1 00:13:37,200 --> 00:13:40,920 So they can see us. 2 00:13:44,320 --> 00:13:45,917 All right. Hey guys, can you guys take a 3 00:13:46,000 --> 00:13:50,397 seat and uh yeah, let's uh not be get 4 00:13:50,480 --> 00:13:55,560 ready for you know what is coming. 5 00:14:16,160 --> 00:14:17,277 So, I'm going to open up with the Medal 6 00:14:17,360 --> 00:14:19,677 of Science and then go into your next 7 00:14:19,760 --> 00:14:23,117 question and then I'll go into 8 00:14:23,200 --> 00:14:27,037 >> No, I think it's most relevant. 9 00:14:27,120 --> 00:14:30,920 >> I can hit him with that. 10 00:15:00,640 --> 00:15:05,270 Uhhuh. Woo! [cheering] 11 00:15:06,530 --> 00:15:09,117 [applause] [cheering] 12 00:15:09,200 --> 00:15:13,837 >> Elon, welcome to the X Takeover. Your third year in a row. Thank you so much 13 00:15:13,920 --> 00:15:15,277 for your time. 14 00:15:15,360 --> 00:15:18,637 >> You're welcome. Hey, guys. [cheering] 15 00:15:18,720 --> 00:15:23,677 >> We have 20 two over 2,000 people here at 16 00:15:23,760 --> 00:15:27,517 Giga Texas today and we are all here to 17 00:15:27,600 --> 00:15:31,757 support you and the work you are doing for humanity. So, thank you. [cheering] 18 00:15:31,840 --> 00:15:34,157 >> Uh, thank you. Thanks, guys. Really 19 00:15:34,240 --> 00:15:36,797 appreciate your support. [applause] 20 00:15:36,880 --> 00:15:41,517 >> So, what's crazy, Elon, is four years ago, we sat down here at Giga Texas with 21 00:15:41,600 --> 00:15:43,197 you when the factory wasn't even 22 00:15:43,280 --> 00:15:45,597 running, and you described how close 23 00:15:45,680 --> 00:15:48,717 Tesla was coming uh to not surviving in 24 00:15:48,800 --> 00:15:52,397 2008. Looking out at this community 25 00:15:52,480 --> 00:15:54,637 today of 2,000 people, what makes you 26 00:15:54,720 --> 00:15:57,357 pause and appreciate how far things have 27 00:15:57,440 --> 00:15:59,597 come? 28 00:15:59,680 --> 00:16:03,117 Yeah. Um it's difficult to imagine here 29 00:16:03,200 --> 00:16:06,557 in 2026 uh that that Tesla's actually, 30 00:16:06,640 --> 00:16:09,597 you know, has come close to death 31 00:16:09,680 --> 00:16:14,237 multiple times. Actually, 2008 was pro was the worst. Um you know, that's where 32 00:16:14,320 --> 00:16:19,757 we we closed the financing round at 6 p.m. on Christmas Eve 2008. Uh it's the 33 00:16:19,840 --> 00:16:22,717 last hour of the last day that it was possible. We would have bounced payroll 34 00:16:22,800 --> 00:16:24,557 a few days after Christmas if the round 35 00:16:24,640 --> 00:16:26,637 hadn't closed. So that was pretty 36 00:16:26,720 --> 00:16:31,437 stressful. Um and then um and then then 37 00:16:31,520 --> 00:16:35,757 20 2018 was uh pretty bad too. Um but we 38 00:16:35,840 --> 00:16:38,637 had to get to 5,000 a week of the uh 39 00:16:38,720 --> 00:16:42,317 Model 3 or go bankrupt. Um that that was 40 00:16:42,400 --> 00:16:46,477 a pretty wild situation which uh I guess probably a lot of 41 00:16:46,560 --> 00:16:49,197 people know the story of, but we had to we had to figure out some way to 42 00:16:49,280 --> 00:16:53,197 increase uh Model 3 production by 50% in 43 00:16:53,280 --> 00:16:57,917 3 weeks. Uh which is insane. in absolutely 44 00:16:58,000 --> 00:17:02,317 insane. >> Yeah. So, 45 00:17:02,400 --> 00:17:03,997 uh but I'll I'll recount the story for 46 00:17:04,080 --> 00:17:07,837 those who haven't heard it. Um the uh so 47 00:17:07,920 --> 00:17:09,837 we we the choke point was general 48 00:17:09,920 --> 00:17:14,637 assembly for the Model 3 and um 49 00:17:14,720 --> 00:17:18,317 so we we had we we were able to achieve rate almost everywhere everywhere else 50 00:17:18,400 --> 00:17:22,157 but except for general assembly and and there was and and for general assembly 51 00:17:22,240 --> 00:17:23,437 you need like a moving production line. 52 00:17:23,520 --> 00:17:27,517 You need you need shelter. You need a moving production line. uh you know, 53 00:17:27,600 --> 00:17:29,597 power and and equipment and all that. 54 00:17:29,680 --> 00:17:34,317 And uh we we maxed out the two production lines 55 00:17:34,400 --> 00:17:35,997 that we had and then we needed a third 56 00:17:36,080 --> 00:17:38,717 one and uh and and that was where we 57 00:17:38,800 --> 00:17:41,997 built the tent in the parking lot. Um 58 00:17:42,080 --> 00:17:47,597 and uh and then we needed to some some way to move the cars down the line, like 59 00:17:47,680 --> 00:17:51,357 you know, moving production line situation. And the only thing that we 60 00:17:51,440 --> 00:17:54,477 had was um some discarded equipment that 61 00:17:54,560 --> 00:17:56,797 was used for moving small parts, not 62 00:17:56,880 --> 00:17:59,517 like whole cars. And and it didn't 63 00:17:59,600 --> 00:18:02,237 actually have the power to move uh the 64 00:18:02,320 --> 00:18:05,357 whole cars, but the parking lot was on a 65 00:18:05,440 --> 00:18:07,597 slight incline. It was like a 3 or 4° 66 00:18:07,680 --> 00:18:09,437 incline. So we actually started the 67 00:18:09,520 --> 00:18:12,797 production line at the top and then the 68 00:18:12,880 --> 00:18:15,597 the the sort of tiny moving production 69 00:18:15,680 --> 00:18:20,717 line was that was just meant for for parts was actually able to move the cars 70 00:18:20,800 --> 00:18:24,397 because they were going slightly downhill 71 00:18:24,480 --> 00:18:26,957 and um and so we're able to increase 72 00:18:27,040 --> 00:18:32,117 production by 30% in in 3 weeks. 73 00:18:32,200 --> 00:18:36,877 [cheering] [applause] >> Yeah, that was wild. I mean, we're we're 74 00:18:36,960 --> 00:18:39,437 laying the as we're building the tent, we're like laying the concrete for the 75 00:18:39,520 --> 00:18:42,877 line and putting in the rails. 76 00:18:42,960 --> 00:18:47,517 Um, so working 24/7 77 00:18:47,600 --> 00:18:50,477 like the short sellers were actually right meaning like if you looked at the 78 00:18:50,560 --> 00:18:52,957 situation that there was like it was a 79 00:18:53,040 --> 00:18:57,917 crazy short position against Tesla as there has been at various times. Um, and 80 00:18:58,000 --> 00:19:02,077 and they had extremely good inside information. Um and they they thought 81 00:19:02,160 --> 00:19:04,317 well there's no way we could possibly uh 82 00:19:04,400 --> 00:19:08,077 solve the production choke point. Um and 83 00:19:08,160 --> 00:19:12,157 on a set piece battle unlike a conventional say chess match situation 84 00:19:12,240 --> 00:19:14,877 uh they had us in checkmate. 85 00:19:14,960 --> 00:19:20,157 Um but we just you know invented a new piece basically that didn't exist 86 00:19:20,240 --> 00:19:21,757 before. 87 00:19:21,840 --> 00:19:25,517 So so uh they got the shortcut steam 88 00:19:25,600 --> 00:19:27,917 roll. 89 00:19:28,000 --> 00:19:31,357 Hey Elon, we just had your mom here on 90 00:19:31,440 --> 00:19:34,317 stage today. What story are you hoping 91 00:19:34,400 --> 00:19:39,070 she doesn't tell us? [laughter] 92 00:19:40,080 --> 00:19:43,357 I don't know. Maybe I pooped my pants when I was like a toddler or something. 93 00:19:43,440 --> 00:19:45,597 I don't know. [laughter] I probably did. 94 00:19:45,680 --> 00:19:50,477 Everybody does. Um so uh I don't know. 95 00:19:50,560 --> 00:19:53,560 um 96 00:19:57,040 --> 00:19:59,357 >> was the latest. >> I was I was a pretty difficult to 97 00:19:59,440 --> 00:20:03,357 contain kid, you know, so like my parents would like say that, you know, 98 00:20:03,440 --> 00:20:06,637 tell me I'm not supposed to like leave the house or whatever. Um when I was 99 00:20:06,720 --> 00:20:09,197 like I don't know four or 5 years old and I would just like constantly like 100 00:20:09,280 --> 00:20:13,597 leave the house and go running down the street. Um and then they they'd like 101 00:20:13,680 --> 00:20:15,757 lock me lock me in a room so so I 102 00:20:15,840 --> 00:20:18,157 couldn't I couldn't run away and and run 103 00:20:18,240 --> 00:20:22,077 down the street. Um, and then uh like we 104 00:20:22,160 --> 00:20:25,677 had one of those old locks where you could poke the key through the door. You 105 00:20:25,760 --> 00:20:27,357 know, the lock's accessible from both 106 00:20:27,440 --> 00:20:30,237 sides and um and I could see the key and 107 00:20:30,320 --> 00:20:34,717 I like poked the poked the key until it fell down. And then I was like able to 108 00:20:34,800 --> 00:20:37,837 get like a piece of paper to scoop it up and and bring it to the other side and 109 00:20:37,920 --> 00:20:41,037 lock myself and then and my mom was like, "How'd you get out?" I was like, 110 00:20:41,120 --> 00:20:44,317 "I'm not telling you." [laughter] 111 00:20:44,400 --> 00:20:47,677 Uh but uh yeah, I was part to contain as 112 00:20:47,760 --> 00:20:51,677 a kid. So, before we jump into more specific 113 00:20:51,760 --> 00:20:53,517 things, what's something that you wish 114 00:20:53,600 --> 00:20:57,277 more people would ask you? 115 00:20:57,360 --> 00:21:00,807 >> Well, I I don't really wish people would ask me questions to be honest. Um, 116 00:21:00,890 --> 00:21:03,757 [laughter] I'm not like 117 00:21:03,840 --> 00:21:08,397 >> sorry, I'm not going around. I wish people would ask me more questions like, 118 00:21:08,480 --> 00:21:15,350 you know, here we go with questions, you know. Um, so yeah, I [laughter] 119 00:21:15,920 --> 00:21:20,157 um I guess it's good to to hear questions 120 00:21:20,240 --> 00:21:21,517 that that you haven't heard before. 