1 00:00:00,450 --> 00:00:03,210 Speaker 1: Hey, Odd Lots listeners, the Odd Lots tour continues and 2 00:00:03,270 --> 00:00:04,630 Speaker 1: our next stop is in Chicago. 3 00:00:04,870 --> 00:00:06,690 Speaker 2: That's right. Joe and I will be at the City 4 00:00:06,830 --> 00:00:10,889 Speaker 2: Winery Chicago on October 15th for a live Odd Lots recording. 5 00:00:11,050 --> 00:00:15,010 Speaker 2: Tickets are on sale now at Bloomberg.com forward slash Odd Lots. 6 00:00:15,310 --> 00:00:17,750 Speaker 1: And of course, a special thank you to Barclays for 7 00:00:17,810 --> 00:00:19,330 Speaker 1: supporting Odd Lots Live. 8 00:00:19,570 --> 00:00:23,290 Speaker 2: So that's October 15th at City Winery in Chicago. Get 9 00:00:23,350 --> 00:00:24,250 Speaker 2: your tickets now. 10 00:00:28,020 --> 00:00:29,680 Speaker 1: Bloomberg Audio Studios. 11 00:00:30,150 --> 00:00:32,500 Speaker 3: Podcasts, radio, news. 12 00:00:43,070 --> 00:00:46,610 Speaker 1: Hello and welcome to another episode of the Odd Lots podcast. 13 00:00:46,750 --> 00:00:47,790 Speaker 3: I'm Joe Wiesenthal. 14 00:00:47,970 --> 00:00:49,019 Speaker 4: And I'm Tracy Alloway. 15 00:00:49,090 --> 00:00:52,099 Speaker 1: So we're doing our live show here at the Vermont 16 00:00:52,180 --> 00:00:54,740 Speaker 1: Theater in Hollywood. And one of the things that I 17 00:00:54,780 --> 00:00:57,300 Speaker 1: know very little about, but that I'm very excited to 18 00:00:57,340 --> 00:01:01,460 Speaker 1: learn more about, is the attempts to turn this part 19 00:01:01,480 --> 00:01:05,100 Speaker 1: of the country into a booming part of our industrial 20 00:01:05,140 --> 00:01:05,919 Speaker 1: tech ecosystem. 21 00:01:06,240 --> 00:01:10,200 Speaker 5: Yeah, so we hear about re-industrialization efforts in America all 22 00:01:10,240 --> 00:01:12,480 Speaker 5: the time, but what does it actually take to try 23 00:01:12,520 --> 00:01:15,260 Speaker 5: to do that? And what are the companies actually doing 24 00:01:15,380 --> 00:01:18,500 Speaker 5: in this space right now? We have two very interesting 25 00:01:18,580 --> 00:01:19,060 Speaker 5: ones for you. 26 00:01:19,170 --> 00:01:21,450 Speaker 1: Yes, I'm very excited. You're going to be hearing our 27 00:01:21,510 --> 00:01:24,190 Speaker 1: chat with Chris Power. He is the founder of Hadrian, 28 00:01:24,230 --> 00:01:26,569 Speaker 1: which is trying to build a new generation of factories, 29 00:01:27,010 --> 00:01:30,309 Speaker 1: as well as Tom Mueller, founder of Impulse Space, also 30 00:01:30,390 --> 00:01:34,170 Speaker 1: the first employee of SpaceX. We're going to learn... about 31 00:01:34,290 --> 00:01:37,030 Speaker 1: these attempts to re-industrialize Southern California. 32 00:01:37,490 --> 00:01:37,990 Speaker 3: Take a listen. 33 00:01:39,730 --> 00:01:41,590 Speaker 4: All right, well, thank you so much for coming on 34 00:01:41,650 --> 00:01:43,530 Speaker 4: All Thoughts. Truly the perfect guests. 35 00:01:43,770 --> 00:01:46,410 Speaker 5: I'm going to start with, I guess, the question I 36 00:01:46,450 --> 00:01:50,420 Speaker 5: alluded to at the beginning, which is, what is your 37 00:01:50,520 --> 00:01:54,820 Speaker 5: narrative for the hollowing out, to use a cliche, of 38 00:01:54,980 --> 00:01:56,200 Speaker 5: US manufacturing? 39 00:01:56,280 --> 00:02:00,100 Speaker 4: Why does it seem that we lost some sort of edge? Chris, 40 00:02:00,120 --> 00:02:00,860 Speaker 4: do you want to start? 41 00:02:02,040 --> 00:02:04,680 Speaker 3: I do. And I think the first question is, do 42 00:02:04,820 --> 00:02:09,359 Speaker 3: you want the accurate answer that's going to take three 43 00:02:09,380 --> 00:02:10,580 Speaker 3: minutes or the political one? 44 00:02:11,840 --> 00:02:14,030 Speaker 2: How long does the political one take? 45 00:02:14,220 --> 00:02:14,930 Speaker 4: Can't you do both? 46 00:02:15,690 --> 00:02:21,950 Speaker 3: So here's what happened. But it happens in context. So 47 00:02:22,970 --> 00:02:30,030 Speaker 3: every great power of all time does four very simple things. 48 00:02:32,190 --> 00:02:37,930 Speaker 3: they have some generative population function, they have the best 49 00:02:38,050 --> 00:02:43,510 Speaker 3: industrial capacity, and then they win or prevent a war, 50 00:02:43,650 --> 00:02:45,790 Speaker 3: and then they get incredibly lazy and they end up 51 00:02:45,850 --> 00:02:48,589 Speaker 3: with a financial industry and they offshore what made them 52 00:02:48,630 --> 00:02:51,290 Speaker 3: successful in the first place. And by the way, this 53 00:02:51,430 --> 00:02:55,470 Speaker 3: function is represented in the trade of the reserve currency 54 00:02:55,790 --> 00:02:59,010 Speaker 3: of the world. So the last three times this happened, 55 00:02:59,620 --> 00:03:03,739 Speaker 3: The Netherlands ceded power to the British Empire, and the 56 00:03:03,820 --> 00:03:07,460 Speaker 3: British Empire ceded power to the American Empire. And at 57 00:03:07,820 --> 00:03:11,940 Speaker 3: each moment of industrial power being retraded by financial power, 58 00:03:11,970 --> 00:03:15,310 Speaker 3: you switch the reserve currency of the world. And the 59 00:03:15,330 --> 00:03:18,870 Speaker 3: mistake that everyone makes, because you have four or five 60 00:03:18,930 --> 00:03:22,830 Speaker 3: generations of softness, is that just because you have the 61 00:03:22,870 --> 00:03:25,950 Speaker 3: reserve currency means you rule the world. And you forget 62 00:03:25,990 --> 00:03:28,010 Speaker 3: the fact that the only reason you have the reserve 63 00:03:28,030 --> 00:03:31,190 Speaker 3: currency is because you had the best shipbuilding capacity or 64 00:03:31,240 --> 00:03:36,160 Speaker 3: manufacturing capacity. So this is also the founding story of Hadrian, 65 00:03:36,180 --> 00:03:39,520 Speaker 3: which is, if you track these things, roughly every 150 years, 66 00:03:39,560 --> 00:03:43,960 Speaker 3: the reserve currency of the world changes. And the reason 67 00:03:44,020 --> 00:03:48,620 Speaker 3: is because you think you're Mike Tyson in your prime, 68 00:03:49,200 --> 00:03:51,920 Speaker 3: and the other guy or gal thinks you're Mike Tyson 69 00:03:51,940 --> 00:03:55,880 Speaker 3: before the Buster Douglas fight. And the pattern remains the same. 70 00:03:56,160 --> 00:04:00,560 Speaker 3: So the founding story of Hadrian and the answer to 71 00:04:00,580 --> 00:04:03,500 Speaker 3: your question is the reason why it's important is because 72 00:04:03,560 --> 00:04:10,930 Speaker 3: you've ultimately traded spreadsheet returns from a high effect and 73 00:04:11,210 --> 00:04:14,610 Speaker 3: luxury of life society and you've forgotten that the world 74 00:04:14,670 --> 00:04:17,870 Speaker 3: is real and eventually that comes back to bite you. 75 00:04:18,170 --> 00:04:21,240 Speaker 1: We just did an episode with Francis Fukuyama and so 76 00:04:21,279 --> 00:04:25,620 Speaker 1: we're very well acquainted with this fantasy that The world comes. 