×
NSF invests $100M in AI-powered cloud labs for scientific research
Written by
Published on
Join our daily newsletter for breaking news, product launches and deals, research breakdowns, and other industry-leading AI coverage
Join Now

The U.S. National Science Foundation announced a new funding opportunity that will invest up to $100 million to create a network of “programmable cloud laboratories” nationwide. These AI-enabled facilities will allow researchers to remotely access cutting-edge technology to automate scientific discovery and innovation, directly implementing a priority from the White House AI Action Plan.

What you should know: The NSF PCL Test Bed initiative will establish artificial intelligence-enabled laboratories that can be remotely accessed to run custom, user-programmed AI workflows.

  • The program will be led by NSF’s Directorate for Technology, Innovation and Partnerships (NSF TIP) and is subject to future appropriations.
  • Initial focus areas include biotechnology and materials science, fields well-positioned to benefit from the programmable cloud laboratory model.
  • These facilities will integrate AI throughout every stage of lab experiments—from pre-experiment design to post-experiment analysis.

The big picture: This initiative builds on NSF’s legacy of transformative investments that have shaped modern technology infrastructure.

  • “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 network represents a crucial step toward addressing the growing need to generate and interpret large volumes of high-quality experimental data across laboratory sciences.

How it works: AI will be integrated throughout the entire experimental process to improve accuracy, efficiency, and overall impact.

  • Pre-experiment: AI will help design optimal setups and predict likely outcomes, reducing trial-and-error while saving time and resources.
  • During experiments: AI will track real-time data through sensors and imaging tools, automatically control conditions, and make real-time adjustments to maintain accuracy or respond to anomalies.
  • Post-experiment: Researchers can leverage AI to plan next steps and accelerate analysis and visualization of data.

Funding details: NSF TIP anticipates making up to six awards to eligible institutions across different sectors.

  • Each award will provide up to $5 million per year for four years.
  • Eligible recipients include institutions of higher education, nonprofit organizations, and for-profit organizations.
  • The initiative will also invest in education and training by providing access to advanced laboratories in classroom settings.

Competitive landscape: PCL joins several other NSF initiatives designed to create safe testing environments for breakthrough technologies.

  • In summer 2024, NSF announced inaugural awards for the National Quantum Virtual Laboratory and Biofoundries initiatives.
  • NSF also launched an Artificial Intelligence-Ready Test Beds initiative to advance AI technologies.
  • These programs collectively support NSF’s vision of developing multiple test platforms where researchers can refine groundbreaking technologies in real-world settings.

What they’re saying: Leadership emphasizes the transformative potential of automated science infrastructure.

  • “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,” Gianchandani added.
NSF to invest in new national network of AI-programmable cloud laboratories

Recent News

Rose-Hulman launches computer science major with AI and cybersecurity tracks

Students can now minor in AI specializations even outside computer science disciplines.

Match Group beats earnings with $50M AI strategy to win back Gen Z

Revenue guidance of $910-920 million exceeded analyst estimates by nearly $30 million.