Figure 2. Pipeline for training vision foundation models using contrastive (A) and generative (B) self-supervised learning (SSL). In the contrastive SSL example, the pretext learning task involves applying random image augmentations and training a model to maximise the agreement of matching image pairs. In the generative SSL example, the pretext task involves masking areas of an image and training a model to reconstruct the missing portions. In both cases, the model learns general imaging features applicable to multiple downstream tasks.