1 00:00:02,043 --> 00:00:03,930 This is Henry, 2 00:00:03,930 --> 00:00:05,328 a cute boy, 3 00:00:05,328 --> 00:00:07,834 and when Henry was three, 4 00:00:07,834 --> 00:00:13,387 his mom found him having some febrile seizures. 5 00:00:13,575 --> 00:00:13,958 Febrile seizures are seizures that occur 6 00:00:13,958 --> 00:00:18,253 when you also have a fever, 7 00:00:18,253 --> 00:00:20,980 and the doctor said, 8 00:00:20,980 --> 00:00:23,746 "Don't worry too much. Kids usually outgrow these." 9 00:00:23,746 --> 00:00:26,144 When he was four, 10 00:00:26,144 --> 00:00:27,838 he had a convulsive seizure, 11 00:00:27,838 --> 00:00:30,909 the kind that you lose consciousness 12 00:00:30,909 --> 00:00:31,740 and shake, 13 00:00:31,740 --> 00:00:33,957 generalized tonic-clonic seizure, 14 00:00:33,957 --> 00:00:38,456 and while the diagnosis of epilepsy 15 00:00:38,456 --> 00:00:41,672 was in the mail, 16 00:00:41,672 --> 00:00:45,141 Henry's mom went to get him out of bed one morning, 17 00:00:45,525 --> 00:00:48,939 and as she went in his room, 18 00:00:48,939 --> 00:00:52,039 she found his cold, lifeless body. 19 00:00:52,039 --> 00:00:58,302 Henry died of SUDEP, 20 00:00:58,302 --> 00:01:01,867 Sudden Unexpected Death in Epilepsy. 21 00:01:01,867 --> 00:01:05,446 I'm curious how many of you have heard of SUDEP? 22 00:01:05,796 --> 00:01:10,233 This is a very well-educated audience, and I see only a few hands. 23 00:01:10,233 --> 00:01:14,113 SUDEP is when an otherwise healthy person with epilepsy 24 00:01:14,113 --> 00:01:18,113 dies and they can't attribute it to anything they can find in an autopsy. 25 00:01:20,322 --> 00:01:24,434 There is a SUDEP every seven to nine minutes. 26 00:01:24,434 --> 00:01:27,313 That's on average two per TED Talk. 27 00:01:31,651 --> 00:01:33,315 Now, a normal brain 28 00:01:33,315 --> 00:01:35,392 has electrical activity. 29 00:01:35,392 --> 00:01:38,170 You can see some of the electrical waves 30 00:01:38,170 --> 00:01:40,792 coming out of this picture of a brain here. 31 00:01:40,792 --> 00:01:44,408 And these should look like typical electrical activity 32 00:01:44,408 --> 00:01:46,465 that an EEG could read on the surface. 33 00:01:46,465 --> 00:01:48,255 When you have a seizure, 34 00:01:48,255 --> 00:01:50,951 it's a bit of unusual electrical activity, 35 00:01:50,951 --> 00:01:52,772 and it can be focal. 36 00:01:52,772 --> 00:01:54,863 It can take place in just a small part of your brain. 37 00:01:54,863 --> 00:01:56,463 When that happens, 38 00:01:56,463 --> 00:01:58,385 you might have a strange sensation. 39 00:01:58,385 --> 00:02:01,160 One could be happening, several could be happening 40 00:02:01,160 --> 00:02:02,511 here in the audience right now 41 00:02:02,511 --> 00:02:04,323 and the person next to you might not even know. 42 00:02:04,323 --> 00:02:08,082 However, if you have a seizure where that little brush fire 43 00:02:08,082 --> 00:02:10,359 spreads like a forest fire over the brain, 44 00:02:10,359 --> 00:02:12,059 then it generalizes, 45 00:02:12,059 --> 00:02:14,317 and that generalized seizure 46 00:02:14,317 --> 00:02:16,581 takes your consciousness away 47 00:02:16,581 --> 00:02:18,968 and causes you to convulse. 48 00:02:18,968 --> 00:02:22,947 There are more SUDEPs in the United States every year 49 00:02:22,947 --> 00:02:25,622 than Sudden Infant Death Syndrome. 