Computer scientist Barry Chen is heading a project to develop deep learning and high-performance computing algorithms that can sift through massive amounts of data for evidence of nuclear proliferation activities to accelerate nonproliferation analysis at a scale beyond what humans could possibly handle manually.
(Download Image)Researchers developing deep learning system to advance nuclear nonproliferation analysis
Artificial neural networks are all around us, deeply embedded in routine functions on the internet. They help online merchants make personalized shopping recommendations, enable social media sites to recognize faces in photos and assist email programs in filtering out spam. Neural networks also have the potential to play a critical role in national security, helping nonproliferation analysts prevent rogue states or nefarious actors from building a nuclear weapon. To accelerate the pace of nonproliferation analysis and scale it to much larger data sets than humans could possibly handle manually, researchers at LLNL are developing new deep learning and high-performance computing algorithms that can sift through massive amounts of data for evidence of nuclear proliferation activities. Read more at LLNL News.
