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Cognitive Computing 2007
Cognitive Computing 2007 May 2-3, 2007 University of California, Berkeley
A Multi-disciplinary Synthesis of Neuroscience, Computer Science, Mathematics, Cognitive Neuroscience, and Information Theory
![]() CITRIS and NERSC Sponsored Research
We have, in the brain and nervous system, an information processing system unrivalled by artificial means. While it trails machines in accuracy and mathematical computation, it wins on adaptability, flexibility, functionality, and parallelism. The ultimate goal is to reverse engineer enough of this system so that the design principles can be applied to building robust and adaptable computer systems. <!--<--> Cognitive Computing is different from Artificial Intelligence (AI) and Neural Networks (NN). From the outset, AI ignored neurobiology. While neural networks started from biological motivation, they too quickly discarded biological plausibility. In both cases, the approach has been to focus on a suitable problem, and to offer a "symbolic" or "neural network" solution to it. The brain, however, works in exactly the opposite fashion, it has evolved a solution that allows it to deal with problems as they arise.
AI and NN technologies take one or more cognitive phenomena exhibited by the brain as a starting point and then try to replicate that capability by inventing algorithms/learning rules. In contrast, CC is about learning how the brain operates, about algorithms, about diligent reverse engineering and testing plausible models. Cognitive Computing is about engineering the mind by reverse engineering the brain.
Event Sponsors
Additional information can be found at http://www-bisc.eecs.berkeley.edu/CognitiveComputing07/ Presentations![]() Opening Remarks and Activities within NERSC
Opening Remarks and Activities within NERSC
![]() Industry-University Cooperative Research Program (IUCRP)
Industry-University Cooperative Research Program (IUCRP)
![]() Towards Engineering the Mind by Reverse Engineering the Brain
Towards Engineering the Mind by Reverse Engineering the Brain
![]() Towards an Understanding of Cortical Function: Problems and Solutions
Towards an Understanding of Cortical Function: Problems and Solutions
![]() From Cognitive Neuroscience to Computing Architectures
From Cognitive Neuroscience to Computing Architectures
![]() The Brain might Optimize Visual Acuity using Cortical Noise via Stochastic Resonance/Sampling
The Brain might Optimize Visual Acuity using Cortical Noise via Stochastic Resonance/Sampling
![]() Bridging the Gap between Cortical Structure and Cortical Function
Bridging the Gap between Cortical Structure and Cortical Function
![]() Opening Remarks and Activities within CITRIS
Opening Remarks and Activities within CITRIS
![]() ![]() Intelligence for the Humanoid Robot ASIMO: A Synthetic Approach to Understanding Principles of Processing in the Brain
Intelligence for the Humanoid Robot ASIMO: A Synthetic Approach to Understanding Principles of Processing in the Brain
![]() The Human Visual Pathways: Maps, Plasticity, and Reading
The Human Visual Pathways: Maps, Plasticity, and Reading
![]() Principles of Cognition as Adaptations to the World
Principles of Cognition as Adaptations to the World
![]() Panel: VC's, Entrepreneurs, and Innovators: The Future of Cognitive Computing
Panel: VC's, Entrepreneurs, and Innovators: The Future of Cognitive Computing
![]() Panelist: The Swartz Foundation for Computational Neuroscience
Panelist: The Swartz Foundation for Computational Neuroscience
![]() Panelist: Redwood Center for Theoretical Neuroscience, UC Berkeley
Panelist: Redwood Center for Theoretical Neuroscience, UC Berkeley
![]() Panelist: EECS and Cognitive Sciences, UC Berkeley
Panelist: EECS and Cognitive Sciences, UC Berkeley
![]() ![]() ![]() ![]() Last Updated: June 6, 2007 - 1:53pm
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