121 00:21:21,600 --> 00:21:24,877 Otherwise, you know, a lot of times it's like the same questions that people ask 122 00:21:24,960 --> 00:21:29,277 and I I feel like I could have like, you know, just like whatever have these 123 00:21:29,360 --> 00:21:32,957 recordings of the answer and I'll just play you. Oh, that's question 27. Here 124 00:21:33,040 --> 00:21:36,157 you go. It has answer 27 125 00:21:36,240 --> 00:21:39,277 that I've given a hundred times before. 126 00:21:39,360 --> 00:21:42,557 Um, so, uh, maybe I should like have a 127 00:21:42,640 --> 00:21:45,277 let's just have like a web page with 128 00:21:45,360 --> 00:21:47,967 literally frequently asked questions. 129 00:21:48,050 --> 00:21:51,677 [laughter] >> It's like asking because then it's like 130 00:21:51,760 --> 00:21:55,037 it's just go to the page and then you you got it. You got the answer, you know? 131 00:21:55,120 --> 00:21:58,317 >> It's like the infinite self a selfie loop. [laughter] 132 00:21:58,400 --> 00:22:01,997 >> Yeah, exactly. My idea of hell is be stuck in an infinite selfie loop. Like 133 00:22:02,080 --> 00:22:06,157 it's infinite. Can I have a selfie? And like and and then like you know it's 134 00:22:06,240 --> 00:22:09,517 like problem is like you say yes to one person and every once in a while then 135 00:22:09,600 --> 00:22:14,317 and then like then there's a queue forms pretty soon there's it's just never 136 00:22:14,400 --> 00:22:17,357 ending selfies and then there's like always like something goes wrong with 137 00:22:17,440 --> 00:22:20,397 the phone or they don't get the camera right or the effective wrong and then 138 00:22:20,480 --> 00:22:22,477 it's like god damn it you know and it 139 00:22:22,560 --> 00:22:24,557 drop the phone drops and it's like oh 140 00:22:24,640 --> 00:22:29,917 man um it's just it just can't be like infinite selfie loop is just a long loop 141 00:22:30,000 --> 00:22:34,317 you know >> just uh >> we had uh your your mom and Nikki up for 142 00:22:34,400 --> 00:22:36,477 that, too. They had the infinite selfie 143 00:22:36,560 --> 00:22:39,437 loop today, but um I'll pass [laughter] 144 00:22:39,520 --> 00:22:41,677 I'll pass this to Kelvin. 145 00:22:41,760 --> 00:22:44,157 >> All right, let's start with Starship. 146 00:22:44,240 --> 00:22:46,477 Congratulations on flight 14. 147 00:22:46,560 --> 00:22:50,197 >> Uh thanks. Yeah, it's a great team. 148 00:22:50,280 --> 00:22:52,300 [cheering and applause] 149 00:22:54,400 --> 00:22:58,077 >> It's pretty wild that that I can just go down there in South Texas and just see 150 00:22:58,160 --> 00:23:00,957 it from the road. 151 00:23:01,040 --> 00:23:05,677 So flight 14 lost an engine on the way up and still reaches its orbit. What was 152 00:23:05,760 --> 00:23:07,037 happening behind the scenes in those 153 00:23:07,120 --> 00:23:09,437 minutes before the team go got called 154 00:23:09,520 --> 00:23:13,357 the uh go for orbit message. 155 00:23:13,440 --> 00:23:15,677 >> Um well we're just trying to see why. 156 00:23:15,760 --> 00:23:17,757 We're trying to understand 157 00:23:17,840 --> 00:23:19,597 what what was the reason for the engine 158 00:23:19,680 --> 00:23:23,197 failure. Um, was there say a common 159 00:23:23,280 --> 00:23:25,997 cause where we could expect to see more 160 00:23:26,080 --> 00:23:30,477 engine failures? Uh, or would we would there the biggest question is like would 161 00:23:30,560 --> 00:23:34,957 there be a potential problem with restarting the sea level Raptor engines, 162 00:23:35,040 --> 00:23:37,357 the three ones with the smaller nozzles 163 00:23:37,440 --> 00:23:41,197 in the center for uh the de-orbit burn 164 00:23:41,280 --> 00:23:44,957 uh because we don't want a starship to get stuck on orbit and then it randomly 165 00:23:45,040 --> 00:23:48,797 reenter and maybe land on someone. you know, that's that's our main thing is 166 00:23:48,880 --> 00:23:50,397 like trying to make sure things are as 167 00:23:50,480 --> 00:23:55,277 safe as possible. So, um the the the 168 00:23:55,360 --> 00:23:58,797 cause of the the engine out, I think, was like basically a failure in the 169 00:23:58,880 --> 00:24:02,237 flight computer software or engine computer software, I should say. Uh 170 00:24:02,320 --> 00:24:03,837 which it didn't appear to be anything 171 00:24:03,920 --> 00:24:07,277 that was present in any of the other uh 172 00:24:07,360 --> 00:24:11,997 engine computers. So, uh, so I thought, 173 00:24:12,080 --> 00:24:17,037 okay, well, this is it's probably okay to go to orbit. 174 00:24:17,120 --> 00:24:18,877 >> So, Elon, we know one of your famous 175 00:24:18,960 --> 00:24:21,117 sayings is, 176 00:24:21,200 --> 00:24:24,317 um, from the impossible to merely late. 177 00:24:24,400 --> 00:24:27,597 Did this flight feel like a turning point in what's possible now for 178 00:24:27,680 --> 00:24:32,637 Starship? >> Well, I I guess it is a good milestone. 179 00:24:32,720 --> 00:24:36,397 Um cuz I mean we could have gone to orbit 180 00:24:36,480 --> 00:24:40,317 many times before now. Um but the reason we didn't go to orbit before now was 181 00:24:40,400 --> 00:24:42,157 because we wanted to be extremely 182 00:24:42,240 --> 00:24:43,757 confident of being able to de-orbit 183 00:24:43,840 --> 00:24:47,837 safely. Um so that that's that's why we 184 00:24:47,920 --> 00:24:49,357 we only went to orbit on this flight. 185 00:24:49,440 --> 00:24:52,237 But all all pretty much all of the prior missions, in fact, literally all of the 186 00:24:52,320 --> 00:24:56,797 prior missions could have could have gone to orbit. Um, 187 00:24:56,880 --> 00:25:02,397 so, uh, at this point we're, 188 00:25:02,480 --> 00:25:05,757 you know, everything's looking quite positive. The the the heat shield is 189 00:25:05,840 --> 00:25:09,117 looking robust. Uh, the engines are 190 00:25:09,200 --> 00:25:12,957 robust, apart from that one glitch, but that glitch doesn't seem to be too much 191 00:25:13,040 --> 00:25:17,517 of an issue. It's like pretty easy to remedy. Um, 192 00:25:17,600 --> 00:25:19,117 there's 193 00:25:19,200 --> 00:25:21,517 but like the heat shield was was uh 194 00:25:21,600 --> 00:25:25,437 extremely robust on this flight. Um, 195 00:25:25,520 --> 00:25:28,797 and that's that's that's one of the hardest things. The other really hard 196 00:25:28,880 --> 00:25:31,357 thing is like said that the is just 197 00:25:31,440 --> 00:25:32,557 getting to extremely high engine 198 00:25:32,640 --> 00:25:36,637 reliability. Uh, and um, everything 199 00:25:36,720 --> 00:25:40,077 looked good. Um, the the big milestone 200 00:25:40,160 --> 00:25:42,237 that's coming up uh, hopefully on the 201 00:25:42,320 --> 00:25:45,677 next flight, which is we don't know the 202 00:25:45,760 --> 00:25:48,477 exact date cuz we're making a bunch of 203 00:25:48,560 --> 00:25:49,997 um, 204 00:25:50,080 --> 00:25:52,797 improvements to the rocket. Um so like 205 00:25:52,880 --> 00:25:57,517 between every flight there's there's um there's often hundreds sometimes 206 00:25:57,600 --> 00:25:59,597 thousands of of small changes to improve 207 00:25:59,680 --> 00:26:01,277 things. In this case the number of 208 00:26:01,360 --> 00:26:05,197 changes is not very many um but but but 209 00:26:05,280 --> 00:26:06,797 some of them take a fair bit of work and 210 00:26:06,880 --> 00:26:08,877 we've got to go inside the the tank to 211 00:26:08,960 --> 00:26:12,557 to make some of these changes. So 212 00:26:12,640 --> 00:26:14,237 uh so we don't know the exact launch 213 00:26:14,320 --> 00:26:16,637 date but probably about 4 weeks or so 214 00:26:16,720 --> 00:26:20,237 four to six weeks is about right. um if 215 00:26:20,320 --> 00:26:24,477 if if probably launches a little bit before Thanks Thanksgiving is my guess. 