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Forget far-away dreams of the future. Artificial intelligence is here now!
Every time you use a smart device or some sort of slick technology—be it a smartwatch, smart speaker, security alarm, or even customer service chat box—you’re engaging with artificial intelligence (AI). If you’re curious about how AI is developed—or question whether AI is real—Artificial Intelligence For Dummies holds the answers you’re looking for. Starting with a basic definition of AI and explanations of data use, algorithms, special hardware, and more, this reference simplifies this complex topic for anyone who wants to understand what operates the devices we can’t live without.
This book will help you:
Almost 80 percent of the devices you interact with every day depend on some sort of AI. And although you don’t need to understand AI to operate your smart speaker or interact with a bot, you’ll feel a little smarter—dare we say more intelligent—when you know what’s going on behind the scenes. So don’t wait. Pick up this popular guide to unlock the secrets of AI today!
John Mueller has produced hundreds of books and articles on topics ranging from networking to home security and from database management to heads-down programming. If he had a nickel for every time he is asked the question, “Is the terminator real?” (No!), he could have retired years ago.
Luca Massaron is a data scientist who specializes in organizing and interpreting big data and turning it into smart data. He has over 20 years??? experience delivering data solutions to clients in a variety of industries.
Introduction 1
About This Book 2
Icons Used in This Book 3
Beyond the Book 4
Where to Go from Here 5
PART 1: INTRODUCING AI 7
Chapter 1: Introducing AI 9
Defining the Term AI 10
Discerning intelligence 10
Discovering four ways to define AI 11
Understanding the History of AI 17
Starting with symbolic logic at Dartmouth 17
Continuing with expert systems 18
Overcoming the AI winters 19
Considering AI Uses 20
Avoiding AI Hype and Overestimation 21
Defining the five tribes and the master algorithm 21
Considering sources of hype 22
Understanding user overestimation 23
Connecting AI to the Underlying Computer 23
Chapter 2: Defining the Role of Data 25
Finding Data Ubiquitous in This Age 26
Understanding Moore’s implications 27
Using data everywhere 28
Putting algorithms into action 30
Using Data Successfully 32
Considering the data sources 32
Obtaining reliable data 33
Making human input more reliable 33
Using automated data collection 35
Collecting personal data ethically 35
Manicuring the Data 37
Dealing with missing data 37
Considering data misalignments 38
Separating useful data from other data 39
Considering the Five Mistruths in Data 39
Commission 40
Omission 40
Perspective 41
Bias 42
Frame of reference 43
Defining the Limits of Data Acquisition 43
Considering Data Security Issues 45
Understanding purposefully biased data 45
Dealing with data-source corruption 47
Cancelling botnets with sinkholing 48
Chapter 3: Considering the Use of Algorithms 49
Understanding the Role of Algorithms 50
Understanding what algorithm means 50
Planning and branching: Trees and nodes 52
Extending the tree using graph nodes 53
Traversing the graph 54
Playing adversarial games 56
Using local search and heuristics 57
Discovering the Learning Machine 60
Leveraging expert systems 61
Introducing machine learning 64
Touching new heights 64
Chapter 4: Pioneering Specialized Hardware 67
Relying on Standard Hardware 68
Understanding the standard hardware 68
Describing standard hardware deficiencies 69
Relying on new computational techniques 71
Using GPUs 73
Considering the von Neumann bottleneck 73
Defining the GPU 74
Considering why GPUs work well 75
Working with Deep Learning Processors (DLPs) 76
Defining the DLP 76
Using the mobile Neural Processing Unit (NPU) 77
Accessing the cloud-based Tenser Processing Unit (TPU) 78
Creating a Specialized Processing Environment 78
Increasing Hardware Capabilities 79
Adding Specialized Sensors 80
Devising Methods to Interact with the Environment 81
PART 2: CONSIDERING THE USES OF AI IN SOCIETY 83
Chapter 5: Seeing AI Uses in Computer Applications 85
Introducing Common Application Types 86
Using AI in typical applications 86