50 00:02:25,622 --> 00:02:29,464 Now, how many of you have heard of Sudden Infant Death Syndrome. 51 00:02:29,464 --> 00:02:31,544 Right? Pretty much every hand goes up. 52 00:02:31,544 --> 00:02:33,566 So what's going on here? 53 00:02:33,566 --> 00:02:38,405 Why is this so much more common and yet people haven't heard of it? 54 00:02:38,609 --> 00:02:40,934 And what can you do to prevent it? 55 00:02:40,934 --> 00:02:44,500 Well, there are two things scientifically shown 56 00:02:44,500 --> 00:02:47,355 that prevent or reduce the risk of SUDEP. 57 00:02:47,355 --> 00:02:49,863 The first is follow your doctor's instructions, 58 00:02:49,863 --> 00:02:51,306 take your medications. 59 00:02:51,306 --> 00:02:53,619 Two thirds of people who have epilepsy 60 00:02:53,619 --> 00:02:55,738 get it under control with their medications. 61 00:02:56,088 --> 00:03:00,283 the second thing that reduces the risk of SUDEP is companionship. 62 00:03:00,283 --> 00:03:05,001 It's having somebody there at the time that you have a seizure. 63 00:03:05,001 --> 00:03:09,270 Now, SUDEP, even though most of you have never heard of it, 64 00:03:09,270 --> 00:03:13,197 is actually the number two cause of years of potential life lost 65 00:03:13,197 --> 00:03:17,159 of all neurological disorders. 66 00:03:17,159 --> 00:03:25,128 The vertical axis is the number of deaths times the remaining lifespan, 67 00:03:25,351 --> 00:03:28,814 so higher is much worse impact. 68 00:03:28,814 --> 00:03:31,760 SUDEP, however, unlike these others 69 00:03:31,760 --> 00:03:37,476 is something that people right here could do something to push that down. 70 00:03:37,964 --> 00:03:45,185 Now, what is Ros Picard, an AI researcher, doing here telling you about SUDEP? Right? 71 00:03:45,185 --> 00:03:47,587 I'm not a neurologist. 72 00:03:47,587 --> 00:03:50,349 When I was working at the Media Lab 73 00:03:50,349 --> 00:03:51,927 on measurement of emotion, 74 00:03:51,927 --> 00:03:55,072 trying to make our machines more intelligent about our emotions, 75 00:03:55,072 --> 00:03:58,011 we started doing a lot of work measuring stress. 76 00:03:58,011 --> 00:04:00,704 We built lots of sensors 77 00:04:00,704 --> 00:04:03,817 that measured it in lots of different ways. 78 00:04:03,817 --> 00:04:06,161 But one of them in particular 79 00:04:06,161 --> 00:04:10,549 grew out of some of this very old work with measuring sweaty palms 80 00:04:10,549 --> 00:04:12,121 with an electrical signal. 81 00:04:12,121 --> 00:04:14,655 This is a signal of skin conductance that's known to go up 82 00:04:14,655 --> 00:04:17,229 when you get nervous, 83 00:04:17,229 --> 00:04:19,380 but it turns out it also goes up with a lot of other interesting conditions. 84 00:04:19,380 --> 00:04:22,153 But measuring it with wires on your hand is really inconvenient. 85 00:04:22,153 --> 00:04:26,284 So we invented a bunch of other ways of doing this at the MIT Media Lab, 86 00:04:26,284 --> 00:04:28,588 And with these wearables, 87 00:04:28,588 --> 00:04:33,417 we started to collect the first ever clinical quality data 24/7. 88 00:04:33,417 --> 00:04:38,705 Here's a picture of what that looked like the first time that an MIT student 89 00:04:38,705 --> 00:04:43,025 collected skin conductance on the wrist 24/7. 