77 00:04:26,660 --> 00:04:29,320 Speaker 3: You're in the fourth turning. Okay. Wait, wait, wait, wait. 78 00:04:29,640 --> 00:04:31,549 Speaker 5: Just out of curiosity, before we go to Tom on 79 00:04:31,560 --> 00:04:34,370 Speaker 5: that question, how often do you think about the Roman Empire? 80 00:04:36,029 --> 00:04:37,130 Speaker 4: I'm assuming a lot. 81 00:04:39,070 --> 00:04:43,260 Speaker 3: A lot in the sense that I think that America was... 82 00:04:43,480 --> 00:04:47,100 Speaker 3: So everyone knows what a weeaboo is, yeah? A what? 83 00:04:48,320 --> 00:04:51,539 Speaker 3: There's a lot of laughs. So America was founded by 84 00:04:51,560 --> 00:04:56,380 Speaker 3: a lot of Romaboos. which is like obsessive Roman. So 85 00:04:56,400 --> 00:05:00,080 Speaker 3: a lot of the fundamental infrastructure of the fourth estate 86 00:05:00,520 --> 00:05:05,670 Speaker 3: and Congress was Roman. The flaw that happened with Rome 87 00:05:05,730 --> 00:05:09,690 Speaker 3: is eventually the elites lost the capacity to connect with reality. 88 00:05:11,850 --> 00:05:15,490 Speaker 3: So in a sense, what you outsource when you have 89 00:05:15,610 --> 00:05:19,840 Speaker 3: a reserve currency is reality and then you get bitten 90 00:05:19,860 --> 00:05:21,840 Speaker 3: in the ass and yeah. 91 00:05:22,220 --> 00:05:26,930 Speaker 5: Tom- What's your version of the decline of US manufacturing story? 92 00:05:27,010 --> 00:05:29,030 Speaker 5: And do you also think about the Roman Empire? 93 00:05:29,070 --> 00:05:30,890 Speaker 6: Well, first of all, I'm going to put on my 94 00:05:30,940 --> 00:05:36,240 Speaker 6: glasses to try and be as smart as this guy. 95 00:05:37,240 --> 00:05:42,320 Speaker 6: My take on that was being a founding employee at SpaceX. 96 00:05:44,240 --> 00:05:45,800 Speaker 6: I still say we because I still feel like I'm 97 00:05:45,820 --> 00:05:47,660 Speaker 6: still at SpaceX, even though I left there five years ago. 98 00:05:49,140 --> 00:05:55,460 Speaker 6: We launched 165 rockets last year, more than any other country. 99 00:05:55,480 --> 00:06:00,750 Speaker 6: And we put 10,000 satellites in orbit, three times everybody 100 00:06:00,810 --> 00:06:04,370 Speaker 6: else's number of satellites. So tell me again why we 101 00:06:04,390 --> 00:06:06,390 Speaker 6: can't build in the U.S.? Okay. 102 00:06:06,770 --> 00:06:07,549 Speaker 1: Great answer. 103 00:06:07,750 --> 00:06:08,250 Speaker 3: Optimistic. 104 00:06:09,710 --> 00:06:12,109 Speaker 1: I'm going to ask you, I promise this will be 105 00:06:12,150 --> 00:06:15,589 Speaker 1: the most cynical question that I ask tonight. 106 00:06:16,060 --> 00:06:16,510 Speaker 6: I promise. 107 00:06:16,880 --> 00:06:18,320 Speaker 3: And I'll ask it to both of you. 108 00:06:19,070 --> 00:06:22,810 Speaker 1: We all love the sound of, quote, reindustrialization. It makes 109 00:06:22,870 --> 00:06:27,169 Speaker 1: us feel really good. There's a lot of imagery associated 110 00:06:27,390 --> 00:06:30,610 Speaker 1: with reindustrialization. 111 00:06:29,490 --> 00:06:31,730 Speaker 3: That we like. We like the image of factories, all 112 00:06:31,770 --> 00:06:32,229 Speaker 3: these things. 113 00:06:33,270 --> 00:06:37,080 Speaker 1: There's this very cynical part of me that when I hear, say, 114 00:06:37,140 --> 00:06:40,539 Speaker 1: like VCs and founders talk about all of this stuff, 115 00:06:41,000 --> 00:06:42,960 Speaker 1: that really what they want to do is they want 116 00:06:42,980 --> 00:06:45,740 Speaker 1: to go on podcasts and give their theory about the 117 00:06:45,779 --> 00:06:49,300 Speaker 1: decline of empires, and that they're actually... No offense. 118 00:06:49,680 --> 00:06:50,940 Speaker 3: And I believe you. 119 00:06:50,960 --> 00:06:54,140 Speaker 1: And then I'm like, yeah, but where's the thing that 120 00:06:54,180 --> 00:06:56,780 Speaker 1: you've built? So why don't we start with you and 121 00:06:56,820 --> 00:06:59,640 Speaker 1: both of you and maybe give me, why don't you 122 00:07:00,380 --> 00:07:02,660 Speaker 1: tell me what you're doing and tell me why I 123 00:07:02,700 --> 00:07:07,060 Speaker 1: should believe it's real rather than creating good footage for 124 00:07:07,110 --> 00:07:08,250 Speaker 1: a 90 second tweet. 125 00:07:08,930 --> 00:07:12,110 Speaker 6: So my company is Impulse Space. I started it within 126 00:07:12,730 --> 00:07:14,640 Speaker 6: six or eight months after I left SpaceX in 2020, 127 00:07:14,630 --> 00:07:21,590 Speaker 6: or 2021, sorry. And We do in-space transportation. So we 128 00:07:21,630 --> 00:07:24,450 Speaker 6: still use SpaceX and other rockets to get to space. 129 00:07:25,270 --> 00:07:29,090 Speaker 6: Everything I build operates in space. So we take over 130 00:07:29,130 --> 00:07:33,010 Speaker 6: where launch vehicles leave off. So think of a launch vehicle, 131 00:07:33,110 --> 00:07:38,150 Speaker 6: especially like Starship, a gigantic launch vehicle that can take 132 00:07:38,150 --> 00:07:41,150 Speaker 6: 100 tons to orbit. Think of it as like the 133 00:07:41,170 --> 00:07:45,340 Speaker 6: container ship coming into a port, the port being a 134 00:07:46,400 --> 00:07:49,470 Speaker 6: certain orbit. And all that cargo needs to go to 135 00:07:49,510 --> 00:07:53,530 Speaker 6: different places. So we provide the sprinter vans and the 136 00:07:55,010 --> 00:07:58,340 Speaker 6: trucks to move that cargo to other places. So we 137 00:07:58,400 --> 00:08:02,800 Speaker 6: have two products. We have one that's a very precision 138 00:08:03,200 --> 00:08:06,400 Speaker 6: maneuvering satellite that has a lot of propulsion. It can 139 00:08:06,460 --> 00:08:10,210 Speaker 6: move very closely. We have three of these on orbit 140 00:08:10,230 --> 00:08:12,050 Speaker 6: right now. Two of them just came within 200 meters 141 00:08:12,090 --> 00:08:15,070 Speaker 6: of each other. There are two football fields, which is 142 00:08:15,110 --> 00:08:18,540 Speaker 6: really close in space, actually. And then we have another 143 00:08:18,660 --> 00:08:21,420 Speaker 6: product called Helios, which is basically a rocket on a rocket. 144 00:08:21,440 --> 00:08:23,900 Speaker 6: It's a giant tank of propellant with a very high 145 00:08:23,920 --> 00:08:26,300 Speaker 6: energy engine that can take you way out. It can 146 00:08:26,360 --> 00:08:29,460 Speaker 6: escape Earth's gravity. It can improve the payload of a 147 00:08:29,500 --> 00:08:32,120 Speaker 6: Falcon 9 to the moon or to Mars by about 148 00:08:32,140 --> 00:08:35,450 Speaker 6: a factor of five. So those are the two main products, 149 00:08:35,490 --> 00:08:37,179 Speaker 6: and then there's other ones I can't talk about. 