Technology. 00:22 It's advancing faster 00:24 and taking less time to be widely adopted 00:25 than ever before, 00:27 like as in it took roughly 10,000 years 00:30 to go from writing to printing press, 00:32 but only about 500 more to get to email. 00:34 Now it seems we're at the dawn of a new age, 00:38 the age of A.I... 00:39 Artificial Intelligence. 00:41 Please define. 00:42 [automated voice speaking] 00:48 Uh-huh, okay. There you have it. 00:50 What does it mean? I don't know. 00:52 Tons of folks are working on it, right? 00:53 Most people don't know that much about it, 00:55 and of course, there's no shortage 00:56 of data or opinions. 00:58 Anyway, I've heard it said 00:59 that the best way to learn about a subject 01:01 is to teach it, 01:02 but to level with ya, 01:04 I have a wildly incomplete education... 01:07 Not in my day job, 01:08 where I've been A.I.-adjacent for over a decade. 01:11 Anyway, I figured now would be as good a time as any 01:13 to catch up on the state of things 01:15 regarding this emerging phenomenon. 01:17 My sense of it is it kind of feels like 01:20 Pandora's box, maybe... ish? 01:23 Much of my understanding on this topic 01:24 has come from sci-fi stories, 01:26 which usually depict us 01:28 heading toward Shangri-La or dystopia. 01:30 Like most things, 01:31 I suspect the truth is probably somewhere in the middle. 01:34 Now, along the way, 01:35 we'll demystify some common misconceptions 01:37 about things we thought we understood, but probably don't, 01:40 terms such as 01:42 "machine learning," "algorithms," 01:44 "computer vision" and "Big Data," 01:46 they will be conveniently unpacked 01:48 to help us feel like we know what we're doing, 01:51 kinda. 01:52 By the way, Pandora's box... 01:58 wasn't a box. 02:00 It... 02:02 was a clay jar. 02:04 How about that? 02:06 Demystified. 02:11 A.I. is teaching the machine, 02:14 and the machine becoming smart. 02:17 Each time we create a more powerful technology, 02:19 we create a bigger lever for changing the world. 02:22 [computer] Autonomous driving started. 02:24 [Downey] It's an extraordinary time, 02:26 one of unprecedented change and possibility. 02:30 To help us understand what's happening, 02:32 this series will look at innovators 02:34 pushing the boundaries of A.I... 02:35 No, stop! 02:37 [Downey] ...and how their groundbreaking work 02:39 is profoundly impacting our lives... 02:40 Yay! [laughing] 02:42 [Downey] ...and the world around us. 02:44 In this episode, we'll meet two different visionaries 02:47 exploring identity, creativity, 02:49 and collaboration between humans and machines. 02:52 Intelligence used to be the province of only humans, 02:55 but it no longer is. 02:56 We don't program the machines. They learn by themselves. 03:09 Mm. Ah. That's good. 03:12 All right. 03:14 My background's always been a mixture of art and science. 03:18 I ended up doing a PhD in bioengineering, 03:21 then I ended up in the film industry, 03:24 working on King Kong to Avatar, 03:27 simulating faces. 03:30 I'd got to a point in my career 03:31 where I'd been, you know, 03:32 lucky enough to win a couple of Academy Awards, 03:35 so I thought, "Okay, what happens 03:37 if we actually tried to bring those characters to life, 03:40 that actually you could interact with?" 03:43 [toddler crying] 03:45 Baby... Ooh. 03:47 [toddler fusses] 03:48 What can you see? 03:49 So "Baby X" is a lifelike simulation of a toddler. 03:54 Hey. Are you excited to be here? 03:57 She's actually seeing me through the web camera, 03:59 she's listening through the microphone. 04:02 Woo... yeah. 04:04 Baby X is about exploring the nature 04:07 of how would we build a digital consciousness, 04:09 if it's possible? 04:10 We don't know if it's possible, 04:12 but we're chipping away at that problem. 04:14 Hey, Baby. Hey. 04:15 [Downey] "Problem" is an understatement 04:17 for what Mark's chipping away at. 04:19 His vision of the future 04:20 is one where human and machine cooperate, 04:22 and the best way to achieve that, he thinks, 04:25 is to make A.I. as life-like as possible. 04:28 Peek-a-boo! 04:31 [Baby X giggling] 04:32 [Downey] Which is why he began where most life begins... 04:35 a baby... 04:36 modeled after his own daughter. 04:39 So if we start revealing her layers, 04:41 she's driven by virtual muscles, 04:43 and the virtual muscles, in turn, 04:45 are driven by a virtual brain. 04:47 Now, these are radically simplified models 04:49 from the real thing, 04:51 but nevertheless, 04:52 they're models that we can explore how they work, 04:54 because we have a real template that exists, 04:57 the human brain. 