House Lawmakers Discuss Potential for AI to Transform Society, Industry
House lawmakers said artificial intelligence and machine learning have a high level of potential to solve scientific problems and improve human life. During a joint hearing Thursday between the Energy and the Research and Technology subcommittees, House Science Committee Chairman…
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Lamar Smith, R-Texas, listed some notable AI efforts: the Lawrence Berkeley National Laboratory and SLAC National Accelerator Laboratory are experimenting with machine learning-based approaches; Argonne National Laboratory researchers are creating a 3D map of human brain neurons; and Carnegie Mellon University’s NextManufacturing Center is combining 3D printing and machine learning for monitoring “the quality of manufactured components in real-time.” Energy Subcommittee Chairman Randy Weber, R-Texas, cited Rice University in his district, where researchers are using machine learning to address geological science. Weber cited the Department of Energy’s goal of fielding exascale computing systems capable of a great many calculations per second by 2021. “With the immense potential for machine learning technologies to answer fundamental scientific questions … it’s clear we should prioritize this research,” Weber said. Research and Technology Subcommittee Chairman Barbara Comstock, R-Va., discussed DOE’s joint effort with the Department of Veterans Affairs, the MVP-Champion program. The program seeks to use advanced computing and machine learning to analyze health records for more than 20 million veterans. “The potential for AI to help humans and further scientific discoveries is immense,” Comstock said. Argonne National Laboratory researcher Bobby Kasthuri told the committee that advanced computing has the potential to transform mental illness and disease treatment, revolutionize computers and algorithms and bolster artificial intelligence capabilities and national and economic security. Carnegie Mellon University professor Anthony Rollett suggested U.S. government agencies be given the capability to support data storage systems, allowing data to be shipped on a “terabyte scale.”