> In the end, code doesn’t make software – people and communities do... It’s hard to beat an incumbent, and even harder to do so without having a large target user community you can capture with a compelling use case.
We need a better name for the category of Machine Learning Workbench tools that include Julia, R, and NumPy+ (the ML ecosystem that uses Python as an Internal DSL). The compelling use case for Julia is that it is a modern language built on top of the LLVM platform (like Rust and Swift). There is no shame in not winning when you were late out of the gate; see the story of ARM. The value proposition hasn't disappeared it just didn't outpace the evolving bricolage of NumPy+ and its new complementers (Jupyter, PyTorch, TensorFlow).
[1] http://webcache.googleusercontent.com/search?q=cache:Awfh5p8...