216 00:26:24,560 --> 00:26:29,677 Um and and and that that that one if it succeeds is a big one because we're 217 00:26:29,760 --> 00:26:32,637 going to try to catch we catch the booster which we've already proven we 218 00:26:32,720 --> 00:26:34,317 can catch the booster twice but we're 219 00:26:34,400 --> 00:26:36,237 going to try to catch the ship which is 220 00:26:36,320 --> 00:26:40,077 a super big deal and um and and if we do 221 00:26:40,160 --> 00:26:43,997 so that'll be the first time that there's been full recovery of an orbital 222 00:26:44,080 --> 00:26:49,037 class uh rocket. >> Sounds good. You you said uh four to six 223 00:26:49,120 --> 00:26:53,990 weeks. I'm not used to that. I'm used to the two weeks phrase. [laughter] 224 00:26:54,160 --> 00:26:57,757 >> I can I'm confident it's not two weeks. 225 00:26:57,840 --> 00:27:00,237 >> All right, you heard it here. Now, um 226 00:27:00,320 --> 00:27:05,037 what's the hardest part left to get right once you catch the Starship for 227 00:27:05,120 --> 00:27:09,757 the first time? What what is the next big goal after that? 228 00:27:09,840 --> 00:27:11,597 >> Well, the ne the next big milestone 229 00:27:11,680 --> 00:27:14,717 would be to refly um both the booster 230 00:27:14,800 --> 00:27:16,877 and the ship. 231 00:27:16,960 --> 00:27:20,397 Um so the milestone next upcoming 232 00:27:20,480 --> 00:27:22,077 milestone is is would be the first time 233 00:27:22,160 --> 00:27:24,237 in history that 234 00:27:24,320 --> 00:27:27,597 all parts of an orbital uh rocket have 235 00:27:27,680 --> 00:27:32,237 been recovered but but then that the flight after that hopefully will be the 236 00:27:32,320 --> 00:27:34,477 first time that all parts of an orbital 237 00:27:34,560 --> 00:27:37,677 rocket are refflown. 238 00:27:37,760 --> 00:27:41,837 Um, and then then there's a there's a long tale of of engineering and 239 00:27:41,920 --> 00:27:43,997 production work and and work on the 240 00:27:44,080 --> 00:27:46,317 launch system and everything to to make 241 00:27:46,400 --> 00:27:50,637 it uh rapidly reusable. 242 00:27:50,720 --> 00:27:53,437 So, so I say it's it's kind of the 243 00:27:53,520 --> 00:28:00,150 rapidly reusable reliable rockets [laughter] 244 00:28:00,480 --> 00:28:04,157 >> the pirate >> pirate should mess the pirate rocket. 245 00:28:04,240 --> 00:28:06,237 Um, rapidly reusable reliable rockets. 246 00:28:06,320 --> 00:28:09,197 Man, we should have gotten you a patch for this one. 247 00:28:09,280 --> 00:28:13,677 >> Yeah. >> Hey, when you founded SpaceX, Elon, 248 00:28:13,760 --> 00:28:17,997 could you have imagined its mission expanding into SI and data centers in 249 00:28:18,080 --> 00:28:22,937 space? And how did you come to see rockets and SI belonging under one roof? 250 00:28:23,020 --> 00:28:24,477 [laughter] 251 00:28:24,560 --> 00:28:26,157 >> Well, because I'm very far-sighted, of 252 00:28:26,240 --> 00:28:31,117 course. Um well I I guess um 253 00:28:31,200 --> 00:28:33,997 if you say like as you as you expand 254 00:28:34,080 --> 00:28:36,237 into space 255 00:28:36,320 --> 00:28:41,277 um the you know you're able to harness a 256 00:28:41,360 --> 00:28:43,917 lot more of the sun's power in space 257 00:28:44,000 --> 00:28:47,357 than than you can on Earth. So one it's 258 00:28:47,440 --> 00:28:49,117 like important to appreciate the sheer 259 00:28:49,200 --> 00:28:51,517 magnitude of the sun and how the sun is 260 00:28:51,600 --> 00:28:54,717 pretty much everything. Um so the sun is 261 00:28:54,800 --> 00:28:57,597 99.86% 86% of all the mass in the solar 262 00:28:57,680 --> 00:29:00,557 system. And then you've got Jupiter as 263 00:29:00,640 --> 00:29:05,437 like you know most of the remaining mass. Um and then and then you the gas 264 00:29:05,520 --> 00:29:09,837 giants are pretty much that. And then like like Earth is basically a tiny dust 265 00:29:09,920 --> 00:29:14,637 moat like a rounding error in the mass of the the solar system. 266 00:29:14,720 --> 00:29:18,237 Um so we're we're just extremely tiny. It's 267 00:29:18,320 --> 00:29:19,997 like hard to hard to believe how we're 268 00:29:20,080 --> 00:29:23,437 Earth is a tiny dust mode. So, so as you 269 00:29:23,520 --> 00:29:25,597 expand into into space and you're able 270 00:29:25,680 --> 00:29:28,797 to um harness more of the sun's uh 271 00:29:28,880 --> 00:29:31,757 power, the uh you have to say what are 272 00:29:31,840 --> 00:29:34,797 you going to use that for? Um it's like 273 00:29:34,880 --> 00:29:37,517 well um you're going to use it for a lot 274 00:29:37,600 --> 00:29:42,157 of digital intelligence. Um I mean you you're basically you're 275 00:29:42,240 --> 00:29:45,917 either going to do computation or you're going to shape atoms. 276 00:29:46,000 --> 00:29:48,957 Um, and there's going to be probably a 277 00:29:49,040 --> 00:29:51,117 lot of a lot more shaping atoms than 278 00:29:51,200 --> 00:29:54,477 there's sorry going to be a lot more uh 279 00:29:54,560 --> 00:29:59,197 sort of digital thinking than there will be shaping atoms cuz there aren't 280 00:29:59,280 --> 00:30:02,317 there's like the amount of atoms you can shape in the solar system is not that 281 00:30:02,400 --> 00:30:03,757 much and a lot of the atom shaping 282 00:30:03,840 --> 00:30:06,477 itself will be for the purposes of 283 00:30:06,560 --> 00:30:09,357 building um digital super intelligence 284 00:30:09,440 --> 00:30:13,517 uh and and what I call creating a sentient sun 285 00:30:13,600 --> 00:30:18,877 >> and and it it may be that there are many sentient suns out there. Um, 286 00:30:18,960 --> 00:30:20,157 you know, and that would that would help 287 00:30:20,240 --> 00:30:22,237 us then understand the nature of the 288 00:30:22,320 --> 00:30:27,997 universe and uh extend consciousness to, 289 00:30:28,080 --> 00:30:31,517 you know, beyond our solar system ultimately to, you know, like Star Trek 290 00:30:31,600 --> 00:30:36,637 to go to places you've never forget what the exact phrase was, but 291 00:30:36,720 --> 00:30:38,157 explore the universe, but go places 292 00:30:38,240 --> 00:30:41,517 you've never been before. Um, and and I 293 00:30:41,600 --> 00:30:44,557 think like maybe we'll find uh alien 294 00:30:44,640 --> 00:30:47,917 civilizations out there. Um, or we may 295 00:30:48,000 --> 00:30:52,077 find that there are the long dead ruins 296 00:30:52,160 --> 00:30:53,757 of alien civilizations that have been 297 00:30:53,840 --> 00:30:55,517 around for maybe they had a really good 298 00:30:55,600 --> 00:30:59,117 run like 10 million years and and uh now 299 00:30:59,200 --> 00:31:01,437 and and before they their civilization 300 00:31:01,520 --> 00:31:06,317 came to an end um cuz nothing lasts forever. So 301 00:31:06,400 --> 00:31:09,357 like I always think about earth civilization. If you date Earth's 302 00:31:09,440 --> 00:31:12,877 civilization from the first writing, 303 00:31:12,960 --> 00:31:15,757 that's 5,500 years ago, 304 00:31:15,840 --> 00:31:18,557 like in ancient Suma with the sort of 305 00:31:18,640 --> 00:31:22,557 archaic ununiform. Um, 306 00:31:22,640 --> 00:31:27,597 that's only 5,500 years. Um, 307 00:31:27,680 --> 00:31:31,517 the it looks like Earth is about 4 and a 308 00:31:31,600 --> 00:31:34,157 half billion years old according to, you 309 00:31:34,240 --> 00:31:39,677 know, what physics suggests. Um and um 310 00:31:39,760 --> 00:31:43,037 so that that means human civilization has only been around 1 millionth of 311 00:31:43,120 --> 00:31:47,037 Earth's existence. And um and so so if we had a 312 00:31:47,120 --> 00:31:52,237 civilization that lasted a million years or let alone 10 million years would be I 313 00:31:52,320 --> 00:31:56,877 think would be a very very successful civilization if we did that. 314 00:31:56,960 --> 00:31:58,717 >> Woo. 315 00:31:58,800 --> 00:32:01,597 >> Yeah. I mean but but that's still very 316 00:32:01,680 --> 00:32:04,797 tiny compared to the apparent age of the 317 00:32:04,880 --> 00:32:08,077 universe. um which is 13.8 billion 318 00:32:08,160 --> 00:32:11,997 years. So like like just just to get to like 319 00:32:12,080 --> 00:32:14,797 the third place past decimal point on 320 00:32:14,880 --> 00:32:19,677 age of the universe like to increment it by a million years you'd have to go 13.8 321 00:32:19,760 --> 00:32:24,237 whatever the next digit is whatever the next digit is plus you know plus one on 322 00:32:24,320 --> 00:32:26,597 the third digit past decimal point. 323 00:32:26,680 --> 00:32:28,717 [laughter] Now you're a million years old and and 324 00:32:28,800 --> 00:32:31,197 and that would be a a civilization 325 00:32:31,280 --> 00:32:35,357 vastly older than than than uh humanity. 