Can it? So it is not using any Nvidia hardware-specific code?
I'm sure it's using NVidia specific code in terms of libraries to speed up various things like DNN's and Image processing.
But, it's still portable in the sense that they are not completely locked in. They just have to use an equivalent toolkit/library from a different vendor. It might really annoy some software developers, but they're not locked in.
Deep neural networks are inherently machine agnostic. When I train an image classification network on a NVidia Titan X in a Ubuntu workstation I get a model that I can then copy to lots of different machines to run an image classification on. Sure the classification might be really slow if I have to run it in an ATOM x86 processor, but it works. Now that's a really example simple, but it can be extended to more complicated things.
In summary it's a whole new ball game now where it's running a lot more general purpose GPU than before.