Saved in:
| Hovedforfatter: | |
|---|---|
| Format: | Recurso digital |
| Sprog: | engelsk |
| Udgivet: |
Zenodo
2025
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| Fag: | |
| Online adgang: | https://doi.org/10.5281/zenodo.16416449 |
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Indholdsfortegnelse:
- <p>The K-Drive Equation is a novel framework for modeling technological progress by quantifying the interplay of inputs (knowledge, demand, population, resources, systems) and frictions (knowledge, social, economic, resource, time, X-factor). Unlike static tech trees, it dynamically accounts for “unknown unknowns” (F_X) and resets friction scores to 1 post-unlock, reflecting how breakthroughs become trivial knowledge. This paper formalizes the equation, presents case studies from Stone Age to Faster-Than-Light (FTL) travel, and outlines use-cases for universities, R&D labs, and policy teams. Applications include forecasting innovation, recovering from societal collapse, and planning off-world colonies. Classroom modules for MIT/Harvard undergrads demonstrate pedagogical value. By mapping and mitigating frictions, the K-Drive Equation accelerates humanity’s path to Kardashev-scale civilizations.</p>