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Technical implementation · AI Search Infrastructure

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Definition

Temperature is a parameter that controls the randomness of an AI model’s outputs during inference. A low temperature produces more deterministic, predictable responses; a high temperature produces more varied and creative outputs. Most AI search systems operate at low temperatures to prioritize factual accuracy over creative variation. Temperature helps explain why AI search responses are relatively consistent across repeated queries — the systems are tuned for reliability, not variety. For brands, this means that a negative or inaccurate AI representation of a brand is not random — it reflects what the system is consistently most confident about. Fixing a bad AI representation requires changing the underlying signals the system draws from, not hoping for a different random output.

Inference

Foundation model

Grounding

Hallucination mitigation

RAG

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