150 00:08:38,770 --> 00:08:44,670 Speaker 3: And what are you actually building? So we build design-agnostic 151 00:08:44,809 --> 00:08:50,059 Speaker 3: autonomous factories, which means... Manufacturing is hard. We will take 152 00:08:50,220 --> 00:08:55,819 Speaker 3: any design and build factories as a service with our 153 00:08:55,900 --> 00:08:59,480 Speaker 3: software platform and our technician base that we train from scratch, 154 00:09:00,500 --> 00:09:05,880 Speaker 3: where we are an automated contract manufacturer. Got it. What 155 00:09:05,920 --> 00:09:10,300 Speaker 3: we actually produce is everything from spaceflight components for the 156 00:09:10,320 --> 00:09:14,760 Speaker 3: products that Tom said to an entire missile to 30% 157 00:09:14,760 --> 00:09:20,150 Speaker 3: of a Virginia-class submarine. So our job is to use 158 00:09:20,210 --> 00:09:25,359 Speaker 3: technology to do process designs into a digital twin, run 159 00:09:25,400 --> 00:09:29,300 Speaker 3: that into factories as a service where we build software-powered 160 00:09:29,360 --> 00:09:35,520 Speaker 3: factories combined with the workforce where we can operate lights 161 00:09:35,600 --> 00:09:39,940 Speaker 3: out 24-7 so we are incredibly more efficient and competent. 162 00:09:40,760 --> 00:09:46,870 Speaker 3: But we are like Foxconn to Apple. We are Foxconn 163 00:09:46,929 --> 00:09:47,970 Speaker 3: to every defense brand. 164 00:09:48,580 --> 00:09:52,110 Speaker 5: When you say autonomous manufacturing, how autonomous are we talking 165 00:09:52,140 --> 00:09:52,500 Speaker 5: about here? 166 00:09:52,570 --> 00:09:55,209 Speaker 4: Could I, for instance, run one of your machines? 167 00:09:55,290 --> 00:09:57,070 Speaker 5: And then also, one of the things I always wonder is, 168 00:09:57,090 --> 00:09:59,910 Speaker 5: when we talk about autonomous machinery, what are the humans 169 00:10:00,010 --> 00:10:01,920 Speaker 5: who are actually running them doing? 170 00:10:02,400 --> 00:10:04,680 Speaker 4: Just like pressing the button that says go and stop? 171 00:10:05,520 --> 00:10:08,020 Speaker 3: So the first thing that people get wrong is if 172 00:10:08,040 --> 00:10:09,959 Speaker 3: you look at a factory and you see a bunch 173 00:10:10,000 --> 00:10:13,959 Speaker 3: of humans moving things, you think it's a like a 174 00:10:14,820 --> 00:10:19,100 Speaker 3: humanoid robot problem. Actually what's happening in advanced manufacturing is 175 00:10:19,140 --> 00:10:23,800 Speaker 3: there's an incredible amount of smart humans either at a 176 00:10:23,870 --> 00:10:27,949 Speaker 3: desktop doing digital engineering or they're at the factory floor 177 00:10:29,090 --> 00:10:33,870 Speaker 3: driving an incredibly dumb computer. And that's 90% of advanced manufacturing. 178 00:10:34,030 --> 00:10:36,220 Speaker 3: This is why we're a software company because it looks 179 00:10:36,270 --> 00:10:39,020 Speaker 3: like to any robotics person that if you could optimize 180 00:10:39,040 --> 00:10:43,100 Speaker 3: a technician not loading the part on the machine or 181 00:10:43,120 --> 00:10:45,760 Speaker 3: the assembly into the robot, that's going to save you money. 182 00:10:45,820 --> 00:10:49,939 Speaker 3: It's not. It's actually all massive amounts of software engineering 183 00:10:49,960 --> 00:10:52,959 Speaker 3: to tie everything together and make it autonomous. The reason 184 00:10:53,040 --> 00:10:56,250 Speaker 3: why a welder or machinist has to stand in front 185 00:10:56,260 --> 00:10:59,750 Speaker 3: of a machine is because it's not closed loop. They're 186 00:11:00,050 --> 00:11:02,689 Speaker 3: genuinely doing trigonometry in their head being like, oh, I 187 00:11:02,710 --> 00:11:05,590 Speaker 3: think the tool's about to break and therefore I have 188 00:11:05,630 --> 00:11:09,170 Speaker 3: to stand in front of it. That's all actually a 189 00:11:09,210 --> 00:11:12,590 Speaker 3: software problem. So we build software power factories to make 190 00:11:12,650 --> 00:11:15,530 Speaker 3: sure that you can do a physical task, which is 191 00:11:15,590 --> 00:11:18,530 Speaker 3: very hard for any robot to do, which is high judgment, 192 00:11:19,750 --> 00:11:22,890 Speaker 3: set up something very fiddly, and then load it into 193 00:11:22,910 --> 00:11:26,170 Speaker 3: a robotics and CNC or welding system and say, go, 194 00:11:26,230 --> 00:11:29,590 Speaker 3: it's done, walk away. And the power of the software 195 00:11:29,630 --> 00:11:32,510 Speaker 3: is that you're able to walk away without being really 196 00:11:32,570 --> 00:11:35,449 Speaker 3: scared that you're going to accidentally make a code change 197 00:11:35,490 --> 00:11:36,870 Speaker 3: and crash a $ 3 million machine. 198 00:11:37,270 --> 00:11:39,689 Speaker 5: I think the trigonometry point was a polite way of 199 00:11:39,730 --> 00:11:41,910 Speaker 5: saying that, no, I could not, in fact, run one 200 00:11:41,950 --> 00:11:43,390 Speaker 5: of these machines, which is fair. 201 00:11:43,410 --> 00:11:44,069 Speaker 4: It's fair. 202 00:11:45,230 --> 00:11:49,550 Speaker 3: I think fundamentally... What humans do in our factories is 203 00:11:49,610 --> 00:11:52,970 Speaker 3: they have high judgment, they have control over what they 204 00:11:53,010 --> 00:11:55,900 Speaker 3: are going to do, and they do very high dexterity tasks. 205 00:11:56,520 --> 00:11:57,969 Speaker 3: Most of the load is on the surface. 206 00:12:14,809 --> 00:12:18,910 Speaker 1: So I was in Shenzhen earlier this year, and one 207 00:12:18,950 --> 00:12:23,689 Speaker 1: of the things that people always talk about the Chinese manufacturing. 208 00:12:24,480 --> 00:12:26,400 Speaker 3: Success is the ecosystem, right? 209 00:12:26,720 --> 00:12:29,620 Speaker 1: You need some part or something like that that's custom fit, 210 00:12:29,660 --> 00:12:32,540 Speaker 1: and there's someone a mile away, and they can make 211 00:12:32,580 --> 00:12:35,679 Speaker 1: it for you that afternoon, and then you have it there. 212 00:12:36,200 --> 00:12:39,320 Speaker 1: And what's interesting or intriguing or why we wanted to 213 00:12:39,380 --> 00:12:42,740 Speaker 1: have this part of the conversation is I know that 214 00:12:42,760 --> 00:12:45,640 Speaker 1: there's actually quite a number of companies in the Southern 215 00:12:45,679 --> 00:12:49,500 Speaker 1: California area building stuff. And I'm curious, like, is it 216 00:12:49,540 --> 00:12:53,140 Speaker 1: becoming rich in the sense that you're complementing each other 217 00:12:53,620 --> 00:12:56,600 Speaker 1: and sort of like building on each other's successes and 218 00:12:56,800 --> 00:12:59,340 Speaker 1: each one of you is increasing the odds of you 219 00:12:59,380 --> 00:13:00,610 Speaker 1: that the other succeeds in some way? 220 00:13:01,300 --> 00:13:04,160 Speaker 6: I think it's both. We're stealing talent from each other, certainly. 