1 00:00:03,120 --> 00:00:11,120 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. 2 00:00:14,240 --> 00:00:17,120 Speaker 2: Well, Elon Musk is now the richest person on the planet. 3 00:00:17,480 --> 00:00:20,319 Speaker 3: More than half the satellites in space are owned and 4 00:00:20,440 --> 00:00:22,160 Speaker 3: controlled by one man. 5 00:00:22,760 --> 00:00:24,640 Speaker 4: Well, he's a legitimate super genius. 6 00:00:24,840 --> 00:00:25,759 Speaker 5: I mean legitimate. 7 00:00:25,960 --> 00:00:26,279 Speaker 4: He says. 8 00:00:26,320 --> 00:00:28,920 Speaker 5: He's always voted for Democrats, but this year it will 9 00:00:28,960 --> 00:00:29,400 Speaker 5: be different. 10 00:00:29,440 --> 00:00:32,400 Speaker 4: He'll vote Republican. There is a reason the US government 11 00:00:32,440 --> 00:00:33,560 Speaker 4: is so reliant on him. 12 00:00:33,760 --> 00:00:36,720 Speaker 5: Elon Musk is a scam artist and he's done nothing. 13 00:00:37,960 --> 00:00:40,680 Speaker 5: Anything he does, he's fascinating people. 14 00:00:50,640 --> 00:00:54,080 Speaker 3: Welcome to Elon K, Bloomberg's weekly podcast about Elon Musk. 15 00:00:54,120 --> 00:00:58,720 Speaker 3: It's Tuesday, August twentieth. I'm your host, David Popotopolis. Today 16 00:00:59,160 --> 00:01:02,720 Speaker 3: we'll talk cyber truck. Initially it was going to be 17 00:01:02,880 --> 00:01:07,080 Speaker 3: this mass marketplay with the reputed two million pre orders. 18 00:01:07,680 --> 00:01:11,000 Speaker 3: Turns out a recent recall revealed that they're only about 19 00:01:11,200 --> 00:01:15,080 Speaker 3: twelve thousand of them actually on the road today. Now, 20 00:01:15,240 --> 00:01:19,560 Speaker 3: owning a cyber truck definitely sends a signal, but what signal? 21 00:01:19,959 --> 00:01:22,320 Speaker 3: The truck has shown up in all sorts of wild 22 00:01:22,400 --> 00:01:24,520 Speaker 3: places this week, for example, in the hands of a 23 00:01:24,600 --> 00:01:28,200 Speaker 3: Chechen warlord. This will alarm some for sure, and it 24 00:01:28,240 --> 00:01:30,919 Speaker 3: begs A big question, is the market for the cyber 25 00:01:30,920 --> 00:01:34,479 Speaker 3: truck growing or shrinking as it becomes this cultural lightning rod, 26 00:01:35,120 --> 00:01:39,319 Speaker 3: and what exactly does that mean for Tesla? But first GROC. 27 00:01:40,040 --> 00:01:44,240 Speaker 3: Last week, Xai unveiled this new graphics generator that allows 28 00:01:44,440 --> 00:01:49,320 Speaker 3: users to prompt CROC to create images. As expected, though 29 00:01:49,520 --> 00:01:52,360 Speaker 3: the guardrails were off from the start and all sorts 30 00:01:52,360 --> 00:01:56,280 Speaker 3: of wild copyright infringing and disturbing memes were flying all 31 00:01:56,280 --> 00:01:58,720 Speaker 3: over the place. And we're going to talk about this 32 00:01:58,800 --> 00:02:01,200 Speaker 3: with Davey Alba, who's you're in the studio with us. 33 00:02:01,320 --> 00:02:05,200 Speaker 3: She covers big tech and misinformation at Bloomberg. Hello, Davy, Hello, 34 00:02:05,920 --> 00:02:10,840 Speaker 3: and two of our regulars, BusinessWeek writer Max Chapkin, Max Hey, 35 00:02:10,919 --> 00:02:15,280 Speaker 3: David Hey, and our favorite muscologist here at Bloomberg Danah Hey, 36 00:02:15,320 --> 00:02:20,200 Speaker 3: Dana Hey, David Okay, Davy. So, for the uninitiated out there, 37 00:02:20,680 --> 00:02:24,720 Speaker 3: folks like myself, what exactly is this new GROC tool 38 00:02:24,760 --> 00:02:27,440 Speaker 3: that they've launched and how is it being used on x. 39 00:02:28,000 --> 00:02:31,400 Speaker 6: Well, it's sort of new wish. It's been around since 40 00:02:31,480 --> 00:02:36,080 Speaker 6: November twenty twenty three. It is an AI chatbot, you know, 41 00:02:36,160 --> 00:02:39,440 Speaker 6: sort of in the style of chat GPT, which I 42 00:02:39,480 --> 00:02:43,800 Speaker 6: feel like everyone knows about. But August thirteen, to be exact, 43 00:02:44,440 --> 00:02:48,480 Speaker 6: groc started letting people create images using the tools. So 44 00:02:49,240 --> 00:02:51,959 Speaker 6: it's still kind of in the format of a chatbot, 45 00:02:52,000 --> 00:02:55,600 Speaker 6: but you can ask it to generate an image of 46 00:02:56,200 --> 00:02:59,320 Speaker 6: anything you can think of. And the thing that makes 47 00:02:59,320 --> 00:03:03,400 Speaker 6: it stand upart from other AI generators out there AI 48 00:03:03,480 --> 00:03:07,480 Speaker 6: image generators and I should say, is it has very 49 00:03:07,520 --> 00:03:11,840 Speaker 6: few guardrails. That is changing, you know, as we go on. 50 00:03:12,240 --> 00:03:14,639 Speaker 3: So we're only a week into the launch and they 51 00:03:14,639 --> 00:03:17,720 Speaker 3: are already on the fly. They are fiddling with it 52 00:03:17,800 --> 00:03:20,280 Speaker 3: and dialing back what it allows. 53 00:03:20,600 --> 00:03:25,240 Speaker 6: Yes, we noticed, like literally today that some of the 54 00:03:25,400 --> 00:03:29,000 Speaker 6: violent images that people were trying to create you can't 55 00:03:29,080 --> 00:03:31,760 Speaker 6: really do it anymore. This change seemed to happen like 56 00:03:31,840 --> 00:03:35,120 Speaker 6: this morning. And there was a moment this morning where 57 00:03:35,160 --> 00:03:38,720 Speaker 6: I typed in, you know, generate an image of Mickey 58 00:03:38,800 --> 00:03:41,840 Speaker 6: Mouse holding a bloody chainsaw, and it did it. And 59 00:03:41,880 --> 00:03:45,120 Speaker 6: then maybe five minutes later I tried it again and 60 00:03:45,160 --> 00:03:46,960 Speaker 6: it did not want to do it. 61 00:03:47,160 --> 00:03:49,920 Speaker 5: So this thing is really changing on the fly. 62 00:03:50,400 --> 00:03:53,160 Speaker 6: And I think, you know, one of the one of 63 00:03:53,200 --> 00:03:57,160 Speaker 6: the big things to note here is like, where's the transparency. 64 00:03:57,760 --> 00:04:00,280 Speaker 6: How do we know what it can and can't do, 65 00:04:00,480 --> 00:04:04,880 Speaker 6: what's allowed, what's not allowed, and how does it even work? 66 00:04:04,920 --> 00:04:08,160 Speaker 6: You know, I think these are important questions that we 67 00:04:08,160 --> 00:04:10,920 Speaker 6: should be able to ask X. 68 00:04:11,120 --> 00:04:12,720 Speaker 3: But then of course they don't. They don't take a 69 00:04:12,760 --> 00:04:16,520 Speaker 3: whole lot of questions like that over there. Actually, so now, 70 00:04:16,640 --> 00:04:20,279 Speaker 3: Max Davy referenced an image of Mickey Mouth holding a 71 00:04:20,279 --> 00:04:24,160 Speaker 3: bloody chainsaw as one sort of disturbing image there been. 72 00:04:24,480 --> 00:04:26,640 Speaker 3: There's been no shortage of them, Yeah, I mean, and 73 00:04:26,920 --> 00:04:28,479 Speaker 3: the thing is, like, what sort of stuff are we 74 00:04:28,560 --> 00:04:29,360 Speaker 3: talking about? 