Signals in the Noise: Preventing Nuclear Proliferation with Machine Learning  Report Launch @NuclearThreatInitiative
Signals in the Noise: Preventing Nuclear Proliferation with Machine Learning  Report Launch  @NuclearThreatInitiative
Uploaded January 2021 | Updated September 2026, 1 week ago
Over two years, the Nuclear Threat Initiative (NTI) and the Center for Advanced Defense Studies (C4ADS) worked together on a pilot project to demonstrate the viability of using PAI and machine learning to detect high-risk and/or illicit nuclear trade. The initiative leveraged NTI’s nuclear expertise and C4ADS’s data management, engineering, and analysis capabilities to identify high-risk nuclear proliferation activities at scale.

For the virtual launch, the team demonstrated how publicly available data, when combined with machine learning, creates new opportunities to see, find, and expose potentially dangerous proliferation activities.

The event featured:
• Ernest J. Moniz , Co-Chair and CEO, NTI
• Page O. Stoutland, Vice President, Scientific and Technical Affairs, NTI
• Jason Arterburn, Program Director, C4ADS
• Erin D. Dumbacher, Senior Program Officer, NTI

Read the full report here: bit.ly/3bwUHEx
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Signals in the Noise: Preventing Nuclear Proliferation with Machine Learning Report Launch

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