1 00:00:02,240 --> 00:00:05,560 Speaker 1: From the heart of where innovation, money and power COLLI 2 00:00:06,360 --> 00:00:10,920 Speaker 1: in Silicon Valley and beyond. This is Bloomberg Technology with 3 00:00:10,960 --> 00:00:27,840 Speaker 1: Emily Jay. I'memoly Jang in San Francisco, and this is 4 00:00:27,880 --> 00:00:30,720 Speaker 1: Bloomberg Technology. Coming up in the next hour, Elon Musk 5 00:00:30,920 --> 00:00:33,720 Speaker 1: teases his plans for Twitter. The billionaire wants to take 6 00:00:33,760 --> 00:00:37,199 Speaker 1: the social platform beyond the town square and create what 7 00:00:37,240 --> 00:00:40,559 Speaker 1: he's calling X, the everything app. What does he need? 8 00:00:41,120 --> 00:00:45,320 Speaker 1: We'll discuss. Plus, Facebook whistle blower Francis Halgan joins me 9 00:00:45,520 --> 00:00:49,319 Speaker 1: one year after her fiery testimony on Capitol Hill. We'll 10 00:00:49,320 --> 00:00:54,280 Speaker 1: talk about what's changed, what hasn't, and what stayed the same, 11 00:00:55,240 --> 00:00:58,040 Speaker 1: and is the blockchain the answer to get everyday people 12 00:00:58,040 --> 00:01:01,040 Speaker 1: to invest in private markets. One funds ends to tokenize 13 00:01:01,040 --> 00:01:04,720 Speaker 1: its investments could open the door to the masses. I 14 00:01:04,720 --> 00:01:07,200 Speaker 1: want to get back to our top story. Musk's about 15 00:01:07,200 --> 00:01:09,440 Speaker 1: face agreed to buy Twitter at the original price, but 16 00:01:09,920 --> 00:01:13,200 Speaker 1: the judge in the Twitter trial saying show will go 17 00:01:13,240 --> 00:01:15,960 Speaker 1: on for now. Let's break it all down with Bloomberg. 18 00:01:16,040 --> 00:01:19,240 Speaker 1: Sarah fryar So from a legal perspective, Sarah, Twitter hasn't 19 00:01:19,280 --> 00:01:22,600 Speaker 1: dropped its lawsuits. They're still going to court as of 20 00:01:22,680 --> 00:01:26,120 Speaker 1: now on October sevente Right, Well, we know that the 21 00:01:26,120 --> 00:01:28,880 Speaker 1: parties are meeting today. We know that Twitter is talking 22 00:01:28,920 --> 00:01:31,800 Speaker 1: with Elon Musk. But yeah, I mean they have not 23 00:01:31,920 --> 00:01:35,119 Speaker 1: said sure, we we trust that this offer that you've 24 00:01:35,120 --> 00:01:37,880 Speaker 1: made is is legitimate and we will do this. Um. 25 00:01:37,920 --> 00:01:40,760 Speaker 1: We haven't seen any joint statement. We haven't seen any 26 00:01:40,959 --> 00:01:43,839 Speaker 1: end to the saga yet. I think we're still staying 27 00:01:43,880 --> 00:01:47,039 Speaker 1: tuned for for what they might decide. And and hey, 28 00:01:47,120 --> 00:01:50,920 Speaker 1: if they don't come to an agreement, um, then we 29 00:01:51,040 --> 00:01:53,440 Speaker 1: might see must opposed in the next couple of days 30 00:01:53,440 --> 00:01:56,880 Speaker 1: and we might see, um, this go to court as 31 00:01:56,880 --> 00:02:00,160 Speaker 1: scheduled on October seventeen. Our understanding is that Twitter to 32 00:02:00,240 --> 00:02:04,520 Speaker 1: ask the court to provide a consent judgment if you will, 33 00:02:04,920 --> 00:02:07,400 Speaker 1: and you know, create an agreement between the court and 34 00:02:07,400 --> 00:02:10,800 Speaker 1: Twitter and Musk, not just between Twitter and Musk, uh, 35 00:02:11,200 --> 00:02:14,000 Speaker 1: that would be enforceable in a court of law. We 36 00:02:14,080 --> 00:02:16,239 Speaker 1: are getting a glimpse into his vision for the social 37 00:02:16,240 --> 00:02:18,480 Speaker 1: media platform. What do you make of this x the 38 00:02:18,600 --> 00:02:21,520 Speaker 1: everything app thing? What does he mean by that? You know, 39 00:02:21,600 --> 00:02:25,000 Speaker 1: you've talked a few times about the idea of having 40 00:02:25,360 --> 00:02:28,360 Speaker 1: an app in the US that would compete with the 41 00:02:28,480 --> 00:02:32,239 Speaker 1: likes of we chat in China. Um, I think we've 42 00:02:32,280 --> 00:02:36,440 Speaker 1: we've seen this ambition before. We've seen this from Mark Zuckerberg, 43 00:02:36,480 --> 00:02:39,120 Speaker 1: We've seen this from Evans speakl. Nobody had quite pulled 44 00:02:39,160 --> 00:02:42,680 Speaker 1: it off, though he's talcumented everything. App Um. I think 45 00:02:42,720 --> 00:02:45,800 Speaker 1: that that is is a big ambition of a lot 46 00:02:45,840 --> 00:02:48,760 Speaker 1: of folks that just the Internet. Um may not work 47 00:02:48,800 --> 00:02:51,880 Speaker 1: the same way here. We'll have to see meantime. You've 48 00:02:51,919 --> 00:02:55,720 Speaker 1: been doing some maths, and I believe the calculation is 49 00:02:55,800 --> 00:02:57,800 Speaker 1: if Elon must gets rid of all the boxs and 50 00:02:57,800 --> 00:03:00,400 Speaker 1: spam on Twitter, he might lose their teena and a 51 00:03:00,440 --> 00:03:04,840 Speaker 1: half million followers on his own. Yeah, I think I 52 00:03:04,880 --> 00:03:07,120 Speaker 1: think a lot of people will lose followers. Listen, And 53 00:03:07,440 --> 00:03:10,600 Speaker 1: it really depends on what you think of as a bought. 54 00:03:10,680 --> 00:03:12,880 Speaker 1: There are a lot of automated account on Twitter that 55 00:03:13,080 --> 00:03:15,160 Speaker 1: that people love, like such as once I tell you 56 00:03:15,240 --> 00:03:17,960 Speaker 1: when an earthquake has happened. Um, I don't think that 57 00:03:17,960 --> 00:03:22,079 Speaker 1: that's what Elon Musk is talking about. Um. His account 58 00:03:22,200 --> 00:03:27,280 Speaker 1: in particular tends to be disportionately affected by folks who 59 00:03:27,320 --> 00:03:29,920 Speaker 1: want to to take his identity to try to to 60 00:03:30,000 --> 00:03:33,760 Speaker 1: do crypto scams, for instance, So I think that um 61 00:03:33,800 --> 00:03:38,080 Speaker 1: that those celebrity accounts um do tend to be more 62 00:03:38,160 --> 00:03:40,520 Speaker 1: overrun by bots, and if he were to get rid 63 00:03:40,560 --> 00:03:43,520 Speaker 1: of that kind of of account on Twitter, would it 64 00:03:43,560 --> 00:03:47,760 Speaker 1: would affect the biggest names like Elon Musk, like Justin Bieber, 65 00:03:48,400 --> 00:03:51,960 Speaker 1: especially the longest standing accounts on Twitter. All right, well, 66 00:03:52,000 --> 00:03:55,160 Speaker 1: interesting that we're starting to see his vision and take 67 00:03:55,480 --> 00:03:59,160 Speaker 1: more shape. Of course, if the steal does indeed go 68 00:03:59,200 --> 00:04:12,400 Speaker 1: through Bloombergs frya thank you as always. One year ago, 69 00:04:12,600 --> 00:04:16,240 Speaker 1: former Facebook employee Francis Hogan shook Silicon Valley and the 70 00:04:16,279 --> 00:04:19,520 Speaker 1: world when she blew the whistle on Facebook. She turned 71 00:04:19,520 --> 00:04:22,679 Speaker 1: over tens of thousands of internal documents from the social 72 00:04:22,720 --> 00:04:27,240 Speaker 1: networking giant to the media and the SEC. The Facebook Papers, 73 00:04:27,320 --> 00:04:30,240 Speaker 1: as they've come to be known, contained disturbing facts about 74 00:04:30,240 --> 00:04:34,000 Speaker 1: the effects that social media platforms, including Instagram, we're having 75 00:04:34,080 --> 00:04:38,040 Speaker 1: on teens and kids. After testifying before US Congress, she 76 00:04:38,080 --> 00:04:41,640 Speaker 1: went on to speak around the world. The question is 77 00:04:41,680 --> 00:04:45,119 Speaker 1: what is Facebook doing to amplify or or expand hate? 78 00:04:45,200 --> 00:04:47,560 Speaker 1: What is it doing to amplify or expand eathing violence? 