> To put it plainly, if you don't have enough data to train a machine learning model, what, exactly, are your options? There is only one option: to do the work by hand. Wikipedia, with its army of volunteers, has a much better shot at getting results this way than any previous effort.

The training data for machine translation models is also human-created. Given some fixed amount of human hours, would you rather them be spent annotating text that can train a translation system that can be used for many things, or a system that can just be used for this project? It all depends on the yield that you get per man-hour.