ETO’s Research Almanac provides high-level data on key trends in emerging technology research, including overall research output, growth, and trends among countries, research institutions, and companies active in R&D. This initial version of the Almanac focuses on topics and applications in artificial intelligence.

In the first of a series of publications, CSET and CNAS outline one potential avenue for the U.S. government to cut off Chinese access to controlled chips via cloud computing, as well its pros, cons, and limitations.

What exactly are the differences between generative AI, large language models, and foundation models? This post aims to clarify what each of these three terms mean, how they overlap, and how they differ.

As technology competition intensifies between the United States and China, governments and policy researchers are looking for metrics to assess each country’s relative strengths and weaknesses. One measure of technology innovation increasingly used by the policy community is research output. Drawing on CSET’s experiences over the last four years, this post shares our best practices for using research output to study national technological competition and inform public policy.

Executive Director Dewey Murdick shares a review of CSET's successes and growth in 2022.

Machine learning advances have powered the development of new and more powerful generative language models. These systems are increasingly able to write text at near human levels. In a new report, authors at CSET, OpenAI, and the Stanford Internet Observatory explore how language models could be misused for influence operations in the future, and they provide a framework for assessing potential mitigation strategies.

ETO's Supply Chain Explorer is designed to quickly orient non-experts to the essential inputs, players, and relationships involved in producing advanced computer chips. Use the Explorer to learn how these chips are made, who makes them, and the tools, materials, and processes involved in the supply chain.

CSET’s CAT presents data related to countries' artificial intelligence ecosystems to give an overview of domestic capabilities, as well as insights on competitiveness and collaboration globally. It presents metrics on AI research, patents, and investment-related activities for AI overall and its various subfields.

CSET's Daniel Chou provides an update on previous CSET research exploring China's security forces' AI research portfolio.

China’s State Key Laboratory system drives the country’s innovation in science and technology. A key part of China’s aim to reduce its dependence on foreign technology, these labs conduct cutting-edge basic and applied research, attract and train domestic and foreign talent, and conduct academic exchanges with foreign counterparts. These laboratories are spread across almost all Chinese provinces except Tibet, with the majority clustered in large coastal cities.