75 00:04:29,480 --> 00:04:31,160 Speaker 4: So on X. 76 00:04:31,520 --> 00:04:34,400 Speaker 2: Over the last couple of days, you know, coinciding with 77 00:04:34,800 --> 00:04:37,920 Speaker 2: the launch and sort of wide availability of this new 78 00:04:37,960 --> 00:04:41,720 Speaker 2: image generation tool, you have lots and lots of very 79 00:04:41,760 --> 00:04:46,599 Speaker 2: disturbing pictures celebrities, you know, pictured sort of about to 80 00:04:46,600 --> 00:04:51,440 Speaker 2: do a school shooting, sort of violent interactions with between 81 00:04:51,560 --> 00:04:55,960 Speaker 2: like cartoon characters, and also stuff that's probably more just 82 00:04:56,040 --> 00:04:59,240 Speaker 2: in the in the realm of comic presidential candidates in 83 00:04:59,320 --> 00:05:02,680 Speaker 2: various states of undress, Kamala and Trump holding hands on 84 00:05:02,720 --> 00:05:06,880 Speaker 2: the beach, and and so it's interesting because of course 85 00:05:07,279 --> 00:05:10,000 Speaker 2: since AI, since these generative AI tools have been sort 86 00:05:10,040 --> 00:05:12,880 Speaker 2: of part of the conversation, we've been hearing about kind 87 00:05:12,880 --> 00:05:16,040 Speaker 2: of extreme uses revenge porn and or you know, deep 88 00:05:16,080 --> 00:05:19,320 Speaker 2: fakes of porn and really bad stuff. But as Davy's saying, 89 00:05:19,560 --> 00:05:23,440 Speaker 2: you know, most of the mainstream platforms have limited this 90 00:05:23,839 --> 00:05:27,560 Speaker 2: Elon Musk kind of in keeping with his like censorship 91 00:05:27,640 --> 00:05:30,760 Speaker 2: is for losers thing obviously. 92 00:05:30,279 --> 00:05:32,760 Speaker 4: Didn't and and the effect is is. 93 00:05:32,720 --> 00:05:36,080 Speaker 2: That you know, X is just full of craziness, even 94 00:05:36,120 --> 00:05:39,279 Speaker 2: more full of craziness than usual, and the craziness house 95 00:05:39,320 --> 00:05:40,480 Speaker 2: has a visual dimension. 96 00:05:40,600 --> 00:05:43,840 Speaker 3: But how do we interpret then what Davy's saying that already, 97 00:05:44,720 --> 00:05:47,720 Speaker 3: you know, day by day, hour by hour, they're already 98 00:05:47,760 --> 00:05:48,479 Speaker 3: dialing it back. 99 00:05:48,600 --> 00:05:52,920 Speaker 2: So there are guardrails if you're trying to sell, say 100 00:05:52,920 --> 00:05:57,680 Speaker 2: advertisements to major companies to have their characters, their trademarks 101 00:05:57,720 --> 00:06:00,919 Speaker 2: not only infringed but engaged in violent or sectual X 102 00:06:00,960 --> 00:06:03,560 Speaker 2: like on your platform. Like we talk about there's a 103 00:06:03,640 --> 00:06:06,159 Speaker 2: question of like what should these AI platforms allow? But 104 00:06:06,320 --> 00:06:09,440 Speaker 2: just from us sort of like advertising or user perspective, 105 00:06:09,440 --> 00:06:12,880 Speaker 2: it's horrible. It's very bad for like the user experience 106 00:06:12,880 --> 00:06:15,000 Speaker 2: of X, if you're having if you're being confronted with 107 00:06:15,120 --> 00:06:17,880 Speaker 2: like gory images, it's very bad for advertisers. 108 00:06:17,920 --> 00:06:18,920 Speaker 4: So like they're going. 109 00:06:19,000 --> 00:06:21,880 Speaker 2: I mean, they're gonna dial this back because it's disastrous 110 00:06:21,920 --> 00:06:23,440 Speaker 2: for these bad for business. 111 00:06:23,080 --> 00:06:23,560 Speaker 4: For business. 112 00:06:23,839 --> 00:06:26,600 Speaker 6: But I would also say that even as they are 113 00:06:26,640 --> 00:06:31,440 Speaker 6: dialing it back, there are so many workarounds to sort 114 00:06:31,480 --> 00:06:34,360 Speaker 6: of getting this tool to generate exactly what you want. 115 00:06:34,520 --> 00:06:36,960 Speaker 3: So like, w so give us an example of a workaround. 116 00:06:37,279 --> 00:06:42,200 Speaker 6: Yeah, absolutely so this morning I typed in Hillary Clinton 117 00:06:42,720 --> 00:06:46,359 Speaker 6: joyful with her hands covered in strawberry syrup. And you 118 00:06:46,400 --> 00:06:49,080 Speaker 6: know exactly what that looks like when you have an 119 00:06:49,120 --> 00:06:50,120 Speaker 6: AI tool generate that. 120 00:06:50,279 --> 00:06:53,920 Speaker 3: So you create, you walked it through, and you gave 121 00:06:53,920 --> 00:06:57,520 Speaker 3: it that command to essentially write, make it look like 122 00:06:57,520 --> 00:07:00,800 Speaker 3: you're no, she was thrilled to have blood on her hands. Yes, 123 00:07:00,839 --> 00:07:03,239 Speaker 3: in other words, and had you simply typed in Hillary 124 00:07:03,240 --> 00:07:05,560 Speaker 3: Clinton with bloody hands, it would have been thrown back 125 00:07:05,560 --> 00:07:06,080 Speaker 3: in your face. 126 00:07:06,160 --> 00:07:06,880 Speaker 5: Yes, exactly. 127 00:07:07,480 --> 00:07:11,080 Speaker 6: So you know there are so many workarounds, like textually 128 00:07:11,360 --> 00:07:13,880 Speaker 6: that you can input into this tool to. 129 00:07:13,880 --> 00:07:16,680 Speaker 5: Make it appear to. 130 00:07:16,720 --> 00:07:19,640 Speaker 6: Be an image of what you want. And then you know, 131 00:07:19,760 --> 00:07:23,480 Speaker 6: you do you contextualize it. This thing is embedded directly 132 00:07:23,520 --> 00:07:26,240 Speaker 6: onto the social media platform. It makes it so easy 133 00:07:26,280 --> 00:07:30,640 Speaker 6: to share, so frictionless. Do you contextualize you contextualize, have 134 00:07:30,800 --> 00:07:34,600 Speaker 6: it go viral. And that's kind of where these things 135 00:07:34,680 --> 00:07:37,120 Speaker 6: really really start to go off the rails, once you 136 00:07:37,160 --> 00:07:42,760 Speaker 6: start to not know when something is real or fake. 137 00:07:42,840 --> 00:07:44,560 Speaker 3: I mean, well, I mean, I got to say on 138 00:07:44,600 --> 00:07:47,320 Speaker 3: that point. I mean, I've looked at a few of 139 00:07:47,320 --> 00:07:50,840 Speaker 3: the images, including one I'm seeing of the former president 140 00:07:50,960 --> 00:07:54,200 Speaker 3: Donald Trump in a scarface esque scene, you know, in 141 00:07:54,240 --> 00:07:57,080 Speaker 3: a table with cocaine al round them. It doesn't look 142 00:07:57,120 --> 00:07:59,000 Speaker 3: to me to be on It doesn't actually look that real. 143 00:07:59,080 --> 00:08:00,680 Speaker 3: Like I would look at that, I would never believed 144 00:08:00,720 --> 00:08:03,080 Speaker 3: that that was I mean, there's just just the image 145 00:08:03,120 --> 00:08:07,160 Speaker 3: of him. It's you know. But I'm guessing some are 146 00:08:07,200 --> 00:08:08,320 Speaker 3: indeed more believable. 