> Julia's potential ability to run on mobile, front end web,...
Julia is designed for interactive, exploratory scientific programming, like Matlab and R. I don't see any reason someone would want to do that on a phone or in a web browser when it already runs natively on a PC. Then there's the matter of Julia being designed to interface efficiently with optimized native C/Fortran libraries.
This. Scientific computing is not interested in running in web browsers.
As a former neuroscientist, I occasionally had connectivity analyses that would take 3 weeks to run. No way would I risk slowing it down with anything unnecessary. A 25% slowdown for using VMs in the browser would mean milliseconds for users and days for me.
R's "shiny" is a counterpoint. Obviously something that takes a week to run isn't going on the web. But a complex model and visualization that can be incrementally updated quickly and in real time? That would be cool.
+1 for this! For large programs -- server side Julia, but having browser native Julia via WebAssembly would make visualization and interactive analysis for data science fantastic. Performance of running large GUI applications and libraries would be much faster since WebAssembly could take advantage of the huge amount of work done for optimizing JS by tiered interpretation/JIT'ing.
I agree there's value on the visualization side. Most scientists still do a poor job of sharing results to the public and other scientists (other than by printed images in your article...)
I understand why some may see Julia as 'designed for scientific computing', but this is mostly a reflection of the work that's been put in to build up the library ecosystem. Julia could end up being a good general purpose language too, the only thing holding it back from this is the lack of library diversity and size.
Julia is designed for interactive, exploratory scientific programming, like Matlab and R. I don't see any reason someone would want to do that on a phone or in a web browser when it already runs natively on a PC. Then there's the matter of Julia being designed to interface efficiently with optimized native C/Fortran libraries.