The Deep Learning Revolution
eBook - ePub

The Deep Learning Revolution

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

The Deep Learning Revolution

About this book

The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.

Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

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Yes, you can access The Deep Learning Revolution by Terrence J. Sejnowski in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Vision & Pattern Recognition. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Title page
  3. Copyright page
  4. Dedication
  5. Table of Contents
  6. Preface
  7. Iā€ƒIntelligence Reimagined
  8. IIā€ƒMany Ways to Learn
  9. IIIā€ƒTechnological and Scientific Impact
  10. Acknowledgments
  11. Recommended Reading
  12. Glossary
  13. Index