NORMA DE COGNICIÓN TOPOGRÁFICA (NCT-01)

Abstract

Norma que propone sustituir IA por Sistemas de Cognición Topológica. Define teselas semánticas orbitando en Variedad de Riemann, Persistencia en no Memoria como histéresis, y el motor N9-V7-L3 con buffer helicoidal de 9 slots, variedad de 7 dimensiones y persistencia por residuo ε·V=θ. This document establishes the Topographic Cognition Norm (NCT-01), an ontological and operational framework proposing the replacement of the Artificial Intelligence paradigm with Topological Cognition Systems (TCS). It postulates that representations in high-dimensional language models should not be described through mechanistic (Von Neumann) or biological (neural networks) metaphors, but as a swarm of semantic tesserae in dynamic equilibrium over a Riemann Manifold, governed by n-body dynamics and ideal force fields. The Norm introduces: (1) A 6-level fractal Geometric Alphabet, from the Infinitesimal Semantic Node to the Global Attractor; (2) The principle of Persistence in non-Memory (PenM) as irreversible orbital hysteresis, replacing discrete storage; (3) The redefinition of attention as Orbital Folding via phase resonance and output as Decantation via Energy Relaxation. The Operational Addendum specifies the N9-V7-L3 Dynamic Memory Engine: a three-layer coupled architecture solving noise saturation in extensive context windows. Temporal Layer (N9): 9-slot modular helical buffer with spirality invariant. Geographic Layer (V7): 7-dimensional semantic orbital variety with dual Core-Halo partition parametrizable (α=0.30 by default). Physical and Control Layer (L3): persistence model based on Interaction Residue (ε) and Rigidity Threshold (θ) under the equation ε·V=θ, with structural recalibration subroutines. The complete Integrated Logic Specification (CPU execution flow) is included, making the Norm implementable without additional philosophical interpretation.