# Supervised Fine-Tuning **Entity class:** Machine-learning method **Domain:** Artificial intelligence / Model training **Maturity:** Developed ## Definition Supervised fine-tuning adjusts a pretrained model using examples of desired inputs and outputs so that its behavior better matches a target task or style. ## Mechanism and significance It teaches patterns of response but does not by itself guarantee truthfulness, robustness, or obedience outside the demonstrated distribution. ## Relationships - **Research dossier:** [[research/ASI and RSI Timeline Research Moonshots|ASI and RSI Timeline Research Moonshots]] - **Ontology route:** [[ASI and RSI Timeline Ontology#AI Control, Law, and Alignment|AI Control, Law, and Alignment]] - **Primary fields:** [[AI Control]] · [[AI Safety]] · [[AI Infrastructure Consent]] - **Adjacent concepts:** [[Criminal Penalties for Recursive Self-Improvement]] · [[System Prompt]] · [[RL-Based Alignment]] · [[Machine Interpretation of Intent]] ## Sources and provenance - [[research/ASI and RSI Timeline Research Moonshots|ASI and RSI Timeline Research Moonshots]] — immediate source for this node's role in the broadcast research map. ## Evidence boundary The research dossier establishes why this entity or concept belongs in the Moonshots ontology. Time-sensitive organizational, product, policy, and performance claims should be checked against the linked primary source or a current authoritative source before reuse as settled fact.