Things like Docker containers or cloud VMs that can be, in principle, applied to any sort of software or computation could be helpful for all sorts of applications we can’t anticipate. They are very general-purpose. That makes sense to me.
The extent to which things designed for deep learning, such as PyTorch, could be applied to ideas outside deep learning seems much more dubious.
And if we’re thinking about ideas that fall within deep learning, but outside what is currently mainstream and popular, then I simply don’t know.
Things like Docker containers or cloud VMs that can be, in principle, applied to any sort of software or computation could be helpful for all sorts of applications we can’t anticipate. They are very general-purpose. That makes sense to me.
The extent to which things designed for deep learning, such as PyTorch, could be applied to ideas outside deep learning seems much more dubious.
And if we’re thinking about ideas that fall within deep learning, but outside what is currently mainstream and popular, then I simply don’t know.