NATIONAL SCIENCE FOUNDATION's update

NSF and the Simons Foundation partner to uncover foundations of deep learning August 25, 2020 Automated systems, designed to simplify our lives, are everywhere. From customer service chatbots to self-driving cars, artificial intelligence and related technologies continue to propel us forward at an ever-increasing pace. Now, the U.S. National Science Foundation and the Simons Foundation Division of Mathematics and Physical Sciences have partnered to fund research through the Mathematical and Scientific Foundations of Deep Learning, or MoDL, program. The interdisciplinary projects seek to understand and develop the theoretical foundations for deep learning networks. Deep Learning is part of a broader family of machine-learning methods that uses artificial neural networks to digest large amounts of raw data inputs and train AI systems without direct human supervision. "NSF and our partners at the Simons Foundation recognize the importance of discovering the mechanisms by which deep learning algorithms work," says Juan Meza, Director of the Division of Mathematical Sciences at NSF. "By understanding the limits of these networks, we can push them to the next level." Each team is receiving a total of $10 million over the next five years. The Collaboration on the Theoretical Foundations of Deep Learning is led by the University of California, Berkeley. Seven additional academic partners, including two international collaborators, make up a team that aims to study the mathematical mechanisms that underpin the practical success of deep learning; explain the limitations of current methods; and expand the accuracy and applicability of deep learning systems. The Transferable, Hierarchical, Expressive, Optimal, Robust, Interpretable NETworks (THEORINET) is led by Johns Hopkins University. With four additional collaborating institutions, THEORINET seeks to analyze properties of deep neural networks; develop robust learning algorithms; uncover new architectures for complex data; and design new representations suitable for transferring to multiple tasks. Complementing NSF's National Artificial Intelligence Research Institutes, the MoDL program supports collaborations between mathematicians, statisticians, electrical engineers and theoretical computer scientists. In addition to ambitious research projects, the program will train students, host workshops and summer schools, and provide open access to results. As the need for data scientists grows, the benefits of programs like this one become clear. The interdisciplinary focus will build mathematical foundations and advance the understanding of deep learning and AI and enable the national workforce.

