What would be the requirements in order for most researchers to agree that a “conclusive” answer has been established to the question “How do neural networks work?”
I ask not because this paper isn’t insightful research, but rather because if you search Google Scholar or arXiv for papers purporting to describe how neural networks “actually work”, you get thousands upon thousands of results all claiming to answer the question, and yet you never really come away with the sense that the question has truly been resolved in a satisfactory way (see also: the measurement problem).
I’ve noticed that each paper uses a totally different approach to addressing the matter that just happens to correspond to the researchers’ existing line of work (It’s topology! No, group theory has the answer! Actually, it’s compressed sensing... computational complexity theory... rebranded old-school quantum chemistry techniques... and so on.)
I suppose my question is more about human psychology than neural networks, since neural networks seem to be working just fine regardless of how well we understand them. But I think it could be useful to organize a multi-disciplinary conference where some open questions regarding machine learning are drafted (similar to Hilbert’s problems), that upon their successful resolution would mean neural networks are no longer widely considered “black boxes”.
I ask not because this paper isn’t insightful research, but rather because if you search Google Scholar or arXiv for papers purporting to describe how neural networks “actually work”, you get thousands upon thousands of results all claiming to answer the question, and yet you never really come away with the sense that the question has truly been resolved in a satisfactory way (see also: the measurement problem).
I’ve noticed that each paper uses a totally different approach to addressing the matter that just happens to correspond to the researchers’ existing line of work (It’s topology! No, group theory has the answer! Actually, it’s compressed sensing... computational complexity theory... rebranded old-school quantum chemistry techniques... and so on.)
I suppose my question is more about human psychology than neural networks, since neural networks seem to be working just fine regardless of how well we understand them. But I think it could be useful to organize a multi-disciplinary conference where some open questions regarding machine learning are drafted (similar to Hilbert’s problems), that upon their successful resolution would mean neural networks are no longer widely considered “black boxes”.