A foundation model is a large-scale AI model trained on broad, diverse data and designed to be adapted to many downstream tasks. Adaptation happens via fine-tuning, prompting, or API access. The term was coined by Stanford's Center for Research on Foundation Models in 2021 and now describes GPT-4, Claude, Gemini, Llama, Mistral, and similar models that form the base layer of the modern AI stack. The foundation model is to AI applications what AWS is to web applications: shared infrastructure that powers everything built on top.
What distinguishes foundation models:
Scale: hundreds of billions to trillions of parameters. Trained on hundreds of billions to trillions of tokens of data.
General-purpose training: trained on broa...