 19: Ten Substantial Contributions of AI to Society 279
Considering Human-Specific Interactions 280
Devising the active human foot 280
Performing constant monitoring 281
Administering medications 281
Developing Industrial Solutions 282
Using AI with 3-D printing 282
Advancing robot technologies 282
Creating New Technology Environments 283
Developing rare new resources 284
Seeing what can’t be seen 284
Working with AI in Space 284
Delivering goods to space stations 284
Mining extraplanetary resources 285
Exploring other planets 286
Chapter 20: Ten Ways in Which AI Has Failed 287
Understanding 288
Interpreting, not analyzing 288
Going beyond pure numbers 289
Considering consequences 290
Discovering 290
Devising new data from old 290
Seeing beyond the patterns 291
Implementing new senses 291
Empathizing 292
Walking in someone’s shoes 292
Developing true relationships 293
Changing perspective 293
Making leaps of faith 293
Index 295
John Paul Mueller has written 108 books and over 600 articles on topics ranging from artificial intelligence to networking to database management. He's also a technical editor and consultant. Luca Massaronis a data scientist and marketing research director specializing in multivariate statistical analysis, machine learning, and customer insight.
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