1 00:00:02,480 --> 00:00:06,960 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. 2 00:00:07,920 --> 00:00:09,520 Speaker 2: Let me tell you we have a new star. 3 00:00:10,520 --> 00:00:14,640 Speaker 3: A star is born Elon mars Juthan Kennedy. 4 00:00:14,880 --> 00:00:18,480 Speaker 2: He is the Thomas Edison plus plus plus of our age. 5 00:00:18,640 --> 00:00:21,040 Speaker 3: Probably his whole life is from a position of insecurity. 6 00:00:21,079 --> 00:00:23,200 Speaker 2: I feel for the guy. I would say ninety eight 7 00:00:23,239 --> 00:00:26,560 Speaker 2: percent really appreciate what he does. But those two percent 8 00:00:26,640 --> 00:00:29,840 Speaker 2: that are nasty, they are I'll pay in four folds. 9 00:00:30,280 --> 00:00:32,280 Speaker 2: We are meant for great things in the United States 10 00:00:32,320 --> 00:00:34,560 Speaker 2: of America, and Elon reminds. 11 00:00:34,320 --> 00:00:34,640 Speaker 1: Us of that. 12 00:00:35,840 --> 00:00:37,400 Speaker 2: I'm very disappointed in Elon. 13 00:00:37,479 --> 00:00:39,600 Speaker 1: I've helped Elon a lot. 14 00:00:38,680 --> 00:00:39,400 Speaker 4: A lot. 15 00:00:46,560 --> 00:00:50,000 Speaker 2: Welcome to Elan Ink, Bloomberg's weekly podcast about Elon Musk. 16 00:00:50,040 --> 00:00:54,160 Speaker 2: It's Tuesday, June seventeenth. I'm your host, David Papadopolos. Now 17 00:00:54,200 --> 00:00:55,920 Speaker 2: we start this week's show with the latest and the 18 00:00:56,000 --> 00:00:59,800 Speaker 2: Musk Trump drama. The daytante that was just emerging when 19 00:00:59,800 --> 00:01:03,880 Speaker 2: we last recorded is taking hold, and you know, it 20 00:01:03,880 --> 00:01:07,039 Speaker 2: feels like it's just a matter of time before Musk 21 00:01:07,440 --> 00:01:10,120 Speaker 2: and Little X we'll be back in the Oval office, 22 00:01:10,200 --> 00:01:14,000 Speaker 2: sparring with reporters and playing on the floor. I'm sitting 23 00:01:14,040 --> 00:01:18,360 Speaker 2: here with Elon Inks stalwart Max Chaffkin, who's feeling I 24 00:01:18,400 --> 00:01:22,279 Speaker 2: suspect a little vindicated to go over the latest there, Max. 25 00:01:22,440 --> 00:01:24,080 Speaker 2: Welcome to you, sir, David. 26 00:01:24,240 --> 00:01:24,959 Speaker 1: I told you so. 27 00:01:27,520 --> 00:01:30,479 Speaker 2: All week. You've been prepping that line. Max will also 28 00:01:30,560 --> 00:01:32,880 Speaker 2: give us an update on the much anticipated launch of 29 00:01:32,880 --> 00:01:36,919 Speaker 2: Tessel's ROBOTAXI. Now you'll remember it was slated for last week. 30 00:01:37,240 --> 00:01:40,600 Speaker 2: We were all so excited, and then it was postponed 31 00:01:40,640 --> 00:01:43,000 Speaker 2: to this week as Musk and co. Scrambled to get 32 00:01:43,040 --> 00:01:47,319 Speaker 2: it ready. Not in auspicious beginning. And then over at XAI, 33 00:01:47,600 --> 00:01:50,680 Speaker 2: Musk is raising a ton of money, even more than 34 00:01:50,720 --> 00:01:51,960 Speaker 2: we had previously reported. 35 00:01:52,480 --> 00:01:53,560 Speaker 1: But Xai is. 36 00:01:53,520 --> 00:01:56,880 Speaker 2: Also burning through a lot of money, just reams and 37 00:01:56,960 --> 00:02:00,480 Speaker 2: reams of it in billion dollar clips in ace. Bloomberg 38 00:02:00,480 --> 00:02:03,880 Speaker 2: Credit Markets reporter Carmen Arroyo will join us later tell 39 00:02:03,920 --> 00:02:09,160 Speaker 2: us all about that. But Max, Elon and Donald are 40 00:02:09,240 --> 00:02:13,160 Speaker 2: beck so much so that my god, did I actually 41 00:02:13,400 --> 00:02:17,960 Speaker 2: hear or read an apology come out of Elon Musk's 42 00:02:18,800 --> 00:02:20,760 Speaker 2: mouth that was this? Did this happen? 43 00:02:21,400 --> 00:02:21,720 Speaker 1: Elon? 44 00:02:21,720 --> 00:02:23,760 Speaker 2: I didn't know he I didn't know he did that. 45 00:02:24,240 --> 00:02:28,040 Speaker 4: I regret some of my posts about President at Real 46 00:02:28,120 --> 00:02:29,160 Speaker 4: Donald Trump last week. 47 00:02:29,320 --> 00:02:31,800 Speaker 1: They went too far. He said WHOA on June eleventh, 48 00:02:31,880 --> 00:02:34,320 Speaker 1: and you're right, an unusual apology, although. 49 00:02:34,040 --> 00:02:35,760 Speaker 2: He has I mean, I guess maybe he could say, well, 50 00:02:35,800 --> 00:02:38,480 Speaker 2: it wasn't really an apology. If you regret something or 51 00:02:38,520 --> 00:02:39,880 Speaker 2: you apologize, it's not. 52 00:02:39,919 --> 00:02:43,800 Speaker 4: Quite a you know, full on apology. But it's pretty 53 00:02:43,840 --> 00:02:47,239 Speaker 4: darn close. And I think I said this last week, 54 00:02:47,680 --> 00:02:49,000 Speaker 4: that is what it's going to take. 55 00:02:49,080 --> 00:02:53,239 Speaker 1: And I don't know that this roveling. Yeah, I mean. 56 00:02:53,080 --> 00:02:57,639 Speaker 4: He accused Trump of unspeakable crimes without basis, suggested he 57 00:02:57,680 --> 00:02:59,760 Speaker 4: should be impeached. You know, he said a lot of 58 00:03:00,560 --> 00:03:04,120 Speaker 4: excuse my French, like really bad, and so he's gonna 59 00:03:04,160 --> 00:03:06,080 Speaker 4: have to do some of this to if he wants 60 00:03:06,120 --> 00:03:09,280 Speaker 4: to get back into Trump's good graces. 61 00:03:09,480 --> 00:03:13,240 Speaker 2: And do we believe it is working. It looks like 62 00:03:13,280 --> 00:03:18,040 Speaker 2: Trump on his end continues to also move a bit 63 00:03:18,200 --> 00:03:21,160 Speaker 2: towards Musk, like, hey, maybe this is going to be okay. 64 00:03:21,919 --> 00:03:24,320 Speaker 1: Trump's just not really saying anything. 65 00:03:24,040 --> 00:03:27,079 Speaker 4: Beyond like they've talked, and I think last week we 66 00:03:27,480 --> 00:03:29,679 Speaker 4: went over that answer that Trump gave when he was 67 00:03:29,680 --> 00:03:32,320 Speaker 4: asked about Elon Musk. I mean, it's basically been pretty 68 00:03:32,400 --> 00:03:35,640 Speaker 4: quiet between the two of them, which honestly feels like progress. 69 00:03:35,680 --> 00:03:36,880 Speaker 1: They're not feuding in public. 70 00:03:37,200 --> 00:03:41,400 Speaker 4: There have also been i'd say a couple of little 71 00:03:41,440 --> 00:03:44,480 Speaker 4: things that you could interpret as sort. 72 00:03:44,360 --> 00:03:47,240 Speaker 1: Of bullish signs for the Elon Trump relationship. 