Innovation & Synergy: The Power of the Implicit
How do we understand the dynamics of sorting out useful ideas from the general chatter of a community? What does the productivity of a community depend on? From a theoretical perspective, models of information within networks help us to understand how information spreads and is aggregated, and that determines the speed with which individuals and organizations can act, innovate and plan their future activities. This talk will describe new mechanisms for automatically identifying communities of practice within large networks and for elucidating the spread of information within those communities. In addition, I will describe a novel methodology for information aggregation that leads to accurate predictions of uncertain events in the real world.
Bernardo Huberman is a Senior HP Fellow and Director of the Information Dynamics Lab at Hewlett Packard Laboratories. His current work centers on the design of novel mechanisms for discovering and aggregating information in distributed systems, as well as understanding the dynamics of large distributed systems. Dr. Huberman has worked in theoretical physics, dealing with systems ranging from superionic conductors to two-dimensional superfluids, and is one of the discoverers of chaos and its properties in a number of physical systems. His research into the dynamics of complex systems helped establish many of the universal properties of cooperative systems, as well as the laws governing the growth and use of the web. He is one of the creators of the field of ecology of computation, and the author of the book "The Laws of the Web".
Bernardo was a member of PARC for many years, a Chairman of the Xerox Council of Fellows and manager of the Internet Ecologies Group. He is also a Consulting Professor of Physics at Stanford University. In addition, he is a fellow of the American Physical Society, a former trustee and Secretary of the Aspen Center for Physics, a fellow of the Japan Society for the Promotion of Science, and a faculty member in the Symbolic Systems Program at Stanford University. He shared the 1990 CECOIA prize in Economics and Artificial Intelligence and the IBM Prize of the Society for Computational Economics. He has held visiting professorships at the University of Paris, the University of Copenhagen and the European School of Business.
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