In many respects, it is. For sure, the recent successes of deep learning have been amazing: we went from being really terrible at supervised learning on perceptual problems (image classification, speech recognition) to being really good at it. Deep learning has been transformative for many subfields of machine learning. But here's the thing: lots of people, most of them not directly involved with deep learning research, tend to extrapolate too much from these recent successes. For instance, when we started achieving below 4% top-5 error on the ImageNet classification task, people started claiming that we had "solved" computer vision.

With all of the success that deep learning is experiencing, the detractors and cheerleaders can be seen coming out of the woodwork. What is the real validity of deep learning, and is it simply hype?