Paper 27 — AXION: Hardware-Agnostic Exchange Architecture for Regional AI Data Infrastructure

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Authors: The First Waters
Cited by: 6
References: 26

Abstract

This working paper develops AXION as a hardware-agnostic exchange architecture for regional AI data infrastructure. The framework does not define a GPU runtime, cloud platform, device-control layer, automated authority system, legal-effect mechanism, public-administration engine, settlement engine, or provider-controlled infrastructure. Instead, it organizes node, data, state, authority, evidence, result, and preservation references through a Coordinate Matrix and relates those references to regional implementation layers through Essential Terra Core and Terra Topology. AXION extends the AGI Structural Alignment Series from document-state coordination, output boundaries, human discretion, role accountability, time-history reference, authority-condition boundaries, candidate-action separation, economic-reference objects, post-cloud preservation, public propagation boundaries, and structural portfolio layering into the domain of AI data infrastructure. The paper defines AXION as a non-platform-centric architecture in which hardware backends, local nodes, public facilities, industrial demand sites, heat-demand references, preservation contexts, and regional deployment layers may correspond without substituting for one another. It introduces the Coordinate Matrix as a seven-axis reference structure; Essential Terra Core as a regional implementation layer; and Terra Topology as a placement grammar for data centers, public facilities, industrial facilities, agricultural facilities, urban demand points, heat-demand points, edge nodes, backup nodes, and preservation zones. The contribution is a public structural framework for making regional AI infrastructure legible while preserving hardware independence, provider independence, institutional autonomy, human responsibility, boundary-preserving interoperability, and non-executive reference discipline. This working paper is Paper 27 of the AGI Structural Alignment Series.

Fields of Study & Subjects

Big Data and Digital Economy Scientific Computing and Data Management Blockchain Technology Applications and Security

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
10 June 2026
Language
EN