>Neural nets are mostly dominant in perceptual domains such as image or speech recognition, where the raw inputs represent a uniform sampling of data values (pixels, audio samples) over space and/or time.

I mostly agree with that, however there have been advancement in scientific areas such as chemistry and biology (DNA/RNA) where the data are definitely meaningful and a lot times categorical. So the methodologies can be applied in wider areas, they just need a lot of domain knowledge and experience.