90 00:04:43,025 --> 00:04:45,696 Let's zoom in a little bit here. 91 00:04:45,696 --> 00:04:48,998 What you see is 24 hours from left to right, 92 00:04:48,998 --> 00:04:50,593 and here is two days of data, 93 00:04:50,593 --> 00:04:53,515 and first what's surprised us 94 00:04:53,515 --> 00:04:56,885 was the sleep was the biggest peak of the day. 95 00:04:56,885 --> 00:04:58,659 Now, that sound broken. Right? 96 00:04:58,659 --> 00:05:01,182 You're calm when you're asleep, so what's going on here? 97 00:05:01,182 --> 00:05:05,616 Well, it turns out that our physiology during sleep 98 00:05:05,616 --> 00:05:08,342 is very different than our physiology during wake, 99 00:05:08,342 --> 00:05:11,855 and while there's still a bit of a mystery why these peaks are usually 100 00:05:11,855 --> 00:05:13,981 the biggest of the day during sleep, 101 00:05:13,981 --> 00:05:17,255 we now believe they're related to memory consolidation 102 00:05:17,255 --> 00:05:19,882 and memory formation during sleep. 103 00:05:20,135 --> 00:05:23,386 We also saw things that were exactly what we expected. 104 00:05:23,386 --> 00:05:26,426 When an MIT student is working hard in the lab 105 00:05:26,426 --> 00:05:28,117 or on homeworks, 106 00:05:28,117 --> 00:05:31,925 there is not only emotional stress, but there's cognitive load, 107 00:05:32,088 --> 00:05:36,973 and it turns out that cognitive load, cognitive effort, mental engagement, 108 00:05:36,973 --> 00:05:39,120 excitement about learning something, 109 00:05:39,120 --> 00:05:41,595 those things also make the signal go up. 110 00:05:42,818 --> 00:05:47,031 Unfortunately, to the embarrassment of the MIT professors, 111 00:05:47,031 --> 00:05:52,070 the low point every day is classroom activity. 112 00:05:53,050 --> 00:05:55,191 Now, I am just showing you one person's data here, 113 00:05:55,191 --> 00:05:58,755 but this unfortunately is true in general. 114 00:06:00,712 --> 00:06:05,117 This sweatband has inside it a home-built skin conductance sensor, 115 00:06:05,117 --> 00:06:09,137 and one day, one of our undergrads knocked on my door 116 00:06:09,137 --> 00:06:13,093 right at the end of the December semester, 117 00:06:13,093 --> 00:06:15,621 and he said, "Professor Picard, 118 00:06:15,621 --> 00:06:17,850 can I please borrow one of your wrist band sensors? 119 00:06:17,850 --> 00:06:20,151 My little brother has autism, 120 00:06:20,151 --> 00:06:21,386 he can't talk, 121 00:06:21,386 --> 00:06:24,497 and I want to see what's stressing him out." 122 00:06:24,770 --> 00:06:27,493 And I said, "Sure, in fact, don't just take one, take two," 123 00:06:27,493 --> 00:06:30,280 because they broke easily back then. 124 00:06:30,280 --> 00:06:32,534 So he took them home, he put them on his little brother. 125 00:06:32,534 --> 00:06:36,209 Now, I was back in MIT looking at the data on my laptop, 126 00:06:36,209 --> 00:06:38,775 and the first day, I thought, hmm, that's odd, 127 00:06:38,775 --> 00:06:41,852 he put them on both wrists instead of waiting for one to break. 128 00:06:42,014 --> 00:06:44,453 OK, fine, don't follow my instructions. 129 00:06:44,453 --> 00:06:46,195 I'm glad he didn't. 130 00:06:46,195 --> 00:06:50,157 Second day, chill, looked like classroom activity. 131 00:06:50,741 --> 00:06:53,644 A few more days ahead. 