Contrastive learning pulls positive augmentations together and pushes dissimilar examples apart.

“And what you then do is you have the like positive part which is like the the different augmentations which get pulled together, and the dis uh like the the dissimilar part they get pushed apart. The downside with this is it's ultimately a very very moving target, like a batch to batch moving target. Because”