The Most Influential Deep Learning Research of 2019

Deep learning has continued its forward movement during 2019 with advances in many exciting research areas like generative adversarial networks (GANs), auto-encoders, and reinforcement learning. In terms of deployments, deep learning is the darling of many contemporary application areas such as computer vision, image recognition, speech recognition, natural language processing, machine translation, autonomous vehicles, and many more. Earlier this year, we saw Google AI Language revolutionize the NLP segment of deep learning with the new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers. The already seminal paper was released on arXiv on May 24. This has led to a storm of follow-on research results.