To exist is to be five-dimensional. Before AI, nature and civilization established stable boundaries and directions; the structural dimension merely organized data, while reserve and intensity remained naturally constrained. AI, through the single-structure-dimension Transformer paradigm, shattered this equilibrium: boundaries became unbounded, directions oscillated, reserves fractured, and intensity exploded. The Western ``scale-is-all-you-need'' approach attempts to implicitly cover the other four dimensions through unlimited structural expansion, inevitably accumulating systemic crises. This paper proposes the Five-Dimensional Native Model(5D-NM), using five-dimensional mathematics as the bridge to translate philosophical ontology directly into neural network meta-architecture. Through five-dimensional embedding, attention, and synergy loss, 5D-NM endogenizes boundary vigilance, structural generation, reserve traceability, direction calibration, and intensity regulation within a unified parameter space, with κ directly participating in gradient descent for end-to-end trainability, measurability, and evolvability.

存在即五维。AI问世前,自然与社会为人类文明设定了相对稳定的边界与方向,结构维只需组织数据,储备与强度自然可控。AI以Transformer单一结构维范式打破了五维平衡:边界被无限放大、方向摇摆不定、储备断裂、强度失控。西方“大力出奇迹”的参数膨胀路线试图以结构扩张隐式覆盖其余四维,必然导致系统性危机。本文提出五维原生模型(5D-NM),以五维数学为桥梁,将五维系统论从哲学存在论直接下沉为神经网络元架构,通过五维嵌入、五维注意力与五维协同损失,使边界警觉、结构生成、储备溯源、方向校准与强度调节内生于同一参数空间,κ直接参与梯度下降,实现端到端的可训练、可度量、可演化。