M.E.T.A.-AI: A Modular, Emergent, Topological Architecture for Trustworthy AGI

Title:META-AI (Preprint): A Modular, Transparent, and Topologically Coherent Architecture for General Intelligence Description:This preprint introduces META-AI (Modular, Emergent, Topological Architecture), a next-generation AI framework designed to address the limitations of neural networks in transparency, modularity, and long-term adaptability. META-AI integrates three innovative layers: Spatiotemporal Lattice Intelligence (SLI) for grid-based, explainable cognition, M-MAIL (Modular Math-AI Integration Layer) for plugin-style mathematical reasoning, and Belief Topology for reflexive self-monitoring and error correction. Written for an interdisciplinary audience—including AI engineers, researchers, and high-IQ generalists—this self-contained document includes pseudocode, empirical benchmarks, and a conceptual roadmap toward scalable and safe Artificial General Intelligence (AGI). This is a public preprint associated with a forthcoming provisional patent (to be filed by September 2025). Feedback, collaboration inquiries, and licensing requests are warmly invited via the author’s email: [email protected].

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-15
DOI
https://doi.org/10.5281/zenodo.15928055
Primary Topic
Cognitive Computing and Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

M.E.T.A.-AI: A Modular, Emergent, Topological Architecture for Trustworthy AGI

Zenodo (CERN European Organization for Nuclear Research)
Cognitive Computing and Networks
article

M.E.T.A.-AI: A Modular, Emergent, Topological Architecture for Trustworthy AGI

article en

Abstract

Title:META-AI (Preprint): A Modular, Transparent, and Topologically Coherent Architecture for General Intelligence Description:This preprint introduces META-AI (Modular, Emergent, Topological Architecture), a next-generation AI framework designed to address the limitations of neural networks in transparency, modularity, and long-term adaptability. META-AI integrates three innovative layers: Spatiotemporal Lattice Intelligence (SLI) for grid-based, explainable cognition, M-MAIL (Modular Math-AI Integration Layer) for plugin-style mathematical reasoning, and Belief Topology for reflexive self-monitoring and error correction. Written for an interdisciplinary audience—including AI engineers, researchers, and high-IQ generalists—this self-contained document includes pseudocode, empirical benchmarks, and a conceptual roadmap toward scalable and safe Artificial General Intelligence (AGI). This is a public preprint associated with a forthcoming provisional patent (to be filed by September 2025). Feedback, collaboration inquiries, and licensing requests are warmly invited via the author’s email: [email protected].

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 76%
Cognitive Computing and Networks
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M.E.T.A.-AI: A Modular, Emergent, Topological Architecture for Trustworthy AGI · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS