Foundation Model

A foundation model is a large neural network pre-trained on broad data and designed to be adapted to many downstream tasks.

What is Foundation Model?

Foundation models are trained once on very large corpora and then re-used. Adaptation happens through prompting, retrieval augmentation, or fine-tuning. Examples include large language models, vision-language models, speech models, and multi-modal models. Vendors host them as APIs or release them as open weights. The term was popularised by the Stanford CRFM in 2021 and is now central to the EU AI Act, which defines specific obligations for general-purpose AI models.

How does Foundation Model apply to enterprise AI?

Enterprise AI systems are usually built on top of a foundation model rather than training from scratch. The buyer choices that matter are vendor, model family, hosting region, version pinning, and whether prompts and outputs are retained.