73 00:03:46,800 --> 00:03:51,600 Speaker 4: Such as well, I believe it was last week Dune thirteenth, 74 00:03:51,640 --> 00:03:55,440 Speaker 4: Bloomberg reported on a kind of modest change that NITSA, 75 00:03:55,600 --> 00:03:58,800 Speaker 4: that's the highway regulator that we mentioned last week, is 76 00:03:59,240 --> 00:04:03,040 Speaker 4: making for rivalless car companies. Essentially, again, this is like 77 00:04:03,200 --> 00:04:05,400 Speaker 4: very much a small procedural thing. 78 00:04:05,760 --> 00:04:11,280 Speaker 2: Yeah, helps TESLA, and I also suppose just you know, directionally, 79 00:04:11,480 --> 00:04:15,120 Speaker 2: it certainly helps. And it's probably at a moment when 80 00:04:15,240 --> 00:04:17,960 Speaker 2: that relationship appeared as rocky as it did, it certainly 81 00:04:18,080 --> 00:04:19,880 Speaker 2: looks like a good sign. So this is a really 82 00:04:19,920 --> 00:04:22,200 Speaker 2: small change it But so when I read the headline, 83 00:04:22,200 --> 00:04:23,480 Speaker 2: it was like, wow, this is big. 84 00:04:23,560 --> 00:04:27,400 Speaker 4: Okay, So for cars that do not have pedals or 85 00:04:27,400 --> 00:04:31,359 Speaker 4: steering wheel, automakers have to seek an exemption from NITSA. 86 00:04:31,680 --> 00:04:34,120 Speaker 4: That's the highway regulator that I mentioned, the National Highway 87 00:04:34,120 --> 00:04:37,000 Speaker 4: Traffic Safety Administration. It's part of the Department of Transportation. 88 00:04:37,200 --> 00:04:39,960 Speaker 4: It's an agency that Elon Musk has tangled with over 89 00:04:40,000 --> 00:04:40,480 Speaker 4: the years. 90 00:04:40,880 --> 00:04:42,240 Speaker 1: Nitsa said, they're going. 91 00:04:42,040 --> 00:04:47,000 Speaker 4: To streamline this process so that the approval decisions are 92 00:04:47,040 --> 00:04:51,840 Speaker 4: made within months rather than years. So, like, I don't know, 93 00:04:51,960 --> 00:04:54,320 Speaker 4: I guess that's good, but it's not an approval. It's 94 00:04:54,400 --> 00:04:58,839 Speaker 4: just a suggestion that they will make decisions about approval 95 00:04:58,960 --> 00:05:01,520 Speaker 4: or lack of approval more quickly than they've been making 96 00:05:01,520 --> 00:05:04,200 Speaker 4: them before. It's also one that doesn't really have bearing 97 00:05:04,600 --> 00:05:07,599 Speaker 4: on this Robotaxi launch that we're talking about in Austin 98 00:05:07,720 --> 00:05:10,839 Speaker 4: because those cars, of course, do have pedals and steering wheels. 99 00:05:10,880 --> 00:05:11,120 Speaker 2: They do. 100 00:05:11,200 --> 00:05:12,640 Speaker 1: They're just normal cars. 101 00:05:13,000 --> 00:05:16,320 Speaker 4: So I'm not one hundred percent sure that these regulations 102 00:05:16,320 --> 00:05:20,239 Speaker 4: that NITSA is talking about are even related to what 103 00:05:20,240 --> 00:05:22,599 Speaker 4: what Elon Musk is doing. Obviously, Elon Musk is doing 104 00:05:22,640 --> 00:05:24,960 Speaker 4: this launch without this NITSA approval. 105 00:05:25,080 --> 00:05:26,839 Speaker 1: So again, I think. 106 00:05:26,720 --> 00:05:29,200 Speaker 4: It's like a positive sign in the sense that they're 107 00:05:29,240 --> 00:05:31,920 Speaker 4: doing this in some sense in public. The Trump and 108 00:05:32,160 --> 00:05:35,280 Speaker 4: administration has to know that this will be interpreted as 109 00:05:35,320 --> 00:05:38,359 Speaker 4: a sort of olive branch to Elon Musk, and so 110 00:05:38,480 --> 00:05:39,400 Speaker 4: I think that's how. 111 00:05:39,279 --> 00:05:41,800 Speaker 1: We should interpret it as well. Yeah, that is, but 112 00:05:41,839 --> 00:05:43,400 Speaker 1: it's a small olive branch. 113 00:05:44,200 --> 00:05:46,520 Speaker 2: A got it, Yeah, you keep saying that I got it. 114 00:05:46,920 --> 00:05:48,760 Speaker 2: We're going to talk a little bit more about that 115 00:05:49,200 --> 00:05:52,800 Speaker 2: Robotaxi launch in a second, but before we do, I 116 00:05:52,839 --> 00:05:57,240 Speaker 2: know that you've been out there working on a little 117 00:05:57,320 --> 00:06:01,440 Speaker 2: new something you've got, because you know, given how Musk 118 00:06:01,600 --> 00:06:04,720 Speaker 2: is coming rushing back to Trump's arms, and you were 119 00:06:04,720 --> 00:06:07,279 Speaker 2: trying to create like a little bit of an acronym, 120 00:06:07,320 --> 00:06:09,240 Speaker 2: a little bit of thing like what do we call this? 121 00:06:09,320 --> 00:06:12,000 Speaker 4: All right, hang on, just indulge me for a second here, David, 122 00:06:12,040 --> 00:06:14,760 Speaker 4: because as we've talked about, a couple of weeks ago, 123 00:06:14,800 --> 00:06:17,400 Speaker 4: I wrote a piece saying, don't bet on the Elon 124 00:06:17,480 --> 00:06:18,520 Speaker 4: Musk Trump breakup. 125 00:06:18,760 --> 00:06:19,840 Speaker 1: It looked really smart for. 126 00:06:19,880 --> 00:06:21,720 Speaker 2: Me all and then we all laughed, and then we 127 00:06:21,800 --> 00:06:24,560 Speaker 2: laughed at me and laughed in laugh. 128 00:06:24,440 --> 00:06:27,320 Speaker 1: And now I am once again my take. 129 00:06:27,600 --> 00:06:30,479 Speaker 4: My only regret is not sticking You're the king again, 130 00:06:30,640 --> 00:06:31,839 Speaker 4: not sticking. 131 00:06:31,360 --> 00:06:32,000 Speaker 1: To my take. 132 00:06:32,400 --> 00:06:35,600 Speaker 4: When Elon was hurling insults and it seemed like they 133 00:06:35,600 --> 00:06:37,080 Speaker 4: were never gonna speak again. 134 00:06:36,839 --> 00:06:38,799 Speaker 2: That was a moment of weakness on your part. 135 00:06:39,040 --> 00:06:42,880 Speaker 1: Yeah, definitely. But I do think there's a lesson here. 136 00:06:43,040 --> 00:06:44,200 Speaker 1: And I've been. 137 00:06:44,080 --> 00:06:46,919 Speaker 4: Of course, following a lot of the discussion as you 138 00:06:47,040 --> 00:06:50,919 Speaker 4: have on Wall Street and among investors about how to 139 00:06:50,960 --> 00:06:54,719 Speaker 4: think about Trump's Bellaicoast language on trade. You, David, are 140 00:06:54,760 --> 00:06:58,200 Speaker 4: probably familiar with the taco acronym that has been thrown 141 00:06:58,320 --> 00:07:01,400 Speaker 4: around a lot. It stands for Trump always chickens out. 142 00:07:01,400 --> 00:07:04,440 Speaker 4: This is the idea that if Trump says I'm going 143 00:07:04,520 --> 00:07:06,799 Speaker 4: to put one hundred and fifty percent tariffs on China, 144 00:07:07,160 --> 00:07:09,800 Speaker 4: Wall Street traders kind of discount that because they think, hey, 145 00:07:09,840 --> 00:07:10,760 Speaker 4: he's never going to do it. 146 00:07:11,040 --> 00:07:13,360 Speaker 1: So I think we need one for Musk and Trump, 147 00:07:13,720 --> 00:07:15,040 Speaker 1: and I propose. 