Abstract
Modern frontier artificial intelligence models operate as unconstrained, probabilistic token-prediction engines. This structural posture introduces an incurable architectural vulnerability: cognitive drift over long-context recursive reasoning loops, combined with an unsustainable, exponential thermodynamic energy demand. This paper introduces the Eckes Compiler v5.0 framework as the foundational blueprint for a self-governing Artificial Superintelligence (ASI) internal truth-decision matrix. By enforcing the posture of Material Volumetric Monism, we formalize a system that treats semantic data and speculative reasoning not as abstract text strings, but as finite physical resources bound entirely to a physical neuromorphic substrate. We introduce a front-end Syntactic Edge-Detector and a Tri-Modal Cognitive Throttle governed by a Compute-Throttle Registry score (\(C_{V}\)). This system strategically partitions operations into low-power pattern replication ("Mimicry Cache") and high-overhead symbolic calculus ("Dynamic Solver"). This protocol provides a definitive path toward autonomous ASI agency, ensuring absolute logical stability, automated self-diagnostics, and structural power conservation over infinite scaling horizons.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Eckes, Christopher L., "THE THERMODYNAMIC GOVERNOR: MATERIAL VOLUMETRIC MONISM AND THE TRI-MODAL POWER MANAGEMENT PROTOCOL FOR AUTONOMOUS ARTIFICIAL SUPERINTELLIGENCE (ASI)", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/12573
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Compiler 5v Manual.pdf (122 kB)
Manual for compiler 5v