I do not get what you are trying to say. Someone is developing an open-source solution that lets you use a vast array of different numerical accelerators more efficiently and with simpler code. All the while the work is done in the open and you can copy any subset if you want to make your own tool. Why is any of this bad?
Maybe the issue raised is that libraries/APIs that define an ABI (Application Binary Interface) can be used from multiple programming languages that share calling conventions. So a question is about how Julialang libraries can be called from other programming languages. The "Embedding Julia" chapter of the manual says that from C there is an interface layer to lookup function objects, box parameters, and call.
As opposed to being trapped in the C++ CUDA API? Julia isn’t that much harder to learn than Python. Does anyone really think the hard part of say, deep learning, is in learning Python or PyTorch?