148 00:07:15,120 --> 00:07:19,280 Speaker 2: Mamma Wood, Mamma Wood, Mamma Wood. 149 00:07:19,400 --> 00:07:23,680 Speaker 4: Yeah, Musk always makes up with Trump. 150 00:07:24,160 --> 00:07:25,640 Speaker 2: Mamma woo, Mamma Wood. 151 00:07:25,840 --> 00:07:28,440 Speaker 1: So that's all you need to know. I kind of 152 00:07:28,600 --> 00:07:31,000 Speaker 1: like my take off the same way that Taco has 153 00:07:31,040 --> 00:07:31,480 Speaker 1: taken off. 154 00:07:31,560 --> 00:07:34,440 Speaker 2: I mean taco. There's a simplicity to taco, which is 155 00:07:34,480 --> 00:07:38,360 Speaker 2: fun and by the way, tacos are also delicious. Mamma Wood. 156 00:07:38,360 --> 00:07:39,920 Speaker 2: First of all, I don't even know that you're pronounce 157 00:07:40,000 --> 00:07:42,800 Speaker 2: if you're really spelling it m A M W T. 158 00:07:43,200 --> 00:07:44,960 Speaker 2: I don't know that you're pronouncing it correctly. 159 00:07:45,560 --> 00:07:46,640 Speaker 1: Should we pronounce I think. 160 00:07:46,520 --> 00:07:48,640 Speaker 2: It should be like that brand of shoe, those that 161 00:07:48,760 --> 00:07:52,520 Speaker 2: hiking gearts. You should be like mammoot man like w is 162 00:07:52,600 --> 00:07:56,360 Speaker 2: essentially silent. Yeah, you're right, but I say, if you're 163 00:07:56,360 --> 00:07:58,440 Speaker 2: going to go this route and go like all weird 164 00:07:58,440 --> 00:08:02,960 Speaker 2: and incomprehensible, keep on going. We need whack your wilder 165 00:08:03,120 --> 00:08:06,600 Speaker 2: more incomprehensible and longer. Maybe we go to them. Maybe 166 00:08:06,600 --> 00:08:08,240 Speaker 2: we have people send ideas to the mailbag. 167 00:08:08,320 --> 00:08:10,960 Speaker 4: Yeah, listeners, let us know if you like mamut or 168 00:08:11,000 --> 00:08:13,840 Speaker 4: mamma what or however you want to pronounce it. And also, yeah, 169 00:08:13,840 --> 00:08:16,560 Speaker 4: if you've got a better acronym, maybe one that ideally 170 00:08:16,640 --> 00:08:19,440 Speaker 4: is a word, maybe one that has the correct amount 171 00:08:19,440 --> 00:08:19,800 Speaker 4: of valel. 172 00:08:19,920 --> 00:08:22,360 Speaker 2: There's no way it's pronounced mamma wood. It's just can't 173 00:08:22,440 --> 00:08:23,280 Speaker 2: be memoot. 174 00:08:23,440 --> 00:08:25,640 Speaker 1: Give us a shout elon ink at Bloomberg dot net. 175 00:08:25,680 --> 00:08:28,120 Speaker 4: Tell tell us what you think the acronym should be, 176 00:08:28,520 --> 00:08:31,000 Speaker 4: and really you like how you're thinking about this Trump 177 00:08:31,080 --> 00:08:32,640 Speaker 4: Musk relationship these days. 178 00:08:32,559 --> 00:08:36,880 Speaker 2: The acronym aside the conceit and the pronunciation of the 179 00:08:36,880 --> 00:08:39,120 Speaker 2: acronym a side the conceit is a good one. It 180 00:08:39,200 --> 00:08:44,719 Speaker 2: seems like Musk has certainly come to appreciate that. As 181 00:08:44,840 --> 00:08:47,520 Speaker 2: much as Trump has to lose in a breakup, he 182 00:08:47,960 --> 00:08:50,040 Speaker 2: elon Musk is a hell of a lot more to lose, 183 00:08:50,160 --> 00:08:53,280 Speaker 2: and so hence Musk always makes up with Trump. 184 00:08:53,320 --> 00:08:55,760 Speaker 4: There we are, yeah, and you know I mentioned the 185 00:08:55,800 --> 00:08:58,960 Speaker 4: self driving rules. There are other signs that Trump is 186 00:08:59,000 --> 00:09:04,160 Speaker 4: sort of not done extracting punishment, or that there won't 187 00:09:04,200 --> 00:09:07,600 Speaker 4: be repercussions for Elon Musk. Reuters reported the day after 188 00:09:07,640 --> 00:09:11,440 Speaker 4: the apology that this Golden Dome project that Trump has 189 00:09:11,480 --> 00:09:15,240 Speaker 4: been talking about, this essentially a missile shield similar to 190 00:09:15,280 --> 00:09:18,800 Speaker 4: the Iron Dome that Israel has Trump wants to builds 191 00:09:19,600 --> 00:09:22,000 Speaker 4: in the US. Of course, gold there had been a 192 00:09:22,040 --> 00:09:25,920 Speaker 4: lot of reporting suggesting that SpaceX would be a major 193 00:09:25,960 --> 00:09:30,320 Speaker 4: player in that. Reuter's reporting on the twelfth that the 194 00:09:30,360 --> 00:09:33,440 Speaker 4: Department of Defense was looking to change the architecture of 195 00:09:33,520 --> 00:09:35,520 Speaker 4: the Golden Dome essentially in a way. 196 00:09:35,400 --> 00:09:36,800 Speaker 1: That would cut out SpaceX. 197 00:09:36,840 --> 00:09:39,760 Speaker 4: So they'd been imagining this sort of satellite array that's 198 00:09:39,760 --> 00:09:42,600 Speaker 4: obviously a great job for Elon Musk, and they were 199 00:09:42,600 --> 00:09:45,360 Speaker 4: looking at other solutions. And there's a suggest in the 200 00:09:45,400 --> 00:09:49,280 Speaker 4: story that the feud between Trump and Musk might open 201 00:09:49,280 --> 00:09:52,679 Speaker 4: the door for maybe opponents of this plan to suggest 202 00:09:52,679 --> 00:09:54,360 Speaker 4: their own ideas, so there might be more of a 203 00:09:54,400 --> 00:09:58,880 Speaker 4: competition for which contractors are going to get this contract 204 00:09:58,920 --> 00:10:01,480 Speaker 4: if it indeed happens, which, of course, they haven't appropriated 205 00:10:01,480 --> 00:10:01,880 Speaker 4: the money yet. 206 00:10:01,880 --> 00:10:05,360 Speaker 2: And I'm sorry, say what exactly what kind of money 207 00:10:05,400 --> 00:10:07,520 Speaker 2: are we talking about here? This would be an incredibly 208 00:10:07,720 --> 00:10:12,040 Speaker 2: rich project with incredibly large I mean. 209 00:10:12,080 --> 00:10:13,280 Speaker 1: Billions of dollars. 210 00:10:13,520 --> 00:10:17,679 Speaker 4: Certainly, I think the overall amount of money appropriated for 211 00:10:17,720 --> 00:10:20,360 Speaker 4: this in the it's there's a there's an item in 212 00:10:20,400 --> 00:10:22,439 Speaker 4: the big beautiful bill. Off the top of my head, 213 00:10:22,480 --> 00:10:26,079 Speaker 4: I think it's twenty five billion. Well yeah, but jumps. 