Probabilistic Decision Models: AI That Returns Typed Decisions with Confidence - Paper Compute Concepts
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A probabilistic decision model evaluates application state against answers declared in advance and returns one of them with a probability. This page covers how decision models work, how they differ from rules, classifiers, and generative LLMs, why calibration is the load-bearing property, how confidence thresholds turn decisions into automation policy, and where a decision model sits in an AI gateway.