1 00:00:04,000 --> 00:00:06,760 Speaker 1: Well, Elon Musk gives now the richest person on the planet. 2 00:00:07,240 --> 00:00:10,080 Speaker 1: More than half the satellites in space are owned and 3 00:00:10,200 --> 00:00:15,600 Speaker 1: controlled by one man starting his own artificial intelligence company. Well, 4 00:00:15,640 --> 00:00:17,279 Speaker 1: he's a legitimate super genius. 5 00:00:17,480 --> 00:00:19,000 Speaker 2: I mean legitimate. He says. 6 00:00:19,000 --> 00:00:21,599 Speaker 3: He's always voted for Democrats, but this year it will 7 00:00:21,640 --> 00:00:22,040 Speaker 3: be different. 8 00:00:22,079 --> 00:00:23,040 Speaker 2: He'll vote Republican. 9 00:00:23,320 --> 00:00:25,759 Speaker 1: There is a reason the US government is so reliant 10 00:00:25,840 --> 00:00:26,239 Speaker 1: on him. 11 00:00:26,440 --> 00:00:30,000 Speaker 2: Elon Musk is a scam artist and he's done nothing. 12 00:00:30,640 --> 00:00:33,400 Speaker 2: Anything he does is fascinating people. 13 00:00:42,520 --> 00:00:45,600 Speaker 1: Welcome to Elon Inc. Where we talk about Elon Musk's 14 00:00:45,680 --> 00:00:49,360 Speaker 1: vast corporate empire, his latest gambits and antics, and try 15 00:00:49,360 --> 00:00:51,520 Speaker 1: to make sense of it all. I'm your host, Max 16 00:00:51,600 --> 00:00:56,880 Speaker 1: Chapkin in for David Poppadopolis. Today we're talking about Tesla. 17 00:00:57,160 --> 00:01:00,840 Speaker 1: The company's fourth quarter sales numbers came out earlier this morning, 18 00:01:01,000 --> 00:01:04,679 Speaker 1: and Elon Musk's car company reported that had delivered nearly 19 00:01:04,800 --> 00:01:08,920 Speaker 1: four hundred and eighty five thousand vehicles between October and December. 20 00:01:09,200 --> 00:01:13,240 Speaker 1: That's basically what Wall Street expected. Meanwhile, something that did 21 00:01:13,240 --> 00:01:17,120 Speaker 1: not meet expectations, Fidelity once again said that x Elon 22 00:01:17,240 --> 00:01:21,640 Speaker 1: Musk's social media company was worthless, not worthless, but worth 23 00:01:21,920 --> 00:01:24,880 Speaker 1: less than it was when Elon bought it. X lost 24 00:01:25,000 --> 00:01:28,040 Speaker 1: nearly eleven percent of its value in November, which sounds 25 00:01:28,600 --> 00:01:30,720 Speaker 1: bad until you realize that was the same month he 26 00:01:30,800 --> 00:01:33,640 Speaker 1: told Bob Eiger, the CEO of one of the world's 27 00:01:33,640 --> 00:01:36,760 Speaker 1: most beloved companies, to go fuck himself, to discuss this 28 00:01:36,920 --> 00:01:39,360 Speaker 1: and to look at what's ahead in the new year. 29 00:01:39,400 --> 00:01:42,040 Speaker 1: We've got our panel here, Sarah Fryar, who leads our 30 00:01:42,080 --> 00:01:46,440 Speaker 1: big tech team here at Bloomberg News. Hello Sarah, Happy New. 31 00:01:46,400 --> 00:01:47,680 Speaker 2: Year, Happy New Year. 32 00:01:48,120 --> 00:01:51,840 Speaker 1: And Dana Hull, the world's most diligent Tesla reporter. Happy 33 00:01:51,840 --> 00:01:56,320 Speaker 1: New Year to you, Dana, twenty twenty four, LFG Okay. 34 00:01:56,800 --> 00:02:00,800 Speaker 1: So Elon Musk has over the last few years, I think, 35 00:02:00,960 --> 00:02:03,960 Speaker 1: Dana correct me if I'm wrong, bragged that he's spent 36 00:02:04,040 --> 00:02:06,560 Speaker 1: the new year delivering cars that he's been, you know, 37 00:02:06,880 --> 00:02:09,560 Speaker 1: in the factory, you know, trying to put the last 38 00:02:09,760 --> 00:02:12,200 Speaker 1: bow on in another year for Tesla. Do we have 39 00:02:12,200 --> 00:02:15,240 Speaker 1: any sense of whether that's what he did over this holiday? 40 00:02:16,240 --> 00:02:18,280 Speaker 3: So it's not that I'm on the phone with Elon, 41 00:02:18,360 --> 00:02:19,840 Speaker 3: but my sense is that he spent part of the 42 00:02:19,840 --> 00:02:22,480 Speaker 3: holidays in Puerto Rico or at least his his jet 43 00:02:22,560 --> 00:02:25,079 Speaker 3: was in Puerto Rico, And yeah, I did not get 44 00:02:25,080 --> 00:02:28,160 Speaker 3: the sense that he was in Fremont or in Austin, 45 00:02:28,840 --> 00:02:31,320 Speaker 3: like helping out the delivery guys, which you know he 46 00:02:31,360 --> 00:02:33,320 Speaker 3: has done in years past. But yeah, no, I mean 47 00:02:33,360 --> 00:02:34,560 Speaker 3: I think I think he was out of town. 48 00:02:35,080 --> 00:02:36,560 Speaker 1: What do you make of the numbers? So four hundred 49 00:02:36,560 --> 00:02:38,919 Speaker 1: and eighty five thousand vehicles for the last three months 50 00:02:38,960 --> 00:02:41,560 Speaker 1: of twenty twenty three, one point eight million cars for 51 00:02:41,600 --> 00:02:44,800 Speaker 1: the year. I mean, it sounds it sounds like a lot. 52 00:02:44,919 --> 00:02:47,800 Speaker 1: I mean in historic terms. On the other hand, you know, 53 00:02:47,880 --> 00:02:49,120 Speaker 1: not as high as some other companies. 54 00:02:49,600 --> 00:02:51,400 Speaker 3: Yeah, So the big news out of the numbers for 55 00:02:51,440 --> 00:02:53,760 Speaker 3: me was they didn't break out how many cyber trucks 56 00:02:53,760 --> 00:02:56,240 Speaker 3: they delivered, which is pretty funny given that this is 57 00:02:56,240 --> 00:03:00,919 Speaker 3: their brand new vehicle. So they delivered, you know, four hundred, 58 00:03:00,160 --> 00:03:04,160 Speaker 3: five hundred and seven vehicles. They broke out the three 59 00:03:04,200 --> 00:03:07,160 Speaker 3: and the Y, and then they had other models which 60 00:03:07,200 --> 00:03:10,000 Speaker 3: includes the S, the X, and the cyber trucks. So 61 00:03:10,040 --> 00:03:12,360 Speaker 3: we have no idea how many cyber trucks have actually 62 00:03:12,360 --> 00:03:14,560 Speaker 3: been handed over to customers, and it just is weird 63 00:03:14,560 --> 00:03:15,800 Speaker 3: that they didn't break that out. 64 00:03:16,000 --> 00:03:18,000 Speaker 2: So it has to be intentional, right. 