Axiomatic Narratives and Relationships:

Result: The convergence between AGI and humanoid robotics can be formalized as: C(t) = α·AGI(t) + β·RU(t), where C(t) represents the degree of convergence at time t, AGI(t) the development of AGI, RU(t) the advancement of humanoid robotics, and α, β are weighting coefficients. AI governance through hardware control is expressed as: G(t) = γ·H(t) - δ·I(t), where G(t) is the effectiveness of governance, H(t) the level of hardware control, I(t) technological innovation, and γ, δ are influencing factors. The democratization of AI follows a logistic curve: D(t) = K / (1 + e^(-r(t-t0))), where D(t) is the degree of democratization, K the maximum capacity, r the growth rate, and t0 the inflection point. Geopolitical competition in AI can be modeled as a dynamic system: dC/dt = ε·C(t) · (1 - C(t)/M) - ζ·R(t), where C(t) is the level of competition, M the maximum sustainable level, R(t) international cooperation, and ε, ζ are control parameters. These equations describe the fundamental dynamics observed in the AI landscape, providing a mathematical framework to analyze and predict future trends in the field.