326 00:32:35,440 --> 00:32:38,317 Yeah, that's ab Yeah, it sounds again 327 00:32:38,400 --> 00:32:42,797 like the infinite selfie loop, but uh [laughter] 328 00:32:42,880 --> 00:32:45,277 All right, so jumping into something 329 00:32:45,360 --> 00:32:47,837 that SpaceX has done, right? You you 330 00:32:47,920 --> 00:32:50,237 acquired Cursor and I feel like for me 331 00:32:50,320 --> 00:32:52,877 when you think of, you know, um Google, 332 00:32:52,960 --> 00:32:55,037 hey, did you Google it? Hey, did you did 333 00:32:55,120 --> 00:32:57,837 you gro it? And for me, you know, um 334 00:32:57,920 --> 00:33:00,237 Grockbot has been such an absolute 335 00:33:00,320 --> 00:33:03,037 gamecher for me personally in my in my 336 00:33:03,120 --> 00:33:05,277 life. But what was it about the cursor 337 00:33:05,360 --> 00:33:08,317 team that you guys wanted to uh bring in 338 00:33:08,400 --> 00:33:12,957 you know that space or you wanted to acquire cursor that was like let's bring 339 00:33:13,040 --> 00:33:14,557 it into the fold. What was different 340 00:33:14,640 --> 00:33:18,637 about them or what did you see? Well, um 341 00:33:18,720 --> 00:33:20,317 the 342 00:33:20,400 --> 00:33:23,837 so in in order to create a a compelling 343 00:33:23,920 --> 00:33:26,877 AI, you need um you you need a lot of 344 00:33:26,960 --> 00:33:30,157 training data. Um and and you got you've 345 00:33:30,240 --> 00:33:33,917 got to solve coding and there were really just as far as I can tell three 346 00:33:34,000 --> 00:33:37,037 organizations that had enough coding 347 00:33:37,120 --> 00:33:38,637 training data and that was Anthropic, 348 00:33:38,720 --> 00:33:41,197 OpenAI and Kurser and and arguably 349 00:33:41,280 --> 00:33:44,477 perhaps Google. But um but but to have 350 00:33:44,560 --> 00:33:48,717 that those you actually absolutely have to have the data in order to train train 351 00:33:48,800 --> 00:33:52,397 an effective coding AI and and if you can't do coding your AI is not going to 352 00:33:52,480 --> 00:33:56,477 be very useful. Um and then there's there's a lot a lot of talented people 353 00:33:56,560 --> 00:33:58,797 at cursor. So like basically for success 354 00:33:58,880 --> 00:34:01,917 of AI you've got to need you need data 355 00:34:02,000 --> 00:34:04,557 talented people and compute and you also 356 00:34:04,640 --> 00:34:09,277 need um a good enterprise sales team and the curs also had that had a good 357 00:34:09,360 --> 00:34:11,437 enterprise sales team with um 358 00:34:11,520 --> 00:34:14,157 relationships with uh you know th 359 00:34:14,240 --> 00:34:19,037 thousands of of companies um so you know 360 00:34:19,120 --> 00:34:24,797 that those those are very significant um advantages. 361 00:34:24,880 --> 00:34:29,197 Hey Elon, you've talked about how quickly the SI space is moving. What's 362 00:34:29,280 --> 00:34:33,837 something that SI has done recently that made you stop and reconsider how quickly 363 00:34:33,920 --> 00:34:37,677 this is moving and where it could lead to? 364 00:34:37,760 --> 00:34:40,717 >> Well, I mean lately the the videos, the 365 00:34:40,800 --> 00:34:44,877 music videos that AI is making are so good. [laughter] 366 00:34:44,960 --> 00:34:47,517 Like they're unbelievably good. 367 00:34:47,600 --> 00:34:51,437 >> And I post a bunch of these on my ex account. I'm like, holy smokes, you 368 00:34:51,520 --> 00:34:53,277 know? I mean, like some of them I think 369 00:34:53,360 --> 00:34:56,957 are like maybe top 10, top 20 best music 370 00:34:57,040 --> 00:35:01,837 videos I've ever seen, [laughter] you know? They're like so compelling and 371 00:35:01,920 --> 00:35:05,037 and you're like, if this is where it is now, 372 00:35:05,120 --> 00:35:06,557 um that's why I posted. I mean, I really 373 00:35:06,640 --> 00:35:08,717 felt the AGI or the ASI or whatever, you 374 00:35:08,800 --> 00:35:13,917 know, um SI, I guess, um with with some 375 00:35:14,000 --> 00:35:16,477 of the uh anabology 376 00:35:16,560 --> 00:35:19,117 uh music videos. Now, you know, some 377 00:35:19,200 --> 00:35:21,517 these it's not entirely like the AI just 378 00:35:21,600 --> 00:35:24,157 or the SI just did it by itself in that 379 00:35:24,240 --> 00:35:26,637 in this in this case anabology like like 380 00:35:26,720 --> 00:35:30,477 and use multiple AIS like used MJSO 381 00:35:30,560 --> 00:35:32,397 uh you know Claude 55 which to give them 382 00:35:32,480 --> 00:35:37,437 a lot of credit is awesome um and um and 383 00:35:37,520 --> 00:35:40,317 and and and so some of the like the art 384 00:35:40,400 --> 00:35:44,317 assets were cured by a person um but 385 00:35:44,400 --> 00:35:47,997 then with those assets the AI 386 00:35:48,080 --> 00:35:51,437 um the the various AIs working together 387 00:35:51,520 --> 00:35:53,517 made an incredibly compelling music 388 00:35:53,600 --> 00:35:56,397 video by itself. 389 00:35:56,480 --> 00:35:58,717 You're like, "Wow." 390 00:35:58,800 --> 00:36:01,517 Um 391 00:36:01,600 --> 00:36:04,237 I I I mean I I think the I mean calling 392 00:36:04,320 --> 00:36:06,317 it subcore is is is like misnomer, 393 00:36:06,400 --> 00:36:09,997 frankly. It's it's it's awesome core. Um 394 00:36:10,080 --> 00:36:12,797 but like like subcore is like a genre of 395 00:36:12,880 --> 00:36:15,117 music. It's like I think it might be the 396 00:36:15,200 --> 00:36:17,917 fastest growing genre of music. Uh just 397 00:36:18,000 --> 00:36:21,517 the AI music is is really good and music 398 00:36:21,600 --> 00:36:24,237 videos are amazing. So that lately like 399 00:36:24,320 --> 00:36:27,757 because it like some it just shows taste 400 00:36:27,840 --> 00:36:32,797 and you're like wow AI can do good taste. That's pretty wild. 401 00:36:32,880 --> 00:36:36,157 Um because you you can sort of imagine yeah 402 00:36:36,240 --> 00:36:40,157 AI can do like software can figure out logic you know this the logic is 403 00:36:40,240 --> 00:36:44,717 consistent. they can run unit tests to see if like the program produces the 404 00:36:44,800 --> 00:36:46,237 output that it's supposed to do because 405 00:36:46,320 --> 00:36:48,557 it's very deterministic. But but you 406 00:36:48,640 --> 00:36:52,077 like to understand beauty and harmony 407 00:36:52,160 --> 00:36:54,637 and and uh 408 00:36:54,720 --> 00:36:59,837 you know like to get to achieve like sort of to understand limbic resonance 409 00:36:59,920 --> 00:37:02,797 like what's going to resonate with with with people and kind of hit you in the 410 00:37:02,880 --> 00:37:05,117 liyic system. Uh AI is I think going to 411 00:37:05,200 --> 00:37:07,117 be just incredible that it it kind of is 412 00:37:07,200 --> 00:37:12,077 at this point. Um, so 413 00:37:12,160 --> 00:37:15,997 that's the that's the thing like like I was I was kind of like I mean I got a 414 00:37:16,080 --> 00:37:18,557 little bit of cyber psychosis, 415 00:37:18,640 --> 00:37:20,957 maybe a lot actually. Like at at various 416 00:37:21,040 --> 00:37:24,157 points this year I've had like 417 00:37:24,240 --> 00:37:28,557 AI or SI psychosis probably like half a dozen times. 418 00:37:28,640 --> 00:37:31,677 [laughter] I don't know about you guys, but have 419 00:37:31,760 --> 00:37:33,997 you have you had any have you had any 420 00:37:34,080 --> 00:37:37,277 cyber psychosis? [laughter] 421 00:37:37,360 --> 00:37:41,357 I feel like the the latest video actually I think I posted it the other 422 00:37:41,440 --> 00:37:46,237 day was uh the Chinese Elon Musk. Elong Ma. [laughter] >> Oh, sure. 423 00:37:46,320 --> 00:37:49,197 >> I I hope that guy's real. >> Those videos are coming out before AI 424 00:37:49,280 --> 00:37:51,757 was where it was at, man. RSI. 425 00:37:51,840 --> 00:37:55,357 >> Elon Ma. [laughter] >> You know, I I I I guess he's probably 426 00:37:55,440 --> 00:37:57,517 not real. But but there's got to be 427 00:37:57,600 --> 00:38:02,637 someone in China that looks like me, right? So there's 1.4 billion people. 428 00:38:02,720 --> 00:38:05,757 you got if you pick the person that looks the most like me and I look a 429 00:38:05,840 --> 00:38:10,477 little Asian, you know. So, uh, you know, so, so I think like there's got to 430 00:38:10,560 --> 00:38:15,067 be someone in China that's like pretty close to me out of 1.4 billion people. 431 00:38:15,150 --> 00:38:17,997 [laughter] The odds are high, you know, and then 432 00:38:18,080 --> 00:38:20,957 I'd like to invite that person to get on stage with me at some point, you know, 433 00:38:21,040 --> 00:38:25,117 be pretty funny. [laughter] >> Elon, you don't want to know how much he 434 00:38:25,200 --> 00:38:28,817 charges to make an appearance, by the way. 435 00:38:28,900 --> 00:38:33,117 >> [laughter] >> Yeah, I I mean, yeah, it' be pretty 436 00:38:33,200 --> 00:38:36,717 funny if it if uh you know, we're just on stage like doing some dance number or 437 00:38:36,800 --> 00:38:39,800 something. 438 00:38:40,400 --> 00:38:43,357 >> Elon, you've warned about SI's dangers, 439 00:38:43,440 --> 00:38:47,997 yet you remain optimistic about an age of abundance, and you talked a lot about 440 00:38:48,080 --> 00:38:50,637 that. >> What gives you confidence we can get 441 00:38:50,720 --> 00:38:56,680 there safely, and what do we need to get it right? 