The Semantic A.I. Reactor (SAIR) Article Swipe
The Semantic A.I. Reactor (SAIR) proposes an architectural core for governed, stateless, and semantically coherent artificial intelligence. Modern large language models operate as unbounded statistical engines without a principled semantic layer. SAIR introduces an invariant semantic framework, a normative audit loop, and cross-model consensus to provide stability, containment, and definitional clarity. A central result of the paper argues that persistent memory cannot be governed safely through policy or operator restraint; therefore, its removal at the architectural level is a structural requirement for safe intelligence systems. Scope of this document. This paper presents theoretical architecture only. It does not include implementation instructions, system schematics, source code, hardware details, or operational procedures. All descriptions are conceptual and abstract, intended for academic analysis and high-level architectural reasoning. Non-reverse-engineering notice. This work is released under CC BY-NC-ND 4.0. No derivatives, reconstructions, implementations, modifications, or reverse-engineering attempts of any system described here are permitted. This publication is intentionally non-actionable: it provides a conceptual framework for governed A.I. architecture, not an engineering blueprint. Purpose. The goal of this publication is to advance research and discussion in AI architecture, safety, and governance by introducing a semantic operating layer designed to ensure statelessness, structural containment, and definitional consistency across intelligent systems.
Related Topics
Concepts
Computer science
Software engineering
Architecture framework
Consistency (knowledge bases)
Scope (computer science)
Semantics (computer science)
Audit
Semantic data model
Artificial intelligence
Architecture
Conceptual model
Normative
Systems engineering
Semantic mapping
Semantic computing
Conceptual architecture
Operator (biology)
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.5281/zenodo.17905595
- OA Status
- green
- OpenAlex ID
- https://openalex.org/W7115005743
All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W7115005743Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5281/zenodo.17905595Digital Object Identifier
- Title
-
The Semantic A.I. Reactor (SAIR)Work title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-12-11Full publication date if available
- Authors
-
Jacobs, AustinList of authors in order
- Landing page
-
https://doi.org/10.5281/zenodo.17905595Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.5281/zenodo.17905595Direct OA link when available
- Concepts
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Computer science, Software engineering, Architecture framework, Consistency (knowledge bases), Scope (computer science), Semantics (computer science), Audit, Semantic data model, Artificial intelligence, Architecture, Conceptual model, Normative, Systems engineering, Semantic mapping, Semantic computing, Conceptual architecture, Operator (biology)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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