Well sort of both. Because of the reasons mentioned above, a purely linear neural net wouldn't be able to learn anything more complicated than simple linear fun

Well sort of both. Because of the reasons mentioned above, a purely linear neural net wouldn't be able to learn anything more complicated than simple linear functions. Adding nonlinearities vastly increases the space of possible functions it can learn.