The human brain is at least a factor of 1 billion more efficient than our present digital technology, and a factor of 10 million more efficient than the best digital technology that we can imagine today. The unavoidable conclusion is that we have something fundamental to learn from the human brain about a new and much more effective form of computation, with a convenient, effective, efficient and reliable bottom-up (BU) approach. In another paper presented at this conference we focused on the computational information conservation properties of optimized numeric words with precisation of meaning. Here, we present a brain-inspired geometric-logical scheme defining fundamental human linguistic and predicative competence. According to CICT, complete duality of Opposition and Implication Geometry in Logical Geometry and Language can model n-dimensional predicative competence and beyond, according to available computational resources. In any case, their combination may provide even a concrete opportunity for the foundation of computational psychiatry and for reformulating psychoanalytical theory in a sharable way.

Brain-Inspired Systems and Predicative Competence

Fiorini, Rodolfo A.
2017-01-01

Abstract

The human brain is at least a factor of 1 billion more efficient than our present digital technology, and a factor of 10 million more efficient than the best digital technology that we can imagine today. The unavoidable conclusion is that we have something fundamental to learn from the human brain about a new and much more effective form of computation, with a convenient, effective, efficient and reliable bottom-up (BU) approach. In another paper presented at this conference we focused on the computational information conservation properties of optimized numeric words with precisation of meaning. Here, we present a brain-inspired geometric-logical scheme defining fundamental human linguistic and predicative competence. According to CICT, complete duality of Opposition and Implication Geometry in Logical Geometry and Language can model n-dimensional predicative competence and beyond, according to available computational resources. In any case, their combination may provide even a concrete opportunity for the foundation of computational psychiatry and for reformulating psychoanalytical theory in a sharable way.
2017
Proceedings of the 16th IEEE International Conference on Cognitive Informatics and Cognitive Computing (IEEE ICCI*CC 2017)
Cognitive intelligence; computational intelligence; cognitive computing; brain-inspired systems; CICT; deep thinking
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1037349
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