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.