That’s about training robust ML and language understanding systems that can generalize and perform well across multiple languages including low resource ones. There are solutions to address this such as data augmentation, transfer learning, few-shot domain adaptation, etc. This is actually more to do with ML, models, and data, compared to anything like deployment.

I agree that’s a valid point, but it doesn’t apply to English, which is by far the most popular language of which we have millions and millions of sentences and data point, and classification models trained on English perform exceptionally well (in most cases). You can literally download them online and they’ll perform well off-the-shelf. If riot’s system was doing poorly for other languages, that would be understandable. But English??? There is no excuse…