132 00:06:53,644 --> 00:06:58,182 The next day, one missed signal was flat 133 00:06:58,182 --> 00:07:02,140 and the other had the biggest peak I've ever seen, 134 00:07:02,736 --> 00:07:05,078 and I thought, what's going on? 135 00:07:05,078 --> 00:07:08,562 We've stressed people out at MIT every way imaginable. 136 00:07:08,562 --> 00:07:12,254 I've never seen a peak this big. 137 00:07:12,254 --> 00:07:14,732 And it was only on one side. 138 00:07:14,732 --> 00:07:17,483 How can you be stressed on one side of your body and not the other? 139 00:07:17,483 --> 00:07:20,950 So I thought one or both sensors must be broken. 140 00:07:21,473 --> 00:07:23,840 Now, I'm an electro engineer by training, 141 00:07:23,840 --> 00:07:26,184 so I started a whole bunch of stuff to try to debug this, 142 00:07:26,184 --> 00:07:28,110 and long story short, I could not reproduce this. 143 00:07:28,110 --> 00:07:32,259 So I resorted to old-fashioned debugging. 144 00:07:32,259 --> 00:07:35,522 I called the student at home on vacation. 145 00:07:35,748 --> 00:07:39,932 "Hi, how's your little brother? How's your Christmas? 146 00:07:39,932 --> 00:07:43,150 Hey, do you have any idea what happened to him?" 147 00:07:43,150 --> 00:07:45,316 And I gave this particular date and time, 148 00:07:45,316 --> 00:07:46,698 and the data. 149 00:07:46,698 --> 00:07:50,019 And he said, "I don't know, I'll check the diary." 150 00:07:50,019 --> 00:07:54,022 Diary? MIT student keeps a diary? 151 00:07:54,022 --> 00:07:55,865 So I waited and he came back. 152 00:07:55,865 --> 00:07:57,428 He had the exact date and time, 153 00:07:57,428 --> 00:08:01,281 and he says, "That was right before he had a grand mal seizure." 154 00:08:02,188 --> 00:08:06,312 Now, at the time, I didn't know anything about epilepsy, 155 00:08:06,312 --> 00:08:08,851 and did a bunch of research, 156 00:08:08,851 --> 00:08:11,767 realized that another student's dad is chief of neurosurgery 157 00:08:11,767 --> 00:08:13,781 at Children's Hospital Boston, 158 00:08:13,781 --> 00:08:16,139 screwed up my courage and called Dr. Joe Madsen. 159 00:08:16,139 --> 00:08:18,876 "Hi, Dr. Madsen, my name's Rosalind Picard. 160 00:08:18,876 --> 00:08:23,075 Is it possible somebody could have 161 00:08:23,075 --> 00:08:27,065 a huge sympathetic nervous system surge" -- 162 00:08:27,065 --> 00:08:29,406 that's what drives the skin conductance -- 163 00:08:29,406 --> 00:08:32,158 "20 minutes before a seizure?" 164 00:08:32,158 --> 00:08:34,865 And he says, "Probably not." 165 00:08:34,865 --> 00:08:37,073 He says, "It's interesting. 166 00:08:37,073 --> 00:08:40,060 We've had people whose hair stands on end on one arm 167 00:08:40,060 --> 00:08:42,491 20 minutes before a seizure." 168 00:08:42,491 --> 00:08:44,439 And I'm like, "On one arm?" 169 00:08:44,439 --> 00:08:46,793 I didn't want to tell him that initially 170 00:08:46,793 --> 00:08:49,375 because I thought this was too ridiculous. 171 00:08:49,375 --> 00:08:51,284 He explained how this could happen in the brain, 172 00:08:51,284 --> 00:08:53,720 and he got interested. I showed him the data. 173 00:08:53,720 --> 00:08:56,092 We made a whole bunch more devices, got them safety certified, 174 00:08:56,092 --> 00:08:58,390 90 families were being enrolled in a study 175 00:08:58,390 --> 00:09:01,890 all with children who were going to be monitored 24/7 176 00:09:01,890 --> 00:09:05,403 with gold standard EEG on their scalp 177 00:09:05,403 --> 00:09:06,885 for reading the brain activity, 178 00:09:06,885 --> 00:09:08,814 video to watch the behavior, 179 00:09:08,814 --> 00:09:12,656 electrocardiogram ECG, and now EDA, electrodermal activity, 180 00:09:12,656 --> 00:09:15,015 to see if there was something in this periphery 181 00:09:15,015 --> 00:09:17,711 that we could easily pick up related to a seizure. 