M.E.T.A.-AI: A Modular, Emergent, Topological Architecture for Trustworthy AGI
Year: 2025
Type: article
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].
Author: Blankert, Jean Philippe
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6912109904
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