65 00:03:17,919 --> 00:03:21,520 Speaker 3: Right, it's a lousy number, so they didn't broadcast it. 66 00:03:21,560 --> 00:03:24,680 Speaker 3: If it was a positive number, they would have absolutely said, oh, 67 00:03:24,720 --> 00:03:26,760 Speaker 3: we you know, we did a thousand or something like that. 68 00:03:26,840 --> 00:03:31,480 Speaker 3: So they're basically obfuscating how many cyber trucks they've actually made. 69 00:03:31,720 --> 00:03:33,560 Speaker 2: And then the big thing. 70 00:03:33,440 --> 00:03:36,720 Speaker 3: Is that they've lost their like EV crown to BYD, 71 00:03:36,920 --> 00:03:40,160 Speaker 3: which is the Warren Buffett backed Chinese company that also 72 00:03:40,200 --> 00:03:42,200 Speaker 3: makes evs, And you know, Musk has said over and 73 00:03:42,200 --> 00:03:44,400 Speaker 3: over again that their biggest competition is in China. But 74 00:03:44,440 --> 00:03:47,280 Speaker 3: this is the first quarter that we've actually seen BYD 75 00:03:47,440 --> 00:03:50,280 Speaker 3: kind of like come ahead now in terms of full 76 00:03:50,440 --> 00:03:53,800 Speaker 3: EV deliveries ahead of Tesla. But the stock reaction today 77 00:03:53,880 --> 00:03:56,320 Speaker 3: is kind of mixed. I think it's like the delivery 78 00:03:56,360 --> 00:03:58,680 Speaker 3: numbers were in line with what Wall Street was expecting, 79 00:03:58,760 --> 00:04:00,480 Speaker 3: but nothing earth shattering. 80 00:04:01,520 --> 00:04:04,120 Speaker 1: So, Sarah, I mean you sort of hinted at this. 81 00:04:04,240 --> 00:04:07,120 Speaker 1: On December twenty ninth, Musk wrote, I stand by my 82 00:04:07,160 --> 00:04:10,000 Speaker 1: prediction that if Tesla executes extremely well over the next 83 00:04:10,000 --> 00:04:13,160 Speaker 1: five years, that the long term value could exceed Apple 84 00:04:13,240 --> 00:04:14,920 Speaker 1: and a Ramco combine. That I mean is that the 85 00:04:14,960 --> 00:04:16,920 Speaker 1: spin that we're going to see like this is just 86 00:04:17,000 --> 00:04:19,240 Speaker 1: you know what, strength on strength. He's just gonna play 87 00:04:19,279 --> 00:04:20,600 Speaker 1: this as a as a huge victory. 88 00:04:21,320 --> 00:04:24,120 Speaker 2: I mean, I think that the game of talking about 89 00:04:24,160 --> 00:04:27,839 Speaker 2: these things is to surprise and delight, right, So you 90 00:04:27,880 --> 00:04:31,200 Speaker 2: want to start with like, you know, this grand vision, 91 00:04:31,279 --> 00:04:35,280 Speaker 2: and I think that's the thing that Musk always excels at. 92 00:04:35,360 --> 00:04:38,120 Speaker 2: He makes people believe that the future is going to 93 00:04:38,200 --> 00:04:43,960 Speaker 2: be like way crazier and unimaginably amazing compared to today. And 94 00:04:44,000 --> 00:04:46,920 Speaker 2: then you know, the details are kind of like they 95 00:04:46,920 --> 00:04:50,359 Speaker 2: should probably exceed expectations, but in the case of Tesla, 96 00:04:50,400 --> 00:04:53,800 Speaker 2: they haven't always except for you know, when it comes 97 00:04:53,839 --> 00:04:58,960 Speaker 2: to the actual uptake of evs or EV's, I think 98 00:04:59,240 --> 00:05:02,719 Speaker 2: for Tesla have a little bit of a better chance 99 00:05:02,800 --> 00:05:06,039 Speaker 2: because the charging network for everyone else is kind of crumbling, 100 00:05:06,120 --> 00:05:09,680 Speaker 2: So you know, that's one way you might bet on them. 101 00:05:09,680 --> 00:05:12,000 Speaker 2: But I think when it comes to talking about the numbers, 102 00:05:12,160 --> 00:05:15,480 Speaker 2: the best case scenario is to just say the future 103 00:05:15,560 --> 00:05:17,760 Speaker 2: is going to be so much better than you can 104 00:05:17,800 --> 00:05:20,360 Speaker 2: even imagine and not focus on what's right now. 105 00:05:20,800 --> 00:05:23,040 Speaker 1: And I guess that's what he's saying. Dan, you brought 106 00:05:23,080 --> 00:05:26,760 Speaker 1: up byd refresh our memories, Like what is BYD and 107 00:05:26,800 --> 00:05:29,200 Speaker 1: to what extent is it fair to compare them to Tesla? 108 00:05:29,480 --> 00:05:32,000 Speaker 1: How similar or different are they from Tesla? 109 00:05:32,640 --> 00:05:34,960 Speaker 3: I mean it's a Chinese electric car company and a 110 00:05:35,000 --> 00:05:37,160 Speaker 3: battery company. And I think that like what most people 111 00:05:37,200 --> 00:05:39,760 Speaker 3: are realizing is that when you look at the EV market, 112 00:05:39,800 --> 00:05:43,039 Speaker 3: there's kind of two clear leaders BYD and Tesla, which 113 00:05:43,040 --> 00:05:47,479 Speaker 3: are vertically integrated companies that make the cars, basically make 114 00:05:47,480 --> 00:05:50,919 Speaker 3: the batteries, know a lot about like powertrain and engineering 115 00:05:50,960 --> 00:05:53,479 Speaker 3: and battery sale development. And then there's like everybody else, 116 00:05:53,480 --> 00:05:55,920 Speaker 3: which is the legacy OEMs that are trying to pivot 117 00:05:55,960 --> 00:05:59,279 Speaker 3: to evs but don't have that kind of in house expertise. 118 00:05:59,360 --> 00:06:01,880 Speaker 3: And so, like one of the big narratives in twenty 119 00:06:01,880 --> 00:06:04,919 Speaker 3: twenty three was like slowing EV growth that like the 120 00:06:04,960 --> 00:06:08,120 Speaker 3: EV market is still growing, but it's like slower than usual, 121 00:06:08,800 --> 00:06:10,840 Speaker 3: and you saw like Ford and GM and all these 122 00:06:10,880 --> 00:06:13,680 Speaker 3: other players kind of like pull back on their expectations. 