182 00:09:18,363 --> 00:09:24,968 We found in 100 percent of the first batch of grand mal seizures 183 00:09:24,968 --> 00:09:28,625 these whopper of responses in the skin conductance. 184 00:09:28,625 --> 00:09:30,652 The blue in the middle, the boy's sleep, 185 00:09:30,652 --> 00:09:32,648 is usually the biggest peak of the day. 186 00:09:32,648 --> 00:09:36,161 These three seizures you see here are popping out of the forest 187 00:09:36,161 --> 00:09:38,783 like redwood trees. 188 00:09:39,238 --> 00:09:43,142 Furthermore, when you couple these skin conductance at the top 189 00:09:43,142 --> 00:09:46,481 with the movement from the wrist 190 00:09:46,481 --> 00:09:51,448 and you get lots of data and train machine learning and AI on it, 191 00:09:51,448 --> 00:09:54,486 you can build an automated AI that detects these patterns 192 00:09:54,486 --> 00:10:00,418 much better than just a shake detector can do. 193 00:10:00,646 --> 00:10:04,669 So we realized that we needed to get this out, 194 00:10:04,669 --> 00:10:07,694 and with the PhD work of ?? 195 00:10:07,694 --> 00:10:10,085 and later great improvements by Empatica, 196 00:10:10,085 --> 00:10:13,953 this has made progress and the seizure detection is much more accurate. 197 00:10:13,953 --> 00:10:16,776 But we also learned some other things about SUDEP during this. 198 00:10:16,776 --> 00:10:18,278 One thing we learned 199 00:10:18,278 --> 00:10:20,116 is that SUDEP is, 200 00:10:20,116 --> 00:10:23,254 while it's rare after a generalized tonic-clonic seizure, 201 00:10:23,254 --> 00:10:26,515 that's when it's most likely to happen after that type, 202 00:10:26,515 --> 00:10:29,554 and when it happens, it doesn't happen during the seizure, 203 00:10:29,554 --> 00:10:32,712 and it doesn't usually happen immediately afterwards, 204 00:10:32,712 --> 00:10:36,820 but immediately afterwards when the person just seems very still and quiet, 205 00:10:36,820 --> 00:10:42,439 they may go into another phase where the breathing stops, 206 00:10:42,439 --> 00:10:45,194 and then after the breathing stops, later the heart stops. 207 00:10:45,392 --> 00:10:47,459 So there's some time to get somebody there. 208 00:10:47,459 --> 00:10:53,445 We also learned that there is a region deep in the brain called the amygdala, 209 00:10:53,445 --> 00:10:56,366 which we had been studying in our emotion research a lot. 210 00:10:56,366 --> 00:10:57,782 We have two amygdalas, 211 00:10:57,782 --> 00:10:59,711 and if you stimulate the right one, 212 00:10:59,711 --> 00:11:02,366 you get a big right skin conductance response. 213 00:11:02,565 --> 00:11:06,538 Now, you have to sign up right now for a craniotomy to get this done, 214 00:11:06,728 --> 00:11:09,140 not exactly something you're going to volunteer to do, 215 00:11:09,140 --> 00:11:11,601 but it causes a big right skin conductance response. 