From Deep Learning to Rational Machines
Book description
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, 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…
Why read it?
1 author picked From Deep Learning to Rational Machines as one of their favorite books. Why do they recommend it?
Don't be fooled by the lack of a breezy narrative. This read is a dense exploration of deep learning's impact and is certainly not an ‘easy read’ by any measure, but its rewards are substantial.
Buckner delves deep into the philosophical debates surrounding AI, particularly the clash between empiricism and rationalism. Through this lens, he develops a "moderate empiricism" that sheds light on the true potential and limitations of AI. While the book demands focus, we found the payoff to be significant.
From Dean's list on groundbreaking books on the future of AI.
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