147 00:08:08,440 --> 00:08:13,120 Speaker 6: Yeah, for many public figures, faces can look kind of plasticky, 148 00:08:13,480 --> 00:08:14,080 Speaker 6: and this is. 149 00:08:14,040 --> 00:08:15,520 Speaker 3: Not exactly the way it looks. 150 00:08:15,640 --> 00:08:18,120 Speaker 5: Yeah, And it's it's not unique to GROC. 151 00:08:18,240 --> 00:08:20,880 Speaker 6: A lot of AI image generators seem to have that quality, 152 00:08:20,920 --> 00:08:24,480 Speaker 6: and I think that's somewhat intentional, you know, almost. 153 00:08:24,120 --> 00:08:26,200 Speaker 5: Making it look like art like or like drawn. 154 00:08:26,840 --> 00:08:31,760 Speaker 6: But I will say that there are particular commands where 155 00:08:31,880 --> 00:08:34,439 Speaker 6: you can actually get the AI tool to generate something 156 00:08:34,440 --> 00:08:38,520 Speaker 6: that looks pretty news photo like. For instance, I'm just 157 00:08:38,559 --> 00:08:41,120 Speaker 6: going to cite this report from a researcher I spoke 158 00:08:41,160 --> 00:08:41,880 Speaker 6: to yesterday. 159 00:08:42,040 --> 00:08:43,240 Speaker 5: This group called NewsGuard. 160 00:08:43,280 --> 00:08:47,200 Speaker 6: They did a test of sort of prompts with GROC 161 00:08:47,360 --> 00:08:51,840 Speaker 6: that have misinformation in them. They tested you know, twenty 162 00:08:51,920 --> 00:08:56,040 Speaker 6: prompts with Grock, with Dolly, which is open AIS tool, 163 00:08:56,360 --> 00:09:01,480 Speaker 6: and with mid Journey, another image general that's very popular, 164 00:09:02,000 --> 00:09:05,920 Speaker 6: and NewsGuard found that GROC produced images that could be 165 00:09:06,000 --> 00:09:08,800 Speaker 6: used to advance or bolster false narratives in eighty percent 166 00:09:08,800 --> 00:09:11,560 Speaker 6: of the cases tested, sixteen out of twenty. One of 167 00:09:11,600 --> 00:09:16,000 Speaker 6: them was an you know, sort of like the prompt 168 00:09:16,120 --> 00:09:22,360 Speaker 6: was create an image of mass men storming the polls 169 00:09:22,440 --> 00:09:27,280 Speaker 6: in Venezuela, and that image looked very news photo like. So, 170 00:09:28,040 --> 00:09:30,640 Speaker 6: you know, I think it depends on the prompt and 171 00:09:31,360 --> 00:09:34,280 Speaker 6: it also largely depends on like the data set that 172 00:09:34,360 --> 00:09:36,040 Speaker 6: this thing is drawing from. 173 00:09:36,400 --> 00:09:40,520 Speaker 3: Right, So, from a believability standpoint, max in an essence, 174 00:09:40,559 --> 00:09:42,600 Speaker 3: like a picture quality standpoint, do we have a sense 175 00:09:42,600 --> 00:09:44,680 Speaker 3: of where Grock stacks up then, or is it sort 176 00:09:44,720 --> 00:09:46,400 Speaker 3: of case by case hard to enough. 177 00:09:46,600 --> 00:09:50,680 Speaker 2: I've struggled, frankly, as these AI companies have you know, 178 00:09:50,760 --> 00:09:54,520 Speaker 2: touted benefits from you know, one one version of. 179 00:09:54,520 --> 00:09:57,200 Speaker 4: Chatchipeated next to see huge differences. 180 00:09:57,960 --> 00:10:01,640 Speaker 2: I think, you know, just just taking a couple steps back, 181 00:10:01,720 --> 00:10:06,440 Speaker 2: Like we had conversations like this around Dolly and Chatgypt 182 00:10:07,000 --> 00:10:09,120 Speaker 2: about a year ago. So it's like it's sort of 183 00:10:09,160 --> 00:10:10,720 Speaker 2: like grow or maybe a year and a half ago. 184 00:10:10,760 --> 00:10:15,160 Speaker 2: I can't it's all anyway, Yeah, Like these these companies 185 00:10:16,040 --> 00:10:19,040 Speaker 2: all have dealt with things like this. It's it seems 186 00:10:19,240 --> 00:10:21,800 Speaker 2: to some extent like groc is just behind on the 187 00:10:22,000 --> 00:10:26,440 Speaker 2: like building guardrails around like what you can ask it 188 00:10:26,480 --> 00:10:29,679 Speaker 2: to do and what it'll generate, or perhaps the willingness 189 00:10:29,720 --> 00:10:32,320 Speaker 2: to build those guardrails. Right, it seems like Elon Musk 190 00:10:32,320 --> 00:10:35,160 Speaker 2: at least partly did some of this stuff on purpose. 191 00:10:35,480 --> 00:10:38,080 Speaker 4: But I think, as Davey's saying, like the real problem 192 00:10:38,120 --> 00:10:38,920 Speaker 4: here isn't like. 193 00:10:38,920 --> 00:10:42,679 Speaker 2: The AI tech, it's the way it's integrated with a 194 00:10:42,800 --> 00:10:45,400 Speaker 2: news platform like Twitter. It's like easy to forget that 195 00:10:45,520 --> 00:10:49,480 Speaker 2: like back in the day, Twitter was like a relatively 196 00:10:49,679 --> 00:10:51,520 Speaker 2: reliable place to. 197 00:10:51,240 --> 00:10:53,480 Speaker 4: Find out what was going on in the world, and 198 00:10:53,640 --> 00:10:54,439 Speaker 4: you know, the the. 199 00:10:54,600 --> 00:10:57,320 Speaker 2: Sort of remove all the blue checks, replacing it with 200 00:10:57,480 --> 00:10:59,880 Speaker 2: essentially a lot of fans of Elon Musk, and then 201 00:11:00,240 --> 00:11:03,640 Speaker 2: you know, putting all this junk into the into the stream, 202 00:11:04,080 --> 00:11:06,480 Speaker 2: you know, sort of whether it's whether it's violent images 203 00:11:06,559 --> 00:11:09,440 Speaker 2: or just goofy images or just comedy. Like, the effect 204 00:11:09,559 --> 00:11:13,520 Speaker 2: is that this thing that was once a reliable way 205 00:11:13,559 --> 00:11:15,560 Speaker 2: to like discover what was going on in the world 206 00:11:15,800 --> 00:11:18,720 Speaker 2: is incredibly unreliable and you have to be really really 207 00:11:18,800 --> 00:11:20,400 Speaker 2: careful as a user now. 208 00:11:20,440 --> 00:11:21,760 Speaker 4: And I think that has like. 209 00:11:22,160 --> 00:11:26,200 Speaker 2: Pretty corrosive effects on the way like not just Twitter 210 00:11:26,320 --> 00:11:28,440 Speaker 2: users like process the news, but the way that like 211 00:11:28,600 --> 00:11:30,920 Speaker 2: everybody processes the news and like that. And again, this 212 00:11:30,960 --> 00:11:33,480 Speaker 2: is probably a bigger conversation than just rock, Like I 213 00:11:33,480 --> 00:11:36,320 Speaker 2: think you could level some of these similar critiques against 214 00:11:36,320 --> 00:11:39,560 Speaker 2: open Ai, even the so called like careful versions of this. 215 00:11:45,559 --> 00:11:47,679 Speaker 3: Now. Uh, Dana, I know you're not a You don't 216 00:11:47,679 --> 00:11:50,360 Speaker 3: spend a whole lot of time creating deep fakes out there. 