1 00:00:02,200 --> 00:00:05,480 Speaker 1: From the heart of where innovation, money and power Collie 2 00:00:06,320 --> 00:00:10,880 Speaker 1: in Silicon Valley and beyond. This is Bloomberg Technology with 3 00:00:10,920 --> 00:00:27,520 Speaker 1: Emily Jay. I'm Emily Jacket, San Francisco, and this is 4 00:00:27,520 --> 00:00:29,920 Speaker 1: Bloomberg Technology coming up in the next hour. In video 5 00:00:30,000 --> 00:00:32,879 Speaker 1: misses on revenue by more than a billion dollars, assigned 6 00:00:32,920 --> 00:00:36,839 Speaker 1: demand for PCs, gaming consoles and other electronics might be 7 00:00:36,960 --> 00:00:40,320 Speaker 1: drying up after a two year pandemic boom. We'll talk 8 00:00:40,360 --> 00:00:44,720 Speaker 1: about just how long the slump could last. Plus, Apple 9 00:00:45,000 --> 00:00:46,960 Speaker 1: is being picky when it comes to M and A, 10 00:00:47,040 --> 00:00:50,519 Speaker 1: why the iphonemaker has slowed down its buying spree despite 11 00:00:50,560 --> 00:00:55,160 Speaker 1: a one seventy nine billion dollar war chest. And is 12 00:00:55,280 --> 00:00:59,160 Speaker 1: Facebook really the underdog now or are we underestimating it 13 00:00:59,200 --> 00:01:01,760 Speaker 1: will count the way in which TikTok still doesn't even 14 00:01:01,800 --> 00:01:04,960 Speaker 1: come close to Meta. All of that in a moment, 15 00:01:04,959 --> 00:01:07,600 Speaker 1: but first, sticking with in video, the graphics chip giant 16 00:01:07,640 --> 00:01:10,360 Speaker 1: missing its own quarterly revenue projections by more than a 17 00:01:10,440 --> 00:01:14,440 Speaker 1: billion dollars evidence that demand for electronics components is drying 18 00:01:14,520 --> 00:01:17,680 Speaker 1: up after a two year pandemic boom boom. Brooks I 19 00:01:17,760 --> 00:01:20,479 Speaker 1: and King, who covers all things semiconductors, joins US now 20 00:01:20,520 --> 00:01:23,640 Speaker 1: and wow, a billion dollars miss is not something you 21 00:01:23,680 --> 00:01:27,200 Speaker 1: normally associate with Jentsen Wong and in video what happened? Yeah, 22 00:01:27,240 --> 00:01:29,640 Speaker 1: I mean, it's it's not a surprise that it happened, 23 00:01:30,080 --> 00:01:32,280 Speaker 1: given what Intel had said, what am D had said, 24 00:01:32,319 --> 00:01:35,720 Speaker 1: what other PC related kind of components make as it said. 25 00:01:35,720 --> 00:01:39,400 Speaker 1: But I think the extent to which they fell short 26 00:01:39,480 --> 00:01:42,200 Speaker 1: and the sort of rapidity with which demand has obviously 27 00:01:42,240 --> 00:01:45,480 Speaker 1: fallen away has obviously caused a lot of concern. And 28 00:01:45,600 --> 00:01:48,640 Speaker 1: that's what the analysts and investors have been talking about today. 29 00:01:48,720 --> 00:01:51,680 Speaker 1: Why did they get their own projections so wrong? Yeah, 30 00:01:51,720 --> 00:01:53,800 Speaker 1: I mean they said, oh, it just happens, how quickly 31 00:01:53,800 --> 00:01:56,840 Speaker 1: it fell off, so so rapidly that we didn't see 32 00:01:56,840 --> 00:01:59,720 Speaker 1: this coming. The concern, or, if you like, the underlying 33 00:02:00,040 --> 00:02:03,680 Speaker 1: fish is that it's not just consumers and not just 34 00:02:04,640 --> 00:02:08,640 Speaker 1: gaming related, but also this crypto dependency that they said 35 00:02:08,680 --> 00:02:12,040 Speaker 1: that they've shared, Our chips aren't good for crypto mining anymore, 36 00:02:12,080 --> 00:02:13,760 Speaker 1: you don't need to worry about that. But then we 37 00:02:13,880 --> 00:02:17,560 Speaker 1: see cryptocurrency has obviously been to a rough time, no 38 00:02:17,680 --> 00:02:20,000 Speaker 1: reason to be mining in a lot of situations. Now, 39 00:02:20,120 --> 00:02:22,959 Speaker 1: maybe those cards are coming back into the gaming market. 40 00:02:23,040 --> 00:02:25,920 Speaker 1: They also pre announced. I mean, how unusual? Is this 41 00:02:26,240 --> 00:02:29,120 Speaker 1: relatively unusual? But again, to be fair to Nvidio, at 42 00:02:29,160 --> 00:02:32,399 Speaker 1: least they did. One of the big themes on Intel's 43 00:02:32,480 --> 00:02:35,280 Speaker 1: kind of disaster at call last week was why didn't 44 00:02:35,320 --> 00:02:37,160 Speaker 1: you pre announce when it was so bad? You know, 45 00:02:37,200 --> 00:02:40,480 Speaker 1: investors don't like surprises. The fact that they did is, 46 00:02:40,560 --> 00:02:43,160 Speaker 1: as you say, unusual. But at least they're being forth 47 00:02:43,280 --> 00:02:45,680 Speaker 1: right and they're being given some credit by at least 48 00:02:45,680 --> 00:02:47,560 Speaker 1: some of the analysts for doing that. So are they 49 00:02:47,560 --> 00:02:50,520 Speaker 1: clearing inventory? And is this something that will be cleared, 50 00:02:50,960 --> 00:02:53,959 Speaker 1: you know, say by the next quarter. That's that's the 51 00:02:54,040 --> 00:02:56,639 Speaker 1: positive scenario. The positive scenario says, this is what the 52 00:02:56,720 --> 00:02:59,520 Speaker 1: chip industry does. They over build, They get it wrong. 53 00:02:59,560 --> 00:03:03,520 Speaker 1: They can't match these supply with short term demand movements. 54 00:03:03,680 --> 00:03:05,600 Speaker 1: As soon as we clear out the inventory, we're back 55 00:03:05,639 --> 00:03:09,520 Speaker 1: to normalize situation. Everything's okay. That's a positive picture. The 56 00:03:09,560 --> 00:03:13,480 Speaker 1: negative is like consumer demand. Meantime, they've been investing in 57 00:03:13,520 --> 00:03:15,960 Speaker 1: the server market and that's actually helped kind of cushion 58 00:03:16,000 --> 00:03:19,399 Speaker 1: the blow. Right, Yeah, no, absolutely right. That's why they're 59 00:03:19,400 --> 00:03:22,760 Speaker 1: the world's most valuable chip company because they've built this 60 00:03:22,840 --> 00:03:26,680 Speaker 1: incredible service business. But even that missed today. So what 61 00:03:26,760 --> 00:03:30,119 Speaker 1: does they say about the broader state of the chip industry. 62 00:03:30,160 --> 00:03:33,919 Speaker 1: I mean, did anybody expect the pandemic boom to to 63 00:03:34,639 --> 00:03:38,240 Speaker 1: last indefinitely? I mean, come on, you're remembering it perfectly. 64 00:03:38,280 --> 00:03:40,680 Speaker 1: How many times, right did we talk about this? How 65 00:03:40,720 --> 00:03:44,280 Speaker 1: many times did chip an industry CEOs tell you things 66 00:03:44,320 --> 00:03:46,920 Speaker 1: are different now? The PC market is a much higher level. 67 00:03:46,960 --> 00:03:50,560 Speaker 1: Everything's okay. Every household needs three or four PCs. Everything's 68 00:03:50,560 --> 00:03:52,560 Speaker 1: going will be okay. And here we are in the 69 00:03:52,560 --> 00:03:56,200 Speaker 1: middle of two two saying that's absolutely not true. All right, 70 00:03:56,280 --> 00:03:59,280 Speaker 1: and King, thank you for all the extra details there. 71 00:03:59,360 --> 00:04:11,640 Speaker 1: We'll be watching shares of Galaxy Digital rising Monday despite 72 00:04:11,680 --> 00:04:15,640 Speaker 1: reporting a five million dollar loss. Bloomberg Shinneli Bassa and 73 00:04:15,640 --> 00:04:19,320 Speaker 1: Caroline I spoke with Novegrats about the state of the 74 00:04:19,360 --> 00:04:23,479 Speaker 1: crypto winter. Take a listen. We've had one credit loss 75 00:04:23,520 --> 00:04:25,840 Speaker 1: in the history of our company, and uh, you know, 76 00:04:25,880 --> 00:04:31,120 Speaker 1: I disclosed the name today. It's a manageall lost relative 77 00:04:31,160 --> 00:04:33,560 Speaker 1: to our balance sheet, relative our credit business. Our credit 78 00:04:33,600 --> 00:04:36,560 Speaker 1: business actually was profitable on the on the quarter. I 79 00:04:36,600 --> 00:04:40,039 Speaker 1: feel pretty good about that. What we saw away from 80 00:04:40,120 --> 00:04:44,000 Speaker 1: us was huge concentration in this one name, which created 81 00:04:44,040 --> 00:04:46,680 Speaker 1: a lot of the systemic risk that we saw. Uh, 82 00:04:46,760 --> 00:04:48,760 Speaker 1: and the and the cascading of bitcoin all the way 83 00:04:48,839 --> 00:04:52,440 Speaker 1: eighteen thousand um. You know, I I don't have a 84 00:04:52,480 --> 00:04:55,960 Speaker 1: crystal ball when I add up the total planes that 85 00:04:56,080 --> 00:04:59,560 Speaker 1: people filed. Uh, it doesn't feel like there'll be a 86 00:04:59,600 --> 00:05:04,320 Speaker 1: lot comes back in that case. You know, you've got Celsius, 87 00:05:04,360 --> 00:05:07,960 Speaker 1: You've got Voyager, You've got lots of other places where 88 00:05:07,960 --> 00:05:11,240 Speaker 1: both institutions and retail lost a lot of money, and 89 00:05:11,279 --> 00:05:13,360 Speaker 1: there will be a business for that where people are 90 00:05:13,400 --> 00:05:16,160 Speaker 1: bidding up. I want to double down on retail because 91 00:05:16,160 --> 00:05:18,159 Speaker 1: you brought it up. You know, you mentioned earlier that 92 00:05:18,200 --> 00:05:20,839 Speaker 1: your skeptical of a soft landing, and to the extent 93 00:05:20,880 --> 00:05:22,880 Speaker 1: that means you mean there's a recession coming that it 94 00:05:22,880 --> 00:05:25,400 Speaker 1: will be a hard landing. How much money will there 95 00:05:25,440 --> 00:05:27,880 Speaker 1: really be on the sidelines to put into crypto, let 96 00:05:27,880 --> 00:05:33,200 Speaker 1: alone any risk asset. Listen, you know, the FED increased 97 00:05:33,960 --> 00:05:37,000 Speaker 1: money to supply at a rate that we've never seen before, 98 00:05:37,040 --> 00:05:40,560 Speaker 1: and they're slowly withdrawing that. There's still a ton of 99 00:05:40,600 --> 00:05:43,480 Speaker 1: money in the system, right There was excess savings in 100 00:05:43,800 --> 00:05:47,560 Speaker 1: retail that's getting worn down some. But there's monster casualties. 