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