National Science Foundation announces new $100 million funding opportunity
The "programmable cloud laboratories" initiative is aimed at expanding access to cutting-edge technology to accelerate the automation of scientific discovery and innovation.
The U.S. National Science Foundation (NSF) has announced a new funding opportunity that would invest up to $100 million to support a network of “programmable cloud laboratories,” aimed at expanding access to cutting-edge technology to accelerate the automation of scientific discovery and innovation.
The NSF Test Bed: Toward a Network of Programmable Cloud Laboratories (NSF PCL Test Bed) would establish artificial intelligence-enabled laboratories nationwide to integrate, test, evaluate and validate the capabilities of new cutting-edge AI-based technologies.
This new program directly implements a priority of the White House AI Action Plan to accelerate AI-enabled science through automated laboratory infrastructure. It will be led by the NSF Directorate for Technology, Innovation and Partnerships (TIP) and subject to future appropriations.
“The idea of a national network of programmable cloud laboratories builds on NSF’s longstanding legacy of transformative investments — such as NSFNET decades ago — that paved the way for the modern internet,” said Erwin Gianchandani, NSF Assistant Director for TIP.
The NSF PCL initiative will invest in a network of laboratories that can be remotely accessed to run custom, user-programmed AI-enabled workflows. These hubs will help bring innovative technologies into practical use during scientific and engineering experiments. The initial focus will be on biotechnology and materials science — fields that are well-positioned to benefit from the programmable cloud laboratory model.
“The PCL initiative will transform how U.S. researchers conduct scientific experiments. It will accelerate scientific progress by advancing AI-enabled technologies that form the backbone of the automated science revolution. This is a crucial step toward addressing the growing need to generate and interpret large volumes of high-quality experimental data in biotechnology, materials science, chemistry and other laboratory sciences,” Gianchandani added.
NSF will hold a webinar to review the new offering at 3 p.m. EDT on August 20. To register, click here.
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