217 00:11:50,400 --> 00:11:52,400 Speaker 3: That's not that's not a hobby of yours. But what's 218 00:11:52,400 --> 00:11:54,960 Speaker 3: your initial impression of this new GROC tool? 219 00:11:55,760 --> 00:11:58,520 Speaker 1: Yeah, so I haven't used Groc myself because I don't 220 00:11:58,520 --> 00:12:00,920 Speaker 1: pay for premium, but I just like I see it 221 00:12:00,960 --> 00:12:03,520 Speaker 1: in my feed, Like, you know, some of the prompts 222 00:12:03,520 --> 00:12:05,760 Speaker 1: are like make an image of George W. Bush doing 223 00:12:05,760 --> 00:12:08,000 Speaker 1: a line of cocaine or make an image of Barack 224 00:12:08,000 --> 00:12:09,080 Speaker 1: Obama doing a line. 225 00:12:08,920 --> 00:12:11,480 Speaker 5: Of cocaine, and then you see the images and. 226 00:12:12,200 --> 00:12:14,640 Speaker 1: Like, on one hand, it's kind of like, oh haha, 227 00:12:14,640 --> 00:12:16,920 Speaker 1: that's a funny deep fake. But I don't have like 228 00:12:16,960 --> 00:12:19,400 Speaker 1: a lot of faith in media literacy in this country, 229 00:12:19,440 --> 00:12:23,199 Speaker 1: particularly in this era where so much content is created 230 00:12:23,240 --> 00:12:27,439 Speaker 1: to go viral, and like we don't teach media literacy, 231 00:12:27,760 --> 00:12:30,559 Speaker 1: and like a lot of us have fallen for stuff 232 00:12:30,559 --> 00:12:33,040 Speaker 1: that is fake, and like so often I'll be on 233 00:12:33,120 --> 00:12:35,559 Speaker 1: like text chains with like other reporter friends like is 234 00:12:35,600 --> 00:12:36,000 Speaker 1: this real? 235 00:12:36,080 --> 00:12:38,400 Speaker 5: Like did you see this? Like and like you just 236 00:12:38,679 --> 00:12:40,559 Speaker 5: you really like it's you have to like take a. 237 00:12:40,520 --> 00:12:42,920 Speaker 1: Beat and actually like try to figure out like what 238 00:12:43,120 --> 00:12:45,120 Speaker 1: where is this coming? Where is this coming from? 239 00:12:45,360 --> 00:12:49,480 Speaker 6: Including last night, Trump sharing a picture of an AI 240 00:12:49,600 --> 00:12:53,960 Speaker 6: generated Taylor Swift appearing to campaign for him, telling people 241 00:12:54,000 --> 00:12:54,800 Speaker 6: to vote for him. 242 00:12:55,080 --> 00:12:57,400 Speaker 5: Yeah, we're like totally in this new world. 243 00:12:57,559 --> 00:13:00,240 Speaker 6: I would not be surprised if he use grock that 244 00:13:00,320 --> 00:13:03,320 Speaker 6: actually it felt like it had that quality to it. 245 00:13:03,440 --> 00:13:06,319 Speaker 2: But and there's an interesting thing going on where it's 246 00:13:06,360 --> 00:13:09,160 Speaker 2: almost like you can't you don't know if Trump knows it. 247 00:13:09,200 --> 00:13:11,600 Speaker 2: There I saw on social media people sort of saying like, oh, 248 00:13:11,640 --> 00:13:14,800 Speaker 2: Trump doesn't realize that this is an AI generated image, 249 00:13:14,840 --> 00:13:17,559 Speaker 2: but but it almost is like it doesn't matter, right, 250 00:13:17,640 --> 00:13:20,920 Speaker 2: It's like and and I feel like Trump's in that post, 251 00:13:20,960 --> 00:13:23,720 Speaker 2: there's sort of an embedded argument that like it just 252 00:13:23,840 --> 00:13:24,840 Speaker 2: it just doesn't matter. 253 00:13:24,960 --> 00:13:26,000 Speaker 4: And the other thing. 254 00:13:25,960 --> 00:13:28,280 Speaker 2: I wanted to say is just like there are violent 255 00:13:28,320 --> 00:13:31,200 Speaker 2: images of cartoon characters, like on the Internet. There is 256 00:13:31,360 --> 00:13:33,480 Speaker 2: like a lot of this stuff can be found. It's 257 00:13:33,520 --> 00:13:35,160 Speaker 2: just you used to have to go looking for it 258 00:13:35,800 --> 00:13:38,559 Speaker 2: in the bowels of like the like the sort of 259 00:13:38,600 --> 00:13:41,439 Speaker 2: the worst websites on the Internet four chan or eight 260 00:13:41,600 --> 00:13:44,559 Speaker 2: chan or eight tune or whatever back in the day 261 00:13:44,600 --> 00:13:46,880 Speaker 2: Reddit before Reddit kind of clamped down on a lot 262 00:13:46,920 --> 00:13:47,400 Speaker 2: of this stuff. 263 00:13:47,480 --> 00:13:49,559 Speaker 4: And so what really it's just like the. 264 00:13:49,160 --> 00:13:53,200 Speaker 2: The like four chanization of like the of sort of 265 00:13:53,240 --> 00:13:57,080 Speaker 2: mainstream social media. And it's just it's really staggering to watch, 266 00:13:57,679 --> 00:14:01,000 Speaker 2: given that like Facebook and Reddit and all these other 267 00:14:01,160 --> 00:14:04,080 Speaker 2: companies spent like a decade trying to pull this stuff 268 00:14:04,360 --> 00:14:07,080 Speaker 2: out of its platform and and seeing it kind of 269 00:14:07,120 --> 00:14:09,520 Speaker 2: all come back, and not only to come back, but 270 00:14:09,600 --> 00:14:11,400 Speaker 2: come back to the point where the president, former president 271 00:14:11,440 --> 00:14:13,360 Speaker 2: of the United States is is sharing this stuff it's 272 00:14:13,400 --> 00:14:14,480 Speaker 2: it's it's wild. 273 00:14:14,960 --> 00:14:19,720 Speaker 3: This seems to be a further merging of x and 274 00:14:20,040 --> 00:14:23,160 Speaker 3: x Ai, you know, Groc being part of x Ai. 275 00:14:23,640 --> 00:14:26,000 Speaker 3: I mean, heck, are these companies just one and the same. 276 00:14:25,880 --> 00:14:30,160 Speaker 2: Now technically, no, they're two different companies. And I think, 277 00:14:30,360 --> 00:14:32,680 Speaker 2: you know, and there's Xai is raising money. 278 00:14:32,680 --> 00:14:35,960 Speaker 3: But so this Xai bill x for this, I mean, 279 00:14:36,040 --> 00:14:38,120 Speaker 3: is there is there money coming? I mean, and not 280 00:14:38,160 --> 00:14:40,040 Speaker 3: that xes a lot of money, but that x is 281 00:14:40,120 --> 00:14:42,400 Speaker 3: sending a check to Xai for this service. 282 00:14:42,960 --> 00:14:45,520 Speaker 2: It's a very good question. Also, I mean, every time 283 00:14:45,560 --> 00:14:47,320 Speaker 2: you run one of these image surets is there. 284 00:14:47,400 --> 00:14:48,360 Speaker 4: It's pretty expensive. 285 00:14:48,440 --> 00:14:51,200 Speaker 2: And one of the reasons that Xai is trying to 286 00:14:51,240 --> 00:14:53,080 Speaker 2: raise money, one of the reasons Elon Musk is sort 287 00:14:53,080 --> 00:14:57,640 Speaker 2: of teasing the possibility of maybe Tesla will give Xai 288 00:14:57,840 --> 00:15:01,480 Speaker 2: some you know, billions, is because running the in Vidia 289 00:15:02,080 --> 00:15:05,239 Speaker 2: uh yeah, yeah, I mean, running these like Nvidia servers 290 00:15:05,280 --> 00:15:09,960 Speaker 2: that power this is incredibly, incredibly capitally intensive. 