When Reality Outpaces Cognition: A New Scaling Principle for Reliable Intelligence

arXiv:2610.20764v1 Announce Type: new Abstract: This paper challenges the understanding capabilities of existing AI paradigms and emerging world models by asking a fundamental question: How quickly can reality change before an intelligent system can no longer reliably perceive, reason, and act? We formulate this as a theory- and model-agnostic challenge in which systems must infer reliable actions for increasingly distant future states across a growing observation--reality gap. We operationalize this challenge through the effective Speed of Coherent Cognition ((S_C^{eff})), defined as the highest tested Speed of Reality ((S_R)) through which a system continuously satisfies a predefined behavioural reliability criterion from baseline. As a proof of concept, reinforcement-learning agents are trained at the baseline (S_R) and evaluated, without retraining, as (S_R) is increased by up to (50imes) while computational resources remain fixed. We compare Transformer and gated-MLP baselines with (Co^4), an architecture inspired by cellular mechanisms implicated in conscious processing and awake thought. Across the tested scenarios, (Co^4) achieves substantially higher (S_C^{eff}) than the baselines, motivating (S_C^{eff}) as a new benchmark and the scaling of coherent cognition as a principle for reliable AI.

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Source: arXiv cs.AI | 2026-10-16