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The Meaning of Things as a Concept in a Strong AI Architecture

Conference paper
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Part of the Lecture Notes in Computer Science book series (LNCS, volume 12177)

Abstract

Artificial intelligence becomes an integral part of human life. At the same time, modern widely used approaches, which work successfully due to the availability of enormous computing power, based on ideas about the work of the brain, suggested more than half a century ago. The proposed model describes the general principles of information processing by the human brain, taking into account the latest achievements. The neuroscientific grounding of this model and its applicability in the creation of AGI or Strong AI are discussed in the article. In this model, the cortical minicolumn is the primary computing processor that works with the semantic description of information. The minicolumn transforms incoming information into its interpretation to a specific context. In this way, a parallel verification of hypotheses of information interpretations is provided when comparing them with information in the memory of each minicolumn of the cortical zone, and, at the same time, determining a significant context is the information transformation rule. The meaning of information is defined as an interpretation that is close to the information available in the memory of a minicolumn. The behavior is a result of modeling of possible situations. Using this approach will allow creating a strong AI or AGI.

Keywords

Meaning of information Artificial general intelligence Strong AI Brain Cerebral cortex Semantic memory Information waves Contextual semantic Cortical minicolumns Context processor Hippocampus Membrane receptors Cluster of receptors Dendrites 

Notes

Acknowledgments

We thank our colleagues from TrueBrainComputing for the discussion of ideas. The authors express their deep gratitude to Olga Pavlovich for translation.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.TrueBrainComputingMoscowRussia

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