216 00:11:11,601 --> 00:11:15,556 Stimulate the left one, big left skin conductance response on the palm. 217 00:11:15,782 --> 00:11:17,404 And furthermore, 218 00:11:17,404 --> 00:11:19,846 when somebody stimulates your amygdala 219 00:11:19,846 --> 00:11:22,542 while you're sitting there and you might just be working, 220 00:11:22,542 --> 00:11:25,201 you don't show any signs of distress, 221 00:11:25,201 --> 00:11:28,404 but you stop breathing, 222 00:11:28,710 --> 00:11:32,839 and you don't start again until somebody stimulates you. 223 00:11:32,839 --> 00:11:34,376 "Hey, Ros, are you there?" 224 00:11:34,376 --> 00:11:36,583 And you open your mouth to talk. 225 00:11:36,583 --> 00:11:39,326 As you take that breath to speak, 226 00:11:39,326 --> 00:11:41,191 you start breathing again. 227 00:11:43,002 --> 00:11:46,841 So we had started with work on stress, 228 00:11:46,841 --> 00:11:50,446 which had enabled us to build lots of sensors 229 00:11:50,446 --> 00:11:51,893 that were gathering high quality enough data 230 00:11:51,893 --> 00:11:53,347 that we could leave the lab and start to get this in the wild, 231 00:11:53,347 --> 00:11:56,665 accidentally found a whopper of a response with the seizure, 232 00:11:56,665 --> 00:11:59,508 neurological activation that can cause a much bigger response 233 00:11:59,508 --> 00:12:00,894 than traditional stressors, 234 00:12:00,894 --> 00:12:02,959 lots of partnership with hospitals and an epilepsy monitoring unit, 235 00:12:02,959 --> 00:12:05,968 especially Children's Hospital Boston 236 00:12:05,968 --> 00:12:07,983 and the Brigham, 237 00:12:07,983 --> 00:12:09,997 and machine learning and AI on top of this 238 00:12:09,997 --> 00:12:13,051 to take and collect lots more data 239 00:12:13,051 --> 00:12:15,907 in service of trying to understand these events 240 00:12:15,907 --> 00:12:18,005 and if we could prevent SUDEP. 241 00:12:18,263 --> 00:12:21,253 This is now commercialized by Empatica, 242 00:12:21,253 --> 00:12:24,763 a startup that I had the privilege to cofound, 243 00:12:24,763 --> 00:12:27,035 and the team there has done an amazing job improving the technology 244 00:12:27,035 --> 00:12:30,776 to make a very beautiful sensor 245 00:12:30,776 --> 00:12:34,391 that not only tells time and does steps and sleep and all that good stuff, 246 00:12:34,391 --> 00:12:37,857 but this is running real time AI and machine learning 247 00:12:37,857 --> 00:12:40,335 to detect generalized tonic-clonic seizures 248 00:12:40,335 --> 00:12:42,596 and send an alert for help 249 00:12:42,596 --> 00:12:45,812 if I were to have a seizure and lose consciousness. 250 00:12:45,812 --> 00:12:48,652 This just got FDA-approved 251 00:12:48,652 --> 00:12:50,774 as the first smartwatch 252 00:12:50,774 --> 00:12:52,792 to get approved in neurology. 253 00:12:54,235 --> 00:13:00,552 (Applause) 254 00:13:02,914 --> 00:13:07,112 Now the next slide is what made my skin conductance go up. 255 00:13:07,242 --> 00:13:08,971 One morning, I'm checking my email 256 00:13:08,971 --> 00:13:11,214 and I see a story from a mom 257 00:13:11,214 --> 00:13:13,012 who said she was in the shower 258 00:13:13,012 --> 00:13:15,547 and her phone was on the counter by the shower, 259 00:13:15,547 --> 00:13:18,436 and it said her daughter might need her help. 260 00:13:18,436 --> 00:13:21,239 So she interrupts her shower and goes running to her daughter's bedroom, 261 00:13:21,239 --> 00:13:25,608 and she finds her daughter face down in bed blue and not breathing. 