AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Description The preceding papers in this series argued that explainability cannot ground accountability in probabilistic AI systems, that hallucination is the expected epistemic consequence of forced answer generation, and that accountable AI therefore requires a formal system language of non-decision, decision boundar...
Large language models are commonly evaluated by the quality of the content they generate. This paper argues that this focus is fundamentally misplaced. In probabilistic systems, content quality is a secondary property; the primary determinant of meaning, reliability, and trustworthiness is the existence of explicit pri...
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