Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This three-part series introduces CSET’s patent clusters, which connect related patents through citations and text similarity.

This new report summarizes a March 2025 workshop hosted by CSET and ORCA, with support from NSF. The workshop brought together more than 30 experts to discuss advancing open science and metascience, and brainstorm how artificial intelligence can be a tool in those efforts. Informed by workshop panels and discussions, the report outlines an agenda for near-term, high-priority next steps to benefit researchers, funders, and policymakers.

This paper presents two new methods for identifying research relevant to emerging technology. The authors developed and deployed technology topic classification and targeted research field scoring over a corpus of scientific literature to identify research relevant to cybersecurity, LLM development, and chips fabrication and design—expanding CSET’s existing set of topic classifications for AI, computer vision, NLP, robotics, and AI safety. The paper summarizes motivation, methods, and results.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This three-part series uses data from a variety of sources to track how three cloud providers—Amazon, Alphabet, and Microsoft—distribute their financial resources to create and sustain demand for their cloud services. By investing in data centers & workforce training, the large tech platforms of Amazon, Google, and Microsoft draw developers, companies, and governments to their tools & services.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This three-part series uses data from a variety of sources to track how three cloud providers—Amazon, Alphabet, and Microsoft—distribute their financial resources to create and sustain demand for their cloud services. By investing in data centers & workforce training, the large tech platforms of Amazon, Google, and Microsoft draw developers, companies, and governments to their tools & services.

Data Snapshots are informative descriptions and quick analyses that dig into CSET’s unique data resources. This three-part series uses data from a variety of sources to track how three cloud providers—Amazon, Alphabet, and Microsoft—distribute their financial resources to create and sustain demand for their cloud services. By investing in data centers & workforce training, the large tech platforms of Amazon, Google, and Microsoft draw developers, companies, and governments to their tools & services.

AI has the potential to revolutionize approaches to climate change research. Using CSET's Map of Science, this data brief maps the production of research publications at the intersection of AI and climate change to better understand how AI methods are being applied to climate change-related research.

Gain- and loss-of-function research have contributed to breakthroughs in vaccine development, genetic research, and gene therapy. At the same time, a subset of gain- and loss-of-function studies involve high-risk, highly virulent pathogens that could spread widely among humans if deliberately or unintentionally released. In this report, we map the gain- and loss-of-function global research landscape using a quantitative approach that combines machine learning with subject-matter expert review.

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.

This data brief identifies the most influential AI researchers in the United States between 2010 and 2021 via three metrics: number of AI publications, citations, and AI h-index. It examines their demographic profiles, career trajectories, and research collaboration rates, finding that most are men in the later stages of their career, largely concentrated in 10 elite universities and companies, and that nearly 70 percent of America’s top AI researchers were born abroad.