Abstract

This version is outdated. The updated May 5, 2025 version is available at Zenodo, DOI 10.5281/zenodo.15331603 The Cernuto-Hobbey Theory of Everything (CH-ToE) proposes a radical shift in our understanding of fundamental reality: the universe does not merely evolve through forces or geometry but follows structured knowledge accumulation (SKA), where quantized learn- ing plateaus drive phase transitions across all domains—physics, biology, artificial intelligence, and intelligence itself. Unlike traditional Theories of Everything (ToEs) that prioritize geometric unification or energetic interactions, CH-ToE introduces knowledge as a quantized, measurable, and fundamental entity that dictates structured transformations. At the core of CH-ToE is the universal knowledge transition parameter, λ (lambda), a measurable threshold dictating when systems transition from uncertainty to structured intelligence. Empirical analysis across multiple domains—quantum mechanics, AI scaling laws, biological evolution, and cosmic structure formation—reveals that phase transitions consistently align with λ, suggesting that knowledge structuring follows universal constraints. The fundamental derivation of λ is given by: λ =√8/ϕ ≈ 1.748 (1) where ϕ is the golden ratio, linking λ to optimal entropy minimization and structured complexity growth. This connection emerges from the principle that knowledge transitions must follow an entropy-optimized path, ensuring minimal energy expenditure while maximizing information structuring. The attached preprint represents an evolving theoretical framework, inviting collaboration, refinement, and empirical testing to advance our understanding of knowledge as a fundamental component of reality. While CH-ToE presents a unifying principle, several key areas require further development.