79 00:04:48,040 --> 00:04:49,840 Speaker 1: I mean, Faceboo didn't invent hate, but you think it's 80 00:04:49,839 --> 00:04:52,919 Speaker 1: making hate worse. Unquestionably, it's making hate worse. So in 81 00:04:52,960 --> 00:04:55,720 Speaker 1: the last year, what has changed, what's improved, and what's 82 00:04:55,760 --> 00:04:59,760 Speaker 1: left to do? Former Facebook employee turned whistleblower Francis Hogan 83 00:05:00,080 --> 00:05:03,040 Speaker 1: joins me. Now, Francis, thank you so much for joining us. 84 00:05:03,080 --> 00:05:06,200 Speaker 1: It is one year to the day since you testified 85 00:05:06,360 --> 00:05:09,520 Speaker 1: before US Congress, and I'm so curious what you feel 86 00:05:09,880 --> 00:05:13,400 Speaker 1: has changed for the better since then and how much 87 00:05:13,400 --> 00:05:15,280 Speaker 1: work is they're still left to do, you know. And 88 00:05:15,320 --> 00:05:19,800 Speaker 1: it's some really basic ways, Um, Facebook has changed substantially, right. So, 89 00:05:19,960 --> 00:05:23,200 Speaker 1: Facebook had ten years to release parental controls for Instagram 90 00:05:23,279 --> 00:05:25,719 Speaker 1: and it never got around to it until after my 91 00:05:25,720 --> 00:05:28,719 Speaker 1: disclosures came out. Uh. There are other things like Facebook 92 00:05:28,720 --> 00:05:31,240 Speaker 1: has never had any public programs around trying to be 93 00:05:31,320 --> 00:05:34,239 Speaker 1: more inclusive on its languages, and they launched something called 94 00:05:34,360 --> 00:05:37,240 Speaker 1: No Language Left Behind UM, which is still only a 95 00:05:37,360 --> 00:05:38,720 Speaker 1: you know, a drop in the bucket, but at least 96 00:05:38,720 --> 00:05:42,960 Speaker 1: they're trying UM. Internationally, we've seen some amazing progress legislatively, 97 00:05:43,200 --> 00:05:46,640 Speaker 1: so there's a law called the Digital Services Act, which 98 00:05:46,680 --> 00:05:50,320 Speaker 1: is the first law that has ever required the major 99 00:05:50,360 --> 00:05:53,800 Speaker 1: platforms to disclose what risks they have, Like actually, they 100 00:05:53,800 --> 00:05:56,400 Speaker 1: would have had to disclose the risks to kids. For example, 101 00:05:56,600 --> 00:05:59,599 Speaker 1: had this law they passed before that finally got across 102 00:05:59,640 --> 00:06:01,480 Speaker 1: the finish line in Europe after a four or five 103 00:06:02,120 --> 00:06:05,480 Speaker 1: year year push. The information my disclosure is was credited 104 00:06:05,480 --> 00:06:07,880 Speaker 1: with giving the last gas and the tank to get 105 00:06:07,880 --> 00:06:10,160 Speaker 1: across the finish line. So some things have changed, but 106 00:06:10,200 --> 00:06:12,640 Speaker 1: we still have a lot more work to do. Facebook 107 00:06:12,640 --> 00:06:14,560 Speaker 1: has also changed its name to meta made this big 108 00:06:14,560 --> 00:06:17,600 Speaker 1: pivot to the metaverse. What are your biggest concerns about 109 00:06:17,680 --> 00:06:21,080 Speaker 1: the new meta today. The way they got here with 110 00:06:21,120 --> 00:06:23,800 Speaker 1: Facebook was because of a set of incentives and and 111 00:06:23,839 --> 00:06:27,159 Speaker 1: a lack of oversight. Those incentives have not meaningfully changed. 112 00:06:27,400 --> 00:06:29,919 Speaker 1: Facebook is still a private company. It's still driven to 113 00:06:29,920 --> 00:06:33,160 Speaker 1: have to increase usage, increased profits quarter after quarter. We 114 00:06:33,520 --> 00:06:35,880 Speaker 1: Facebook set its initial launch of the metaverse, we're going 115 00:06:35,920 --> 00:06:37,800 Speaker 1: to do safety by a design up front. But from 116 00:06:37,800 --> 00:06:40,600 Speaker 1: what we're seeing over the last you know, last year, 117 00:06:41,240 --> 00:06:43,520 Speaker 1: um is that they're repeating the same problems that they 118 00:06:43,560 --> 00:06:46,600 Speaker 1: had with Facebook that the first time they let journalists 119 00:06:46,640 --> 00:06:50,559 Speaker 1: into the metaverse, immediately women started gang grouped. Why didn't 120 00:06:50,560 --> 00:06:53,120 Speaker 1: they talk to some women beforehand on like what might 121 00:06:53,200 --> 00:06:55,120 Speaker 1: be dangerous that that that they could face in a 122 00:06:55,600 --> 00:06:59,120 Speaker 1: space like this, So we need to see meta actively 123 00:06:59,160 --> 00:07:02,760 Speaker 1: engaging with the pulp engagement experts and saying, let's design 124 00:07:02,800 --> 00:07:05,480 Speaker 1: for safety from the certain So they just said today 125 00:07:05,520 --> 00:07:09,000 Speaker 1: they're going to ask users for more direct feedback on 126 00:07:09,240 --> 00:07:12,360 Speaker 1: what they'd like to see in their feed their algorithm 127 00:07:12,480 --> 00:07:15,800 Speaker 1: is that a good? Is that a positive step? In 128 00:07:15,840 --> 00:07:18,560 Speaker 1: your view that it might have been? And there's a 129 00:07:18,560 --> 00:07:20,480 Speaker 1: lot of ways to do this that would have huge 130 00:07:20,480 --> 00:07:24,440 Speaker 1: opportunities for change. Many people know of kids who struggle 131 00:07:24,480 --> 00:07:27,880 Speaker 1: with mental health issues, eating disorders. Um. Part of what 132 00:07:28,000 --> 00:07:31,119 Speaker 1: happens is Facebook's algorithms have a tendency to push people 133 00:07:31,120 --> 00:07:33,720 Speaker 1: towards more extreme content. You know, you might start something 134 00:07:33,760 --> 00:07:36,240 Speaker 1: like healthy eating and get pushed to pro interacts the content. 135 00:07:36,880 --> 00:07:40,000 Speaker 1: Imagine a world where kid who's trying to fight against 136 00:07:40,040 --> 00:07:42,440 Speaker 1: these things, who knows this is a negative venture uh 137 00:07:42,800 --> 00:07:45,560 Speaker 1: influence on them. Imagine if Facebook actually said, hey, we 138 00:07:45,680 --> 00:07:47,920 Speaker 1: noticed you're looking at a lot of content that other 139 00:07:48,040 --> 00:07:50,880 Speaker 1: users have said makes them feel blue. Do you want 140 00:07:50,880 --> 00:07:53,480 Speaker 1: to keep looking at it? Imagine if we have that 141 00:07:53,520 --> 00:07:56,440 Speaker 1: ability to influence our feeds, probably a lot of kids 142 00:07:56,480 --> 00:07:59,080 Speaker 1: would be a lot healthier today. Interestingly, he told Joe 143 00:07:59,160 --> 00:08:02,200 Speaker 1: Rogan this story about how he rejected the idea of 144 00:08:02,240 --> 00:08:04,560 Speaker 1: an angry emoji and then said he wasn't here to 145 00:08:04,600 --> 00:08:07,800 Speaker 1: design a service that makes people more angry. Do you 146 00:08:07,840 --> 00:08:12,000 Speaker 1: think that's a little bit of rebusionist and history. It's interesting. 147 00:08:12,120 --> 00:08:16,000 Speaker 1: So when you look at the documents around emojis, the 148 00:08:16,040 --> 00:08:19,840 Speaker 1: reason why they added them was they wanted people to um. 149 00:08:19,920 --> 00:08:23,360 Speaker 1: People felt bad putting like a thumbs up on something 150 00:08:23,400 --> 00:08:25,160 Speaker 1: that made them really angry. They don't want to be 151 00:08:25,160 --> 00:08:28,720 Speaker 1: sewn is endorsing that idea. It's one of these things 152 00:08:28,720 --> 00:08:33,240 Speaker 1: where Facebook didn't think about the uninterested, unanticipated consequences of 153 00:08:33,280 --> 00:08:35,880 Speaker 1: some of these design decisions. When you make an avenue 154 00:08:36,040 --> 00:08:38,920 Speaker 1: where you could do it actively solicit more anger, you're 155 00:08:39,000 --> 00:08:41,880 Speaker 1: going to get more angry content. So I haven't seen 156 00:08:41,880 --> 00:08:44,280 Speaker 1: anything that documents saying that Mark said say no to 157 00:08:44,320 --> 00:08:47,679 Speaker 1: the angry face um and, but I can imagine that 158 00:08:47,720 --> 00:08:50,480 Speaker 1: he wishes as he had. Now now you testify that 159 00:08:50,800 --> 00:08:54,480 Speaker 1: only Mark Zuckerberg was holding Mark Zuckerberg accountable. And I'm 160 00:08:54,480 --> 00:08:58,520 Speaker 1: curious what you think of Cyril Sandberg's departure after fourteen years. 161 00:08:58,559 --> 00:09:02,040 Speaker 1: Do you think her leaving will change the internal culture? 162 00:09:02,679 --> 00:09:05,360 Speaker 1: And if so, so, I have a so so the 163 00:09:05,360 --> 00:09:07,480 Speaker 1: fact that Mark remains, I think is a much more 164 00:09:07,520 --> 00:09:11,199 Speaker 1: significant issue than Cheryl leaving. You know, Marcus surrounded himself 165 00:09:11,200 --> 00:09:13,600 Speaker 1: with people who tell him the same kinds of stories 166 00:09:13,640 --> 00:09:16,079 Speaker 1: over and over again. You know, Facebook is just a mirror. 