That being said, it does make it easier to develop statistically aware web-apps (a particular interest of mine), so that's definitely good.
Not that I know what I'm talking about, I've never used Fortran.
Is it because it would take a long time or because it's inherently hard?
Why do you assume that JS can never be integrated with LAPACK etc.? That's hardly impossible.
And then there is a bias in those benchmarks, see for example the ones for quicksort: in Python they only time the duration of the sort itself, whereas (at least in Julia and JS) they time both the creation of the random array and the time needed to sort it.
Sorry, R, Matlab, Python, Syntax, Fortran have actual libraries for this stuff, JS, no.
Sure, you could achieve the same with a general purpose PL, but you would have to implement everything from scratch.
JavaScript is faster than MatLAB etc in these examples, but as mentioned already it's slower at matrix multiplication and I'm sure that's just one example.
Does JavaScript have tonnes of libs? Does it have type-checking? Does it have all those other things that I would be desperate for if I was performing important calculations? Can I distribute the computing easily? Etc, etc.
Let's stop comparing programming languages as if they're one tool to do one job. Different programming languages have different applications and are suited for different jobs.