Realizing AI’s wide range of fields 88
Considering the Chinese Room argument 88
Seeing How AI Makes Applications Friendlier 89
Performing Corrections Automatically 91
Considering the kinds of corrections 91
Seeing the benefits of automatic corrections 92
Understanding why automated corrections don’t work 92
Making Suggestions 93
Getting suggestions based on past actions 93
Getting suggestions based on groups 93
Obtaining the wrong suggestions 94
Considering AI-based Errors 95
Chapter 6: Automating Common Processes 97
Developing Solutions for Boredom 98
Making tasks more interesting 98
Helping humans work more efficiently 99
Understanding how AI reduces boredom 100
Considering how AI can’t reduce boredom 101
Working in Industrial Settings 101
Developing various levels of automation 102
Using more than just robots 103
Relying on automation alone 104
Creating a Safe Environment 104
Considering the role of boredom in accidents 104
Using AI to avoid safety issues 105
Understanding that AI can’t eliminate safety issues 105
Chapter 7: Using AI to Address Medical Needs 107
Implementing Portable Patient Monitoring 108
Wearing helpful monitors 109
Relying on critical wearable monitors 109
Using movable monitors 110
Making Humans More Capable 111
Using games for therapy 111
Considering the use of exoskeletons 113
Addressing a Range of Physical Abilities 114
Considering the software-based solutions 115
Relying on hardware augmentation 116
Seeing AI in prosthetics 116
Completing Analysis in New Ways 117
Relying on Telepresence 118
Defining telepresence 118
Considering examples of telepresence 118
Understanding telepresence limitations 119
Devising New Surgical Techniques 120
Making surgical suggestions 120
Assisting a surgeon 121
Replacing the surgeon with monitoring 122
Performing Tasks Using Automation 122
Working with medical records 123
Predicting the future 123
Making procedures safer 124
Creating better medications 124
Combining Robots and Medical Professionals 125
Chapter 8: Relying on AI to Improve Human Interaction 127
Developing New Ways to Communicate 128
Creating new alphabets 129
Working with emoji and other meaningful graphics 129
Automating language translation 130
Incorporating body language .131
Exchanging Ideas 133
Creating connections 133
Augmenting communication 133
Defining trends 134
Using Multimedia 134
Embellishing Human Sensory Perception 135
Shifting data spectrum 135
Augmenting human senses 136
PART 3: WORKING WITH SOFTWARE-BASED AI APPLICATIONS 139
Chapter 9: Performing Data Analysis for AI 141
Defining Data Analysis 142
Understanding why analysis is important 144
Reconsidering the value of data 145
Defining Machine Learning 147
Understanding how machine learning works 148
Understanding the benefits of machine learning 149
Being useful; being mundane 150
Specifying the limits of machine learning 150
Considering How to Learn from Data 152
Supervised learning 153
Unsupervised learning 154
Reinforcement learning 154
Chapter 10: Employing Machine Learning in AI 155
Taking Many Different Roads to Learning 156
Discovering five main approaches to AI learning 156
Delving into the three most promising AI learning approaches 159
Awaiting the next breakthrough 160
Exploring the Truth in Probabilities 160
Determining what probabilities can do 162
Considering prior knowledge 163
Envisioning the world as a graph 166
Growing Trees that Can Classify 170
Predicting outcomes by splitting data 170
Making decisions based on trees 172
Pruning overgrown trees 174
Chapter 11: Improving AI with Deep Learning 175
Shaping Neural Networks Similar to the Human Brain 176
Introducing the neuron 176
Starting with the miraculous perceptron 176
Mimicking the Learning Brain 179
Considering simple neural networks 179
Figuring out the secret is in the weights 180
Understanding the role of backpropagation 182
Introducing Deep Learning 182
Explaining the differences between deep learning and other forms of neural networks 185
Finding even smarter solutions 186
Detecting Edges and Shapes from Images 188
Starting with character recognition 189
Explaining how convolutions work 190
Advancing using image challenges 191
Learning to Imitate Art and Life .193
Memorizing sequences that matter 193
Discovering the magic of AI conversations 194
Going for the state of the pretrained art 196