123 00:06:13,720 --> 00:06:17,479 Speaker 3: But like BYD and and Tesla are totally leading the 124 00:06:17,480 --> 00:06:20,320 Speaker 3: world in volume, and Tesla deliveries year over year it 125 00:06:20,360 --> 00:06:23,440 Speaker 3: was thirty eight percent growth. I mean that's that's still 126 00:06:23,480 --> 00:06:26,520 Speaker 3: like significant growth. I mean, Tesla's growth is not like 127 00:06:26,560 --> 00:06:29,400 Speaker 3: the runaway fifty percent growth that they have had some years, 128 00:06:29,440 --> 00:06:31,960 Speaker 3: but it's still it's still growing. And yeah, I mean 129 00:06:31,960 --> 00:06:34,240 Speaker 3: I think BYD does not really sell cars in the 130 00:06:34,279 --> 00:06:36,240 Speaker 3: United States. So that's why, like a lot of people 131 00:06:36,440 --> 00:06:38,720 Speaker 3: like are like what the hell is BYD because you 132 00:06:38,720 --> 00:06:41,160 Speaker 3: don't see like a BYD car on the freeway. 133 00:06:41,480 --> 00:06:43,440 Speaker 2: But they are a massive player. 134 00:06:44,279 --> 00:06:46,400 Speaker 1: Yeah, and China is a massive market, a massive market 135 00:06:46,400 --> 00:06:50,280 Speaker 1: that of course Tesla has wanted to participate in. I mean, 136 00:06:50,320 --> 00:06:52,960 Speaker 1: does this, I mean, does this bode ill at least 137 00:06:52,960 --> 00:06:56,599 Speaker 1: for Tesla's sort of like big hope for growth in China. 138 00:06:57,480 --> 00:06:59,480 Speaker 3: I think it's going to be very interesting to see 139 00:06:59,520 --> 00:07:02,239 Speaker 3: in the coming year how Tesla reacts to be widdy 140 00:07:02,480 --> 00:07:04,760 Speaker 3: in China. They've done a lot to kind of cut 141 00:07:04,800 --> 00:07:07,839 Speaker 3: prices in China. They do a lot of marketing in China. 142 00:07:07,880 --> 00:07:10,160 Speaker 3: You know, Tesla owes a lot to China. I mean, 143 00:07:10,200 --> 00:07:13,160 Speaker 3: the Chinese government really supported the building of that factory 144 00:07:13,200 --> 00:07:16,640 Speaker 3: in Shanghai. And after the United States, China is far 145 00:07:16,680 --> 00:07:19,160 Speaker 3: and away Tesla's largest market. So I think just like 146 00:07:19,320 --> 00:07:21,880 Speaker 3: keeping an eye on price cuts and in the ways 147 00:07:21,920 --> 00:07:24,840 Speaker 3: that Tesla tries to pull demand levers in China's going 148 00:07:24,880 --> 00:07:25,640 Speaker 3: to be really interesting. 149 00:07:26,200 --> 00:07:29,440 Speaker 1: Sarah, do you think that Elon Musk's sort of seeding 150 00:07:29,480 --> 00:07:32,280 Speaker 1: the crown, the electric vehicle crown to another company is significant? 151 00:07:32,320 --> 00:07:34,600 Speaker 1: I mean, how much of his mythology is kind of 152 00:07:34,640 --> 00:07:36,920 Speaker 1: baked into like being the market leader. Do you think this, 153 00:07:37,280 --> 00:07:39,840 Speaker 1: you know, ultimately becomes no big deal. 154 00:07:40,080 --> 00:07:42,480 Speaker 2: I think if if I'm Elon Musk, I'm taking credit 155 00:07:42,520 --> 00:07:45,640 Speaker 2: for it, right, it's like a victory because he started 156 00:07:45,680 --> 00:07:50,240 Speaker 2: the evy revolution of the modern era, and so other 157 00:07:50,320 --> 00:07:53,400 Speaker 2: companies succeeding in it. It's like a reflection of his 158 00:07:53,520 --> 00:07:56,800 Speaker 2: own influence on the market, or at least that's how 159 00:07:57,040 --> 00:08:01,160 Speaker 2: I'd see if I were being optimistic. But I think that, 160 00:08:01,520 --> 00:08:03,240 Speaker 2: you know, in the past, we've heard him say, like 161 00:08:04,080 --> 00:08:06,880 Speaker 2: take credit for the whole ev revolution, which is why 162 00:08:06,880 --> 00:08:10,520 Speaker 2: we've talked about how he felt so snubbed when Biden 163 00:08:10,680 --> 00:08:13,520 Speaker 2: didn't so much as mentioned Tesla when he talked about 164 00:08:13,600 --> 00:08:16,080 Speaker 2: the proliferation of EV's in the US. 165 00:08:16,600 --> 00:08:18,880 Speaker 1: Dana, you talked about the cyber truck briefly, you know. 166 00:08:19,040 --> 00:08:21,520 Speaker 1: I read your article on Bloomberg dot Com about sort 167 00:08:21,520 --> 00:08:23,960 Speaker 1: of different guesses as to how many cyber trucks were sold. 168 00:08:24,000 --> 00:08:26,880 Speaker 1: I think the analyst estimates range from anywhere from what 169 00:08:27,000 --> 00:08:30,320 Speaker 1: several hundred to several thousand. We know that there was 170 00:08:30,400 --> 00:08:32,920 Speaker 1: at least one cyber truck out there because there was 171 00:08:32,920 --> 00:08:36,760 Speaker 1: a crash reported over the weekend involving a Toyota Corolla 172 00:08:36,880 --> 00:08:39,320 Speaker 1: did not end super well for the Corolla, although there 173 00:08:39,320 --> 00:08:42,840 Speaker 1: are no injuries. I mean, just just from sort of 174 00:08:42,880 --> 00:08:46,800 Speaker 1: social media and scattered reports from Tesla dealerships, do we 175 00:08:46,840 --> 00:08:50,160 Speaker 1: have any sense of how many cyber trucks are on 176 00:08:50,200 --> 00:08:52,960 Speaker 1: the road or how this whole process is going that 177 00:08:52,960 --> 00:08:55,080 Speaker 1: we've been talking about for the last few months. 178 00:08:55,160 --> 00:08:56,960 Speaker 3: I think Elon tweeted over the weekend that there are 179 00:08:57,000 --> 00:08:59,080 Speaker 3: a couple hundred out there now and a lot of 180 00:08:59,080 --> 00:09:02,160 Speaker 3: them are in so a couple of hundred on the roads, 181 00:09:02,200 --> 00:09:04,520 Speaker 3: I guess in the hands of customers. You know, there 182 00:09:04,559 --> 00:09:07,520 Speaker 3: are cyber trucks in showrooms. You know, it's a big 183 00:09:07,559 --> 00:09:09,440 Speaker 3: marketing thing for Tesla. They want people to come to 184 00:09:09,440 --> 00:09:11,520 Speaker 3: the showroom to see the cyber truck and then hopefully 185 00:09:11,520 --> 00:09:13,000 Speaker 3: like sit in a model why and then buy a 186 00:09:13,040 --> 00:09:16,000 Speaker 3: model why. I mean I saw one in real life. 187 00:09:16,040 --> 00:09:18,400 Speaker 3: I was walking to Trader Joe's and like one drove by, 188 00:09:18,440 --> 00:09:19,920 Speaker 3: and I was like, oh, there's a cyber. 