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Research

NAIRR Pilot Meeting 2025

The inaugural annual meeting of the NAIRR Pilot program was held recently in Arlington near Washington DC. It was February. It was cold outside, very cold for an Arizonan, but the atmosphere was warm inside.

The National Artificial Intelligence Research Resource (NAIRR) Pilot, launched in January 2024, is a groundbreaking initiative aimed at democratizing access to AI resources in the United States. Led by the National Science Foundation (NSF) in collaboration with 12 federal agencies and 26 private-sector and academic partners, the NAIRR Pilot is designed to provide researchers with essential AI computing power, datasets, and tools. The NAIRR Pilot is organized into four operational focus areas: 1. NAIRR Open: Led by NSF, this area supports open AI research by providing access to AI resources through the NAIRR Pilot Portal and coordinated allocations. 2. NAIRR Secure: Co-led by the National Institutes of Health (NIH) and the Department of Energy (DOE), this focus area supports AI research requiring privacy and security-preserving resources. 3. NAIRR Software: Also under NSF's leadership, this area facilitates the interoperable use of AI software, platforms, tools, and services across NAIRR Pilot resources. 4. NAIRR Classroom: Aimed at broadening participation, this focus area emphasizes education, training, user support, and outreach to new communities.

Annual Meeting Lessons learnt, challenges and opportunities were a focal point for attendees. We frequently broke into small groups to discuss these subjects. After all, a pilot program is all about learning what works and what can be improved. By conducting this in person, many people from different agencies, Universities and resource providers came together and got to know each other better. Sometimes the best experiences come from those conversations over a coffee (or tea) break. The keynote presentations featured on-going research funded by the pilot. We saw the intensive and innovative research that studies how plants can respond to increasingly harsh growing conditions, and the health improvement potential that will come from better understanding of proteins. We heard how pathways can be better developed for careers in AI.

Progress and Future Directions By May 2024, 35 projects had received computational access, covering AI ethics, language models, and healthcare applications. The NSF continues to seek additional datasets and expand its impact. As the NAIRR Pilot evolves, it represents a significant step towardresponsible AI research, which will benefit society as a whole.

Supercomputing 2024

Our research computing team was represented at the recent Supercomputing 2024 Conference in Atlanta. We typically collaborate with Arizona State University (ASU) and Northern Arizona University (NAU) for booth presence. However, this year we greatly increased our footprint and teamed up with our Institute for Computation & Data-Enabled Insight (ICDI). Much work went on in preparation that enabled us to offer several VR experiences that highlighted UArizona research and iconic sites like the Biosphere 2 and telescopes that in part comprise the Event Horizon Telescope

We also welcomed Dr. Bryan Carter and Ash Black who brought VR experiences and provided conference experience for their students.

A New Era in Research: The Nobel Prizes Showcase AI’s Transformative Power

What do two of the recent Nobel Prize awards have in common? In both cases of the Chemistry award and the Physics award, the committees recognized the transformative power of artificial intelligence, and the high-performance computing (HPC) that underpins it.

Geoffrey Hinton of Google DeepMind and Princeton professor John J Hopfield received the physics honor for their groundbreaking work in artificial neural networks. “The laureates’ work has already been of the greatest benefit. In physics we use artificial neural networks in a vast range of areas, such as developing new materials with specific properties,” says Ellen Moons, Chair of the Nobel Committee for Physics.

Demis Hassabis and John Jumper from Google's AI division DeepMind and David Baker from the University of Washington were awarded the 2024 Nobel Prize in Chemistry. Hassabis and Jumper received the award for AlphaFold2, an AI system that accurately predicts the 3D structures of proteins from their amino acid sequences in minutes. AlphaFold has predicted over 200 million protein structures, and has, so far, over 2 million users. This means it has already potentially saved millions of dollars and hundreds of millions of years in research time.

Researchers at the University of Arizona take advantage of AlphaFold to advance their studies of protein folding using Puma, our newer supercomputer. We host the dataset to save researchers a lot of time, storage capacity, and provide compute performance. Our copy has over 200,000 files in 2.8TB. The latest is a lot bigger. We also host the containers with the code required.