Does Deep Learning always have to Reinvent the Wheel?

Machine learning and in particular deep learning revolutionize the world as we know it today. We have seen tremendous advances in speech and image recognition, followed by the application of deep learning to many other domains. In many of those domains, deep learning is now the state of the art or is even going beyond it. A clear trend is that networks are growing more and more complex and more and more computationally demanding. Today, we are building ever-increasing networks that are built on top of previous generations of network topologies.