[anonymousJim12]

I just watched the video and the presenter makes it clear that Google picked Swift ultimately and eliminated Julia from evaluation in previous knockout rounds.

I don't use either and to be honest was surprised that their original set of languages evaluated was C++, Rust, Julia and Swift. Seems like an odd list of languages to start with when discussing ML.

[melling]

You are saying something completely different. Google ultimately picked one language to support. That doesn’t disqualify Alan’s point about Julia.

I found these slides that look like Alan’s from a different talk. The first slide was his point:

https://arpa-e.energy.gov/sites/default/files/2a%20-%20Edelm...

[anonymousJim12]

I am saying something completely different. The presenter in your YouTube link makes it clear that Julia made the cut for evaluation but that ultimately Swift was the only language left standing. The slides make this less clear as they stop before the final knockout round.

I believe this[0] is the "study" the presenter is summarizing, which further makes it clear that Julia did not in fact "make the cut". Put another way, if we are going to argue that Google said Julia makes the cut, we could just as easily make the argument that Rust and C++ made the cut.

[0] https://github.com/tensorflow/swift/blob/master/docs/WhySwif... w

[dragonwriter]

Is it “Google” or a single permission-to-fail R&D team at Google headed by the creator of Swift that focussed on languages with features like those of Swift and ultimately settled on Swift?

Because Google is fairly well known for being a “decide as late as possible, often after multiple competing options from different teams are in place and being used in real signifcant applications” organization.

[nexus7]

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.