Hi Eryk,
Indeed there’s a “winner takes it all phenomenon” for languages, and building models that only support the most well-resources languages participates in that trend. But so does our usage of English on this forum!
On a more positive note, the 1000+ models released by Helsinki-NLP using OPUS include some pretty low-resource languages.
Another idea would be to fine-tune BERT to translating between a low-resource language and English, making use of the low-resource language similarity with other top 100 languages. For example, the Tetun language (which I work with) is low-resource, but has similarities with both Portuguese and Indonesian, which are part of BERT. Is that something that you’ve considered?