Theoretical synthesis demonstrates an edge-deployable neuro-monolithic intelligence architecture verified via Lean 4, indicating biological scalability in artificial general intelligence.
This monograph presents the formal synthesis of the Neuro-Monolithic Architecture Global Intelligence Framework (NMAGIF). It establishes the theoretical and mathematical foundations for true biological scalability in artificial general intelligence by dismantling the "thin client" paradigm and replacing it with the Fractal Monolith. Package Contents: NMAGIF_Monograph_v_4_2_EN.pdf: Master monograph (150 pages, Stage 10.0 "Sphere Topology" Edition), containing the 12 core chapters and Annexe G (Empirical Telemetry & Visual Atlas, Doc ID: NMAGIF-TR-2026-ANNEX-G-V1). NMAGIF_Lean4_Verification_Release_4_2.pdf: Machine-checked Lean 4 formal verification dossier (25 theorems, 0 sorry, 0 admit) structured into a two-tier epistemic architecture: Tier-1 (11 theorems): Strictly verified discrete solver invariants over R (JKO metric positivity, monotone Burg entropy decay, discrete mass conservation) and continuous hardware epsilon-isomorphism bridge. Tier-2 (14 theorems): Axiomatic domain specifications characterizing the macroscopic non-equilibrium state machine and topological phase transitions. research-dossiers.pdf: Supplementary research dossiers indexing the companion mathematical and experimental corpus. The entire architecture runs autonomously at ~25 Hz on dedicated neural edge hardware with hardware-accelerated tensor co-processing, validated by live smoke tests, mass topology tests, and machine-checked formal proofs. Released under CC BY 4.0.
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Valéry Kourbanov (2026) studied this question.