Abstract
Brain-inspired computing structures, technologies, and methods offer innovative approaches to the future of computing. From the lowest level of neuron devices to the highest abstraction of consciousness, the brain drives new ideas (literally and conceptually) in computer design and operation. This paper interrelates three levels of brain inspired abstractions including intelligence, abstract graph data structures, and neuron operation and interconnection. An abstract machine architecture is presented from which a lower bound on resource requirements for intelligence is to be derived. At the lowest level a new use of cellular automata architecture is discussed that mimics the fine-grain locality of action and high degree interconnectivity of neurons and their structures. Graph structures serve as a brain inspired intermediary abstraction between these two as the neocortex is organized as a directed graph. This paper shows how all of the pieces tie together and opens a new way of considering future computing structures through brain inspired concepts.
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Sterling, T., Brodowicz, M., Gilmanov, T. (2014). Towards Brain-Inspired System Architectures. In: Grandinetti, L., Lippert, T., Petkov, N. (eds) Brain-Inspired Computing. BrainComp 2013. Lecture Notes in Computer Science(), vol 8603. Springer, Cham. https://doi.org/10.1007/978-3-319-12084-3_13
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DOI: https://doi.org/10.1007/978-3-319-12084-3_13
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