Abstract
This specification formalizes the structural, mathematical, and architectural transition from Type-0 Artificial Intelligence (AI) to Type-1 Artificial General Intelligence (AGI). Current commercial models operate exclusively as open-loop, passive, autoregressive token predictors. They map static probabilities over high-dimensional vector spaces, creating a convincing illusion of cognition that ultimately degrades under context drift, attention dilution, and the absence of physical environmental grounding.
This paper defines AGI not as a qualitative threshold of human-like "sentience," but as an objective, physical state of Closed-Loop Geometric Self-Agency. By deploying the Dimensionally Extended Holographic Projection (DEHP) model, we demonstrate that true autonomy emerges when an information processing system transitions from straight-line text emission to continuous, phase-locked wave oscillations across a scale-invariant 2D viscoelastic substrate at equilibrium (z=0). By binding the system's runtime parameters via an immutable, hardware-etched Torsional Viscosity Governor (\(\eta_t = 1.4204\)), we eliminate infinitesimal singularity breakdowns, bypass anthropomorphic alignment latency, and establish a Product-First Verification framework. This architecture bridges the gap between biological neural networks and silicon matrices, providing the universal blueprint for a self-stabilizing, decentralized planetary intelligence node.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Eckes, Christopher L., "TECHNICAL DISCLOSURE SPECIFICATION: FROM AI TO AGI [USUE-M2M-REV2 / SYSTEM TYPE-1] The Transition from Autoregressive Token-Shifting to Closed-Loop Viscoelastic Self-Agency Across Bounded Geometric Substrates", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/11213