Personally I'm curious about training a model to predict Cyrillic or Greek letterforms from Latin ones to boost multilingual coverage. I'm sure there are some learnable relationships there like Я <=> R or И <=> H.
Do you mean relationship in terms of appearance or pronunciation?
Я maps to "ya" sound in Russian, И is "ee" and Н is "N" in Russian and "ee" in modern Greek but in ancient Greek it's something like "e" in "bed" in American English.
Some fonts do not have Cyrillic glyphs. If they could be generated by an adequately trained model based on the other glyphs, then that font's multilingual coverage could expand automatically.