The Institute for Artificial Intelligence and Fundamental Interactions (IAIFI) will enable physics discoveries and advance foundational artificial intelligence (AI) through the development of novel AI approaches that incorporate first principles from fundamental physics. AI is transforming many aspects of society, including the ways that scientists are pursuing groundbreaking discoveries. For many years, physicists have been at the forefront of applying AI methods to investigate fundamental questions about the Universe. As an example, AI played a key role in the discovery and study of the Higgs boson, the last missing ingredient in the Standard Model of particle physics. Further progress will require a revolutionary leap in AI, as both the complexity of physics problems and the size of physics datasets continue to grow. The goal of the IAIFI is to develop and deploy the next generation of AI technologies, based on the transformative idea that artificial intelligence can directly incorporate physics intelligence. IAIFI researchers will use these new AI technologies to tackle some of the most challenging problems in physics, from precision calculations of the structure of matter, to gravitational wave detection of merging black holes, to the extraction of new physical laws from noisy data. IAIFI researchers will also transfer these technologies to the broader AI community, since trustworthy AI is as important for physics discovery as it is for other applications of AI in society. To cultivate human intelligence, the IAIFI will promote training, education, and outreach at the intersection of physics and AI. In this way, the IAIFI will advance physics knowledge – from the smallest building blocks of nature to the largest structures in the Universe – and galvanize AI research innovation.

The IAIFI will enable physics discoveries and advance foundational AI through the development of novel “Ab initio AI” approaches that incorporate first principles and best practices from fundamental physics. Ab initio AI will make intractable theoretical physics calculations feasible, predicting complex emergent phenomena that are computationally daunting to tackle even though the underlying physical laws are well understood. It will also transform many experimental physics applications, where ab initio principles will be used to design AI methods that are more easily verifiable using well-understood calibration data samples, leading to better quantification of uncertainties. While each physics use-inspired goal will present its own issues, the IAIFI’s focus will be on finding shared solutions, since these problems involve similar prior knowledge, are based on the same underlying ab initio principles, and face common experimental and theoretical challenges. The same challenges that arise in the development and deployment of AI methods across a broad spectrum of frontier physics research, including verification and interpretability of AI solutions, are also faced in other AI application domains. Therefore, by developing ab initio AI, the IAIFI will accelerate the pace of physics discovery, extend the frontiers of AI research, and develop new pathways for broad adoption. The IAIFI will make Cambridge and the surrounding Boston area a nexus point for collaborative efforts aimed at advancing both physics and AI and at connecting to industry and science partnerships. Part of the IAIFI mission will be to disseminate knowledge about (and enthusiasm for) physics, AI, and their intersection through various workforce development, digital learning, outreach, broadening participation, and knowledge transfer programs.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Physics (PHY)
Type
Cooperative Agreement (Coop)
Application #
2019786
Program Officer
Saul Gonzalez
Project Start
Project End
Budget Start
2020-11-01
Budget End
2025-10-31
Support Year
Fiscal Year
2020
Total Cost
$4,000,000
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Type
DUNS #
City
Cambridge
State
MA
Country
United States
Zip Code
02139