Digital humans that look just like us | Doug Roble

137,959 views ・ 2019-05-28

TED


Please double-click on the English subtitles below to play the video.

00:13
Hello.
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I'm not a real person.
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I'm actually a copy of a real person.
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Although, I feel like a real person.
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It's kind of hard to explain.
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Hold on -- I think I saw a real person ... there's one.
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Let's bring him onstage.
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Hello.
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(Applause)
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What you see up there is a digital human.
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I'm wearing an inertial motion capture suit
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that's figuring what my body is doing.
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And I've got a single camera here that's watching my face
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and feeding some machine-learning software that's taking my expressions,
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like, "Hm, hm, hm,"
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and transferring it to that guy.
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We call him "DigiDoug."
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He's actually a 3-D character that I'm controlling live in real time.
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So, I work in visual effects.
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And in visual effects,
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one of the hardest things to do is to create believable, digital humans
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that the audience accepts as real.
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People are just really good at recognizing other people.
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Go figure!
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So, that's OK, we like a challenge.
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Over the last 15 years,
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we've been putting humans and creatures into film
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that you accept as real.
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If they're happy, you should feel happy.
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And if they feel pain, you should empathize with them.
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We're getting pretty good at it, too.
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But it's really, really difficult.
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Effects like these take thousands of hours
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and hundreds of really talented artists.
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But things have changed.
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Over the last five years,
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computers and graphics cards have gotten seriously fast.
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And machine learning, deep learning, has happened.
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So we asked ourselves:
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Do you suppose we could create a photo-realistic human,
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like we're doing for film,
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but where you're seeing the actual emotions and the details
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of the person who's controlling the digital human
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in real time?
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In fact, that's our goal:
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If you were having a conversation with DigiDoug
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one-on-one,
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is it real enough so that you could tell whether or not I was lying to you?
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So that was our goal.
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About a year and a half ago, we set off to achieve this goal.
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What I'm going to do now is take you basically on a little bit of a journey
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to see exactly what we had to do to get where we are.
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We had to capture an enormous amount of data.
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In fact, by the end of this thing,
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we had probably one of the largest facial data sets on the planet.
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Of my face.
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(Laughter)
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Why me?
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Well, I'll do just about anything for science.
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I mean, look at me!
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I mean, come on.
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We had to first figure out what my face actually looked like.
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Not just a photograph or a 3-D scan,
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but what it actually looked like in any photograph,
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how light interacts with my skin.
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Luckily for us, about three blocks away from our Los Angeles studio
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is this place called ICT.
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They're a research lab
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that's associated with the University of Southern California.
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They have a device there, it's called the "light stage."
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It has a zillion individually controlled lights
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and a whole bunch of cameras.
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And with that, we can reconstruct my face under a myriad of lighting conditions.
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We even captured the blood flow
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and how my face changes when I make expressions.
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This let us build a model of my face that, quite frankly, is just amazing.
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It's got an unfortunate level of detail, unfortunately.
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(Laughter)
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You can see every pore, every wrinkle.
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But we had to have that.
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Reality is all about detail.
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And without it, you miss it.
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We are far from done, though.
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This let us build a model of my face that looked like me.
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But it didn't really move like me.
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And that's where machine learning comes in.
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And machine learning needs a ton of data.
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So I sat down in front of some high-resolution motion-capturing device.
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And also, we did this traditional motion capture with markers.
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We created a whole bunch of images of my face
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and moving point clouds that represented that shapes of my face.
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Man, I made a lot of expressions,
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I said different lines in different emotional states ...
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We had to do a lot of capture with this.
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Once we had this enormous amount of data,
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we built and trained deep neural networks.
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And when we were finished with that,
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in 16 milliseconds,
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the neural network can look at my image
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and figure out everything about my face.
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It can compute my expression, my wrinkles, my blood flow --
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even how my eyelashes move.
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This is then rendered and displayed up there
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with all the detail that we captured previously.
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We're far from done.
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This is very much a work in progress.
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This is actually the first time we've shown it outside of our company.
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And, you know, it doesn't look as convincing as we want;
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I've got wires coming out of the back of me,
