From Deep Learning to Rational Machines (Oxford University Press)
Friday, 29 December 2023

Subtitled "What the History of Philosophy Can Teach Us about the Future of Artificial Intelligence", this book provides a framework for thinking about foundational philosophical questions surrounding the use of deep artificial neural networks ("deep learning") to achieve artificial intelligence. Specifically, Cameron J. Buckner  links recent breakthroughs to classic works in empiricist philosophy of mind 

<ASIN:0197653308 >

This book explains how recent deep learning breakthroughs realized some of the most ambitious ideas about these faculties from philosophers such as Aristotle, Ibn Sina (Avicenna), John Locke, David Hume, William James, and Sophie de Grouchy. It illustrates the utility of this interdisciplinary connection by showing how it can provide benefits to both philosophy and computer science.

Author: Cameron J. Buckner
Publisher: Oxford University Press
Date: December 2023
Pages: 440
ISBN: 978-0197653302
Print: 0197653308
Kindle: B0CL9JBSD8
Audience: General
Level: Introductory/Intermediate
Category: Artificial Intelligence

For recommended titles on AI see  AI Books To Inspire You in our Programmer's Bookshelf section.

 

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Learn to Code by Solving Problems

Author: Dr. Daniel Zingaro
Publisher: No Starch Press
Date: June 2021
Pages: 335
ISBN: 978-1718501324
Print: 1718501323
Kindle: B08FH92YL8
Audience: People wanting to learn Python
Rating: 4
Reviewer: Mike James
Solving problems - sounds good?



Embracing Modern C++ Safely

Author: Dr. John Lakos, Vittorio Romeo, Dr. Rostislav Khlebnikov and  Alisdair Meredith
Publisher: Addison-Wesley
Date: December 2021
Pages: 1376
ISBN: 978-0137380350
Print: 0137380356
Kindle: B09HTFQB92
Audience: C++ developers
Rating: 4
Reviewer: Harry Fairhead
Writing safe C++ - sounds essential

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