Dennett's Real Patterns in Science and Nature
Language: English
Published by MIT Press Ltd Mär 2026, 2026
- Softcover
- New
Seller: Wegmann1855, Zwiesel, GermanyWegmann1855
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Neuware -How the concept of a pattern, as understood in information science and applied in contemporary AI, can address deep questions in science and philosophy.The explosive growth of AI and machine learning in recent decades is predicated on the recognition and exploitation of patterns in data. Of course, scientists have engaged in their ownless automatedprocesses of pattern recognition since the birth of science itself, and biological organisms evolved their own neural networks for pattern recognition long before people and their technology came along.In his seminal work, "Real Patterns," philosopher and cognitive scientist Daniel Dennett laid out a road map for connecting the idea of "patterns" as understood by information theory to the practices of scientists and to our own cognitive capacity to model and predict the world around us. In this bookthe first dedicated to the topic of real patternsTyler Millhouse, Steve Petersen, and Don Ross follow this road map. They explore the relevance of patterns to important aspects of both science and nature, including the emergence of high-level structure in physics, the nature of biological species, the measurement of welfare in economics, the evaluation of causal models, and the possibility of understanding in large neural networks.…
Seller Inventory # 9780262052030
- Title
- Dennett's Real Patterns in Science and Nature
- Author
- Tyler Millhouse
- Publisher
- MIT Press Ltd Mär 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0262052032
- ISBN 13
- 9780262052030
- Item weight
- 378 grams
- Dimensions
- 224x150x24 mm
The explosive growth of AI and machine learning in recent decades is predicated on the recognition and exploitation of patterns in data. Of course, scientists have engaged in their own—less automated—processes of pattern recognition since the birth of science itself, and biological organisms evolved their own neural networks for pattern recognition long before people and their technology came along.
In his seminal work, “Real Patterns,” philosopher and cognitive scientist Daniel Dennett laid out a roadmap for connecting the idea of “patterns” as understood by information theory to the practices of scientists and to our own cognitive capacity to model and predict the world around us. In this book—the first dedicated to the topic of real patterns—Tyler Millhouse, Steve Petersen, and Don Ross follow this roadmap. They explore the relevance of patterns to important aspects of both science and nature, including the emergence of high-level structure in physics; the nature of biological species; the measurement of welfare in economics; the evaluation of causal models; and the possibility of understanding in large neural networks.
"Synopsis" may belong to another edition of this title.
About the Author
Steve Petersen is Professor of Philosophy at Niagara University. His work has appeared in journals like Philosophical Studies and Synthese, and in collections like The Ethics of Artificial Intelligence. He has been supported by the Survival and Flourishing Fund, the Center for Effective Altruism's Long-Term Future Fund, the Future of Life Institute, and the Center for AI Safety.
Don Ross is Professor in the School of Society, Politics, and Ethics at University College Cork, Ireland; Professor in the School of Economics at the University of Cape Town, South Africa; and Program Director for Methodology at the Center for the Economic Analysis of Risk, Robinson College of Business, Georgia State University, Atlanta. He is an author or editor of 20 books, including Every Thing Must Go (with James Ladyman) and most recently The Gambling Animal (with Glenn Harrison).
"About the title" may belong to another edition of this title.
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