ML Syntax seems to be made for machines, not for the average human mind. Parsing language that is 'too unnatural' is a bit of a strain when compared to something that looks like average grammar if you squint at it, so it doesn't surprise me at all.

It's also a bit in the realm of scientific/academic programming vs. real-world bulk programming where it's mostly just CRUD, mapping and business rules. It's all still important if that's how money is made, but as far as I can tell, most programming isn't really all that involved with 'quality languages' and more about feature output from a backlog. If you can do that for cheap with a fresh can of Python developers and some extra EC2 instances on AWS, that's an easy choice vs. someone who might want to do it in Lisp instead for example.