Thanks everyone... it's super helpful to read your comments. @Tim: ok, that makes sense and is clear. I think I was worried the language would have a jumble of commands (not just in those categories you list) which subtly fused variables in memory. Your comment helps me reason about it.
@Tobias: Yep, I agree the scalability of the language is key. I was just hoping that we could do this while also keeping the ability of non-programmers to start reasoning about Julia code immediately. I definitely don't want to suggesting Julia look like Matlab or R ... I just want variable assignment and functions (at the high-level prototype stage) to behave in a way that a scientist/mathematician/statistician would expect. BTW: when I first tried to break from Matlab and use Numpy I spent a full two days on a small project that ended up being completely wrong because of the shared memory issue that I didn't realize at first. I was scarred, hence my sensitivity to the issue:) Again, thanks a ton and keep up the good work.
