I appreciate the insight! I’m new to ML (coming from the bio research side of things) and trying to keep up.

Any papers or models you could point to using this for a specific purpose?

I guess it’s a matter of how you define unsupervised, but isn’t SSL closer to supervised learning because there’s a ground-truth to compare the prediction to? Whereas if you’re just clustering some high dimensional data, you might not know what the “true” or most accurate way of clustering that information might be, especially in something like genomics where there’s a lot of information that has an unknown purpose.

That seems like it would be hard to prove, given how commonplace braces are among wealthy populations who would probably not be malnourished.