This is interesting, but because of the growth of the number of ML frameworks and languages, when new ones pop up it would be great for them to release methods to transfer existing models to their language. I would love some extra compatibility with AWS for deploying deep learning models in prod but since I already have existing models running in production, it's a hard sale for me to re-train and re-implement from scratch existing work.
Recently there is more and more initiative to have standard format in deeplearning environnement.
dlpack for tensor format (https://github.com/dmlc/dlpack)
onnx for saved NN (https://github.com/onnx/onnx)
and tvm for execution (http://tvmlang.org/2017/10/06/nnvm-compiler-announcement.htm...)