[aivosha]

One can always fork python to keep it "general" if it ever comes to that. In fact I would argue both ML and non-ML domains would benefit from that fork. The reason python is used in ML is not because its intrinsically good for it, but because it happened to have a good set of libraries and community at the right time and place. Having specialized subset of python fine-tuned/"compiled" for ML would be a good path for it as a product to evolve towards. I would not mind having all kinds of ML related, algebraic operations as part of the language so the code reads more naturally. And not only that, all frameworks have to support that language and thus become much more interchangeable. Just like you can have CPython and pypy and others that converge into the same language, imagine the same thing with TensorFlow, PyTorch and alike converging to a singe language that support builtin ML-operations.