Catalyzing Deep Learning’s Impact in the Enterprise
Deep learning is in the early stages of unlocking tremendous economic value outside its impact in the large technology companies. While the algorithms have revolutionized consumer experiences in domains as varied as speech interfaces, image search, language translation, and game AI, enterprises are relatively early in their efforts to apply these algorithms to domains such as improving automotive speech interfaces, agricultural robotics and genomics, financial document summarization and finding anomalies in IoT data. Individual data scientists can draw from several open source frameworks and basic hardware resources during the very initial investigative phases but quickly require significant hardware and software resources to build and deploy production models. Nervana has built a deep learning platform to make it easy for data scientists to start from the iterative, investigatory phase and take models all the way to deployment. Nervana’s platform is designed for speed and scale, and serves as a catalyst for all types of organizations to benefit from the full potential of deep learning.
Arjun is the founder and VP Algorithms (Heading ML/DL & Data Science) at Nervana. His prior work has spanned neurophysiology and large scale machine learning. His interests are artificial intelligence, virtual reality, brain-machine interfaces, entrepreneurship, and tennis.