Abstract
Current Large Language Models (LLMs) suffer from a fundamental problem:
hallucination
- thegeneration of plausible but factually incorrect information. We present BTRS (Babylon TowerReasoning System), a novel layered knowledge architecture that eliminates hallucination throughstructured knowledge representation, upward pulse propagation, authority-controlled factverification, and strategic caching mechanisms.
BTRS organizes human knowledge into hierarchical rings (0 to ∞), where each ring serves a specificepistemic function. Information flows unidirectionally upward via "pulse propagation," withconsistency validation at each layer. The system achieves near-zero hallucination rates whilemaintaining computational
Abstract Current Large Language Models (LLMs) suffer from a fundamental problem: hallucination - thegeneration of plausible but factually incorrect information. We present BTRS (Babylon TowerReasoning System), a novel layered knowledge architecture that eliminates hallucination throughstructured knowledge representation, upward pulse propagation, authority-controlled factverification, and strategic caching mechanisms. BTRS organizes human knowledge into hierarchical rings (0 to ∞), where each ring serves a specificepistemic function. Information flows unidirectionally upward via "pulse propagation," withconsistency validation at each layer. The system achieves near-zero hallucination rates whilemaintaining computational
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