推进美国空军部人工智能挑战 (Advancing AI Challenges for the United States Department of the Air Force)

Christian Prothmann,Vijay Gadepally,Jeremy Kepner,Koley Borchard,Luca Carlone,Zachary Folcik,J. Daniel Grith,Michael Houle,Jonathan P. How,Nathan Hughes,Ifueko Igbinedion,Hayden Jananthan,Tejas Jayashankar,Michael Jones,Sertac Karaman,Binoy G. Kurien,Alejandro Lancho,Giovanni Lavezzi,Gary C. F. Lee,Charles E. Leiserson,Richard Linares,Lindsey McEvoy,Peter Michaleas,Chasen Milner,Alex Pentland,Yury Polyanskiy,Jovan Popovich,Jeffrey Price,Tim W. Reid,Stephanie Riley,Siddharth Samsi,Peter Saunders,Olga Simek,Mark S. Veillette,Amir Weiss,Gregory W. Wornell,Daniela Rus,Scott T. Ruppel

from arxiv, 8 pages, 8 figures, 59 references. To appear in IEEE HPEC 2025

The DAF-MIT AI Accelerator is a collaboration between the United States Department of the Air Force (DAF) and the Massachusetts Institute of Technology (MIT). This program pioneers fundamental advances in artificial intelligence (AI) to expand the competitive advantage of the United States in the defense and civilian sectors. In recent years, AI Accelerator projects have developed and launched public challenge problems aimed at advancing AI research in priority areas. Hallmarks of AI Accelerator challenges include large, publicly available, and AI-ready datasets to stimulate open-source solutions and engage the wider academic and private sector AI ecosystem. This article supplements our previous publication, which introduced AI Accelerator challenges. We provide an update on how ongoing and new challenges have successfully contributed to AI research and applications of AI technologies.

翻译：DAF-MIT人工智能加速器是美国空军部（DAF）与麻省理工学院（MIT）之间的合作项目。该计划旨在推动人工智能（AI）基础研究的突破性进展，以增强美国在国防和民用领域的竞争优势。近年来，人工智能加速器项目已开发并发布了多项公开挑战问题，旨在促进优先领域的人工智能研究。这些挑战的显著特征包括提供大规模、公开可用且适配人工智能处理的数据集，以激励开源解决方案，并吸引更广泛的学术界和私营部门人工智能生态系统参与。本文是对先前介绍人工智能加速器挑战的出版物的补充。我们进一步更新了当前及新增挑战如何成功推动人工智能研究及其技术应用的最新进展。