Name: Dr. Yann LeCun, "How Could Machines Learn as Efficiently as Animals and Humans?"
Uploaded: 2018-01-06T15:25:17.000Z
Duration: 1 h 31 min 38 s
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And I'm Rossi Luo, faculty host for today's event.

And for those of you new to our departmental seminar,

the format is usually that the presentation

followed by a question and answer session.

And because of the size of crowd today, we

thing to capture your questions and for videotaping and also

And today I'm very pleased to introduce Professor Yann LeCun.

Professor LeCun is a director of Facebook AI Research,

And he is also senior professor of computer science,

neuroscience, and electronic computer engineering

He's also the founding director of NYU Center for Data Science.

Before joining NYU, he had a research department

Professor LeCun has made extraordinary research

contributions in machine learning, computer vision,

mobile robotics, computational neuroscience.

And he is also a founding father of convolutional nets.

the creation of new an exploding field in machine learning

called artificial intelligence tool for various range

of applications from image to natural text processing.

including the election to the US National

How Can Machines Learn as Efficiently as Animals

told me you drove from Boston or many places are very far.

So without further ado, let's welcome Professor Yann LeCun

A game I play now occasionally when I give a talk here is I

count how many former colleagues from AT&T are in the room.

So, how can machines learn as efficiently

Here it is in a slightly less vernacular form.

Recently, I gave a talk at a conference in Columbia

called the Compositional and Cognitive Neuroscience

All of these AI systems that we see now, none of them

And what he means by this is that none of them

actually learn stuff that are as complicated as what

So we don't have robots that are nearly as

You know, we have machines that can play golf better

And so that tells us there are major pieces of learning

That animals are able to do that, we don't do--

and telling you the punch line in advance, which

is that we need a new paradigm for learning,

or a new way of formulating that has old paradigms that

will allow machines to learn how the world works the way animals

So all the applications of machine learning,

AI, deep learning, all the stuff you see the actual real world

applications, most of them use supervised learning.

Most of them use some form of supervised learning.

And you know, supervised learning, we all--

I'm sure most of you in the room know what it is.

You want to build a machine that classifies cars from airplanes.

If it says airplane, you adjust the knobs on the machine

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Dr. Yann LeCun, "How Could Machines Learn as Efficiently as Animals and Humans?"

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