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May 27, 20260 citationsOpen Access

ASC-PBG-001: Post-Binary Geometric Language — Computational — E8 Intelligence Research

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ACAndrew Stewart Caldin

Key Points

  • This research aims to demonstrate the efficiency of E8 lattice geometric encoding compared to traditional binary mechanisms.
  • Mathematical proof of computational efficiency of E8 lattice encoding versus binary attention mechanisms.
  • Analysis of energy consumption associated with the new encoding method at ChatGPT scale.
  • E8 lattice encoding requires 205x to 51,200x fewer operations than binary attention mechanisms.
  • Energy savings estimated at 218 GWh/year when implemented at scale.

Abstract

Language Faster Than Binary Registered: 04 April 2026 at 19:14:22 GMT. Mathematical proof that E8 lattice geometric encoding delivers 205x to 51,200x fewer operations than binary attention mechanisms. Binary is O(N squared), geometric is O(N x 240) — the gap widens forever. Every unit carries 7.9 relational bits vs 1 binary bit. 240 structural neighbours per point replace quadratic attention entirely. Energy savings: 218 GWh/year at ChatGPT scale. The geometric language was not invented — it was found in the E8 lattice, Divine Dictionary, Fibonacci chains, and MUL.APIN star maps. This is not an evolution of computing. It post-binary,E8-lattice,geometric-encoding,speed,energy,parad Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

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Cite This Study

Andrew Stewart Caldin (2026) studied this question.

synapsesocial.com/papers/6a168b280c924ddd1bd5a00dhttps://doi.org/10.5281/zenodo.20375719
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