This explainer overviews techniques to produce smaller and more efficient language models that require fewer resources to develop and operate. Importantly, information on how to leverage these techniques, and many of the subsequent small models, are openly available online for anyone to use. The combination of both small (i.e., easy to use) and open (i.e., easy to access) could have significant implications for artificial intelligence development.

In collaboration with colleagues from CNAS and the Atlantic Council, CSET Researchers Ngor Luong and Emily Weinstein provided this comment in request to Treasury's Advanced Notice of Rule-making request for public comment (TREAS-DO-2023-0009-0001).

This report summarizes more than 20 CSET reports, translations, and data analyses to provide insight into the steps China has taken to increase its technological competitiveness beyond its own borders.

This report summarizes more than 20 CSET reports, translations, and data analyses to provide insight into China’s internal actions to advance and implement its technology-related policy goals

Scout is ETO's discovery tool for Chinese-language writing on science and technology. Scout compiles, tags, and summarizes news and commentary from selected Chinese sources, helping English-speaking users easily keep up to date, skim the latest news, and discover new perspectives. Use the Scout web interface to browse and filter articles, or get customized updates delivered to your inbox through the Scout email service.

Translation Snapshots are short posts that highlight related translations produced by CSET’s in-house translation team. Each snapshot identifies relevant translations, provides short summaries, and links to the full translations. Check back regularly for additional Translation Snapshots highlighting our work.

This brief examines trends in patents generated through federally funded research, otherwise known as Bayh-Dole patents. We find that while Bayh-Dole patents make up a small proportion of U.S. patents overall, they are much more common in certain fields, especially in biosciences and national defense related fields. Academic institutions are major recipients of Bayh-Dole patents, and the funding landscape for patent-producing research has shifted since Bayh-Dole came into effect in 1980.

Artificial intelligence that makes news headlines, such as ChatGPT, typically runs in well-maintained data centers with an abundant supply of compute and power. However, these resources are more limited on many systems in the real world, such as drones, satellites, or ground vehicles. As a result, the AI that can run onboard these devices will often be inferior to state of the art models. That can affect their usability and the need for additional safeguards in high-risk contexts. This issue brief contextualizes these challenges and provides policymakers with recommendations on how to engage with these technologies.

Foundation models could eventually introduce several pathways for undermining state security: accidents, inadvertent escalation, unintentional conflict, the proliferation of weapons, and the interference with human diplomacy are just a few on a long list. The Confidence-Building Measures for Artificial Intelligence workshop hosted by the Geopolitics Team at OpenAI and the Berkeley Risk and Security Lab at the University of California brought together a multistakeholder group to think through the tools and strategies to mitigate the potential risks introduced by foundation models to international security.

Technical talent is vital to innovation and economic growth, and attracting these highly mobile workers is critical to staying on the cutting-edge of the technological frontier. Conventional wisdom holds that the defense community generally struggles to access this talent pool. This policy brief uses LinkedIn data to track the movement of tech workers between industries and metro areas, with a particular focus on the U.S. Department of Defense, the defense industrial base, and the so-called “Big Tech” companies.