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.
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.
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...
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
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.