San Francisco, United States – Snorkel AI, a data-centric AI platform company, announced that Georgetown University’s Centre for Security and Emerging Technology (CSET) is using Snorkel Flow to build next-generation NLP applications. Snorkel Flow, the data-centric AI platform powered by programmatic labeling and foundation models, equipped the CSET data science team to collaborate closely with analysts to gather, process, and interpret data at scale to rapidly develop complex NLP applications.
CSET is a policy research organisation within Georgetown University’s Walsh School of Foreign Service. It produces data-driven research on the security implications of emerging technologies and provides nonpartisan analysis to the policy community. Learn more about Snorkel AI and CSET here.
CSET’s mission includes preparing a new generation of decision-makers to address the challenges and opportunities of emerging technologies such as artificial intelligence, advanced computing, and biotechnology. It provides unprecedented coverage of the emerging technology ecosystem and its security implications, bolstered by novel methods to classify documents, including foreign-language and technical materials from diverse sources for analytic purposes. CSET was looking to accelerate its development of high-quality models to inform CSET’s data-driven policy recommendations.
CSET piloted the use of Snorkel Flow to classify thousands of complex biomedical research articles related to nuanced topics in virology. With Snorkel Flow, CSET reduced the time spent on labeling data to train models. Snorkel Flow’s data-centric AI workflows allowed for more efficient collaboration between data scientists and analysts and reduced the resources spent on manual labeling. Overall, Snorkel Flow has improved the CSET team’s ability to spin up more projects and explore new projects faster.
“We are thrilled to partner with Snorkel AI on this important work,” says CSET director of data science and research Catherine Aiken. “With Snorkel Flow, we cut labeling time and significantly accelerated model development when delivering NLP solutions.”
Data science teams often struggle with a disjointed process for collaborating with subject-matter experts that involves spreadsheets, Slack channels, Python scripts, and loads of manual labeling. With Snorkel Flow, CSET benefited from an integrated platform with programmatic labeling, error analysis, active learning, and advanced techniques such as labeling with embedding clusters.
“We first experimented with research code open-sourced by the Snorkel AI team,” Aiken says. “Snorkel Flow provided us with additional capabilities for building and deploying production-ready NLP solutions.”
Snorkel AI CEO and co-founder Alex Ratner, adds “CSET is a leader in the field of national security and emerging technologies, and we are excited to work with them to explore the potential of AI in this important area. We believe that by bringing together top researchers and technologists, we can make significant strides in advancing policymaking.”
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