What is a foundation model?
A foundation model is a large AI model: usually transformer-based: trained on broad data at scale, designed to be adapted: fine-tuned, instruction-tuned, or simply prompted into thousands of downstream tasks it was never explicitly trained for. GPT-class language models, image generators and multimodal models are all foundation models; the term (coined at Stanford in 2021) describes the engineering pattern, while EU law regulates the same object as a general-purpose AI model.
Why lawyers care about the pattern
- Value-chain allocation: one company trains the model, another fine-tunes it, a third deploys the product: AI Act duties split across that chain, and provider status can transfer with significant modification;
- Inherited risk: downstream products inherit training-data provenance issues (copyright, TDM opt-outs, personal data) they cannot fully audit, which is why vendor contracts carry the weight;
- Concentration: most of the market builds on a handful of models, making model-provider terms de facto industry regulation.
Related
Large language model, fine-tuning, GPAI rules for builders.
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