PPT-Efficient Digital Neurons for Large Scale Cortical Architectures

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James E Smith 2014 ACMIEEE 41st International Symposium on Computer Architecture ISCA 1 Presented by Rasmus Lüscher Executive Summary Motivation Large scale architectures

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Efficient Digital Neurons for Large Scale Cortical Architectures: Transcript


James E Smith 2014 ACMIEEE 41st International Symposium on Computer Architecture ISCA 1 Presented by Rasmus Lüscher Executive Summary Motivation Large scale architectures are needed to emulate the neocortex to support research studying the operation of the brain. Corresponding author.1. INTRODUCTIONWith the primary scale of mapping becoming larger in order tocope with the developments, the work involved in keeping mapsup-to-date has increased considerably. DIVISION MockUp, PTC SCAPE SCAPE This work was par�ally supported by the SCAPE Project. The SCAPE project is co-funded by the European Union under FP7 ICT-2009.4.1 (Grant Agreement More informa�onwww By. Chi . Bemieh. . Fule. August 6, 2013. THESIS PRESENTATION . Outline. . of. . today’s. presentation. Justification of the study. Problem . statement. Hypotheses. Conceptual. . framework. Research . Yaohui Tang. Max-Planck-Institute for Biological Cybernetics. What is coma?. Coma is a state of unconsciousness, which is marked by a lack of awareness and response to external . stimulus.. Steven . Laureys. Final Defense Presentation. by Steven Y. Ko. Thesis Focus. One class of operations. that faces . one common set of challenges. . cutting across . four diverse and popular types of distributed infrastructures. DIVISION MockUp, PTC Neuronal migration defects. Hippocampal sclerosis. April 18, 2015. Overview. Neuronal migration defects. Pachygyria. /. Lissencephaly. Polymicrogyria. Neuronal heterotopia. Cortical dysplasia. Hippocampal sclerosis. John Doyle, Caltech. Rethinking fundamentals*. Parameter estimation and goodness of fit measures for . fat tail. distributions. Hard limits . on robust, efficient networks integrating . comms. , controls, energy, materials. Cognitive Anteater Robotics Lab (CARL). Department of Cognitive Sciences. Kristofor . D. . Carlson. , Michael . Beyeler. , Ting-. Shuo. Chou, . Nikil. . Dutt. , Jeffrey L. . Krichmar. Overview. Spiking Neural Networks (SNNs). Slides on LRTDP and UCT are courtesy . Mausam. /. Kolobov. . Ideas for Efficient Algorithms... Use heuristic search (and reachability information). LAO*, RTDP. Use execution and/or Simulation. “Actual Execution” Reinforcement learning. Fat tails, hard limits, thin layers John Doyle, Caltech Rethinking fundamentals* Parameter estimation and goodness of fit measures for fat tail distributions Hard limits on robust, efficient networks integrating . cortex. Cortical fields, Brodmann areas. Mark Kozsurek, M.D., Ph.D. .. mark@kozsurek.hu. EM II., 30/09/2019. http://controlmind.info/human-brain/right-and-left-brain. In a broader sense the . pallium. Division of Neuroscience. Hammersmith Hospital Campus. Imperial . College London. Sherrington . (1924). “. To move things is all mankind can do, for such the sole executant is muscle, whether in whispering a syllable or felling a .

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