We'll have to see where this all leads, to ver the next few years/decades. Maybe someone will manage to combine "a proper fundamental understanding of trained neural networks," and good results. That'll lead to (perhaps) good theories, to explain the good results.
If "good results" continue to outpace our understanding of wtf the useful NN is up to... It'll have to be studied expirementaly, like the way we study biology.
Ie, we might see CS theory adapt from "mathematical," to "scientific" to in its methods and theories.
The current trajectory seems to be heading here. There is tremendous interest and resources in NNs. As they become more commercially important, interest and resources dedicated to developing them increases. They only need the NNs to work, not to be scriptable.
Scientists are not just going to give up though. They'll study NNs expirementaly as black boxes if that's all they have.
We'll have to see where this all leads, to ver the next few years/decades. Maybe someone will manage to combine "a proper fundamental understanding of trained neural networks," and good results. That'll lead to (perhaps) good theories, to explain the good results.
If "good results" continue to outpace our understanding of wtf the useful NN is up to... It'll have to be studied expirementaly, like the way we study biology.
Ie, we might see CS theory adapt from "mathematical," to "scientific" to in its methods and theories.
The current trajectory seems to be heading here. There is tremendous interest and resources in NNs. As they become more commercially important, interest and resources dedicated to developing them increases. They only need the NNs to work, not to be scriptable.
Scientists are not just going to give up though. They'll study NNs expirementaly as black boxes if that's all they have.