openCAMBRIDGE, MA

NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI)

National Science Foundation

Description

This grant renews funding for NSF's Institute for Artificial Intelligence and Fundamental Interactions (IAIFI) for the next five-year period. IAIFI is a research institute which is centered at MIT but which involves four Boston-area universities (MIT, Harvard, Northeastern, and Tufts). The over-arching goal of IAIFI is to enable physics discoveries and advance foundational artificial intelligence (AI) through the development of novel AI approaches that incorporate first principles from fundamental physics. This research is extremely timely and intrinsically cross-disciplinary. On the one hand, AI is transforming many aspects of society, including the ways in which scientists are pursuing groundbreaking discoveries. Indeed, for many years, physicists have been at the forefront of applying AI methods to investigate fundamental questions about the Universe --- for 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 whose discovery generated a Nobel Prize. On the other hand, further progress in such physics research will require and can help to foster a revolutionary leap in AI, as both the complexity of physics problems and the size of physics datasets continue to grow. By bringing physics and AI researchers together, IAIFI continues to stimulate developments in both directions. IAIFI will continue 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 are using 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 are also transferring these technologies back to the broader AI community, since trustworthy AI is as important for other applications of AI in society as it is for physics discovery. To further cultivate human intelligence, IAIFI will also continue to promote training, education, and outreach at the intersection of physics and AI. In this way, IAIFI will continue to advance physics knowledge –-- from the smallest building blocks of nature to the largest structures in the Universe --- while at the same time galvanizing AI research innovation. More technically, by combining revolutionary advances in deep learning from AI with the time-tested strategies of deep thinking from physics, IAIFI researchers will continue to gain a deeper understanding of our universe and of intelligence itself. IAIFI’s Foundational AI research infuses physics principles into AI to create state-of-the-art AI innovations, particularly in the subfields of representation learning, robust AI, and reinforcement learning. IAIFI researchers are developing AI techniques that can be used across a variety of applications while also using physics principles to better understand AI itself. IAIFI is also impacting theoretical physics by utilizing AI tools and techniques to enable physics discovery through the acceleration of theoretical physics calculations, especially in relation to nuclear/particle physics, quantum field theory and string theory, and quantum many-body physics. IAIFI research also has substantial impact on experimental physics at major NSF-funded facilities, including the Large Hadron Collider and the Laser Interferometer Gravitational-Wave Observatory, as well as at various neutrino experiments. Finally, IAIFI’s impact on Astrophysics --- a data-rich field that will significantly increase its data volume over the next decade --- is at the cutting edge of developing techniques for analyzing an unprecedented amount of information. Developments in this field can be used for applications ranging from image classification to data interpretation to anomaly detection, particularly in relation to dark- NSF Award ID: 2525568 | Program: 01002728DB NSF RESEARCH & RELATED ACTIVIT,01002829DB NSF RESEARCH & RELATED ACTIVIT,01002627DB NSF RESEARCH & RELATED ACTIVIT,01002930DB NSF RESEARCH & RELATED ACTIVIT,01003031DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Jesse Thaler | Institution: Massachusetts Institute of Technology, CAMBRIDGE, MA | Award Amount: $4,980,000 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2525568 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2525568.html

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Grant Details

Funding Range

$4,980,000 - $4,980,000

Deadline

May 31, 2031

Geographic Scope

CAMBRIDGE, MA

Status
open

External Links

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