167 00:09:16,160 --> 00:09:19,160 Speaker 1: It doesn't have responsibility. All these things that we're complaining 168 00:09:19,200 --> 00:09:21,560 Speaker 1: about have always been present. We're just showing them to 169 00:09:21,559 --> 00:09:23,280 Speaker 1: people who don't. We don't play any role in this. 170 00:09:23,440 --> 00:09:25,839 Speaker 1: We have no power. And Cheryl was a voice inside 171 00:09:25,840 --> 00:09:27,920 Speaker 1: the company who said, Hey, we have to get in 172 00:09:27,960 --> 00:09:30,839 Speaker 1: front of issues. We can't just be reactive. We can't 173 00:09:30,840 --> 00:09:33,760 Speaker 1: wait for another story to leak. You can't wait for 174 00:09:33,920 --> 00:09:36,320 Speaker 1: you know, another UN report saying we caused an ethnic 175 00:09:36,440 --> 00:09:40,199 Speaker 1: violence incident, um, like what happened with men more um. 176 00:09:40,240 --> 00:09:42,959 Speaker 1: I worry that because we don't have Cheryl's voice inside 177 00:09:42,960 --> 00:09:45,800 Speaker 1: of the company, that the number of senior leaders who 178 00:09:45,880 --> 00:09:48,360 Speaker 1: raised these issues has has gone down in a meaningful way. 179 00:09:49,360 --> 00:09:51,880 Speaker 1: Elections are coming up. What are you watching? What's your 180 00:09:51,920 --> 00:09:56,080 Speaker 1: take on how Meta is handling uh this new election 181 00:09:56,640 --> 00:10:00,640 Speaker 1: so far? I'm deeply concerned about the upcoming election. UH. 182 00:10:00,679 --> 00:10:03,400 Speaker 1: Other news sources, I believe in air Times have reported 183 00:10:03,400 --> 00:10:06,080 Speaker 1: on how Facebook shrunk their election team from around three 184 00:10:06,120 --> 00:10:09,559 Speaker 1: hundred people to sixty people UH later earlier this year. 185 00:10:10,120 --> 00:10:13,240 Speaker 1: That's a huge deal. When I was at Facebook, I 186 00:10:13,400 --> 00:10:16,240 Speaker 1: watched I worked in threat intelligence for the last eight 187 00:10:16,240 --> 00:10:18,400 Speaker 1: months I was in the company, and I watched some 188 00:10:18,520 --> 00:10:21,760 Speaker 1: catch over and over again, things like Russian influence operations. 189 00:10:22,160 --> 00:10:25,440 Speaker 1: There are a number of foreign nations, Russia, China ran 190 00:10:26,240 --> 00:10:29,640 Speaker 1: even smaller countries than know that as an open society, 191 00:10:30,280 --> 00:10:36,040 Speaker 1: as these unregulated, underinvested in platforms show like there's ways 192 00:10:36,080 --> 00:10:37,880 Speaker 1: that they can go in there and manipulate our elections. 193 00:10:38,160 --> 00:10:40,480 Speaker 1: And before Facebook was really trying, they were giving. They 194 00:10:40,480 --> 00:10:42,600 Speaker 1: were giving, perhaps not the best they could do, but 195 00:10:42,600 --> 00:10:46,839 Speaker 1: they were truly really trying to blunt those edges. And 196 00:10:46,920 --> 00:10:48,960 Speaker 1: I can't imagine that they can do an effective job 197 00:10:49,040 --> 00:10:52,560 Speaker 1: with fewer people protecting our elections. I know you've been 198 00:10:52,559 --> 00:10:56,720 Speaker 1: talking to lawmakers. We've got the American Innovation and Choice 199 00:10:56,720 --> 00:11:00,360 Speaker 1: Online at from UH Senators Club Buchar and Grass. We've 200 00:11:00,400 --> 00:11:03,160 Speaker 1: got Lena Cohn being more aggressive at the FTC. You 201 00:11:03,240 --> 00:11:06,800 Speaker 1: have the Supreme Court looking at Section two thirty. What 202 00:11:06,960 --> 00:11:10,000 Speaker 1: is one way the law could change to have the 203 00:11:10,040 --> 00:11:15,520 Speaker 1: most dramatic, potentially positive impact on big tech? In your view, 204 00:11:16,440 --> 00:11:19,680 Speaker 1: I am a strong advocate for the platform account of 205 00:11:19,679 --> 00:11:25,120 Speaker 1: the Platform Accountability and Transparency act UM because right now 206 00:11:25,320 --> 00:11:28,520 Speaker 1: we can't see behind the curtain of social media. We 207 00:11:28,520 --> 00:11:31,240 Speaker 1: were able to push for safety features and cars or 208 00:11:31,320 --> 00:11:34,240 Speaker 1: found in the partner of transportation, you know, reducing the 209 00:11:34,240 --> 00:11:38,079 Speaker 1: fatality from automobile automobile accents by effectively three and a 210 00:11:38,120 --> 00:11:41,520 Speaker 1: half times, because we could actually control cars, you know, 211 00:11:41,559 --> 00:11:43,640 Speaker 1: we could crash test them, we could take them apart, 212 00:11:44,000 --> 00:11:46,080 Speaker 1: we could understand how they were built and what what 213 00:11:46,200 --> 00:11:48,760 Speaker 1: shortcuts have been made. Right now, we can't do any 214 00:11:48,800 --> 00:11:51,040 Speaker 1: of those things for social media. We can't crash test it, 215 00:11:51,160 --> 00:11:53,360 Speaker 1: we can't confirm how it could be safer, so we 216 00:11:53,400 --> 00:11:56,080 Speaker 1: don't know what to demand. So I hope they passed 217 00:11:56,120 --> 00:12:00,120 Speaker 1: pat in addition to an equabahar. All right, we're to 218 00:12:00,120 --> 00:12:03,040 Speaker 1: continue this conversation after a quick break. Former Facebook employee 219 00:12:03,040 --> 00:12:05,480 Speaker 1: Turn whistle blower Francis Howgan to stay with us. I 220 00:12:05,520 --> 00:12:08,280 Speaker 1: want to hear so much more, and especially I want 221 00:12:08,280 --> 00:12:11,280 Speaker 1: to hear your thoughts on Elon Must potentially taking over Twitter. 222 00:12:11,280 --> 00:12:13,679 Speaker 1: Will be right back in a moment. This is Bloomberg 223 00:12:26,160 --> 00:12:29,760 Speaker 1: continuing our conversation now with former Facebook employee Turn whistleblower 224 00:12:29,840 --> 00:12:32,520 Speaker 1: Francis Howgan Francis, I want to get your thoughts on, 225 00:12:32,559 --> 00:12:34,680 Speaker 1: of course, the biggest news rocking social media that is 226 00:12:34,720 --> 00:12:38,560 Speaker 1: Elon Musk saying he'll take over Twitter. After all, what 227 00:12:38,640 --> 00:12:41,560 Speaker 1: are the risks in your view of the world's richest 228 00:12:41,600 --> 00:12:46,160 Speaker 1: man owning such an influential communications platform. The fact that 229 00:12:46,200 --> 00:12:49,200 Speaker 1: Elon Musk can make a decision to buy one of 230 00:12:49,640 --> 00:12:52,920 Speaker 1: our public spaces, um and be able to unilaterally make 231 00:12:52,960 --> 00:12:56,199 Speaker 1: that decision really shows us how vulnerable we are right 232 00:12:56,200 --> 00:13:00,880 Speaker 1: now and listing critical pieces of civic infrastructure to private 233 00:13:00,920 --> 00:13:04,520 Speaker 1: corporations now they're not even though they functionally work as 234 00:13:04,679 --> 00:13:07,560 Speaker 1: large parts of our information ecosystem, we have no ability 235 00:13:07,559 --> 00:13:10,000 Speaker 1: to influence them. They can be bought and sold by 236 00:13:10,160 --> 00:13:12,240 Speaker 1: anyone who has the money. Um So, I think they're 237 00:13:12,280 --> 00:13:15,480 Speaker 1: a great illustration of how we've really put a lot 238 00:13:15,559 --> 00:13:20,280 Speaker 1: of trust and a lot of um responsibility into the 239 00:13:20,320 --> 00:13:23,080 Speaker 1: hands of a private company. He could own Twitter in 240 00:13:23,080 --> 00:13:26,920 Speaker 1: a matter of days. Right before its from election. He 241 00:13:27,040 --> 00:13:31,280 Speaker 1: has said he wants to reinstate former President Trump. What 242 00:13:31,360 --> 00:13:35,680 Speaker 1: are the biggest concerns about that and and his approach 243 00:13:35,760 --> 00:13:40,000 Speaker 1: to quote unquote free speech in general. M hm so, 244 00:13:40,040 --> 00:13:42,680 Speaker 1: I think it was some big opportunities with regard to 245 00:13:42,720 --> 00:13:45,240 Speaker 1: how Elon Musk is approaching safety. So the fact that 246 00:13:45,240 --> 00:13:47,720 Speaker 1: he came out across like straight off the bat and 247 00:13:47,760 --> 00:13:50,600 Speaker 1: said we need to be worried about bots means he's 248 00:13:50,600 --> 00:13:52,720 Speaker 1: talking to someone who's at least talking to some people 249 00:13:52,720 --> 00:13:54,920 Speaker 1: who know what they're talking about. Because the number one 250 00:13:54,920 --> 00:13:58,160 Speaker 1: threat to our elections are bots. You know, there are 251 00:13:58,240 --> 00:14:01,679 Speaker 1: large influence operations that act as amplifiers for them for 252 00:14:01,920 --> 00:14:04,800 Speaker 1: whoever owns those networks, and often in the case that's 253 00:14:04,840 --> 00:14:10,440 Speaker 1: foreign foreign organizations like Russia, China, um Iran. The fact 254 00:14:10,440 --> 00:14:13,040 Speaker 1: that he's stepping in before the election is a big opportunity. 255 00:14:13,360 --> 00:14:15,880 Speaker 1: At the same time, I hope he takes time to 256 00:14:15,960 --> 00:14:19,040 Speaker 1: listen to the security and trust, trust and safety professionals 257 00:14:19,040 --> 00:14:22,120 Speaker 1: inside of Twitter, because every single social networks different and 258 00:14:22,160 --> 00:14:24,560 Speaker 1: they all have their own quirks and their own struggles, 259 00:14:24,840 --> 00:14:26,560 Speaker 1: and so I hope he takes the time to really 260 00:14:26,720 --> 00:14:29,600 Speaker 1: understand what those teems have done over time so that 261 00:14:29,640 --> 00:14:32,520 Speaker 1: we don't disrupt things before the election. Now, according to 262 00:14:32,560 --> 00:14:35,160 Speaker 1: the SEC, UH and the Information also did a big 263 00:14:35,200 --> 00:14:37,640 Speaker 1: piece on this, and you there's been a huge spike 264 00:14:38,080 --> 00:14:40,880 Speaker 1: in the number of whistleblowers that have come forward since 265 00:14:40,920 --> 00:14:43,600 Speaker 1: you came forward. One of them is Peter Zachco, a 266 00:14:43,640 --> 00:14:48,720 Speaker 1: former Twitter employee who talked about the egregious um egregious 267 00:14:48,720 --> 00:14:51,760 Speaker 1: flaws in Twitter's own security. What do you make of 268 00:14:51,920 --> 00:14:55,840 Speaker 1: the rise in these whistleblowers and the role that they 269 00:14:55,880 --> 00:15:00,000 Speaker 1: can play in providing transparency where Congress has failed to regulate. 