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by ddragon 2603 days ago
I upvoted it not because because I use Swift (or intend to use it) but because I find it interesting that the concept of differentiable programming is pushed further and further. Having a host language being used to write and compile a second language (which is implemented in a third language) just feels restrictive in many ways.

I do think what is being done with Julia, Cassette, Flux and Zygote more interesting since it's Julia all the way down (while Tensorflow's backend is still C++) and the compiler work is focusing on not being specific to one implementation or technique, but allowing any such language extensions (such as auto-parallelization and other forms of source to source transformations) to be done by any 100% Julia library. So if Tensorflow for Swift (regardless of the actual reasons behind the choice of the language) proves that the technique is a significant upgrade over what currently exists, it could spark interest in the competing approaches, and I think Julia can help pushing the concept even further.
1 comments
itsmuriuki 2602 days ago
"I like Swift and all but our ML/DL/RL/DS tools and libraries are in Python (and occasionally R"

the python interoperability allows you to use all python libraries but in swift

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ddragon 2602 days ago
In the perspective of someone who writes Julia, which can also call directly any Python method (and R, Fortran, C and C++), that's a nice stopgap, but you really want a true native ecosystem. Not only there is more mental effort dealing with two languages at the same time (which might lead to people just use Python in the first place), the whole purpose of Swift for Tensorflow is having a language with first class differentiation support, which is pointless when the ecosystem is fragmented in multiple languages.

And there is the risk that the community simply ends up considering that good enough and just make wrappers (since it needs a lot of work to create something nearly as good from scratch). Thankfully that didn't happen with the Julia community, and the key is probably making the creation of the tools much easier so they can catch up to mature but constantly evolving environments.

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