Not a great metric either, as models with simpler output (like text embedding models, which output a single number representing 'similarity', or machine vision models to recognize objects) are extensively trained.

Another example is NNEDI3, very primitive edge enhancement. Or Languagetool's tiny 'word confusion' model: https://forum.languagetool.org/t/neural-network-rules/2225