❤pdf From Deep Learning to Rational Machines: What the History of Philosophy Can Teach Us about

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BESTSELLER
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From Deep Learning to Rational Machines What the
History of Philosophy Can Teach Us about the
Future of Artificial Intelligence
Sinopsis
This book provides a framework for thinking about
foundational philosophical questions surrounding
the use of deep artificial neural networks
(quotdee learningquot to achieve artificial
intelligence. Specifically, it links recent
breakthroughs to classic works in empiricist
philosophy of mind. In recent assessments of deep
learning's potential, scientists have cited
historical figures from the philosophical debate
between nativism and empiricism, which concerns
the origins of abstract knowledge. These
empiricists were faculty psychologists that is,
they argued that the extraction of abstract
knowledge from experience involves the active
engagement of psychological faculties such as
perception, memory, imagination, attention, and
empathy. 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 computer
scientists can continue to mine the history of
philosophy for ideas and aspirational targets to
hit, and philosophers can see how some of the
historical empiricists' most ambitious
speculations can now be realized in specific
computational systems.
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Bestselling new book releases
From Deep Learning to Rational Machines What the
History of Philosophy Can Teach Us about the
Future of Artificial Intelligence
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From Deep Learning to Rational Machines What the
History of Philosophy Can Teach Us about the
Future of Artificial Intelligence