101 00:05:47,560 --> 00:05:51,520 Speaker 1: People got really nervous, and we had a pretty dramatic 102 00:05:51,560 --> 00:05:53,960 Speaker 1: sell off in the first half of the year. And 103 00:05:54,000 --> 00:05:56,080 Speaker 1: so I don't think we're going to see what we 104 00:05:56,120 --> 00:05:58,680 Speaker 1: saw last year when money is flowing in and it's 105 00:05:58,720 --> 00:06:01,880 Speaker 1: all it's all booming. But I don't think it's armageddon 106 00:06:01,920 --> 00:06:05,839 Speaker 1: here yet either. Uh And so again I I, you know, 107 00:06:05,880 --> 00:06:10,320 Speaker 1: will Bitcoin get through thirty thousand on this move up, 108 00:06:11,040 --> 00:06:13,599 Speaker 1: We'll see. I'm doubtful. I think we're gonna probably be 109 00:06:13,600 --> 00:06:16,520 Speaker 1: in this range now. I'm quite frankuively be happy if 110 00:06:16,520 --> 00:06:20,120 Speaker 1: we're in a a you know, twenty two thousand or 111 00:06:20,120 --> 00:06:22,960 Speaker 1: twenty thousand thirty thousand range for a while. With the 112 00:06:23,000 --> 00:06:25,400 Speaker 1: next move breaking up, hearium has got a little bit 113 00:06:25,440 --> 00:06:27,240 Speaker 1: more juice at the top of its range. It can 114 00:06:27,279 --> 00:06:30,719 Speaker 1: be you know, makes out, it could go higher. That's 115 00:06:30,760 --> 00:06:33,320 Speaker 1: got a real story. But I don't see, you know, 116 00:06:33,360 --> 00:06:38,279 Speaker 1: the mania that we saw in one or twenty seventeen reigniting. Listen. 117 00:06:38,320 --> 00:06:43,760 Speaker 1: I hope are wrong. Galaxy Digital CEO Mike novograts there. Meantime, 118 00:06:43,960 --> 00:06:47,239 Speaker 1: Apple used to acquire a company every three to four weeks, 119 00:06:47,240 --> 00:06:50,839 Speaker 1: but it's dramatically slowed. It's dealmaking in the last two years. 120 00:06:50,960 --> 00:06:53,680 Speaker 1: Apple spent one a app billion dollars on payments tied 121 00:06:53,720 --> 00:06:57,160 Speaker 1: to acquisitions in fiscal year twenty, but just over two 122 00:06:57,279 --> 00:07:00,440 Speaker 1: hundred million dollars in the last ten months. Brig Smart 123 00:07:00,440 --> 00:07:04,000 Speaker 1: German here to discuss. So why is Apple slowing down 124 00:07:04,040 --> 00:07:07,920 Speaker 1: the pace of deal Smart that's a good question. Well, 125 00:07:08,000 --> 00:07:10,000 Speaker 1: when you look at this chart, when you think about it, 126 00:07:10,080 --> 00:07:12,600 Speaker 1: the first two things you might you know, the reasons 127 00:07:12,640 --> 00:07:15,920 Speaker 1: you might propose as one, COVID Right, COVID messed up. 128 00:07:16,080 --> 00:07:18,520 Speaker 1: You know everyone's business plan. You have to tear it 129 00:07:18,560 --> 00:07:21,440 Speaker 1: all up and start over. Right. The second is regulation. 130 00:07:21,600 --> 00:07:26,040 Speaker 1: Obviously you have the FTC going after in video Microsoft deals, 131 00:07:26,080 --> 00:07:29,240 Speaker 1: you have the act Division deal for nearly seventy billion dollars, 132 00:07:29,240 --> 00:07:31,880 Speaker 1: you have Meta Amazon, all these players spending so much 133 00:07:31,920 --> 00:07:34,440 Speaker 1: money and the regulators assuming them and trying to get 134 00:07:34,440 --> 00:07:37,480 Speaker 1: in their way. And so maybe Apple is fearful of that, 135 00:07:38,040 --> 00:07:41,000 Speaker 1: as a new note inside of the regulatory filings to 136 00:07:41,080 --> 00:07:43,920 Speaker 1: the SEC may suggest. But I think it's really neither 137 00:07:43,960 --> 00:07:46,840 Speaker 1: of those, because you look, that was really the height 138 00:07:47,000 --> 00:07:49,600 Speaker 1: of the pandemic. In that year they spent more than 139 00:07:49,640 --> 00:07:53,760 Speaker 1: they had since right. I also think that Apple is 140 00:07:53,800 --> 00:07:57,720 Speaker 1: not spending amounts of money that necessarily would lead to 141 00:07:58,200 --> 00:08:01,720 Speaker 1: scrutiny from the FTC. You know, their government's globally right, 142 00:08:01,800 --> 00:08:03,400 Speaker 1: So I think this is a matter of fact of 143 00:08:03,400 --> 00:08:08,040 Speaker 1: their product development schedule. One, two investing in other areas, 144 00:08:08,040 --> 00:08:11,440 Speaker 1: and three maybe they're trying to go at it more alone, right, 145 00:08:11,480 --> 00:08:14,640 Speaker 1: without needing to acquire companies. But at the same time, 146 00:08:14,760 --> 00:08:17,760 Speaker 1: this is extremely odd. I would bet that most people 147 00:08:17,920 --> 00:08:21,600 Speaker 1: don't know that Serie face, I D Touch, I D 148 00:08:21,920 --> 00:08:24,880 Speaker 1: Apple Music, Apple News, the weather app. I could sit 149 00:08:24,920 --> 00:08:27,480 Speaker 1: here for ten minutes giving you a list of iPhone 150 00:08:27,520 --> 00:08:30,360 Speaker 1: features that we all use every day. Those all stemmed 151 00:08:30,360 --> 00:08:33,880 Speaker 1: from acquisitions, and so buying smaller companies and startups and 152 00:08:33,960 --> 00:08:37,280 Speaker 1: core technologies and engineering teams has been core to the 153 00:08:37,320 --> 00:08:41,200 Speaker 1: Apple development process ever before, since Steve Jobs even returned 154 00:08:41,200 --> 00:08:43,720 Speaker 1: to the company in the late nineties. That's interesting because 155 00:08:43,760 --> 00:08:47,680 Speaker 1: Apple has never been one to make big acquisitions, certainly 156 00:08:47,760 --> 00:08:51,280 Speaker 1: not to the scale that Mark Zuckerberg has. For example, 157 00:08:51,600 --> 00:08:55,520 Speaker 1: How how is them not making these smaller acquisitions over 158 00:08:55,559 --> 00:08:58,360 Speaker 1: at least the last year going to impact the product 159 00:08:58,360 --> 00:09:01,560 Speaker 1: development cycle? You know, I would look at it this way. 160 00:09:01,720 --> 00:09:04,560 Speaker 1: I think that these acquisitions have helped Apple get to 161 00:09:04,600 --> 00:09:07,959 Speaker 1: where they want to get much more quickly, right and 162 00:09:08,080 --> 00:09:10,800 Speaker 1: at lower costs, you know, per se Right, I'll give 163 00:09:10,840 --> 00:09:16,120 Speaker 1: you my favorite Apple acquisition is probably authentic back in right, 164 00:09:16,160 --> 00:09:18,920 Speaker 1: they bought that company, and all that company did was 165 00:09:19,040 --> 00:09:22,760 Speaker 1: make very secure and reliable fingerprint scanners, right, and that 166 00:09:22,760 --> 00:09:25,000 Speaker 1: that led to touch I D on the iPhone five s. 167 00:09:26,080 --> 00:09:29,640 Speaker 1: Remember how cool that was? Right? And so those little things, 168 00:09:29,760 --> 00:09:32,040 Speaker 1: even though they're not big deals, led to some pretty 169 00:09:32,080 --> 00:09:34,880 Speaker 1: cool features that have helped them sell new phones. Right. 170 00:09:35,080 --> 00:09:37,440 Speaker 1: And to answer your question, I think they should really 171 00:09:37,480 --> 00:09:41,760 Speaker 1: be snapping up autonomous car companies, car companies in general 172 00:09:41,840 --> 00:09:46,360 Speaker 1: car manufacturing to really bring that Apple car closer to fruition. 