Institute for Artificial Intelligence and Fundamental Interactions (IAIFI): Infusing physics intelligence into artificial intelligence

Author:

Thaler Jesse1ORCID,Williams Mike1ORCID,LaFleur Marisa1

Affiliation:

1. Massachusetts Institute of Technology Cambridge Massachusetts USA

Abstract

AbstractThe NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI, pronounced /aI‐faI/) is one of the inaugural NSF AI research institutes (https://iaifi.org). The IAIFI is enabling physics discoveries and advancing foundational AI through the development of novel AI approaches that incorporate first principles from fundamental physics. By combining state‐of‐the‐art research with early career talent and a growing AI + physics community in the Boston area and beyond, the IAIFI is enabling researchers to develop AI technologies to tackle some of the most challenging problems in physics, and 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, IAIFI researchers are applying physics principles to develop more robust AI tools and to illuminate existing AI technologies. To cultivate human intelligence, the IAIFI promotes training, education, and public engagement at the intersection of physics and AI. In these ways, the IAIFI is fusing deep learning with deep thinking to gain a deeper understanding of our universe and AI.

Funder

National Science Foundation

Publisher

Wiley

Reference8 articles.

1. SHAPER: can you hear the shape of a jet?

2. Sampling using SU(N) gauge equivariant flows

3. Kitouni O. N.Nolte andM.Williams.2022. “Finding NEEMo: Geometric Fitting using Neural Estimation of the Energy Mover's Distance.” ArXiv.https://doi.org/10.48550/arXiv.2209.15624

4. Lasby M. A.Golubeva U.Evci M.Nica andY.Ioannou.2023. “Dynamic Sparse Training with Stuctured Sparsity.” ArXiv.https://doi.org/10.48550/arXiv.2305.02299

5. Liu Z. O.Kitouni N.Nolte E. J.Michaud M.Tegmark andM.Williams.2022. “Towards Understanding Grokking: An Effective Theory of Representation Learning.” ArXiv.https://doi.org/10.48550/arXiv.2205.10343

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3