Findings about the coronavirus have emerged from the CORD-19 collection of more than 52,000 scholarly papers. The dataset, coordinated by CSET’s Dewey Murdick, has over 1.5 million visits and 75,000 downloads.

Saif M. Khan and Alexander Mann offer a deep dive into the strategic advantages of AI chips in their recently published report. Among their findings: companies increasingly use AI chips to lower the high-costs of training for certain deep-learning projects.

Within four days of the CORD-19 database going live, “it received more than 594,000 views and 183 analyses.” The project has produced preliminary findings—including COVID-19 protein structure and risk factors.

A collaborative effort led by CSET across tech companies, philanthropic organizations and the US government led to the creation of CORD-19”—a database of 44,000 scholarly articles on COVID-19 using machine learning to help researchers swiftly answer key questions.

Within the first five days of launch, the CORD-19 database had “already garnered over 500,000 views, and been downloaded more than 18,000 times.” CSET coordinated the effort at the urging of the White House Office of Science and Technology Policy.

Read this feature on CSET's work to organize the AI scholarly community in an effort to use data-mining techniques to spur scientific discoveries that address COVID-19.

As the COVID pandemic moves across the world, many AI researchers have been wondering how they can best help. A good starting place is developing new data mining and text analysis tools for the COVID-19 Open Research Dataset (CORD-19).

CSET's Director of Data Science, Dewey Murdick, joined Federal Drive with Tom Temin to discuss CORD-19, a collaboration between the White House and research groups coordinated by CSET to aggregate scholarly articles on the coronavirus.

The COVID-19 Open Research Dataset is the result of a collaboration between CSET, the Allen Institute for Artificial Intelligence, Microsoft, the National Library of Medicine at the National Institutes of Health (NIH), and the Chan Zuckerberg Initiative in response to a request by the White House OSTP.

How can machine learning advance COVID-19 research? By harnessing the collective insight of more than 29,000 scholarly articles on the coronavirus and creating an open database for researchers. CSET has coordinated a joint database effort called CORD-19.