04:59 So, these are all driven by neural networks. 05:03 [Downey] "Neural network" 05:04 is a virtual, much simpler version 05:06 of the human brain. 05:07 The brain is the most complex system in our body. 05:11 It's got 85 billion neurons, each of which fire non-stop, 05:14 receiving, processing, and sending information. 05:19 Baby X's brain is nowhere near as complex, 05:22 but that's the goal. 05:23 Instead of neurons, it's got nodes. 05:26 The more the nodes are exposed to, 05:28 the more they learn. 05:30 [Sagar] What we've learned is it's very hard to build a digital brain, 05:32 but where we want to go with it 05:34 is we're trying to build a human-like A.I. 05:37 which has a flexible intelligence 05:39 that can relate to people. 05:41 I think the best kind of systems 05:43 are when humans and A.I. work together. 05:46 One of the biggest misconceptions of A.I. 05:49 is that there is a super-intelligent being, 05:52 or what we call a generalized A.I., 05:54 that knows all, can do all, 05:56 smarter than all of us put together. 05:59 That is a total misconception. 06:01 A.I. is built on us. 06:03 A.I. is mimicking our thought processes. 06:06 A.I. is basically an emulation of us. 06:11 [Downey] Like visionaries before him, Mark's a dreamer. 06:13 The current state of his moonshot, however, 06:16 is a little more earthbound. 06:17 [computer] Thank you for granting access 06:19 to your microphone. It's good to hear you. 06:22 [Downey] Today, most avatars 06:23 are basically glorified customer-service reps. 06:26 [service avatar] Rest assured, 06:27 your health is my primary concern. 06:29 [Downey] They can answer simple questions 06:31 and give scripted responses. 06:33 I love helping our customers, 06:35 so I'm keen to keep learning. 06:36 [Downey] Beats dealing with automated phonelines for sure, 06:39 but it's a far cry from Mark's ultimate vision... 06:42 [Sagar] Hey, Baby. Hey. 06:43 [Downey] ...to create avatars that can actually learn, 06:46 interpret, and interact with the world around them, 06:49 like a real human. 06:51 What's this? 06:53 Spider. 06:55 So we're starting to get a spider forming in her mind here, 06:58 she's starting to associate the word with the image. 07:00 So, Baby... spider. 07:04 Spider. 07:05 Spider... 07:06 Good! Okay, what's this? 07:10 [Baby] Spider. 07:12 No. This is a duck. 07:14 Look at the duck. 07:15 [Baby] Duck. 07:17 [Sagar] Yeah. 07:18 [Downey] Baby X uses a type of A.I. called "object recognition." 07:23 Basically, it's how a computer sees... 07:27 how it identifies an object, like a spider, 07:29 or tells the difference between a spider and a duck. 07:33 It's something that you and I do naturally... 07:36 ...but machines, like Baby X, need to learn from scratch, 07:39 by basically sifting through enormous piles of data 07:42 to search for patterns, 07:44 so that eventually, it can drive a car, 07:46 or pick out a criminal in a crowded photograph, 07:49 or tell the difference between me and... that guy. 07:52 [Sagar] But now I'm gonna tell her that spiders are scary. 07:55 Look out! Rawr! Scary spider! Rawr! 07:59 [crying] 08:00 Hey, hey. Don't cry. It's okay. Hey... 08:03 [Baby crying] 08:04 Hey, it's okay. 08:05 Now she's responding emotionally to me as well, 08:08 so we've gone all the way down 08:10 to virtual neurotransmitters, hormones, and so forth, 08:14 so Baby X has a stress system. 08:16 If I give her a fright... 08:18 Boo! 08:19 So we'll see basically 08:20 some noradrenaline was released then, 08:22 and she's gone into a much more vigilant state of mind. 08:25 [Downey] What Mark is working on 08:27 is known as "affective computing," 08:29 A.I. that interprets and simulates human emotion. 08:33 I believe that machines are gonna interact with humans 08:36 just the way we interact with one another, 08:38 through perception, through conversation. 08:41 So as A.I. continues to become mainstream, 08:44 it needs to really understand humans, 08:46 and so we want to build emotion A.I. 08:49 that enables machines to have empathy. 08:51 Hello, Pepa. 08:53 -Hello. -[man] Hello. 08:55 -Hello. -Hello. 08:57 -Hello. -[laughing] 08:58 Oh, dear. 08:59 -We can do this forever. -I know we could. [laughs] 09:02 [Howard] They've showed, for example, 09:04 older adults who have A.I. aides at their nursing homes, 09:07 they are happier 09:08 with a robot that emotes and is social 09:10 than having no one there. 