[ssivark]

> do not need innovative code

I think this is a good deciding factor. Not just for “big data”. In my experience, with its combination of flexibility and raw speed, Julia makes implementing new algorithms (from scratch) a breezy experience. The strong research/academic presence in the community also helps towards encouraging decent Julia libraries for a lot of cutting edge work.

So if you are working in an area where that could make a significant difference, it’s an excellent reason to use Julia.

> will need to develop killer app packages. The next PyTorch needs to be written in Julia. Will that happen?

If enough cutting-edge work happens in Julia, it’s likely that a few great tools/platforms will emerge from that. We’re already seeing that in the scientific modeling ecosystem (as an example), with Differential Equations infrastructure and PumasAI.