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Do you think the only solution is neurosymbolic integration? Or could there be feasible neural solutions to this too?
Neurosymbolic models, aka "writing software by hand to do the things DL can't" is already what everyone is doing to address this. It works to a large extent, but it is very labor intensive.
Definitely. Maybe deep learning will always have a risk factor that we just aren't used to computers having. We can take steps to minimize it, but can't really eliminate it.
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