Overview
- Presents unique perspectives on ideas in deep learning and artificial intelligence, and their historical and philosophical roots
- Offers an introduction to cognitive aspects of deep learning, including those which are not tackled by existing deep learning applications but currently exist only as ideas
- Highlights the roots of deep learning in philosophical and psychological concepts, which may also have a substantial impact on future developments in the field
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Table of contents (12 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this exciting field, including the pioneering work of Rudolf Carnap, Warren McCulloch, Walter Pitts, Bulcsú László, and Geoffrey Hinton.
Topics and features:
- Provides a brief history of mathematical logic, and discusses the critical role of philosophy, psychology, and neuroscience in the history of AI
- Presents a philosophical case for the use of fuzzy logic approaches in AI
- Investigates the similarities and differences between the Word2vec word embedding algorithm, and the ideas of Wittgenstein and Firth on linguistics
- Examines how developments in machine learning provide insights into the philosophical challenge of justifying inductive inferences
- Debates, with reference to philosophical anthropology, whether an advanced general artificial intelligence might be considered as a living being
- Investigates the issue of computational complexity through deep-learning strategies for understanding AI-complete problems and developing strong AI
- Explores philosophical questions at the intersection of AI and transhumanism
This inspirational volume will rekindle a passion for deep learning in those already experienced in coding and studying this discipline, and provide a philosophical big-picture perspective for those new to the field.
Editors and Affiliations
About the editor
Bibliographic Information
Book Title: Guide to Deep Learning Basics
Book Subtitle: Logical, Historical and Philosophical Perspectives
Editors: Sandro Skansi
DOI: https://doi.org/10.1007/978-3-030-37591-1
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-37590-4Published: 24 January 2020
Softcover ISBN: 978-3-030-37593-5Published: 24 January 2021
eBook ISBN: 978-3-030-37591-1Published: 23 January 2020
Edition Number: 1
Number of Pages: VIII, 140
Number of Illustrations: 8 b/w illustrations, 4 illustrations in colour
Topics: Machine Learning, Computational Intelligence, Philosophy of Technology, History of Computing