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and there's a sixth-of-a-second delay
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between when we capture the video and we display it up there.
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Sixth of a second -- that's crazy good!
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But it's still why you're hearing a bit of an echo and stuff.
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And you know, this machine learning stuff is brand-new to us,
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sometimes it's hard to convince to do the right thing, you know?
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It goes a little sideways.
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(Laughter)
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But why did we do this?
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Well, there's two reasons, really.
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First of all, it is just crazy cool.
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(Laughter)
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How cool is it?
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Well, with the push of a button,
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I can deliver this talk as a completely different character.
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This is Elbor.
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We put him together to test how this would work
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with a different appearance.
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And the cool thing about this technology is that, while I've changed my character,
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the performance is still all me.
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I tend to talk out of the right side of my mouth;
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so does Elbor.
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(Laughter)
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Now, the second reason we did this, and you can imagine,
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is this is going to be great for film.
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This is a brand-new, exciting tool
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for artists and directors and storytellers.
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It's pretty obvious, right?
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I mean, this is going to be really neat to have.
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But also, now that we've built it,
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it's clear that this is going to go way beyond film.
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But wait.
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Didn't I just change my identity with the push of a button?
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Isn't this like "deepfake" and face-swapping
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that you guys may have heard of?
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Well, yeah.
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In fact, we are using some of the same technology
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that deepfake is using.
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Deepfake is 2-D and image based, while ours is full 3-D
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and way more powerful.
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But they're very related.
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And now I can hear you thinking,
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"Darn it!
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I though I could at least trust and believe in video.
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If it was live video, didn't it have to be true?"
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Well, we know that's not really the case, right?
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Even without this, there are simple tricks that you can do with video
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like how you frame a shot
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that can make it really misrepresent what's actually going on.
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And I've been working in visual effects for a long time,
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and I've known for a long time
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that with enough effort, we can fool anyone about anything.
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What this stuff and deepfake is doing
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is making it easier and more accessible to manipulate video,
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just like Photoshop did for manipulating images, some time ago.
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I prefer to think about
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how this technology could bring humanity to other technology
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and bring us all closer together.
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Now that you've seen this,
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think about the possibilities.
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Right off the bat, you're going to see it in live events and concerts, like this.
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Digital celebrities, especially with new projection technology,
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are going to be just like the movies, but alive and in real time.
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And new forms of communication are coming.
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You can already interact with DigiDoug in VR.
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And it is eye-opening.
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It's just like you and I are in the same room,
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even though we may be miles apart.
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Heck, the next time you make a video call,
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you will be able to choose the version of you
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you want people to see.
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It's like really, really good makeup.
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I was scanned about a year and a half ago.
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I've aged.
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DigiDoug hasn't.
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On video calls, I never have to grow old.
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And as you can imagine, this is going to be used
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to give virtual assistants a body and a face.
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A humanity.
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I already love it that when I talk to virtual assistants,
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they answer back in a soothing, humanlike voice.
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Now they'll have a face.
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And you'll get all the nonverbal cues that make communication so much easier.
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It's going to be really nice.
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You'll be able to tell when a virtual assistant is busy or confused
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or concerned about something.
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Now, I couldn't leave the stage
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without you actually being able to see my real face,
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so you can do some comparison.
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So let me take off my helmet here.
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Yeah, don't worry, it looks way worse than it feels.
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(Laughter)
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So this is where we are.
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Let me put this back on here.
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(Laughter)
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Doink!
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So this is where we are.
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We're on the cusp of being able to interact with digital humans
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that are strikingly real,
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whether they're being controlled by a person or a machine.
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And like all new technology these days,
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it's going to come with some serious and real concerns
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that we have to deal with.
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But I am just so really excited
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about the ability to bring something that I've seen only in science fiction
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for my entire life
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into reality.
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Communicating with computers will be like talking to a friend.
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And talking to faraway friends
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will be like sitting with them together in the same room.
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Thank you very much.
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(Applause)
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