Big Data Challenges and Advanced Computing Solutions

Citation
Big Data Challenges and Advanced Computing Solutions, Joint Hearing Before the Subcommittee on Energy & Subcommittee on Research and Technology Committee on Science, Space, and Technology, House of Representatives, 115th Congress, 2d Sess. (July 12, 2018) (full-text).

Overview
From the opening statement of Randy Weber:

"Today, we will explore the application of machine-learning-based algorithms to big-data science challenges. Born from the artificial intelligence (AI) movement that began in the 1950s, machine learning is a data-analysis technique that gives computers the ability to learn directly from data without being explicitly programmed. [...] Today, specialized algorithms termed 'deep learning' are leading the field of machine-learning-based approaches. These algorithms are able to train computers to perform certain tasks at levels that can exceed human ability. Machine learning also has the potential to improve computational science methods for many big-data problems. As the Nation's largest federal sponsor of basic research in the physical sciences with expertise in big-data science, advanced algorithms, data analytics, and high-performance computing, the Department of Energy is uniquely equipped to fund robust fundamental research in machine learning. The Department also manages the 17 DOE national labs and 27 world-leading scientific user facilities, which are instrumental to connecting basic science and advanced computing."