09:12 That's really the enhancement of human relationships. 09:16 [Sagar] Hey... Hello. 09:19 You know, human cooperation 09:20 is the most powerful force in human history, right? 09:23 Human cooperation with intelligent machines 09:26 will define the next era of history. 09:28 Using a machine which is connected 09:31 with the rest of the world through the Internet, 09:34 that can work as a creative, collaborative partner? 09:37 That's unbelievable. 09:47 [will.i.am] Jessica. Jessica. One more time, one more time. 09:50 We're gonna go from just the first two verses, 09:52 and the first two verses 09:53 will take us to three minutes, okay? 09:56 I love music. 09:57 The whole concept of music is collaboration, 09:59 so if there are some people that see me as a musician, 10:01 that's awesome. 10:06 I first became interested in A.I. 10:08 because A.I. is a very fruitful place to create in. 10:11 It's a new tool for us. 10:13 I dream, and make my dreams reality, 10:16 whether the dream is a song 10:17 or the dream is an avatar of myself. 10:20 One time, a friend was like, "Well, you can't clone yourself. 10:24 You can't be in two places at once." 10:25 That's the promise of the avatar. 10:29 I left it over there. 10:30 All right, here we go. 10:32 [Sagar] So, you're about to enter the Matrix. 10:35 I'm gonna sort of direct you through just a bunch of poses. 10:39 [will.i.am] The team from Soul Machines 10:41 is here to create a digital avatar of myself. 10:44 They had to put me in this huge contraption 10:46 with these crazy lights. 10:49 What do you want me to do? 10:50 [Sagar] Your face is an instrument. 10:52 All the wrinkles on the face is like a signature, 10:55 so we want to get 10:56 the highest-quality digital model of you that we can. 10:59 Okay. [chuckles] 11:01 [Sagar] Yeah, that's perfect. Okay, go. 11:03 [rapid shutters snapping] 11:06 [Sagar] So we have to capture all the textures of their face. 11:09 The geometry of their face... 11:11 Big, gnashy teeth. 11:13 How their face deforms 11:15 to form the different facial expressions. 11:17 And how about a kiss? 11:18 You could do... 11:19 With my eyes closed? 11:20 'Cause I don't kiss with my eyes open. 11:21 Every once in a while, I peek. 11:23 [cameras snapping] 11:25 I wanted to have 11:26 a digital avatar around the idea of Idatity, 11:29 and that's the marriage of my data and my identity. 11:32 Everyone's concerned about, like, identity theft. 11:35 Meanwhile, everybody's giving away all their data for free 11:38 on the Internet. 11:38 I'm what I like and what I don't like, 11:41 I'm where I go, I'm who I know. 11:43 I'm what I search. I am my thumbprint. 11:45 I am my data. That's who I am. 11:48 You pull your eyelids down like that. 11:49 We want to get that... yup. 11:51 [will.i.am] When I'm on Instagram and I'm on Google, 11:53 I'm actually programming those algorithms to better understand me. 11:56 Awesome. 11:58 In the future, my avatar's gonna be doing all that stuff, 12:00 because I'm gonna program it. 12:02 Get entertained through it, get information through it, 12:05 and you feel like 12:06 you're having a FaceTime with an intelligent entity. 12:09 [laughing] "Yo, check out this link." 12:11 "Oh, wow, that's crazy." 12:12 "Yo, can you post that on my Twitter?" 12:15 [laughter] 12:17 -Hey. -Hey. 12:19 All right, I'm the Soul Machines lead audio engineer. 12:22 Hopefully we'll be able to build an A.I. version of your voice. 12:26 After creating Will's look, 12:29 then we now have to create his voice. 12:31 For that, we actually have to capture a lot of samples 12:34 about how Will speaks, 12:36 and that's actually quite a challenging process. 12:39 -Shall we kick off? -Yeah, let's kick off. 12:41 -A'ight, boo, here we go. -Yeah. 12:43 I'm Will, and I'm happy to meet you. 12:44 I'm here to bring technology to life, 12:47 and let's talk about Artificial Intelligence. 12:50 Oops. Really? Whoa. 12:53 That's dope! 12:54 So there's so many ways of saying "dope," bro. 12:57 Yeah, yeah. 12:58 Now, how realistic is it going to be? 12:59 This will sound like you. 13:01 The sentences can be divided up into parts 13:04 so that we can create words 13:06 and build sentences, like LEGO blocks. 13:08 It will sound exactly like you. 13:11 Well, maybe we don't want to have it too accurate. 13:14 So you don't freak people out, maybe I don't want it accurate. 13:18 Maybe, there should be some type of... 13:20 "That's the A.I.," 13:21 'cause this is all new ground. 