Swift for Tensorflow has started to attract people with Data Science background to Swift, however, for the ecosystem to thrive there needs to be basic libraries other than Tensorflow. This brings up a couple of questions:
Should Tensorflow be the defacto matrix library? S4TF operations on CPU can be way faster than Python's Numpy, not sure why but some test I've done show that S4TF uses all the cpu cores while numpy used only a few. However, I am not sure if S4TF Tensors can be flexible enough, even when running on the CPU backend, for applications such as generic image processing. In other words, could you do anything that numpy can do with S4TF Tensors on the CPU?