189 00:09:19,679 --> 00:09:22,280 Speaker 2: Truck, so an actual moving one, an actual moving one. 190 00:09:22,720 --> 00:09:25,679 Speaker 2: You know, they largely seem to be like on the 191 00:09:25,800 --> 00:09:29,040 Speaker 2: road in Texas and in California. I think that's where 192 00:09:29,040 --> 00:09:31,560 Speaker 2: the first deliveries are probably going to. But you know, 193 00:09:31,600 --> 00:09:33,559 Speaker 2: they've warned that it's going to be a very slow ram. 194 00:09:33,720 --> 00:09:35,400 Speaker 2: I just think the fact that they didn't break out 195 00:09:35,760 --> 00:09:38,880 Speaker 2: how many of the delivered in today's quarterly sales report 196 00:09:38,960 --> 00:09:41,240 Speaker 2: is just really telling, like it's not a lot. The 197 00:09:41,320 --> 00:09:44,840 Speaker 2: crash that you mentioned was kind of classic in that, like, 198 00:09:45,400 --> 00:09:48,280 Speaker 2: you know, we don't really I mean, most journalists don't 199 00:09:48,280 --> 00:09:50,960 Speaker 2: write about car crashes unless it's a Tesla, and that's 200 00:09:50,960 --> 00:09:52,880 Speaker 2: been like a beef that Tesla has had for quite 201 00:09:52,880 --> 00:09:55,520 Speaker 2: some time. Like God, you know, like there are thousands 202 00:09:55,559 --> 00:09:58,360 Speaker 2: of car crashes across the country every day and like 203 00:09:58,440 --> 00:10:01,000 Speaker 2: none of them make headlines unless it's Tesla. In this case, 204 00:10:01,040 --> 00:10:03,840 Speaker 2: I think the Corolla across the median and like ran 205 00:10:03,880 --> 00:10:06,960 Speaker 2: into the cyber truck, and there's no evidence that the 206 00:10:07,000 --> 00:10:09,080 Speaker 2: cyber truck caused this crash. 207 00:10:09,120 --> 00:10:11,560 Speaker 1: And crucially, I think you know, the Corolla driver's okay, 208 00:10:11,720 --> 00:10:15,040 Speaker 1: which obviously there are people warning and probably validly warning 209 00:10:15,040 --> 00:10:17,439 Speaker 1: about the size of this thing and the potential danger 210 00:10:17,480 --> 00:10:19,719 Speaker 1: composed to sedans, although in this case it seems like 211 00:10:19,840 --> 00:10:22,839 Speaker 1: luckily everybody was okay. I mean, for me, the big 212 00:10:22,880 --> 00:10:26,280 Speaker 1: thing with the cyber truck is that this, you know, 213 00:10:26,320 --> 00:10:30,760 Speaker 1: it's this kind of boundary breaking vehicle. It's totally different, 214 00:10:30,760 --> 00:10:33,160 Speaker 1: it's totally sci fi and because of the way it's 215 00:10:33,240 --> 00:10:35,760 Speaker 1: rolling out, there's a bit of a letdown here, and 216 00:10:36,000 --> 00:10:37,800 Speaker 1: we see it in these numbers, you know, we see 217 00:10:37,840 --> 00:10:40,640 Speaker 1: it over the last few weeks where Elon Musk did 218 00:10:40,679 --> 00:10:43,080 Speaker 1: this amazing thing. He introduced this like back to the 219 00:10:43,120 --> 00:10:46,679 Speaker 1: future car and it's kind of like, you know, not 220 00:10:46,760 --> 00:10:49,400 Speaker 1: a whole lot of excitement, partly because they haven't managed 221 00:10:49,400 --> 00:10:50,960 Speaker 1: to get these on the road. 222 00:10:51,600 --> 00:10:53,680 Speaker 2: All the ones I've seen in San Francisco have been 223 00:10:54,280 --> 00:10:58,960 Speaker 2: prototypes that actual employees are testing or driving. Yeah, they 224 00:10:58,960 --> 00:11:00,959 Speaker 2: say RC and the side release candidate. 225 00:11:01,360 --> 00:11:03,280 Speaker 1: Does that make you the coolest person in San Francisco 226 00:11:03,440 --> 00:11:06,280 Speaker 1: or the least cool person in San Francisco, Sarah? 227 00:11:06,520 --> 00:11:10,040 Speaker 2: That I've seen them, they're just surrounding by. 228 00:11:10,040 --> 00:11:12,839 Speaker 1: You Ris here. All right. So last thing I want 229 00:11:12,840 --> 00:11:15,400 Speaker 1: to do before we move on is just is Dan, 230 00:11:15,440 --> 00:11:17,959 Speaker 1: I just get a sense from you over what this 231 00:11:18,080 --> 00:11:20,520 Speaker 1: means for the for Tesla going forward. So we're going 232 00:11:20,600 --> 00:11:22,360 Speaker 1: to see an earnings report at the end of the 233 00:11:22,640 --> 00:11:24,400 Speaker 1: at the end of the month. What are you thinking 234 00:11:24,440 --> 00:11:26,840 Speaker 1: about there? What are you thinking about kind of looking 235 00:11:26,880 --> 00:11:29,599 Speaker 1: ahead for Elon Musk's car company. 236 00:11:29,800 --> 00:11:32,160 Speaker 3: Yeah, So the big question I think on everybody's mind 237 00:11:32,240 --> 00:11:34,680 Speaker 3: is what guidance does Tesla give for twenty twenty four 238 00:11:34,679 --> 00:11:36,720 Speaker 3: in terms of how many vehicles are they going to deliver? 239 00:11:37,000 --> 00:11:39,319 Speaker 3: You know, they set a target of one point eight 240 00:11:39,360 --> 00:11:42,480 Speaker 3: million for twenty twenty three. They met that target, but 241 00:11:42,559 --> 00:11:43,719 Speaker 3: what is it for twenty twenty four? 242 00:11:43,840 --> 00:11:44,360 Speaker 1: Is it like. 243 00:11:44,400 --> 00:11:46,600 Speaker 3: Barely any growth? Is it going to be like two million, 244 00:11:46,679 --> 00:11:48,120 Speaker 3: Is it going to be two point five? Is it 245 00:11:48,160 --> 00:11:50,840 Speaker 3: going to be three? I mean, Elon is always about growth, 246 00:11:50,840 --> 00:11:52,600 Speaker 3: and they don't really have They have like a pretty 247 00:11:52,640 --> 00:11:55,360 Speaker 3: stale lineup right now, and the cyber truck is not 248 00:11:55,520 --> 00:11:57,480 Speaker 3: out in high volumes. So how are they going to 249 00:11:57,600 --> 00:12:01,400 Speaker 3: grow given that, like their best seller. 