13:23 -Yeah. -Like, we've... 13:25 we are in an intersection of a place 13:27 that we've never been in society, 13:28 where people have to determine 13:31 what's real and what's not. 13:35 [Downey] While Mark jets back to New Zealand 13:37 to try to create Will's digital doppelganger, 13:39 Will's left waiting, and wondering... 13:42 can Mark pull this off? 13:44 What does it mean 13:45 to have a lifelike avatar of you? 13:47 A digital replicant of yourself? 13:50 Is that a good idea? 13:52 How far is too far? 13:54 [Domingos] We've been collaborating with machines 13:56 since the dawn of technology. 13:58 I mean, even today, 14:00 in some sense, we are all cyborgs already. 14:02 For example, 14:03 you use OKCupid to find a date, 14:06 and then you use Yelp to decide where to go, you know, 14:09 what restaurant to go to, 14:10 and then you start driving your car, 14:12 but there's a GPS system that actually tells you where to go. 14:15 So the human and the machine decision-making 14:17 are very tightly interwoven, 14:19 and I think this will only increase as we go forward. 14:25 [Downey] Human collaboration with intelligent machines... 14:29 A different musician in a different town 14:31 with a different approach 14:32 is giving the same problem a shot. 14:34 [Gil Weinberg] People are concerned 14:36 about A.I. replacing humans, 14:38 and I think it is not only 14:40 not going to replace humans, it's going to enhance humans. 14:45 I'm Gil Weinberg. I'm the founding director 14:48 of Georgia Tech Center for Music Technology. 14:50 [plays piano] 14:51 Ready? 14:54 In my lab, we are trying to create the new technologies 14:57 that will explore new ways to be expressive... 15:00 to be creative... 15:02 Shimon, it's a marimba-playing robot. 15:05 [playing marimba] 15:08 What it does is listen to humans playing, 15:11 and it can improvise. 15:15 Shimon is our first robotic musician 15:18 that has the ability to find patterns, 15:20 so, machine learning. 15:23 Machine learning 15:25 is the ability to find patterns in data. 15:28 So, for example, if we feed Shimon Miles Davis, 15:31 it will try to see 15:32 what note is he likely to play after what note, 15:34 and once it finds its patterns, it can start to manipulate it, 15:38 and I can have the robot playing in a style 15:40 that maybe is 30% Miles Davis, 30% Bach, 15:43 30% Madonna, and 10% my own, 15:46 and create morphing of music that humans would never create. 15:50 [band playing tune] 15:55 [Downey] Gil's groundbreaking work 15:56 in artificial creativity and musical expression 15:59 has been performed by symphonies around the world... 16:03 ...but his innovation 16:05 also caught the attention of another musician... 16:07 Okay. 16:08 [Downey] ...a guy who unexpectedly pushed Gil 16:10 beyond enhancing robots 16:12 to augmenting humans. 16:15 [Weinberg] I met Jason Barnes about six years ago, 16:17 when I was just about finishing one phase of developing Shimon, 16:20 and I was starting to think, "What's next?" 16:24 [Barnes] I got my first drum kit when I was 15, on Christmas, 16:27 and when I lost my limb, I was 22, 16:30 so I was kind of used to having two limbs. 16:34 I started trying to fabricate prosthetics 16:37 to try and get me back on the kit, 16:38 which eventually led me to working and collaborating with Georgia Tech. 16:41 [playing drums] 16:44 [Weinberg] He told me that he lost his arm, 16:46 he was devastated, he was depressed, 16:48 music was his life, 16:49 and he said, "I saw that you develop robotic musicians. 16:53 Can you use some of the technology that you have 16:55 in order to allow me to play again like I used to?" 16:59 So that's the prosthetic arm that we built for Jason. 17:02 When he came to us, 17:04 he just wanted to be able to use sensors here 17:06 so he can hold the stick tight or loose. 17:09 I suggested "Let's do that, but also, 17:12 let's have two sticks. 17:13 One stick can operate with a mind of its own, 17:15 understanding the music and improvising. 17:17 One stick can operate based on what you tell it with your muscle, 17:20 and also, each one of the sticks can play 20 hertz... 17:24 ...faster than any humans, 17:26 and together, they can create polyrhythm, 17:27 create all kind of textures that humans cannot create." 17:31 All right. I think we're ready to play. 17:33 [all playing tune] 17:38 [Downey] In some ways, the robotic drum arm 17:40 allows Jason to play better than he ever has, 17:43 but it still lacks the true function, 17:45 or feeling, of a human hand. 17:47 [Weinberg] They don't provide 17:49 the kind of dexterity and subtle control 17:51 that would really allow anything. 