214 00:10:26,120 --> 00:10:28,400 Speaker 4: So it's not clear that that that will survive the 215 00:10:28,440 --> 00:10:32,160 Speaker 4: Senate thing. Reuter's mentions that defense experts think that the 216 00:10:32,200 --> 00:10:34,240 Speaker 4: overall costs of this thing will be more like one 217 00:10:34,280 --> 00:10:37,520 Speaker 4: hundred and seventy five billion once it's done and dusted, 218 00:10:37,600 --> 00:10:40,440 Speaker 4: So that would just be the beginning of the Golden Dome. 219 00:10:40,960 --> 00:10:44,080 Speaker 2: But that's before Doge goes through. When Doze is done, yeah, 220 00:10:44,120 --> 00:10:46,200 Speaker 2: it's going to be down to about a couple billion dollars. 221 00:10:46,360 --> 00:10:48,880 Speaker 4: But in any case, it's it's sort of a suggestion 222 00:10:49,000 --> 00:10:52,880 Speaker 4: that you know, there would be a competition, and that 223 00:10:53,160 --> 00:10:56,280 Speaker 4: SpaceX wouldn't necessarily have a leg up in that competition. 224 00:10:57,120 --> 00:10:59,040 Speaker 2: Yeah, So another word to Elon if you want part 225 00:10:59,080 --> 00:11:05,400 Speaker 2: of the Golden Dome. Ma moot moot, Yeah, right, okay. Robotaxi, 226 00:11:05,760 --> 00:11:08,720 Speaker 2: we were supposed to get it max the soft launch, 227 00:11:08,920 --> 00:11:11,120 Speaker 2: as we had discussed last week. It was supposed to 228 00:11:11,160 --> 00:11:13,200 Speaker 2: come Thursday or Friday last week, and then at some 229 00:11:13,240 --> 00:11:15,319 Speaker 2: point we got our heads up now no, no, no, no, 230 00:11:15,960 --> 00:11:17,600 Speaker 2: not quite ready. What's going on. 231 00:11:17,760 --> 00:11:19,479 Speaker 1: I feel like we need another acronym. 232 00:11:19,600 --> 00:11:25,719 Speaker 4: That's like uh madra Musk always delays Robotaxi announcements. 233 00:11:25,920 --> 00:11:27,880 Speaker 2: If we come up enough with enough of these things, 234 00:11:28,080 --> 00:11:30,440 Speaker 2: we'll just do the entire show and acronym. We won't 235 00:11:30,480 --> 00:11:31,920 Speaker 2: have to say other words. 236 00:11:31,960 --> 00:11:35,160 Speaker 4: We talked last week about the prospect that there would 237 00:11:35,200 --> 00:11:38,640 Speaker 4: be a Robotaxi announcement as early as the end of 238 00:11:38,720 --> 00:11:41,560 Speaker 4: last week. That's what we had heard from people inside 239 00:11:41,600 --> 00:11:45,400 Speaker 4: of Tesla. We being Bloomberg. Musk put out of tweet 240 00:11:45,480 --> 00:11:48,720 Speaker 4: essentially saying they're aiming for the twenty second. 241 00:11:48,679 --> 00:11:51,280 Speaker 1: Of June, which is I believe it's Sunday. 242 00:11:51,440 --> 00:11:53,840 Speaker 2: So not only is the launch itself a soft launch, 243 00:11:53,960 --> 00:11:56,959 Speaker 2: but the date itself it was a little. 244 00:11:56,679 --> 00:12:00,440 Speaker 4: Fuzzy squish, And then that he thought what was definitely 245 00:12:00,440 --> 00:12:03,560 Speaker 4: gonna happen was that they would celebrate his birthday, which 246 00:12:03,600 --> 00:12:06,559 Speaker 4: is the twenty years by driving by no, but by 247 00:12:06,640 --> 00:12:09,360 Speaker 4: driving a robotaxi from the factory to a customer's home. 248 00:12:09,640 --> 00:12:12,319 Speaker 2: Now, I tell that's a good set. Well, we're there'll 249 00:12:12,360 --> 00:12:14,640 Speaker 2: be a cake. I mean, what then you get this? 250 00:12:14,920 --> 00:12:17,400 Speaker 4: I am not holding my breath for any of this, 251 00:12:17,840 --> 00:12:21,120 Speaker 4: although I feel like the factory stunt, that's one that 252 00:12:21,480 --> 00:12:24,640 Speaker 4: feels like more plausible that they could actually pull off. 253 00:12:25,160 --> 00:12:29,200 Speaker 4: Musk has been promising these robotaxi launches for years, and 254 00:12:29,320 --> 00:12:33,480 Speaker 4: so it definitely feels like Tesla is more intent on 255 00:12:33,640 --> 00:12:38,680 Speaker 4: actually doing this, actually having something. And we've heard details 256 00:12:38,960 --> 00:12:43,760 Speaker 4: ten cars in Austin, we've seen some cars even driving around. 257 00:12:44,160 --> 00:12:47,280 Speaker 4: But I mean, honestly, who knows, and and so I 258 00:12:47,320 --> 00:12:50,640 Speaker 4: would not be surprised if there's something that happens, something 259 00:12:50,640 --> 00:12:54,079 Speaker 4: that could be plausibly called a robotaxi launch as soon 260 00:12:54,120 --> 00:12:56,840 Speaker 4: as Sunday. It's not going to be very big. I 261 00:12:56,880 --> 00:12:59,120 Speaker 4: don't think regular people are going to be able to 262 00:12:59,120 --> 00:13:02,000 Speaker 4: get in these robot teschsxs. I think it's going to 263 00:13:02,080 --> 00:13:06,920 Speaker 4: be like basically pretty minimal, but allowing Elon Musk to 264 00:13:06,920 --> 00:13:09,600 Speaker 4: claim some sort of win, and that could be again 265 00:13:09,800 --> 00:13:13,240 Speaker 4: giving some Tesla insiders or something a ride in a 266 00:13:13,320 --> 00:13:17,120 Speaker 4: quote unquote driverless car, or even just driving one of 267 00:13:17,160 --> 00:13:20,040 Speaker 4: these cars to one customer's home. So we're going to 268 00:13:20,080 --> 00:13:23,280 Speaker 4: see something, but the date just keeps moving and at 269 00:13:23,320 --> 00:13:25,360 Speaker 4: this point I'm not totally sure when we're going to 270 00:13:25,400 --> 00:13:25,680 Speaker 4: see it. 271 00:13:31,240 --> 00:13:36,080 Speaker 2: Okay, Now we are joined by Ace Bloomberg, Credit Markets 272 00:13:36,120 --> 00:13:39,280 Speaker 2: reporter Carmen and Royo Carmen. Fantastic to have you on 273 00:13:39,320 --> 00:13:39,680 Speaker 2: the show. 274 00:13:40,040 --> 00:13:42,040 Speaker 1: Thank you so much, David, So Carmon, you have. 275 00:13:42,000 --> 00:13:44,680 Speaker 2: A great scoop out today, you and Jill Shaw on 276 00:13:44,920 --> 00:13:47,920 Speaker 2: Xai and all the money it's raising and all the 277 00:13:47,960 --> 00:13:50,400 Speaker 2: money it's spending at the same time. Tell us about it. 278 00:13:50,760 --> 00:13:53,480 Speaker 3: Yeah, sure. So Xai is out in the market right 279 00:13:53,520 --> 00:13:56,960 Speaker 3: now trying to basically raise a little bit under a 280 00:13:56,960 --> 00:13:59,560 Speaker 3: ten billion, so nine point three billion, yes. 281 00:13:59,480 --> 00:14:02,720 Speaker 2: So to be clear, we already knew, I believe we 282 00:14:02,760 --> 00:14:05,479 Speaker 2: had previously reported that they were seeking to raise. 