270 00:15:00,320 --> 00:15:03,560 Speaker 1: There's if if if viewers take away only one thing 271 00:15:03,600 --> 00:15:06,400 Speaker 1: today from the time that we spent together, it's the 272 00:15:06,440 --> 00:15:09,080 Speaker 1: idea that more and more of our economy is driven 273 00:15:09,160 --> 00:15:12,080 Speaker 1: by opaque systems now. So you know, back when we 274 00:15:12,840 --> 00:15:16,200 Speaker 1: had a more industrial oriented economy, you know, you could 275 00:15:16,200 --> 00:15:19,200 Speaker 1: buy the products of those factories, you can interview workers 276 00:15:19,200 --> 00:15:21,680 Speaker 1: who worked in those factors and understand what was happening. 277 00:15:22,160 --> 00:15:24,960 Speaker 1: But now we have more and more systems where the 278 00:15:25,000 --> 00:15:28,080 Speaker 1: important details all live on data centers. You know, all 279 00:15:28,120 --> 00:15:30,560 Speaker 1: we get to see is our own strings were limited 280 00:15:30,680 --> 00:15:33,440 Speaker 1: in understanding how these systems work, or like, what choices 281 00:15:33,440 --> 00:15:37,480 Speaker 1: were made? What are the consequences. Whistleblowers are only going 282 00:15:37,520 --> 00:15:41,360 Speaker 1: to become more and more important because in the case 283 00:15:41,400 --> 00:15:44,040 Speaker 1: of things like trust and safety online, you know, there 284 00:15:44,040 --> 00:15:47,080 Speaker 1: are no academic classes you've been taken this today. You know, 285 00:15:47,080 --> 00:15:49,840 Speaker 1: there's like a feel on content moderation of places like Stamford, 286 00:15:49,920 --> 00:15:53,840 Speaker 1: but that's that's about it. We're reliant on professionals like 287 00:15:54,000 --> 00:15:57,920 Speaker 1: like Peter Um to understand what the limitations are in 288 00:15:57,960 --> 00:16:00,520 Speaker 1: these things. There are first lineup to us, and we 289 00:16:00,600 --> 00:16:03,080 Speaker 1: need to be protecting them. What do you think of TikTok? 290 00:16:03,200 --> 00:16:06,640 Speaker 1: Is there a unique threat posed by TikTok? In particular? 291 00:16:07,320 --> 00:16:11,920 Speaker 1: I'm particularly concerned about TikTok because TikTok is intentionally designed 292 00:16:11,960 --> 00:16:15,080 Speaker 1: to be manipulated. You know, it's a system that originally 293 00:16:15,120 --> 00:16:18,120 Speaker 1: originated in China. Um with the end. It's a system 294 00:16:18,160 --> 00:16:21,480 Speaker 1: that's it's architected from the beginning with controlling what messages 295 00:16:21,520 --> 00:16:26,520 Speaker 1: are distributed. There are it's they're famous um um. When 296 00:16:26,560 --> 00:16:28,200 Speaker 1: you get there are control rooms you can go into. 297 00:16:28,320 --> 00:16:31,080 Speaker 1: We can see the most important, most popular content TikTok. 298 00:16:31,160 --> 00:16:32,960 Speaker 1: And there have been scandals where things like if you're 299 00:16:33,040 --> 00:16:36,200 Speaker 1: visibly gay or visibly disabled, your video has got taken down. 300 00:16:36,760 --> 00:16:40,200 Speaker 1: We should be deeply concerned that, uh, this is a 301 00:16:40,280 --> 00:16:43,320 Speaker 1: Chinese company. You know, let's say China invaded Taiwan. I 302 00:16:43,400 --> 00:16:46,280 Speaker 1: guarantee you we would not see any pro Thailanese messages 303 00:16:46,320 --> 00:16:50,400 Speaker 1: going across TikTok, and because it's designed to be incredibly sticky, 304 00:16:50,440 --> 00:16:53,720 Speaker 1: being incredibly addictive, Like you can't passively watch TikTok, like 305 00:16:53,720 --> 00:16:55,640 Speaker 1: it polls you and you have to engage in order 306 00:16:55,640 --> 00:16:57,040 Speaker 1: to get the next video. There's like a little hit 307 00:16:57,080 --> 00:16:59,520 Speaker 1: of dopamine over and over again. You know, it draws 308 00:16:59,240 --> 00:17:03,240 Speaker 1: his kids, And so I strongly encourage us to look 309 00:17:03,240 --> 00:17:05,480 Speaker 1: at do we want to have China having so much 310 00:17:05,520 --> 00:17:09,720 Speaker 1: influence over our information environment, particularly for our children. Now, 311 00:17:09,840 --> 00:17:13,840 Speaker 1: I know you've been on a year of public speaking engagements, 312 00:17:13,880 --> 00:17:17,800 Speaker 1: testifying before other governments. You also moved to Puerto Rico. 313 00:17:18,320 --> 00:17:20,840 Speaker 1: You got married, I moved. I moved two years ago. 314 00:17:20,840 --> 00:17:24,760 Speaker 1: In profit booked two years ago, Yeah, two years ago. Okay, 315 00:17:25,119 --> 00:17:28,359 Speaker 1: so you were in Puerto Rico. Um, you launched this 316 00:17:28,400 --> 00:17:31,840 Speaker 1: new nonprofit Beyond the Screen. Talk to us a little 317 00:17:31,840 --> 00:17:34,600 Speaker 1: bit about how how has your life changed since becoming 318 00:17:34,600 --> 00:17:39,920 Speaker 1: a whistleblower quote unquote, and do you have any regrets? Interesting? 319 00:17:40,200 --> 00:17:42,040 Speaker 1: I think the biggest way in which my life has 320 00:17:42,119 --> 00:17:44,400 Speaker 1: changed is you know, I can I can sleep at night, 321 00:17:44,960 --> 00:17:47,760 Speaker 1: you know, like before I came out. Um, I think 322 00:17:47,800 --> 00:17:50,320 Speaker 1: anyone who's ever had hold of secret where you thought 323 00:17:51,200 --> 00:17:54,200 Speaker 1: other people's lives were on the line. Knows how hard 324 00:17:54,280 --> 00:17:58,240 Speaker 1: that is. And you know I had I had to 325 00:17:58,240 --> 00:18:00,480 Speaker 1: get a new passport right about the time I left Facebook, 326 00:18:01,200 --> 00:18:03,280 Speaker 1: and I had to get a new driver's license this 327 00:18:03,320 --> 00:18:05,520 Speaker 1: year because I had lost my driver's license. And I 328 00:18:05,520 --> 00:18:07,440 Speaker 1: looked at those two photos and I was like, oh, 329 00:18:07,480 --> 00:18:10,680 Speaker 1: my goodness, I aged backwards ten years. Like that's not 330 00:18:10,680 --> 00:18:14,560 Speaker 1: how it's supposed to work. UM. And so I have 331 00:18:14,640 --> 00:18:17,560 Speaker 1: been so grateful for the experience over the last year 332 00:18:17,600 --> 00:18:22,120 Speaker 1: because I know how few public figures that are women. UM, 333 00:18:22,440 --> 00:18:26,960 Speaker 1: I have easy life online and like I have opened 334 00:18:27,040 --> 00:18:30,000 Speaker 1: d ms on Twitter, Instagram and no one harasses me. 335 00:18:30,320 --> 00:18:33,400 Speaker 1: You know, I've I've I've only felt supported and I'm 336 00:18:33,440 --> 00:18:36,480 Speaker 1: I'm so grateful UM to be able to give people 337 00:18:36,480 --> 00:18:39,119 Speaker 1: hope about the idea that we can change social media. 