The Language Funnel Hypothesis: A Unified Mechanistic Framework for Biological and Artificial Intelligence Acquisition

This paper introduces the “Language Funnel Hypothesis” as a mechanistic framework for second language (L2) acquisition, analogizing continuous second language (L2) input to “sand” flowing through a cognitive funnel, while consolidated L2 representations emerge as “stones” at the narrow end. Input is quantified as energy-like “sand volume,” modulated by work weight (intensity/focus), L1 interference (as a competitive denominator), activation thresholds, and temporal variance (signal instability). By deriving equations for effective activation intensity and variance-weighted consolidation rates, the model mathematically accounts for the inefficiency of fragmented learning and the nonlinear dynamics of bilingual competition. Five falsifiable predictions are proposed, including threshold-driven zero consolidation under persistent L1 dominance, variance-locked efficiency collapse, and high-weight-driven acceleration of consolidation. The framework bridges psycholinguistic interference theories with dynamical systems and information-theoretic approaches to learning, offering testable implications for input optimization in L2 pedagogy, cognitive modeling, and broader artificial intelligence alignment.