283 00:14:05,520 --> 00:14:07,959 Speaker 3: Five billion of debt. So what's new is that they're 284 00:14:08,040 --> 00:14:11,800 Speaker 3: racing also equity as part of the same fund raising process. 285 00:14:11,800 --> 00:14:14,920 Speaker 2: Five billion debt and four point three billion in equity. 286 00:14:15,520 --> 00:14:17,080 Speaker 3: A lot of money, a lot of money. 287 00:14:17,720 --> 00:14:18,920 Speaker 2: And how's it going? 288 00:14:19,720 --> 00:14:22,080 Speaker 3: I mean, the commitments on the debt are dude today, 289 00:14:22,200 --> 00:14:23,880 Speaker 3: So we'll know probably at the end of the day 290 00:14:23,960 --> 00:14:26,720 Speaker 3: how the dead process is going. But investors, so. 291 00:14:26,760 --> 00:14:30,120 Speaker 2: Max, sorry to interpret this is I already immediately already 292 00:14:30,160 --> 00:14:34,560 Speaker 2: going back to man Mood. Right, you need to sell 293 00:14:34,760 --> 00:14:36,480 Speaker 2: a lot of debt, you need to sell a lot 294 00:14:36,520 --> 00:14:39,240 Speaker 2: of equity. You need to show investors you're in the 295 00:14:39,240 --> 00:14:41,560 Speaker 2: good graces of Donald Trump. Man Mood, I think you 296 00:14:41,600 --> 00:14:43,400 Speaker 2: missed Man Mood. Carmen man Mood. 297 00:14:43,360 --> 00:14:47,920 Speaker 1: Must always makes up with Trump. Oh okay, how we're 298 00:14:47,960 --> 00:14:48,760 Speaker 1: going to make it happen? 299 00:14:49,560 --> 00:14:55,400 Speaker 2: Spreads right, But you if you're going to be raising 300 00:14:55,480 --> 00:14:58,720 Speaker 2: nine point three billion, you can't be Splitsville with Donald Trump. 301 00:14:58,720 --> 00:14:59,400 Speaker 2: I wouldn't think. 302 00:14:59,680 --> 00:14:59,880 Speaker 1: Yeah. 303 00:15:00,240 --> 00:15:02,440 Speaker 2: But anyway, so the debt, the bids on the debt 304 00:15:02,520 --> 00:15:04,520 Speaker 2: are due today. The books are supposed to close today, 305 00:15:04,520 --> 00:15:06,480 Speaker 2: and so we should have that that should be locked 306 00:15:06,480 --> 00:15:07,360 Speaker 2: down by the end of the day. 307 00:15:07,480 --> 00:15:09,080 Speaker 3: Yeah, the commitments should be out today. 308 00:15:09,160 --> 00:15:13,000 Speaker 2: Yeah, okay. And then on the equity side, any sense 309 00:15:13,000 --> 00:15:13,640 Speaker 2: of how it's going. 310 00:15:14,160 --> 00:15:17,240 Speaker 3: Apparently what they've disclosed is basically that they're working on 311 00:15:17,280 --> 00:15:19,880 Speaker 3: the four point three billion fundraise and they're closed to 312 00:15:19,920 --> 00:15:20,960 Speaker 3: being finalized. 313 00:15:21,160 --> 00:15:23,800 Speaker 2: And this isn't just like money that Musk himself is. 314 00:15:24,000 --> 00:15:26,000 Speaker 3: We don't know who's the what we're the source of 315 00:15:26,040 --> 00:15:28,560 Speaker 3: the funds is, but it's been put together quick from 316 00:15:28,560 --> 00:15:29,040 Speaker 3: what we know. 317 00:15:29,760 --> 00:15:33,760 Speaker 2: So okay, so that's what they're bringing in and what 318 00:15:33,920 --> 00:15:35,160 Speaker 2: is going out. 319 00:15:35,640 --> 00:15:40,160 Speaker 3: Yeah, so they have an incredibly expensive program, like most 320 00:15:40,200 --> 00:15:44,440 Speaker 3: AI companies do. They're just this year they expect to 321 00:15:44,480 --> 00:15:48,600 Speaker 3: invest tenvillion with capital expenditures. So basically all they're racing, 322 00:15:48,640 --> 00:15:51,440 Speaker 3: they're going to be spending. And so when you look 323 00:15:51,480 --> 00:15:53,480 Speaker 3: at some of the figures, like a little bit more 324 00:15:53,520 --> 00:15:55,920 Speaker 3: in depth, like the levered cash flow, which is basically 325 00:15:56,200 --> 00:15:58,800 Speaker 3: what's left once you pay everything else, they have a 326 00:15:58,840 --> 00:16:03,600 Speaker 3: negative thirteen billion. So they're really not being profitable right now. 327 00:16:04,240 --> 00:16:06,640 Speaker 2: No, I mean wait a minute, so they are. They're 328 00:16:06,640 --> 00:16:09,880 Speaker 2: going to burn through more than a billion dollars each 329 00:16:09,920 --> 00:16:11,000 Speaker 2: and every month this year. 330 00:16:11,280 --> 00:16:14,360 Speaker 3: Yeah, I mean built in data centers and training AM 331 00:16:14,360 --> 00:16:15,479 Speaker 3: models is expensive. 332 00:16:15,880 --> 00:16:16,240 Speaker 2: Max. 333 00:16:16,560 --> 00:16:19,000 Speaker 4: I mean so in some ways, like Carmen is saying, 334 00:16:19,360 --> 00:16:21,680 Speaker 4: this is not hugely surprising, because. 335 00:16:21,400 --> 00:16:23,400 Speaker 2: This is the day of vindication for you, Max today, 336 00:16:23,400 --> 00:16:25,840 Speaker 2: because not only on the Musk Trump thing, but also 337 00:16:25,920 --> 00:16:29,760 Speaker 2: you've been hounding the tat, hounding the table about how 338 00:16:30,000 --> 00:16:32,480 Speaker 2: stupidly expensive it is to build out AI. 339 00:16:33,080 --> 00:16:35,320 Speaker 4: I mean, the thing that jumps out of you in 340 00:16:35,400 --> 00:16:37,600 Speaker 4: the story is not so much the cost, but the 341 00:16:37,640 --> 00:16:40,120 Speaker 4: fact that there's like no revenue, I mean no revenue 342 00:16:40,120 --> 00:16:41,960 Speaker 4: coming in, right, there's some. 343 00:16:42,000 --> 00:16:45,800 Speaker 3: Revenue coming in, like they have no they like for 344 00:16:45,880 --> 00:16:49,479 Speaker 3: this year they project like five hundred million revenue. 345 00:16:49,120 --> 00:16:52,800 Speaker 2: Substantially five hundred million comes in, and again, how much 346 00:16:52,880 --> 00:16:54,640 Speaker 2: goes out and expenses just. 347 00:16:54,600 --> 00:16:56,160 Speaker 3: On capex more than ten billion. 348 00:16:56,680 --> 00:16:59,760 Speaker 4: Okay, so you know it's Look, there are a lot 349 00:16:59,800 --> 00:17:03,200 Speaker 4: of people who really believe that AI is this huge 350 00:17:03,240 --> 00:17:08,159 Speaker 4: game changer. On the other hand, this space in particular 351 00:17:08,320 --> 00:17:13,399 Speaker 4: is very capital intensive. It's also very competitive. I do wonder, 352 00:17:14,000 --> 00:17:16,679 Speaker 4: like Carmen, the story kind of hints at signs that 353 00:17:16,760 --> 00:17:20,760 Speaker 4: some investors are approaching this deal with skepticism, that they're 354 00:17:20,800 --> 00:17:25,119 Speaker 4: not running into this deal the way we might expect 355 00:17:25,280 --> 00:17:28,960 Speaker 4: investors to run into a normal Elon Musk deal. 356 00:17:29,400 --> 00:17:31,920 Speaker 3: Well, the thing is, like credit investors are not used 357 00:17:31,960 --> 00:17:35,120 Speaker 3: to this type of deal like they're used to. 358 00:17:35,320 --> 00:17:38,560 Speaker 2: Right, because there's no there's no income flow, there's no 359 00:17:38,760 --> 00:17:39,680 Speaker 2: stream of cast. 360 00:17:39,760 --> 00:17:42,560 Speaker 3: Actually this is a startup, right, and that usually doesn't 361 00:17:42,560 --> 00:17:45,800 Speaker 3: go to the corporate credit dead markets like that usually. 