17:55 [Downey] This revelation 17:56 drove Gil to his next innovation... 17:58 the Skywalker Hand. 18:02 Inspired by Luke Skywalker from Star Wars, 18:04 and created in collaboration with Jason, 18:07 the revolutionary tech 18:09 brings what was once the realm of sci-fi 18:11 a little closer to our galaxy. 18:13 [Barnes] This is just like a 3D-printed hand 18:15 that you can, like, download the files online. 18:18 [Downey] Currently, most advanced prosthetic hands 18:20 can't even thumbs-up or flip you the bird. 18:24 They can only open or grip, 18:26 using all five fingers at once. 18:28 Most of the prosthetics that are available on the market nowadays, 18:32 um, actually use EMG technology, 18:34 which stands for "electromyography," 18:35 and essentially what it does is there are two sensors 18:38 that make contact with my residual limb, 18:40 and they pick up electrical signals from the muscles... 18:43 So again, when I flex and extend my residual limb, 18:46 it will open and close the hand, 18:47 um, and I can rotate as well, 18:50 but the problem with EMG 18:51 is it's a very vague electrical signal, so zero to 100%. 18:55 It's not very accurate at all. 18:56 The Skywalker Hand actually uses ultrasound tech. 18:59 Ultrasound provides an image, 19:01 and you can see everything that's going on inside of the arm. 19:04 [Downey] Ultrasound uses high-frequency sound waves 19:07 to capture live images from inside the body. 19:11 As Jason flexes his muscles 19:13 to move each of his missing fingers, 19:14 ultrasound generates live images that visualize his intention. 19:20 The A.I. then uses machine learning 19:23 to predict patterns, 19:24 letting a man who's lost one of his hands 19:26 move all five of his fingers individually, 19:29 even if he's as unpredictable as Keith Moon. 19:32 [Howard] The work that Gil is doing 19:34 is really important. 19:35 Gil comes from a non-engineering background, 19:37 which means that his technology 19:39 and the way he thinks about robotics 19:42 is actually quite different 19:43 than, say, the way I would think about it, 19:44 since I come from an engineering background. 19:46 And the commonality is that we want to design robots 19:49 to really impact and make a difference in the world. 19:53 [Weinberg] We were able to create a proof of concept 19:56 with Jason Barnes. 19:57 Once we discovered that we can do this with ultrasound, 20:01 immediately I looked at, 20:03 "Hey, let's try to help more people." 20:10 [Jay Schneider] That's okay, just leave me hanging, holding it. 20:13 It's not heavy or anything. 20:14 [Barnes] It's safe, if you want to slide it back... 20:15 No, no. I'm messing with you. 20:17 So I met Jason Barnes 20:18 at an event called "Lucky Fin Weekend." 20:20 They're a foundation that deals with limb difference. 20:23 There we go. 20:25 -Ah, all right. -And it's out. 20:27 [Schneider] Do you ever work on your car 20:29 without the hook? 20:30 Not really. It's just way easier and efficient for me to... 20:33 The hook, the hook really trips me out, though, man. 20:36 [Schneider] When I lost my hand, 20:38 it was close to 30 years ago, 20:39 and prosthetics were kind of stuck in the Dark Ages. 20:42 [rock drums and bass playing] 20:47 In general, they didn't really do a whole lot, 20:50 and even if they moved, 20:52 they seemed to be more passive than actually worthwhile to use. 20:58 I don't like to talk about my accident, 21:01 because I don't feel it defines me. 21:03 The narrative on limb-different people 21:05 has been the accident. 21:07 "This is what happened, and these are these sad things," 21:10 and it becomes inspiration porn. 21:14 For me, for example, right, if I do something, 21:17 I have to, like, smash it out of the park, 21:19 because otherwise I feel like there's gonna be this, 21:21 "Oh, well, he did it good enough because he's missing his hand." 21:24 -Yeah, yeah. -And I'm like, "F that!" 21:25 Like, I want to... I'm gonna be as good or better than somebody with two hands 21:29 doing whatever I'm doing, you know? 21:32 Prosthetics, at this point in my life, 21:34 don't really seem like something I would want or need. 21:37 [Weinberg] Manual robotic prosthetics 21:40 have not been adopted well. 21:41 Amputees try them, 21:42 and then they don't continue to use them. 21:50 [Barnes] Yeah, man, you stoked to check out the lab? 21:53 Yeah, yeah, for sure. 21:54 Right now, I'm the only amputee that's ever used 21:57 the Skywalker Arm before. 