It is targeted at places where Numerical Scientific computing is required. It's not just Matlab, Julia also targets Python and R where as these languages are us

It is targeted at places where Numerical Scientific computing is required. It's not just Matlab, Julia also targets Python and R where as these languages are used primarily as prototyping languages, Julia's pitch is that are good enough to become a production level code. For that matter even Google in its Tensorflow for Swift article referred Julia's this link. Also another advantage of Julia is its not trying to replace Python or R but to work alongside with them and interoperability. From Swift for Tensorflow doc: Julia is another great language with an open and active community. They are currently investing in machine learning techniques, and even have good interoperability with Python APIs. The Julia community shares many common values as with our project, which they published in a very like-minded blog post after our project was well underway. We are not experts in Julia, but since its compilation approach is based on type specialization, it may have enough of a representation and infrastructure to host the Graph Program Extraction techniques we rely on.