6 predictions for the future of deep learning

Deep learning is many things, but it isn't simple. Even if you're a data scientist who has mastered the basics of artificial neural networks, you may need time to get up to speed on the intricacies of convolutional, recurrent, generative, and every other species of multilayered deep learning algorithm. As deep learning innovations proliferate, there's a risk this technology will grow too complex for average developers to grasp without intensive study. But I'm confident that, by the end of this decade, the deep learning industry will have simplified its offerings considerably so that they're comprehensible and useful to the average developer. Currently, deep learning professionals have a glut of tooling options, most of which are open source.