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Artificial Intelligence For Dummies

Buch | Softcover
336 Seiten
2018
John Wiley & Sons Inc (Verlag)
978-1-119-46765-6 (ISBN)
29,21 inkl. MwSt
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Step into the future with AI

The term "Artificial Intelligence" has been around since the 1950s, but a lot has changed since then. Today, AI is referenced in the news, books, movies, and TV shows, and the exact definition is often misinterpreted. Artificial Intelligence For Dummies provides a clear introduction to AI and how it’s being used today.

Inside, you’ll get a clear overview of the technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field.



Learn about what AI has contributed to society
Explore uses for AI in computer applications
Discover the limits of what AI can do
Find out about the history of AI

The world of AI is fascinating—and this hands-on guide makes it more accessible than ever!

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.

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

Erscheinungsdatum
Verlagsort New York
Sprache englisch
Maße 187 x 234 mm
Gewicht 614 g
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Naturwissenschaften
ISBN-10 1-119-46765-9 / 1119467659
ISBN-13 978-1-119-46765-6 / 9781119467656
Zustand Neuware
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