Why Swift for TensorFlow?
It's interesting how it's going to play out. On one hand side, Swift is a pleasant language to work with (despite its infancy). But on the other, having a Tensorflow API doesn't suddenly give it a bunch of libraries for statistics, comp. vision, modeling, visualisation, etc. that Python/R/Julia <i>cough</i>MATLAB<i>cough</i> have.<p>Nowadays, it's difficult enough to convince people to drop e.g. MATLAB for R or Python for Julia (let's assume that there's some merit to it), despite them having excellent counterparts for almost everything. Swift's success in this domain depends solely on the adoption by developers/researchers/engineers. Unless they're just going to mostly use it internally (as Google is known to).<p>Which brings me to the last point - why on Earth would they pick Swift (apart from Christ Lattner being involved) when Julia was on the table? It ticks all their boxes and has more mature ecosystem for all things "data". Provided rationale is hardly convincing.