How Do Artificial Intelligences Think? The Three Mathematico-Cognitive Factors of Categorical Segmentation Operated by Synthetic Neurons

Michael Pichat, William Pogrund, Armanush Gasparian, Paloma Pichat, Samuel Demarchi +1 more
12/26/2024
q-bio.NCcs.AIcs.NE

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Abstract

How do the synthetic neurons in language models create "thought categories" to segment and analyze their informational environment? What are the cognitive characteristics, at the very level of formal neurons, of this artificial categorical thought? Based on the mathematical nature of algebraic operations inherent to neuronal aggregation functions, we attempt to identify mathematico-cognitive factors that genetically shape the categorical reconstruction of the informational world faced by artificial cognition. This study explores these concepts through the notions of priming, attention, and categorical phasing.

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Cite this paper

@article{pichat2024artificial,
  title  = {How Do Artificial Intelligences Think? The Three Mathematico-Cognitive Factors of Categorical Segmentation Operated by Synthetic Neurons},
  author = {Michael Pichat and William Pogrund and Armanush Gasparian and Paloma Pichat and Samuel Demarchi and Michael Veillet-Guillem},
  year   = {2024},
  eprint = {2501.06196},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2501.06196v1}
}

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