Also, building symbolic models from neural models isn't the only useful way to combine the approaches. You can, for example, build symbolic models by capturing

Also, building symbolic models from neural models isn't the only useful way to combine the approaches. You can, for example, build symbolic models by capturing human knowledge and use the symbolic models to guide and constrain the neural ones. As an example from work I'm doing now, you might have a sample that the neural model recognizes as A, and causally-connected sample that it recognizes as B, and a symbolic model that says that a change from A to B implies C.