AIBullisharXiv – CS AI · Mar 57/10
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Architectural Proprioception in State Space Models: Thermodynamic Training Induces Anticipatory Halt Detection
Researchers introduce the Probability Navigation Architecture (PNA) framework that trains State Space Models with thermodynamic principles, discovering that SSMs develop 'architectural proprioception' - the ability to predict when to stop computation based on internal state entropy. This breakthrough shows SSMs can achieve computational self-awareness while Transformers cannot, with significant implications for efficient AI inference systems.