In this talk, I start with a brief introduction to the history of deep learning and its application to natural language processing (NLP) tasks. Then I describes in detail the deep learning technologies that are recently developed for three areas of NLP tasks. First is a series of deep learning models to model semantic similarities between texts and images, the task that is fundamental to a wide range of applications, such as Web search ranking, recommendation, image captioning and machine translation. Second is a set of neural models developed for machine reading comprehension and question answering. Third is the use of deep learning for various of dialogue agents, including task-completion bots and social chat bots.