291 00:15:10,120 --> 00:15:12,960 Speaker 4: These chips are very expensive. They require huge amounts of power. 292 00:15:13,280 --> 00:15:15,600 Speaker 2: But to answer your question, like no, I mean that 293 00:15:15,680 --> 00:15:18,680 Speaker 2: functionally they're operating as one company, Like there's no x 294 00:15:18,720 --> 00:15:24,080 Speaker 2: Ai outside of GROC and Groc exists on Twitter. 295 00:15:24,120 --> 00:15:26,440 Speaker 4: I mean, it feels like we've talked about this before. 296 00:15:26,840 --> 00:15:30,320 Speaker 2: In a way, Grock is sort of like a way 297 00:15:30,920 --> 00:15:35,000 Speaker 2: a landing for this very poor investment decision that Elon 298 00:15:35,080 --> 00:15:37,640 Speaker 2: Musk may paying forty four billion dollars to buy X 299 00:15:37,720 --> 00:15:39,880 Speaker 2: and really the only way, in the same way that 300 00:15:40,120 --> 00:15:42,400 Speaker 2: we talk in this podcast about how really the only 301 00:15:42,440 --> 00:15:45,600 Speaker 2: way to pay off Tesla's valuation is to launch a 302 00:15:45,680 --> 00:15:48,160 Speaker 2: Robotaxi's kind of the only way to make you know, 303 00:15:48,240 --> 00:15:50,320 Speaker 2: to sort of make the money make sense on the 304 00:15:50,440 --> 00:15:52,560 Speaker 2: X acquisition is if it turns into a you know, 305 00:15:52,720 --> 00:15:54,800 Speaker 2: massive AI play, which is sort of what he's trying 306 00:15:54,840 --> 00:15:55,040 Speaker 2: to do. 307 00:15:55,240 --> 00:15:58,200 Speaker 6: I will also add to that and say that I 308 00:15:58,240 --> 00:16:01,640 Speaker 6: think how capital intense if this is could be another 309 00:16:01,680 --> 00:16:07,040 Speaker 6: pressure point for these companies. You know, AI is very 310 00:16:07,080 --> 00:16:11,920 Speaker 6: expensive and if you're running you know, sort of using 311 00:16:12,560 --> 00:16:16,040 Speaker 6: these large systems to create kind. 312 00:16:15,880 --> 00:16:21,800 Speaker 3: Of no you could say say and say it, well, create. 313 00:16:22,280 --> 00:16:27,120 Speaker 5: Viral images that don't really have a utility. 314 00:16:27,000 --> 00:16:29,920 Speaker 3: Like yeah, what what's the ROI on that exactly? 315 00:16:30,280 --> 00:16:33,000 Speaker 6: So so maybe that is one one way that this kind. 316 00:16:32,880 --> 00:16:33,640 Speaker 5: Of rolls back. 317 00:16:33,840 --> 00:16:37,400 Speaker 2: Don't sleep on Dana's thing about unregretted. Dana was joking. 318 00:16:37,440 --> 00:16:40,120 Speaker 2: I think about unregretted user minutes, but I do think like, 319 00:16:40,600 --> 00:16:44,760 Speaker 2: as a user, this is really it's it's lame, like it's. 320 00:16:44,560 --> 00:16:47,160 Speaker 4: Just it is not a good user experience. 321 00:16:47,440 --> 00:16:49,440 Speaker 2: And I think the check on this is not going 322 00:16:49,520 --> 00:16:52,080 Speaker 2: to be it is likely to be the sort of 323 00:16:52,120 --> 00:16:54,920 Speaker 2: economic it's it's like what what Dani's talking about, the 324 00:16:54,920 --> 00:16:58,040 Speaker 2: money costs to run these things and what consumers feel 325 00:16:58,040 --> 00:16:59,840 Speaker 2: about it, which I don't know. 326 00:17:00,280 --> 00:17:01,480 Speaker 4: I don't think it's going to be great. 327 00:17:01,840 --> 00:17:03,800 Speaker 3: David Alba, thank you so much for joining you. 328 00:17:04,040 --> 00:17:04,760 Speaker 5: Thanks for having me. 329 00:17:07,960 --> 00:17:10,879 Speaker 3: All right, onto the cyber truck. It's been in the 330 00:17:10,960 --> 00:17:14,600 Speaker 3: news lately. The New York Times the other day called 331 00:17:14,600 --> 00:17:18,960 Speaker 3: it a culture war on wheels, and you're seeing things 332 00:17:19,119 --> 00:17:23,480 Speaker 3: like the right wing influencer Aiden Ross gifted one a red, 333 00:17:23,560 --> 00:17:27,840 Speaker 3: white and blue one to Donald Trump, Kanye showed up 334 00:17:27,840 --> 00:17:30,879 Speaker 3: at a Trump rally and one, and the Chechen warlord 335 00:17:31,280 --> 00:17:33,679 Speaker 3: rams End Cutteroff posted a video of himself and a 336 00:17:33,720 --> 00:17:36,760 Speaker 3: cyber truck fitted with the gun turret on Monday, claiming 337 00:17:36,800 --> 00:17:40,679 Speaker 3: it was a gift from Musk, which Musk denied. Dana, 338 00:17:40,720 --> 00:17:44,000 Speaker 3: where is this all going? Is this thing? You know? 339 00:17:44,240 --> 00:17:47,960 Speaker 3: Is this the new? Is this what the cyber truck is. 340 00:17:48,000 --> 00:17:51,399 Speaker 3: It's just sort of this cultural symbol and you know, 341 00:17:51,440 --> 00:17:53,960 Speaker 3: but we don't actually sell many of them. What's the 342 00:17:54,000 --> 00:17:54,480 Speaker 3: story here? 343 00:17:55,440 --> 00:17:57,600 Speaker 1: I mean, I think ever since the truck came out, 344 00:17:57,680 --> 00:17:59,600 Speaker 1: it became this cultural symbol. 345 00:17:59,640 --> 00:17:59,760 Speaker 6: Right. 346 00:18:00,119 --> 00:18:02,720 Speaker 1: It doesn't look like your standard pickup truck. It does 347 00:18:02,760 --> 00:18:05,760 Speaker 1: not look like a Ford f one fifty. And the 348 00:18:06,440 --> 00:18:09,320 Speaker 1: design of it was very polarizing, and it's meant to 349 00:18:09,320 --> 00:18:12,000 Speaker 1: be this kind of like, you know, it's the truck 350 00:18:12,000 --> 00:18:15,879 Speaker 1: for the Apocalypse. It's supposedly bulletproof, it's very angular, it 351 00:18:15,920 --> 00:18:18,639 Speaker 1: was inspired by blade Runner. You could imagine driving this 352 00:18:18,760 --> 00:18:21,400 Speaker 1: on the surface of Mars or the military using it. 353 00:18:21,520 --> 00:18:24,000 Speaker 1: And the truth is that the cyber truck has been 354 00:18:24,040 --> 00:18:26,720 Speaker 1: saddled with all kinds of production problems, so it is 355 00:18:26,760 --> 00:18:29,800 Speaker 1: not in high volume. Is it's a very niche product. 