Good afternoon, everyone.
This is Yibiao Zhao.
I'm the CEO and Co-founder of iSee.
Today I will talk about engineering common sense.
In 2015, I joined Professor Josh Tenenbaum's lab at MIT,
working on a collaborative robot.
Our objective is trying to teach a robot
to understand its human collaborators by doing
common sense reasoning.
One type of common sense is so-called the theory
of mind, which is the ability to let the human being understand
the mental state of others.
Let's take a look at this theory of mind in action--
this experiment by [? Juan ?] [INAUDIBLE] [? Tomasello. ?]
In this video, the adult is trying to perform some action,
but he cannot.
This 18-month-old young child is observing the corner.
With his limited life experience,
he cannot only figure out intention of the adults,
but also find his best way to help him.
Look at his eyes--
absolutely incredible.
Let's contrast this with current AI technology.
Current artificial intelligence has already
beaten the best human players at a goal
with limited demand and finite rules.
However, it still lacks this kind
of flexible, common-sense reasoning
to do what the young child can do in the real world.
Because of this, most robots are separated
from human working space--
as simply, it's not safe to be together.
At MIT, I'm very fortunate to join the team
to develop the computational model to mimic what's going on
in that 18-month-old's mind.
And to engineer this type of flexible common-sense,
to enable a robot to collaborate with humans.
We realize by enabling a robot to collaborate with humans
we can create a huge opportunity,
by using AI to bring robots into our lives.
So we started the company, iSee.
We believe robots should not only see, but also
truly understand.
A self-driving car can be the first kind of personal robot
that can fundamentally change our lives.
However, there are major challenges.
First of all, the self-driving car
has to understand other human drivers,
and predict their behavior-- so that we
can drive cooperatively, and also proactively.
So here, the current AI is only generalized
based on the training set.
While we're driving, there's an unlimited number
of corner cases.
It's simple to collect the data set,
but it's almost impossible to collect
a data set to cover everything in the world.
So today, I have a challenge.
I have to learn how to use this thing--
you know, second.
Humans are very amazing to deal with new situations.
At iSee, we're trying to mimic this type of intelligence.
We build a new type of AI, that can flexibly
compose new situations, and solve
them using common-sense reasoning in real time.
Like I mentioned before, we also need
to enable a car to drive cooperatively and proactively.
The current system can estimate the position velocity
of other vehicles, and then react to it.
At iSee, we're trying to build a system that also understands
the intention of other drivers.
Because of this, we can pretty reliably
predict the behavior of other human drivers,
and to drive proactively.
One example of this is, when cars merge on a highway.
The car not only needs to estimate
the intention of others, but also
needs to negotiate who goes first.
I'm going to show you a video of how
an iSee car negotiates traffic.
iSee car heading down Route 2, which
[INAUDIBLE] for unfriendly drivers.
Here you see the iSee car is about to see the other car
coming down from the ramp--
just like that 18-month young child is going to do.
The car-- we're about to ease the gas--
make some time to predict the intention of the other driver.
And to gently brake, to make room for the other car
to merge.
This is some of the ability [INAUDIBLE]
human looks very trivial.
But this is something that no other system can do well.
This is just the beginning.
We have enjoyed when our cars run the area
for more than 10,000 miles.
We believe we will be the first company
to build truly safe, smart, and the humanistic AI--
and to bring this type of AI, integrating into our society
seamlessly, and to benefit our lives.
Thank you.
And we're looking forward to contribute at MIT IQ.
Thank you.
[APPLAUSE]