221 00:13:04,720 --> 00:13:07,940 Speaker 6: And we're competing for talent, for sure. There are so 222 00:13:08,020 --> 00:13:14,030 Speaker 6: many companies that a lot of founders that were ex-SpaceX 223 00:13:14,090 --> 00:13:16,290 Speaker 6: like me and a lot of my employees are ex-SpaceX 224 00:13:16,770 --> 00:13:19,190 Speaker 6: and other. And then like right across the street from 225 00:13:19,210 --> 00:13:22,240 Speaker 6: me is Northrop Grumman, which was TRW. I worked there 226 00:13:22,260 --> 00:13:24,679 Speaker 6: for 15 years. It's literally across the street from me. 227 00:13:24,780 --> 00:13:26,700 Speaker 6: I look out of my office window and I was 228 00:13:26,740 --> 00:13:29,650 Speaker 6: in that building. We steal a lot of people from them. 229 00:13:29,809 --> 00:13:33,460 Speaker 6: We steal from Boeing. It's just there's only so much 230 00:13:33,540 --> 00:13:37,220 Speaker 6: talent in the area, and there's so many companies growing 231 00:13:37,320 --> 00:13:39,820 Speaker 6: so fast. We're bringing it back. I was talking in 232 00:13:39,840 --> 00:13:42,200 Speaker 6: the green room about this chart that I used to 233 00:13:42,240 --> 00:13:46,000 Speaker 6: love that showed aerospace jobs in the South Bay like this, 234 00:13:46,240 --> 00:13:49,709 Speaker 6: and SpaceX started in 2002. It took maybe three or 235 00:13:49,750 --> 00:13:51,510 Speaker 6: four years, and it started going up, and it's just 236 00:13:51,550 --> 00:13:56,250 Speaker 6: going past that. And you think about all the other 237 00:13:56,290 --> 00:14:01,250 Speaker 6: startups are not, necessarily all space startups. There's nuclear companies, 238 00:14:01,350 --> 00:14:08,050 Speaker 6: there's drone companies, there's, you know, defense companies, there's 3D 239 00:14:08,090 --> 00:14:13,970 Speaker 6: printing companies, all kinds of new tech happening in the area. 240 00:14:14,010 --> 00:14:16,890 Speaker 6: And if you go even further, like not just South Bay, but, 241 00:14:17,450 --> 00:14:20,030 Speaker 6: you know, like Anduril, you know, down in Orange County 242 00:14:20,070 --> 00:14:23,729 Speaker 6: and the general area, it's just, I always say that, like, 243 00:14:24,750 --> 00:14:27,910 Speaker 6: software is done in In Silicon Valley, hardware is done 244 00:14:28,030 --> 00:14:28,350 Speaker 6: in LA. 245 00:14:29,370 --> 00:14:31,150 Speaker 5: Wait, can both of you say a little bit more 246 00:14:31,430 --> 00:14:35,920 Speaker 5: about how you think about producing stuff in-house versus sourcing 247 00:14:35,980 --> 00:14:39,160 Speaker 5: it externally? Because you think about SpaceX, and one of 248 00:14:39,180 --> 00:14:41,920 Speaker 5: the famous things about SpaceX is vertical integration, right? The 249 00:14:42,000 --> 00:14:46,470 Speaker 5: idea that there weren't enough space manufacturers making vital components, 250 00:14:46,520 --> 00:14:48,690 Speaker 5: so they brought everything in-house in order to do it 251 00:14:49,490 --> 00:14:52,450 Speaker 5: to the speed at which Elon desires, to put it 252 00:14:52,570 --> 00:14:53,870 Speaker 5: politely or mildly. 253 00:14:54,570 --> 00:14:56,010 Speaker 4: How do you think about that tradeoff? 254 00:14:56,070 --> 00:14:59,620 Speaker 6: I mean, that's a great discussion to have because Chris 255 00:14:59,820 --> 00:15:02,340 Speaker 6: and I, you know, it involves both of us because 256 00:15:02,560 --> 00:15:05,360 Speaker 6: we're very vertically integrated at Impulse, just like we were 257 00:15:05,440 --> 00:15:09,040 Speaker 6: at SpaceX. But also, we buy a lot of parts 258 00:15:09,070 --> 00:15:13,350 Speaker 6: from outside. Like, I think it's really important to, like, 259 00:15:13,930 --> 00:15:17,810 Speaker 6: you make your first development engine or spacecraft, you build 260 00:15:17,850 --> 00:15:20,190 Speaker 6: it yourself, and you learn all of the problems that 261 00:15:20,210 --> 00:15:24,230 Speaker 6: you're going to have assembling it, machining it, If I 262 00:15:24,270 --> 00:15:27,050 Speaker 6: gave a development thing to a machine shop and they 263 00:15:27,090 --> 00:15:29,290 Speaker 6: had all these problems with the drawing and making the part, 264 00:15:29,310 --> 00:15:30,470 Speaker 6: and then we get it and we can't assemble it. 265 00:15:30,650 --> 00:15:34,470 Speaker 6: You learn it on your prototypes. And once you get 266 00:15:34,510 --> 00:15:37,130 Speaker 6: that tight, then you send it out. I know Chris 267 00:15:37,170 --> 00:15:39,870 Speaker 6: is getting ready to make Raptor parts. So even SpaceX 268 00:15:40,130 --> 00:15:42,960 Speaker 6: is sending parts out. We get to the point where 269 00:15:42,980 --> 00:15:46,540 Speaker 6: you get into production. That's when you don't need to 270 00:15:46,600 --> 00:15:50,900 Speaker 6: grow your facility to handle high production. Maybe you'll keep 271 00:15:51,000 --> 00:15:55,730 Speaker 6: some of the really super secret parts in your house, 272 00:15:55,790 --> 00:16:00,130 Speaker 6: but you'll send the easier-to-machine or stuff that his shop 273 00:16:00,150 --> 00:16:03,210 Speaker 6: can make really great out. That's my take on that. 274 00:16:03,860 --> 00:16:08,600 Speaker 3: I agree. I think every company should have 10% to 15% in-house. 275 00:16:09,220 --> 00:16:12,620 Speaker 3: There's no amount of software or service in the world that, like, 276 00:16:13,080 --> 00:16:15,180 Speaker 3: you've got a hot pot, you need the one genius 277 00:16:15,220 --> 00:16:16,989 Speaker 3: guy to make it in an hour to hit flight. 278 00:16:18,410 --> 00:16:23,410 Speaker 3: But scale has to happen externally. Mm-hmm. For us, as 279 00:16:23,650 --> 00:16:27,489 Speaker 3: a contract manufacturer, for some customers, we make parts. For 280 00:16:27,510 --> 00:16:31,000 Speaker 3: some customers, we make the entire missile. And for submarines, 281 00:16:31,040 --> 00:16:35,560 Speaker 3: we make somewhere in halfway. Even for us, what I 282 00:16:35,620 --> 00:16:39,430 Speaker 3: trade off is I think in manufacturing, you sell and 283 00:16:39,470 --> 00:16:44,490 Speaker 3: buy trust. So our vertical integration strategy is we want 284 00:16:44,510 --> 00:16:48,930 Speaker 3: to outsource everything possible to every reindustrialized startup, every small 285 00:16:48,970 --> 00:16:51,270 Speaker 3: business that we possibly can because we have so many 286 00:16:51,330 --> 00:16:56,270 Speaker 3: programs to run. But we vertically integrate where we just 287 00:16:56,330 --> 00:16:58,770 Speaker 3: don't believe you're going to get the job done. And 288 00:16:58,810 --> 00:17:01,109 Speaker 3: it's not a financial trade. It's like I'll put a 289 00:17:01,110 --> 00:17:05,490 Speaker 3: $ 2 million piece of CapEx in the ground and hire 290 00:17:05,550 --> 00:17:08,190 Speaker 3: a team to do it because I would rather spend 291 00:17:08,290 --> 00:17:11,730 Speaker 3: more money making sure we're on schedule than then taking 292 00:17:11,770 --> 00:17:15,170 Speaker 3: the risk that outsourcing it to a legacy casting facility 293 00:17:15,190 --> 00:17:17,660 Speaker 3: that's been late for the last 30 years on every 294 00:17:18,200 --> 00:17:22,680 Speaker 3: submarine program, for me, it's all about trust. It's not economics. 295 00:17:22,740 --> 00:17:25,240 Speaker 3: It's not anything. It's just I needed to be on time, 296 00:17:25,480 --> 00:17:28,560 Speaker 3: and most of America is incompetent in terms of trust 297 00:17:28,580 --> 00:17:30,610 Speaker 3: and schedule. Is that fair? 298 00:17:30,630 --> 00:17:33,990 Speaker 6: Manufacturing a machine shop or a manufacturing house that you 299 00:17:34,010 --> 00:17:35,010 Speaker 6: can trust is gold. 300 00:17:36,170 --> 00:17:39,139 Speaker 1: You know, we actually did an interview yesterday with the 301 00:17:39,200 --> 00:17:44,100 Speaker 1: guy who's heading the LA 2028 Olympics. But I recently 302 00:17:44,160 --> 00:17:48,290 Speaker 1: saw the robot Olympics in China and all the humanoid Olympics. 