338 00:18:39,520 --> 00:18:41,159 Speaker 1: You know, we were going to figure out how to 339 00:18:41,160 --> 00:18:43,120 Speaker 1: do this and we can do it together, all right. Well, 340 00:18:43,160 --> 00:18:47,360 Speaker 1: thank you so much for obviously sharing your story with us. 341 00:18:47,760 --> 00:18:51,119 Speaker 1: Everybody check out Beyond the Screen, Francis Halgan's new nonprofit, 342 00:18:51,600 --> 00:18:54,760 Speaker 1: UM Francis, thank you for taking the time. We appreciate it. 343 00:19:03,560 --> 00:19:06,119 Speaker 1: Welcome back to Bow technology and Emily changing San Francisco 344 00:19:06,520 --> 00:19:10,200 Speaker 1: Elon Musk wants to turn Twitter into the everything app. 345 00:19:10,240 --> 00:19:14,520 Speaker 1: Here to explain what that might mean, are Ed Ludlow So, Ed, 346 00:19:14,560 --> 00:19:16,440 Speaker 1: what kind of clues do we have about what he's 347 00:19:16,440 --> 00:19:18,720 Speaker 1: really talking about here? Yeah, you know we have clues 348 00:19:18,760 --> 00:19:20,760 Speaker 1: and shameless plug I kind of put a piece out 349 00:19:20,800 --> 00:19:23,280 Speaker 1: on Twitter this morning about some of the things Muskas 350 00:19:23,280 --> 00:19:25,840 Speaker 1: talked about changing. We're certainly at a stage where there's 351 00:19:25,840 --> 00:19:27,920 Speaker 1: more questions and answers, right. You see that reflected in 352 00:19:28,000 --> 00:19:31,240 Speaker 1: equity markets. You know, Twitter is down after a ginormous 353 00:19:31,280 --> 00:19:34,680 Speaker 1: game twenty four hours ago. Tesla down on concern Musk 354 00:19:34,680 --> 00:19:36,800 Speaker 1: will have to sell down Tesla stock to fund this 355 00:19:36,880 --> 00:19:40,040 Speaker 1: deal that he's distracted. But this is this idea of 356 00:19:40,400 --> 00:19:43,280 Speaker 1: X the everything app. And you know what Muscar has 357 00:19:43,320 --> 00:19:46,359 Speaker 1: talked about in the past on stage and tweets is 358 00:19:46,440 --> 00:19:49,440 Speaker 1: growing Twitter from a user base of around two dred 359 00:19:49,520 --> 00:19:52,080 Speaker 1: forty million currently to one billion, And I think a 360 00:19:52,080 --> 00:19:54,320 Speaker 1: lot of the street are looking for signs of what 361 00:19:54,400 --> 00:19:56,240 Speaker 1: that means. If we bring up this chart and look 362 00:19:56,280 --> 00:20:00,600 Speaker 1: at sort of Twitter's revenue growth relative to Tesla, Twitter's 363 00:20:00,640 --> 00:20:03,040 Speaker 1: growth has been underwhelming, right, and there is hope that 364 00:20:03,160 --> 00:20:06,720 Speaker 1: Musk can inject some new ideas for Twitter itself. That's 365 00:20:06,760 --> 00:20:10,240 Speaker 1: about opening up the algorithm, open sourcing it about dealing 366 00:20:10,240 --> 00:20:13,200 Speaker 1: with the box issues, having a time limited edit button. 367 00:20:13,440 --> 00:20:15,879 Speaker 1: But he's also talked about this idea that Twitter can 368 00:20:15,920 --> 00:20:19,040 Speaker 1: be a one stop shop for other things, more video functionality, 369 00:20:19,520 --> 00:20:22,840 Speaker 1: making it more akin, perhaps too a we Chat in Asia. 370 00:20:22,880 --> 00:20:25,879 Speaker 1: You know, there's many more users in China alone using 371 00:20:25,920 --> 00:20:29,000 Speaker 1: we Chat and various functionality on it than are using 372 00:20:29,040 --> 00:20:31,840 Speaker 1: Twitter globally. So I think there's a lot of optimism 373 00:20:32,080 --> 00:20:33,720 Speaker 1: they can do that. But I go back to the 374 00:20:33,760 --> 00:20:37,040 Speaker 1: discussion we discovered between Dorsey and Musk in those court 375 00:20:37,119 --> 00:20:40,080 Speaker 1: filings and the text that were released as part of discovery. 376 00:20:40,640 --> 00:20:42,720 Speaker 1: They want to enact changes and they felt that the 377 00:20:42,760 --> 00:20:45,960 Speaker 1: only way to do that was to take the company private. 378 00:20:46,119 --> 00:20:48,720 Speaker 1: There's optimism on the street that will happen, and there's 379 00:20:48,720 --> 00:20:51,400 Speaker 1: also optimism from the cell side that Musk will unlock 380 00:20:51,520 --> 00:20:54,560 Speaker 1: the new functionality that will help Twitter's user based grow 381 00:20:54,760 --> 00:20:56,639 Speaker 1: but also help its top line growth as well. The 382 00:20:56,840 --> 00:21:00,399 Speaker 1: kind of wild card. Musk isn't interested in ad based model. 383 00:21:00,600 --> 00:21:02,080 Speaker 1: He wants to kind of move away from that and 384 00:21:02,119 --> 00:21:04,960 Speaker 1: monetizes in other ways. So it's gonna be really interesting. 385 00:21:05,000 --> 00:21:07,440 Speaker 1: But again, let's take a reality check. M I think 386 00:21:07,480 --> 00:21:09,800 Speaker 1: we're a long way away from knowing what's going on. 387 00:21:10,119 --> 00:21:12,879 Speaker 1: Am I going to Delaware? Are you going to Delaware? 388 00:21:13,200 --> 00:21:16,600 Speaker 1: Nobody knows, We do not know, And boy, what I 389 00:21:16,640 --> 00:21:17,800 Speaker 1: love to know if you and I are going to 390 00:21:17,840 --> 00:21:20,840 Speaker 1: be in Delaware in two weeks? Okay, thank you? And 391 00:21:21,119 --> 00:21:22,879 Speaker 1: I want to dig into this a little further with 392 00:21:23,080 --> 00:21:26,920 Speaker 1: Lead Edge Capital founding partner Mitchell Green. Mitch, you know, 393 00:21:27,160 --> 00:21:30,480 Speaker 1: I know you're an investor in Uber, which has aspired 394 00:21:30,560 --> 00:21:33,080 Speaker 1: to this sort of super app idea. We've seen ten 395 00:21:33,160 --> 00:21:35,679 Speaker 1: Cent really succeed at it. What do you make of 396 00:21:35,760 --> 00:21:38,800 Speaker 1: Elon Musk's idea to try to turn Twitter into an 397 00:21:38,920 --> 00:21:44,679 Speaker 1: everything app? Look, Um, it's hard. There hasn't look we're 398 00:21:44,720 --> 00:21:47,280 Speaker 1: not We don't only lub anymore. But we do own 399 00:21:47,359 --> 00:21:52,560 Speaker 1: byte Dance, which obviously on the very popular TikTok app um. 400 00:21:52,680 --> 00:21:55,920 Speaker 1: We do all. We were early investors in Ali Baba Group, 401 00:21:56,400 --> 00:21:59,320 Speaker 1: which is obviously uh and then as well as Aunt Financial, 402 00:21:59,320 --> 00:22:02,480 Speaker 1: which is building super ap Um. I think he's got 403 00:22:02,520 --> 00:22:04,520 Speaker 1: his work caught out to him, but we're sure going 404 00:22:04,560 --> 00:22:07,040 Speaker 1: to talk about it. And then three to five years, 405 00:22:07,080 --> 00:22:10,000 Speaker 1: we're gonna know, Um, you know, did it work? Look Ellen? 406 00:22:10,160 --> 00:22:12,919 Speaker 1: Is that I totally agree that he can't accomplish this. 407 00:22:13,040 --> 00:22:14,439 Speaker 1: What he wants to try to do is in a 408 00:22:14,520 --> 00:22:18,359 Speaker 1: public company. Um, surely, I'm sure it's not. Having not 409 00:22:18,520 --> 00:22:20,240 Speaker 1: spent a ton of time looking at Twitter, I'm sure 410 00:22:20,240 --> 00:22:22,520 Speaker 1: it's not the most efficiently running business. I'm sure there's 411 00:22:22,520 --> 00:22:24,720 Speaker 1: tons of ways he can fix it. It will take 412 00:22:24,760 --> 00:22:28,000 Speaker 1: a lot of time. He's amazing at sending rockets into 413 00:22:28,000 --> 00:22:31,639 Speaker 1: space and he proved the world wrong. Um, you know 414 00:22:31,720 --> 00:22:37,120 Speaker 1: with his car business. He obviously started his career in payments. Um, 415 00:22:38,040 --> 00:22:41,760 Speaker 1: time will tell if it. Uh, if he's successful and 416 00:22:41,840 --> 00:22:43,679 Speaker 1: turning around Twitter, I think he's It's it's it's a 417 00:22:43,800 --> 00:22:48,200 Speaker 1: very um tall order. Uh. And it's not like Facebook 418 00:22:48,240 --> 00:22:50,200 Speaker 1: and Bite Dance are gonna sit around and doing nothing 419 00:22:50,400 --> 00:22:52,119 Speaker 1: while the well, you know, while he tries to do it. 420 00:22:52,240 --> 00:22:55,119 Speaker 1: So from a bigger picture, you know, I find it 421 00:22:55,200 --> 00:22:58,600 Speaker 1: interesting that we could potentially see this massive deal, you know, 422 00:22:58,800 --> 00:23:01,959 Speaker 1: him buying Twitter for forty billion dollars happened in the 423 00:23:01,960 --> 00:23:06,480 Speaker 1: middle of you know, potentially you know, drop into a 424 00:23:06,560 --> 00:23:09,880 Speaker 1: recession where we also saw Adobe agree to by Figma 425 00:23:09,960 --> 00:23:13,200 Speaker 1: for twenty billion dollars and we're waiting for this big 426 00:23:13,240 --> 00:23:16,679 Speaker 1: Microsoft Activision deal. What do you think about how the 427 00:23:16,840 --> 00:23:20,560 Speaker 1: M and A landscape is keeping up pace despite the 428 00:23:20,600 --> 00:23:24,520 Speaker 1: fact that the economy is so bad. Well, it's a 429 00:23:24,560 --> 00:23:28,439 Speaker 1: great question UM corporates around the world to have You know, 430 00:23:29,000 --> 00:23:35,160 Speaker 1: these tech corporates Google, Microsoft, Facebook, Cammazon, keV, you know, Ali, Baba, 431 00:23:35,240 --> 00:23:41,560 Speaker 1: ten Cent have ginormous sums of cash UM by Oracle 432 00:23:41,600 --> 00:23:43,440 Speaker 1: you can add in their step. You get in there 433 00:23:44,080 --> 00:23:46,440 Speaker 1: at some point. I think we're gonna wake up over 434 00:23:46,480 --> 00:23:50,280 Speaker 1: the next twelve to fift eighteen months and there's gonna 435 00:23:50,280 --> 00:23:51,919 Speaker 1: be a heck of a lot more M and A 436 00:23:52,040 --> 00:23:54,359 Speaker 1: than we've seen in a long time. I don't know 437 00:23:54,359 --> 00:23:57,680 Speaker 1: when it's gonna happen. Maybe I don't think it's starting yet. 438 00:23:58,320 --> 00:24:00,199 Speaker 1: I also think you're gonna see a way of a 439 00:24:00,240 --> 00:24:04,280 Speaker 1: biout activity to UM the problem. I think where the 440 00:24:04,280 --> 00:24:07,320 