Did you know that Java for instance, was originally designed to run on interactive TVs? But then, Java run on many type of devices and in broad range of use-cas

Did you know that Java for instance, was originally designed to run on interactive TVs? But then, Java run on many type of devices and in broad range of use-cases (maybe with the exception of TVs :-)). The original niche for which a programming language is designed may or may not be indicative for what it is used in the end. Julia strikes a very good balance between performance, flexibility (macros) and ease-of-use (default type inference). I won't be surprised if there are other niches outside of scientific computing where these characteristics are desirable. The biggest obstacle I see for the adoption of Julia outside of the scientific computing realm are the latencies due to compilation. There are already 3-party solutions for this (like PackageCompiler{X,}.jl) but imho they are not robust yet enough for widespread adoption, but this might be about to change when different effort join forces [1]. [1] https://github.com/JuliaLang/PackageCompiler.jl/pull/304 https://github.com/JuliaLang/PackageCompiler.jl/pull/304