My research (ML for binary function recognition) uses obfuscation and diverse compilation for data augmentation.

Intuitively, obfuscation is a form of anti-optimization. My hope is that it's differentiable, so perhaps given enough knowledge of obfuscation, an ML model can make corresponding optimizations to "undo" them, then for more performance, apply those same un-obfuscations to code that hasn't already been obfuscated.