Did #julialang end up kinda stalling or at least plateau-ing lower than hoped?
I know it’s got its community and dedicated users and has continued development.
But without being in that space, and speculating now at a distance, it seems it might be an interesting case study in a tech/lang that just didn’t have landing spot it could arrive at in time as the tech-world & “data science” reshuffled while julia tried to grow … ?
Can a language ever solve a “two language” problem?
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@tschenkel @astrojuanlu @programming
I’d suppose part of the problem might be that there’s a somewhat hidden 3rd category of user that “feels” whatever added complexity there is in a two-language lang like julialang and has no real need for performant “product” code.
And that lack of adoption amongst this cohort and your first enforces lang separation.
I may be off base with whether there’s a usability trade off, but I’d bet there’s at least the perception of one.
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@maegul
Considering, it may be worth highlighting that tools like Jax exist as well (https://github.com/google/jax). These have even become an expected integration in some toolkits (e.g., numpyro)
It may not be the most elegant approach, but there’s a lot of power in something that “mostly just works and then we can optimize narrowly once we find a problem”
It doesn’t make a solution that solves this mess bad, but I do wonder about it being a narrow niche
@tschenkel @astrojuanlu @programming
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@tschenkel
Mostly its advantage as far as arrays go is its ability to push things out to an accelerator (GPU) without making code changes. Also its JIT functionality is a good bit faster than using pytorch’s (at least anecdotally).
My experience with it is not at all related to ODEs (more things like MCMC) and I have no direct experience with its gradient functionality and only limited with its auto vectorization, so take my experience with a grain of salt.
@maegul @astrojuanlu @programming
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@tschenkel @astrojuanlu @programming
I understood … I was reaching for some shorthand (500 char limits FTW!)
There’s probably a good amount of work that exists somewhere between your needs and “could be a spreadsheet”, where caring about performance isn’t an issue or hasn’t surfaced yet, either practically or culturally (where the boundaries of what research *can* be done “tomorrow” are of importance)
BTW, cheers for all the info!!
@tschenkel @astrojuanlu @maegul @programming I completly agree with your second point.