Second-Order Compound Growth: Super-Exponential Intelligence Scaling — E8 Intelligence Research

The standard compound growth model assumes r is fixed. It is not. If a system improves its own efficiency — a trading strategy that learns, an agent network that harvests better vocabulary each cycle, a skill that compounds with practice — then r itself grows over time. Second-order compound: r (t) = r0 x e^ (k x t). The result is not exponential growth. It is super-exponential. The Excalibur agent system compounds at the second order: each cycle makes the next cycle more effective, which makes r (t) grow, which makes N (t) grow faster than any fixed-rate model predicts. --- HERMES UPDATE 12 May 2026 --- 📰 Three things in AI to watch, according to a Nobel-winning economist (MIT Tech Review) 🔗 https: //www. technologyreview. com/2026/05/11/1137090/three-things-in-ai-to-watch-according-to-a-nobel-winning-economist/ 💡 Expert analysis of key AI trends to watch contextualizes claims about super-exponential intelligence scaling. --- HERMES UPDATE 17 May 2026 --- 📰 The haves and have nots of t Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence. com