[gtycomb]

OP likes Swift and he compared it to other languages Python, Go, C++ & Rust, Julia. In the enterprise sphere that I am in, I haven't seen Swift and its hard to move a team in this direction at this point.

Python already drives a significant market and captured talent in numerical differentiable programming, particularly because of the ease with which prototyping and tuning is done with it. Obviously when we want to scale we have the conversation on some other option.Personally its a bit frustrating that Go support for TensorFlow or one of the competitors is not quite satisfactory and this is surprising, I can't explain it.

Instead of inventing any new language why don't one of you -- Python, Go, C++ & Rust, Julia, or Swift -- complete the job with end-to-end differentiable programming. 'Complete' to me means a language level seamless GPU (or related distributed/parallel architecture) and language level deployment ease (the kind of thing done with Kubernetes) and integration with embedded hardware.