> "Because Julia’s compiler is different from the interpreters used for languages like Python or R, you may find that Julia’s performance is unintuitive at first. If you find that something is slow, we highly recommend reading through the Performance Tips section before trying anything else. Once you understand how Julia works, it’s easy to write code that’s nearly as fast as C."
If Julia needs a "Performance Tips" section to produce fast code, I might as well use Python.
The "speed" from Julia comes from LLVM, but there is nothing stopping Python to use LLVM as well where it _makes sense_ (which is the case with XLA in TensorFlow, for example).
I see no plus value in learning Julia over existing tools, there is nothing revolutionary or nothing that could alleviate future risks.
If Julia needs a "Performance Tips" section to produce fast code, I might as well use Python.
The "speed" from Julia comes from LLVM, but there is nothing stopping Python to use LLVM as well where it _makes sense_ (which is the case with XLA in TensorFlow, for example).
I see no plus value in learning Julia over existing tools, there is nothing revolutionary or nothing that could alleviate future risks.