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Personally, I really enjoy the design and level of abstraction that Pytorch provides. FastAI has always felt too abstracted and trying to go outside the bounds of it gets really hard and complex, really fast. I glanced through the paper and while it certainly looks interesting and to be an improvement, I am not very convinced that doing custom things will be easy, like it is with Pytorch. My experience has been that it is easy, if you already understand all the pieces of the entire library, which is not an easy task at all.

That being said, I admire the passion and effort that goes into FastAI and I think it does a great job at providing an entry point into the world of ML/deep learning that is far more accessible to people. I'll probably still read through the library because I always pick up interesting ideas and learn new things when reading other peoples code, especially when a lot of thought has been put into structuring a library.

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