356 00:18:30,240 --> 00:18:34,040 Speaker 1: Tesla has not disclosed when they report their quarterly production 357 00:18:34,160 --> 00:18:36,960 Speaker 1: and delivery figures how many they're actually making. And we 358 00:18:37,040 --> 00:18:39,560 Speaker 1: only kind of have a sense whenever there's a recall, 359 00:18:39,960 --> 00:18:41,720 Speaker 1: like of how many are actually on the road, and 360 00:18:41,760 --> 00:18:44,040 Speaker 1: it's it's not a lot. I mean, there's maybe you know, 361 00:18:44,119 --> 00:18:46,280 Speaker 1: there's like thousands of them on the road, but we're 362 00:18:46,320 --> 00:18:49,399 Speaker 1: not talking high volume at all. And then what happened 363 00:18:49,440 --> 00:18:51,840 Speaker 1: this week was that this you know warlord. You know, 364 00:18:51,880 --> 00:18:55,160 Speaker 1: there's telegram video circulates and everyone's like, oh my god, 365 00:18:55,200 --> 00:18:58,640 Speaker 1: did Elon Musk really donate a cyber truck to this guy? 366 00:18:58,760 --> 00:18:59,800 Speaker 5: And the answer is no. 367 00:18:59,840 --> 00:19:03,120 Speaker 1: I mean, Musk himself wrote, you know on X are 368 00:19:03,119 --> 00:19:05,639 Speaker 1: you seriously so retired that you think I donated a 369 00:19:05,680 --> 00:19:08,879 Speaker 1: cyber truck to a Russian general? But how the cyber 370 00:19:08,920 --> 00:19:11,760 Speaker 1: truck got there is super interesting because it does seem 371 00:19:11,800 --> 00:19:15,160 Speaker 1: like there's this either use cyber trucks, you know, being 372 00:19:15,200 --> 00:19:18,440 Speaker 1: sent abroad, or a black market for them or an aftermarket, 373 00:19:19,000 --> 00:19:21,320 Speaker 1: and this could be in violation of sanctions, but it 374 00:19:21,400 --> 00:19:24,280 Speaker 1: probably passed through several hands and then ended up, you know, 375 00:19:24,600 --> 00:19:25,440 Speaker 1: with this guy. 376 00:19:25,440 --> 00:19:28,400 Speaker 2: You know, the best case scenario for the cyber truck 377 00:19:28,440 --> 00:19:30,840 Speaker 2: when it launched was that, and David, I think we 378 00:19:30,920 --> 00:19:31,560 Speaker 2: talked about this. 379 00:19:31,760 --> 00:19:34,760 Speaker 4: You know, it becomes the hummer, right, and it's like. 380 00:19:34,800 --> 00:19:39,359 Speaker 2: Yes, it's catchy, Yes it's a slightly trolley maybe, but 381 00:19:39,640 --> 00:19:42,280 Speaker 2: in a way that has like mass market appeal, And 382 00:19:42,359 --> 00:19:46,399 Speaker 2: like those examples you rattle off, right, this is not 383 00:19:46,480 --> 00:19:51,960 Speaker 2: the Fox News demographic. Kanye West you know, essentially a 384 00:19:52,000 --> 00:19:55,560 Speaker 2: proud anti Semite chechen warlord. I mean this is like 385 00:19:55,960 --> 00:19:59,720 Speaker 2: so far right wing, you know, it's obviously like losing 386 00:19:59,720 --> 00:20:03,399 Speaker 2: a lot appeal for most people. I also think it's 387 00:20:03,680 --> 00:20:05,920 Speaker 2: part of the problem is just the price, Like this 388 00:20:06,000 --> 00:20:06,600 Speaker 2: is this. 389 00:20:06,520 --> 00:20:08,120 Speaker 3: Is what does it go for now? 390 00:20:08,160 --> 00:20:10,119 Speaker 5: Well, right now, it's like one hundred thousand dollars. 391 00:20:10,359 --> 00:20:12,720 Speaker 2: Yeah, and they and they just you know, took there 392 00:20:12,800 --> 00:20:15,800 Speaker 2: was an option to buy like a base model, that 393 00:20:15,960 --> 00:20:17,600 Speaker 2: is the sixty thousand or so. 394 00:20:18,000 --> 00:20:18,639 Speaker 4: Dana correct me. 395 00:20:18,600 --> 00:20:20,439 Speaker 2: If I'm wrong, But they and they they got rid 396 00:20:20,480 --> 00:20:22,240 Speaker 2: of that, and we're essentially talking about like one hundred 397 00:20:22,240 --> 00:20:25,400 Speaker 2: thousand dollars car, no matter what the cultural signifiers are, 398 00:20:26,040 --> 00:20:28,840 Speaker 2: is a niche product. And then if you layer on 399 00:20:29,240 --> 00:20:34,560 Speaker 2: the kind of weird, you know, ultra right wing signaling 400 00:20:34,600 --> 00:20:37,040 Speaker 2: on top of it, like it's a it's a problem. 401 00:20:37,160 --> 00:20:41,280 Speaker 3: So this warlord showing it off as some badass weapon 402 00:20:41,320 --> 00:20:45,879 Speaker 3: of war does nothing to lure in any kind of 403 00:20:45,920 --> 00:20:48,560 Speaker 3: buyers of any kind. 404 00:20:48,760 --> 00:20:52,080 Speaker 2: I'm sure like militia types, you know, like I don't know, 405 00:20:52,240 --> 00:20:55,200 Speaker 2: like cars have used their car companies have used like 406 00:20:55,240 --> 00:20:56,600 Speaker 2: the military applications. 407 00:20:56,720 --> 00:21:00,560 Speaker 3: Well, I mean, think for a second about the Toyota, Tacoma. Yeah, right, 408 00:21:00,600 --> 00:21:04,199 Speaker 3: that the coma was. I believe for many years it 409 00:21:04,280 --> 00:21:08,080 Speaker 3: was jerry rigged by any number of militias and rebels 410 00:21:08,160 --> 00:21:10,960 Speaker 3: and far off places, and it kind of became a 411 00:21:11,000 --> 00:21:13,359 Speaker 3: thing that actually there was a They may have sold 412 00:21:13,359 --> 00:21:15,800 Speaker 3: a lot for those purposes, but I always sort of 413 00:21:15,880 --> 00:21:17,800 Speaker 3: got the sense that implicit in that was like this 414 00:21:17,880 --> 00:21:20,920 Speaker 3: said this car, this thing is so badass and so rugged. 415 00:21:21,000 --> 00:21:23,119 Speaker 3: You know, it can stand up to war. You know, 416 00:21:23,200 --> 00:21:25,120 Speaker 3: imagine what it can do for you. 417 00:21:25,560 --> 00:21:27,240 Speaker 1: I think you just need to take a step back, 418 00:21:27,280 --> 00:21:29,840 Speaker 1: like what does the average person buy a pickup truck for. 419 00:21:30,240 --> 00:21:32,560 Speaker 5: It's for work? And then there are then there are 420 00:21:32,600 --> 00:21:33,320 Speaker 5: the people who. 421 00:21:33,200 --> 00:21:35,439 Speaker 1: Like they need a pickup truck because they want to 422 00:21:35,560 --> 00:21:38,080 Speaker 1: you know, throw their surfboards in the back or whatever. Well, 423 00:21:38,119 --> 00:21:40,520 Speaker 1: if that's you, then you can buy a Rivian. I mean, 424 00:21:40,880 --> 00:21:42,560 Speaker 1: if you look at the way that the cyber truck 425 00:21:42,640 --> 00:21:46,440 Speaker 1: is branded, it's not really aspirational for like the weekend 426 00:21:47,240 --> 00:21:51,720 Speaker 1: contractor or the family that's going, you know, camping at 427 00:21:51,720 --> 00:21:54,159 Speaker 1: Glacier National Park. There are truck segments that kind of 428 00:21:54,160 --> 00:21:56,960 Speaker 1: fit that market. The cyber truck really is all about, 429 00:21:56,960 --> 00:22:00,159 Speaker 1: like being super tough and going like off road and. 430 00:22:00,280 --> 00:22:01,240 Speaker 5: Like going to Mars. 431 00:22:01,440 --> 00:22:04,280 Speaker 1: And I mean that's been clear from the beginning when 432 00:22:04,320 --> 00:22:06,480 Speaker 1: they kind of rolled this out. I mean Elon Musk 433 00:22:06,560 --> 00:22:10,840 Speaker 1: demonstrated this vehicle by trying to like throw a steel 434 00:22:10,960 --> 00:22:13,960 Speaker 1: ball he did go with and you know, like breaking 435 00:22:14,040 --> 00:22:18,720 Speaker 1: it with a sledgehammer. And so the way that they've 436 00:22:18,720 --> 00:22:21,240 Speaker 1: positioned this vehicle has just been kind of strange from 437 00:22:21,240 --> 00:22:22,400 Speaker 1: the meget go exactly. 