| _version_ | 1866902079878987776 |
|---|---|
| author | Grandic, Sanjin |
| author_facet | Grandic, Sanjin |
| contents | <div> <div> <div> <div> <h2>The current paradigm of artificial intelligence is built on a foundation of waste. It confuses computational brute force with genuine intelligence, consuming gigawatt-hours of energy and billions of dollars in a relentless, undiscriminating burn of tokens. This is not a path to cognition; it is a path t<em>o thermodynamic insolvency.</em></h2> <h2>I propose a fundamental rupture.</h2> <h2><strong><em>The Grandic Architecture abandons this inefficient model at its core. It introduces a new cognitive physics, one governed by causal determinism and intent-driven computation. This is not an incremental improvement in scaling laws; it is a categorical shift in how intelligence processes information.</em></strong></h2> <h2>This document provides the quantitative evidence for that shift. The data presented herein, from token reduction to energy savings, <em><strong>is not the result of marginal optimization.</strong></em> <br><br></h2> <h2>Together, <strong><em>they collapse the inefficiency of probabilistic computation, replacing it with a deterministic, resource-aware, and logically verifiable process.</em></strong></h2> <h2>The numbers that follow are not merely projections.<em><strong> They are the logical consequence of building an AI that thinks with purpose, rather than one that merely computes without cause</strong></em>.</h2> </div> </div> <h2> </h2> <div> <div> <div> <div> </div> <div> </div> </div> <div> <div> </div> <div> </div> </div> <div> <div> </div> <div> </div> </div> <div> <div> </div> <div> </div> </div> <div> <div> </div> <div> </div> </div> </div> <div> </div> </div> </div> </div> <div> </div> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17438164 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Causality Chain Enforcement (GCCE): A Quantum-Resilient AI Memory and Security Architecture Grandic, Sanjin <div> <div> <div> <div> <h2>The current paradigm of artificial intelligence is built on a foundation of waste. It confuses computational brute force with genuine intelligence, consuming gigawatt-hours of energy and billions of dollars in a relentless, undiscriminating burn of tokens. This is not a path to cognition; it is a path t<em>o thermodynamic insolvency.</em></h2> <h2>I propose a fundamental rupture.</h2> <h2><strong><em>The Grandic Architecture abandons this inefficient model at its core. It introduces a new cognitive physics, one governed by causal determinism and intent-driven computation. This is not an incremental improvement in scaling laws; it is a categorical shift in how intelligence processes information.</em></strong></h2> <h2>This document provides the quantitative evidence for that shift. The data presented herein, from token reduction to energy savings, <em><strong>is not the result of marginal optimization.</strong></em> <br><br></h2> <h2>Together, <strong><em>they collapse the inefficiency of probabilistic computation, replacing it with a deterministic, resource-aware, and logically verifiable process.</em></strong></h2> <h2>The numbers that follow are not merely projections.<em><strong> They are the logical consequence of building an AI that thinks with purpose, rather than one that merely computes without cause</strong></em>.</h2> </div> </div> <h2> </h2> <div> <div> <div> <div> </div> <div> </div> </div> <div> <div> </div> <div> </div> </div> <div> <div> </div> <div> </div> </div> <div> <div> </div> <div> </div> </div> <div> <div> </div> <div> </div> </div> </div> <div> </div> </div> </div> </div> <div> </div> |
| title | Causality Chain Enforcement (GCCE): A Quantum-Resilient AI Memory and Security Architecture |
| url | https://doi.org/10.5281/zenodo.17438164 |