LLMs may be overhyped, but transformers in general are underhyped.

LLMs make a lot of mistakes because they don't actually know what words mean. The key thing is though - it's much harder to generate coherent text when you don't know what the words mean. In a similar vein it's completely unreasonable to expect an LLM to perform visual tasks when it literally has no sense of sight.

The fact that it can kind of sort of do these things at all is evidence of the super-human generalization potential of the transformer architecture.

This isn't very obvious for English because we have prior knowledge of what words mean, but it's a lot more obvious when applied to languages humans don't understand, like DNA and amino acid sequences.