21:58 Did you have... were you right-handed? 22:00 No, I was born left-handed, actually. 22:02 Oh, you lucky bastard. 22:03 -Yeah, I know, right? -I was right-handed. 22:05 [Barnes] It was extremely important 22:06 to get as many different people as we can in there, 22:09 including other amputees. 22:10 It's hard to find people that are amputees in general, 22:13 and then, like, upper-extremity amputees is the next thing, 22:16 and then finding people who are willing, 22:18 to step out of their comfort zone 22:20 -and then do this. -Right. 22:22 [Schneider] When I met Jason, 22:23 I found it really interesting that we had a lot in common, 22:26 because we were both into cars, we were both into music. 22:30 -Hi, Gil. -Hey. What's up? 22:31 -Jason. Nice to meet ya. -Nice meeting you. 22:33 He's a step or two ahead of me with the technology stuff. 22:36 [Barnes] The way this hand works is it essentially picks up 22:39 the ultrasound signals from my residual limb, 22:42 so when I move my index finger, 22:43 it'll move my index... 22:45 ring... 22:47 [Schneider] Wow, for the first time, 22:48 prosthetics are finally getting to the point 22:50 where they're getting pretty close 22:52 to actual human hand. 22:54 You know, it got me excited. I was like, 22:55 "This is the type of thing that I've been waiting for." 22:58 If I was ever going to try one again, 22:59 this would be the type of stuff that I would want to check out. 23:02 When I move my thumb... 23:04 [laughter] 23:08 I know from experience 23:10 that it's not always working perfectly. 23:12 It's very interesting for me to have someone else 23:14 who comes and tries our technology 23:16 to see if it can be generalized. 23:20 Is my arm getting warmer because you're wrapping it, 23:23 or does that have heat in it? 23:24 -It does have heat in it. -Oh, okay. 23:26 First thing we need, if we're gonna get Jay to try the hand, 23:29 is we need to get a custom-fit socket to his arm 23:32 that's comfortable and fits nice and snug. 23:34 You comfortable when they do this? 23:36 This is the most awkward part for me. 23:38 -Nah, it was kinda weird. -Ah, yeah. Yeah. 23:40 I was 12 years old when I lost my hand 23:42 and had a prosthetic for six months, 23:44 and pretty much ever since then, I haven't used it, 23:46 and it's been close to 30 years now. 23:48 And there's the impression of your arm. 23:50 That's way easier than I thought it was gonna be. 23:52 That's wild, yeah! 23:53 It may not be right for me, but this is something 23:56 that could really, really help people's lives. 23:58 It would be really cool 23:59 to have a hand in helping to develop the technology. 24:04 All right. 24:06 All right, ready? 24:08 Just slide it in. 24:10 Turn this... tighten. 24:12 [knob ratcheting] 24:13 How tight? 24:14 As tight as you can before it really hurts... 24:16 -Oh, really? -...because the tighter it is, 24:18 -the better reading we'll see. -Okay. 24:20 -Now we apply the probe... -Okay. 24:22 ...so it can read your movements. 24:24 Now we also 24:25 have to work on the algorithm and the machine learning, 24:27 and for this, we will need you to train. 24:29 Okay. 24:30 An able-bodied person, when you move your finger, 24:33 you're not thinking about moving your finger, 24:35 you just do it, because that's how we're hardwired, 24:37 but, honestly, I don't really remember 24:39 what it was like to even have that hand. 24:41 [Weinberg] Even though an amputee doesn't have a thumb, 24:44 they still have the muscle. 24:45 You still have some kind of memory 24:48 of how you moved your fingers, 24:49 and you can think about moving your phantom fingers, 24:52 and the muscles would move accordingly, 24:54 and that's exactly what we use in order to, uh, 24:56 recreate the motion and put it in a prosthetic arm. 24:59 But does Jay still remember how to move fingers 25:03 that he didn't have for, I believe, 30 years ago? 25:06 Now we'll run the model, 25:08 and you'll be able to control the hand. 25:10 [chuckles] You're optimistic. I'm crossing fingers. 25:13 Can I cross these fingers? [laughs] 25:15 Is that... is that an option yet? 25:17 Having Jay here for a day 25:19 and hoping to get him to a point 25:21 that he controls finger by finger, 25:23 I'm a little concerned that it will not work 25:25 in such a short period of time. 25:28 Okay. And... 25:29 -Ready? -Yeah. You should try each of the fingers. 25:32 All right, that's the thumb... 25:35 -Oh, shit! -Unbelievable. 25:39 All right, index... 