Harvard University on Tuesday launched the Kempner Institute for the Study of Natural and Artificial Intelligence, a new University-wide initiative standing at the intersection of neuroscience and artificial intelligence, seeking fundamental principles that underlie both human and machine intelligence. The fruits of discoveries will flow in both directions, enhancing understanding of how humans think, perceive the world around them, make decisions, and learn, thereby advancing the rapidly evolving field of AI.
The institute will be funded by a $500 million gift from Priscilla Chan and Mark Zuckerberg, which was announced Tuesday by the Chan Zuckerberg Initiative. The gift will support 10 new faculty appointments, significant new computing infrastructure, and resources to allow students to flow between labs in pursuit of ideas and knowledge. The institute’s name honors Zuckerberg’s mother, Karen Kempner Zuckerberg, and her parents — Zuckerberg’s grandparents — Sidney and Gertrude Kempner. Chan and Zuckerberg have given generously to Harvard in the past, supporting students, faculty, and researchers in a range of areas, including around public service, literacy, and cures.
“The Kempner Institute at Harvard represents a remarkable opportunity to bring together approaches and expertise in biological and cognitive science with machine learning, statistics, and computer science to make real progress in understanding how the human brain works to improve how we address disease, create new therapies, and advance our understanding of the human body and the world more broadly,” said President Larry Bacow.
“Priscilla Chan and Mark Zuckerberg have demonstrated a remarkable commitment to promoting discovery, innovation, and service at Harvard and other academic institutions around the United States,” said Bacow. “Their support for the creation of the Kempner Institute will advance Harvard’s education and research mission and is only the most recent way in which they have sought to do so. From supporting the study of COVID-19 treatments and advancing literacy research to boosting public service opportunities for undergraduates, they have shown a genuine commitment through their work at the Chan Zuckerberg Initiative and beyond to curing disease, improving lives, and encouraging others to serve.”
A focus of the institute will be training future generations of leaders and researchers in this area through funding dedicated to supporting undergraduate and graduate students as well as postdoctoral fellows. The institute, expected to open at the new Science and Engineering Complex in Allston by the end of 2022, is committed to the active recruitment of individuals from backgrounds traditionally underrepresented in STEM fields. It will be headed by Bernardo Sabatini, the Alice and Rodman W. Moorhead III Professor of Neurobiology at Harvard Medical School, and Sham Kakade, who in January will become a Gordon McKay Professor of Computer Science and Statistics at the Harvard John A. Paulson School of Engineering and Applied Sciences and a professor in the Faculty of Arts and Sciences. With a faculty steering committee made up of faculty across Schools and disciplines, the institute will convene experts in computer science, applied mathematics, neuroscience, cognitive science, statistics, and engineering.
Sabatini and Kakade, who is coming to Harvard from the University of Washington, spoke with the Gazette about the new effort and the promise and challenge presented by AI and the role it might play in all of our lives. Interview has been edited for length and clarity.
Bernardo Sabatini and Sham Kakade
GAZETTE: Tell me about the new institute. What is its main reason for being?
SABATINI: The institute is designed to take from two fields and bring them together, hopefully to create something that’s essentially new, though it’s been tried in a couple of places. Imagine that you have over here cognitive scientists and neurobiologists who study the human brain, including the basic biological mechanisms of intelligence and decision-making. And then over there, you have people from computer science, from mathematics and statistics, who study artificial intelligence systems. Those groups don’t talk to each other very much.
We want to recruit from both populations to fill in the middle and to create a new population, through education, through graduate programs, through funding programs — to grow from academic infancy — those equally versed in neuroscience and in AI systems, who can be leaders for the next generation.
Over the millions of years that vertebrates have been evolving, the human brain has developed specializations that are fundamental for learning and intelligence. We need to know what those are to understand their benefits and to ask whether they can make AI systems better. At the same time, as people who study AI and machine learning (ML) develop mathematical theories as to how those systems work and can say that a network of the following structure with the following properties learns by calculating the following function, then we can take those theories and ask, “Is that actually how the human brain works?”
KAKADE: There’s a question of why now? In the technological space, the advancements are remarkable even to me, as a researcher who knows how these things are being made. I think there’s a long way to go, but many of us feel that this is the right time to study intelligence more broadly. You might also ask: Why is this mission unique and why is this institute different from what’s being done in academia and in industry? Academia is good at putting out ideas. Industry is good at turning ideas into reality. We’re in a bit of a sweet spot. We have the scale to study approaches at a very different level: It’s not going to be just individual labs pursuing their own ideas. We may not be as big as the biggest companies, but we can work on the types of problems that they work on, such as having the compute resources to work on large language models. Industry has exciting research, but the spectrum of ideas produced is very different, because they have different objectives.
GAZETTE: Is it by default going to be human intelligence that you’re studying, as opposed to some other animal intelligence?
SABATINI: Clearly one is interested in understanding human intelligence because it’s the most impressive among animals, but we will draw from the studies of any organism to gain insights into how intelligence works. The institute itself is going to be all dry lab, purely computational, but we will happily take data from animal studies. We will also have a collaborative grant program to seed directed studies and fund groups that we think will generate data crucial to understanding intelligence.
GAZETTE: You mention large-scale computing. Will that hardware require new systems being installed? Or are you going to use the existing infrastructure?
SABATINI: We’re going to buy a lot of GPUs [graphics processing units, that, like CPUs, power many computers] and also make use of cloud computing services.
GAZETTE: What about the institute’s faculty, both new and those already at Harvard working on these questions?
SABATINI: There’s great expertise already at Harvard, and one goal is to bring that expertise together. Basically, we want this institute to be a destination: If you care about intelligence, whether it’s natural or artificial, you should want to come to this institute. That will draw from Harvard and across the world. We have new faculty coming to Harvard who will be explicitly in this domain, who will then help recruit graduate students. We’re going to have professional engineering support on staff to help people translate ideas into code and into deployable solutions. There will also be a very impressive computational back end — hardware to be able to do sophisticated models in a way that is not common in academia. We will have programs by which people already at Harvard can have access to the compute structure and be involved in teaching and recruiting students, and our resources will be available to collaborative Harvard graduate programs, and so forth. We want the community to be as big as possible.
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