Foundation Model
A large model trained broadly once, then adapted to many downstream tasks instead of being built per task.
The foundation model idea inverts the old workflow: rather than training a fresh model for every problem, you train one general model at great expense and adapt it cheaply via prompting or fine-tuning. That economics is why a handful of labs train models and everyone else builds on top. The EU AI Act addresses much the same thing under the name general-purpose AI model.
In practice: One base model powering a support bot, a code assistant, and a summariser — all with the same weights.