173 00:09:46,559 --> 00:09:49,840 Speaker 1: Remember when Elon Musk said that Apple buying Tesla on 174 00:09:49,880 --> 00:09:52,640 Speaker 1: the table for a market cap around sixty billion, was 175 00:09:52,679 --> 00:09:55,319 Speaker 1: on the table about five years ago before the Model 176 00:09:55,360 --> 00:09:57,880 Speaker 1: three came out. Imagine if Apple would have bought Tesla 177 00:09:57,920 --> 00:10:01,120 Speaker 1: back then, how different the our industry would look today 178 00:10:01,240 --> 00:10:03,280 Speaker 1: for just a sixty billion dollar deal. And when I say, 179 00:10:03,360 --> 00:10:06,040 Speaker 1: just if you compare a sixty billion dollar deal compared 180 00:10:06,080 --> 00:10:09,120 Speaker 1: to Apple's cash balance over the last decade or so, right, 181 00:10:09,160 --> 00:10:12,200 Speaker 1: it is small potatoes. So I think their acquisition strategy 182 00:10:12,400 --> 00:10:14,120 Speaker 1: has paid off in a lot of ways, but we're 183 00:10:14,120 --> 00:10:16,079 Speaker 1: seeing some changes here, at least for the last two 184 00:10:16,120 --> 00:10:20,280 Speaker 1: fiscal years. All right, Mark German and Ali, Thanks Mark 185 00:10:20,400 --> 00:10:24,120 Speaker 1: as always. Thanks all right. Coming up digital rights in 186 00:10:24,240 --> 00:10:27,800 Speaker 1: a post row world. How to navigate what can and 187 00:10:28,000 --> 00:10:30,400 Speaker 1: can't be used against you when it comes to your 188 00:10:30,440 --> 00:10:47,720 Speaker 1: web searches. That is next. This is Bloomberg. Their companies 189 00:10:47,800 --> 00:10:51,560 Speaker 1: provide a very important service that allows people to access 190 00:10:51,600 --> 00:10:56,400 Speaker 1: information about their healthcare. Tech companies could choose to uh 191 00:10:56,720 --> 00:11:02,000 Speaker 1: provide that information, provide free security services to websites disseminating 192 00:11:02,080 --> 00:11:05,439 Speaker 1: that information so they're protected from vigilante hackers. The other 193 00:11:05,559 --> 00:11:09,040 Speaker 1: things that tech company can do is become very prepared 194 00:11:09,200 --> 00:11:11,599 Speaker 1: to go into court and actually pushed back against the 195 00:11:11,640 --> 00:11:14,400 Speaker 1: requests that they get from law enforcement. They have enough 196 00:11:14,640 --> 00:11:18,240 Speaker 1: data on all of us to serve their business model. 197 00:11:18,320 --> 00:11:22,199 Speaker 1: They don't need data about people's private health choices in 198 00:11:22,360 --> 00:11:25,719 Speaker 1: order to make money. And if they are disregarding the 199 00:11:26,080 --> 00:11:29,600 Speaker 1: rights and welfare of the people that they are serving 200 00:11:29,679 --> 00:11:32,760 Speaker 1: through the technologies that they provide, those people are going 201 00:11:32,840 --> 00:11:38,840 Speaker 1: to be less and less able to participate. As abortion 202 00:11:38,920 --> 00:11:42,520 Speaker 1: restrictions tighten in various states across the United States, questions 203 00:11:42,559 --> 00:11:46,480 Speaker 1: remain about privacy. How will new laws be enforced in 204 00:11:46,559 --> 00:11:49,640 Speaker 1: the digital age. Privacy advocates warn that location and other 205 00:11:49,720 --> 00:11:52,079 Speaker 1: kinds of data could be used to track individuals who 206 00:11:52,160 --> 00:11:56,160 Speaker 1: visit abortion clinics or travel across state lines. Joining me 207 00:11:56,240 --> 00:11:58,960 Speaker 1: out to dig deeper into this is Alexandra Gibbons, President 208 00:11:59,080 --> 00:12:02,600 Speaker 1: of the Center for to Democracy and Technology. Alexandra, thank 209 00:12:02,600 --> 00:12:05,200 Speaker 1: you so much for joining us. So what's not being 210 00:12:05,280 --> 00:12:08,480 Speaker 1: talked about? Um when we think about the power that 211 00:12:08,600 --> 00:12:13,319 Speaker 1: these companies have and that the threat that our information 212 00:12:13,880 --> 00:12:17,160 Speaker 1: could be used against us. I think this really is 213 00:12:17,280 --> 00:12:19,839 Speaker 1: a wake up moment for the tech companies to think 214 00:12:19,880 --> 00:12:23,079 Speaker 1: about the sheer amount of information that they have and 215 00:12:23,160 --> 00:12:26,000 Speaker 1: to know that their users want that information to be protected. 216 00:12:26,440 --> 00:12:28,800 Speaker 1: So we need companies thinking about just how much data 217 00:12:28,840 --> 00:12:31,240 Speaker 1: they collect, how long they store it for, where they're 218 00:12:31,280 --> 00:12:33,800 Speaker 1: sharing it with, and getting really smart about how they 219 00:12:33,840 --> 00:12:37,000 Speaker 1: respond to law enforcement requests as well. What kind of 220 00:12:37,120 --> 00:12:40,839 Speaker 1: data are you most worried about that these companies have. 221 00:12:42,400 --> 00:12:44,719 Speaker 1: So right after the news of the overturning of rovi 222 00:12:44,840 --> 00:12:47,120 Speaker 1: weight came out, there was a big conversation about period 223 00:12:47,200 --> 00:12:50,400 Speaker 1: tracking apps and that matters. But users need to realize 224 00:12:50,440 --> 00:12:52,400 Speaker 1: that there's a lot more they should be focused on. 225 00:12:52,920 --> 00:12:56,640 Speaker 1: We're talking about your browser information, what websites you visited, 226 00:12:57,000 --> 00:13:00,760 Speaker 1: your search history, your online purchases of some he purchases, 227 00:13:01,120 --> 00:13:04,120 Speaker 1: medication that could be used in the case of an abortion, 228 00:13:04,559 --> 00:13:07,640 Speaker 1: and then also the subject matter of your texts and emails, 229 00:13:07,960 --> 00:13:10,760 Speaker 1: and finally your location information, which we can be collected 230 00:13:10,800 --> 00:13:13,360 Speaker 1: by your phone, by apps on your phone, and also 231 00:13:13,480 --> 00:13:18,880 Speaker 1: by your Internet service provider as well. How should tech 232 00:13:18,960 --> 00:13:23,839 Speaker 1: companies prepare themselves to deal with this? They need to 233 00:13:23,880 --> 00:13:26,079 Speaker 1: think about a couple of different things. One is just 234 00:13:26,160 --> 00:13:29,280 Speaker 1: their data collection practices. In the first place, we're about 235 00:13:29,320 --> 00:13:31,839 Speaker 1: to enter a world where law enforcement is asking these 236 00:13:31,920 --> 00:13:35,719 Speaker 1: companies to hand over their customers most sensitive information for 237 00:13:35,840 --> 00:13:38,800 Speaker 1: prosecutions that are wildly unpopular when you look at the 238 00:13:38,800 --> 00:13:41,800 Speaker 1: broader American public. So companies need to think about what 239 00:13:41,920 --> 00:13:44,679 Speaker 1: they're collecting, how long they're keeping it for, and then 240 00:13:44,720 --> 00:13:47,400 Speaker 1: also how they are responding to these law enforcement requests. 241 00:13:47,440 --> 00:13:50,400 Speaker 1: If they get them. They need to be requiring a warrant. 242 00:13:50,679 --> 00:13:52,439 Speaker 1: They need to be fighting to make sure that those 243 00:13:52,480 --> 00:13:55,520 Speaker 1: warrants are narrowly tailored. They need to be pushing back 244 00:13:55,640 --> 00:13:59,400 Speaker 1: for law enforcement doing overbroad phishing expeditions, and they need 245 00:13:59,440 --> 00:14:01,720 Speaker 1: to be telling users about the request that they're getting 246 00:14:01,720 --> 00:14:05,200 Speaker 1: so we can have more transparency in the space. You've 247 00:14:05,240 --> 00:14:08,400 Speaker 1: also talked about how worried you are about a chilling 248 00:14:08,440 --> 00:14:13,000 Speaker 1: effect on free speech when it comes to information around abortion. 249 00:14:13,080 --> 00:14:16,079 Speaker 1: Can you explain that there's a big conversation to be 250 00:14:16,200 --> 00:14:20,200 Speaker 1: had here around online content moderation, So how companies can 251 00:14:20,280 --> 00:14:23,280 Speaker 1: make sure that they're helping people get access to reliable, 252 00:14:23,480 --> 00:14:28,360 Speaker 1: accurate information about abortion services, pushing away miss and disinformation, 253 00:14:29,000 --> 00:14:31,640 Speaker 1: and then also just pushing back on the growing number 254 00:14:31,680 --> 00:14:34,800 Speaker 1: of state laws were likely to see of state legislatures 255 00:14:34,840 --> 00:14:38,200 Speaker 1: trying to make it illegal to post online information about 256 00:14:38,280 --> 00:14:41,560 Speaker 1: how to access reproductive care. So we need the companies 257 00:14:41,600 --> 00:14:43,760 Speaker 1: to be thinking about what they're curating, what are the 258 00:14:43,840 --> 00:14:46,760 Speaker 1: signals they can put online to help give access to 259 00:14:46,920 --> 00:14:49,680 Speaker 1: good health care information fairly similar to what they've had 260 00:14:49,720 --> 00:14:52,440 Speaker 1: to do under COVID really um and also make sure 261 00:14:52,480 --> 00:14:55,840 Speaker 1: that they are not, you know, falling for these statutes 262 00:14:55,920 --> 00:14:59,320 Speaker 1: that try to access limit access to good information about 263 00:14:59,360 --> 00:15:04,080 Speaker 1: reproductive air. Are there ways that big tech companies could 264 00:15:04,160 --> 00:15:07,080 Speaker 1: help women wanting to make this choice or who feel 265 00:15:07,120 --> 00:15:09,800 Speaker 1: like they have no choice but to make this quote 266 00:15:09,880 --> 00:15:13,760 Speaker 1: unquote choice. Yeah, I mean, it's all about knowing your options, right. 