250 00:12:01,160 --> 00:12:02,959 Speaker 1: The Model Why, is four years old. 251 00:12:03,000 --> 00:12:05,800 Speaker 3: I mean, I'm sure that they'll like refresh it, they'll 252 00:12:05,840 --> 00:12:08,560 Speaker 3: probably enter some new markets, but they don't have anything 253 00:12:08,600 --> 00:12:11,760 Speaker 3: fancy and snazzy, and the cyber truck is going to 254 00:12:11,800 --> 00:12:14,240 Speaker 3: be very slow going, So just the whole question of 255 00:12:14,280 --> 00:12:17,040 Speaker 3: their guidance is the big one for investors. And then 256 00:12:17,080 --> 00:12:19,600 Speaker 3: how do these price cuts that they've had all year 257 00:12:19,800 --> 00:12:22,640 Speaker 3: impact the margins and it? You know, in twenty twenty three, 258 00:12:22,760 --> 00:12:25,360 Speaker 3: Elon Musk made this very shrewd decision that they were 259 00:12:25,400 --> 00:12:29,520 Speaker 3: going to chase volume over margins to kind of protect 260 00:12:29,520 --> 00:12:31,840 Speaker 3: their market share, and that gambit basically worked. I mean, 261 00:12:32,040 --> 00:12:35,960 Speaker 3: they cut prices, they moved metal, but how far how 262 00:12:36,000 --> 00:12:36,960 Speaker 3: low are they willing to go? 263 00:12:37,000 --> 00:12:37,839 Speaker 2: I mean, are they going to. 264 00:12:37,760 --> 00:12:40,520 Speaker 3: Continue to cut prices or have we reached kind of 265 00:12:40,520 --> 00:12:43,720 Speaker 3: like a steady state. And then do they start advertising, 266 00:12:43,760 --> 00:12:45,480 Speaker 3: Like what are they going to do to actually get 267 00:12:45,600 --> 00:12:48,800 Speaker 3: new people into these cars? People who are not like 268 00:12:48,840 --> 00:12:52,920 Speaker 3: your generic like sort of early adopter, tech savvy, you know, 269 00:12:53,040 --> 00:12:57,160 Speaker 3: environmental climate change caring person Like the wave of people 270 00:12:57,200 --> 00:13:00,240 Speaker 3: who wanted to buy an EV basically already have out. 271 00:13:00,240 --> 00:13:03,520 Speaker 3: It's this like real effort to kind of convince Middle 272 00:13:03,559 --> 00:13:06,840 Speaker 3: America to consider an EV and that's something that Tesla 273 00:13:06,840 --> 00:13:07,560 Speaker 3: hasn't really had. 274 00:13:07,480 --> 00:13:09,240 Speaker 2: To do before. Well, we know they're going to advertise 275 00:13:09,280 --> 00:13:12,480 Speaker 2: on X yeah, which really needs it, right, Yeah. 276 00:13:12,360 --> 00:13:14,640 Speaker 3: I wonder how much they'll spend with what the spend 277 00:13:14,679 --> 00:13:15,040 Speaker 3: will be. 278 00:13:19,360 --> 00:13:22,640 Speaker 1: All right, well, let's talk about X then, because you know, 279 00:13:22,679 --> 00:13:25,640 Speaker 1: on the last day of twenty twenty three, Axios reported 280 00:13:25,640 --> 00:13:27,720 Speaker 1: that Fidelity, as I said at the top of the show, 281 00:13:27,760 --> 00:13:32,560 Speaker 1: the big asset manager, cut its valuation of the company, uh, 282 00:13:33,040 --> 00:13:36,679 Speaker 1: making it seventy one point five percent less valuable than 283 00:13:36,720 --> 00:13:38,680 Speaker 1: it was at the time that Elon Musk purchased it 284 00:13:38,720 --> 00:13:41,160 Speaker 1: for forty four billion. I think that implies a valuation 285 00:13:41,240 --> 00:13:45,559 Speaker 1: about just over twelve billion. This disclosure includes a nearly 286 00:13:45,559 --> 00:13:49,880 Speaker 1: eleven percent drop in November. Sarah, I found myself kind 287 00:13:49,920 --> 00:13:52,640 Speaker 1: of a nerd to this kind of report just because 288 00:13:52,640 --> 00:13:55,719 Speaker 1: it's like, oh, yeah, you know this platform that's been 289 00:13:55,800 --> 00:13:58,520 Speaker 1: gasping for air for months that Elon Musk has been 290 00:13:58,720 --> 00:14:03,679 Speaker 1: you know, insulting you know, advertisers. It's almost like, yeah, no, crap, 291 00:14:03,720 --> 00:14:06,960 Speaker 1: it's lost a lot of money. What does this report mean? 292 00:14:07,760 --> 00:14:11,479 Speaker 2: I think that there is some real significance here because 293 00:14:12,440 --> 00:14:17,600 Speaker 2: we don't have any insight right now into how X 294 00:14:17,800 --> 00:14:22,440 Speaker 2: is valuing itself, how they are telling bankers they're doing, 295 00:14:22,880 --> 00:14:25,800 Speaker 2: and investors what kind of information those people are getting, 296 00:14:26,200 --> 00:14:29,480 Speaker 2: and so the Fidelity numbers, although you know it's not 297 00:14:29,560 --> 00:14:31,840 Speaker 2: perfect we don't know how many shares they hold, we 298 00:14:31,880 --> 00:14:36,720 Speaker 2: don't know what kind of information they get from from X. 299 00:14:37,160 --> 00:14:41,680 Speaker 2: It is at least like a rare public disclosure of 300 00:14:41,720 --> 00:14:43,720 Speaker 2: something about this company. 301 00:14:43,800 --> 00:14:46,120 Speaker 1: Yeah, and I guess it's also a counterpoint. You know. 302 00:14:46,760 --> 00:14:49,880 Speaker 1: Unfortunately for me, I listened to the Kathy Wood Elon 303 00:14:49,960 --> 00:14:54,680 Speaker 1: Musk Twitter spaces Kathy would investor in X, and you know, 304 00:14:55,600 --> 00:14:57,800 Speaker 1: sort of spent most of the time talking her book 305 00:14:58,040 --> 00:15:01,320 Speaker 1: and was sort of keeping praise on the on Elon 306 00:15:01,400 --> 00:15:04,400 Speaker 1: Musk's campaign to take on the woke mind virus, as 307 00:15:04,440 --> 00:15:06,120 Speaker 1: she sees it. And so of course this is a 308 00:15:06,160 --> 00:15:09,320 Speaker 1: counterpoint and maybe like a douse of cold water or 309 00:15:09,320 --> 00:15:12,720 Speaker 1: something on the kind of universe of boosters who've been 310 00:15:12,800 --> 00:15:13,840 Speaker 1: kind of promoting this thing. 311 00:15:14,120 --> 00:15:16,400 Speaker 3: I think it's also just interesting because it really kind 312 00:15:16,400 --> 00:15:20,320 Speaker 3: of punctuates this myth of Elon as being this financial genius, right, 313 00:15:20,400 --> 00:15:23,160 Speaker 3: like he has done all these incredible things. SpaceX is 314 00:15:23,160 --> 00:15:26,480 Speaker 3: the most valuable private company in the US. Tesla is 315 00:15:26,520 --> 00:15:29,720 Speaker 3: like the eighth or ninth largest company in the world. 