Future of deep learning (compared to traditional machine learning)
That's very interesting topic. So thumbs up from my side. Now coming to the point. Deep learning may be hot now but some variants of it or something new all together may emerge later. Let me point out the reasons I feel deep learning maybe getting old or will get.

Slow Learner


Slow learner as in, it converges to an optimal solution slowly but with GPU acceleration the training speed can be improved dramatically. The slowness is affected by the learning rate.
Adjusting the learning rate affects the reliability of the resulting deep neural net.

Huge Training Data Requirement


Deep learning requires very huge training data to achieve good performance. The presence of a huge number of parameters to adjust requires some huge example sets. The fact that deep learning requires such a large number of training examples makes it dull in some way, despite such huge training set requirement deep neural nets do have error rates of about 10%.

Overfitting


Deep learning tends to overfit easily but with the new dropout algorithm, this problem can be avoided but with some consequences such as an increase in error rates.

Poor Initial State


Deep neural nets have parameters that need to be initialized. The most used method is random initialization, this results in neural nets with very poor initial states. Compare this to a mammalian brain, the brain is born with some rigid instincts such as basic survival behavioral patterns.

Sensory Data Transformations


For example in visual object recognition tasks, images undergo various geometric and photometric transformations that need to be modeled by a recognition system to rectify new image observations. Deep learning as used today does not take such transformations into account, this is one of the reasons why deep neural nets still suffer from relatively high error rates (relative to a human).
Some other reason can be the slow transformation, algorithms mayb emerge together in future, strcture and the approaches. These are some pin points from my side. You can also go through these posts, they're also on it and to the point-

KDnuggets
Huffington Post

Cheers! :)