What is artificial intelligence model post-training?
Definition
Artificial intelligence model post-training changes model behavior after pretraining. Techniques can include supervised fine-tuning, preference optimization, reward-based learning and other forms of adaptation using curated task examples or feedback.
Operational traces can make post-training more relevant to a specific business, but they may contain sensitive data and correlated mistakes. Teams need consent, provenance, redaction, evaluation and separation between training examples and independent test cases.
Acronyms and aliases
AI model post-training acronymmodel post-training variant
Related terms
Frequently asked questions
How is post-training different from pretraining?
Pretraining learns broad patterns from large datasets, while post-training adapts behavior using narrower examples, preferences, rewards or domain-specific data.
Can private operational data be used for model post-training?
Yes, when authorized and protected, but organizations must manage privacy, rights, security, provenance and independent evaluation carefully.
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