267 00:15:13,920 --> 00:15:17,160 Speaker 1: It's about a woman being able to understand the circumstances 268 00:15:17,280 --> 00:15:20,360 Speaker 1: that she's in and make an informed decision. And so 269 00:15:20,800 --> 00:15:23,040 Speaker 1: some of the things that we've seen companies do which 270 00:15:23,120 --> 00:15:25,920 Speaker 1: I admire and like, is, for example, of a person 271 00:15:26,000 --> 00:15:29,320 Speaker 1: searches for abortion services, what are the ads that can 272 00:15:29,440 --> 00:15:31,720 Speaker 1: come up against that search, you know, down the bar 273 00:15:31,840 --> 00:15:34,000 Speaker 1: on the side of your search engine. How do we 274 00:15:34,160 --> 00:15:37,120 Speaker 1: make sure that those are from certified providers, They are 275 00:15:37,200 --> 00:15:40,560 Speaker 1: trusted ads, They're not from places that actually are trying 276 00:15:40,680 --> 00:15:44,200 Speaker 1: to trap people that are seeking information about abortion care. 277 00:15:44,560 --> 00:15:46,880 Speaker 1: And we have reason to believe in this climate, the 278 00:15:47,080 --> 00:15:50,600 Speaker 1: crisis pregnancy centers, which come from the anti abortion movement 279 00:15:51,040 --> 00:15:53,480 Speaker 1: might well be trying to target people who are running 280 00:15:53,480 --> 00:15:55,840 Speaker 1: those searches. So there are things like that, What are 281 00:15:55,880 --> 00:15:59,480 Speaker 1: the indicators for trusted information that platforms can do? And 282 00:15:59,560 --> 00:16:02,800 Speaker 1: then how can they really quickly respond to fraudulent websites, 283 00:16:03,000 --> 00:16:05,840 Speaker 1: websites that are trying to entrapt people seeking information for 284 00:16:06,000 --> 00:16:09,840 Speaker 1: care and d escalating the spread of viral miss and 285 00:16:09,920 --> 00:16:14,240 Speaker 1: disinformation about abortion services as well. What are your biggest 286 00:16:14,520 --> 00:16:19,640 Speaker 1: fears about how technology could potentially be used against us. 287 00:16:20,440 --> 00:16:22,920 Speaker 1: I think they're starting to become true already, which is 288 00:16:23,040 --> 00:16:24,760 Speaker 1: the care of the fear that these are going to 289 00:16:24,800 --> 00:16:28,120 Speaker 1: be used in prosecutions. And also when you look at 290 00:16:28,160 --> 00:16:31,240 Speaker 1: some of these state statutes, it's not just law enforcement 291 00:16:31,320 --> 00:16:35,440 Speaker 1: prosecutions against people who are seeking or providing reproductive care, 292 00:16:35,920 --> 00:16:38,800 Speaker 1: but there are some statutes out there that authorized individual 293 00:16:38,920 --> 00:16:42,120 Speaker 1: citizens to go out as private bounty bounty hunters and 294 00:16:42,200 --> 00:16:45,200 Speaker 1: follow their own lawsuits against people that they suspect of 295 00:16:45,280 --> 00:16:48,800 Speaker 1: aiding and abetting abortions. That's really dangerous because it creates 296 00:16:48,880 --> 00:16:52,240 Speaker 1: this incentive system for you know, the Wild West, for 297 00:16:52,400 --> 00:16:54,880 Speaker 1: lone rangers to go out there be tracking down information 298 00:16:54,920 --> 00:16:58,600 Speaker 1: about their neighbors, bringing these lawsuits with the promise of 299 00:16:58,680 --> 00:17:00,800 Speaker 1: the state paying them a ten thousand dollar bounty if 300 00:17:00,840 --> 00:17:04,320 Speaker 1: they do so. That is a really worrying environment for 301 00:17:04,440 --> 00:17:08,920 Speaker 1: people's privacy and ability to access good information online. So 302 00:17:09,119 --> 00:17:11,520 Speaker 1: that is the type of landscape that the tech companies 303 00:17:11,600 --> 00:17:13,800 Speaker 1: just should not want to get themselves in the middle of. 304 00:17:14,280 --> 00:17:16,639 Speaker 1: And that is why we need the tech companies really 305 00:17:16,760 --> 00:17:20,200 Speaker 1: limiting their collection of sensitive health information that could be 306 00:17:20,400 --> 00:17:23,280 Speaker 1: used to create an inference that somebody has accessed abortion 307 00:17:23,400 --> 00:17:26,720 Speaker 1: services or any other type of reproductive care that could 308 00:17:26,760 --> 00:17:31,879 Speaker 1: expose them to litigation or prosecution. It's potentially very terrifying. 309 00:17:32,680 --> 00:17:37,560 Speaker 1: Have you seen any particular examples, UM, where this has 310 00:17:37,600 --> 00:17:40,399 Speaker 1: happened or where this is happening already? So there have 311 00:17:40,600 --> 00:17:43,680 Speaker 1: already been cases, even before the overturning of Roe v. Wade, 312 00:17:43,800 --> 00:17:47,800 Speaker 1: there were women who were being prosecuted for their pregnancy outcomes, 313 00:17:48,240 --> 00:17:52,040 Speaker 1: being accused of self inducing miscarriages late in their term. 314 00:17:52,560 --> 00:17:56,160 Speaker 1: And what was used in those prosecutions where people's browsing histories, 315 00:17:56,200 --> 00:17:59,600 Speaker 1: their online purchase history evidence that they had purchased certain 316 00:17:59,640 --> 00:18:03,200 Speaker 1: medications online. And then even in one case, the subject 317 00:18:03,359 --> 00:18:05,920 Speaker 1: and the contents of a woman's text messages with a 318 00:18:06,000 --> 00:18:07,520 Speaker 1: friend as she was trying to get it vice on 319 00:18:07,640 --> 00:18:10,720 Speaker 1: what to do. So we've seen already in these cases 320 00:18:11,040 --> 00:18:13,879 Speaker 1: that digital evidence can be used in evidence against you. 321 00:18:14,000 --> 00:18:15,760 Speaker 1: And so that's a reason why users need to be 322 00:18:15,840 --> 00:18:18,280 Speaker 1: careful and why the companies really need to be watching 323 00:18:18,359 --> 00:18:23,200 Speaker 1: us as well. Chilling indeed, Alexander Gibbons, thank you for 324 00:18:23,359 --> 00:18:26,280 Speaker 1: shedding light on this issue. Really appreciated. President of the 325 00:18:26,320 --> 00:18:30,479 Speaker 1: Center for Democracy and Technology, UM, thank you for stopping by. 326 00:18:39,840 --> 00:18:42,400 Speaker 1: Welcome back to Bloomer Technology, and Emily Check in San Francisco. 327 00:18:42,520 --> 00:18:46,280 Speaker 1: SoftBank says it will sell some or all of its 328 00:18:46,320 --> 00:18:49,840 Speaker 1: shares in so far reported holdings equivalent to a nine 329 00:18:49,920 --> 00:18:54,000 Speaker 1: percent steak. Soft Bank reporting a record net loss as 330 00:18:54,040 --> 00:18:57,360 Speaker 1: a self and Global Tech Stocks continues to hammer its 331 00:18:57,480 --> 00:19:00,879 Speaker 1: Vision Fund portfolio. I want to get back to markets now. 332 00:19:00,920 --> 00:19:04,440 Speaker 1: Shares of EV makers and clean energy companies jumping after 333 00:19:04,480 --> 00:19:08,119 Speaker 1: the US Senate passed a landmark bill on climate or 334 00:19:08,160 --> 00:19:11,200 Speaker 1: at Ludlow back with the movers. Yes, So the bill 335 00:19:11,359 --> 00:19:13,320 Speaker 1: moved those you'd expect them to a lot of EV 336 00:19:13,520 --> 00:19:16,440 Speaker 1: main names. Three seventy four billion dollars of energy and 337 00:19:16,480 --> 00:19:18,680 Speaker 1: climate spending is ear marks. You look at names like 338 00:19:18,760 --> 00:19:21,119 Speaker 1: Tesla actually been up much higher around five percent, but 339 00:19:21,200 --> 00:19:23,080 Speaker 1: closing up eight tenths of one percent, and some of 340 00:19:23,119 --> 00:19:26,399 Speaker 1: these smaller EV makers and legacy names like GM and Ford. 341 00:19:27,240 --> 00:19:30,560 Speaker 1: It ends the per manufacturer limit on the seventy dollar 342 00:19:30,640 --> 00:19:34,240 Speaker 1: tax credit, which is something we'd expected, had been negotiated 343 00:19:34,280 --> 00:19:36,119 Speaker 1: for many months, and of course that scene as a 344 00:19:36,200 --> 00:19:39,200 Speaker 1: tail wind for demand. But there are price limits. Anything 345 00:19:39,240 --> 00:19:42,480 Speaker 1: over fifty five dollars for an evy car or sedan 346 00:19:42,960 --> 00:19:46,359 Speaker 1: is not eligible, and anything over eighty dollars for a 347 00:19:46,440 --> 00:19:49,280 Speaker 1: pickup or suv is not eligible. But this is what 348 00:19:49,359 --> 00:19:51,840 Speaker 1: we've been waiting for the government to kind of give 349 00:19:51,920 --> 00:19:54,560 Speaker 1: this industry a bit of a push get it going. 