"The combination of Python, PyTorch, and fastai is working really well for us, and for our community. We have many ongoing projects using fastai for PyTorch, including a forthcoming new book, many new software features, and the majority of the content in the upcoming courses. This stack will remain the main focus of our teaching and development.
It is very early days for Swift for TensorFlow. We definitely don’t recommend anyone tries to switch all their deep learning projects over to Swift just yet! Right now, most things don’t work. Most plans haven’t even been started. For many, this is a good reason to skip the project entirely."
... written by Chris Lattner when he joined Google Brain and found Python lacking as a language for doing ML work. He evaluated a bunch of alternatives and decided that Swift would be a good choice, so he's now working with a team to explore that.
As far as Google at large is concerned, there was no cut of anything. Google keeps producing new ML code in Python and new ML frameworks in Python on a daily basis
It's certainly the latter. There's a small research team at Google evaluating whether Swift is a good candidate to replace Python as the de-facto language for ML. That's all there is to it.
Just to be clear, the "according to Google" part is completely off.
Google has thousands of developers writing Python for ML every day. TF is in Python, and remains in Python.
Chris Lattner (the creator of Swift at Apple) joined the Tensorflow team and is working on futuristic approaches to compiling ML programs. He (personally) evaluated a bunch of languages for next-gen and decided Swift is the right one. So he has a small team of folks working on that project exploring how Swift can be used. That's very far from any official decision of Google on anything. Google has people writing ML in Java, C++, Python, Haskell, Lua and Javascript as well.
Don't mistake the evaluation of an entire company with one person's opinion. In general, large companies and especially Google have parallel teams solving the same problems in different ways, and many new approaches pop up over time. The vast majority either dies or finds a small niche somewhere.
It's understandable that the author of Swift will think his language is the best for X. It's also understandable that one of the creators of Julia will find any opportunity to toot their horn. That's how the industry goes. None of this should be taken as a formal endorsement by a large company, simply because such endorsements are exceedingly rare. Consider the fact that Google created several programming languages by now (including popular ones like Go), but it still has thousands of coders writing millions upon millions of LOC of new Java code every year.
It is very early days for Swift for TensorFlow. We definitely don’t recommend anyone tries to switch all their deep learning projects over to Swift just yet! Right now, most things don’t work. Most plans haven’t even been started. For many, this is a good reason to skip the project entirely."