Speaker 1: buyout by the by where the body WI Bio fund activity, 441 00:24:07,320 --> 00:24:10,080 Speaker 1: propequity fund activity right now is pretty slow, and you've 442 00:24:10,119 --> 00:24:15,320 Speaker 1: seen busted deals UM just because the credit markets are 443 00:24:15,480 --> 00:24:18,679 Speaker 1: not in good shape. UM just related you know, like 444 00:24:18,760 --> 00:24:22,359 Speaker 1: there's a huge back, there's a huge we're not credit 445 00:24:22,400 --> 00:24:25,800 Speaker 1: investors but there is a huge like log jam right 446 00:24:25,800 --> 00:24:28,359 Speaker 1: now with the citric steal within these banks are going 447 00:24:28,400 --> 00:24:32,040 Speaker 1: to take ginormous losses on them um and so like 448 00:24:32,080 --> 00:24:34,200 Speaker 1: the credit markets for a lot of this activity is 449 00:24:34,240 --> 00:24:36,800 Speaker 1: super slow. So I don't know how much leverage that 450 00:24:36,880 --> 00:24:39,480 Speaker 1: Twitter is going to take in this buyout and things 451 00:24:39,520 --> 00:24:42,280 Speaker 1: like that, but like anything that requires lots and I 452 00:24:42,280 --> 00:24:44,920 Speaker 1: think that's why you're seeing spreads lots of the potential 453 00:24:44,960 --> 00:24:47,479 Speaker 1: deals like trade pretty wide because the credit markets are 454 00:24:47,520 --> 00:24:51,359 Speaker 1: so uncertain right now now that it isn't impact strategic Okay, 455 00:24:51,480 --> 00:24:53,919 Speaker 1: let's talk in a little bit about venture and the 456 00:24:53,960 --> 00:24:57,080 Speaker 1: private markets. Venture firms seem to have a lot of 457 00:24:57,160 --> 00:25:00,600 Speaker 1: dry powder that is piling up and not a lot 458 00:25:00,600 --> 00:25:03,320 Speaker 1: of places to put it. Some folks have told us 459 00:25:03,320 --> 00:25:07,000 Speaker 1: they're waiting for evaluations to go down before they deploy anything. 460 00:25:07,119 --> 00:25:10,040 Speaker 1: Of course, there are a lot of companies UM struggling 461 00:25:10,080 --> 00:25:14,840 Speaker 1: and suddenly their balance sheets don't look so attractive to investors. 462 00:25:15,440 --> 00:25:19,400 Speaker 1: What are you seeing? How are you evolving your strategy? 463 00:25:19,760 --> 00:25:24,760 Speaker 1: As macro economic concerns remain good economy bad ecoun. I 464 00:25:24,800 --> 00:25:27,360 Speaker 1: think nobody knows where the economy is going. I read 465 00:25:27,400 --> 00:25:30,520 Speaker 1: an I S I survey that said, like investors think 466 00:25:30,560 --> 00:25:33,280 Speaker 1: that there's gonna be a recession in the crowd is 467 00:25:33,359 --> 00:25:35,679 Speaker 1: usually wrong. It's not like we're all sitting around in 468 00:25:35,760 --> 00:25:39,480 Speaker 1: February of three, you know, sorry, in February of twenty thinking, 469 00:25:39,560 --> 00:25:41,320 Speaker 1: you know, COVID was gonna happen a month later in 470 00:25:41,359 --> 00:25:43,719 Speaker 1: August of oh eight, like all the world's about ten 471 00:25:43,720 --> 00:25:47,000 Speaker 1: because lemon Butter is about to blow up? Who knows. 472 00:25:47,480 --> 00:25:49,480 Speaker 1: Like the crowd is usually wrong. By the way, I'm 473 00:25:49,520 --> 00:25:53,760 Speaker 1: probably myself in the crowd um in terms of like 474 00:25:53,920 --> 00:25:57,000 Speaker 1: the venture landscape where growth equity landscape right now, and 475 00:25:57,040 --> 00:25:59,440 Speaker 1: I think you could you can expand it to private 476 00:25:59,480 --> 00:26:04,240 Speaker 1: equity lands escape or real estate asset landscape, just specifically 477 00:26:04,240 --> 00:26:07,480 Speaker 1: in like the venture and like if you're thinking, like, hey, 478 00:26:07,760 --> 00:26:11,159 Speaker 1: companies with fifteen million revenue to a hundred million revenue 479 00:26:11,200 --> 00:26:14,800 Speaker 1: that are software and internet or fintech businesses, there's just 480 00:26:15,560 --> 00:26:19,359 Speaker 1: too big a spread between what the buyer wants and 481 00:26:19,400 --> 00:26:22,800 Speaker 1: what like a private aquor venture funds gonna pay because 482 00:26:22,800 --> 00:26:27,680 Speaker 1: it's driven by public markets and in companies right now 483 00:26:28,320 --> 00:26:30,600 Speaker 1: for the most part. And I think the spread is 484 00:26:30,720 --> 00:26:33,640 Speaker 1: already started to come down, Like it's definitely tightened up 485 00:26:33,800 --> 00:26:37,600 Speaker 1: from today where it was six months ago. You just 486 00:26:37,640 --> 00:26:40,199 Speaker 1: have to make the assumption that public private markets lead 487 00:26:40,240 --> 00:26:43,000 Speaker 1: public markets, are public markets lead private markets. And as 488 00:26:43,040 --> 00:26:45,760 Speaker 1: a result, like tons of companies raise money in the 489 00:26:45,800 --> 00:26:48,240 Speaker 1: back half of twenty one and early in twenty two, 490 00:26:48,800 --> 00:26:51,560 Speaker 1: and like there raised like two years of money, and 491 00:26:51,600 --> 00:26:54,639 Speaker 1: so like your company right now that raised still has 492 00:26:54,640 --> 00:26:57,040 Speaker 1: a hundred million plus in the balance sheet. Your last 493 00:26:57,119 --> 00:26:59,439 Speaker 1: route was probably done at too high a price. But like, 494 00:26:59,640 --> 00:27:02,879 Speaker 1: you don't have to raise money right now. Fast forward 495 00:27:02,920 --> 00:27:07,480 Speaker 1: a year, you might be intercession. At that point, you've 496 00:27:07,480 --> 00:27:10,159 Speaker 1: probably burned a bunch of money. We think it's going 497 00:27:10,240 --> 00:27:12,520 Speaker 1: to take another six to twelve months for a lot 498 00:27:12,560 --> 00:27:14,679 Speaker 1: of this stuff to work through, and that you know, 499 00:27:14,760 --> 00:27:17,600 Speaker 1: the back half of next year in the twenty four 500 00:27:17,600 --> 00:27:20,080 Speaker 1: will be super busy because then a bunch of these 501 00:27:20,080 --> 00:27:23,479 Speaker 1: companies are going to raise and those companies that hit 502 00:27:23,560 --> 00:27:27,600 Speaker 1: or beat their numbers might raise up grounds um, but 503 00:27:27,640 --> 00:27:30,919 Speaker 1: those companies that miss their numbers will probably be raising 504 00:27:31,080 --> 00:27:34,840 Speaker 1: death rounds. But again, who knows, maybe not maybe pull 505 00:27:34,880 --> 00:27:36,960 Speaker 1: the markets go back up, but if cops stay where 506 00:27:37,000 --> 00:27:39,240 Speaker 1: they are today, which is kind of near historical averages. 507 00:27:40,760 --> 00:27:43,520 Speaker 1: So what advice are you giving your portfolio companies right now. 508 00:27:44,359 --> 00:27:49,520 Speaker 1: Great question. Don't panic. Um is one thing. Run your 509 00:27:49,600 --> 00:27:54,320 Speaker 1: business like, you know, keep your best employees, keep your 510 00:27:54,320 --> 00:27:59,720 Speaker 1: best employees happy. Um. You know, layoffs are not always bad. 511 00:28:00,280 --> 00:28:02,160 Speaker 1: You know, some of the greatest companies on Earth over 512 00:28:02,240 --> 00:28:05,119 Speaker 1: year over time, and like laid off percent other people 513 00:28:05,119 --> 00:28:07,240 Speaker 1: every year, like g was like, well long for doing 514 00:28:07,280 --> 00:28:10,000 Speaker 1: it thirty years ago. Is trimming Like all these companies 515 00:28:10,040 --> 00:28:13,359 Speaker 1: are run with too much fat, every company on every 516 00:28:13,400 --> 00:28:16,000 Speaker 1: software company that's been funded with venture funding. So what 517 00:28:16,040 --> 00:28:19,680 Speaker 1: are we telling them? That's a great question. I think 518 00:28:19,720 --> 00:28:22,360 Speaker 1: we're telling them. Look, make sure you're you've got capital 519 00:28:22,760 --> 00:28:26,520 Speaker 1: for the next like eighteen months. Make sure unit your 520 00:28:26,600 --> 00:28:29,360 Speaker 1: unit economics work so like you know, you don't need 521 00:28:29,359 --> 00:28:31,720 Speaker 1: three or four year customer paybacks. You pay back and 522 00:28:31,760 --> 00:28:36,200 Speaker 1: you know eighteen months are under um. But make sure 523 00:28:36,240 --> 00:28:39,120 Speaker 1: you're invested in the future, like don't freak out like 524 00:28:39,200 --> 00:28:41,400 Speaker 1: the great We're gonna look back in five or ten 525 00:28:41,480 --> 00:28:43,640 Speaker 1: years from now and like great companies will have been 526 00:28:43,640 --> 00:28:46,640 Speaker 1: created during this time period and you need to be bold. 527 00:28:47,000 --> 00:28:48,720 Speaker 1: You just won't want to be smart about it. And 528 00:28:48,760 --> 00:28:50,840 Speaker 1: make sure you're not standing on the cliff, you know, 529 00:28:50,920 --> 00:28:54,680 Speaker 1: with your pants down. If the tag goes out. Okay, 530 00:28:54,920 --> 00:28:57,280 Speaker 1: don't panic, don't freak out, and don't stay on a 531 00:28:57,320 --> 00:29:00,880 Speaker 1: cliff with your pants down. Those are all tensible pieces 532 00:29:00,920 --> 00:29:04,360 Speaker 1: of advice. Mitch. All right, Mitch Green, thanks for giving 533 00:29:04,360 --> 00:29:08,720 Speaker 1: it to us straight as always. Appreciate your thoughts on 534 00:29:08,760 --> 00:29:12,600 Speaker 1: all of this, Thank you. Okay, Coming up, how the 535 00:29:12,640 --> 00:29:16,200 Speaker 1: blockchain could help everyday people invest in some of the 536 00:29:16,200 --> 00:29:20,600 Speaker 1: world's most popular private companies in the world. This is 537 00:29:20,640 --> 00:29:39,560 Speaker 1: Bloomberg time now for our crypto reporting. Today we're covering 538 00:29:39,560 --> 00:29:43,400 Speaker 1: the so called tokenization of funds, which could potentially expand 539 00:29:43,440 --> 00:29:46,560 Speaker 1: access to private markets to a broader set of investors. 