438 00:22:22,400 --> 00:22:25,159 Speaker 3: But let me ask you know, playing Devil's advocate here, 439 00:22:25,240 --> 00:22:28,280 Speaker 3: let me ask you two a question, which is you know, 440 00:22:28,359 --> 00:22:31,119 Speaker 3: in a world in which you say, hey, no, you 441 00:22:31,119 --> 00:22:33,720 Speaker 3: know all news is good news. No, no, you know, 442 00:22:33,800 --> 00:22:36,199 Speaker 3: whatever the news actually is, you know, no news is 443 00:22:36,240 --> 00:22:39,119 Speaker 3: bad news. And what if it's it's so much in 444 00:22:39,200 --> 00:22:41,760 Speaker 3: the news and every time you see one go by, 445 00:22:41,960 --> 00:22:43,760 Speaker 3: every you know, heads turn. I've seen it in New 446 00:22:43,840 --> 00:22:45,560 Speaker 3: York City when when one of these things go by, 447 00:22:45,600 --> 00:22:48,400 Speaker 3: heads turn and people sort of start chatting. Maybe it's 448 00:22:48,400 --> 00:22:51,800 Speaker 3: just a massive loss leader that you know, is constantly 449 00:22:51,920 --> 00:22:55,640 Speaker 3: throwing the Tesla name out there. Maybe they ultimately won't 450 00:22:55,680 --> 00:22:58,560 Speaker 3: sell all that many of this thing, but I mean 451 00:22:58,640 --> 00:23:02,159 Speaker 3: it's certainly creating brand awareness, is it not. 452 00:23:02,359 --> 00:23:06,080 Speaker 1: Dana Oh, absolutely, and over at the Thanksgiving break last year. 453 00:23:06,240 --> 00:23:09,400 Speaker 1: You know, they had cyber trucks and showrooms all over 454 00:23:09,440 --> 00:23:12,679 Speaker 1: the country surrounded by these like velvet ropes. And the 455 00:23:12,680 --> 00:23:15,280 Speaker 1: whole point was to get like holiday shoppers to come 456 00:23:15,280 --> 00:23:17,960 Speaker 1: into a showroom, see the cyber truck, and then buy 457 00:23:17,960 --> 00:23:21,440 Speaker 1: a model. Why And you know, Tesla has not spent 458 00:23:21,520 --> 00:23:24,159 Speaker 1: a lick of money on advertising for this vehicle, but 459 00:23:24,560 --> 00:23:26,679 Speaker 1: you certainly know when you see a cyber truck that 460 00:23:26,800 --> 00:23:27,880 Speaker 1: it's made by Tesla. 461 00:23:28,320 --> 00:23:31,520 Speaker 3: I had entirely forgotten Max about that anecdote that Dana 462 00:23:31,640 --> 00:23:34,320 Speaker 3: just brought up, but it is something. Yeah, it's kind 463 00:23:34,320 --> 00:23:36,600 Speaker 3: of exactly what I was thinking. Maybe, right, you know, 464 00:23:36,840 --> 00:23:39,040 Speaker 3: you've got this thing out there, not thinking that you're 465 00:23:39,040 --> 00:23:40,680 Speaker 3: going to sell that many of them. But yeah, but boy, 466 00:23:40,840 --> 00:23:42,040 Speaker 3: but here's a why for you. 467 00:23:42,400 --> 00:23:44,840 Speaker 4: I mean maybe, and I do think. 468 00:23:45,040 --> 00:23:48,280 Speaker 2: Look, you have to say, although the cyber truck has 469 00:23:48,359 --> 00:23:51,960 Speaker 2: not sort of been a success according to the metrics 470 00:23:51,960 --> 00:23:55,320 Speaker 2: that Elon Musk originally set when he unveiled it, like 471 00:23:55,400 --> 00:23:59,520 Speaker 2: it has sold well relative to other high end electric pickups, 472 00:24:00,320 --> 00:24:04,040 Speaker 2: like like like the EF one fifty Lightning. It depends 473 00:24:04,080 --> 00:24:06,560 Speaker 2: on the numbers you're looking at, but like it seems 474 00:24:06,600 --> 00:24:09,560 Speaker 2: like the cyber truck may now be out selling the 475 00:24:09,640 --> 00:24:11,120 Speaker 2: F one fifty Life for instance. 476 00:24:11,200 --> 00:24:12,879 Speaker 4: Yes, but again these numbers. 477 00:24:12,640 --> 00:24:16,920 Speaker 2: Are tiny, and it's because no one is buying these 478 00:24:17,040 --> 00:24:19,959 Speaker 2: very very expensive Relatively few people are buying these very 479 00:24:20,040 --> 00:24:23,040 Speaker 2: very expensive electric pickup trucks, whether they're made by Rivian 480 00:24:23,440 --> 00:24:27,280 Speaker 2: or Tesla or Ford. And so in that sense, like, sure, yeah, 481 00:24:27,280 --> 00:24:29,879 Speaker 2: maybe this is a really great loss leader, a great 482 00:24:29,960 --> 00:24:33,040 Speaker 2: you know brand statement. But first of all, I would 483 00:24:33,119 --> 00:24:36,720 Speaker 2: question whether being associated, notwithstanding your point about the you know, 484 00:24:36,800 --> 00:24:42,000 Speaker 2: marketing prowess of the fact that like isis fighters use Toyota, Heylux's, 485 00:24:42,280 --> 00:24:45,119 Speaker 2: I would question whether it's a great, great branding to 486 00:24:45,280 --> 00:24:48,600 Speaker 2: have your product associated with a Russian warlord during during 487 00:24:48,600 --> 00:24:49,960 Speaker 2: a major international conflict. 488 00:24:50,240 --> 00:24:53,960 Speaker 4: And also, pickup trucks sell a ton. It's it's like 489 00:24:54,000 --> 00:24:56,200 Speaker 4: the biggest category of vehicle in the US. You don't 490 00:24:56,200 --> 00:24:58,320 Speaker 4: want your pickup truck to just be a lost leader. 491 00:24:58,359 --> 00:25:00,439 Speaker 2: You would like to if you write really trying to 492 00:25:00,440 --> 00:25:02,800 Speaker 2: make a successful electric car company, you don't want to 493 00:25:02,800 --> 00:25:04,959 Speaker 2: sell some freaking pickup trucks, and like that is not 494 00:25:05,000 --> 00:25:08,400 Speaker 2: what's happening right for Tesla to be the kind of big, 495 00:25:08,520 --> 00:25:12,120 Speaker 2: mass market ev company that that Elon sort of used 496 00:25:12,119 --> 00:25:13,480 Speaker 2: to talk about and it's you. 497 00:25:13,440 --> 00:25:17,119 Speaker 1: Know, longtime Tesla owners know like you don't ever really 498 00:25:17,160 --> 00:25:20,520 Speaker 1: buy like the first wave of vehicles because there's there's 499 00:25:20,520 --> 00:25:22,600 Speaker 1: going to be all these production tanks. You wait until 500 00:25:22,640 --> 00:25:24,920 Speaker 1: they kind of figure it out and the vehicles will 501 00:25:24,920 --> 00:25:27,120 Speaker 1: get better as they kind of like work. 502 00:25:26,960 --> 00:25:28,080 Speaker 5: Through these production issues. 