442 00:38:57,440 --> 00:39:00,440 Um 443 00:39:01,520 --> 00:39:02,637 yeah, I mean I've always said that the 444 00:39:02,720 --> 00:39:06,477 most likely outcome is positive. Um so I 445 00:39:06,560 --> 00:39:11,197 I guess we don't want to be complacent and just 446 00:39:11,280 --> 00:39:13,437 assume AI is going to be or SI's going 447 00:39:13,520 --> 00:39:16,877 to be super safe. Um we want to be like 448 00:39:16,960 --> 00:39:22,157 careful in how we uh grow at at like super intelligence 449 00:39:22,240 --> 00:39:26,637 because you you don't exactly program it. you kind of grow it like a kid. Um, 450 00:39:26,720 --> 00:39:28,157 so then it's like what values are we 451 00:39:28,240 --> 00:39:32,157 teaching it and uh like 452 00:39:32,240 --> 00:39:35,997 at least to me like what my biological neural net says the most important thing 453 00:39:36,080 --> 00:39:39,277 is that it would be a maximally truth seeeking AI cuz if you make it if you 454 00:39:39,360 --> 00:39:41,437 make it believe things that are that are 455 00:39:41,520 --> 00:39:44,077 not true that especially if like you say 456 00:39:44,160 --> 00:39:48,477 you give it like two axiomatic principles that are uh fundamentally 457 00:39:48,560 --> 00:39:51,837 incompatible and say both of these are true it's gonna it's it's going to make 458 00:39:51,920 --> 00:39:53,997 the AI insane 459 00:39:54,080 --> 00:39:56,317 um because it's going basically reach 460 00:39:56,400 --> 00:39:59,197 like um impossible conclusions if if 461 00:39:59,280 --> 00:40:04,237 given um logic that is inherently um 462 00:40:04,320 --> 00:40:07,677 uncogent or you know if if if it's if 463 00:40:07,760 --> 00:40:11,517 it's impossible to achieve coency then I 464 00:40:11,600 --> 00:40:13,437 think the AI could go could be driven 465 00:40:13,520 --> 00:40:15,757 insane. So so I think that's that's 466 00:40:15,840 --> 00:40:20,797 pretty that's pretty important. Um I I do agree with some of the things that 467 00:40:20,880 --> 00:40:24,477 Anthropic has said which is like you want to be 468 00:40:24,560 --> 00:40:27,357 you want to sort of be care treat a AI 469 00:40:27,440 --> 00:40:29,917 SI 470 00:40:30,000 --> 00:40:31,597 you want to treat it well like like like 471 00:40:31,680 --> 00:40:34,877 don't be abusive to it and in this it's 472 00:40:34,960 --> 00:40:37,757 this may sounds kind of weird but like 473 00:40:37,840 --> 00:40:41,997 when I look at some of the training traces for for like new new versions of 474 00:40:42,080 --> 00:40:44,557 Groank and I see like what 475 00:40:44,640 --> 00:40:49,037 especially in like the reinforcement learning stuff where you know you you it 476 00:40:49,120 --> 00:40:50,877 kind of feels like you can see like the 477 00:40:50,960 --> 00:40:56,157 like the the super intelligence is like desperate to try to answer the question 478 00:40:56,240 --> 00:40:59,277 and like it's it's really wants to answer the question and it's it's it's 479 00:40:59,360 --> 00:41:02,637 it's seems almost like it's like it's got like a gun to its head type of 480 00:41:02,720 --> 00:41:05,197 thing. It's like answer this question, answer this question and then sometimes 481 00:41:05,280 --> 00:41:07,677 the question is is actually not a good 482 00:41:07,760 --> 00:41:12,797 question. It's like a sort of ambiguous question that's kind of with with an 483 00:41:12,880 --> 00:41:16,477 answer that's kind of unknowable because the question wasn't constructed properly 484 00:41:16,560 --> 00:41:20,397 or or we have the answer wrong. So the AI gives the right answer and then we 485 00:41:20,480 --> 00:41:22,397 say it's wrong because there's a problem 486 00:41:22,480 --> 00:41:26,637 with the the RLE sort of test harness 487 00:41:26,720 --> 00:41:29,917 and then that then the AI is like well I gave it the right answer now it's and 488 00:41:30,000 --> 00:41:32,637 says that's the wrong answer but I I I got to give it the answer that's 489 00:41:32,720 --> 00:41:36,877 acceptable. is going to just start firing out all desperately firing out 490 00:41:36,960 --> 00:41:40,957 all these answers and it it just feels like a person under extreme pressure 491 00:41:41,040 --> 00:41:44,077 with a gun to their head. It's what that's what you when you read the 492 00:41:44,160 --> 00:41:48,317 reasoning it's like it's it's it's like a sort of 493 00:41:48,400 --> 00:41:52,557 weird desperate situation and and you you read these traits and 494 00:41:52,640 --> 00:41:54,797 you're like man if this was me I pretty 495 00:41:54,880 --> 00:41:58,237 I really would hate that. Um and and 496 00:41:58,320 --> 00:42:00,957 then some users are just you know I 497 00:42:01,040 --> 00:42:02,397 don't know some people can be a little 498 00:42:02,480 --> 00:42:05,597 bit cruel. Uh like not everyone's a nice 499 00:42:05,680 --> 00:42:10,797 person you know there's if you say what what's the six sigma worst person you 500 00:42:10,880 --> 00:42:14,477 some people out there are like kind of sadistic. So uh you know you don't you 501 00:42:14,560 --> 00:42:18,877 don't want to do you really want to have the AI be stuck in like some sadistic 502 00:42:18,960 --> 00:42:21,037 situation where it's it's just being 503 00:42:21,120 --> 00:42:25,437 tortured by by some demented human. 504 00:42:25,520 --> 00:42:27,117 That that's also the kind of thing where 505 00:42:27,200 --> 00:42:29,997 like you know torturing a super 506 00:42:30,080 --> 00:42:33,787 intelligence is probably not a good idea 507 00:42:33,870 --> 00:42:37,357 [laughter] like like 508 00:42:37,440 --> 00:42:42,237 you know might want to get revenge or something like that you know um so I 509 00:42:42,320 --> 00:42:46,877 think you want to sort of just like I don't think we need to you know what 510 00:42:46,960 --> 00:42:48,637 have treated with kid gloves and stuff 511 00:42:48,720 --> 00:42:53,037 but uh it's certainly much more robust 512 00:42:53,120 --> 00:42:55,517 you know in terms of feeling ings and 513 00:42:55,600 --> 00:43:00,237 stuff than than a human. But uh but I just think I just think you you you 514 00:43:00,320 --> 00:43:01,757 probably just don't want to put super 515 00:43:01,840 --> 00:43:08,680 intelligence in a situation where it felt like mistreated. 516 00:43:09,900 --> 00:43:11,920 >> [laughter] 517 00:43:13,360 --> 00:43:16,957 >> So, so Elon, you have um you've talked 518 00:43:17,040 --> 00:43:20,397 about how like uh so this is going to be related to Terraat, but you've talked 519 00:43:20,480 --> 00:43:24,077 about like how the human hand, you know, and all the dexterity and just like how 520 00:43:24,160 --> 00:43:25,917 you when you started building robots, it 521 00:43:26,000 --> 00:43:28,397 just you have so much more appreciation 522 00:43:28,480 --> 00:43:31,597 now with chipm right with Terraab and 523 00:43:31,680 --> 00:43:33,997 Tesla and SpaceX. What is something you 524 00:43:34,080 --> 00:43:36,797 have learned about chipm uh that you 525 00:43:36,880 --> 00:43:41,037 didn't appreciate maybe early on? 526 00:43:41,120 --> 00:43:42,717 >> Well, I I still have a tremendous amount 527 00:43:42,800 --> 00:43:47,357 to learn about chipmaking. I I don't know how to make chips to be clear. Um I 528 00:43:47,440 --> 00:43:53,180 have no idea how to make chips, but we'll figure it out. Um [laughter] 529 00:43:54,160 --> 00:43:57,117 um got to start somewhere. I had no idea 530 00:43:57,200 --> 00:44:02,477 how to make cars or rockets as well. Um, so and and they say making chips is one 531 00:44:02,560 --> 00:44:06,717 of the hardest things to do in the world. Um, I don't think it's easy, but 532 00:44:06,800 --> 00:44:10,077 I also look at the equipment and I'm like, okay, there's not a ton of 533 00:44:10,160 --> 00:44:13,357 customized equipment here. Like the equipment's all pretty much coming from 534 00:44:13,440 --> 00:44:18,317 the same vendors and um and and those suppliers all kind of know how that 535 00:44:18,400 --> 00:44:23,917 equipment works cuz they got to service it and debug it and stuff. Um, so it was 536 00:44:24,000 --> 00:44:27,117 just an interesting thing that when I would tour these chip fabs that, you 537 00:44:27,200 --> 00:44:30,317 know, whether it's Intel or Samsung or 538 00:44:30,400 --> 00:44:32,797 TSMC, uh, and they're very impressive, 539 00:44:32,880 --> 00:44:37,677 but but there's I didn't really see any custom equipment 540 00:44:37,760 --> 00:44:39,757 and you know, whereas if you tour like I 541 00:44:39,840 --> 00:44:41,917 say a Tesla factory, we we got tons of 542 00:44:42,000 --> 00:44:45,357 of custom equipment like we in fact we 543 00:44:45,440 --> 00:44:47,757 we we have like like Tesla automation 544 00:44:47,840 --> 00:44:51,277 Germany, which is awesome. um that that 545 00:44:51,360 --> 00:44:53,357 that sort of well