Tangential, but this brings up a really interesting question for me. LLMs are multi-lingual without really trying assuming the languages in question are sufficiently well-represented in their training corpus. I presume their ability to translate comes from the fact that there are lots of human-translated passages in their corpus; the same work in multiple languages, which lets them figure out the necessary mappings b…
Languages encode similar human experiences, so their conceptual spaces probably have natural alignments even without translation examples. Words for common objects or emotions might cluster similarly.
But without seeing actual translations, a model would miss nuances, idioms, and how languages carve up meaning differently. It might grasp that "dog" and "perro" relate to similar concepts without knowing they're direct translations.