A foundation model is an AI model that is traiuned on a vast corpus of training data of a braid type, but which can be tuned to more specific domians. The earliest examples were large language models, but there are now foundation models for other media, so the term large X model (LxM) is sometimes used. Foundation mdoels are very expensive to create and often very lareg and hence expensive to run. However the ability to tune these models amortises the costs of initial production, and there are techniques to prune the large parameter spaces after training.
Used on Chap. 23: page 574