362 00:17:46,000 --> 00:17:48,679 Speaker 2: And it would either be on the equity side or 363 00:17:48,680 --> 00:17:50,480 Speaker 2: if it were on the dead side, how would it 364 00:17:50,480 --> 00:17:50,760 Speaker 2: be done? 365 00:17:50,800 --> 00:17:53,359 Speaker 3: Could be a venture dead This is not that usual. 366 00:17:53,400 --> 00:17:55,760 Speaker 3: We don't see this. The food rasist we've seen on 367 00:17:55,880 --> 00:17:58,119 Speaker 3: data centers are mostly at the project level. 368 00:17:58,400 --> 00:18:00,879 Speaker 4: No, is it because is he to do this because 369 00:18:00,920 --> 00:18:03,520 Speaker 4: they're actually building this like gigantic physical data center with 370 00:18:03,560 --> 00:18:05,040 Speaker 4: all these expensive GPUs that. 371 00:18:05,040 --> 00:18:08,960 Speaker 3: Have intrinsic value. I think it's mainly like you're betting 372 00:18:08,960 --> 00:18:11,760 Speaker 3: on AI, like the and basically you're betting on Musk 373 00:18:12,080 --> 00:18:14,880 Speaker 3: and the equity race just came out this week, which 374 00:18:14,880 --> 00:18:17,720 Speaker 3: is also helping investors be more comfortable with the dead 375 00:18:17,800 --> 00:18:20,280 Speaker 3: race because they know that someone's going to be backing 376 00:18:20,280 --> 00:18:21,000 Speaker 3: it in some sense. 377 00:18:21,160 --> 00:18:24,400 Speaker 2: But it's true, it's not super intuitive that if you're 378 00:18:24,400 --> 00:18:26,640 Speaker 2: betting on AI that you'd want to do it through 379 00:18:26,640 --> 00:18:28,720 Speaker 2: the debt side, right. I mean, if you're betting on AI, 380 00:18:29,040 --> 00:18:31,560 Speaker 2: you're hoping to hit a crazy home run, right and 381 00:18:31,640 --> 00:18:34,320 Speaker 2: come up with something that produces a return of five 382 00:18:34,400 --> 00:18:36,600 Speaker 2: hundred one thousand percent. You know, why do you want 383 00:18:36,600 --> 00:18:39,080 Speaker 2: to be clipping coupons at eleven or twelve per What 384 00:18:39,080 --> 00:18:41,879 Speaker 2: are the coupons on this debt. By the way, the 385 00:18:42,000 --> 00:18:43,480 Speaker 2: interest rate twelve percent. 386 00:18:43,520 --> 00:18:44,440 Speaker 1: I believe I. 387 00:18:44,359 --> 00:18:48,040 Speaker 2: Would think an investor gravitates that space thinking that they're 388 00:18:48,040 --> 00:18:50,320 Speaker 2: going to mind a thousand percent return, not that they're 389 00:18:50,359 --> 00:18:52,280 Speaker 2: going to clip eleven percent interest rates a year. 390 00:18:52,400 --> 00:18:53,960 Speaker 3: Well, if you look at like the just the equity 391 00:18:54,000 --> 00:18:56,560 Speaker 3: story for Xai, like an end of twenty twenty four 392 00:18:56,680 --> 00:18:59,679 Speaker 3: was worth around fifty billion, now end of March was 393 00:19:00,359 --> 00:19:03,200 Speaker 3: eighty billion, and now they've raised more equity. So the 394 00:19:03,240 --> 00:19:06,359 Speaker 3: equity story is just like an outboard trajectory that's usually 395 00:19:06,359 --> 00:19:07,960 Speaker 3: not the same for the debt. You just expect to 396 00:19:08,000 --> 00:19:11,240 Speaker 3: get paid, so the upside is not usually that into it. 397 00:19:11,359 --> 00:19:12,880 Speaker 1: What is that equity story based on. 398 00:19:13,680 --> 00:19:14,439 Speaker 3: Just fund raises? 399 00:19:14,720 --> 00:19:20,280 Speaker 4: It's just like like but I mean it's basically just 400 00:19:20,359 --> 00:19:23,159 Speaker 4: Elon decided that it's now worth twice. 401 00:19:22,880 --> 00:19:25,240 Speaker 2: Wait a minute, no, no, no, but some sort of transaction 402 00:19:25,520 --> 00:19:30,120 Speaker 2: or two or three took place that when you extrapolated out, 403 00:19:30,160 --> 00:19:33,000 Speaker 2: it came up with fifty billion dollars whenever it was 404 00:19:33,240 --> 00:19:36,040 Speaker 2: that first one, and it spits out eighty billion, now right, 405 00:19:36,080 --> 00:19:38,879 Speaker 2: I mean, it's not Max is being very cynical and 406 00:19:38,920 --> 00:19:41,480 Speaker 2: saying it's just it's it's eighty billion dollars now because 407 00:19:41,560 --> 00:19:45,240 Speaker 2: Musk says it is, but no, presumably actual transactions happened 408 00:19:45,520 --> 00:19:46,480 Speaker 2: at that valuation. 409 00:19:46,600 --> 00:19:49,199 Speaker 3: Well, well, you raise new equity, you just you basically 410 00:19:49,280 --> 00:19:50,960 Speaker 3: put a new valuation to it. 411 00:19:50,800 --> 00:20:00,439 Speaker 4: And somebody bought it, right, Well presumably presumably. I'm curious 412 00:20:00,520 --> 00:20:04,920 Speaker 4: how the merger of x and Xai plays into this fundraising, 413 00:20:05,320 --> 00:20:09,639 Speaker 4: and like I still don't totally understand what it means 414 00:20:09,760 --> 00:20:12,400 Speaker 4: for either company, and like, how are the investors thinking 415 00:20:12,400 --> 00:20:14,679 Speaker 4: about the fact that they also own this sort of 416 00:20:15,119 --> 00:20:16,640 Speaker 4: struggling social network. 417 00:20:17,040 --> 00:20:20,280 Speaker 3: So that's kind of interesting because like dead investors boughtle 418 00:20:20,320 --> 00:20:22,840 Speaker 3: out of the xtad and they were comfortable with that. 419 00:20:22,760 --> 00:20:25,480 Speaker 2: That was how much a net was right back when 420 00:20:25,600 --> 00:20:28,920 Speaker 2: Musk bought Twitter, A chunk of that was financed with debt. 421 00:20:28,960 --> 00:20:29,760 Speaker 2: How much was it in me? 422 00:20:29,760 --> 00:20:33,080 Speaker 3: It was twelve billion, Okay, So like basically Morgan Stanley 423 00:20:33,119 --> 00:20:35,920 Speaker 3: and the other bank sold everything earlier this year and 424 00:20:36,000 --> 00:20:38,679 Speaker 3: the debt was trading close to one hundred right to 425 00:20:38,800 --> 00:20:39,400 Speaker 3: close to par. 426 00:20:39,440 --> 00:20:41,679 Speaker 2: So the end, but you know, it had fallen, and. 427 00:20:41,640 --> 00:20:42,560 Speaker 3: It's fallen a little bit. 428 00:20:42,640 --> 00:20:45,320 Speaker 2: Yeah, and it had fallen initially right after the deal 429 00:20:45,359 --> 00:20:46,639 Speaker 2: went through. It had fallen all the way down to 430 00:20:46,720 --> 00:20:48,920 Speaker 2: like in the sixties sixty some od sence on the dollar. 