NSF advances artificial intelligence research with new nationwide institutes

08/26/2020

NSF advances artificial intelligence research with new nationwide institutes August 26, 2020 WASHINGTON — The U.S. National Science Foundation is establishing new artificial intelligence institutes to accelerate research, expand America's workforce, and transform society in the decades to come. Enabled by sustained federal investment and channeled toward issues of national importance, continued advancement in AI research holds the potential for further economic impact and improvements in quality of life. With an investment of over $100 million over the next five years, NSF's Artificial Intelligence Institutes represent the nation's most significant federal investment in AI research and workforce development to date. The $20 million investment in each of five NSF AI institutes is just the beginning, with more institute announcements anticipated in the coming years. "NSF's long history of investment in AI research and workforce development paved the way for many of the breakthrough commercial technologies permeating and driving society today," said NSF Director Sethuraman Panchanathan. "NSF invests more than $500 million in AI research annually. We are supporting five NSF AI Institutes this year, with more to follow, creating hubs for academia, industry, and government to collaborate on profound discoveries and develop new capabilities to advance American competitiveness for decades to come." Led by NSF, and in partnership with the U.S. Department of Agriculture's National Institute of Food and Agriculture, the U.S. Department of Homeland's Security Science and Technology Directorate, and the U.S. Department of Transportation's Federal Highway Administration, these institutes will serve as nodes in a broader nationwide network that will pursue transformational advances in sectors of societal impact, from extreme weather preparedness to K-12 education. In addition to the five new NSF AI Institutes, USDA is announcing two of its first institutes today supported through this joint program, providing an additional $40 million over the next five years. NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography, led by a team at the University of Oklahoma, Norman, assembles researchers in AI, atmospheric and ocean science, and risk communication to develop user-driven trustworthy AI that addresses pressing concerns in weather, climate, and coastal hazards prediction. With AI certificate programs aimed at workforce skills, the institute is providing the research and training necessary for the future workforce to deliver the advances needed to deal with forecasting and prediction challenges. NSF AI Institute for Foundations of Machine Learning, led by a team at the University of Texas, Austin, focuses on major theoretical challenges in AI, including next-generation algorithms for deep learning, neural architecture optimization, and efficient robust statistics. The institute's partners include large industrial technology companies and the city of Austin. Major online coursework and research initiatives will bring current AI tools to thousands of students and professionals across the country. NSF AI Institute for Student-AI Teaming, led by a team at the University of Colorado, Boulder, develops groundbreaking AI that helps both students and teachers to work and learn together more effectively, and equitably, while helping educators focus on what they do best: inspiring and teaching students. The vision is to develop engaging "AI partners" that will observe, participate in, and facilitate collaborative STEM learning conversations by interacting naturally through speech, gesture, gaze, and facial expression in real-world classrooms and remote learning settings. NSF AI Institute for Molecular Discovery, Synthetic Strategy, and Manufacturing (or the NSF Molecule Maker Lab), led by a team at the University of Illinois at Urbana-Champaign, focuses on development of new AI-enabled tools to accelerate automated chemical synthesis and advance the discovery and manufacture of novel materials and bioactive compounds. The institute also serves as a training ground for the next generation of scientists with combined expertise in AI, chemistry, and bioengineering. NSF AI Institute for Artificial Intelligence and Fundamental Interactions, led by a team at the Massachusetts Institute of Technology, incorporates workforce development, digital learning, outreach, and knowledge transfer programs to develop AI methods that integrate the laws of physics as a guiding framework to advance our knowledge — from the smallest building blocks of nature to the largest structures in the universe — and galvanize AI research innovation to broaden societal impacts. USDA-NIFA AI Institute for Next Generation Food Systems, led by a team at the University of California, Davis, integrates a holistic view of the food system with AI and bioinformatics to understand biological data and processes, addressing issues of molecular breeding to optimize traits for yield, crop quality, and pest/disease resistance; agricultural production, food processing and distribution, and nutrition. Major emphasis is on inclusive education and outreach approaches to build a diverse, next-generation workforce. USDA-NIFA AI Institute for Future Agricultural Resilience, Management, and Sustainability, led by a team at the University of Illinois at Urbana-Champaign, advances AI research in computer vision, machine learning, soft object manipulation and intuitive human-robot interaction to solve major agricultural challenges including labor shortages, efficiency and welfare in animal agriculture, environmental resilience of crops, and the need to safeguard soil health. The institute features a new joint Computer Science + Agriculture degree and global clearinghouse to foster collaboration in AI-driven agriculture research. "The National AI Institutes being awarded today comprise large, multi-disciplinary, and multi-sector collaborations: they bring together consortia of dozens of universities and other organizations, ultimately spanning academia, government, and industry," said Michael Kratsios, U.S. Chief Technology Officer. "In effect, over the next five years, some of the best minds in the country will be tackling some of the grandest challenges that we face, both in terms of new AI techniques as well as breakthroughs in fields of science and engineering and sectors of our economy. And along the way, they will nurture the future American workforce in AI research and practice." Learn more about the NSF AI Institutes and artificial intelligence research by visiting nsf.gov. For more on NSF's investments in AI, see our fact sheet, "American Leadership in Artificial Intelligence" and the NSF Science Matters article "New NSF AI Research Institutes Push Forward the Frontiers of Artificial Intelligence".

Check out the latest from NSF’s Science Matters blog. Wed, 26 Aug 2020 New AI Research Institutes to push forward the frontiers of artificial intelligence You open a letter from your grandmother. No money falls out, but you keep reading anyway. Her “old-fashioned” handwriting is different from what you are used to, the cursive script filled with curls and other flourishes. It takes a minute to adjust, but your brain can easily make out the message: The neighborhood cats are still stalking her backyard bird feeder, and she loves you very much. Your brain’s ability to decipher different types of handwritten text is extraordinary. It’s just one of many human abilities that scientists are inspired to replicate through the use of artificial intelligence. AI machine learning techniques rely on neural networks—layers of algorithms inspired by the human brain that enable incremental learning through mining large amounts of data. It’s how you are able to deposit checks in your bank account by snapping a quick photo with your phone. And it’s how Netflix knew to recommend the Fyre Festival documentary based on the fact that you’ve viewed every episode of Tiger King twice—including that bonus quarantine episode.    The applications of AI extend far beyond handwriting analysis and binge-watching, though. Advances in AI research over the last several decades have enabled breakthroughs across nearly every sector of society, from understanding the cosmos to advancing healthcare to improving our transportation systems and enhancing manufacturing. As the primary non-defense federal funder of fundamental AI research, the U.S. National Science Foundation has played a leading role in supporting basic and translational research, advancing and scaling computing resources that power AI innovations, as well as building education and workforce development for America’s AI researchers and practitioners. ... Continue Reading