Vector Symbolic Architectures: A New Building Material for AGI
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1 year ago
Simon Levy presents at AGI-08 on a paper by the speaker and Ross Gayler. The authors provide an overview of Vector Symbolic Architectures (VSA), a class of structured associative memory models that offers a number of desirable features for artificial general intelligence. By directly encoding structure using familiar, computationally efficient algorithms, VSA bypasses many of the problems that have consumed unnecessary effort and attention in previous connectionist work. Example applications from opposite ends of the AI spectrum – visual map-seeking circuits and structured analogy processing – attest to the generality and power of the VSA approach in building new solutions for AI.Simon Levy presents at AGI-08 on a paper by the speaker and Ross Gayler. The authors provide an overview of Vector Symbolic Architectures (V...all »Simon Levy presents at AGI-08 on a paper by the speaker and Ross Gayler. The authors provide an overview of Vector Symbolic Architectures (VSA), a class of structured associative memory models that offers a number of desirable features for artificial general intelligence. By directly encoding structure using familiar, computationally efficient algorithms, VSA bypasses many of the problems that have consumed unnecessary effort and attention in previous connectionist work. Example applications from opposite ends of the AI spectrum – visual map-seeking circuits and structured analogy processing – attest to the generality and power of the VSA approach in building new solutions for AI.«
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