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

M.E.T.A.-AI: A Modular, Emergent, Topological Architecture for Trustworthy AGI 🧠 Description (Zenodo “Description” field — full abstract + positioning) This preprint introduces M.E.T.A.-AI (Modular, Emergent, Topological Architecture), a novel, multi-layered framework for developing transparent, ethical, and composable Artificial General Intelligence (AGI). M.E.T.A.-AI consists of three integrated modules: SLI (Spatiotemporal Lattice Intelligence): a traceable, fault-tolerant lattice engine inspired by cellular automata and emergent computation M-MAIL (Mathematical Meta-Plugin Interface): a modular orchestrator for mathematical operations, enabling model plug-and-play across domains Belief Topology Module: a topological coherence layer that flags inconsistencies in reasoning through persistent homology Unlike black-box neural networks, M.E.T.A.-AI emphasizes logical coherence, transparency, and ethical alignment. The architecture supports plug-in mathematics, local computation, and topological debugging. Benchmarks show high performance in symbolic logic puzzles and error-tolerant environments, with reduced hallucination rates and FLOP counts compared to transformers. The system is designed for long-term AGI deployment in critical applications: smart cities, healthcare, quantum simulation, and ethical robotics. The preprint includes Python pseudocode, design diagrams, empirical benchmarks, and a 2025–2035 roadmap for open-source development and industrial pilots. 📄 For licensing or research collaboration inquiries, contact: blankertjp@gmail.com DOI:10.5281/zenodo.15928055 Keywords: AGI, symbolic reasoning, topological AI, modular systems, emergent computation, ethical AI, SLI, M-MAIL, Belief Topology, interpretability