350 00:19:55,000 --> 00:19:56,800 Speaker 1: Not done much for the stock so far this year, though, 351 00:19:56,840 --> 00:19:59,520 Speaker 1: you look at the performance of Tesla versus legacy names 352 00:19:59,560 --> 00:20:02,600 Speaker 1: like G and Forward year to date, there's still under 353 00:20:02,680 --> 00:20:05,320 Speaker 1: pressure and we're still seeing different declines. But I walk 354 00:20:05,359 --> 00:20:07,040 Speaker 1: over to this side of the screen and you do 355 00:20:07,160 --> 00:20:10,359 Speaker 1: see Forward in particular closing that share gap on tests 356 00:20:10,400 --> 00:20:12,919 Speaker 1: or in terms of year to date performance because they 357 00:20:12,960 --> 00:20:15,160 Speaker 1: are starting to ramp up their own activity, and again 358 00:20:15,280 --> 00:20:17,920 Speaker 1: with government support, there is hope that they'll see more. 359 00:20:18,080 --> 00:20:20,360 Speaker 1: It wasn't just evs as well. There are measures within 360 00:20:20,480 --> 00:20:23,520 Speaker 1: the bill for support for renewable energy, not just in 361 00:20:23,600 --> 00:20:25,920 Speaker 1: the form of solar, but also in hydrogen plug in 362 00:20:26,000 --> 00:20:28,440 Speaker 1: as well, and you see some names here across solar 363 00:20:28,800 --> 00:20:31,520 Speaker 1: moving pretty significantly on the back of that bill being 364 00:20:31,560 --> 00:20:33,639 Speaker 1: negotiated overnight. Not all the way there goes to the 365 00:20:33,720 --> 00:20:36,560 Speaker 1: House next for the expectation, even though this is trimmed 366 00:20:36,600 --> 00:20:38,879 Speaker 1: out down from where we started a year ago, is 367 00:20:38,920 --> 00:20:42,159 Speaker 1: that this is a really big play ultimately to reduce 368 00:20:42,240 --> 00:20:45,520 Speaker 1: common mission from where we were in two thousand five. 369 00:20:45,640 --> 00:20:50,679 Speaker 1: Interesting development, All right, thank you well. Mark Zuckerberg's new 370 00:20:50,760 --> 00:20:55,000 Speaker 1: narrative from matter has consistently involved pitching Facebook's platforms as 371 00:20:55,040 --> 00:20:58,719 Speaker 1: the underdog, especially when it comes to regulation and competition. 372 00:20:58,880 --> 00:21:01,360 Speaker 1: But Facebook may be in a better position to take 373 00:21:01,400 --> 00:21:04,600 Speaker 1: on TikTok than Zuckerberg is leading the public to believe, 374 00:21:04,920 --> 00:21:07,440 Speaker 1: according to Bloomberg Business Weeks Max Chaffkin, in a different 375 00:21:07,480 --> 00:21:11,120 Speaker 1: regulatory environment, Zuckerberg might simply try to buy TikTok. That's 376 00:21:11,119 --> 00:21:15,640 Speaker 1: not possible at the moment. Thus his strategy is evolving. 377 00:21:15,720 --> 00:21:19,119 Speaker 1: Max Chafkin joins me, Now, so does anybody really believe 378 00:21:19,200 --> 00:21:23,720 Speaker 1: Mark Zuckerberg when he says Meta is an underdog? Well, 379 00:21:23,760 --> 00:21:26,400 Speaker 1: I mean we've seen, uh yeah, a bunch of raft 380 00:21:26,440 --> 00:21:29,760 Speaker 1: of stories all about the the you know, existential challenges 381 00:21:29,800 --> 00:21:32,680 Speaker 1: facing Facebook, and of course investors have sent the stock 382 00:21:32,720 --> 00:21:36,880 Speaker 1: down something like since February, so so they're definitely people 383 00:21:36,920 --> 00:21:39,879 Speaker 1: out there with concerns, and I think what's happening is 384 00:21:39,960 --> 00:21:42,359 Speaker 1: that Zuckerberg is kind of leaning into them. So you 385 00:21:42,480 --> 00:21:47,520 Speaker 1: do have um economic challenges, right, So Facebook really benefited 386 00:21:47,600 --> 00:21:50,960 Speaker 1: from COVID stay at home orders and the sort of 387 00:21:51,080 --> 00:21:54,119 Speaker 1: explosion of e commerce shopping that's all gone away, and 388 00:21:54,200 --> 00:21:56,920 Speaker 1: then you do have this kind of cultural challenge where 389 00:21:57,200 --> 00:22:00,200 Speaker 1: TikTok is, you know, getting a lot of mind here. 390 00:22:00,280 --> 00:22:03,120 Speaker 1: It seems like a lot of the younger people, of course, 391 00:22:03,160 --> 00:22:05,359 Speaker 1: are are into TikTok. They're not into Facebook. And Z 392 00:22:05,600 --> 00:22:07,840 Speaker 1: were using that and saying, you know, we're we're really 393 00:22:07,920 --> 00:22:10,439 Speaker 1: in trouble. We need to We're gonna have this intense period. 394 00:22:10,600 --> 00:22:13,840 Speaker 1: He's kind of rattling the saber in terms of hiring, 395 00:22:13,960 --> 00:22:16,760 Speaker 1: telling employees you know, they shouldn't take vacations and and 396 00:22:17,000 --> 00:22:18,879 Speaker 1: you know they need to weed out the bad performers. 397 00:22:19,200 --> 00:22:22,320 Speaker 1: And I think this is as you say, it's strategic. Um, 398 00:22:22,480 --> 00:22:25,120 Speaker 1: it's both an effort to try to get more productivity 399 00:22:25,160 --> 00:22:27,760 Speaker 1: out of his staff um, and also kind of a 400 00:22:27,800 --> 00:22:31,200 Speaker 1: positioning thing because Facebook faces um serious and I trust 401 00:22:31,240 --> 00:22:34,159 Speaker 1: scrutiny on a couple of different fronts, and playing up 402 00:22:34,320 --> 00:22:38,080 Speaker 1: challenges from competition is of course one way to uh 403 00:22:38,359 --> 00:22:42,440 Speaker 1: to kind of diffuse a situation. How would you assess 404 00:22:42,880 --> 00:22:46,440 Speaker 1: Facebook position of power with respect to TikTok? You know, 405 00:22:46,520 --> 00:22:50,200 Speaker 1: what does Facebook have on TikTok and what is TikTok's 406 00:22:50,320 --> 00:22:54,440 Speaker 1: actual advantage. Yeah, so Facebook, it's really easy to to 407 00:22:54,520 --> 00:22:56,760 Speaker 1: sort of forget this. But Facebook is like way, way, 408 00:22:56,920 --> 00:23:00,479 Speaker 1: way bigger than TikTok. We we don't know, uh, exactly 409 00:23:00,560 --> 00:23:03,200 Speaker 1: how much money TikTok is making, but you know, independent 410 00:23:03,320 --> 00:23:06,440 Speaker 1: estimates put it at at four billion dollars in revenue 411 00:23:06,720 --> 00:23:11,159 Speaker 1: in and so on. Facebook, you know, is something like 412 00:23:11,600 --> 00:23:13,920 Speaker 1: over a hundred billion dollars right there. They're making like 413 00:23:14,119 --> 00:23:18,239 Speaker 1: eight times TikTok's revenue in profit for the year. Now, 414 00:23:18,480 --> 00:23:21,080 Speaker 1: TikTok could you know, and and there is a lot 415 00:23:21,119 --> 00:23:23,280 Speaker 1: of chatter about this. You know, TikTok gonna sort of 416 00:23:23,320 --> 00:23:25,320 Speaker 1: turn on the cash machine and and it's going to 417 00:23:25,400 --> 00:23:27,440 Speaker 1: find ways to make money. But but they haven't done 418 00:23:27,480 --> 00:23:29,920 Speaker 1: that yet. And there's really no reason to think that 419 00:23:30,119 --> 00:23:34,680 Speaker 1: they will be any better at monetizing than Mark Zuckerberg is. 420 00:23:34,800 --> 00:23:37,600 Speaker 1: Because what Facebook is, Bill, is this kind of incredible 421 00:23:38,040 --> 00:23:42,080 Speaker 1: cash machine for turning online attention into into revenue. And 422 00:23:42,440 --> 00:23:45,400 Speaker 1: he has, as you know, has been well documented, basically 423 00:23:45,480 --> 00:23:49,280 Speaker 1: a monopoly on on social media advertising, and TikTok is 424 00:23:49,320 --> 00:23:52,280 Speaker 1: certainly eating into that. But but really it's a very 425 00:23:52,359 --> 00:23:55,399 Speaker 1: long way away from um, you know, eating Mark Zuckerbook's 426 00:23:55,440 --> 00:23:59,440 Speaker 1: lunch that said, TikTok does seem to be way way 427 00:23:59,560 --> 00:24:04,920 Speaker 1: way inning the attention war with Facebook, or is that 428 00:24:05,080 --> 00:24:08,840 Speaker 1: also a misperception. Well, I think that's absolutely true, but 429 00:24:08,960 --> 00:24:11,280 Speaker 1: it's easy to forget that lots of other companies have 430 00:24:11,400 --> 00:24:13,920 Speaker 1: won this attention word Facebook. You know, there's been a 431 00:24:14,000 --> 00:24:15,720 Speaker 1: lot of people have pointed out that Facebook's kind of 432 00:24:15,800 --> 00:24:18,520 Speaker 1: lost it's cool or something like that. But what that 433 00:24:18,600 --> 00:24:20,480 Speaker 1: kind of overlooks is it's lost it's cool for like 434 00:24:20,760 --> 00:24:24,080 Speaker 1: the last ten years, right, Facebook lost its school first 435 00:24:24,680 --> 00:24:28,040 Speaker 1: to Instagram. Uh there was you know, Twitter was the 436 00:24:28,080 --> 00:24:31,560 Speaker 1: hot thing for a while, and over time Mark Zuckerberg 437 00:24:31,600 --> 00:24:34,959 Speaker 1: has found ways to maneuver the company. And now there 438 00:24:35,080 --> 00:24:37,600 