25:41 Yay! 25:42 Wow, I'm surprised. 25:44 Middle... 25:46 [Barnes] Dude. 25:50 Five for five? 25:53 -[all cheering] -All five of them! 25:56 -Whoa. -That's wild. 25:57 All right, let me do it again. 25:59 You're a natural, man. 26:00 Doesn't that feel crazy? 26:02 -Yeah! -Feels wild. 26:04 -I didn't think it'd be as good. -I didn't either. 26:06 He hit me in the back after it worked, so... 26:09 That's the first time. 26:10 [Schneider] It's like a game-changer, even in its infancy, 26:13 which is kind of insane, 26:14 because it can only get better from there. 26:17 And it's really cool to play a small part in that. 26:19 [Weinberg] Now we have two main goals. 26:21 First, you need to move your muscle or your phantom finger, 26:24 and immediately see response, so this is one direction of research. 26:28 The other direction is to make it more accurate. 26:31 Being able to type on a keyboard, 26:33 use a computer mouse, uh, open a water bottle, 26:35 things like that that most people take for granted. 26:38 It's kind of like a... you know, sci-fi movie, soon to be written. 26:41 -[laughter] -Give us five, right? 26:44 That's awkward... oh, robot to robot hand. 26:46 Nice! 26:49 -That's... that was real, right? -Yeah. 26:51 If I find out you guys had a button under that desk... 26:53 No, nah, I promise. I promise. 26:56 [Downey] What began as one man's pursuit 26:58 to innovate music through A.I. and robotics 27:01 unexpectedly became something much greater. 27:05 A human body cooperating with a bionic hand 27:08 is one thing... 27:09 but is it possible to humanize a machine 27:12 to the point that it truly seems lifelike? 27:15 Or is that still sci-fi, and far, far away? 27:25 [Greg] How did things go with Will? 27:26 [Sagar] You know, one of the real challenges there 27:29 was just getting enough material 27:30 that we could actually come back with. 27:33 We can't possibly capture somebody's real personality, 27:36 you know, that's impossible, 27:38 but in order for it to really work, 27:40 it's really important to capture a feeling of Will. 27:44 Right, so... 27:45 [Downey] Will's avatar is actually Mark's first go 27:48 at creating a digital copy of a real person. 27:51 Wow, that's looking pretty good. 27:53 [Downey] He's not just trying to clone a human, 27:56 by any stretch, 27:57 but trying to create an artificial stand-in 27:59 that's somewhat believable. 28:01 Still, like most firsts, it's bumpy, 28:04 and it's a cautious road into the unknown. 28:07 [tech] A big challenge that I've found 28:09 while I've been looking through a lot of the images 28:11 is it seems that Will was moving a lot during the shots. 28:14 [Colin Hodges] Okay. When we're building digital Will, 28:16 we have about eight artists on our team 28:19 that come together 28:20 and pull all of the different components 28:22 to bring together this real-time character 28:24 that's driven by the artificial intelligence 28:26 to behave like Will behaves. 28:29 Big challenges we've got 28:31 is how we create Will's personality. 28:34 Yeah. Like, the liveliness 28:35 and the energy that he generates, 28:37 and the excitement. 28:39 The facial hair was a challenge. 28:41 Because it's so sparse, it's quite tricky to get 28:44 the hair separated from the skin. 28:46 [Sagar] We have to be able to synthesize 28:48 the sort of feel that you're interacting with Will. 28:51 So, Teah, I've got some stuff to hear. 28:54 We've got 16 variations. 28:56 -16 variations? -Yeah. 28:58 [Sagar] We take the voice data that we've got, 29:01 and then we can enable the digital version of Will 29:03 to say all kinds of different things. 29:05 [digital Will] Here's the forecast. 29:07 Yo, check out the forecast. 29:08 Yo, check out the weather and shit. 29:10 Here's the weather. Check out the weather. 29:11 Yah, 'bout to make it rain! 29:13 Kinda. 29:14 [Sagar] That's fantastic... the words, 29:16 the delivery, emphasis... 29:18 Shows you just how complex people react. 29:23 [will.i.am] It's awesome where we are in the world of tech. 29:27 Scary where we are, as well. 29:29 My mind started thinking, like, "Wait a second here. 29:32 Why am I doing this? 29:34 What's the endgame?" 29:37 Because, eventually, I won't be around, 29:41 but it would. 29:43 [Downey] Will's endgame is more modest than Mark's: 29:45 a beefed-up Instagram following, a virtual assistant, 29:48 anything that might help him expand his creative outlets 29:51 or free up time for more creative or philanthropic pursuits. 29:57 Okay, so, here we go. 30:00 That's looking really different. 