The Deterministic Unification Model: Completing AI Theory Through State-Transition Computation

摘要

This white paper introduces the Deterministic Unification Model, a unified theoretical framework that resolves eighty years of fragmented artificial intelligence theory. By integrating contributions from Turing, Shannon, Boole, Feynman, Pearl, Hinton, LeCun, Goodfellow, Paige, and Bin into a single deterministic state transition equation, the model provides a foundation for safe, reproducible, and auditable machine intelligence. It describes the mathematical structure of deterministic computation, contrasts it with probabilistic architectures, and outlines implications for aerospace, healthcare, automotive systems, robotics, entertainment engineering, and cybersecurity. A United States non provisional patent application covering this architecture was filed on November 25, 2025 (Application Number 19 400 020). A provisional patent application establishing priority was filed on April 18, 2025.