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

• URL: http://arxiv.org/abs/2501.06196v1
• Date: Thu, 26 Dec 2024 16:26:00 GMT
• Title: How Do Artificial Intelligences Think? The Three Mathematico-Cognitive Factors of Categorical Segmentation Operated by Synthetic Neurons
• Authors: Michael Pichat, William Pogrund, Armanush Gasparian, Paloma Pichat, Samuel Demarchi, Michael Veillet-Guillem,
• Abstract summary: How do the synthetic neurons in language models create "thought" categories to segment and analyze their informational environment? This study explores these concepts through the notions of priming, attention, and categorical phasing.
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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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