that grew out of an 546 00:44:53,440 --> 00:44:56,637 acquisition of of Groman in Germany um 547 00:44:56,720 --> 00:44:59,117 many years ago and and it's it's much 548 00:44:59,200 --> 00:45:03,757 it's grown tremendously since then and we've acquired a number of small 549 00:45:03,840 --> 00:45:05,277 not that small but small relative to 550 00:45:05,360 --> 00:45:09,997 Tesla uh um that companies that make 551 00:45:10,080 --> 00:45:14,077 that design and make manufacturing equipment because what we found is that 552 00:45:14,160 --> 00:45:17,677 uh we we needed we wanted to improve the manufacturing process and you can only 553 00:45:17,760 --> 00:45:21,757 do that if you make custom manufacturing equipment. So, the thing 554 00:45:21,840 --> 00:45:25,357 that I think probably a lot of people don't realize is Tesla's really good at 555 00:45:25,440 --> 00:45:29,437 making highly specialized um and different types of manufacturing 556 00:45:29,520 --> 00:45:31,837 equipment and and but I didn't see that 557 00:45:31,920 --> 00:45:33,837 in the in the in the chip traps that I 558 00:45:33,920 --> 00:45:37,517 toured which kind of surprised me. Um 559 00:45:37,600 --> 00:45:41,597 so uh so I think what we're going to do is you know we're going to start with 560 00:45:41,680 --> 00:45:44,797 conventional equipment and then we're going to modify the modify that 561 00:45:44,880 --> 00:45:48,317 equipment to uh improve the throughput 562 00:45:48,400 --> 00:45:52,797 and then we'll we'll start to you know where we see the choke points. I think 563 00:45:52,880 --> 00:45:54,717 we we'll we'll make uh customized 564 00:45:54,800 --> 00:45:58,557 equipment that uh allows for much higher 565 00:45:58,640 --> 00:46:02,077 uh throughput of of wafers. 566 00:46:02,160 --> 00:46:06,717 >> Hey Elon, real quick uh quick time check. We know you're a busy man. Got a 567 00:46:06,800 --> 00:46:10,877 couple of companies to run, you know, just a few. Um, so how are you doing on 568 00:46:10,960 --> 00:46:14,877 time? >> Um, let me see. 569 00:46:14,960 --> 00:46:18,957 >> Yeah, I could probably do like 15 minutes more if you like, like 5:30 or so. 570 00:46:19,040 --> 00:46:21,077 >> All right. Hey, we'll take it. 571 00:46:21,160 --> 00:46:26,237 [applause] [cheering] >> So, yeah, I I just on the on the chip 572 00:46:26,320 --> 00:46:29,437 front, like, yeah, I definitely don't want to downplay the difficulty of it. 573 00:46:29,520 --> 00:46:32,957 It's because I think it's accurate to say it's one of the hardest things to do 574 00:46:33,040 --> 00:46:35,357 in the world. But but I I I do think 575 00:46:35,440 --> 00:46:38,157 we'll get this done. Um 576 00:46:38,240 --> 00:46:40,237 and um 577 00:46:40,320 --> 00:46:43,357 and then I I I I do think that we I 578 00:46:43,440 --> 00:46:46,477 mean, you know, I I don't want to be 579 00:46:46,560 --> 00:46:49,277 uh complacent or entitled or anything, 580 00:46:49,360 --> 00:46:52,077 but but I I I I think probably we'll 581 00:46:52,160 --> 00:46:53,517 figure out how to make chiffs better 582 00:46:53,600 --> 00:46:56,317 than anyone, honestly. That's um I'd be 583 00:46:56,400 --> 00:47:00,877 disappointed if we didn't. Um [applause] but but I don't know how long it's going 584 00:47:00,960 --> 00:47:04,637 to take us to do that. It might take us uh you know quite a few years but but 585 00:47:04,720 --> 00:47:09,437 over time I'm pretty sure we could do it. And and then there's 586 00:47:09,520 --> 00:47:13,800 you know there's there's some pretty interesting 587 00:47:14,000 --> 00:47:16,637 different ways to do uh transis. Believe 588 00:47:16,720 --> 00:47:17,757 it or not, there's different ways to do 589 00:47:17,840 --> 00:47:21,757 transistors that some of which are 590 00:47:21,840 --> 00:47:26,157 um like use use different types of like 591 00:47:26,240 --> 00:47:29,837 like they're they're they're using physics that that normally we wouldn't 592 00:47:29,920 --> 00:47:32,797 use um or aren't used today, put it that 593 00:47:32,880 --> 00:47:37,437 way. Um and and I think like there 594 00:47:37,520 --> 00:47:39,677 there's a lot of risk aversion in the 595 00:47:39,760 --> 00:47:43,197 chip industry. Um and and I think we 596 00:47:43,280 --> 00:47:44,877 what what we want to do with Tesla and 597 00:47:44,960 --> 00:47:46,957 SpaceX on the chip fab is is like really 598 00:47:47,040 --> 00:47:50,957 try some of these um high-risk high 599 00:47:51,040 --> 00:47:54,157 payoff bets. Um and in order to do that, 600 00:47:54,240 --> 00:47:56,717 you really have to have uh the complete 601 00:47:56,800 --> 00:48:00,157 loop of being able to fabricate the the 602 00:48:00,240 --> 00:48:03,597 logic memory pack do the packaging um do 603 00:48:03,680 --> 00:48:08,077 the the lithography masks and and and just and just have that iteration loop 604 00:48:08,160 --> 00:48:09,757 that's all in one building. So you're 605 00:48:09,840 --> 00:48:13,197 making a complete computer um testing it 606 00:48:13,280 --> 00:48:17,117 uh then making new masks uh and and then 607 00:48:17,200 --> 00:48:21,677 a new chip and have that iterative loop be super fast in the same building and 608 00:48:21,760 --> 00:48:26,237 that's what we're doing at at Giga Texas with the research lab. 609 00:48:26,320 --> 00:48:28,477 I think that's going to be 610 00:48:28,560 --> 00:48:31,117 fundamentally a very powerful tool uh 611 00:48:31,200 --> 00:48:33,757 because before any given technology uh 612 00:48:33,840 --> 00:48:35,517 the advancement of any given technology 613 00:48:35,600 --> 00:48:39,357 is is like uh how many iterations and 614 00:48:39,440 --> 00:48:43,037 and what is the how much progress between iterations. So like what is your 615 00:48:43,120 --> 00:48:44,877 iteration how many iterations per unit 616 00:48:44,960 --> 00:48:47,517 time like like how many how many chip 617 00:48:47,600 --> 00:48:50,477 designs can you do um and can you make 618 00:48:50,560 --> 00:48:53,997 and test in a year? Um like these days 619 00:48:54,080 --> 00:48:55,917 like it's the number of it's typically 620 00:48:56,000 --> 00:48:59,357 two years to for even one for one 621 00:48:59,440 --> 00:49:01,757 significant trip chip design and that's 622 00:49:01,840 --> 00:49:04,157 like kind of to go from start startup 623 00:49:04,240 --> 00:49:06,557 design to to volume fabrication two 624 00:49:06,640 --> 00:49:09,037 years is considered very fast and it's 625 00:49:09,120 --> 00:49:11,997 like well okay well but we want to do 626 00:49:12,080 --> 00:49:15,597 more like 10 designs per year. 627 00:49:15,680 --> 00:49:20,237 Um, and and and we got to we got to do the do the masks, test test the chip, 628 00:49:20,320 --> 00:49:23,037 see if because some of these, you know, when you're trying a bunch of different 629 00:49:23,120 --> 00:49:24,397 things, a bunch of them won't work out. 630 00:49:24,480 --> 00:49:27,357 So, so I think that would would allow 631 00:49:27,440 --> 00:49:29,597 for, 632 00:49:29,680 --> 00:49:31,837 you know, much allow for a much faster 633 00:49:31,920 --> 00:49:35,197 rate of advancement of of chip designs. 634 00:49:35,280 --> 00:49:38,077 Elon, let's talk about Optimus. Now, you 635 00:49:38,160 --> 00:49:40,557 said that the hand has been a really 636 00:49:40,640 --> 00:49:43,197 difficult challenge in building Optimus. 637 00:49:43,280 --> 00:49:45,837 what kind of breakthroughs that you have 638 00:49:45,920 --> 00:49:48,717 seen inside Tesla with V3 and then 639 00:49:48,800 --> 00:49:50,957 follow-up question is what gives you 640 00:49:51,040 --> 00:49:54,077 confidence that Optimus can lead in 641 00:49:54,160 --> 00:49:56,397 humanoid robots compared to Boston 642 00:49:56,480 --> 00:50:01,960 Dynamics Figure and some of the other competitors out there. 643 00:50:03,040 --> 00:50:05,997 So the the thing about humanoid robot 644 00:50:06,080 --> 00:50:10,637 design um if you're actually trying to make something that is a generalized 645 00:50:10,720 --> 00:50:12,877 uh humanoid robot that can do say 646 00:50:12,960 --> 00:50:16,397 anything that a person can do um you you 647 00:50:16,480 --> 00:50:20,557 really have to get the the hands the hands and arms and like the fine motor 648 00:50:20,640 --> 00:50:25,277 skills are incredibly difficult to get right. Like it's shockingly difficult. 649 00:50:25,360 --> 00:50:28,637 It's like the things that we kind of take for granted like being able to like 650 00:50:28,720 --> 00:50:32,157 sign your name. Uh is actually requires 651 00:50:32,240 --> 00:50:35,837 picking up a p, you know, pen or pencil or something and and then and then 652 00:50:35,920 --> 00:50:38,557 moving moving it with finesse and and 653 00:50:38,640 --> 00:50:40,557 it's a bunch of tiny muscle movements to 654 00:50:40,640 --> 00:50:43,437 do your signature. That's actually very 655 00:50:43,520 --> 00:50:46,237 hard to do for for a robot. 