316 00:15:29,840 --> 00:15:33,120 Speaker 3: He like really shrewdly raised capital at a time when 317 00:15:33,160 --> 00:15:35,600 Speaker 3: interest rates were low, and then like X is like 318 00:15:35,640 --> 00:15:37,760 Speaker 3: the big time that he really missed time in the market, 319 00:15:37,800 --> 00:15:41,040 Speaker 3: he overpaid, He spent forty four billion dollars on this 320 00:15:41,120 --> 00:15:44,680 Speaker 3: thing right before the market started to createor and he 321 00:15:44,720 --> 00:15:46,440 Speaker 3: has not been able to turn it around. And like 322 00:15:46,520 --> 00:15:48,400 Speaker 3: for him to sort of be the owner of a 323 00:15:48,440 --> 00:15:51,040 Speaker 3: company that is now worth far less than what he 324 00:15:51,080 --> 00:15:53,480 Speaker 3: paid for it, and then he's got all this debt. 325 00:15:53,320 --> 00:15:56,120 Speaker 2: That he has to service. And also I think what's 326 00:15:56,240 --> 00:16:00,200 Speaker 2: important here is this number is not about Elon. I 327 00:16:00,200 --> 00:16:03,640 Speaker 2: mean a lot of the other rhetoric about X, the 328 00:16:03,680 --> 00:16:06,520 Speaker 2: other decisions we've seen people make have been about his 329 00:16:06,680 --> 00:16:10,600 Speaker 2: behavior directly, you know, advertisers pulling money. Elon Musk calls 330 00:16:10,640 --> 00:16:15,080 Speaker 2: them haters, says, go f yourself. Like he he really 331 00:16:15,120 --> 00:16:19,880 Speaker 2: feels like every time somebody takes money away from X, 332 00:16:19,920 --> 00:16:24,200 Speaker 2: that's you know, a personal slight against him and the 333 00:16:24,240 --> 00:16:28,960 Speaker 2: company and the future. This you know, consciousness of humanity 334 00:16:29,040 --> 00:16:32,240 Speaker 2: or what have you. This is about Fidelity telling its 335 00:16:32,280 --> 00:16:35,880 Speaker 2: investors here's what we have and what it's worth based 336 00:16:35,920 --> 00:16:38,240 Speaker 2: on our best guesses, based on all the numbers we 337 00:16:38,360 --> 00:16:41,600 Speaker 2: have all you know, whether it's a third party valuation 338 00:16:41,920 --> 00:16:45,440 Speaker 2: or you know, market comps or what have you. This 339 00:16:45,560 --> 00:16:48,520 Speaker 2: is Fidelity, you know, not making it about Elon just 340 00:16:48,600 --> 00:16:51,520 Speaker 2: kind of giving an update to their portfolio. 341 00:16:51,720 --> 00:16:54,680 Speaker 1: Do we have any sense actually what goes into this 342 00:16:54,680 --> 00:16:57,320 Speaker 1: this sort of valuation, or like what they're even going on. 343 00:16:57,480 --> 00:16:59,560 Speaker 2: I mean, that's that's the hard part. It's all behind 344 00:16:59,560 --> 00:17:02,480 Speaker 2: the scenes that we know that X has given its 345 00:17:03,120 --> 00:17:06,840 Speaker 2: largest holders some information about the progress of the business. 346 00:17:07,200 --> 00:17:11,760 Speaker 2: Bloomberg reported that the company's ad sales were projected to 347 00:17:11,960 --> 00:17:16,080 Speaker 2: slump this year to about two point five billion. That 348 00:17:16,280 --> 00:17:20,720 Speaker 2: is a dramatic slump from from last year. So there's 349 00:17:20,760 --> 00:17:23,359 Speaker 2: some real, you know, money at play here. I should 350 00:17:23,359 --> 00:17:27,919 Speaker 2: note that this change in valuation happened almost right after 351 00:17:28,560 --> 00:17:32,280 Speaker 2: the Musk comments to advertisers at the deal Book conference. 352 00:17:32,359 --> 00:17:35,960 Speaker 2: This is a November thirtieth update, so it could have 353 00:17:36,040 --> 00:17:38,320 Speaker 2: even you know, they're going to have to reevaluate it. 354 00:17:38,840 --> 00:17:41,479 Speaker 1: And does this have any impact on the you know, 355 00:17:41,520 --> 00:17:43,359 Speaker 1: the debt payments that Elon Musk give, you know, the 356 00:17:43,560 --> 00:17:47,280 Speaker 1: efforts to renegotiate debt, like the like what Sarah looking ahead, 357 00:17:47,680 --> 00:17:50,880 Speaker 1: where is X financially and like, does does Elon Musk 358 00:17:50,920 --> 00:17:53,119 Speaker 1: have you know, have any hope of of sort of 359 00:17:53,359 --> 00:17:54,520 Speaker 1: quickly turning things around? 360 00:17:55,040 --> 00:17:57,240 Speaker 2: Well quickly is going to be tough, but you know, 361 00:17:57,600 --> 00:18:01,280 Speaker 2: all of the banks have the debt on hand on 362 00:18:01,320 --> 00:18:04,600 Speaker 2: their balance sheets. Obviously it's been uncomfortable for them. They 363 00:18:04,600 --> 00:18:07,560 Speaker 2: can't sell it. They've tried, and they have this agreement 364 00:18:07,600 --> 00:18:10,479 Speaker 2: amongst themselves that if they sell it, you know, everyone 365 00:18:10,520 --> 00:18:12,880 Speaker 2: gets to sell it at the same price. So it's 366 00:18:12,880 --> 00:18:15,520 Speaker 2: not like, you know, Morgan Stanley can just sell it 367 00:18:15,560 --> 00:18:18,639 Speaker 2: at twenty cents on the dollar and get rid of it. 368 00:18:19,160 --> 00:18:23,120 Speaker 2: If they sell it at that amount, everyone is allowed 369 00:18:23,160 --> 00:18:26,360 Speaker 2: to sell whatever portion they have. That's so they don't 370 00:18:26,440 --> 00:18:30,560 Speaker 2: end up undercutting each other on offloading this debt. Eventually, 371 00:18:31,000 --> 00:18:32,960 Speaker 2: so a few things could happen. I mean, there could 372 00:18:33,000 --> 00:18:38,200 Speaker 2: be restructuring of X. If it gets really bad, they 373 00:18:38,200 --> 00:18:41,800 Speaker 2: could go into some as Musk has hinted at. I 374 00:18:41,840 --> 00:18:48,080 Speaker 2: don't think that they will because if that happens, then 375 00:18:48,240 --> 00:18:53,280 Speaker 2: all the equity would just become zero. And I don't 376 00:18:53,320 --> 00:18:55,640 Speaker 2: think that Musk would want to do that to all 377 00:18:55,720 --> 00:19:01,120 Speaker 2: his close friends and investors that put money into this company. 