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The Allure of Machinic LifeCybernetics, Artificial Life, and the New AI$
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John Johnston

Print publication date: 2008

Print ISBN-13: 9780262101264

Published to MIT Press Scholarship Online: August 2013

DOI: 10.7551/mitpress/9780262101264.001.0001

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Learning from Neuroscience: New Prospects for Building Intelligent Machines

Learning from Neuroscience: New Prospects for Building Intelligent Machines

Chapter:
(p.385) 8 Learning from Neuroscience: New Prospects for Building Intelligent Machines
Source:
The Allure of Machinic Life
Author(s):

John Johnston

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262101264.003.0009

This chapter discusses why further success in the building of intelligent machines will most likely be tied to progress in understanding how the human brain actually works. It argues that the bottom-up view of neuroscience and the top-down view of classic artificial intelligence (AI) do not meet in the middle, where all the interesting behavior—perception, complex movement, and a basic ability to cope with the environment—seems to lie. It describes three current research initiatives that operate in or are moving toward this middle realm. The first (Eric Baum) serves as a transition from classic AI and cognitive science. The second (Jeff Hawkins) plunges us into a theory of the brain as a memory prediction machine. The third (Steve Grand) involves the actual building of a working baby android. The chapter concludes by considering some recent research in self-modeling and communication.

Keywords:   artificial intelligence, cognitive science, brain, memory prediction, baby android, self-modeling, communication

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