Space Regulatory Glossary AI & Data Science

fine-tuning

noun

1. The process of further training a pre-trained AI model on a domain-specific dataset to improve its performance on targeted tasks. Fine-tuning adjusts the model's weights to better handle specialized vocabulary, document formats, or classification categories.
2. For regulatory AI, fine-tuning trades off against RAG and prompt engineering: it can improve extraction accuracy on known document types but requires curated training data, risks overfitting to historical formats, and must be repeated when the base model is updated.

Related terms

large language model A neural network trained on large text corpora that generates, summarizes, and reasons about natural language. Models… inference The process of running a trained AI model to produce outputs from new inputs, as opposed to training the model.… retrieval-augmented generation An AI architecture that grounds a language model's output in retrieved source documents rather than relying solely on…

Browse all terms in the Space Regulatory Glossary →