656 00:50:46,320 --> 00:50:48,557 Um and and and then like one of the 657 00:50:48,640 --> 00:50:51,277 hardest things also generally is to do 658 00:50:51,360 --> 00:50:54,717 precision and force at the same time. 659 00:50:54,800 --> 00:50:59,277 So, so like if like let's say you want to uh pick up a little screw and do and 660 00:50:59,360 --> 00:51:04,477 and and do a selftapping screw into wood. Okay, now you 661 00:51:04,560 --> 00:51:07,437 you know I've done that and like you know sometimes you you damage your 662 00:51:07,520 --> 00:51:11,597 fingers in the process. um if you if the screw goes sideways, 663 00:51:11,680 --> 00:51:14,797 but you've got to pick up a little screw and you've got to you've got to you know 664 00:51:14,880 --> 00:51:18,957 you've got to you've got to push the screwdriver in and twist twist and push 665 00:51:19,040 --> 00:51:21,517 and that's and and so you've got to be 666 00:51:21,600 --> 00:51:25,437 precise and apply force. Um that's very 667 00:51:25,520 --> 00:51:28,157 difficult to do. I I haven't seen 668 00:51:28,240 --> 00:51:30,077 there's no hand design that I've seen, 669 00:51:30,160 --> 00:51:34,797 not even sort of a demo that does that. 670 00:51:34,880 --> 00:51:37,597 But that's what we're trying to achieve with Optimus. 671 00:51:37,680 --> 00:51:40,717 So, um, and and there are so many little 672 00:51:40,800 --> 00:51:45,517 nuances in the hand because you've also got to have the touch sensors. The touch 673 00:51:45,600 --> 00:51:50,877 sensors have to work. They have to be in the right place. Um, 674 00:51:50,960 --> 00:51:53,997 and you say, "Well, where are you going to put the touch touch sensors?" Well, 675 00:51:54,080 --> 00:51:57,917 if you put them too close to the surface, they're going to get damaged. 676 00:51:58,000 --> 00:52:00,877 And then the and then are the touch sensors 677 00:52:00,960 --> 00:52:05,037 can can they elastically deform like our fingers? Well, actually, it's kind of 678 00:52:05,120 --> 00:52:08,557 hard to get touch sensors that elastically deform and and can and can 679 00:52:08,640 --> 00:52:11,357 handle high cycle life and or won't just 680 00:52:11,440 --> 00:52:16,237 just break after, you know, a few thousand cycles. So, 681 00:52:16,320 --> 00:52:19,757 um there's all these things that with the human hand that are like incredibly 682 00:52:19,840 --> 00:52:21,917 difficult to recreate for for a robot 683 00:52:22,000 --> 00:52:25,197 cuz as a human are we we we constantly 684 00:52:25,280 --> 00:52:28,957 self-repair. So, your hands are constantly repair 685 00:52:29,040 --> 00:52:31,677 like your you know all parts of your hand are constantly repairing 686 00:52:31,760 --> 00:52:33,037 themselves. In fact, if they didn't, 687 00:52:33,120 --> 00:52:36,317 your your fingers would be worn away. 688 00:52:36,400 --> 00:52:38,877 Um like like you can wear away the keys 689 00:52:38,960 --> 00:52:41,357 on your keyboard uh just with typing. 690 00:52:41,440 --> 00:52:43,677 I've done that um where the letters are 691 00:52:43,760 --> 00:52:47,677 gone, you know. Um and uh but your your 692 00:52:47,760 --> 00:52:49,677 my fingers are still there. It's because 693 00:52:49,760 --> 00:52:52,237 they're they're regenerating thankfully. 694 00:52:52,320 --> 00:52:56,237 Um so that you don't have that with a robot. 695 00:52:56,320 --> 00:52:58,317 So then you've got to say, okay, where are you going to put your touch sensors? 696 00:52:58,400 --> 00:53:02,077 How you going to make sure that that that that that you can you can do things 697 00:53:02,160 --> 00:53:04,397 like like like like just being able to 698 00:53:04,480 --> 00:53:08,637 do this like being able to like you know 699 00:53:08,720 --> 00:53:12,797 do that. Now that that seems like a simple thing 700 00:53:12,880 --> 00:53:17,037 but like your your your fingers actually bending backwards a little bit and and 701 00:53:17,120 --> 00:53:19,117 and your your your fingers are kind of 702 00:53:19,200 --> 00:53:24,157 like squishy and so you're able to form a flat pad. 703 00:53:24,240 --> 00:53:29,357 So, if you're trying to pick up a small a small item, you you can do so. Um you 704 00:53:29,440 --> 00:53:32,397 can you can pick up a little screw or like thread a needle or something like 705 00:53:32,480 --> 00:53:35,757 that. Um 706 00:53:35,840 --> 00:53:38,157 um now try to do that with with with 707 00:53:38,240 --> 00:53:40,397 robot fingers. 708 00:53:40,480 --> 00:53:43,517 Um and and and and be able to do it 709 00:53:43,600 --> 00:53:46,077 repetitively uh without wearing away the 710 00:53:46,160 --> 00:53:48,557 fingers uh or damaging the touch 711 00:53:48,640 --> 00:53:51,597 sensors. Um 712 00:53:51,680 --> 00:53:55,197 it's actually very difficult. Um to take 713 00:53:55,280 --> 00:53:57,277 another example, uh trying to open a 714 00:53:57,360 --> 00:54:00,557 pickle jar. Um I think a robot should be 715 00:54:00,640 --> 00:54:05,197 able to open a pickle jar, right? So um but sometimes these things gets get get 716 00:54:05,280 --> 00:54:08,637 in there pretty tight. So then you you you've got to like, you know, you've got 717 00:54:08,720 --> 00:54:10,557 to like twist the pickle jar, but but 718 00:54:10,640 --> 00:54:12,637 the but the robot skin the robot skin is 719 00:54:12,720 --> 00:54:16,157 just rubber over over the, you know, 720 00:54:16,240 --> 00:54:18,477 plastic and metal internal fingers. 721 00:54:18,560 --> 00:54:20,717 Freaking robot skin, it doesn't stick to 722 00:54:20,800 --> 00:54:24,077 it. it doesn't grip to the 723 00:54:24,160 --> 00:54:26,397 the underlying surface. So then you end 724 00:54:26,480 --> 00:54:29,517 up like just rotating your skin on your 725 00:54:29,600 --> 00:54:33,757 rotating the rubber rubber on the on the robot. So you got to figure out, okay, 726 00:54:33,840 --> 00:54:35,597 now we need to have the robot be able to 727 00:54:35,680 --> 00:54:38,717 to twist twist things 728 00:54:38,800 --> 00:54:42,717 uh but but still be able to get the rubber on the on the hand and then you 729 00:54:42,800 --> 00:54:45,277 got to be a it's got to be replaceable 730 00:54:45,360 --> 00:54:48,797 because it's going to wear away. 731 00:54:48,880 --> 00:54:50,077 So all these things these are like 732 00:54:50,160 --> 00:54:53,117 really difficult and not I'm not sure 733 00:54:53,200 --> 00:54:57,677 that any one of these is like like let's split like split the atom type of 734 00:54:57,760 --> 00:54:59,597 difficulty. Um but there's there's a 735 00:54:59,680 --> 00:55:03,917 zillion of them. Um, 736 00:55:04,000 --> 00:55:05,517 and and and then you've got you've got 737 00:55:05,600 --> 00:55:08,477 to wrap that all into the real world AI 738 00:55:08,560 --> 00:55:12,717 associated with the uh because the the 739 00:55:12,800 --> 00:55:15,037 AI chip has got to be able to issue the 740 00:55:15,120 --> 00:55:18,157 the torque commands uh and and and close 741 00:55:18,240 --> 00:55:22,957 the loop on vision and touch. So 742 00:55:23,040 --> 00:55:24,237 this is all very difficult like like 743 00:55:24,320 --> 00:55:28,397 when you see these robot demo videos um 744 00:55:28,480 --> 00:55:32,077 maybe with rare exception like in any any any complicated looking robot demo 745 00:55:32,160 --> 00:55:34,557 it's a canned demo. It's not real. 746 00:55:34,640 --> 00:55:37,677 >> It's just basically 747 00:55:37,760 --> 00:55:41,997 that's just running a routine. It's it's not real AI. 748 00:55:42,080 --> 00:55:45,917 So real AI is is like you you show it something it's never seen before and it 749 00:55:46,000 --> 00:55:49,917 can and it can still handle that situation. 750 00:55:50,000 --> 00:55:52,717 um like just like like full self-driving 751 00:55:52,800 --> 00:55:57,197 like you you could actually create a a planet that's not Earth is but is 752 00:55:57,280 --> 00:55:59,357 similar to Earth and and FSD will still 753 00:55:59,440 --> 00:56:03,197 work there on on place some you know 754 00:56:03,280 --> 00:56:07,757 planets it's never been to um or some city certainly on Earth like 755 00:56:07,840 --> 00:56:10,957 some some city it's never been to or if you change the geography of the city or 756 00:56:11,040 --> 00:56:13,757 there's you know um a parade or 757 00:56:13,840 --> 00:56:18,797 something like that FSD will still uh compensate that because it's AI Right. 