AI Fundamentals

Foundation Models

Large AI models trained on broad data that can be adapted to many downstream tasks. These models serve as a foundation for building specialized applications through fine-tuning or prompting.

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Fine-tuning
Continuing to train a pretrained model on a task-specific dataset to change its behavior, style, or domain knowledge. Techniques range from full fine-tuning (all weights) to parameter-efficient methods like LoRA and QLoRA that update only small adapter layers.

Also referenced: Large Language Model, Transfer Learning.

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Foundation Models is part of the AI Fundamentals vocabulary used in the Generative AI Maturity Framework. See the full glossary for the complete set of 149 defined terms, or take the free maturity assessment to see where your organisation stands.

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