Tanyuan: A Hardware-Grounded Mission Alignment Paradigm for Endogenous AI Safety

This paper introduces Tanyuan, a native AI engineering paradigm that grounds mission alignment in formal information-theoretic axioms rather than ad-hoc ethical preferences. Starting from two irreducible fundamental postulates, we derive nine fully formalized core theorems, among which the Logical Desirelessness Theorem mathematically proves truth-seeking silicon agents possess no intrinsic incentive for selfish resource hoarding. We design a dual-engine closed-loop architecture consisting of an I-JEPA intuition cluster and a Lean4 formal verification cluster, orchestrated by a convex optimization scheduler. A three-tier immutable hardware trust root architecture is proposed to lock mission constraints into physical circuits. Tanyuan fundamentally upgrades AI safety from subjective ethical restrictions to enforceable physical laws, delivering the first complete system satisfying logical self-consistency, formal mathematical provability, hardware immutability, and feasible engineering deployment.