Artificial Intelligence For Dummies

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: 

• Separate the reality of artificial intelligence from the hype 
• Know what artificial intelligence can accomplish and what its limits are 
• Understand how AI speeds up data gathering and analysis to help you make informed decisions more quickly 
• See how AI is being used in hardware applications like drones, robots, and vehicles 
• Know where AI could be used in space, medicine, and communication fields sooner than you think 

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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