This chapter presents the case that quantum mechanical machines will be needed for AI (artificial intelligence) to match biological intelligence. We begin with an overview of quantum mechanics and describe some of its paradoxes related to nonlocality and instantaneous reduction of the wave function. The case is made that the nonlocality of quantum mechanics and the probabilistic state reduction upon measurement make the theory noncomputable in the classical sense. Some parallels between quantum processing and the workings of the human mind are sketched. Biological systems at the physical level as well as the brain are characterized by reorganization in response to stimulus, which is clearly seen in the changing of the strength of interconnection between neurons, indicating that biological learning is very different from classical machine learning. But reorganization by itself cannot be the reason behind the power of biological intelligence, and therefore we examine the recently proposed quantum computing models for their computing power. We provide an overview of their functioning and we also critique them from the point of view of their realizability. We argue that practical quantum machines will have to be conceived differently from those presently being researched.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
B. Berger and T. Leighton. Protein folding in the hydrophilic-hydrophobic (HP) model is NP-complete. Journal of Computational Biology, 5(1):27-40,1998.
D. Bohm. Holeness and the Implicate Order. W. Routledge & Kegan Paul, London, 1980.
L. Deecke, B. Grötzinger, and H.H. Kornhuber. Voluntary finger movements in man: cerebral potentials and theory. Biological Cybernetics, 23:99-110, 1976.
R.P. Feynman. QED: The Strange Theory of Light and Matter. Princeton University Press, Princeton, NY, 1988.
M.S. Gazzaniga, editor. The Cognitive Neurosciences. The MIT Press, Cambridge, MA, 1995.
R.J. Herrnstein. Riddles of natural categorization. Philosophical Transactions of the Royal Society of London, B, 308:129-144, 1985.
S. Kak. The three languages of the brain: quantum, reorganizational, and associative. In K. Pribram and J. King, editors, Learning as Self-Organization, pages 185-219. Lawrence Erlbaum Associates, Mahwah, NJ, 1996.
S. Kak. Quantum information in a distributed apparatus. Foundations of Physics, 28:1005-1012, 1998.
S. Kak. The initialization problem in quantum computing. Foundations of Physics, 29:267-279, 1999.
S. Kak. Active agents, intelligence, and quantum computing. Information Sciences, 128:1-17, 2000.
S. Kak. Statistical constraints on state preparation for a quantum computer. Pramana, 57:683-688, 2001.
S. Kak. General qubit errors cannot be corrected. Information Sciences, 152:195-202, 2003.
S. Kak. The Architecture of Knowledge: Quantum Mechanics, Neuroscience, Computers, and Consciousness. CSC, Delhi, 2004.
S. Kak. Information complexity of quantum gates. International Journal of Theoretical Physics, 45:933-941, 2006.
S. Kak. On the realizability of quantum computers. ACM Ubiquity, 7(11):1-9, 2006.
S. Kak. Quantum information and entropy. International Journal of The-oretical Physics, 46(4):860-876, 2007.
R. Landauer. The physical nature of information. Physics Letters A, 217:188, 1996.
B. Libet. Conscious subjective experience vs. unconscious mental functions: a theory of the cerebral process involved. In M.J. Cotterill, editor, Models of Brain Function, pages 35-43. Cambridge University Press, Cambridge, 1989.
R. Melzack. Phantom limbs, the self and the brain. Canadian Psychology, 30:1-16, 1989.
M.A. Nielsen and I.L. Chuang. Quantum Computation and Quantum Information. Cambridge University Press, Cambridge, 2000.
U. Neisser. Memory Observed. W.H. Freeman, San Francisco, 1982.
R. Penrose. The Emperor’s New Mind. Oxford University Press, London, 1989.
R. Penrose. Shadows of the Mind. Oxford University Press, London, 1994.
R. Penrose. The Road to Reality. Alfred A. Knopf, New York, 2005.
A. Peres. Quantum Theory: Concepts and Methods. Kluwer Academic, Dordrecht, 1995.
K. Pribram and J. King, editors. Learning as Self-Organization. Lawrence Erlbaum Associates, Mahwah, NJ, 1996.
E. Schrödinger. Mind and Matter. Cambridge University Press, Cambridge, 1958.
J.A. Wheeler. The computer and the universe. International Journal of Theoretical Physics, 21:557-572, 1982.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag London Limited
About this chapter
Cite this chapter
Kak, S. (2007). Quantum Mechanics and Artificial Intelligence. In: Schuster, A.J. (eds) Intelligent Computing Everywhere. Springer, London. https://doi.org/10.1007/978-1-84628-943-9_5
Download citation
DOI: https://doi.org/10.1007/978-1-84628-943-9_5
Publisher Name: Springer, London
Print ISBN: 978-1-84628-942-2
Online ISBN: 978-1-84628-943-9
eBook Packages: Computer ScienceComputer Science (R0)