Mechanisms of Learning Through the Actualization of Discrepancies

Main Article Content

Jaba Tkemaladze

Abstract

Adaptive systems, whether biological or artificial, rely on internal models to interact with their environment. This study investigates a learning mechanism driven by discrepancies between predictions and reality. A two-level computational system is analyzed: (1) passive pattern memorization and (2) active model correction. Key adaptive elements include fixed input-processing blocks (analogous to sensory channels), dynamic weight adjustments (memory-like), and a balance between model updating (learning acceleration) and stabilization. Memory plays a central role, with statistical data (*_tendency.csv) forming predictive foundations and an optimization algorithm refining them. Healthy adaptation requires equilibrium between plasticity and resilience. The framework demonstrates broad applicability, spanning AI and cognitive science. Unlike traditional views of memory as mere recall, this model emphasizes its dual role in both memorization and world-model formation, achieved through integrated memory functions. The results highlight memory’s potential as a core adaptive mechanism, bridging machine and biological learning. This approach advances AI development while offering novel insights into natural cognition, underscoring the parallels between artificial and biological adaptive systems.

Article Details

Section

Technology and Innovations

Author Biography

Jaba Tkemaladze, Longevity Clinic

Dr Jaba Tkemaladze is a Professor, a Scientist, and a President of Longevity Alliance Georgia.

Research Director at Longevity Clinic.

Replacing old adult stem cells with induced and safe young adult stem cells.

World-renowned scientist. Developed the Centriolar theory of differentiation and the Centriolar theory of organism ageing. With acquired experience in both academia and industry.

Training in medicine at Tbilisi State Medical University and then at the Psychiatry Research Institute further deepened my knowledge in the laboratory of the Institute of Morphology. Namely, combined experimental and computational methods to study the ageing process and the various ways of manipulating age-related diseases and improvement of human health.

Also served as a Scientific Advisory Board Member in Georgia's Ministry of Defense and Longevity Alliance. Published over 50 scientific articles, given over 100 invited talks and received several awards.

His Rejuvenation Formula: Rejuvenation = Replacement of Old Centrioles with Young Ones.

How to Cite

Tkemaladze, J. (2025). Mechanisms of Learning Through the Actualization of Discrepancies. Longevity Horizon, 1(3). DOI:https://doi.org/10.5281/zenodo.15200612

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