Self-Organizing and Self-Repairing Mass Memories for Autosophy Multimedia Archiving.

Replacing the Data Processing Computer with Self-Learning Machines based on the Autosophy Information Theory

Authors: Klaus Holtz, Eric Holtz, Diana Kalienky.

Published / Presented at: ICETE 2005, 2nd International Conference on e-Business and Telecommunication Networks, Volume II, Reading, UK – October 3 – 7, 2005.

Level: Expert

Abstract: The programmed data processing computer may soon be eclipsed by a next generation of brain-like learning machines based on the "Autosophy" information theory. This will require a paradigm shift in memory technology, from random addressable memories to self-organizing failure-proof memories. The computer is essentially a blind calculating machine that cannot find "meaning" as our own brains obviously can. All that can be achieved are mere programmed simulations. The problem can be traced to an outdated (Shannon) information theory, which treats all data as "quantities." A new Autosophy information theory, in contrast, treats all data as "addresses." The original research explains the functioning of self-assembling natural structures, such a chemical crystals or living trees. The same principles can also grow self-assembling data structures that grow like data crystals or data trees in electronic memories without computing or programming. The resulting brain-like systems would require virtually unlimited capacity, failure-proof memories. The memories should be self-checking, self-repairing, self-healing, clonable, both random and content addressable, with low power consumption and very small size for mobile robots. Replacing the programmed data processing "computer" with brain-like "autosopher" promises a true paradigm shift in technology, resulting in system architectures with true "learning" and eventually true Artificial Intelligence.   

Keywords: Autosophy, Information Theory, Multimedia Archiving, Self-Assembling Data Networks, Self-Repairing Memories, Content Addressable Memories, Artificial Intelligence.

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