I think one big problem is that people understand LLMs as text-generation models, when really they're just sequence prediction models, which is a highly versatile, but data-hungry, architecture for encoding relationships and knowledge. LLMs are tuned for text input and output, but they just work on numbers and the general transformer architecture is highly generalizable.