Foundation models (FM) are deep learning models trained on vast
quantities of unstructured, unlabeled data that can be used for a
wide range of tasks out of the box or adapted to specific tasks through fine-tuning. Examples of these models are GPT-4, PaLM,
DALL·E 2, and Stable Diffusion.
Definitions – Foundation models (FM)
