In this op-ed, former presidential candidate Pete Buttigieg cites CSET research by Remco Zwetsloot on China's tech talent and a report by Zach Arnold and Ashwin Acharya on China's AI R&D.

CSET's Helen Toner highlights OpenAI's delayed release of GPT-2 and the increased attention it brought to publication norms in the AI research community in 2019. This piece was featured in In the Shanghai Institute for Science of Science's "AI Governance in 2019" report.

Is Russia’s new facial recognition system as effective as promised? CSET’s Rita Konaev cautions that applying the technology in real-world conditions and on a broad scale could lead to a drop in accuracy.

CSET's Saif M. Khan and Remco Zwetsloot joined the Brookings Cafeteria podcast to weigh in on the tech competition between the United States and China.

“Is Senator Cotton right in claiming many Chinese students are going back to China, armed with cutting-edge training in fields like AI? The available evidence — including our research — suggests he’s not,” writes CSET Research Fellow Remco Zwetsloot.

“Congress must continue to function during national crises, even if we cannot meet in person for weeks or months at a time.” Senators Portman and Durbin and CSET Founding Director Jason Matheny make the case for remote congressional voting.

Findings about the coronavirus have emerged from the CORD-19 collection of more than 52,000 scholarly papers. The dataset, coordinated by CSET’s Dewey Murdick, has over 1.5 million visits and 75,000 downloads.

Saif M. Khan and Alexander Mann offer a deep dive into the strategic advantages of AI chips in their recently published report. Among their findings: companies increasingly use AI chips to lower the high-costs of training for certain deep-learning projects.

Within four days of the CORD-19 database going live, “it received more than 594,000 views and 183 analyses.” The project has produced preliminary findings—including COVID-19 protein structure and risk factors.

A collaborative effort led by CSET across tech companies, philanthropic organizations and the US government led to the creation of CORD-19”—a database of 44,000 scholarly articles on COVID-19 using machine learning to help researchers swiftly answer key questions.