540 00:29:46,600 --> 00:29:48,640 Speaker 1: For that, I want to bring in Bloomberg Shanali, Bossi, 541 00:29:48,720 --> 00:29:51,200 Speaker 1: Shanali take it away. Thank you, Emily. You know, whenever 542 00:29:51,240 --> 00:29:53,640 Speaker 1: I go around to investment conferences more and more, this 543 00:29:53,720 --> 00:29:58,479 Speaker 1: gentleman named Carlos Domingo, the CEO of Securities, is often 544 00:29:58,680 --> 00:30:01,240 Speaker 1: there and he is joining us now to talk about 545 00:30:01,320 --> 00:30:04,719 Speaker 1: this because recently today really they announced the deal with 546 00:30:04,760 --> 00:30:08,800 Speaker 1: Hamilton Lane, recently another deal with KKR. Carlos, when you're 547 00:30:08,840 --> 00:30:12,120 Speaker 1: talking to these large fund managers, Hamilton Lane alone has 548 00:30:12,480 --> 00:30:17,200 Speaker 1: more than eight hundred billion dollars under supervision. How quickly 549 00:30:17,240 --> 00:30:19,840 Speaker 1: are they starting to look at blockchain as a way 550 00:30:19,920 --> 00:30:23,520 Speaker 1: to expand their investor base and bring more people into 551 00:30:23,560 --> 00:30:28,160 Speaker 1: their funds. Any thanks for hiring me. I think it's 552 00:30:28,160 --> 00:30:30,680 Speaker 1: been a journey for these asset managers. We started talking 553 00:30:30,680 --> 00:30:33,160 Speaker 1: to them, you know, back into thousand eight into some 554 00:30:33,240 --> 00:30:36,160 Speaker 1: of them like they care, and you know, they've been 555 00:30:36,520 --> 00:30:39,680 Speaker 1: basically building out the internal capabilities and the knowledge. And 556 00:30:39,680 --> 00:30:41,560 Speaker 1: at the same time, the industry has evolved as well 557 00:30:41,600 --> 00:30:44,640 Speaker 1: in terms of, you know, making locking easier to use, 558 00:30:44,720 --> 00:30:46,760 Speaker 1: in terms of like you know, wal It's performance of 559 00:30:46,800 --> 00:30:49,920 Speaker 1: the underlying blockchains, et cetera. And also more importantly the 560 00:30:49,920 --> 00:30:52,800 Speaker 1: regulatory quality of what does it mean to actually recognize 561 00:30:52,800 --> 00:30:54,680 Speaker 1: a fund on the blockchain and the COO can manage 562 00:30:54,680 --> 00:30:57,640 Speaker 1: those securities and who has license to do that, et cetera. 563 00:30:57,720 --> 00:30:59,080 Speaker 1: So it's been kind of a journey. But I think 564 00:30:59,120 --> 00:31:01,280 Speaker 1: at this point in time, and I think that the 565 00:31:01,320 --> 00:31:04,480 Speaker 1: fact that Kker and Hamilton language are too massive privativity 566 00:31:04,520 --> 00:31:07,760 Speaker 1: firms have decided to do that, I think it signals 567 00:31:07,840 --> 00:31:10,360 Speaker 1: an inflection point in the industry where we're gonna start 568 00:31:10,360 --> 00:31:13,720 Speaker 1: seeing massive adoption going forward. So let's say KKR as 569 00:31:13,720 --> 00:31:17,000 Speaker 1: an example, because an everyday person can't really say, hey, 570 00:31:17,080 --> 00:31:20,040 Speaker 1: let me put ten thou dollars into a KKR fund. 571 00:31:20,280 --> 00:31:24,600 Speaker 1: But now they're making a private acquity fund available through tokenization. 572 00:31:24,840 --> 00:31:26,880 Speaker 1: What does that mean? How is it different from a 573 00:31:26,920 --> 00:31:31,400 Speaker 1: traditional private equity fund? Is there a key separation between 574 00:31:31,440 --> 00:31:33,160 Speaker 1: that and the normal fund that you would invest in 575 00:31:33,200 --> 00:31:37,480 Speaker 1: as a large institution. Well so as managers, as you said, 576 00:31:37,520 --> 00:31:40,000 Speaker 1: I think they've recognized that, you know, they've been extremely 577 00:31:40,000 --> 00:31:44,680 Speaker 1: successful building UM primarily going after institutional investors and drag 578 00:31:44,720 --> 00:31:47,720 Speaker 1: networks individuals, and that they are you know, there is 579 00:31:47,760 --> 00:31:51,600 Speaker 1: a new breath of investors that are individual investors. They 580 00:31:51,600 --> 00:31:55,480 Speaker 1: are much younger, they're digital, et cetera. That they don't 581 00:31:55,480 --> 00:31:58,000 Speaker 1: have access to those products at all because of the 582 00:31:58,000 --> 00:32:00,440 Speaker 1: structure of the products is the sign for institutions, etcetera. 583 00:32:00,560 --> 00:32:02,680 Speaker 1: So they all recognize that they have to figure out 584 00:32:02,680 --> 00:32:05,120 Speaker 1: how to reach out to them. And I think they see, 585 00:32:05,480 --> 00:32:08,920 Speaker 1: you know, blockin and organization as the most if you 586 00:32:08,960 --> 00:32:11,760 Speaker 1: want modern and advanced way of providing this, you know, 587 00:32:11,800 --> 00:32:14,400 Speaker 1: fractional ownership in a very efficient way, being able to 588 00:32:14,480 --> 00:32:17,880 Speaker 1: track the beneficial ownership of the of the securities provide 589 00:32:17,960 --> 00:32:21,600 Speaker 1: you know, our compliance as a servicing, etcetera. So they 590 00:32:21,680 --> 00:32:24,080 Speaker 1: all that conversation usually is very easy, and I think 591 00:32:24,080 --> 00:32:27,280 Speaker 1: what balls down later is about how do we do it, etcetera. 592 00:32:27,760 --> 00:32:30,800 Speaker 1: The fund itself is based similarities, slightly different in the 593 00:32:30,800 --> 00:32:34,080 Speaker 1: sense that this is a feeder that hasn't slightly different structure, 594 00:32:34,720 --> 00:32:38,120 Speaker 1: which we're trying to make it actually more individual investor friendly. 595 00:32:38,480 --> 00:32:42,240 Speaker 1: So but overall you should expect that the performance of 596 00:32:42,320 --> 00:32:45,360 Speaker 1: the organized version you know, very closely tracks the performance 597 00:32:45,360 --> 00:32:49,320 Speaker 1: of the original privadiquity that was only available for institutions. Now, 598 00:32:49,360 --> 00:32:51,760 Speaker 1: how much of this was even possible even five or 599 00:32:51,800 --> 00:32:54,080 Speaker 1: six or seven years ago. How much was this made 600 00:32:54,120 --> 00:32:58,040 Speaker 1: possible because SEC rules have made it more possible for 601 00:32:58,200 --> 00:33:02,880 Speaker 1: credited investors to invest in a wider array of funds. Well, 602 00:33:03,160 --> 00:33:06,880 Speaker 1: the assisty rules to allow for more accessibility to create 603 00:33:06,920 --> 00:33:10,640 Speaker 1: the investors haven't really changed significantly. They did some improvements, 604 00:33:10,880 --> 00:33:13,840 Speaker 1: uh two years ago in terms of who qualifies and 605 00:33:13,880 --> 00:33:16,320 Speaker 1: a created investor. I think what also has happened is 606 00:33:16,320 --> 00:33:18,560 Speaker 1: that more and more people are create investors, right because 607 00:33:18,600 --> 00:33:20,600 Speaker 1: you you know, the wealth is growing in the in 608 00:33:20,680 --> 00:33:24,640 Speaker 1: the United States and today is around thirteen point six 609 00:33:24,640 --> 00:33:28,040 Speaker 1: million people that qualify as the created investors. That's more 610 00:33:28,040 --> 00:33:31,160 Speaker 1: than ten percent of the households that collectively managed seventy 611 00:33:31,240 --> 00:33:33,960 Speaker 1: five tillion dollars. I think the issue was that the 612 00:33:34,080 --> 00:33:38,160 Speaker 1: products that those susset management companies had, they were not 613 00:33:38,200 --> 00:33:40,640 Speaker 1: accessible to these investors because they're not being served by 614 00:33:40,680 --> 00:33:43,920 Speaker 1: the current however wealth management or reach the investor advice. 