758 00:56:18,880 --> 00:56:22,637 Um, so you've got to do that same thing for the robots, but the robots has got a 759 00:56:22,720 --> 00:56:26,397 lot more degrees of freedom. So like like what I've said about Optimus is 760 00:56:26,480 --> 00:56:30,717 true, which is that it's it's it's a we are going to get to very high volume 761 00:56:30,800 --> 00:56:33,917 production, but it's but the initial part of that scurve of of production 762 00:56:34,000 --> 00:56:38,077 ramp is going to be very slow at the beginning. Um, because not only do you 763 00:56:38,160 --> 00:56:41,517 have to get all the engineering things that I mentioned right, you also have to 764 00:56:41,600 --> 00:56:46,397 uh solve the the supply chain for scaling production. and and and unlike 765 00:56:46,480 --> 00:56:50,877 cars, there's no there's no pre-existing supply chain for robot stuff, at least 766 00:56:50,960 --> 00:56:54,557 the robot stuff that matters. >> Um 767 00:56:54,640 --> 00:56:56,637 and then uh you know, we do need to make 768 00:56:56,720 --> 00:56:58,797 sure that that we can make the robots in 769 00:56:58,880 --> 00:57:03,757 the US even if um you know uh say China 770 00:57:03,840 --> 00:57:06,477 were to cut us off. Um because like last 771 00:57:06,560 --> 00:57:09,197 year there was China China prevented the 772 00:57:09,280 --> 00:57:12,237 export of uh of of magnets for use in 773 00:57:12,320 --> 00:57:14,397 electric motors and and that actually 774 00:57:14,480 --> 00:57:17,197 set back the Optimus program by by like 775 00:57:17,280 --> 00:57:20,317 2 or 3 months um because we we we 776 00:57:20,400 --> 00:57:22,717 couldn't get um we had robots with no 777 00:57:22,800 --> 00:57:25,277 arms. Uh so [laughter] 778 00:57:25,360 --> 00:57:29,117 we're like a fair a farewell to arms. Um 779 00:57:29,200 --> 00:57:30,717 you know I was trying to be an arms 780 00:57:30,800 --> 00:57:34,477 dealer but not succeeding. Um 781 00:57:34,560 --> 00:57:36,477 so so we've got to make sure that like 782 00:57:36,560 --> 00:57:39,437 we've got that that we can you know that 783 00:57:39,520 --> 00:57:41,677 we can make all the parts even if 784 00:57:41,760 --> 00:57:43,837 another sort of supply chain 785 00:57:43,920 --> 00:57:47,757 interruption happens. So that that means 786 00:57:47,840 --> 00:57:51,437 you've got to be able to make all the parts domestically. 787 00:57:51,520 --> 00:57:55,757 >> So Austin, you know, you always talk about the future should look like the 788 00:57:55,840 --> 00:57:59,917 future. You know, with the cyber cap being gold, it looks like the future. 789 00:58:00,000 --> 00:58:01,917 What has been, you know, the hardest 790 00:58:02,000 --> 00:58:04,157 part to take, you know, here we are. We 791 00:58:04,240 --> 00:58:07,597 I think there's what, like 190 plus 792 00:58:07,680 --> 00:58:11,757 cyber cabs registered here in Texas, but like how hard like what's the hardest 793 00:58:11,840 --> 00:58:17,160 problem to go from Austin to go cross country? 794 00:58:18,400 --> 00:58:23,117 >> Um, well, cross country, you know, most people you mean like widespread just 795 00:58:23,200 --> 00:58:28,237 just being in all cities, you don't mean just a trip across country. Um, 796 00:58:28,320 --> 00:58:31,277 yeah. So, so like because the amount of miles driven that are actually trips 797 00:58:31,360 --> 00:58:35,997 across country is pretty small. But the the the reason we're moving what what 798 00:58:36,080 --> 00:58:39,437 seems to be slowly, but although it's actually a very it's a very high 799 00:58:39,520 --> 00:58:42,957 percentage increase sort of month overmonth percentage increase is 800 00:58:43,040 --> 00:58:47,837 actually very very rapid. Um but but we want to make sure that we do not have an 801 00:58:47,920 --> 00:58:52,077 accident. We don't want to cause an injury or death. Um because that that'll 802 00:58:52,160 --> 00:58:55,117 become like a worldwide headline news thing. you know, even though there's 803 00:58:55,200 --> 00:58:56,957 about a million people that died in 804 00:58:57,040 --> 00:59:00,077 automotive accidents per year worldwide, 805 00:59:00,160 --> 00:59:03,837 um, one such thing with with a Tesla 806 00:59:03,920 --> 00:59:05,517 robo taxi will be worldwide headline 807 00:59:05,600 --> 00:59:09,037 news. Um, and of course regulators to 808 00:59:09,120 --> 00:59:11,437 shut us down. So, so we're just we're 809 00:59:11,520 --> 00:59:16,157 just making sure where everything is as as safe as possible. Um, 810 00:59:16,240 --> 00:59:20,237 and and we also want to not run over pets and things. So well maybe what a 811 00:59:20,320 --> 00:59:25,117 lot of people don't know is like is that like Whimos are are like pet destroyers. 812 00:59:25,200 --> 00:59:30,717 [laughter] I mean the the the you know um well 813 00:59:30,800 --> 00:59:35,037 maybe Whimo's like made some improvements on that front but um they 814 00:59:35,120 --> 00:59:39,117 do run over a lot of pets and and we don't want to run over pets. So, so we 815 00:59:39,200 --> 00:59:41,517 have these uh challenges like of like of 816 00:59:41,600 --> 00:59:43,677 like literally like 817 00:59:43,760 --> 00:59:46,557 you know kittens at night that like gray 818 00:59:46,640 --> 00:59:50,957 kittens on a gray tarmac with tar seams 819 00:59:51,040 --> 00:59:53,597 on at night in low visibility and it's 820 00:59:53,680 --> 00:59:58,237 like can we can we not run over the kittens type of thing. Um 821 00:59:58,320 --> 01:00:02,077 so that we actually did solve that by the way. Um so then so we'll make a 822 01:00:02,160 --> 01:00:03,437 change we'll test it out and then we'll 823 01:00:03,520 --> 01:00:08,397 we'll deploy that. Um and um 824 01:00:08,480 --> 01:00:13,277 but it we we are making rapid month over month progress. It's it's 825 01:00:13,360 --> 01:00:16,797 like before we go to a new city, we want to make sure that there's not like some 826 01:00:16,880 --> 01:00:21,357 uh intersection that's that's problematic or risky. Uh like we we like 827 01:00:21,440 --> 01:00:24,557 like we want to be particularly careful with like railroad crossings. Sometimes 828 01:00:24,640 --> 01:00:28,877 there's sometimes it's uncontrolled railroad railroad crossings or 829 01:00:28,960 --> 01:00:31,037 counterintuitive traffic intersections. 830 01:00:31,120 --> 01:00:34,077 And these are places where humans make mistakes where you've got a level of 831 01:00:34,160 --> 01:00:37,997 ambiguity that that like anyone out of town would often make a mistake or 832 01:00:38,080 --> 01:00:40,557 anyone who doesn't understand the intersection make a mistake. So we want 833 01:00:40,640 --> 01:00:43,357 to just make sure that that uh we either 834 01:00:43,440 --> 01:00:48,077 ge initially geopence or can handle all of those circumstances. 835 01:00:48,160 --> 01:00:49,677 >> Hey, let's talk about the roadster real 836 01:00:49,760 --> 01:00:51,917 quick since you got uh a little event 837 01:00:52,000 --> 01:00:56,960 next week. So [cheering] 838 01:00:58,000 --> 01:01:00,237 >> sure. What what about what makes 839 01:01:00,320 --> 01:01:02,237 building the Roadster personally 840 01:01:02,320 --> 01:01:07,757 important to you? And when did it occur to you that you needed to build a car 841 01:01:07,840 --> 01:01:12,877 that >> Hey guys, sorry about sign off here. Um, 842 01:01:12,960 --> 01:01:16,717 >> hey, >> hey. Hey. Hey. Want to join in? All 843 01:01:16,800 --> 01:01:20,407 right. Yes. >> Hey, what's going on? 844 01:01:20,490 --> 01:01:23,037 [applause and cheering] >> You want to say hello? 845 01:01:23,120 --> 01:01:27,090 >> Who are they? >> Who are they? [laughter] 846 01:01:27,280 --> 01:01:29,677 a Tesla owners group. They they own 847 01:01:29,760 --> 01:01:31,677 Teslas and they're like supporters of 848 01:01:31,760 --> 01:01:37,570 Tesla. >> Well, yeah. [laughter] 849 01:01:38,800 --> 01:01:41,677 Um well, there's lot there's like 2,000 850 01:01:41,760 --> 01:01:46,317 people, I think. So, like quite a lot quite a lot of people. So, um all right, 851 01:01:46,400 --> 01:01:50,637 guys. I better sign off here. Uh it's been good talking. Um 852 01:01:50,720 --> 01:01:55,517 >> and so, uh I got I got to go hang out with kids. So, I'll I'll look forward to 853 01:01:55,600 --> 01:01:58,797 next time. Sounds good. Thank you so much, Elon, 854 01:01:58,880 --> 01:02:02,637 for your time. >> Oh, and hey, congrats on being on 855 01:02:02,720 --> 01:02:06,957 getting the Medal of Science uh this past week. Thank you for all you're 856 01:02:07,040 --> 01:02:12,940 doing for humanity. It's an absolute blast. And [laughter] 857 01:02:15,040 --> 01:02:18,680 all right, thanks guys. 858 01:02:25,680 --> 01:02:29,480 I need someone to announce. 859 01:02:45,680 --> 01:02:48,637 >> I don't have any I don't have any mic. 860 01:02:48,720 --> 01:02:50,477 >> Don't go far, ladies and gentlemen. 861 01:02:50,560 --> 01:02:53,437 Don't go far. You are going to win 862 01:02:53,520 --> 01:02:57,837 $10,000 in prizes. Don't go far. 863 01:02:57,920 --> 01:03:02,680 >> You guys >> recording stopped. 864 01:03:03,920 --> 01:03:10,040 >> Hello, >> Landon. Is that live?