Speaker 1: is one important difference. Whereas in the past, you know, 439 00:24:37,720 --> 00:24:39,920 Speaker 1: he would have just bought TikTok, right, that is not 440 00:24:40,040 --> 00:24:43,640 Speaker 1: possible because of FTC scrutiny. You know, he could try, 441 00:24:43,720 --> 00:24:45,879 Speaker 1: but it seems almost certain that the government would try 442 00:24:45,880 --> 00:24:47,760 Speaker 1: to block it, given that they're trying to block this 443 00:24:47,960 --> 00:24:51,200 Speaker 1: much smaller acquisition. So that's something that is not available 444 00:24:51,240 --> 00:24:54,160 Speaker 1: to him. But what is available to him is copying, 445 00:24:54,280 --> 00:24:57,440 Speaker 1: and we're seeing Facebook do that with its reals product 446 00:24:57,680 --> 00:25:00,399 Speaker 1: and with these efforts to to have more you AI 447 00:25:00,560 --> 00:25:03,639 Speaker 1: driven discovery, basically a TikTok like intervace. Those are the 448 00:25:03,680 --> 00:25:06,439 Speaker 1: complaint that that's what led to all these complaints from um, 449 00:25:06,600 --> 00:25:11,280 Speaker 1: you know, Instagram influencers and Kardashian adjacent UM types. UM. Now, 450 00:25:11,400 --> 00:25:13,960 Speaker 1: But the thing is, we know this is working in 451 00:25:14,160 --> 00:25:17,159 Speaker 1: part because Facebook has said one reason their revenue is 452 00:25:17,280 --> 00:25:21,399 Speaker 1: lower has been lower, is because they're driving users into 453 00:25:21,520 --> 00:25:25,240 Speaker 1: these TikTok like platforms which do not monetize as well. 454 00:25:25,520 --> 00:25:28,600 Speaker 1: So they're making a choice. They're choosing, you know, copying 455 00:25:29,000 --> 00:25:32,320 Speaker 1: TikTok versus driving revenue. And on one hand, you can say, 456 00:25:32,320 --> 00:25:34,680 Speaker 1: well that that bodes ill, right, that that suggests they're 457 00:25:34,680 --> 00:25:37,040 Speaker 1: not monetizing. Well, on the other hand, it does look 458 00:25:37,080 --> 00:25:40,200 Speaker 1: like they're making progress in terms of this copycat approach. 459 00:25:40,440 --> 00:25:42,120 Speaker 1: And again I don't don't see any reason to think 460 00:25:42,160 --> 00:25:44,320 Speaker 1: that it won't work. It's worked, you know, many times 461 00:25:44,400 --> 00:25:47,120 Speaker 1: before in the history of this company. All right, great 462 00:25:47,160 --> 00:25:50,760 Speaker 1: piece by you, UM Bloomberg Business Week, Max Chafkin as 463 00:25:50,840 --> 00:25:54,080 Speaker 1: always great to have you come up. Bitcoin and coin 464 00:25:54,160 --> 00:25:57,159 Speaker 1: based both rallying is winter getting a little warmer? F 465 00:25:57,280 --> 00:26:00,440 Speaker 1: t x U S president Brett Harrison joins to weigh 466 00:26:00,440 --> 00:26:20,359 Speaker 1: in on that question. Next, this is Bloomberg coin Bay 467 00:26:20,440 --> 00:26:23,800 Speaker 1: shares rallied for a fifth straight day as investors continue 468 00:26:23,880 --> 00:26:27,440 Speaker 1: to pile into the largest US crypto exchange following news 469 00:26:27,480 --> 00:26:30,760 Speaker 1: of its partnership with black Rock to help institutional investors 470 00:26:30,840 --> 00:26:35,200 Speaker 1: manage and trade bitcoin. This as Bitcoin also rallying breaking 471 00:26:35,240 --> 00:26:39,680 Speaker 1: above the dollar mark. Welcome news for the crypto platform 472 00:26:39,720 --> 00:26:42,200 Speaker 1: ahead of its second quarter results after the close of 473 00:26:42,320 --> 00:26:45,760 Speaker 1: market later this week. Here to discuss what's happening this winter, 474 00:26:45,960 --> 00:26:47,359 Speaker 1: I want to bring in f t x U S 475 00:26:47,400 --> 00:26:50,200 Speaker 1: president Brett Harrison for his read on this and much 476 00:26:50,280 --> 00:26:52,720 Speaker 1: more so, what do you make of this coin based 477 00:26:52,800 --> 00:26:55,600 Speaker 1: black Rock news, Brett? So, it does seem to be 478 00:26:55,760 --> 00:26:59,320 Speaker 1: that the winter is starting to though here. Um, you know, 479 00:26:59,480 --> 00:27:01,720 Speaker 1: prices are obviously rising, and what's what are we actually 480 00:27:01,760 --> 00:27:04,800 Speaker 1: seeing here? A lot of these forced liquidations in the market, 481 00:27:04,920 --> 00:27:07,439 Speaker 1: they're start they're starting to come to an end. Um, 482 00:27:07,720 --> 00:27:11,840 Speaker 1: No more news about different either exchanges or lending platforms 483 00:27:11,880 --> 00:27:16,840 Speaker 1: going under, voyagers returning funds, large undeployed, bigger capital starting 484 00:27:16,880 --> 00:27:18,880 Speaker 1: to be deployed again. And then of course this news 485 00:27:18,920 --> 00:27:21,480 Speaker 1: coming out with coin base and with black Rock, showing 486 00:27:21,560 --> 00:27:24,680 Speaker 1: that the institutional demand to be able to trade crypto 487 00:27:25,040 --> 00:27:27,440 Speaker 1: through some of the more traditional huge players in the 488 00:27:27,480 --> 00:27:30,320 Speaker 1: market is not slowed down, and in fact, as the 489 00:27:30,400 --> 00:27:32,359 Speaker 1: saying goes that this is the time to build, people 490 00:27:32,359 --> 00:27:35,000 Speaker 1: are obviously building now, and as we start to come 491 00:27:35,040 --> 00:27:37,240 Speaker 1: out of this win term, people are trading again the 492 00:27:37,359 --> 00:27:39,159 Speaker 1: tools the capital will be in place to do so. 493 00:27:39,560 --> 00:27:41,639 Speaker 1: And of course all of this against the backdrop of 494 00:27:42,240 --> 00:27:46,280 Speaker 1: more progress in Congress uh Savan now Boosmen coming out 495 00:27:46,320 --> 00:27:49,000 Speaker 1: with their big crypto bill, a lot of positive signs 496 00:27:49,000 --> 00:27:52,880 Speaker 1: around that, all in bringing positive sentiment to crypto markets 497 00:27:52,920 --> 00:27:56,520 Speaker 1: and to the equity markets that are relating to crypto. Still, 498 00:27:56,560 --> 00:28:00,520 Speaker 1: you've got coin base and robin Hood slashing their head count. 499 00:28:01,119 --> 00:28:03,720 Speaker 1: What mistakes do you think these companies made when they 500 00:28:03,800 --> 00:28:07,960 Speaker 1: were scaling? You know, looking across the growth text sector, 501 00:28:08,080 --> 00:28:11,399 Speaker 1: there are so many companies talking about either layoffs or 502 00:28:11,520 --> 00:28:14,320 Speaker 1: hiring freezes. I mean everything from guest coin based in 503 00:28:14,400 --> 00:28:17,399 Speaker 1: robin Hood, but also Google and Microsoft and Tesla. I 504 00:28:17,480 --> 00:28:19,680 Speaker 1: think there's a real lesson learned here, which is that 505 00:28:20,440 --> 00:28:23,520 Speaker 1: these growth companies, which typically have operated under the model 506 00:28:23,600 --> 00:28:27,080 Speaker 1: that headcount growth is a sign of company growth, are 507 00:28:27,119 --> 00:28:29,800 Speaker 1: realizing that actually sometimes headcount growth can get in the 508 00:28:29,880 --> 00:28:32,840 Speaker 1: way of company growth. If you don't have a lean 509 00:28:32,960 --> 00:28:36,200 Speaker 1: staff where you can prioritize the most important buildouts, where 510 00:28:36,200 --> 00:28:38,160 Speaker 1: you can get things done, you can move nimbly. With 511 00:28:38,240 --> 00:28:41,040 Speaker 1: a market that moves extremely criply, like crypto, it's going 512 00:28:41,080 --> 00:28:43,080 Speaker 1: to be difficult to keep pace. And when there's a 513 00:28:43,120 --> 00:28:46,320 Speaker 1: winter and things are slowing down, retail volume is drying up, 514 00:28:46,680 --> 00:28:48,760 Speaker 1: and you have to focus on the most important things. 515 00:28:49,040 --> 00:28:51,480 Speaker 1: That means will have to pull back on those employees, 516 00:28:51,520 --> 00:28:54,760 Speaker 1: which can be devastating to build up this giant workforce, 517 00:28:55,000 --> 00:28:56,560 Speaker 1: and that have to lay those people off who have 518 00:28:56,640 --> 00:28:58,680 Speaker 1: worked so hard for their company. I mean, that's why 519 00:28:58,720 --> 00:29:00,840 Speaker 1: I think that companies like f t X, but of 520 00:29:00,920 --> 00:29:03,080 Speaker 1: course you're not the only company to do this. Showing 521 00:29:03,160 --> 00:29:05,200 Speaker 1: that you can operate with a leaner model, with a 522 00:29:05,240 --> 00:29:07,960 Speaker 1: smaller team and really be able to focus on the 523 00:29:08,040 --> 00:29:10,440 Speaker 1: highest priority items of all time and get things done 524 00:29:10,840 --> 00:29:12,800 Speaker 1: is super important for me. Be able to weather even 525 00:29:12,840 --> 00:29:16,320 Speaker 1: the downturns in the market. F t X has been 526 00:29:16,520 --> 00:29:19,600 Speaker 1: really inquisitive through this winter, and I wonder if winters 527 00:29:19,600 --> 00:29:22,760 Speaker 1: start starting to thaw, how does that impact your strategy 528 00:29:22,840 --> 00:29:26,200 Speaker 1: around deals. Do you expect valuations to stay low or 529 00:29:26,240 --> 00:29:31,680 Speaker 1: start to creep up. And could that mean less opportunities. Yeah, absolutely, 530 00:29:31,760 --> 00:29:33,960 Speaker 1: I mean, as you said, you know, during this past 531 00:29:34,080 --> 00:29:35,880 Speaker 1: let's say a couple of months, there have been a 532 00:29:35,920 --> 00:29:38,560 Speaker 1: lot of opportunities presented to us as far as potential 533 00:29:38,680 --> 00:29:41,480 Speaker 1: deals with you know, other companies that are looking for 534 00:29:41,640 --> 00:29:44,520 Speaker 1: capital injections. UM, they need help, you know, getting back 535 00:29:44,560 --> 00:29:48,280 Speaker 1: in business. There's possible merger opportunities, lower private equity valuations. 