I have this deep seated fear that NNs will be the death of the lessons learned from 1970-2010. After all, if you can use massive amounts of compute to materialize what seems to be a good enough function approximator, why do advanced algorithms at all?
Obviously the reason we should is that approximators like the NNs have explainability issues and corner case unpredictability issues plus they are bad at real world complexity (which is why self driving efforts continue to struggle even when exposed to a narrow subset of the real world).
I have this deep seated fear that NNs will be the death of the lessons learned from 1970-2010. After all, if you can use massive amounts of compute to materialize what seems to be a good enough function approximator, why do advanced algorithms at all?
Obviously the reason we should is that approximators like the NNs have explainability issues and corner case unpredictability issues plus they are bad at real world complexity (which is why self driving efforts continue to struggle even when exposed to a narrow subset of the real world).