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What I mean when I say that machine learning in Elixir is production-ready

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Re: What I mean when I say that machine learning in Elixir is production-ready

#11

Post by notarobot123 »

cmdrk wrote: post #8
ambicapter wrote: post #3

I see so much breathless adoration for Erlang and Elixir, how come it hasn't taken over the world in all this time?

take a look at the Who's Hiring threads - despite the love the BEAM gets on this website, it seems very few folks are brave enough (or public enough) to hire Erlang/Elixir/Gleam/etc engineers. I've seen one or two Elixir jobs each posting and zero Erlang jobs in the last 6 months or so of Ctrl-F'ing the posts as I see them.

It sounds like Elixir might be a competitive advantage for attracting talent for the companies that do actually use it (much like python in the mid-2000s[0])

[0] - https://paulgraham.com/pypar.html

Re: What I mean when I say that machine learning in Elixir is production-ready

#13

Post by arter »

ambicapter wrote: post #3

I see so much breathless adoration for Erlang and Elixir, how come it hasn't taken over the world in all this time?

Just because it hasn't taken over the world it doesn't mean it's proponents adorations are baseless ?

I agree that the article falls flat on providing descriptive reasons how Elixir compliments machine learning. But that shouldn't be an argument against the product, but rather against it's cult following that does not provide sufficiently detailed and advanced examples and explanations. Something extremely common in tech journalism.

Good ideas and technologies do get underappreciated and wide spread adoption I would wager is not at all correlated to quality. Javascript, c++, java and others are good examples. Yes they have taken over the world at one point, but there are better designed languages out there. It just seems that people don't want to relearn a new paradigm and you can write software on anything.

Re: What I mean when I say that machine learning in Elixir is production-ready

#15

Post by indigo0086 »

ambicapter wrote: post #3

I see so much breathless adoration for Erlang and Elixir, how come it hasn't taken over the world in all this time?

Same reason you don't see taken over the world. The demands of the world are different to the demand of small passionate communities.

Re: What I mean when I say that machine learning in Elixir is production-ready

#16

Post by peoplefromibiza »

arter wrote: post #13
ambicapter wrote: post #3

I see so much breathless adoration for Erlang and Elixir, how come it hasn't taken over the world in all this time?

Just because it hasn't taken over the world it doesn't mean it's proponents adorations are baseless ? I agree that the article falls flat on providing descriptive reasons how Elixir compliments machine learning. But that shouldn't be an argument against the product, but rather against it's cult following that does not provide sufficiently detailed and advanced examples and explanations. Something extremely common in…

> how Elixir compliments machine learning

one simple example: what Jose Valim calls Distributed²

You can have a livebook (similar to notebook, but distributed and live) and distribute your load not only on multiple GPUs on your machine, but on multiple GPUS on multiple machines

with basically zero effort

https://www.youtube.com/watch?v=MSMyRBJAoSs

Re: What I mean when I say that machine learning in Elixir is production-ready

#17

Post by hello_computer »

ambicapter wrote: post #3

I see so much breathless adoration for Erlang and Elixir, how come it hasn't taken over the world in all this time?

Elixir is a combinatorics mess (circa 2020: two different string types, three different types of exception, return AND throw versions for almost every func, slow compiler without much in the way of compile-time checking, constant breakages over trivial renamings "just because", having to burrow into erlang errs half the time since many elixir funcs are just wrappers). Half the libraries we used were abandoned. I take every recommendation with a grain of salt. I think people got invested in the hype, and are trying to keep the sinking ship afloat.

Erlang is a different story. If you're interested in the BEAM, it isn't terrible. It has a few of the same problems, but the combinatorics are reduced.

Re: What I mean when I say that machine learning in Elixir is production-ready

#19

Post by ambicapter »

macintux wrote: post #7
ambicapter wrote: post #3

I see so much breathless adoration for Erlang and Elixir, how come it hasn't taken over the world in all this time?

Inertia: curly braces rule the world. Imperative/OO programming are ubiquitous, FP not so much. Corporate sponsorship: even with curly braces and mutability, Go probably wouldn't have gained its mindshare without Google. Performance: It's getting much better, but the BEAM was never designed for maximum performance. People don't like slow platforms, despite the other advantages. Scale: much like one of the databases w…

> Performance: It's getting much better, but the BEAM was never designed for maximum performance. People don't like slow platforms, despite the other advantages.

> Scale: much like one of the databases written in Erlang, Riak, you typically don't need a BEAM language until your solution is large enough that you've already written it in something else.

These two seem to contradict one another. How can it not be fast but scale well (I'm thinking of a way as I type this but I'll let you answer)?

Re: What I mean when I say that machine learning in Elixir is production-ready

#20

Post by jerf »

ambicapter wrote: post #3

I see so much breathless adoration for Erlang and Elixir, how come it hasn't taken over the world in all this time?

https://news.ycombinator.com/item?id=34546143

https://news.ycombinator.com/item?id=7277957

And also "taking over the world" is generally a larger task than people realize. C is still fairly strong, and at this point it is basically the baseline against we programmers issue our complaints, with only rare and very contrarian compliments given to it... yet there it is. Language turnover is really quite slow.

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