[mcilai]

(ml expert here) This doesn't seem true. Neural networks are great at detection, so they should be similarly good at determining whether two objects are identical or not. The fact that their networks didn't do better than chance (as opposed to a "disappointing 10%" error rate") suggests that they trained their networks wrong.

[BugsJustFindMe]

non-ml-specific computer vision expert here

There's only one problem in computer vision, and it's not unique to the field at all: balancing sensitivity vs specificity. Modern applications of ML don't solve that.