615 00:33:44,080 --> 00:33:46,720 Speaker 1: So that's what it begs the question, when you're looking 616 00:33:46,760 --> 00:33:49,640 Speaker 1: at the opportunity to invest in a broader array of alternatives, 617 00:33:49,680 --> 00:33:53,520 Speaker 1: do you think that crypto blockchain technology in particular can 618 00:33:53,560 --> 00:33:56,920 Speaker 1: be used for more of these types of purposes, more 619 00:33:57,000 --> 00:33:59,160 Speaker 1: than they will be used in the in the longer 620 00:33:59,280 --> 00:34:03,400 Speaker 1: term future for actual tokens. Actually, you know, if you 621 00:34:03,560 --> 00:34:05,080 Speaker 1: if you look at the size of the of the 622 00:34:05,080 --> 00:34:07,200 Speaker 1: space that we're looking at, this is we're talking about 623 00:34:07,200 --> 00:34:09,480 Speaker 1: two lunch and twillions of dollars of real world assets 624 00:34:09,560 --> 00:34:12,720 Speaker 1: and funds and you know, credit and real estate exec 625 00:34:12,920 --> 00:34:15,120 Speaker 1: that can be organized and put into the into the blockchains. 626 00:34:15,160 --> 00:34:18,000 Speaker 1: So that works anything else that you've seen in more 627 00:34:18,040 --> 00:34:20,680 Speaker 1: like native digital assets if you want, like bacon or 628 00:34:20,719 --> 00:34:22,440 Speaker 1: a theory. So I think that the potential of this 629 00:34:23,120 --> 00:34:27,040 Speaker 1: becoming the biggest thing in crypto is definitely there. Carlos Amingo, 630 00:34:27,120 --> 00:34:30,120 Speaker 1: that's the CEO of Securities. Looking forward to your next day. 631 00:34:30,120 --> 00:34:31,880 Speaker 1: I'll hope you come back to talk to us about it. 632 00:34:31,920 --> 00:34:35,640 Speaker 1: I'm only definitely thanks for having me. All right, Actionality, 633 00:34:36,160 --> 00:34:49,239 Speaker 1: thank you. Welcome back to Bloomberg Technology. SpaceX launching a 634 00:34:49,360 --> 00:34:53,200 Speaker 1: manned crew of four on an assa mission to the 635 00:34:53,239 --> 00:34:57,000 Speaker 1: International Space Station, including a Russian cosmo and the first 636 00:34:57,080 --> 00:35:00,880 Speaker 1: Native American woman to travel to space. Are at Ludlow 637 00:35:01,080 --> 00:35:04,279 Speaker 1: back with all the details and what exactly happened today. Yeah, 638 00:35:04,320 --> 00:35:07,480 Speaker 1: so we're deep into a twenty nine hour journey to 639 00:35:07,520 --> 00:35:10,360 Speaker 1: the International Space Station. As you said, Nicoleman one of 640 00:35:10,400 --> 00:35:13,000 Speaker 1: the crew members. In fact, the crew commander becomes the 641 00:35:13,040 --> 00:35:16,239 Speaker 1: first Native American woman to go to space. So it's 642 00:35:16,239 --> 00:35:20,080 Speaker 1: a landmark in that respect. She is a member of 643 00:35:20,160 --> 00:35:24,040 Speaker 1: one of the Round Valley Indian tribes here in California. 644 00:35:24,640 --> 00:35:26,839 Speaker 1: But there was also a Russian cosmonaut on board. It's 645 00:35:26,840 --> 00:35:29,960 Speaker 1: the first time SpaceX is carrying a Russian citizen, a 646 00:35:30,040 --> 00:35:33,799 Speaker 1: Russian cosmonaut from US soil to the I S S. 647 00:35:34,160 --> 00:35:35,960 Speaker 1: And as you know, and we talked about this week, 648 00:35:36,000 --> 00:35:38,239 Speaker 1: some of the controversial tweets Elon Mosk, who is the 649 00:35:38,239 --> 00:35:41,120 Speaker 1: CEO of SpaceX, made about the war in Ukraine and 650 00:35:41,200 --> 00:35:44,680 Speaker 1: about his belief about it a negotiated settlement with Russia. 651 00:35:44,719 --> 00:35:46,680 Speaker 1: But it's going to take them twenty nine hours to 652 00:35:46,680 --> 00:35:49,080 Speaker 1: get there. Talk to me in the next show and 653 00:35:49,080 --> 00:35:50,840 Speaker 1: we'll see if they made it safely. But this is 654 00:35:50,880 --> 00:35:54,120 Speaker 1: a kind of routine operation for SpaceX rights their fifth 655 00:35:54,200 --> 00:35:58,759 Speaker 1: crew mission, the eighth or ninth human flight mission, and 656 00:35:58,880 --> 00:36:01,759 Speaker 1: you know it takes the crew two miles above the Earth. 657 00:36:01,840 --> 00:36:04,360 Speaker 1: So how does this fit into them the broader mission 658 00:36:04,400 --> 00:36:07,399 Speaker 1: and the other things that SpaceX is working on. Yeah, 659 00:36:07,480 --> 00:36:10,040 Speaker 1: I think you know what SpaceX is really doing in 660 00:36:10,080 --> 00:36:13,719 Speaker 1: conjuncture in NASA is ramping up to go beyond the 661 00:36:13,719 --> 00:36:16,239 Speaker 1: International Space Station, right. You know, they're involved in the 662 00:36:16,280 --> 00:36:19,440 Speaker 1: project more broadly to go to the Moon, which that 663 00:36:19,520 --> 00:36:22,839 Speaker 1: relies on a different company's rocket Artemis, and as we know, 664 00:36:22,960 --> 00:36:26,240 Speaker 1: that is behind schedule. We don't expect SLS an Artemis 665 00:36:26,239 --> 00:36:29,120 Speaker 1: to launch until about mid November. You know, the next 666 00:36:29,200 --> 00:36:32,880 Speaker 1: kind of big mission for SpaceX in kind of advancing 667 00:36:32,960 --> 00:36:35,840 Speaker 1: humansplace fright is Polaris Dawn. And you know, through the 668 00:36:35,880 --> 00:36:39,920 Speaker 1: Polaris program that they basically are going to push the 669 00:36:39,920 --> 00:36:42,920 Speaker 1: boundaries of what they're capable of doing in terms of 670 00:36:42,960 --> 00:36:45,680 Speaker 1: how long and how often humans can go into space. 671 00:36:45,960 --> 00:36:48,880 Speaker 1: But part of that is contingent on the development of Starship. 672 00:36:48,960 --> 00:36:51,680 Speaker 1: And what we're really waiting on from SpaceX is news 673 00:36:51,680 --> 00:36:54,120 Speaker 1: of when we'll get that orbital test flight of Starship, 674 00:36:54,520 --> 00:36:56,040 Speaker 1: because we don't know when that will be. And we've 675 00:36:56,040 --> 00:36:59,600 Speaker 1: talked so much about Tesla and the impact on Tesla 676 00:36:59,640 --> 00:37:02,600 Speaker 1: with e Musk taking over Twitter, unless so about SpaceX 677 00:37:02,600 --> 00:37:04,400 Speaker 1: since as a private company, But what do we know 678 00:37:04,400 --> 00:37:08,520 Speaker 1: about how folks SpaceX feel about Elon Musk taking on 679 00:37:08,560 --> 00:37:12,520 Speaker 1: another big company? Yeah, I mean, generally speaking, Elon Musk 680 00:37:12,560 --> 00:37:15,480 Speaker 1: has also been divisive within the ranks at SpaceX, right. 681 00:37:15,520 --> 00:37:17,560 Speaker 1: There are many employees that do not believe in some 682 00:37:17,600 --> 00:37:19,960 Speaker 1: of the things he said and disagree with some of 683 00:37:20,040 --> 00:37:23,120 Speaker 1: his actions. There is also an element of key man risk. 684 00:37:23,200 --> 00:37:26,920 Speaker 1: You know, Elon Musk is a hands on manager and 685 00:37:26,960 --> 00:37:29,480 Speaker 1: executive at SpaceX in much the same way that he 686 00:37:29,600 --> 00:37:32,799 Speaker 1: is Tesla. You know, he often attends some of the 687 00:37:32,880 --> 00:37:36,520 Speaker 1: key launches. He's often present in Hawthorne where space Sex 688 00:37:36,600 --> 00:37:39,520 Speaker 1: is kind of headquarters and R and D Center is. 689 00:37:39,760 --> 00:37:41,439 Speaker 1: So there is a question, you know, if he takes 690 00:37:41,480 --> 00:37:43,920 Speaker 1: on Twitter what does that mean with respect to how 691 00:37:43,920 --> 00:37:46,319 Speaker 1: he splits his time between those three companies. But as 692 00:37:46,360 --> 00:37:48,160 Speaker 1: we know, he is a man that spends a lot 693 00:37:48,239 --> 00:37:50,040 Speaker 1: of time on a private jet, a lot of time 694 00:37:50,040 --> 00:37:52,120 Speaker 1: on his phone, and doesn't sleep as much as the 695 00:37:52,160 --> 00:37:56,200 Speaker 1: average human. All Right, Indeed, at love Low, thank you. 696 00:37:56,440 --> 00:37:58,920 Speaker 1: As always, we'll be watching for the results of this 697 00:37:59,000 --> 00:38:01,359 Speaker 1: latest mission. Um, and that does that for this edition 698 00:38:01,400 --> 00:38:04,920 Speaker 1: of Bloomberg Technology. Uh. Coming up Thursday, we've got Google 699 00:38:04,960 --> 00:38:09,440 Speaker 1: Senior vice president of Devices and Services, Rick Ostrolo at 700 00:38:09,440 --> 00:38:13,960 Speaker 1: the company's Made by Google hardware launch event. I'm Emily 701 00:38:14,040 --> 00:38:16,360 Speaker 1: Chang in San Francisco. This is Bloomberg