Deep learning at scale and use cases

Deep learning has made a major impact in the last three years. Imperfect interactions with machines, such as speech or image processing, have been made robust by deep learning that finds usable structure in large datasets. Naveen Rao outlines deep learning challenges and explores how changes to the organization of computation and communication can lead to advances in capabilities.

Deep learning has made a major impact in the last three years. Imperfect interactions with machines, such as speech, natural language processing, and image processing, have been made robust by deep learning that finds usable structure in large datasets. However, the training process is lengthy and has proven difficult to scale due to constraints of existing compute architectures. In addition, there is a need for standardized tools for building and scaling deep learning solutions. Naveen Rao outlines deep learning challenges and explores how changes to the organization of computation and communication can lead to advances in capabilities. Naveen also discusses potential use cases and how current Nervana customers are transforming the way they do business by using artificial intelligence.