303 00:17:48,310 --> 00:17:50,210 Speaker 3: And they were, like, running. It was, like, really impressive. 304 00:17:51,670 --> 00:17:52,550 Speaker 3: Let's be honest. 305 00:17:53,190 --> 00:17:56,770 Speaker 1: In future Olympics, will Americans ever medal in the humanoid 306 00:17:56,790 --> 00:17:57,790 Speaker 1: robotic Olympics? 307 00:17:59,440 --> 00:18:04,000 Speaker 3: Not yet, but I'd take a roided-up Midwesterner versus a 308 00:18:04,040 --> 00:18:05,540 Speaker 3: communist robot every day of the week. 309 00:18:10,119 --> 00:18:10,680 Speaker 6: I would, too. 310 00:18:10,700 --> 00:18:11,540 Speaker 4: That's a good answer. 311 00:18:11,660 --> 00:18:15,590 Speaker 1: But, no, but this is a serious question because future 312 00:18:15,660 --> 00:18:17,389 Speaker 1: warfare could be. 313 00:18:17,410 --> 00:18:19,909 Speaker 3: No, it is. It is. 314 00:18:20,350 --> 00:18:22,870 Speaker 1: And I would not want to put up a roided-up 315 00:18:22,910 --> 00:18:25,250 Speaker 1: Midwesterner against a robot that, like. 316 00:18:25,350 --> 00:18:27,780 Speaker 3: Well, I was glad to know that you're full of clankers, but.... 317 00:18:29,400 --> 00:18:33,040 Speaker 1: But no, seriously, like how anxious should we be about 318 00:18:33,119 --> 00:18:33,840 Speaker 1: the robot gas? 319 00:18:34,080 --> 00:18:40,940 Speaker 3: So in terms of, so let me go back a step. Netherlands, 320 00:18:40,980 --> 00:18:44,420 Speaker 3: British Empire, American Republic. The next trade is the CCP 321 00:18:44,440 --> 00:18:47,580 Speaker 3: versus America. America has a lot of flaws. We like 322 00:18:47,619 --> 00:18:49,720 Speaker 3: to debate because we are so rich that we get 323 00:18:49,760 --> 00:18:52,010 Speaker 3: to debate the culture of the country instead of fighting 324 00:18:52,050 --> 00:18:55,230 Speaker 3: for survival out of a famine. Ultimately, hard power wins 325 00:18:55,270 --> 00:18:57,409 Speaker 3: politics because at some point you don't want to be 326 00:18:57,450 --> 00:18:59,500 Speaker 3: polite and you can just be like, well, I have 327 00:18:59,500 --> 00:19:07,780 Speaker 3: 2000 warships. Yeah. We have our current missile inventory in 328 00:19:07,880 --> 00:19:12,040 Speaker 3: any war game. We expand everything in the warehouse and 329 00:19:12,060 --> 00:19:16,260 Speaker 3: we run out in seven days. China produced 2,600 ships 330 00:19:16,420 --> 00:19:19,379 Speaker 3: and we produced six, et cetera, et cetera, et cetera. 331 00:19:20,220 --> 00:19:23,340 Speaker 3: And the thing that you need to realize is in 332 00:19:23,660 --> 00:19:26,859 Speaker 3: Germany versus America, which is the proxy of World War II, 333 00:19:27,780 --> 00:19:31,899 Speaker 3: We actually sucked at engineering. The German engineers destroyed us. 334 00:19:32,790 --> 00:19:35,950 Speaker 3: We just McDonald's the out of them. We were China 335 00:19:36,050 --> 00:19:37,970 Speaker 3: in World War II. No, no, no, it's not a 336 00:19:37,990 --> 00:19:40,750 Speaker 3: laughing matter. We were China in World War II. We 337 00:19:40,770 --> 00:19:43,170 Speaker 3: just outproduced them. We had better logistics. We made more 338 00:19:43,190 --> 00:19:47,290 Speaker 3: stuff because we weren't rich, but we're the industrial superpower 339 00:19:47,350 --> 00:19:50,899 Speaker 3: and we became rich because of Bretton Woods. You're in 340 00:19:50,940 --> 00:19:56,960 Speaker 3: the same situation. So it's incredibly serious because you're in 341 00:19:57,000 --> 00:20:00,060 Speaker 3: the fourth turning where you are, like we spent the 342 00:20:00,100 --> 00:20:05,340 Speaker 3: last 10 years in COVID trading cat pictures on JPEGs 343 00:20:05,400 --> 00:20:08,900 Speaker 3: on the internet. Yeah. And we've forgotten why we're successful 344 00:20:08,920 --> 00:20:11,780 Speaker 3: in the first place, which ultimately was we were the 345 00:20:11,980 --> 00:20:16,400 Speaker 3: largest industrial superpower in the world. So the reason why 346 00:20:16,440 --> 00:20:19,700 Speaker 3: it's serious is you can have the best engineering in 347 00:20:19,720 --> 00:20:22,210 Speaker 3: the world, like you've got the best Raytheon missile, but 348 00:20:22,250 --> 00:20:25,230 Speaker 3: if you literally can't just make mass, which is ultimately 349 00:20:25,250 --> 00:20:29,710 Speaker 3: a production issue, there's no choice. So we are so 350 00:20:29,770 --> 00:20:32,689 Speaker 3: far behind and no one realizes this purely because you 351 00:20:32,710 --> 00:20:38,230 Speaker 3: were in a cultural time where America currently is IBM. 352 00:20:39,510 --> 00:20:42,530 Speaker 3: And you go to the board of IBM and you say, hey, guys, 353 00:20:42,770 --> 00:20:45,609 Speaker 3: would you like to invent Claude Code? And the board 354 00:20:45,630 --> 00:20:48,480 Speaker 3: and the CEO says, yes, sir. And you look back 355 00:20:48,540 --> 00:20:51,940 Speaker 3: at your 500,000 employees and you go, we're f * * * ed. 356 00:20:53,320 --> 00:20:56,320 Speaker 3: And the good thing is America's got a lot of dynamism. 357 00:20:56,380 --> 00:21:00,560 Speaker 3: America's got people like Tom Mueller and Elon and the 358 00:21:00,600 --> 00:21:03,480 Speaker 3: nuclear stuff. It's possible to correct, but we are so 359 00:21:03,560 --> 00:21:07,560 Speaker 3: far behind... that ultimately robotics is how good are we 360 00:21:07,619 --> 00:21:11,419 Speaker 3: at software, but ultimately most of software, especially AI, is 361 00:21:11,500 --> 00:21:14,980 Speaker 3: now determined on what is the velocity of your training data, 362 00:21:15,000 --> 00:21:19,129 Speaker 3: which means physical world deployment, which means mass manufacturing. So 363 00:21:19,910 --> 00:21:23,690 Speaker 3: it's a real civilizational fight, and it's not this fun 364 00:21:23,770 --> 00:21:27,070 Speaker 3: game between American companies where like, hey, if Tesla ships 365 00:21:27,109 --> 00:21:30,490 Speaker 3: more Optimus versus Google, the consumer's going to end up 366 00:21:30,530 --> 00:21:33,409 Speaker 3: in a better product. No, no, no. No, they're going 367 00:21:33,430 --> 00:21:37,350 Speaker 3: to kill you. And people are not tracking this at all. 368 00:21:37,510 --> 00:21:39,010 Speaker 3: And Tom, I know you're much more of a space 369 00:21:39,050 --> 00:21:41,649 Speaker 3: guy than defense guy, but I'd love your opinion on this. 370 00:21:42,270 --> 00:21:45,929 Speaker 6: Well, I have a pretty, I've been thinking about robots 371 00:21:45,970 --> 00:21:49,700 Speaker 6: a lot lately. And I think that the resources of 372 00:21:49,720 --> 00:21:53,219 Speaker 6: the moon are going to be needed to do what 373 00:21:53,260 --> 00:21:55,820 Speaker 6: we want to do in space. And how do you 374 00:21:55,859 --> 00:21:59,879 Speaker 6: do that? Like having people on the moon, like an 375 00:21:59,980 --> 00:22:03,050 Speaker 6: army of people working on the moon, It's just not sustainable. 