The Bayesian Reflex: A Predictive Coding Engine for Artificial Intelligence

• URL: http://arxiv.org/abs/2608.00492v1
• Date: Sat, 01 Aug 2026 07:32:39 GMT
• Title: The Bayesian Reflex: A Predictive Coding Engine for Artificial Intelligence
• Abstract summary: This paper introduces the Bayesian reflex, a computational framework that directly instantiates predictive coding through three pillars.<n>We show that recent breakthroughs provide the missing algorithmic ingredients.<n>The resulting framework enables mathematically principled, scalable, and brain-inspired continual learning, perception, and decision-making.
• Score: 1.2183405753834562
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Predictive coding offers a powerful theory of cortical computation, but corresponding scalable algorithmic implementations for artificial intelligence have remained elusive. This paper introduces the Bayesian reflex, a computational framework that directly instantiates predictive coding through three pillars: belief maintenance via hierarchical generative models, sequential Bayesian updating via prediction-error minimization, and uncertainty-driven action via active inference. We show that recent breakthroughs---ellipsoidal decomposition for exact $i.i.d.$ sampling, recursive Gaussian processes for deep hierarchical inference, and derivative-aware Bayesian optimization---provide the missing algorithmic ingredients. The resulting framework enables mathematically principled, scalable, and brain-inspired continual learning, perception, and decision-making. We illustrate its versatility through applications ranging from climate model evaluation to prime number discovery, offering a blueprint for truly adaptive artificial intelligence.

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