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      Artificial Intuition : The Improbable Deep Learning Revolution

      I challenge you to find a field as interesting and exciting as Deep Learning. This book is a spin-off from my previous book "The Deep Learning AI Playbook". The Playbook was meant for a professional audience. This is targeted to a much wider audience. There are two kinds of audiences, those looking to explore and those looking to optimize. There are two ways to learn, learning by exploration and learning by exploitation. This book is about exploration into the emerging field of Deep Learning. It's more like a popular science book and less of a business book. It's not going to provide any practical advice of how to use or deploy Deep Learning. However, it's a book that will explore this new field in many more perspectives. So at the very least, you’ll walk away with the ability  to hold a very informative and impressive conversation about this unique subject.

      It's my hope that having less constraints on what I can express can lead to a more insightful and novel book. There are plenty of ideas that are either too general or too speculative to fit within a business oriented book. With a business book, you always want to manage expectations.  Artificial Intelligence is one of those topics that you want to keep speaking in a conservative manner.  That's one reason I felt the need for this book. Perhaps the freedom to be more liberal can give readers more ideas as where this field is heading. Also, it's not just business that needs to understand Deep Learning. We are all going to be profoundly impacted by this new kind of Artificial Intelligence and it is critical we all develop at least a good intuition of how it will change the world.The images in the front cover are all generated using Deep Learning technology.

      The images on the cover of the book are generated by Deep Learning automation. 

      Preface 12

      1 Introduction 14

      A New Kind of Artificial Intelligence 16

      What is Deep Learning? 20

      Explaining to a Five Year Old 23

      Tribes of Artificial Intelligence 24

      The Deep Learning Industrial Complex 31

      Heart Throbbing Hardware 36

      The Sputnik Moment in Asia 40

      2 Deep Learning is Eating the World 44

      Self Driving Machines 44

      Artistic Machines 47

      The Uncanny Valley 49

      Reading Human Minds 51

      Machines that Teach 54

      Summary 55

      3 Our Cognitive Stack 59

      Variety of Human Intelligences 60

      Learning using Intuition 64

      Natural Stupidity 71

      Hacking Intuition 74

      Human Legacy Bias 77

      4 Artificial Intuition 82

      Limits of Rationality 83

      Artificial Intuition 86

      Characteristics of Artificial Intuition 93

      Growing Innate Intuition 97

      Intuition Demolishes Logic 101

      5 Uncertain Reality 105

      Unknowable Knowns 106

      Probability and Causality 108

      Cargo Cult Science and Alchemy 116

      Exploitation, Exploration and Representation 124

      A Roadmap for Deep Learning 129

      Meta Model 134

      Stochastic Gradient Descent 138

      A Reality Checklist 145

      Deep Learning Limitations 147

      Artificial General Intelligence 153

      6 The Learning Universe 156

      Alien Intelligences in Our Midst 157

      Biological Brains are Digital 160

      The Holographic Principle 163

      Imaginary Numbers 169

      Non-Equilibrium Information Dynamics 175

      Chaos and Entanglement 183

      Deconstructing Complexity 188

      Sand Piles 194

      The Origins of Life and Learning 197

      7 Capitalism in the Age of Intelligence 203

      Disruption with Learning Platforms 204

      Architectures of Participation 209

      Levels of Automation 212

      The Responsive Corporation 215

      8 Knowledge Creation 219

      Accelerated Productivity 220

      The Agile Manifesto 223

      Pattern Languages 227

      Alchemy and Black Magic 232

      Data is the new Vineyard 234

      Humans in the Loop 235

      9 Contextual Adaptation 240

      Biologically Inspired Architecture 241

      Generalization 243

      Deep Teaching 247

      Three Dimensions of Cognition 250

      The Spectrum of Embodied Learning 256

      10 Conversational Cognition 262

      Coordinating Rationality and Intuition 265

      Learning to Communicate 270

      The Many Body Problem 274

      Explainability 277

      AlphaGo Zero’s Self-Learning 279

      Architectures of Collaboration 287

      Machine Self-Awareness 293

      The Strange Loop 298

      11 Human Compatible AI 304

      Jobs that are Safe 305

      Temporal Impedance Mismatch 311

      Decisions and Responsibility 312

      AI Regulation 314

      Seven Deadly Sins 317

      Provably Beneficial AI 321

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