376 00:22:03,090 --> 00:22:06,430 Speaker 6: It's too dangerous. It's too expensive. It's not a good 377 00:22:06,450 --> 00:22:10,649 Speaker 6: environment for humans. Maybe a few, but you want an 378 00:22:10,810 --> 00:22:13,490 Speaker 6: army of robots to build on the moon and eventually Mars. 379 00:22:14,530 --> 00:22:17,189 Speaker 6: And what do you need to make a really good robot? 380 00:22:17,210 --> 00:22:20,469 Speaker 6: I think you need three things. You need dexterity. You 381 00:22:20,490 --> 00:22:22,850 Speaker 6: need a human hand, basically, and people are working on that. 382 00:22:23,109 --> 00:22:26,310 Speaker 6: You need great vision, which is already pretty much solved. 383 00:22:26,430 --> 00:22:29,820 Speaker 6: And you need a brain, AI. Once those pieces all 384 00:22:29,859 --> 00:22:34,169 Speaker 6: come together, You have the capability to be human plus superhuman. 385 00:22:35,869 --> 00:22:38,169 Speaker 6: Of course, that can be used in war also. But 386 00:22:38,410 --> 00:22:40,150 Speaker 6: for me, I always think about what you can do 387 00:22:40,230 --> 00:22:44,750 Speaker 6: in space because it's such a harsh environment. Humans should 388 00:22:44,790 --> 00:22:48,210 Speaker 6: not have to be there. We should choose to go there. 389 00:22:49,050 --> 00:22:53,409 Speaker 6: But to try and work and build there is a 390 00:22:53,450 --> 00:22:56,310 Speaker 6: losing game, I think. And we don't need to do 391 00:22:56,369 --> 00:22:58,179 Speaker 6: it because robots are on the cusp of doing it. 392 00:23:14,640 --> 00:23:19,050 Speaker 5: What is the actual key constraint to your respective businesses then? 393 00:23:19,090 --> 00:23:21,950 Speaker 5: Because when you say these things, everything is couched in 394 00:23:21,990 --> 00:23:25,609 Speaker 5: these existential terms like war. 395 00:23:25,330 --> 00:23:27,310 Speaker 4: And death, and I'm sure we all want to survive. 396 00:23:27,369 --> 00:23:32,170 Speaker 5: So why aren't we cracking this particular problem? I've seen 397 00:23:32,190 --> 00:23:35,070 Speaker 5: your respective valuations, so it's probably not a question of money, 398 00:23:35,170 --> 00:23:38,590 Speaker 5: but is it a question of labor or materials, or 399 00:23:38,670 --> 00:23:39,530 Speaker 5: what's going on here? 400 00:23:39,550 --> 00:23:48,460 Speaker 6: You go first. You know, the last two weeks, I 401 00:23:48,500 --> 00:23:50,520 Speaker 6: think the discussion has been, will the AI just kill 402 00:23:50,560 --> 00:23:56,100 Speaker 6: us outright before we even get to war, right? Yeah, 403 00:23:56,119 --> 00:24:00,120 Speaker 6: technology is a great thing. It's a super dangerous thing. 404 00:24:00,160 --> 00:24:04,020 Speaker 6: I think there's been no greater example of that than AI. 405 00:24:04,320 --> 00:24:10,160 Speaker 6: And I read Superintelligence by Ben Bostrom, like when that 406 00:24:10,180 --> 00:24:11,700 Speaker 6: came out, like 10, 15 years ago. 407 00:24:11,780 --> 00:24:12,020 Speaker 4: Yeah. 408 00:24:12,280 --> 00:24:16,389 Speaker 6: And Elon read it too, and we were scared. Like, 409 00:24:16,770 --> 00:24:20,350 Speaker 6: it was just like, that book was so comprehensive. And 410 00:24:20,470 --> 00:24:23,140 Speaker 6: it's like, well, at least, you know, the futurists think 411 00:24:23,180 --> 00:24:27,180 Speaker 6: this is like, you know, 2045, 2050, this is going 412 00:24:27,440 --> 00:24:32,820 Speaker 6: to happen. Because of LLMs, nobody knew that an LLM, 413 00:24:32,900 --> 00:24:36,040 Speaker 6: if you just study human language and do these neural networks, 414 00:24:36,540 --> 00:24:38,940 Speaker 6: how much could be in there, right? We still don't understand. 415 00:24:39,460 --> 00:24:42,460 Speaker 6: So it happened much sooner than we thought, and we're 416 00:24:42,500 --> 00:24:47,420 Speaker 6: not ready for it. And here we are. We can't 417 00:24:47,460 --> 00:24:49,220 Speaker 6: slow down too much. I think we're ahead of China 418 00:24:49,240 --> 00:24:50,850 Speaker 6: so we can slow down, but we can't slow down 419 00:24:50,900 --> 00:24:53,909 Speaker 6: too much and let them get ahead because whoever has 420 00:24:53,970 --> 00:24:56,850 Speaker 6: the super intelligent AI could possibly rule the world. I 421 00:24:56,869 --> 00:25:01,350 Speaker 6: think that's probably true. So we're at a really important 422 00:25:01,410 --> 00:25:02,570 Speaker 6: place in history right now. 423 00:25:03,430 --> 00:25:05,869 Speaker 1: You know, when I asked that question about the Robot Olympics, 424 00:25:06,369 --> 00:25:08,389 Speaker 1: I was really hoping your answer was going to be 425 00:25:08,430 --> 00:25:11,470 Speaker 1: something like, Yeah, that's just show. We're really not that 426 00:25:11,530 --> 00:25:14,130 Speaker 1: far behind. Like I was I was trying to set 427 00:25:14,150 --> 00:25:17,010 Speaker 1: you up for like an optimistic spin. I thought, oh, no, 428 00:25:17,090 --> 00:25:20,490 Speaker 1: don't get fooled by like those videos you see of robots. 429 00:25:20,560 --> 00:25:26,740 Speaker 1: But everything since then has been unfortunately. By the way, 430 00:25:26,760 --> 00:25:29,760 Speaker 1: I understand we're a nicotine fueled empire. I heard that 431 00:25:29,820 --> 00:25:32,560 Speaker 1: great that great powers are fueled by nicotine. 432 00:25:32,660 --> 00:25:35,180 Speaker 3: Every great company or empire is fueled by one drug. 433 00:25:35,540 --> 00:25:38,320 Speaker 3: Stripe was an Adderall company. Everyone in manufacturing is a 434 00:25:38,359 --> 00:25:41,200 Speaker 3: nicotine and alcohol fuel supplier. 435 00:25:41,240 --> 00:25:41,620 Speaker 6: Caffeine. 436 00:25:41,880 --> 00:25:46,350 Speaker 1: So, Tommy, you said something really important, actually, at the beginning, 437 00:25:46,640 --> 00:25:50,070 Speaker 1: which is, you know, you mentioned the number of rockets 438 00:25:50,130 --> 00:25:52,490 Speaker 1: that we've launched. And we always say, oh, you can't 439 00:25:52,530 --> 00:25:55,990 Speaker 1: build in America. But it is evidently provably false because 440 00:25:56,030 --> 00:26:00,210 Speaker 1: there was this one individual who actually built the biggest 441 00:26:00,250 --> 00:26:03,730 Speaker 1: car company in the world and built the biggest rocket 442 00:26:03,770 --> 00:26:07,730 Speaker 1: company and the biggest satellite company, et cetera, which there 443 00:26:07,750 --> 00:26:10,109 Speaker 1: are not multiple of him, but it was clearly in 444 00:26:10,170 --> 00:26:12,510 Speaker 1: retrospect possible to build big things. 445 00:26:12,650 --> 00:26:15,270 Speaker 6: And he was about to build the biggest data server 446 00:26:15,530 --> 00:26:16,690 Speaker 6: company in the world. 447 00:26:16,730 --> 00:26:16,930 Speaker 3: Right. 448 00:26:17,290 --> 00:26:23,250 Speaker 1: So I don't know, you know, what is, as SpaceX 449 00:26:23,310 --> 00:26:27,449 Speaker 1: employee number one, what was it, how would you characterize 450 00:26:27,490 --> 00:26:31,140 Speaker 1: to a broad public what Elon was capable of doing, 451 00:26:31,260 --> 00:26:34,419 Speaker 1: which so many people presume cannot or could not have 452 00:26:34,440 --> 00:26:36,800 Speaker 1: been done in the U.S. in the first half of 453 00:26:37,160 --> 00:26:38,540 Speaker 1: the first two decades of the century? 