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What makes people smarter than computers? The work described in these two volumes suggests that the answer lies in the massively parallel architecture of the human mind. It is some of the most exciting work in cognitive science, unifying neural and cognitive processes in a highly computational framework, with links to artificial intelligence.
Although thought and problem solving have a sequential character when viewed over a time frame of minutes or hours, the authors argue that each step in the sequence is the result of the simultaneous activity of a large number of simple computational elements, each influencing others and being influenced by them. Parallel Distributed Processing describes their work in developing a theoretical framework for describing this parallel distributed processing activity and in applying the framework to the development of models of aspects of perception, memory, language, and thought.
Volume 2 applies to a number of specific issues in cognitive science and neuroscience. Some chapters describe models of aspects of perception, memory, language, and thought. Others discuss the relation between parallel distributed processing models and neurophysiology or describe models that are specifically addressed to neurophysiological data. The book concludes with an epilogue noting the strengths and weaknesses of the approach and directions for the future.
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What makes people smarter than computers? The work described in these two volumes suggests that the answer lies in the massively parallel architecture of the human mind. It is some of the most exciting work in cognitive science, unifying neural and cognitive processes in a highly computational framework, with links to artificial intelligence.
Although thought and problem solving have a sequential character when viewed over a time frame of minutes or hours, the authors argue that each step in the sequence is the result of the simultaneous activity of a large number of simple computational elements, each influencing others and being influenced by them. Parallel Distributed Processing describes their work in developing a theoretical framework for describing this parallel distributed processing activity and in applying the framework to the development of models of aspects of perception, memory, language, and thought.
Volume 2 applies to a number of specific issues in cognitive science and neuroscience. Some chapters describe models of aspects of perception, memory, language, and thought. Others discuss the relation between parallel distributed processing models and neurophysiology or describe models that are specifically addressed to neurophysiological data. The book concludes with an epilogue noting the strengths and weaknesses of the approach and directions for the future.