Chinese AI company DeepSeek has upended assumptions about cutting-edge AI development by creating cost-effective, efficient models without relying on the most advanced chips.
Leveraging innovative techniques and a narrow window to acquire powerful Nvidia hardware, DeepSeek’s approach is reshaping Silicon Valley’s strategies and pressuring U.S. policymakers to rethink export controls. Experts believe the company’s success signals a transformative moment in the global AI race.
Faculty experts at the George Washington University are available to offer insight, analysis and commentary on emerging AI technology and global dynamics. If you would like to speak with an expert, please contact the GW Media Relations team at gwmedia@gwu.edu.
Jeffrey Ding is an Assistant Professor of Political Science at the George Washington University. Ding’s research interests center on emerging technologies and international politics. His forthcoming book manuscript investigates how technological revolutions affect the rise and fall of great powers. By analyzing historical cases of industrial revolutions that sparked power transitions and conducting statistical analysis on cross-country technology adoption, Ding has developed insights for how emerging technologies like AI could affect the U.S.-China power balance. Other research projects tackle how states should identify strategic technologies, innovation-centrism in assessments of national scientific and technological capabilities, and interstate cooperation on nuclear safety and security technologies.
Neil Johnson is a professor of physics at the George Washington University and leads a new initiative in Complexity and Data Science which combines cross-disciplinary fundamental research with data science to attack complex real-world problems. His research interests lie in the broad area of Complex Systems and ‘many-body’ out-of-equilibrium systems of collections of objects, ranging from crowds of particles to crowds of people and from environments as distinct as quantum information processing in nanostructures through to the online world of collective behavior on social media.
In December 2024, Johnson released a paper that mathematically explores how a far smaller and nominally weaker ‘David’ AI GPT can beat a huge ‘Goliath’ one, by being more agile while it is running.
Johnson says, “The trick lies in DeepSeek being more agile: while it is running, DeepSeek is continually ‘aware’ of what it is outputting by assembling pieces from different parts of its small system, rather than trying to do the whole thing at once in some sluggish and less adaptable form like ChatGPT.”
Susan Ariel Aaronson, a research professor of international affairs at the George Washington University, is also the director of the Digital Trade and Data Governance Hub and co-PI at the NSF Trustworthy AI Institute, TRAILS. Her research focuses on AI governance, data governance, competitiveness in data-driven services such as XR, and AI and digital trade. Aaronson currently directs projects on governing data for generative AI, ensuring that data is globally accurate, complete, and representative and on AI protectionism. She can discuss what AI policy might look like under a Trump administration, including concerns around data protection, trustworthy AI and antitrust initiatives.
Aram Gavoor, Associate Dean for Academic Affairs; Professorial Lecturer in Law; Professor (by courtesy), Trachtenberg School of Public Policy & Public Administration at the George Washington University Law School. Dean Gavoor is an internationally recognized scholar in national security, American administrative law, artificial intelligence, and federal courts. He previously served as Senior Counsel for National Security in the Civil Division of the U.S. Department of Justice.
Scott J. White, Associate Professor and Director of the Cybersecurity Program and Cyber Academy at the College of Professional Studies at the George Washington University. Dr. White is an expert in cybersecurity, cybercrime, counter-terrorism and infrastructure protection. He has worked for a variety of law enforcement agencies in the US, the UK and Canada; as well as holds a Queen’s Commission and was an Officer with the Canadian Security Intelligence Service.
Zoe Szaznfarber is a Professor of Engineering Management and Systems Engineering at the George Washington University. Szajnfarber’s research group seeks to understand the fundamental dynamics of innovation in the monopsony market that characterizes government space and defense activities, as a basis for decision making. Current projects include mapping the innovation ecosystem at NASA, ESA and the DoD, modeling the interactions between organizational and technical systems architecture over time, and valuing alternative technology investment strategies and their impact on individual preference structures.
David Broniatowski conducts research in decision-making under risk, group decision-making, system architecture, and behavioral epidemiology. This research program draws upon a wide range of techniques including formal mathematical modeling, experimental design, automated text analysis and natural language processing, social and technical network analysis, and big data. Current projects include a text network analysis of transcripts from the US Food and Drug Administration’s Circulatory Systems Advisory Panel meetings, a mathematical formalization of Fuzzy Trace Theory — a leading theory of decision-making under risk, derivation of metrics for flexibility and controllability for complex engineered socio-technical systems, and using Twitter data to conduct surveillance of influenza infection and the resulting social response.
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