The U.S. National Science Foundation is proud to announce a new partnership with Voltage Park in support of the National Artificial Intelligence Research Resource (NAIRR) pilot — a transformative public-private initiative designed to drive U.S. AI innovation, discovery and national competitiveness by expanding access to the tools and resources essential for cutting-edge AI resources for researchers and educators across the country.

Voltage Park, a company committed to broadening access to AI infrastructure, will contribute high-performance cloud computing resources and expert support to help researchers nationwide pursue breakthrough innovations in AI. As part of the partnership, Voltage Park will provide one million NVIDIA H100 GPU hours, enabling a diverse range of AI research projects in science, engineering, health, climate, and more.

“Voltage Park’s participation significantly strengthens our ability to deliver on the promise of the NAIRR pilot,” said Brian Stone, performing the duties of the NSF director. “By partnering with visionary private sector organizations like Voltage Park, we are expanding the frontiers of AI research and ensuring that the US continues to lead in AI innovation.”  

​​​“Expanding access to advanced computing is not just a technical initiative—it’s a strategic priority,” said Ozan Kaya, Chief Executive Officer of Voltage Park. “By lowering the barriers to high-performance AI infrastructure, we can unlock innovation from a more diverse and representative set of researchers. That inclusivity is what drives

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Metamaterials are a special class of engineered materials, designed to have properties not found in nature. Glaucio Paulino, a professor at Princeton University, discusses his work on developing modular chiral origami metamaterials, engineering control approaches and the ways they might benefit society.

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Managing diabetes is a daily challenge faced by nearly 40 million Americans. It involves tracking food intake, timing medication and engaging in physical activity. Getting it wrong can lead to serious health issues; therefore, developing better prediction tools is a vital part of effective diabetes care.

To support better diabetes management, researchers funded by multiple U.S. National Science Foundation grants are developing innovative tools that help patients predict blood sugar levels more precisely without compromising the privacy of their health data. This cutting-edge approach could transform how people with diabetes monitor and manage their condition in real-time.

At the core of this technology is a method called federated learning, which allows artificial intelligence models to be trained across many patients’ devices without sending any personal data to a central server. This setup is ideal for healthcare, where data privacy is paramount and patients often use battery- and memory-limited smart devices. But early federated learning systems struggled to adapt to individual differences, like how people eat, move or react to insulin.

To address this challenge, the research team grouped patients based on their carbohydrate (e.g., sugar and starch) intake levels. The idea is that people who eat in similar ways tend to show similar glucose patterns. By training the AI on these grouped behaviors, the model became more effective at making personalized blood glucose predictions.

To test

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