Preprint / scholarly article

Holographic Observation Quotients and Fractal Boundaries: A Model-Agnostic Design Theory for Compute-Optimal Learning

K. Takahashi

Published
DOI
10.5281/zenodo.17601860

Abstract

On the bulk side, the theory assumes an EVI gradient flow of an energy functional on P(X) and a Lipschitz performance functional whose near-optimal sublevel sets have finite Minkowski dimension.

Keywords

  • AI
  • machine learning
  • large language models
  • scaling laws
  • compute-performance
  • evi
  • gradient flows
  • fractals
  • observation quotients
  • holographic
  • holographic compute law

Identifiers and source records