Guide to Deep Learning Basics: Logical, Historical and Philosophical Perspectives 1st ed. 2020 Edition [NulledPremium]
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- LanguageEnglish
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Book details
File Size: 2.50 MB
Format: pdf
Print Length: 140 pages
Publisher: Springer; 1st ed. 2020 edition (January 23, 2020)
Publication Date: January 23, 2020
Sold by: Amazon.com Services LLC
Language: English
ASIN: B0846GYCDD
Benefits:
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
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.
Table of contents (12 chapters)
Mathematical Logic: Mathematics of Logic or Logic of Mathematics
The McCulloch–Pitts Paper from the Perspective of Mathematical Logic
From the Linguistic Turn to the Cognitive Turn and Back Again
Why Not Fuzzy Logic?
Meaning as Use: From Wittgenstein to Google’s Word2vec
Rudolf Carnap–The Grandfather of Artificial Neural Networks: The Influence of Carnap’s Philosophy on Walter Pitts
A Lost Croatian Cybernetic Machine Translation Program
The Architectures of Geoffrey Hinton
Machine Learning and the Philosophical Problems of Induction
The Artificial Intelligence Singularity: What It Is and What It Is Not
AI-Completeness: Using Deep Learning to Eliminate the Human Factor
Transhumanism and Artificial Intelligence: Philosophical
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