[ddragon]

Sorry, you're right in that Julia is written in C/C++, so everything Julia does can be solved in those by writing a language (like Julia itself, and not unlike Tensorflow original interface) and compiling it on demand and finding a way to eval the new code and recover the results. I was talking along the ways of how to make it sort of convenient (at least viable to implent unlike the former), as an extension to the C++ compiler itself where you can just tell the compiler what stays AoT and what is JIT'd but otherwise keep the same C++ syntax.

Not to mention if you want to reimplement Julia's logic in C++ you'll have to develop it's sophisticated type inference, since Julia compiler is so aggressive that it will compile at once entire blocks of program (the entire program if it can) as long as it can infer what types are used downstream, which is why it can compete with AoT compiled languages (it's basicaly a "Just Ahead of Time Compiler")