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Guide to Deep Learning Basics = Logi...
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Guide to Deep Learning Basics = Logical, Historical and Philosophical Perspectives /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Guide to Deep Learning Basics/ edited by Sandro Skansi.
其他題名:
Logical, Historical and Philosophical Perspectives /
其他作者:
Skansi, Sandro.
面頁冊數:
VIII, 140 p. 12 illus., 4 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
History of Computing. -
電子資源:
https://doi.org/10.1007/978-3-030-37591-1
ISBN:
9783030375911
Guide to Deep Learning Basics = Logical, Historical and Philosophical Perspectives /
Guide to Deep Learning Basics
Logical, Historical and Philosophical Perspectives /[electronic resource] :edited by Sandro Skansi. - 1st ed. 2020. - VIII, 140 p. 12 illus., 4 illus. in color.online resource.
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 Architecture 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 Aspects.
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. Dr. Sandro Skansi is an Assistant Professor of Logic at the University of Zagreb, Croatia.
ISBN: 9783030375911
Standard No.: 10.1007/978-3-030-37591-1doiSubjects--Topical Terms:
669953
History of Computing.
LC Class. No.: Q325.5-.7
Dewey Class. No.: 006.31
Guide to Deep Learning Basics = Logical, Historical and Philosophical Perspectives /
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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 Architecture 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 Aspects.
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