Jennifer Melot is the Technical Lead for CSET’s Emerging Technology Observatory initiative. Previously she was a Senior Software Engineer on CSET’s data team working on data pipeline automation and scaling, as well as user interface design and implementation. Before coming to CSET, she worked in the Artificial Intelligence Technology and Systems (formerly Human Language Technology) group at MIT Lincoln Laboratory, supporting work for government sponsors on pronunciation modeling and feedback, data management and review, and test and evaluation of human language technology systems. She holds an S.B. from MIT, where she double-majored in Computer Science and Linguistics.
ETO Open-source software Research and Community Activity (ORCA)July 2023
ETO’s Open-source software Research and Community Activity (ORCA) tool compiles data on open-source software (OSS) used in science and technology research.
ETO Research AlmanacMay 2023
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.
ETO Supply Chain ExplorerOctober 2022
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.
Country Activity TrackerAugust 2022
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.
Harnessed LightningOctober 2021
This report examines nearly 350 artificial intelligence-related equipment contracts awarded by the People’s Liberation Army and state-owned defense enterprises in 2020 to assess how the Chinese military is adopting AI. The report identifies China’s key AI defense industry suppliers, highlights gaps in U.S. export control policies, and contextualizes the PLA’s AI investments within China’s broader strategy to compete militarily with the United States.
AI Education CatalogOctober 2021
Created through a joint partnership between CSET and the AI Education Project, the AI Education Catalog aims to raise awareness of the AI-related programs available to students and educators, as well as to help inform AI education and workforce policy.
CSET Map of ScienceOctober 2021
CSET is excited to present the Map of Science user interface. Using a merged corpus of more than 260 million scientific documents, CSET clustered research based on citation links and mapped the clusters spatially using those linkages. The resulting Map provides a visual representation of the landscape of science, with detailed information on more than 123,000 clusters of research including 130 million scientific papers.
National Cybersecurity Center MapJune 2021
China wants to be a “cyber powerhouse” (网络强国). At the heart of this mission is the sprawling 40 km2 campus of the National Cybersecurity Center. Formally called the National Cybersecurity Talent and Innovation Base (国家网络安全人才与创新基地), the NCC is being built in Wuhan. The campus, which China began constructing in 2017 and is still building, includes seven centers for research, talent cultivation, and entrepreneurship; two government-focused laboratories; and a National Cybersecurity School.
PARAT – Tracking the Activity of AI CompaniesJune 2021
CSET’s Private-sector AI-Related Activity Tracker (PARAT) collects data related to companies’ AI research and development to inform analysis of the global AI sector. The global AI market is already expanding rapidly and is likely to continue growing in the coming years. Identifying “AI companies” helps illustrate the size and health of the AI industry in which they participate as well as the most sought-after skills and experience in the AI workforce.
AI Definitions Affect PolicymakingJune 2020
The task of artificial intelligence policymaking is complex and challenging, made all the more difficult by such a rapidly evolving technology. In order to address the security and economic implications of AI, policymakers must be able to viably define, categorize and assess AI research and technology. In this issue brief, CSET puts forward a functional definition of AI, based on three core principles, that significantly outperforms methods developed over the last decade.