Axiomatic Narrative and Relational Insights:

Result: The AI ecosystem evolves according to the function E(t) = A * e^(r*t), where A represents the initial state of AI and r the rate of innovation. The convergence between domains is described by C(d1, d2) = ∫(f(d1) * g(d2))dt, with f and g functions of development for domains d1 and d2. Computational efficiency follows P(c) = k * log(c), where c is computing capacity and k a scalability constant. Multimodal integration is expressed by M(x, y, z) = α*x + β*y + γ*z, with x, y, z representing text, image, and video. The propagation of innovation is modeled by dI/dt = σI(1-I/K), where I is the level of innovation and K the maximum system capacity. These equations describe a rapidly evolving AI system characterized by multidisciplinary integration, computational scalability, and convergence towards general applications, defining a unique trajectory for the future development of artificial intelligence.