DOE investing in machine learning tools for data analysis -- GCN

To help researchers better analyze the massive amount of data they collect from their experiments, the Department of Energy is dedicating $29 million to develop new machine learning tools and advanced algorithms that will benefit multiple scientific fields and inform cutting-edge solutions for a variety of complex problems. Today's scientific facilities, instruments and high-performance computing (HPC) simulations regularly generate terabytes of data -- so much that traditional analysis methods can struggle to interpret the data efficiently. More advanced machine learning tools can identify patterns in data that humans cannot detect, running up to thousands of times faster than traditional data analysis techniques. "As research tools like computers or microscopes have gotten more powerful, the amount of data they can gather has gotten overwhelming--and scientists need new capabilities to make sense of it all," Energy Secretary Jennifer M. Granholm said. "Advanced analysis methods will help them unlock the full potential behind all this data, so that we can solve even our most complex challenges."