They are both doomed because neither is transformative enough to justify adoption. They are going to need to solve much harder problems to do that.

Take Rust as an example. It solved a problem that most people weren’t even paying attention to, because the accepted wisdom said it was impossible.

Haven’t tried Mojo yet but I have tried Julia and it kinda sucked balls. Sorry Julia fans, but it did. My main complaints:

• It’s a research language like MATLAB, so the emphasis is on repl’s, trying things out etc. But the compilation model is like C++. When you import a package it spends like 2 minutes compiling it. I think it’s supposed to cache it but the second time it was still like 10 seconds for me just to import a package. I believe they’ve improved this since I used it but still, huge red flag.
• 1-based indexing. Come on guys. Anyone using this is smart enough to learn 0-based indexing. It’s like putting a steering wheel in a jet fighter because you worry about pilots getting confused by a joystick. Again, red flag.
• The plotting libraries (a core feature for this sort of language) kind of sucks. In fairness nothing comes close to MATLAB on this front. I ended up paying for MATLAB because of that.

There’s also this article which has more reasons.

I am leaving it a while longer before I try Mojo.

Julia mid diff Mojo

Julia no diff Python

Discuss.

Julia better bc parallel computing is easy to write in Julia, metaprogramming is also easy in Julia.