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Almost all tech decisions come with a set of tradeoffs. I wouldn't trust articles praising certain technology because they are probably ignoring the tradeoffs t

Almost all tech decisions come with a set of tradeoffs. I wouldn't trust articles praising certain technology because they are probably ignoring the tradeoffs that come with it. Elixir is great for a chat application. At the same time it's probably not the right choice for a Machine Learning project. Of course there are a number of absolutes that I look for regardless of the context: * How good is the documentation? * Is it actively maintained? * Is it mature? * etc.

lostcolony 8y ago
Interesting example you chose there. While Elixir doesn't have a "when to use/not to use", it mentions its ties to Erlang quite clearly, and Erlang has this http://erlang.org/faq/introduction.html http://erlang.org/faq/introduction.html, specifically section 1.4, "What sort of problems is Erlang not particularly suitable for?" Relatedly, while I wouldn't use either for many types of ML...I wouldn't use Python either. The only benefit to using Python in this space is it has libraries bound atop C/C++ implementations. Erlang/Elixir doesn't, that I know of, but that doesn't prevent it from being done if someone wanted to. In terms of actually building something from the ground up...well, it depends. It isn't fast...but it does make the concurrency part easy to model ( https://www.amazon.com/Handbook-Neuroevolution-Through-Erlang-Gene/dp/1461444624 https://www.amazon.com/Handbook-Neuroevolution-Through-Erlan... for instance), and for learning/prototyping that might be what you're prioritizing for. Certainly, Erlang/Elixir have seen use in high speed trading and ad bidding platforms, things known for needing low latency.