378 00:19:01,160 --> 00:19:04,840 Speaker 2: And he's actually said like, I don't I don't plan 379 00:19:04,960 --> 00:19:08,800 Speaker 2: to start losing money for people now. So I think 380 00:19:08,800 --> 00:19:10,360 Speaker 2: he's going to try to find a way to turn 381 00:19:10,400 --> 00:19:13,359 Speaker 2: it around. My best guess is that he's going to 382 00:19:13,560 --> 00:19:18,520 Speaker 2: use the Grock AI as like a launch point for 383 00:19:18,600 --> 00:19:23,240 Speaker 2: trying to make X about more than just a social 384 00:19:23,280 --> 00:19:27,040 Speaker 2: network and ride the AI hypewave. That's one way that 385 00:19:27,040 --> 00:19:30,040 Speaker 2: could happen. But then, you know, everyone has a chatbot now, 386 00:19:30,080 --> 00:19:31,159 Speaker 2: so how special is that? 387 00:19:31,840 --> 00:19:38,080 Speaker 4: I guess we'll see, all right, Before we get to 388 00:19:38,119 --> 00:19:40,480 Speaker 4: any you know, full fully fledged predictions, I want to 389 00:19:40,520 --> 00:19:43,159 Speaker 4: ask one more question to Dana, which is, you know, 390 00:19:43,320 --> 00:19:45,800 Speaker 4: we've been talking I feel like for a year, over 391 00:19:45,840 --> 00:19:47,440 Speaker 4: a year really over. 392 00:19:47,560 --> 00:19:50,960 Speaker 1: The sort of behavior on X potentially spilling over to Tesla. 393 00:19:51,040 --> 00:19:54,560 Speaker 1: You know, we got these new numbers basically meeting expectations. 394 00:19:54,640 --> 00:19:57,679 Speaker 1: Why hasn't what's happening on X seemed to have an 395 00:19:57,720 --> 00:20:00,399 Speaker 1: impact on Tesla? And can we are we getting to 396 00:20:00,400 --> 00:20:02,080 Speaker 1: the point where you can include maybe it won't like 397 00:20:02,160 --> 00:20:04,760 Speaker 1: maybe maybe the attributes of the car, you know, exist 398 00:20:04,880 --> 00:20:05,440 Speaker 1: on their own. 399 00:20:06,080 --> 00:20:07,760 Speaker 3: Well, I mean, you and I have kind of wrote 400 00:20:07,760 --> 00:20:10,000 Speaker 3: a story about this last year, right, Like, there's definitely 401 00:20:10,119 --> 00:20:13,320 Speaker 3: anecdotal evidence that there are there's like a never Tesla crowd. 402 00:20:13,359 --> 00:20:15,680 Speaker 3: There are consumers out in the world who will never 403 00:20:15,680 --> 00:20:18,119 Speaker 3: buy a Tesla because they think that what Elon Musk 404 00:20:18,160 --> 00:20:23,119 Speaker 3: has done to Twitter slash X is like abhorrent and 405 00:20:23,160 --> 00:20:26,680 Speaker 3: like they're just never going to buy a Tesla. But fundamentally, 406 00:20:26,720 --> 00:20:29,760 Speaker 3: people buy cars because of the price and the range 407 00:20:29,840 --> 00:20:32,720 Speaker 3: and the quality of the technology, and like Tesla is 408 00:20:32,720 --> 00:20:34,600 Speaker 3: still kind of the main game in town, at least 409 00:20:34,600 --> 00:20:36,120 Speaker 3: here in the United States. I think the other thing 410 00:20:36,200 --> 00:20:39,240 Speaker 3: is that how Elon behaves, it's so much more of 411 00:20:39,280 --> 00:20:41,480 Speaker 3: like a US centric thing that people pay attention to 412 00:20:41,600 --> 00:20:44,080 Speaker 3: than it is globally, Like I'm not I'm not aware 413 00:20:44,119 --> 00:20:47,920 Speaker 3: of like how closely the average consumer in China tracks 414 00:20:47,920 --> 00:20:50,560 Speaker 3: what Elon Musk is saying on Twitter at you know, 415 00:20:50,640 --> 00:20:53,040 Speaker 3: two o'clock in the morning. And so the brand has 416 00:20:53,080 --> 00:20:56,120 Speaker 3: always been very closely intertwined with Elon. But what you're 417 00:20:56,160 --> 00:20:58,800 Speaker 3: seeing on X and Sarah alluded to this earlier, is 418 00:20:59,520 --> 00:21:02,879 Speaker 3: like a lot more Tesla executives are now using X 419 00:21:02,920 --> 00:21:06,240 Speaker 3: to kind of promote the company, like like more executives 420 00:21:06,240 --> 00:21:10,080 Speaker 3: are tweeting, you know, every every facet of Tesla now 421 00:21:10,080 --> 00:21:12,440 Speaker 3: has its own handle, like the cyber truck and the 422 00:21:13,400 --> 00:21:17,320 Speaker 3: recruiting team and the factories and like optimists th Robot 423 00:21:17,359 --> 00:21:20,000 Speaker 3: has its own like you know, Twitter account, And so 424 00:21:20,320 --> 00:21:22,800 Speaker 3: you're seeing more the company do a lot more kind 425 00:21:22,840 --> 00:21:26,479 Speaker 3: of marketing on X. And to Sarah's point, they're going 426 00:21:26,520 --> 00:21:28,520 Speaker 3: to start advertising or they already have or like that. 427 00:21:28,680 --> 00:21:30,320 Speaker 3: That's going to be a really interesting thing to watch 428 00:21:30,320 --> 00:21:31,240 Speaker 3: in twenty twenty four. 429 00:21:32,040 --> 00:21:35,119 Speaker 1: All right, so we'll we'll keep an eye on that. 430 00:21:35,320 --> 00:21:37,920 Speaker 1: But now I want to turn to predictions. It's it's 431 00:21:38,080 --> 00:21:40,280 Speaker 1: the beginning of the year. I think we should go around. 432 00:21:40,320 --> 00:21:43,440 Speaker 1: Each of us should make a prediction. Sarah, let's start 433 00:21:43,440 --> 00:21:45,640 Speaker 1: with you predictions for twenty twenty four. 434 00:21:46,080 --> 00:21:50,280 Speaker 2: So I think that we are going to see X 435 00:21:50,880 --> 00:21:57,200 Speaker 2: have much less influence on the twenty twenty four elections 436 00:21:57,280 --> 00:22:00,840 Speaker 2: than everyone thinks they will. I think by then the 437 00:22:00,840 --> 00:22:07,640 Speaker 2: political conversation will have moved maybe elsewhere, or or if 438 00:22:07,640 --> 00:22:11,840 Speaker 2: it is if it is another Trump versus Biden election, 439 00:22:12,119 --> 00:22:13,720 Speaker 2: I think that there's just going to be a lot 440 00:22:13,760 --> 00:22:18,240 Speaker 2: of widespread apathy about that pairing and people who dislike 441 00:22:18,320 --> 00:22:21,840 Speaker 2: both candidates, and there just won't be nearly the level 442 00:22:21,880 --> 00:22:26,400 Speaker 2: of discussion line that we saw in the prior election. 