Saved in:
| Main Author: | |
|---|---|
| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2025
|
| Online Access: | https://doi.org/10.5281/zenodo.17438164 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of 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>