Eh, not really in the data wrangling and machine learning space, at least not quite yet. It's not really amenable to writing libraries for numerical processing - it ends up being super tedious to write something like numpy (you have to implement for every data type, there's at least a dozen+) and nigh-impossible to write an API like pandas, because dataframes are just too dynamic. You could do these things, but it's just super unpleasant.

I'm hoping generics makes it easier to write things like numpy, without doing `meao_u8`, `mean_u16` etc.

+ there's bool, int/uint8,16,32,64, float32/64, complex64/128, that's 13 right there, plus object, a bunch of extended sizes on some architectures, and c-alias types.