http://docs.julialang.org/en/release-0.5/manual/noteworthy-d...
At the highest level, Julia operates on all of the elements of a matrix for each operation, is 1-based, assigns by reference, is case-sensitive, has the range operator (:) like python, but doesn't allow negative indices to read from the end.
Now for some get off my lawn:
In terms of learnability from easiest to hardest, I would rank them:
Python
MATLAB
Julia
R
I'm still hoping for a pure functional language that operates on matrices and doesn't introduce a lot of non-imperative operators and terminology. For example closures with immutable data gets us a fair part of the way to Clojure, without the learning curve. For the most part I've given up on ever learning Erlang, Haskell, Scala, etc even though I know Scheme. Maybe F#, I dunno. I feel that Rust is one level of abstraction beneath my pain threshold. Swift is too micromanagy when it comes to nulls. Javascript has abandoned its scripting roots to regress back towards C++ and its new syntactic sugar isn't helping things. I really want to like Go but worry it will be superseded by a truly concurrent language running on video cards with automagic error handling. I've given up on CUDA and OpenCL due to their roots in OpenGL, because their metaphors are too cumbersome compared to MATLAB. C++ and PHP are still my most loved and hated languages because they do everything wrong but excel at things like performance and laziness. In the end, these are my primary goals.