454 00:26:39,600 --> 00:26:44,000 Speaker 6: I mean, you know, I went through, I couldn't hire, 455 00:26:44,020 --> 00:26:46,369 Speaker 6: when we first started, there was like four of us. 456 00:26:46,869 --> 00:26:49,470 Speaker 6: And I couldn't, all the people I worked with at TRW, 457 00:26:49,550 --> 00:26:51,030 Speaker 6: all of them like rolled their eyes and would not 458 00:26:51,090 --> 00:26:54,810 Speaker 6: come work with me. All the Rocketdyne guys, Rocketdyne did 459 00:26:54,910 --> 00:26:57,510 Speaker 6: all the engines that got us to the moon back 460 00:26:57,530 --> 00:27:02,420 Speaker 6: in the 60s. None of them, like only governments and 461 00:27:02,580 --> 00:27:05,859 Speaker 6: big money can build a rocket that can get to orbit. 462 00:27:06,320 --> 00:27:10,500 Speaker 6: So we had at every step people saying you can't 463 00:27:10,560 --> 00:27:12,879 Speaker 6: do it. Like you can't build an engine that can 464 00:27:12,920 --> 00:27:15,680 Speaker 6: do this. You can't, a pump fed engine. You can't 465 00:27:15,720 --> 00:27:17,800 Speaker 6: get to orbit. Okay, you can get to orbit with 466 00:27:17,840 --> 00:27:22,000 Speaker 6: a little single engine rocket. You can't get to orbit 467 00:27:22,020 --> 00:27:24,619 Speaker 6: with a nine engine, you know, Falcon 9 orbit. We 468 00:27:24,640 --> 00:27:27,600 Speaker 6: did that. You can't get a space capsule to work. 469 00:27:28,140 --> 00:27:30,639 Speaker 6: We did that. You can't go fly humans to the 470 00:27:30,680 --> 00:27:33,590 Speaker 6: space station. Dragon right now is the only, in the 471 00:27:33,619 --> 00:27:35,350 Speaker 6: Western world, the only way to get to our space 472 00:27:35,390 --> 00:27:39,130 Speaker 6: station is a SpaceX Dragon capsule. We did that. And 473 00:27:39,270 --> 00:27:43,770 Speaker 6: so the biggest rocket in the world is Starship. No 474 00:27:43,810 --> 00:27:46,950 Speaker 6: way can you do that. It's flying. It's about ready 475 00:27:46,970 --> 00:27:52,710 Speaker 6: to become aircraft-like operational. So when Elon's, people still call 476 00:27:52,750 --> 00:27:54,790 Speaker 6: it hype, and I don't because I've been through it 477 00:27:54,990 --> 00:27:58,659 Speaker 6: for almost 25 years. It's not hype. He's going to 478 00:27:58,700 --> 00:28:03,909 Speaker 6: build it. I believe if it's possible, it will be solved. 479 00:28:04,930 --> 00:28:08,050 Speaker 6: And it might take longer than Elon thinks, but he 480 00:28:08,070 --> 00:28:08,570 Speaker 6: will solve it. 481 00:28:09,510 --> 00:28:12,150 Speaker 4: What's the most surprising thing you ever saw Elon do? 482 00:28:13,109 --> 00:28:14,990 Speaker 6: I've talked about this. I think the one thing, I 483 00:28:15,030 --> 00:28:19,230 Speaker 6: was in the meeting when they presented the landing legs 484 00:28:19,490 --> 00:28:24,180 Speaker 6: for Starship, and they were super heavy. Starship is stainless steel. 485 00:28:24,260 --> 00:28:27,639 Speaker 6: It's a heavy machine. And anything that's secondary structure, like 486 00:28:27,680 --> 00:28:30,119 Speaker 6: landing legs, we need to get rid of it. He says, 487 00:28:30,140 --> 00:28:32,100 Speaker 6: we're going to get rid of the landing legs. We're 488 00:28:32,119 --> 00:28:36,700 Speaker 6: going to catch it in the air on chopsticks, like 489 00:28:36,740 --> 00:28:40,090 Speaker 6: catching a fly with chopsticks. And we all just rolled 490 00:28:40,130 --> 00:28:42,530 Speaker 6: our eyes like, this is crazy. There's just no way. 491 00:28:43,030 --> 00:28:46,270 Speaker 6: Did you all see it? Starship, the biggest rocket in 492 00:28:46,310 --> 00:28:49,709 Speaker 6: the world, came in and landed on the chopsticks. And 493 00:28:49,890 --> 00:28:51,560 Speaker 6: none of us, I wouldn't say none of us, but 494 00:28:51,620 --> 00:28:53,300 Speaker 6: some of us did not believe it could be done. 495 00:28:54,340 --> 00:28:58,240 Speaker 6: And it was done. And it's like, if it's possible, 496 00:28:58,730 --> 00:28:59,370 Speaker 6: it's solvable. 497 00:29:00,810 --> 00:29:03,730 Speaker 1: I have a sort of a nuts and bolts question. 498 00:29:03,830 --> 00:29:07,150 Speaker 3: Maybe I guess literally. But trade policy. 499 00:29:07,230 --> 00:29:10,290 Speaker 1: So obviously there is a view, okay, like one way 500 00:29:10,370 --> 00:29:14,690 Speaker 1: to accelerate demand for American production is tariffs and so forth. 501 00:29:15,280 --> 00:29:18,240 Speaker 1: I have also heard, however, from talking to other people 502 00:29:18,260 --> 00:29:21,580 Speaker 1: in the industrial space, that it cuts both ways. because 503 00:29:21,620 --> 00:29:25,160 Speaker 1: there are certain components that must be imported and therefore 504 00:29:25,270 --> 00:29:28,310 Speaker 1: raises the cost of certain input goods into this. 505 00:29:28,710 --> 00:29:30,150 Speaker 3: And I'm curious what you've. 506 00:29:29,950 --> 00:29:32,850 Speaker 1: Seen in your own world, the degree to which some 507 00:29:32,890 --> 00:29:34,910 Speaker 1: of these policies can perhaps cut. 508 00:29:34,770 --> 00:29:39,850 Speaker 3: In both directions. So this is a very nuanced answer. 509 00:29:40,280 --> 00:29:44,820 Speaker 3: and both administrations have gotten it slightly wrong. Okay. So 510 00:29:44,840 --> 00:29:50,640 Speaker 3: let me set the macro which most people don't understand. 511 00:29:52,400 --> 00:30:00,360 Speaker 3: Fundamentally there's four inputs to manufacturing. There's energy, There's labor, 512 00:30:00,540 --> 00:30:05,350 Speaker 3: there's capex financing costs, and then there's export tariffs. Okay. 513 00:30:06,720 --> 00:30:11,710 Speaker 3: In most circumstances, you know, and I've done this exercise, 514 00:30:12,230 --> 00:30:15,930 Speaker 3: if you dial our factory down to 0% labor costs, 0% energy, whatever, 515 00:30:16,610 --> 00:30:21,470 Speaker 3: Chinese imports are still three. I can make a component 516 00:30:21,490 --> 00:30:24,570 Speaker 3: for a customer. I can buy the raw material in 517 00:30:24,590 --> 00:30:26,810 Speaker 3: the United States, and it's three times the cost of 518 00:30:26,830 --> 00:30:30,520 Speaker 3: the component imported from China. For some of our commercial customers. 