MIT Quest for Intelligence Launch: The Core – Human and Machine Intelligence

MIT Quest for Intelligence Launch: The Core – Human and Machine Intelligence


Thank you, David, for
those wonderful comments. Good morning everyone. My name is Mike Sipser, I’m
the Dean of Science at MIT. The intelligence quest
embodies MIT’S commitment to the pursuit of deep
scientific inquiry around one of the most challenging
problems of our time, how the brain produces
intelligent behavior, and how machines can
safely and efficiently exhibit intelligent behavior. Many of today’s major
advances in machine learning and artificial
intelligence have benefited from science done years ago. Future transformative
advances in AI may very well require
an understanding of the mechanisms of the human
mind in engineering terms. A convergence of
science and engineering, this constitutes the core of
the MIT intelligence quest. MIT’s strengths in brain,
and cognitive sciences, and in computer science,
uniquely positioned us to lead the effort to
understand intelligence and our faculty and students
believe the time is now. It is my privilege to
introduce this session on the core of distinguished
scientists and engineers who are working at the
forefront of this quest, so I’m just going to run
through introductions of all of the folks who
are going to be speaking in this first session
and then they’re going to come up
one-by-one to speak. Our first speaker
is Jim DiCarlo, head of the Department of Brain
and Cognitive Sciences at MIT, the Peter deFlorez
professor of neuroscience, an investigator at the McGovern
Institute for Brain Research. Jim’s research goal
is to reverse engineer the brain mechanisms that
underlie visual intelligence. If you read Jim’s piece in
Wired Magazine last month, you may already know
that he is confident that powerful insights
in artificial and human intelligence can be gained
by combining core research in engineering and in science. After Jim, Daniela
Rus will speak. Daniela is the director of the
Computer Science and Artificial Intelligence Laboratory, better
known as CSAIL and the Andrew and Erna Viterbi Professor
of Electrical Engineering and Computer Science. Her research addresses
some of the gaps between the function
of today’s robots and the promise
of future robots, increasing the ability
of machines to reason, learn, adapt to complex tasks
in human centered environments. Daniela’s talk will
be on the future of intelligence engineering. After Daniela, Tomaso
Poggio will speak. Tommy is the Eugene
McDermott professor of Brain and Cognitive Sciences,
an investigator at the McGovern Institute for Brain
Research, and the Director of the Center for Brains,
Minds, and Machines, a multi-institutional
center funded by the NSF. Tommy’s research program
posits that learning is at the core of the
problem of intelligence, both biological and artificial. He aims to understand
the processes that underlie learning, memory,
and reasoning, developing top to bottom computational models
to explain how humans visually perceive the world around them. He will speak to us on the
science and engineering of intelligence. Following Tommy in the session
today will be Antonio Tarralba. Antonio is a professor
in the Department of Electrical Engineering
and Computer Science and a member of CSAIL. He’s also director of the
MIT-IBM Watson AI Lab. An expert in computer
vision machine learning, and human visual
perception, Antonio’s project spanned a wide range
from investigating object recognition, and
scene understanding, and pictures and movies, to
studying the inner workings of deep neural networks. He will speak to us
about teaching machines to see and hear. After that we’ll hear
from Laura Schultz. Laura is a professor
of cognitive science in the Department of Brain
and Cognitive Sciences at MIT. She’s also the
principal investigator in MIT’S early childhood
cognition laboratory. Laura studies the
representations and learning mechanisms that underlie our
commonsense understanding of the physical and
social world, all of which is constructed during
early childhood. After Laura in the
program today is Rebecca Saxe, a professor
of cognitive neuroscience in the Department of Brain
and Cognitive Sciences, an investigator at the
McGovern Institute. Rebecca studies
the question, how does the brain an electrical
and biological machine construct abstract thoughts. She’ll speak to
us about how we go about building a social brain. And finally, we will
hear from Josh Tenenbaum, he’ll be the last speaker
in the morning session. Josh is a professor of
computational cognitive science in the Department of Brain
and Cognitive Sciences, he’s a member of
CSAIL and a researcher in the Center for Brains,
Minds, and Machines. His research centers on
perception, learning, and common reasoning,
with the twin goals of better understanding
human intelligence in computational
terms and building more human like
intelligence in machines. The machine learning and
artificial intelligence algorithms developed
by Josh’s group are currently used by
hundreds of other science and engineering groups
around the world. Josh will conclude
this mornings session with a talk on scaling
artificial intelligence, but doing so the human way. So first, I will turn
the podium over to Josh. To Jim, sorry.