The team led by Columbia University won a $20 million NSF grant to develop the AI ​​Institute

New York, NY—May 4, 2023—The National Science Foundation (NSF) today announced a $20 million grant to establish the AI ​​Institute for Artificial and Natural Intelligence (ARNI), an interdisciplinary center led by Columbia University that will work with top researchers around the world. countries to focus on national priorities: linking the major advances made in artificial intelligence (AI) systems to revolutions in our understanding of the brain.

Collaborative partnership

ARNI is a collaboration between Columbia, Baylor College of Medicine, City University of New York, Harvard, Princeton, Howard Hughes Medical Institute, Mila Quebec AI Institute, Tuskegee University, University of Pennsylvania, and UTHealth Houston. Industry partners include Amazon, DeepMind, Google, IBM, and Meta, and outreach partners include Neuromatch Academy and the New York Hall of Science. As well as receiving NSF funding, ARNI is funded by a partnership between NSF and the Office of the Undersecretary of Defense for Intelligence and Security (R&E).

“The National Science Foundation has long been a strong supporter of research at Columbia University and we are very excited about this new collaboration,” said Mary Boyce, Provost, Columbia University. “The AI ​​Institute for Artificial and Natural Intelligence is leveraging not only our interdisciplinary strengths across the University, but also our partnerships — both old and new — across the country. By bringing together the tremendous advances made in AI systems and our growing understanding of the brain, ARNI will fuel advances in neuroscience and AI, and transform our world in the next decade.”

A revolution in neuroscience, cognitive science and AI research

The last 10 years have seen spectacular advances in interrogating neural activity, circuits, and learning, but our neuroscientific insights have so far only superficially informed AI. Instead, our rapidly evolving AI methods and systems based on large amounts of data are just starting to impact neuroscience. ARNI will meet the urgent need for a new paradigm of interdisciplinary research between neuroscience, cognitive science and AI. This will accelerate progress in all three areas and expand the transformative impact on society in the next decade.

“ARNI is an ambitious plan that requires dedicated efforts across institutions, and we have assembled one of the strongest research groups in theoretical neuroscience and basic machine learning in the world,” said Jeannette Wing, Executive Vice President of Research, Columbia University. “Our PI builds on existing, and often closely interacting, neural and AI groups at Columbia, Baylor, Penn, along with Janelia, MILA, Google/DeepMind, and Meta. At the same time, we are building new bridges to Tuskegee, CUNY, Yale, IBM and beyond. Our track record is already strong and now, thanks to the National Science Foundation, we hope ARNI can meet the urgent need for a new paradigm of interdisciplinary research between neuroscience and AI.”

Research team

ARNI will be led by Principal Investigators (PIs) Richard Zemel, Kathleen McKeown, and Christos Papadimitriou (Computer Science, Engineering Columbia), Liam Paninski (Zuckerman Institute and Department of Statistics and Neuroscience, Columbia University), and Xaq Pitkow (Baylor College of Medicine) , University of Rice). This PI brings together expertise from multiple disciplines, including artificial intelligence, theoretical computer science, statistics, neuroscience, physics, and cognitive science. They will work with large research teams to overcome the limitations and challenges of today’s machine learning systems, including learning with limited data, reasoning about causality and uncertainty, and lifelong learning – all hallmarks of biological systems – while also pushing our boundaries. understanding of how the brain calculates and learns.

Bridging the gap between artificial and biological tissue

ARNI will bridge the current significant gap between artificial and biological networks and provide space for broad and diverse applications, from industrial sectors, such as powerful and interpretable medical decisions and smarter home assistants; for social applications, such as better social safety nets and multimodal assistance systems to assist the vulnerable; to scientific discoveries such as providing hypotheses about brain function and creating powerful tools for extracting insights from enormous data.

“Thanks to new AI algorithms, our knowledge of neuroscience and cognitive science is growing every day,” said Shih-Fu Chang, Columbia Dean of Engineering. “And with our growing knowledge of the brain and cognitive sciences, we have better AI algorithms, making progress on critical applications that impact our world. ARNI aims to address the limitations of today’s AI while also introducing modern AI into neuroscience, basic machine learning, and cognitive science. Engineers are critical to applying scientific insights to real-world problems, and we look forward to the groundbreaking discoveries that will come from these exciting large-scale collaborations. We thank the National Science Foundation for helping us create this modern interdisciplinary arsenal, coming together to generate new insights and advance this very important new field.”

Trustworthy system

Richard Zemel, Director of ARNI and Trianthe Dakolias Professor of Engineering and Applied Science at Columbia Engineering, has been instrumental in the development of AI technology, most recently as co-founder and Research Director of the Vector Institute for Artificial Intelligence. His research spans machine learning and its interactions with neuroscience and cognitive science, as well as robust and equitable machine learning. He notes that strong and fair machine learning is essential for using these new AI tools to improve society.

“A key characteristic of our approach is the focus on developing interpretable models, often based on causal, cognitively based approaches, based on our research on the brain,” said Zemel. “This will lead to the development of trusted systems that can explain their reasoning to end users in terms they understand. This is especially important in high-risk applications such as healthcare, law and to support vulnerable populations.”

Education and outreach

The Institute will provide educational and research opportunities for undergraduate and graduate students, as well as postdoctoral trainees, within and at the interface of AI, neuroscience, and cognitive science. Outreach partners, including Neuromatch Academy and the New York Hall of Science, will help inform the public about these new developments and teach important skills to the next generation of students.

Columbian Engineering

Since 1864, the Fu Foundation School of Engineering and Applied Science at Columbia University has been a resource to the world for major advances in human advancement. Today, Columbia Engineering is a leading engineering school and hub for high-impact research. Embedded in New York City, the School brings together more than 250 faculty members and more than 6,000 undergraduate and graduate students from around the world to push the boundaries of knowledge and solve humanity’s most pressing problems.

Zuckerman Institute

Working closely with Columbia’s Zuckerman Institute, the ARNI team includes leading senior investigators and visionaries in the fields of theoretical and cognitive neuroscience. The Zuckerman Institute brings together a diverse range of researchers whose expertise spans multiple interdisciplinary areas of neuroscience research, providing an unparalleled intellectual environment, multi-level support and opportunities for interaction.

NSF

The US National Science Foundation drives the nation forward by advancing fundamental research in all fields of science and engineering. NSF supports research and people by providing the facilities, instruments and funding to support their ingenuity and maintain the US as a global leader in research and innovation. With a fiscal 2022 budget of $8.8 billion, NSF funds span all 50 states through grants to nearly 2,000 colleges, universities and institutions. Annually, NSF receives more than 40,000 competitive proposals and generates approximately 11,000 new awards. The award includes support for cooperative research with industry, Arctic and Antarctic research and operations, and US participation in international scientific endeavours. www.nsf.gov