NIST Awards $6 Million to Carnegie Mellon University to Establish an AI Cooperative Research Center

NIST Awards $6 Million to Carnegie Mellon University to Establish an AI Cooperative Research Center

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GAITHERSBURG, Md. — Today, U.S. Secretary of Commerce Gina Raimondo announced that the Department of Commerce’s National Institute of Standards and Technology (NIST) has awarded $6 million to Carnegie Mellon University (CMU) to establish a joint center to support cooperative research and experimentation for the test and evaluation of modern AI capabilities and tools. The center will be housed on the Carnegie Mellon campus, in Pittsburgh.


“Artificial intelligence is the defining technology of our generation, and at the Commerce Department we are committed to working with America’s world-class higher education institutions, like Carnegie Mellon University, to advance safe, secure and trustworthy development of AI,” Raimondo said. “I am excited to announce this NIST award of $6 million for Carnegie Mellon to boost research of AI systems and support a new generation of scientists and engineers that will help advance American innovation globally.”


The CMU/NIST AI Measurement Science & Engineering Cooperative Research Center will seek to advance AI risk management practices and evaluation approaches through stakeholder partnerships and translate assessment capabilities and methodologies into practice. 


“This new cooperative research center will expand NIST’s knowledge base and fundamental research capacity in AI,” said Under Secretary of Commerce for Standards and Technology and NIST Director Laurie E. Locascio. “Through this partnership, we will strengthen our understanding of foundation models and support new research — and new researchers — in this rapidly evolving field.”


The center will focus on foundational research and developing AI system-level tooling, metrics, evaluation procedures, development processes, and best practices to help AI builders consistently engineer safe AI systems. Its efforts will align with NIST AI priorities including better methods for measuring validity, reliability, safety, privacy and security; accountability, transparency, fairness and explainability; and generative AI evaluation at any stage of de ..

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