Does deep learning always have to reinvent the wheel? MarkTechPost

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 application of deep learning to many other domains. In many of those domains, deep learning is now 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.