Making one AI compete against another AI 198
Pondering reinforcement learning 201
PART 4: WORKING WITH AI IN HARDWARE APPLICATIONS 207
Chapter 12: Developing Robots 209
Defining Robot Roles 210
Overcoming the sci-fi view of robots 211
Being humanoid can be hard 214
Working with robots 217
Assembling a Basic Robot 220
Considering the components 220
Sensing the world 221
Controlling a robot 222
Chapter 13: Flying with Drones 223
Acknowledging the State of the Art 224
Flying unmanned to missions 224
Meeting the quadcopter 226
Defining Uses for Drones 227
Seeing drones in nonmilitary roles 229
Powering up drones using AI 233
Understanding regulatory issues 234
Chapter 14: Utilizing the AI-Driven Car 237
Getting a Short History 238
Understanding the Future of Mobility 239
Climbing the six levels of autonomy 239
Rethinking the role of cars in our lives 241
Taking a step back from unmet expectations 244
Getting into a Self-Driving Car 246
Putting all the tech together 247
Letting AI into the scene 249
Understanding that it’s not just AI 249
Overcoming Uncertainty of Perceptions 251
Introducing the car’s senses 252
Putting together what you perceive 254
PART 5: CONSIDERING THE FUTURE OF AI 257
Chapter 15: Understanding the Nonstarter Application 259
Using AI Where It Won’t Work 260
Defining the limits of AI 260
Applying AI incorrectly 263
Entering a world of unrealistic expectations 264
Considering the Effects of AI Winters 265
Understanding the AI winter 265
Defining the causes of the AI winter 265
Rebuilding expectations with new goals 267
Creating Solutions in Search of a Problem 269
Defining a gizmo 269
Avoiding the infomercial 270
Understanding when humans do it better 271
Looking for the simple solution 272
Chapter 16: Seeing AI in Space 273
Observing the Universe 274
Seeing clearly for the first time 274
Finding new places to go 275
Considering the evolution of the universe 276
Creating new scientific principles 276
Performing Space Mining 277
Harvesting water 277
Obtaining rare earths and other metals 278
Finding new elements 279
Enhancing communication 280
Exploring New Places 280
Starting with the probe 281
Relying on robotic missions 282
Adding the human element 283
Building Structures in Space 284
Taking your first space vacation 285
Performing scientific investigation 285
Industrializing space 286
Using space for storage 286
Chapter 17: Engaging in Human Endeavors 287
Keeping Human Beings Popular 288
Living and Working in Space 289
Creating Cities in Hostile Environments 290
Building cities in the ocean 290
Creating space-based habitats 291
Constructing moon-based resources 293
Making Humans More Efficient 294
Fixing Problems on a Planetary Scale 296
Contemplating how the world works 296
Locating potential sources of problems 297
Defining potential solutions 298
Seeing the effects of the solutions 299
Trying again 299
PART 6: THE PART OF TENS 301
Chapter 18: Ten Occupational Categories that AI Can’t Replace 303
Performing Human Interaction 304
Teaching children 304
Nursing 304
Addressing personal needs 305
Solving developmental issues 305
Creating New Things 306
Inventing 306
Being artistic 307
Imagining the unreal 307
Making Intuitive Decisions 308
Investigating crime 308
Monitoring situations in real time 308
Separating fact from fiction 309
Chapter 19: Ten Substantial Contributions of AI to Society 311
Considering Human-Specific Interactions 312
Devising the active human foot 312
Performing constant monitoring 313
Administering medications 313
Developing Industrial Solutions 314
Using AI with 3-D printing 314
Advancing robot technologies 314
Creating New Technology Environments 315
Developing rare new resources 315
Seeing what can’t be seen 316
Working with AI in Space 316
Delivering goods to space stations 316
Mining extraplanetary resources 317
Exploring other planets 318
Chapter 20: Ten Ways in Which AI Has Failed 319
Understanding 320
Interpreting, not analyzing 321
Going beyond pure numbers 321
Considering consequences 322
Discovering 322
Devising new data from old 323
Seeing beyond the patterns 323
Implementing new senses 324
Empathizing 324
Walking in someone’s shoes 325
Developing true relationships 325
Changing perspective 326
Making leaps of faith 326
Index 327
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