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The U.S. National Science Foundation Directorate for Technology, Innovation and Partnerships (NSF TIP) announced an inaugural investment of nearly $32 million to five teams across the U.S. through the NSF Use-Inspired Acceleration of Protein Design (NSF USPRD) initiative. This effort aims to accelerate the translation of artificial intelligence-based approaches to protein design and enable new applications of importance to the U.S. bioeconomy.

“NSF is pleased to bring together experts from both industry and academia to confront and overcome barriers to the widespread adoption of AI-enabled protein design,” said Erwin Gianchandani, NSF assistant director for TIP. “Each of the five awardees will focus on developing novel approaches to translate protein design techniques into practical, market-ready solutions. These efforts aim to unlock new uses for this technology in biomanufacturing, advanced materials, and other critical industries. Simply put, NSF USPRD represents a strategic investment in maintaining American leadership in biotechnology at a time of intense global competition.”

Researchers have made significant progress in predicting the 3D structures of proteins and are now leveraging this knowledge to design proteins with specific, desirable characteristics. These advances have been driven by macromolecular modeling, access to training data, applications of AI and machine learning, and high-throughput methods for protein characterization. The NSF USPRD investment seeks to build on this foundation by bringing together cross-disciplinary and cross-sector experts nationwide. The goal is to

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The U.S. National Science Foundation announced over $2 million in planning grants to support the development of artificial intelligence-ready test beds — real-world environments that will accelerate the design, evaluation and deployment of AI technologies across sectors critical to America’s economy and prosperity.

The initiative is a joint effort led by the NSF directorates for Computer and Information Science and Engineering (NSF CISE) and Technology, Innovation and Partnerships (NSF TIP), implementing a priority issued in the White House’s recent AI Action Plan to invest in secure, real-world settings that allow researchers to prototype new AI systems and translate them to the market.

“The AI-ready test beds program is uniquely NSF,” said Ellen Zegura, NSF acting assistant director for CISE. “It leverages critical, existing test environments to drive AI progress. This initiative not only builds the foundation for new breakthroughs in AI research but also helps bridge the gap between research and applications by connecting researchers with real-world challenges and enabling them to explore how AI can be most effectively applied in practice.”

As AI systems become increasingly integrated into areas ranging from emergency response to wireless networks, evaluating their reliability and performance beyond controlled settings is essential to developing long-term, impactful solutions that benefit the nation. NSF’s test bed investments ensure that AI breakthroughs are tested for impact, scalability and built to serve the public

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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

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