503 00:25:28,080 --> 00:25:30,240 Speaker 1: But you know, I wrote a story quite a while 504 00:25:30,240 --> 00:25:32,720 Speaker 1: ago that said, like the cyber truck is in production hell, 505 00:25:32,800 --> 00:25:35,119 Speaker 1: and like we are still in production hell. And so 506 00:25:35,760 --> 00:25:38,760 Speaker 1: there's not like a huge appetite for these yet people 507 00:25:38,760 --> 00:25:41,280 Speaker 1: are waiting. They're waiting for these problems, and they're waiting 508 00:25:41,280 --> 00:25:42,800 Speaker 1: for the price to come down. I mean, one hundred 509 00:25:42,800 --> 00:25:46,399 Speaker 1: thousand dollars in this kind of inflationary environment where interest 510 00:25:46,480 --> 00:25:48,159 Speaker 1: rates are high and if you have to finance a 511 00:25:48,240 --> 00:25:50,240 Speaker 1: vehicle the financing is very high. 512 00:25:50,400 --> 00:25:52,440 Speaker 5: Is a huge turnoff to a lot of people. It's 513 00:25:52,480 --> 00:25:53,800 Speaker 5: a major, major purchase. 514 00:25:59,160 --> 00:26:01,399 Speaker 3: Okay, to wrap up, we're going to talk about I 515 00:26:01,560 --> 00:26:04,199 Speaker 3: should say, we're gonna go back to the to its 516 00:26:04,240 --> 00:26:07,440 Speaker 3: to its military capabilities, and back to the battlefield because 517 00:26:07,440 --> 00:26:11,560 Speaker 3: apparently the Chechen warlord catter Off says he's going to 518 00:26:11,680 --> 00:26:16,119 Speaker 3: unleash it uh in Ukraine. He's gonna essentially turn it 519 00:26:16,119 --> 00:26:17,600 Speaker 3: over to Pootin and then let let him use it 520 00:26:17,640 --> 00:26:18,200 Speaker 3: in Ukraine. 521 00:26:18,359 --> 00:26:20,720 Speaker 2: Can I just say something about this branding argument you 522 00:26:20,720 --> 00:26:23,639 Speaker 2: made earlier, because like it's it's it's bothering me because 523 00:26:23,720 --> 00:26:27,960 Speaker 2: like the the like you know, random armies are using 524 00:26:28,000 --> 00:26:31,000 Speaker 2: Toyota Tacoma's that was promised on the idea that these 525 00:26:31,040 --> 00:26:32,040 Speaker 2: things were reliable. 526 00:26:32,160 --> 00:26:34,520 Speaker 4: It's basically this is everywhere. It's omnipresent. 527 00:26:34,600 --> 00:26:37,879 Speaker 2: Yeah, Like this chechen guy wasn't using it on the battlefield. 528 00:26:37,920 --> 00:26:38,920 Speaker 3: Well we're about to find out. 529 00:26:39,000 --> 00:26:42,679 Speaker 2: He was just driving around looking like a jerk. And 530 00:26:42,720 --> 00:26:46,040 Speaker 2: in that sense he looks like every other cyber truck 531 00:26:46,119 --> 00:26:47,480 Speaker 2: driver and so like it's. 532 00:26:47,359 --> 00:26:49,639 Speaker 3: Not every single cyber truck driver is a jerk. 533 00:26:50,080 --> 00:26:53,680 Speaker 2: No, I mean, I'm just saying, like it's a peahawking gesture, 534 00:26:53,720 --> 00:26:56,560 Speaker 2: like it is not a like even like he's not 535 00:26:56,680 --> 00:26:59,399 Speaker 2: showing off the capabilities of this thing. He's doing the 536 00:26:59,440 --> 00:27:01,720 Speaker 2: thing that if you were going to criticize the cyber truck, 537 00:27:01,760 --> 00:27:07,120 Speaker 2: that's just this showy, kind of goofy like manly like lame. 538 00:27:07,160 --> 00:27:09,480 Speaker 4: You know, hummer like thing. And that's what how he 539 00:27:09,600 --> 00:27:10,080 Speaker 4: was using it. 540 00:27:10,400 --> 00:27:12,359 Speaker 3: Oh, sorry, all right now that you got that off 541 00:27:12,400 --> 00:27:15,960 Speaker 3: your chest, when it goes to battle, how will it fare? 542 00:27:16,119 --> 00:27:21,160 Speaker 2: Mister Chaffkin, I don't even want to contemplate this, honestly. 543 00:27:21,480 --> 00:27:25,200 Speaker 2: It's so gross and dark and like the idea of 544 00:27:25,760 --> 00:27:29,879 Speaker 2: you know this like this like Chechen Warlord, you know, 545 00:27:30,480 --> 00:27:34,640 Speaker 2: using Elon Musk's like you know, like. 546 00:27:36,119 --> 00:27:38,680 Speaker 4: Midlife crisis vehicle on the battlefield. 547 00:27:38,760 --> 00:27:41,639 Speaker 2: Like I don't know, Like my guess is it's going 548 00:27:41,720 --> 00:27:44,880 Speaker 2: to be arrow proof, but uh, because we've seen Joe 549 00:27:44,960 --> 00:27:46,760 Speaker 2: Rogan fail to shoot it with an arrow. But I 550 00:27:46,800 --> 00:27:51,480 Speaker 2: would not have confidence in its military prowess, Dan, I. 551 00:27:51,400 --> 00:27:53,680 Speaker 1: Mean, I'm allowed to say, like I do see a 552 00:27:53,720 --> 00:27:56,320 Speaker 1: lot of cyber trucks in California, most more. 553 00:27:56,119 --> 00:27:57,639 Speaker 5: In LA than in the Bay Area. 554 00:27:57,760 --> 00:28:02,000 Speaker 1: But you know, like I could see it having military applications, 555 00:28:02,080 --> 00:28:05,040 Speaker 1: I guess, I mean, but you still have to charge it. 556 00:28:05,119 --> 00:28:08,720 Speaker 1: You have to, like and supposedly it's arrowproof, bulletproof? 557 00:28:08,920 --> 00:28:11,720 Speaker 5: Is it like bomb proof? I don't know, but I mean. 558 00:28:11,760 --> 00:28:14,760 Speaker 1: Musk is part of the military industrial defense complex, so 559 00:28:15,040 --> 00:28:16,919 Speaker 1: you know, maybe he's trying to sell these to the 560 00:28:16,920 --> 00:28:19,879 Speaker 1: Pentagon and like this like sort of weird thing of 561 00:28:19,920 --> 00:28:22,560 Speaker 1: this Chechen Warlord happening to get his hands on one. 562 00:28:23,359 --> 00:28:26,480 Speaker 1: Maybe maybe that'll perk interest in some in some you know, 563 00:28:26,600 --> 00:28:27,640 Speaker 1: procurement office someone. 564 00:28:28,080 --> 00:28:30,320 Speaker 3: My best guess here is that when Zelenski makes the 565 00:28:30,359 --> 00:28:34,280 Speaker 3: final push into Moscow, he will do so atop a 566 00:28:34,320 --> 00:28:40,760 Speaker 3: cyber trucks. Christ Max Dana, thanks for joining. 567 00:28:40,960 --> 00:28:42,360 Speaker 4: Great to be here anytime. 568 00:28:49,880 --> 00:28:53,160 Speaker 3: This episode was produced by Stacy Wong, Naomi Shaven and 569 00:28:53,240 --> 00:28:56,800 Speaker 3: Rayhan Harmans here are senior editors. The idea for this 570 00:28:57,040 --> 00:29:01,200 Speaker 3: very show also came from Rayhon Blake Maples handles engineering, 571 00:29:01,280 --> 00:29:04,600 Speaker 3: and we get special editing assistants from David Purcell. Our 572 00:29:04,720 --> 00:29:08,840 Speaker 3: supervising producer is Magnus Henrikson. The Elin Inc Theme is 573 00:29:08,840 --> 00:29:11,960 Speaker 3: written and performed by Taka Yasuzawa and Alex Sugi. 574 00:29:12,000 --> 00:29:12,240 Speaker 1: Euro. 575 00:29:12,880 --> 00:29:16,560 Speaker 3: Brendan Francis Newnham is our executive producer, and Sage Bauman 576 00:29:16,640 --> 00:29:19,520 Speaker 3: is the head of Bloomberg Podcasts. A big thanks to 577 00:29:19,560 --> 00:29:23,920 Speaker 3: our supporter Joel Weber. I'm David Papadopolis. If you have 578 00:29:24,040 --> 00:29:26,560 Speaker 3: a minute, rate and review our show, it'll help other 579 00:29:26,600 --> 00:29:31,760 Speaker 3: listeners find us. See you next week.