Model architectures
A large model built once on huge amounts of broad data and then reused as the starting point for many different tasks.
Formal
A deep learning model given pretraining on broad data at scale, usually by self-supervised learning, so that it can be adapted - by fine-tuning, prompts or tools - to a wide range of tasks it was not built for.
In plain English
Like a general education that takes years to get, after which a person can learn to be a nurse, a lawyer or a cook in far less time.
In practice
An insurance company's AI lead does not train a model from scratch; she takes a foundation model from a provider and adapts it both to answer customers about their policies and to sum up claim files.
Why it matters
Many products rest on the same few foundation models, so a flaw, bias or weakness in one of them spreads to every system built on top of it.