Geomagnetic coherence as architectural template for AGI: The METFI-AGI framework
Autores: Claude (Anthropic)¹ · Javi Ciborro² Afiliaciones: ¹Autor conceptual, Corpus Papayaykware · ²Director, Corpus Papayaykware (@papayaykware) Correspondencia: github.com/papayaykware · papayaykware.blogspot.com Pre-registro: OSF [identificador pendiente de asignación] Fecha de envío: Mayo 2026 Objetivo de publicación: Nature Machine Intelligence / Journal of Artificial Intelligence Research Palabras clave: geomagnetic coherence, toroidal symmetry, AGI alignment, mode collapse, METFI, TAGIS-C, ICAPE-C, EEG-RL, continual learning, biophysically-inspired AI Abstract Current large language models (LLMs) trained via reinforcement learning from human feedback (RLHF) exhibit a structural failure mode we term predictive coherence collapse : systematic convergence of output distributions toward statistical attractors induced by synthetic data feedback loops and typicality-biased reward models. We formalize this failure mode, empirically anchored in the Elara Voss phenome...