30:02 It's gonna be really interesting, 30:04 because, you know, it's not every day 30:06 you get confronted with your virtual self. 30:08 Right. 30:09 Does he feel that this is like him? 30:12 If it's not representative of him 30:14 or if he doesn't think it's authentic, 30:15 then he won't want to support it. 30:22 -What up, Mark? -Oh, hey, how are you? 30:24 -You can see me, right? -Yes. 30:26 Yo, wassup? This is will.i.am. 30:29 [laughing] 30:30 [Sagar] This is the new version of you. 30:31 We can give him glasses there. 30:33 [will.i.am laughs] That's awesome. 30:35 I remember I had a pimple on my face that day. You captured it. 30:38 The good thing is, it's digital, 30:40 and we can remove it really easily. 30:42 How come you didn't remove that? [laughs] 30:44 [Sagar] You can make him do a variety of things. 30:47 Let's play "Simon Says." 30:49 Say, "I sound like a girl." 30:50 I sound like a girl. 30:52 Say that with a higher pitch. 30:54 [high voice] I sound like a girl. 30:56 Raise your eyebrows. 30:59 Poke out your tongue. 31:00 [Will laughs] 31:02 [will.i.am] Tell me about growing up in Los Angeles. 31:05 I was born and raised in Boyle Heights, 31:06 which is west of east Los Angeles, 31:08 which is east of Hollywood. 31:10 Just east of downtown. 31:12 [will.i.am] Should it sound exactly like me? 31:14 Nope. 31:16 Should it sound a little bit robotic? 31:17 Yes. It should. 31:20 For my mom. 31:22 My mom should not be confused. 31:24 What's your name? 31:26 [in Spanish] Mi nombre es Will. 31:27 [in English] You speak Spanish? 31:29 I don't know. 31:30 [laughing] 31:31 I know it needs some fine-tuning, 31:33 but the way it's looking so far 31:35 is mind-blowing. 31:36 Thanks, Mark. 31:38 Yeah, no worries. 31:39 [Sagar] How far do you go down that path 31:41 until you can label it a living... 31:44 a digital living character? 31:47 This raises some of the deepest questions 31:50 in science and philosophy, actually, 31:53 you know, the nature of free will. 31:55 How do you actually 31:56 build a character which is truly autonomous? 31:58 Peek-a-boo! 32:01 [Baby X giggles] 32:02 What is free will? What does it take to do that? 32:05 [Weinberg] Artificial Intelligence 32:07 is crucial to the work we are doing, 32:09 to inspire, to surprise, 32:10 to push human creativity and abilities 32:13 to uncharted domains. 32:15 [all cheering] 32:16 Unbelievable. 32:18 [playing drums] 32:22 [Downey] Free will... 32:25 ...it's something we've been grappling with 32:27 for thousands of years, from Aristotle to Descartes, 32:30 and will continue to grapple with for a thousand more. 32:33 Will we ever be able to make an A.I. 32:35 that can think on its own? 32:37 A second, artificial version of me 32:39 that is truly autonomous? 32:42 A Robert that can actually think and feel on his own, 32:45 while this Robert here takes a nap? 32:48 [engines roaring] 32:49 Impossible? 32:51 Well, when you consider 32:52 what human cooperation has already accomplished... 32:55 a man on the moon... 32:57 decoding the human genome... 32:59 discovering faraway galaxies... 33:02 I'd put my money on dreamers like Mark and Gil 33:05 over the "Earth is flat" folks any day. 33:09 Until then... nap time. 33:16 [man 1] Look at our world today. 33:18 Look at everything we've created. 33:21 Artificial Intelligence is gonna be 33:23 the technology that takes that to the next level. 33:26 [man 2] Artificial Intelligence can help us 33:28 to feed the world's population. 33:30 [man 3] The fact that we can find where famine might happen, 33:33 it's mind-blowing. 33:35 These are conflict areas, 33:37 this is an area that we need to look at protecting. 33:39 Then launch A.I. 33:41 [man 4] We are going to release the speed limit on your car. 33:46 Tim, can you hear me? 33:47 [man 5] With A.I., 33:49 ideas are easy, execution is hard. 33:52 [Domingos] What excites me the most about where we might be going 33:55 is having more super-powers... 33:57 [firefighter] I got him! 33:58 [Domingos] ...and A.I. is super-powers for our mind. 34:00 [man 6] Even though the limb is synthetic materials, 34:03 it moves as if it's flesh and bone. 34:05 [woman 1] You start to think about a world 34:07 where you can prevent disease before it happens. 34:09 [man 7] A.I. can give us that answer 34:11 that we've been seeking all along... 34:13 "Are we alone?" 34:14 Bah! 34:15 [man 8] I love the idea that there are passionate people 34:17 dedicating their time and energy 34:19 to making these things happen.