I have made the same rants about numeric computing language issues as the Julia creators. I would avidly adopt Julia based on the documentation on the website.

I have made the same rants about numeric computing language issues as the Julia creators. I would avidly adopt Julia based on the documentation on the website. It seems to me that this is a beautifully conceived language given the concerns it attempts to address. Amazing even if the performance never improves. The R thread on the dev list gives an accurate representation of the obstacles to Julia being widely adopted, however. One might become very unhappy while using R, but sometimes you have to use it, because something you want is only in R, due to the ubiquity of that tool for stats. If Python, which does not have that many disadvantages besides not having been explicitly designed to appeal to users like me, cannot unseat Matlab and R, Julia will have a difficult time. But I will give it a try, and will implement some simple but core algorithms that I use a lot. Another idea to test Julia's usefulness would be to port a tool like Waffles to Julia. In my opinion implementing such a sensible tool like Waffles in C++ is a heartbreak.