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Comment on High Performance Numeric Programming with Swift: Explorations and Reflectionsparent

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Jeremy, if you're up for it, could you talk any more about your explorations of Julia?

I see (and agree with) your point about worse non-numeric stuff, but if you stand back and squint I get the impression Julia does most of what you applaud here, with the added benefits of a more transparent compiler and a more numeric-focused community (no need for BasicMath there!).

In particular, Flux.jl seems like a fairly direct competitor of S4TF, and this blogpost [0] really blew me away.

[0] https://www.julialang.org/blog/2018/12/ml-language-compiler

The post says Julia is not good for general purpose programming. I think it is good for that, it's just that it does not have as many packages as Python, that's all. I will offer one reason, Julia syntax is actually very much like Python's in many respects. So how can Python be good for general purpose programming but Julia not? So if the sentence is more like, Julia doesn't have as many packages for general programming then I think it's more precise

That sounds totally fair. I haven't used Julia for a couple of years so my comments on it are dated and not well informed. Everyone I know that uses Julia nowadays loves it.

Flux.jl does look terrific. Frankly, part of my interest in this little Swift research project was to pick something that's not at all well explored, and try to dig in to it.

Julia is much more mature for machine learning than Swift at this point. So it would be a better choice if you want something that's at least somewhat ready for use now - but I was really wanting to get in on the ground floor on something that's just getting started.

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