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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 communi