Preprint / scholarly article

From AI Capability Growth to Real-Economy Growth: A Semi-Endogenous Model of Physical and Institutional Bottlenecks

K. Takahashi

Published
DOI
10.5281/zenodo.18677068

Full text PDF (Zenodo)

Abstract

This preprint quantifies how rapid AI capability growth in information space is filtered by physical and institutional constraints, yielding reflection-adjusted semi-endogenous growth laws and bottleneck-switch timing results. It formulates a hybrid ODE-jump model that separates potential algorithmic progress from realized real-economy deployment across compute infrastructure, energy, permitting, and regulatory readiness.

Keywords

  • AI capability growth
  • semi-endogenous growth
  • real-economy translation
  • physical bottlenecks
  • institutional bottlenecks
  • information-to-reality gap
  • hybrid ODE-jump model
  • bottleneck-switch timing
  • compute deployment
  • knowledge production
  • reflection-adjusted growth
  • AI economics

Identifiers and source records