> A good saw is spec'ed by a woodworker and made by a metalworker. So this is what I see in the TensorFlow for Swift project. If you look at the core contribu

> A good saw is spec'ed by a woodworker and made by a metalworker. So this is what I see in the TensorFlow for Swift project. If you look at the core contributors, you have a team of ML experts, as well as the original creator of the language. It still remains to be seen how it will go, but it seems like the right group of people to go about this effort. > Python has some really high-quality DS/ML tooling built by people who know software and the problem domain. See that's where you lose me a bit. There is a lot of really exceptional work done in Python, but in my view that's in spite of the language. Python strikes me as as a language which has been adopted in the scientific community because it's low barrier to entry makes it approachable to non-expert programmers, but comes up lacking when compared to modern programming languages. Between the version fragmentation, environment management, type system and the nature of runtime errors there are a lot of pain points which are already solved problems in other languages. When I have to work in Python, I am not particularly happy to do so. Maybe Julia solves these problems. But I also wonder whether the scientific/ML community really knows what they're missing.