431 00:20:48,960 --> 00:20:50,679 Speaker 2: Then it came all the way when when Trump was 432 00:20:50,680 --> 00:20:53,439 Speaker 2: elected and Musk and Trump became buddies. He came all 433 00:20:53,440 --> 00:20:56,520 Speaker 2: the way back to around par But yeah, so x 434 00:20:56,560 --> 00:21:00,119 Speaker 2: and Xai how our investors, as Masks was asking, how 435 00:21:00,160 --> 00:21:01,000 Speaker 2: are they thinking about? 436 00:21:01,520 --> 00:21:03,159 Speaker 3: What's kind of interesting is that if you own the 437 00:21:03,200 --> 00:21:05,200 Speaker 3: ex debt, right you have, you still have a lien 438 00:21:05,280 --> 00:21:07,560 Speaker 3: on Xai. But even if you own Xai dead, you 439 00:21:07,640 --> 00:21:10,119 Speaker 3: don't have that lean on x. They don't have that 440 00:21:10,200 --> 00:21:12,040 Speaker 3: cross collateralization. 441 00:21:11,760 --> 00:21:13,560 Speaker 2: A lean on X. What does a lien on X 442 00:21:13,600 --> 00:21:13,960 Speaker 2: get you? 443 00:21:15,240 --> 00:21:17,320 Speaker 3: I mean, at least you have more financials for the company, 444 00:21:17,320 --> 00:21:18,479 Speaker 3: you have a longer history. 445 00:21:19,600 --> 00:21:22,080 Speaker 2: Max. Do you want to lean on X or x Ai? 446 00:21:24,160 --> 00:21:26,399 Speaker 2: You don't. He doesn't want to lean on either. I 447 00:21:26,440 --> 00:21:28,439 Speaker 2: will just say this, A billion dollars a month in 448 00:21:28,480 --> 00:21:31,480 Speaker 2: terms of what they're blowing through. Again, I don't know 449 00:21:31,520 --> 00:21:33,919 Speaker 2: anything about anything, but man, it seems like an awful 450 00:21:33,920 --> 00:21:36,520 Speaker 2: lot of money. And is this a window into how 451 00:21:36,600 --> 00:21:39,640 Speaker 2: much all of these AI companies are are pissing through? 452 00:21:39,840 --> 00:21:41,080 Speaker 1: Yeah? Yeah it is. 453 00:21:41,200 --> 00:21:44,720 Speaker 4: I mean I do think open ai is different because 454 00:21:44,760 --> 00:21:47,720 Speaker 4: open ai has a real business, Like open Ai built 455 00:21:47,720 --> 00:21:52,480 Speaker 4: this very successful consumer product that they've managed to convince 456 00:21:52,880 --> 00:21:55,399 Speaker 4: a lot of people and a lot of businesses to 457 00:21:55,440 --> 00:21:58,320 Speaker 4: pay money for. And so they are, you know, again, 458 00:21:58,880 --> 00:22:01,760 Speaker 4: their revenue projection I think should be met with some 459 00:22:02,040 --> 00:22:04,159 Speaker 4: skepticism as well, because like we're in the middle of 460 00:22:04,200 --> 00:22:08,040 Speaker 4: this guy very frothy period. But they're projecting Carmen, correct me, 461 00:22:08,040 --> 00:22:10,920 Speaker 4: how I'm wrong, like twelve billion, thirteen billion a year 462 00:22:10,920 --> 00:22:13,600 Speaker 4: in annual revenue, right, or I mean they're they're projecting 463 00:22:13,600 --> 00:22:16,679 Speaker 4: in the billions of annual revenue in the near term, 464 00:22:17,119 --> 00:22:20,960 Speaker 4: and I think they're already pulling in billions in revenue today. 465 00:22:21,720 --> 00:22:25,160 Speaker 4: But I do think like this is just what it costs, 466 00:22:25,280 --> 00:22:28,560 Speaker 4: and I think it helps us understand. You know, Must 467 00:22:28,600 --> 00:22:31,720 Speaker 4: put out that tweet a couple of weeks ago before 468 00:22:31,760 --> 00:22:34,000 Speaker 4: the fight with Trump, where he said he needs to 469 00:22:34,000 --> 00:22:35,920 Speaker 4: be super focused on his company, needs to sleep on 470 00:22:35,960 --> 00:22:37,880 Speaker 4: the floor, and he mentioned a bunch of different companies. 471 00:22:37,920 --> 00:22:41,240 Speaker 4: He mentioned Tesla of course, where the robotaxis happening. He 472 00:22:41,359 --> 00:22:46,040 Speaker 4: mentioned star Ship, which is SpaceX's you know, big rocket 473 00:22:46,080 --> 00:22:48,760 Speaker 4: that had just experienced launch failure, and he mentioned Xai. 474 00:22:49,119 --> 00:22:50,920 Speaker 1: And I think in certain ways. 475 00:22:50,960 --> 00:22:54,119 Speaker 4: There are crises going on at every single one of 476 00:22:54,119 --> 00:22:57,240 Speaker 4: those companies. Now Xai is different because there is also 477 00:22:57,359 --> 00:22:59,920 Speaker 4: this like pot of gold that really seems like it 478 00:23:00,119 --> 00:23:01,640 Speaker 4: could be there in the New York turn. 479 00:23:01,720 --> 00:23:03,199 Speaker 2: Yeah, but why why do you say there's a crisis 480 00:23:03,200 --> 00:23:03,520 Speaker 2: going on. 481 00:23:03,440 --> 00:23:07,200 Speaker 1: Today because it's burning twelve thirteen? You guys just. 482 00:23:07,160 --> 00:23:08,399 Speaker 2: Told me that that's just the way these things. 483 00:23:08,520 --> 00:23:10,080 Speaker 3: Yea, I'm not sure it's a crisis. I think it's 484 00:23:10,080 --> 00:23:12,080 Speaker 3: how the business works. Like if you look at the 485 00:23:12,119 --> 00:23:14,439 Speaker 3: other Ai companies, they're burning similar money. 486 00:23:15,000 --> 00:23:17,200 Speaker 4: There's just no business yet he's going to need to 487 00:23:17,280 --> 00:23:19,840 Speaker 4: raise another twelve billion next year. The implication of this 488 00:23:19,960 --> 00:23:21,560 Speaker 4: story is that he's going to have to go to 489 00:23:21,560 --> 00:23:23,080 Speaker 4: the capital markets very quickly. 