Consciousness Bandwidth and Frequency Orthogonality (II): Artificial Intelligence as a High-Energy Non-Cognitive Information Metabolism System

BO ZHANG

2026.79.0376

DOI https://doi.org/10.59332/jbis-079-10-0376

This paper develops a physical framework for understanding contemporary artificial intelligence as a high-energy, non- cognitive information metabolism system. Building on scale-centric causality and frequency orthogonality, it relates energy- flux density to characteristic coherence frequency and argues that large-scale AI computation can generate internally coherent causal dynamics without implying biological cognition or subjective awareness. The mismatch between machine and human timescales is analysed through sampling theory as causal aliasing, with implications for interpretability, alignment, and human–AI interaction. The framework also suggests a local analogue of the Fermi paradox: advanced intelligences operating at substantially different energetic and temporal scales may become causally inaccessible despite spatial proximity.

Keywords: Artificial intelligence, Information Metabolism, Energy Flux Density, Frequency Orthogonality, Scale-centric Causality, Causal Aliasing, AI Alignment, Fermi Paradox