Very interesting. They are baking auto differentiation/gradient computation directly into the compiler ? How will this be work, since you invoke TF and TF computes gradients (at least on the loss functions) using Python/C++ from first principles.
It'll be nice to use the Xcode build system, but given that Xcode isn't open source, I wonder how this will play out. Is there a way to use Bazel natively with Swift ?
The key thing here is that the Swift compiler is computing gradients using SCT techniques, not TensorFlow. This has a number of advantages that we'll go into in the white paper we are going to publish in April, so I'd prefer to wait until that spells it all out rather than go into detail here.
All this works no matter how you choose to build your code: Xcode, Bazel, SwiftPM, makefiles, whatever. Also, since ML scripts are frequently small, a simple #! script like we showed in the demo is perfectly reasonable for many things.
It'll be nice to use the Xcode build system, but given that Xcode isn't open source, I wonder how this will play out. Is there a way to use Bazel natively with Swift ?
Exciting times though !