The K-Drive Equation: A Dynamic Model for Mapping and Accelerating Technological Progress
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| Natura: | Recurso digital |
| Lingua: | inglese |
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Zenodo
2025
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| _version_ | 1866902206338301952 |
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| author | Brown, Travon |
| author_facet | Brown, Travon |
| contents | <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> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16416449 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | The K-Drive Equation: A Dynamic Model for Mapping and Accelerating Technological Progress Brown, Travon technological progress <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> |
| title | The K-Drive Equation: A Dynamic Model for Mapping and Accelerating Technological Progress |
| topic | technological progress |
| url | https://doi.org/10.5281/zenodo.16416449 |