519 00:30:30,570 --> 00:30:30,850 Speaker 5: Yeah. 520 00:30:32,180 --> 00:30:35,090 Speaker 3: If I dial my business model down to zero. So 521 00:30:35,170 --> 00:30:38,870 Speaker 3: fundamentally what the tariffs meant to prevent is first principles, 522 00:30:38,970 --> 00:30:44,950 Speaker 3: the CCP is subsidizing energy, labor, capital, and export tariffs 523 00:30:45,630 --> 00:30:49,890 Speaker 3: to draw competency out, again, to the fourth turning comment, 524 00:30:50,250 --> 00:30:55,820 Speaker 3: to generate industrial power subsidized by the American consumer. Same 525 00:30:55,860 --> 00:30:59,220 Speaker 3: with drones. The reason why we are bad at drones 526 00:30:59,240 --> 00:31:03,850 Speaker 3: is not because DJI is the best software drone company, 527 00:31:04,370 --> 00:31:06,570 Speaker 3: but those things cost $ 60 and they sell them to 528 00:31:06,630 --> 00:31:13,590 Speaker 3: American consumers for $ 20. This is an explicit understanding that 529 00:31:14,270 --> 00:31:18,630 Speaker 3: China has always treated industrial policy like national security, and 530 00:31:18,650 --> 00:31:24,070 Speaker 3: since 1985, America has treated industrial policy like financial spreadsheet 531 00:31:24,230 --> 00:31:28,770 Speaker 3: returns for hedge funds. That's point number one. The intent 532 00:31:28,910 --> 00:31:33,870 Speaker 3: of every Biden or Trump subsidy or economic policy was 533 00:31:33,950 --> 00:31:38,730 Speaker 3: to give Americans an even playing field against a country 534 00:31:38,790 --> 00:31:42,140 Speaker 3: that is operating their industrial base like national security. That's 535 00:31:42,180 --> 00:31:47,260 Speaker 3: point number one. In terms of tariffs, it's complicated. The 536 00:31:47,300 --> 00:31:50,100 Speaker 3: reason why it's complicated is for two reasons. One is 537 00:31:50,780 --> 00:31:55,480 Speaker 3: you have to ring fence everything around China And in practice, 538 00:31:55,520 --> 00:31:57,560 Speaker 3: what happens is if you only ban China, but you 539 00:31:57,580 --> 00:32:03,020 Speaker 3: don't ban Singapore, some Chinese company will ship something to Singapore, 540 00:32:03,060 --> 00:32:05,240 Speaker 3: they'll call it Singapore, and it's the same impact on 541 00:32:05,270 --> 00:32:09,430 Speaker 3: the American workforce or industrial policy. The third thing is 542 00:32:09,750 --> 00:32:15,210 Speaker 3: that there's a definition issue here. So as an example, 543 00:32:15,230 --> 00:32:19,209 Speaker 3: raw materials from China, they're on the tariffs. If you 544 00:32:19,250 --> 00:32:21,110 Speaker 3: have a little bit of human labor in it, it's 545 00:32:21,150 --> 00:32:25,700 Speaker 3: an assembly. And that's negative against American businesses that are 546 00:32:25,720 --> 00:32:29,300 Speaker 3: trying to import assemblies from Mexico. So there's no, there 547 00:32:29,320 --> 00:32:31,840 Speaker 3: are trade-offs all over the place. The principle was correct, 548 00:32:31,900 --> 00:32:36,000 Speaker 3: which is provide Americans an even playing field against a 549 00:32:37,180 --> 00:32:40,760 Speaker 3: company that has a fake balance sheet and projects 6% 550 00:32:40,760 --> 00:32:44,580 Speaker 3: GDP growth and draws American capital in, American consumer capital in. 551 00:32:45,060 --> 00:32:47,140 Speaker 3: That has to get solved. It's not American suck at 552 00:32:47,160 --> 00:32:51,330 Speaker 3: manufacturing or software engineers not good at manufacturing autonomy. You're 553 00:32:51,370 --> 00:32:56,410 Speaker 3: subsidizing from 30% to 60%. Every implementation is like really 554 00:32:56,470 --> 00:33:00,230 Speaker 3: tough to do in terms of the nuance. The correct 555 00:33:00,270 --> 00:33:02,510 Speaker 3: thing to do, in my opinion, is what we just 556 00:33:02,530 --> 00:33:06,230 Speaker 3: did with drones and robots, which is it's a terrible 557 00:33:06,310 --> 00:33:13,250 Speaker 3: idea that every American police drone or military drone can 558 00:33:13,290 --> 00:33:16,610 Speaker 3: have any Chinese circuit board in it. Because obviously you 559 00:33:16,650 --> 00:33:19,430 Speaker 3: can then turn them into like, if we go to war, 560 00:33:19,450 --> 00:33:21,890 Speaker 3: you're going to zap the guy in the head. Same 561 00:33:21,930 --> 00:33:26,560 Speaker 3: thing with robots. I would like a $ 10, 000 laundry folding robot, 562 00:33:27,000 --> 00:33:31,020 Speaker 3: but industrial policy means that you're going to buy a 563 00:33:31,000 --> 00:33:34,460 Speaker 3: $ 30, 000 laundry folding robot because otherwise it's going to kill 564 00:33:34,480 --> 00:33:36,940 Speaker 3: you eventually, and that's bad leverage for the country. No, 565 00:33:36,960 --> 00:33:40,670 Speaker 3: I'm serious. Because they don't actually make them for $ 10, 000. 566 00:33:40,510 --> 00:33:43,590 Speaker 3: They make them for $ 30, 000, but the national policy says 567 00:33:43,610 --> 00:33:45,950 Speaker 3: I would much rather have every laundry folding robot in 568 00:33:46,010 --> 00:33:49,490 Speaker 3: America cost $ 10, 000 because the American consumer is the largest 569 00:33:49,550 --> 00:33:52,980 Speaker 3: capital allocator in the world. much bigger than Blackstone and BlackRock. 570 00:33:53,840 --> 00:34:00,240 Speaker 3: So the banning of components and assemblies to say you've 571 00:34:00,280 --> 00:34:04,200 Speaker 3: got to buy American-American allies and let the market correct 572 00:34:04,240 --> 00:34:11,890 Speaker 3: for cost is correct. Tariffs are a imperfect way to 573 00:34:11,969 --> 00:34:15,190 Speaker 3: do that, but the core principle for any administration of 574 00:34:15,310 --> 00:34:19,190 Speaker 3: leveling the playing field is correct. But each side has 575 00:34:19,230 --> 00:34:23,680 Speaker 3: gotten this materially wrong because it's complicated. And there's many 576 00:34:23,960 --> 00:34:28,560 Speaker 3: ways to commit fraud inside any regulatory system. Chris and Tom, oh. 577 00:34:28,980 --> 00:34:30,739 Speaker 5: Oh, I was going to say, we could go on 578 00:34:31,000 --> 00:34:32,560 Speaker 5: for a long time, but we're going to have to 579 00:34:32,580 --> 00:34:34,170 Speaker 5: leave it there because we've run out of time. But 580 00:34:34,210 --> 00:34:36,950 Speaker 5: Chris and Tom, thank you so much for coming on OddLots. 581 00:34:37,010 --> 00:34:37,780 Speaker 4: Really appreciate it. 582 00:34:37,830 --> 00:34:38,290 Speaker 2: Thank you. 583 00:34:53,860 --> 00:34:56,960 Speaker 5: That was our conversation with Chris Power and Tom Miller 584 00:34:57,040 --> 00:34:59,060 Speaker 5: recorded live here in L.A. 585 00:34:59,380 --> 00:35:01,960 Speaker 4: I'm Tracy Allaway. You can follow me at Tracy Allaway. 586 00:35:02,060 --> 00:35:04,920 Speaker 3: And I'm Jill Weisenthal. You can follow me at The Stalwart. 587 00:35:05,180 --> 00:35:08,660 Speaker 1: Follow our producers, Carmen Rodriguez at Carmen Armit, Dashiell Bennett 588 00:35:08,739 --> 00:35:12,000 Speaker 1: at Dashbot, Cale Brooks at Cale Brooks, and Kevin Lozano 589 00:35:12,200 --> 00:35:13,300 Speaker 1: at Kevin Lloyd Lozano. 590 00:35:13,710 --> 00:35:15,720 Speaker 5: And for more OddLots content, you should check out our 591 00:35:15,739 --> 00:35:19,259 Speaker 5: daily newsletter. You can find that at bloomberg.com forward slash OddLots. 592 00:35:19,400 --> 00:35:21,299 Speaker 1: And you can chat about all these topics 24-7 in 593 00:35:21,400 --> 00:35:25,220 Speaker 1: our Discord, discord.gg slash OddLots. 594 00:35:25,530 --> 00:35:28,210 Speaker 5: And if you enjoyed this conversation, then please like the 595 00:35:28,250 --> 00:35:30,930 Speaker 5: video or leave a comment or better yet, subscribe. 596 00:35:31,110 --> 00:35:43,160 Speaker 3: Thanks for watching and listening. Thank you.