262 00:13:25,608 --> 00:13:29,046 She flips her over, human stimulation, 263 00:13:29,046 --> 00:13:32,746 and her daughter takes a breath, and another breath, 264 00:13:32,936 --> 00:13:36,890 and her daughter turns pink and is fine. 265 00:13:37,791 --> 00:13:40,851 I think I turned white reading this email. 266 00:13:40,851 --> 00:13:43,385 My first response is, "Oh no, it's not perfect. 267 00:13:43,385 --> 00:13:45,234 The Bluetooth could break. The battery could die. 268 00:13:45,234 --> 00:13:47,590 All these things could go wrong. Don't rely on this." 269 00:13:47,590 --> 00:13:49,435 And she said, "It's OK. 270 00:13:49,435 --> 00:13:51,667 I know no technology is perfect. 271 00:13:51,667 --> 00:13:54,601 None of us can always be there all the time. 272 00:13:54,601 --> 00:13:59,450 But this, this device plus AI 273 00:13:59,450 --> 00:14:02,984 enabled me to get there in time to save my daughter's life. 274 00:14:06,245 --> 00:14:08,103 Now, I've been mentioning children, 275 00:14:08,103 --> 00:14:13,834 but SUDEP peaks actually among people in their 20s, 30s, and 40s, 276 00:14:13,834 --> 00:14:16,832 and the next line I'm going to put up 277 00:14:16,832 --> 00:14:18,044 is probably going to make some people uncomfortable, 278 00:14:18,044 --> 00:14:22,908 but it's less uncomfortable than we'll all be 279 00:14:22,908 --> 00:14:24,807 if this list is extended to somebody you know. 280 00:14:24,807 --> 00:14:27,437 Could this happen to somebody you know? 281 00:14:27,437 --> 00:14:30,133 And the reason I bring up this uncomfortable question 282 00:14:30,133 --> 00:14:34,926 is because one in 26 of you will have epilepsy at some point, 283 00:14:34,926 --> 00:14:37,398 and from what I've been learning, 284 00:14:37,398 --> 00:14:40,547 people with epilepsy often don't tell their friends and their neighbors 285 00:14:40,547 --> 00:14:41,698 that they have it. 286 00:14:41,698 --> 00:14:46,995 So if you're willing to let them use an AI or whatever 287 00:14:46,995 --> 00:14:51,321 to summon you in a moment of possible need, 288 00:14:51,321 --> 00:14:53,032 if you would let them know that, 289 00:14:53,032 --> 00:14:55,386 you could make a difference in their life. 290 00:14:56,000 --> 00:15:00,397 Why do all this hard work to build AIs? 291 00:15:00,397 --> 00:15:01,927 A couple of reasons here: 292 00:15:01,927 --> 00:15:03,856 one is Natasha, the girl who lived, 293 00:15:03,856 --> 00:15:07,575 and her family wanted me to tell you her name. 294 00:15:07,575 --> 00:15:09,115 Another is her family 295 00:15:09,115 --> 00:15:11,849 and the wonderful people out there 296 00:15:11,849 --> 00:15:13,970 who want to be there to support people who have conditions 297 00:15:13,970 --> 00:15:18,063 that they've felt uncomfortable in the past mentioning to others. 298 00:15:18,253 --> 00:15:20,311 And the other reason is all of you, 299 00:15:20,311 --> 00:15:22,849 because we have the opportunity 300 00:15:22,849 --> 00:15:25,481 to shape the future of AI. 301 00:15:25,481 --> 00:15:28,273 We can actually change it, 302 00:15:28,273 --> 00:15:30,203 because we are the ones building it. 303 00:15:30,203 --> 00:15:32,352 So let's build AI 304 00:15:32,352 --> 00:15:35,991 that makes everybody's lives better. 305 00:15:35,991 --> 00:15:38,588 Thank you. 306 00:15:38,588 --> 00:15:41,691 (Applause)