Emergence of Superintelligence from Collective Near-Critical Dynamics in Reentrant Neural Fields
Byung Gyu Chae

TL;DR
This paper proposes that superintelligence emerges from collective critical dynamics in neural systems, where phase transitions and self-organized criticality create a stable, flexible cognitive regime distinct from simple quantitative scaling.
Contribution
It introduces a unified dynamical field-theoretic framework showing how collective coupling drives neural systems toward criticality, leading to superintelligence as a phase transition rather than mere scale expansion.
Findings
Identification of power-law scaling in collective relaxation rates
Demonstration of a meta-stable infrared phase with long-lived inference trajectories
Establishment of a protected critical regime balancing coherence and flexibility
Abstract
Superintelligence is commonly envisioned as a quantitative extrapolation of human cognitive abilities driven by scale and computational power. Here we show that qualitative transitions in intelligence instead arise as dynamical phase transitions governed by collective critical dynamics. Building on a unified dynamical field-theoretic framework for cognition, we demonstrate that progressive collective coupling generated by reentrant mixing drives the system toward an infrared critical regime in which an extensive band of slow collective modes emerges. This spectral condensation reorganizes cognitive dynamics from localized relaxation to coherent motion along emergent low-dimensional manifolds. Through numerical analysis of the time-scale density of states, we identify robust power-law scaling of collective relaxation rates with well-defined critical exponents, placing the system within…
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Taxonomy
TopicsNeural Networks and Reservoir Computing · stochastic dynamics and bifurcation · Embodied and Extended Cognition
