The U.S. National Science Foundation 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 (NSF 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.
These facilities will make it possible to use AI throughout every stage of lab experiments- from pre-experiment to post-experiment - to improve accuracy, efficiency, understanding and overall impact. For example, in the pre-experiment stage, researchers can explore how AI might help design the best setup or predict likely outcomes, which can reduce trial-and-error and save time and resources. During the experiment, AI could track real-time data through sensors or imaging tools, automatically control conditions, and make real-time adjustments to maintain accuracy or respond to anomalies. Post-experiment, researchers could leverage AI to plan next steps or speed up the analysis and visualization of data.
The PCL initiative will also invest in education and training by providing access to advanced laboratories in classroom settings. NSF TIP anticipates making up to six awards - each up to $5 million per year for four years - to institutions of higher education, nonprofit organizations and for-profit organizations.
PCL is one of several opportunities that underpin NSF's vision of developing multiple test platforms where researchers can safely and securely refine groundbreaking technologies in real-world settings. In summer 2024, NSF announced the inaugural awards for the National Quantum Virtual Laboratory and Biofoundries to Enable Access to Infrastructure and Resources for Advancing Modern Biology and Biotechnology initiatives. NSF also launched a new Artificial Intelligence-Ready Test Beds initiative to advance AI technologies.
Learn more about the NSF PCL initiative.