443 00:22:26,800 --> 00:22:32,320 Speaker 2: So maybe this is my like fingers crossed. 444 00:22:31,920 --> 00:22:34,640 Speaker 1: But you're just wish casting here, I think. 445 00:22:34,720 --> 00:22:37,040 Speaker 2: Well, I also think that you know, we're seeing a 446 00:22:37,080 --> 00:22:40,720 Speaker 2: decrease in relevance of the platform itself. 447 00:22:41,080 --> 00:22:45,200 Speaker 1: When Donald Trump names Grock his you know, likely candidate 448 00:22:45,280 --> 00:22:47,600 Speaker 1: for Secretary of Defense, then you will have to eat 449 00:22:47,640 --> 00:22:50,840 Speaker 1: your words. I will, Dana, what about you? What do 450 00:22:50,880 --> 00:22:53,280 Speaker 1: we have? Can you? Sarah gave us Actually what I 451 00:22:53,320 --> 00:22:56,160 Speaker 1: think is a pretty positive prediction. It's something to look 452 00:22:56,160 --> 00:22:58,280 Speaker 1: forward to for twenty twenty four. What do you have? 453 00:22:58,440 --> 00:23:01,840 Speaker 1: What are you sort of hoping for or expecting in 454 00:23:01,880 --> 00:23:02,320 Speaker 1: the new year. 455 00:23:02,520 --> 00:23:04,200 Speaker 3: So I guess my prediction is that I think Elon 456 00:23:04,280 --> 00:23:07,200 Speaker 3: Musk is going to increasingly cast himself as like an 457 00:23:07,200 --> 00:23:11,000 Speaker 3: aggrieved victim of government overreach. And we've already seen this 458 00:23:11,560 --> 00:23:14,919 Speaker 3: play out with you know, he has tangled with regulatory 459 00:23:15,040 --> 00:23:18,280 Speaker 3: agencies his entire career. You know, NITS is the fun Police, 460 00:23:18,320 --> 00:23:21,720 Speaker 3: the SEC is this Short Seller Enrichment Commission. 461 00:23:21,359 --> 00:23:24,000 Speaker 2: The FTC, and the FCC. He's no fan of them. 462 00:23:24,080 --> 00:23:29,040 Speaker 3: And like, as his empire grows, like various government agencies 463 00:23:29,040 --> 00:23:32,000 Speaker 3: are going to try to, you know, rain him in 464 00:23:32,280 --> 00:23:35,200 Speaker 3: with varying degrees and pretty limited success. But I think 465 00:23:35,240 --> 00:23:37,680 Speaker 3: that going into an election cycle, you're just going to 466 00:23:37,720 --> 00:23:40,680 Speaker 3: see Elon increasingly take the tack that like he is 467 00:23:40,680 --> 00:23:43,080 Speaker 3: a victim of big government overreach and that all these 468 00:23:43,119 --> 00:23:46,480 Speaker 3: regulatory agencies and Biden in particular are out to get him, 469 00:23:46,640 --> 00:23:50,000 Speaker 3: and that like these mean government people are trying to 470 00:23:50,800 --> 00:23:54,400 Speaker 3: you know, ruin him and don't appreciate all that he's 471 00:23:54,440 --> 00:23:57,080 Speaker 3: done for job growth in the United States. 472 00:23:57,240 --> 00:24:00,360 Speaker 1: My prediction is sort of related to Sarah's, but it's 473 00:24:00,359 --> 00:24:04,960 Speaker 1: maybe a little less serious. I predict that Elon Musk 474 00:24:05,080 --> 00:24:11,600 Speaker 1: and Georgia Maloney, the leader of Italy, will intensify their alliance. 475 00:24:11,840 --> 00:24:14,800 Speaker 1: However that means, and I do think we should be 476 00:24:14,920 --> 00:24:18,439 Speaker 1: on Elon Musk romance watch here. I hope I'm not 477 00:24:18,520 --> 00:24:21,440 Speaker 1: overstepping the bounds of the good sense of this podcast, 478 00:24:21,480 --> 00:24:24,200 Speaker 1: but Elon Musk spent part of December there. He spent 479 00:24:24,280 --> 00:24:26,960 Speaker 1: a lot of time talking about the need to make 480 00:24:27,040 --> 00:24:30,719 Speaker 1: more Italians, and I do think there's some breadcrumbs here 481 00:24:30,720 --> 00:24:32,400 Speaker 1: if we're willing to follow him, I. 482 00:24:32,320 --> 00:24:34,680 Speaker 3: Think the podcast might want to consider like a trip 483 00:24:34,720 --> 00:24:36,680 Speaker 3: to Italy to kind of do some on the ground 484 00:24:36,680 --> 00:24:39,119 Speaker 3: reporting here. I mean, it seems like this is you know, 485 00:24:39,200 --> 00:24:42,520 Speaker 3: New Year's New Beginnings Coliseum episode. A lot of people 486 00:24:43,400 --> 00:24:46,280 Speaker 3: take stock of their relationships when the New year begins. 487 00:24:46,800 --> 00:24:48,920 Speaker 1: I agree we need an off site and I will 488 00:24:49,000 --> 00:24:54,920 Speaker 1: bring that up with David Popadopolis the next time he's here. Okay, 489 00:24:55,000 --> 00:24:57,720 Speaker 1: let's leave it there. Thanks for listening to Elon Inc. 490 00:24:57,880 --> 00:25:00,840 Speaker 1: And thanks to our panel Sarah Fryar and Dana Hall. 491 00:25:01,680 --> 00:25:03,879 Speaker 2: Always a pleasure anytime. 492 00:25:10,920 --> 00:25:14,760 Speaker 1: This episode was produced by Stacy Wong. Naomi Shaven and 493 00:25:14,880 --> 00:25:18,879 Speaker 1: Rayhan Harmansi are our senior editors. The idea for this 494 00:25:19,280 --> 00:25:23,600 Speaker 1: very show also came from Rayhon Blake Maples handles engineering, 495 00:25:23,640 --> 00:25:26,359 Speaker 1: and we get special editing assistants from the one and 496 00:25:26,400 --> 00:25:30,880 Speaker 1: only Jeffrey Grocott. Our supervising producer is Magnus Hendrickson. Thanks 497 00:25:30,920 --> 00:25:33,960 Speaker 1: a bunch to BusinessWeek Editor Joel Weber. The Elon Inc. 498 00:25:34,080 --> 00:25:37,240 Speaker 1: Theme is written and performed by Taka Yazuzawa and Alex 499 00:25:37,280 --> 00:25:40,600 Speaker 1: Sigierira Sage Bauman is the head of Bloomberg Podcasts and 500 00:25:40,640 --> 00:25:44,320 Speaker 1: our executive producer. I'm Max Chafkin. If you have a minute, 501 00:25:44,480 --> 00:25:47,520 Speaker 1: rate and review our show, it'll help other listeners find 502 00:25:47,600 --> 00:25:50,080 Speaker 1: us and we will appreciate it. Happy New Year to 503 00:25:50,080 --> 00:25:51,160 Speaker 1: you and see you next week.