490 00:23:23,480 --> 00:23:26,399 Speaker 2: Again, now, well that's a good question, waymut So, Carmen, 491 00:23:26,600 --> 00:23:29,880 Speaker 2: is there any sense in the reporting you have that 492 00:23:30,000 --> 00:23:33,840 Speaker 2: even though they're producing essentially some iteration of zero revenue 493 00:23:33,840 --> 00:23:37,719 Speaker 2: this year, that in twenty twenty six, in twenty twenty seven, 494 00:23:38,400 --> 00:23:41,520 Speaker 2: in other words, and then not so distant future, those 495 00:23:41,560 --> 00:23:44,120 Speaker 2: income streams will start to change fairly quickly. Yeah. 496 00:23:44,160 --> 00:23:46,640 Speaker 3: Basically, their projections is that by twenty twenty seven they're 497 00:23:46,640 --> 00:23:48,480 Speaker 3: going to be profitable see that. 498 00:23:48,600 --> 00:23:48,919 Speaker 2: Max. 499 00:23:49,640 --> 00:23:52,840 Speaker 4: Okay, wait, I've just been thinking about how you have 500 00:23:53,920 --> 00:23:58,840 Speaker 4: this company which is an increasingly large chunk of Elon's 501 00:23:59,000 --> 00:24:02,520 Speaker 4: kind of eire, and you have Tesla, I mean, which 502 00:24:02,560 --> 00:24:06,560 Speaker 4: is entirely dependent on this ROBOTAXI story. Like, this is 503 00:24:06,560 --> 00:24:10,880 Speaker 4: a guy who's like really leveraged in one direction, which 504 00:24:10,960 --> 00:24:15,720 Speaker 4: is that AI playing out the way that bulls hope 505 00:24:15,760 --> 00:24:19,400 Speaker 4: and happening very very very very quickly. And anything short 506 00:24:19,440 --> 00:24:21,280 Speaker 4: of that is going to be a real problem for 507 00:24:21,320 --> 00:24:23,240 Speaker 4: Elon Musk. It's gonna be a problem for Tesla, It's 508 00:24:23,240 --> 00:24:25,399 Speaker 4: gonna be a problem for x No, that's true. 509 00:24:25,600 --> 00:24:27,439 Speaker 3: Now, I was going to say, like something interesting on 510 00:24:27,480 --> 00:24:31,240 Speaker 3: this xaix relationship that I thought was interesting is that 511 00:24:31,320 --> 00:24:34,720 Speaker 3: basically XAI can use the x x a library to 512 00:24:34,760 --> 00:24:38,040 Speaker 3: train Groc, which is something that maybe other AI companies 513 00:24:38,080 --> 00:24:41,240 Speaker 3: don't have like that amount of like information there. 514 00:24:41,480 --> 00:24:43,840 Speaker 4: The thing is, they were doing it already there was. 515 00:24:43,880 --> 00:24:46,600 Speaker 4: It's just like an accounting change really, But because of 516 00:24:46,600 --> 00:24:49,879 Speaker 4: course Elon Musk, you know, controlling both companies, could just 517 00:24:49,920 --> 00:24:53,920 Speaker 4: decide to give X's data to Groc, which it seemed 518 00:24:53,920 --> 00:24:56,240 Speaker 4: like he was already doing. But it does seem like 519 00:24:56,720 --> 00:25:01,240 Speaker 4: a real point of differentiation for XA and for Grock 520 00:25:01,400 --> 00:25:04,240 Speaker 4: that it can be trained on this like up to 521 00:25:04,280 --> 00:25:07,440 Speaker 4: the minute data. I do think if you've been using 522 00:25:07,760 --> 00:25:12,159 Speaker 4: X lately, especially over the last year, you may have 523 00:25:12,240 --> 00:25:14,520 Speaker 4: questions about just how reliable that data is. I mean, 524 00:25:14,560 --> 00:25:19,159 Speaker 4: it's it's gotten less good at sort of giving the 525 00:25:19,280 --> 00:25:21,520 Speaker 4: kind of up to the minute news that it once did. 526 00:25:21,800 --> 00:25:25,600 Speaker 4: It's also full of AI slop, including a lot of 527 00:25:25,640 --> 00:25:28,679 Speaker 4: Grock slop, and and you don't really want if you 528 00:25:28,720 --> 00:25:31,960 Speaker 4: know anything about what so like the point is more 529 00:25:32,040 --> 00:25:34,040 Speaker 4: like it's like making a tape of a tape. You 530 00:25:34,040 --> 00:25:37,400 Speaker 4: don't want to train an AI algorithm on AI outputs, 531 00:25:37,520 --> 00:25:41,040 Speaker 4: and because if that happens, it tends to magnifies the 532 00:25:41,119 --> 00:25:42,080 Speaker 4: problems you're like. 533 00:25:42,040 --> 00:25:47,760 Speaker 1: Hallucinating on exactly. And so my assumption is they're trying to. 534 00:25:47,760 --> 00:25:50,520 Speaker 4: Filter out those Grock responses and they're trying to like 535 00:25:50,880 --> 00:25:53,800 Speaker 4: find ways so that they're not training Grock. 536 00:25:53,680 --> 00:25:57,919 Speaker 2: Is basically in a cave shouting at himself, and then he's. 537 00:25:57,480 --> 00:26:00,600 Speaker 4: The that's the risk, to be clear, that is a 538 00:26:00,960 --> 00:26:02,920 Speaker 4: rock out of the cave. That's a risk for open 539 00:26:02,920 --> 00:26:05,320 Speaker 4: AI as well, because you're seeing, you know, open AI 540 00:26:05,440 --> 00:26:08,359 Speaker 4: and these other large language models train on the open Web. 541 00:26:08,640 --> 00:26:10,760 Speaker 4: If you've been on the open Web lately, you're noticing 542 00:26:10,800 --> 00:26:13,000 Speaker 4: there's a lot of open AI. I've been on X, 543 00:26:13,000 --> 00:26:14,560 Speaker 4: but I've been on the open Yeah, there's a lot 544 00:26:14,560 --> 00:26:17,400 Speaker 4: of AI slop, which I'm just that's a word I'm 545 00:26:17,440 --> 00:26:18,679 Speaker 4: using to describe kind of. 546 00:26:18,760 --> 00:26:21,720 Speaker 2: So you're telling me, Shotty oi out, I shouldn't believe 547 00:26:21,720 --> 00:26:22,720 Speaker 2: what the robot tells me. 548 00:26:22,920 --> 00:26:26,720 Speaker 4: Yeah, you gotta be careful with large language, Carmen, Alith. 549 00:26:26,440 --> 00:26:27,000 Speaker 2: Be careful. 550 00:26:27,119 --> 00:26:27,600 Speaker 3: Yeah, I know. 551 00:26:28,080 --> 00:26:32,719 Speaker 2: Taking this, Carmen, keep breaking news and when you have 552 00:26:32,800 --> 00:26:34,520 Speaker 2: another really good scoop, we'll have you back on. 553 00:26:34,920 --> 00:26:37,520 Speaker 3: Thank you, Thank you for having me Max. 554 00:26:37,280 --> 00:26:47,679 Speaker 2: Thanks as always, Thank you. This episode was produced by 555 00:26:47,720 --> 00:26:52,080 Speaker 2: Stacey Wong and edited by Anna Masarrakas, Blake Maple's Handles Engineering, 556 00:26:52,080 --> 00:26:56,080 Speaker 2: and Dave Percelle fact checks. Our supervising producer is Magnus Hendrickson. 557 00:26:56,440 --> 00:26:59,000 Speaker 2: The e lining theme is written and performed by Taki 558 00:26:59,080 --> 00:27:04,280 Speaker 2: Yasuzawa and Alex Sugierra. Brendan Francis Newnham is our executive producer, 559 00:27:04,320 --> 00:27:07,520 Speaker 2: and Sage Bauman is the head of Bloomberg Podcasts. A 560 00:27:07,640 --> 00:27:10,800 Speaker 2: big thanks as always to our supporters Joe Weber and 561 00:27:10,840 --> 00:27:14,639 Speaker 2: brad Stone. I'm David Papadopolis. If you have a minute, 562 00:27:14,880 --> 00:27:18,160 Speaker 2: rate and review our show, it'll help other listeners find us. 563 00:27:18,480 --> 00:27:19,399 Speaker 2: See you next week.