536 00:29:48,680 --> 00:29:51,960 Speaker 1: And yes, as as investor confidence starts to come back 537 00:29:51,960 --> 00:29:54,720 Speaker 1: into the sector, I mean those opportunities will start to 538 00:29:54,800 --> 00:29:57,040 Speaker 1: dry up as you know, these companies will start to 539 00:29:57,160 --> 00:29:59,640 Speaker 1: get their volumes back, they'll start to get revenue again. 540 00:30:00,000 --> 00:30:03,520 Speaker 1: Don't want to be able to increase their existing pipeline 541 00:30:03,520 --> 00:30:06,320 Speaker 1: of projects and capital in the same way they were before. Um. 542 00:30:06,400 --> 00:30:08,440 Speaker 1: But there's still plenty of opportunities in the market, and 543 00:30:08,560 --> 00:30:13,120 Speaker 1: certainly ones that we're looking at. Ft X is expanding. 544 00:30:13,160 --> 00:30:16,520 Speaker 1: It's no stock trading fee to all of its US users, 545 00:30:16,560 --> 00:30:19,960 Speaker 1: including non crypto investors. What's the end game here? Is 546 00:30:20,600 --> 00:30:23,400 Speaker 1: robin Hood a competitor or still a potential target for 547 00:30:23,880 --> 00:30:27,240 Speaker 1: some kind of stake. I mean, it's certainly the case 548 00:30:27,280 --> 00:30:29,280 Speaker 1: that they're a competitor. I mean, they've been a competitor 549 00:30:29,400 --> 00:30:31,840 Speaker 1: for a while when they started out in the stock 550 00:30:31,880 --> 00:30:34,320 Speaker 1: trading business and then they added crypto the odd of 551 00:30:34,320 --> 00:30:36,920 Speaker 1: the ability to trade bitcoin neither on their platform. They've 552 00:30:36,960 --> 00:30:39,000 Speaker 1: since been adding more and more assets. I think just 553 00:30:39,120 --> 00:30:43,400 Speaker 1: today they added Avalanche, and so they have realized that 554 00:30:43,440 --> 00:30:47,680 Speaker 1: their customer demand for retail crypto trading is incredible, and 555 00:30:47,960 --> 00:30:50,000 Speaker 1: so they've been a competitor ross for quite some time. 556 00:30:50,360 --> 00:30:53,000 Speaker 1: What we've realized is that we can do a great 557 00:30:53,080 --> 00:30:55,880 Speaker 1: job providing a stock trading platform to our users as well. 558 00:30:56,200 --> 00:30:58,680 Speaker 1: We can do so without relying on payment for order flow. 559 00:30:58,720 --> 00:31:01,320 Speaker 1: We can get people more advanced analytics and tools to 560 00:31:01,360 --> 00:31:03,880 Speaker 1: be able to make smarter investment decisions. We want to 561 00:31:03,960 --> 00:31:07,040 Speaker 1: make our platform more one that is involved with educating 562 00:31:07,080 --> 00:31:09,880 Speaker 1: our users and how to make um you know, how 563 00:31:09,920 --> 00:31:12,120 Speaker 1: to do trades in a responsible way as opposed to 564 00:31:12,200 --> 00:31:14,280 Speaker 1: being more kind of gamified. And so in that sense, 565 00:31:14,360 --> 00:31:15,920 Speaker 1: we think that we have a good shot at competing 566 00:31:15,960 --> 00:31:18,080 Speaker 1: with them on this platform, and we're pretty excited about 567 00:31:18,360 --> 00:31:21,080 Speaker 1: all of the initial user growth that we've seen in 568 00:31:21,160 --> 00:31:24,440 Speaker 1: trading stocks in f t x US. You've also, you know, 569 00:31:24,560 --> 00:31:27,440 Speaker 1: made a number of different sports partnerships your name is 570 00:31:27,480 --> 00:31:32,160 Speaker 1: on some arenas now partnership with Major League Baseball. How 571 00:31:32,280 --> 00:31:38,400 Speaker 1: much are these sports partnership sponsorships actually paying off. Yeah, 572 00:31:38,480 --> 00:31:41,920 Speaker 1: it's hard to put a quantification on that number of 573 00:31:42,000 --> 00:31:44,480 Speaker 1: exactly how much it's paid off. We think that from 574 00:31:44,480 --> 00:31:47,800 Speaker 1: a qualitative perspective, it's been tremendously important for our brand. 575 00:31:48,120 --> 00:31:51,440 Speaker 1: Think about that one year ago, almost no one in 576 00:31:51,520 --> 00:31:53,440 Speaker 1: the US had heard of f t x U S. 577 00:31:53,760 --> 00:31:57,040 Speaker 1: We were going up against you know, uh coin based 578 00:31:57,080 --> 00:31:59,320 Speaker 1: and Cracking and Gemini and different companies that have been 579 00:31:59,320 --> 00:32:01,760 Speaker 1: around for a day gade, and in an industry that 580 00:32:01,880 --> 00:32:05,720 Speaker 1: requires the trusts in your brands that cryptocurrency does. With 581 00:32:05,840 --> 00:32:08,600 Speaker 1: all the noise out there, with exchanges going down, with hacks, 582 00:32:08,720 --> 00:32:11,840 Speaker 1: with the scams, you have to establish that brand presence, 583 00:32:11,960 --> 00:32:15,200 Speaker 1: especially in the United States, and for us, doing things 584 00:32:15,280 --> 00:32:18,000 Speaker 1: like partnering with the major Major League Baseball or you know, 585 00:32:18,040 --> 00:32:20,960 Speaker 1: putting our name in the text arena basically catapulted us 586 00:32:21,040 --> 00:32:23,120 Speaker 1: into the public consciousness in a way that you know, 587 00:32:23,200 --> 00:32:26,040 Speaker 1: going to more traditional advertising routes such as Google ads 588 00:32:26,120 --> 00:32:28,360 Speaker 1: or Facebook ads wouldn't have been able to achieve in 589 00:32:28,440 --> 00:32:30,960 Speaker 1: such a short period of time. All Right, Brett Harrison 590 00:32:31,080 --> 00:32:33,120 Speaker 1: president of f t x U S always going to 591 00:32:33,160 --> 00:32:34,960 Speaker 1: have you, Brett. Thank you for Stoff and my hook. 592 00:32:43,760 --> 00:32:46,440 Speaker 1: As families ease into the back to school season throughout 593 00:32:46,440 --> 00:32:48,200 Speaker 1: the country, let's take a look at trends in the 594 00:32:48,280 --> 00:32:51,640 Speaker 1: world of education technology. Dual Lingo, for one b analyst 595 00:32:51,720 --> 00:32:54,680 Speaker 1: estimates during its second quarter earnings report last week even 596 00:32:54,800 --> 00:32:58,160 Speaker 1: boosted its revenue guidance for the year. I want to 597 00:32:58,200 --> 00:33:00,040 Speaker 1: talk about this and more with Dual Lingo C and 598 00:33:00,160 --> 00:33:03,520 Speaker 1: co founder Louise foun On. So going into a new 599 00:33:03,600 --> 00:33:06,920 Speaker 1: school year, Louise, is the pandemic boom has that been 600 00:33:07,000 --> 00:33:09,680 Speaker 1: keeping up or is it starting to wane? Well, you know, 601 00:33:09,760 --> 00:33:12,800 Speaker 1: the pandemic. The pandemic was interesting for us. It wasn't 602 00:33:13,080 --> 00:33:15,520 Speaker 1: a crazy boom. I mean, we we did benefit a 603 00:33:15,560 --> 00:33:17,320 Speaker 1: little bit from the pandemic, but we have been growing 604 00:33:17,400 --> 00:33:19,800 Speaker 1: steadily since before the pandemic. And you know a lot 605 00:33:19,800 --> 00:33:22,280 Speaker 1: of people have asked us if if afterwards our users 606 00:33:22,320 --> 00:33:24,040 Speaker 1: went down or anything, but we didn't see any of that, 607 00:33:24,160 --> 00:33:26,080 Speaker 1: And I think it's just because we you know, we 608 00:33:26,200 --> 00:33:27,840 Speaker 1: we have used this in every single country in the world, 609 00:33:28,040 --> 00:33:31,320 Speaker 1: and you know, in every associomic, the whole part of 610 00:33:31,360 --> 00:33:34,280 Speaker 1: the economic spectrum so what are the most interesting themes 611 00:33:34,320 --> 00:33:38,720 Speaker 1: going into this particular year. Now that schools generally have 612 00:33:38,920 --> 00:33:42,640 Speaker 1: been basically open for about a year since COVID. I 613 00:33:42,720 --> 00:33:44,640 Speaker 1: think one of the things that it's interesting is that 614 00:33:45,320 --> 00:33:48,800 Speaker 1: we schools in general have just adopted educational technology a 615 00:33:48,920 --> 00:33:51,360 Speaker 1: lot more, and we're going to continue seeing that. So 616 00:33:51,440 --> 00:33:53,320 Speaker 1: we're we're expecting a big back to school bump. We 617 00:33:53,440 --> 00:33:55,680 Speaker 1: usually get it around this year. You know, dual linguists. 