not from fly.io, but my experience is that most data scientists will just prefer to lump it with the tools they know (pandas / R) on CPUs, rather than delving into things like rapids https://rapids.ai -- even if it makes things faster/cheaper.
I might have had a bad sample set so far. But the "doing statistics" bit seems to be the interesting thing for them. the tooling doesn't really factor into solutions/plans that often. and learning something new because "engineer say it shinier" doesn't really seem to motivate them much :/
Do many DS use Google Colab and click the GPU option? That made me think GPUs would be more popular (due to speed).
Also GPUs may be used when productionizing work done by DS but maybe I am in a tiny niche here of (Data Science) intersection (Scale up) minus (Deep learning LLM etc.)
I might have had a bad sample set so far. But the "doing statistics" bit seems to be the interesting thing for them. the tooling doesn't really factor into solutions/plans that often. and learning something new because "engineer say it shinier" doesn't really seem to motivate them much :/