Comment by eigenspace | Hacker News Reader

Comment by eigenspace | Hacker News Reader

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So you're disappointed that Mike Innes and a handful of other open source contributors haven't quite caught up yet with the efforts of Google and Facebook pouring billions of dollars into TensorFlow and PyTorch in pursuit of one of the most lucrative and hyped modern markets?

Well, for that it depends on what you're into. For traditional, coding bootcamp machine learning, Flux.jl is still behind, but I'd point out that the only high performance, usable NeuralODE library is still built on Flux.jl and DifferentialEquations.jl as far as I understand and mostly consists of some import statements and a few function compositions / overloads. Someone already did deep learning on fully homomorphic encrypteded data using Flux.jl. Many 'niche', cutting edge things are still best done with Flux.jl because Flux is fundamentally more flexible than things like PyTorch and TensorFlow. It's using the entire programming language as a framework in a very generic way that PyTorch and Tensorflow can only ape by building ever more complex custom compilers and DSLs with ever diverging semantics from Python.

If Flux.jl is an example of the Julia community's failures to compete I'd say we have very little to worry about, and I look forward to seeing what a well funded commercial entity could build in Julia with a few billion dollars.

Consider me a curious client who trains and deploys production models on a weekly basis and considers Julia. Well even if I could rewrite our model in Julia how would I go with prod deployment and who would help me if I get stuck? For Tensorflow, I can use Java API and effortlessly plug in trained model into our Java stack. In case of PyTorch we can bring up a Python service with the same little effort just because Python has it all.

When it comes to work, niche languages lose their ground once you start digging deeper and attempt to venture slightly outside their focus domain. They do not have dedicated teams or industrial money and will always lag behind. Look at DL4J, they have a whole company working on it for many years.

Of course time will tell but considering the results so far I am not convinced that investing time into learning a new language will pay off. Especially considering Julia interop with C/C++.

> Especially considering Julia interop with C/C++.

Is the interop bad?

As far as I'm aware, Julia interop with C/C++ is particularly excellent. So, maybe the poster can clarify?

Well, it's been 4 years so maybe it's better now: https://www.zverovich.net/2016/05/13/giving-up-on-julia.html

Well, running "Hello, World" still takes 0.3 ms :D

That is truly the dumbest critique of Julia that's been published. So dumb I didn't bother refuting it at the time, but apparently people take it seriously?

- Hello world is slow? Really? Yeah, it's not a hello-world-oriented programming language.

- One-based indexing is questionable? Troll much?

- Using `ccall` is unsafe? No kidding, there's no way to call a shared library that doesn't crash if you lie to it.

- `@printf` sucks? Then don't use it. I never do. The `print` function works for 99% of cases.

- Julia development is slowing down? Whiffed on that call.

Regarding the C ffi point, you can use Clang.jl to generate correct bindings so that you don't have to read C header files. But note that if you want to call a function in C you need to look at and match its signature, so it's not all that onerous to have to do the same from Julia. Julia's C interop is so good that several other languages have copied it since it came out.

Yeah, but how else would you judge about the language before spending months on learning it? Critique can be dumb like 1-based index for arrays or nitpicking on syntax. However, I tried Julia several years ago and start-up times was the reason I dropped it. Was it a dumb thing to do too? I was disappointed that a promise of being a dynamic language came with some "but"s. And if you have a lot of scripts that you need to run one-by-one, you don't notice the real speed of the language, all you notice is sluggishness.

If one isn't willing to spend some time on learning a language, one simply shouldn't write a scathing blogpost about it.

> So dumb I didn't bother refuting it at the time, but apparently people take it seriously?

You definitely should have because from what I saw during my google searches this idiotic article was mentioned a couple of times.

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