618 00:33:55,800 --> 00:33:57,960 Speaker 1: It is used by about half of all schools in 619 00:33:58,000 --> 00:34:01,200 Speaker 1: the United States for teaching fore languages, and so we're 620 00:34:01,480 --> 00:34:04,400 Speaker 1: very excited about that. I think. I think generally educational 621 00:34:04,480 --> 00:34:07,040 Speaker 1: technology is just scariest thing. You've actually been leaning into 622 00:34:07,160 --> 00:34:09,600 Speaker 1: TikTok when it comes to add spend. Talk to us 623 00:34:09,640 --> 00:34:12,440 Speaker 1: a little bit about that and why, well, it's actually 624 00:34:12,520 --> 00:34:15,080 Speaker 1: not at spend. We we have been leading into TikTok. 625 00:34:15,120 --> 00:34:17,320 Speaker 1: But but it's all organic. I mean, really, the spend 626 00:34:17,320 --> 00:34:19,400 Speaker 1: that we have on our TikTok is really the salary 627 00:34:19,480 --> 00:34:22,120 Speaker 1: of of uh, you know, our our employees who who 628 00:34:22,160 --> 00:34:24,480 Speaker 1: run the account. We're blessed that we have a very 629 00:34:24,560 --> 00:34:27,279 Speaker 1: lovable mascot dual ing with the dual the owl, and 630 00:34:27,719 --> 00:34:30,120 Speaker 1: we make all these videos that that go viral. Um, 631 00:34:30,320 --> 00:34:33,200 Speaker 1: some of them have them, you know, are massbot dancing, etcetera. 632 00:34:33,320 --> 00:34:36,680 Speaker 1: So that's what felt really well for us. UM. You know, 633 00:34:36,960 --> 00:34:39,360 Speaker 1: it's approximately it's about ten percent of our users in 634 00:34:39,440 --> 00:34:42,400 Speaker 1: the US new users in the US come from from TikTok, 635 00:34:42,440 --> 00:34:44,600 Speaker 1: and it's it's been very efficient. I mean, again, the 636 00:34:45,120 --> 00:34:47,040 Speaker 1: main spend there is just the salary of a couple 637 00:34:47,080 --> 00:34:49,040 Speaker 1: of people that run it. Interesting because we were talking 638 00:34:49,080 --> 00:34:52,720 Speaker 1: about TikTok versus Facebook and Instagram earlier, and I'm curious 639 00:34:52,840 --> 00:34:56,399 Speaker 1: how you would assess the impact and power of both. 640 00:34:56,520 --> 00:34:59,719 Speaker 1: I mean, do you see TikTok as more powerful or 641 00:35:00,000 --> 00:35:03,000 Speaker 1: potentially a lot more powerful than the other two platforms. Well, 642 00:35:03,080 --> 00:35:05,880 Speaker 1: for us, TikTok has just been significantly more powerful. Um. 643 00:35:06,239 --> 00:35:08,000 Speaker 1: I mean I think I think some of it I 644 00:35:08,080 --> 00:35:09,520 Speaker 1: just has to do with the fact that that it's 645 00:35:09,680 --> 00:35:12,680 Speaker 1: on these days. It's kind of the cool thing. But 646 00:35:12,800 --> 00:35:17,040 Speaker 1: it's also you know, the algorithm really rewards content that 647 00:35:17,200 --> 00:35:18,920 Speaker 1: is that is enjoyable, and I think we've managed to 648 00:35:18,960 --> 00:35:22,919 Speaker 1: create very enjoyable kind of viral content that has worked 649 00:35:22,920 --> 00:35:24,960 Speaker 1: out very very well for us. To a Longo is 650 00:35:25,040 --> 00:35:27,960 Speaker 1: back in China's app stores after a one year hiatus 651 00:35:28,080 --> 00:35:30,920 Speaker 1: talked to us about the impact of the crackdown and 652 00:35:31,120 --> 00:35:34,080 Speaker 1: and how much did that set you back? Yeah, well, China. 653 00:35:34,280 --> 00:35:37,239 Speaker 1: China is a very interesting market for wellfore generally for 654 00:35:37,560 --> 00:35:40,000 Speaker 1: for everything, but for language learning. Is the largest language 655 00:35:40,080 --> 00:35:42,200 Speaker 1: learning market in the world. But for US, the Chinese 656 00:35:42,200 --> 00:35:44,239 Speaker 1: market has always been relatively small. It's only about one 657 00:35:44,280 --> 00:35:46,799 Speaker 1: percent of our our revenue and also of our daily 658 00:35:46,800 --> 00:35:50,520 Speaker 1: active users. About about nine months ago, so UM, we 659 00:35:50,719 --> 00:35:53,960 Speaker 1: got taken down from the app stores, which what it 660 00:35:54,040 --> 00:35:56,080 Speaker 1: meant is are all the users that already had to 661 00:35:56,080 --> 00:35:58,200 Speaker 1: do a lingual could continue using us, but new users 662 00:35:58,719 --> 00:36:01,600 Speaker 1: could not get in there. UM. And and you know, 663 00:36:01,600 --> 00:36:04,200 Speaker 1: about a month ago or so we were reinstated UH 664 00:36:04,360 --> 00:36:07,120 Speaker 1: and we started growing again. Um. And at this point 665 00:36:07,200 --> 00:36:09,400 Speaker 1: we're back to the traffic levels that we had before 666 00:36:09,640 --> 00:36:12,000 Speaker 1: we we got taken down. But for us, even though 667 00:36:12,040 --> 00:36:14,960 Speaker 1: it's it's it's a very interesting market. We also know 668 00:36:15,120 --> 00:36:18,799 Speaker 1: that Western companies UH usually don't do super well in China. 669 00:36:18,920 --> 00:36:21,200 Speaker 1: So um, you know, it's an interesting market, but but 670 00:36:21,280 --> 00:36:24,680 Speaker 1: it's only about one percent of our of our revenues. Now, 671 00:36:25,160 --> 00:36:27,439 Speaker 1: you know, we're no question we're facing a difficult macro 672 00:36:27,640 --> 00:36:31,520 Speaker 1: environment inflation. You know the R word we're hearing over 673 00:36:31,600 --> 00:36:35,839 Speaker 1: and over again. Sometimes it's you know, more impending than 674 00:36:36,120 --> 00:36:39,560 Speaker 1: than than not. Um, how are you expecting that to 675 00:36:39,719 --> 00:36:43,160 Speaker 1: impact your business and the at tech market in general? 676 00:36:43,640 --> 00:36:47,759 Speaker 1: Is this a discretionary market where you know, if companies 677 00:36:48,040 --> 00:36:52,399 Speaker 1: or customers are gonna have to choose, they'll spend less year. Um, well, 678 00:36:52,640 --> 00:36:54,960 Speaker 1: we haven't seen any kind of weakness in our numbers. 679 00:36:55,040 --> 00:36:56,920 Speaker 1: I mean we you know we we we beat our 680 00:36:56,960 --> 00:36:59,600 Speaker 1: our estimates, We increased our guidance for the quarter, and 681 00:36:59,840 --> 00:37:01,120 Speaker 1: I think some of it it just has to do 682 00:37:01,239 --> 00:37:03,640 Speaker 1: with the fact that we're still pretty early in our journey. 683 00:37:04,000 --> 00:37:06,440 Speaker 1: Language learning is a is a very large market. It's 684 00:37:06,440 --> 00:37:08,400 Speaker 1: about sixty billion dollars a year, but most of it 685 00:37:08,520 --> 00:37:11,080 Speaker 1: is still offline. So if you think about language and 686 00:37:11,080 --> 00:37:13,040 Speaker 1: the language learning market, most of it is kind of 687 00:37:13,320 --> 00:37:16,279 Speaker 1: people learning English in night school in Brazil or something 688 00:37:16,360 --> 00:37:19,400 Speaker 1: like that, and and it's shifting online like you know, 689 00:37:19,560 --> 00:37:22,279 Speaker 1: the way dating shifted online over the last twenty years. 690 00:37:22,360 --> 00:37:25,040 Speaker 1: Language learning is still kind of shifting online. So we're 691 00:37:25,080 --> 00:37:27,160 Speaker 1: still in the in the early parts of our growth 692 00:37:27,239 --> 00:37:29,200 Speaker 1: in terms of user growth and also in terms of 693 00:37:29,239 --> 00:37:32,040 Speaker 1: revenue growth. So so we just haven't seen any weakness 694 00:37:32,080 --> 00:37:34,600 Speaker 1: in our numbers. Um. You know the other thing about 695 00:37:34,680 --> 00:37:37,480 Speaker 1: is we have a freemium model where uh, you know, 696 00:37:37,600 --> 00:37:39,839 Speaker 1: people can learn as much as they want on dueling 697 00:37:40,040 --> 00:37:43,240 Speaker 1: entirely for free and then they can they can actually 698 00:37:43,320 --> 00:37:46,319 Speaker 1: turn turn off the ads if you know they pay. 699 00:37:46,760 --> 00:37:49,160 Speaker 1: So so far we just you know, this just hasn't 700 00:37:49,160 --> 00:37:52,640 Speaker 1: affected us at all. Interesting, all right, Weles found On 701 00:37:52,800 --> 00:37:54,880 Speaker 1: CEEO and co founder of Dual Lingo. Thank you so 702 00:37:55,000 --> 00:37:58,000 Speaker 1: much for joining us and giving a snapchat of what's 703 00:37:58,040 --> 00:38:00,520 Speaker 1: going on in your industry. That does it for this 704 00:38:00,719 --> 00:38:04,160 Speaker 1: edition of Bloomberg Technology. Later this week Tuesday, we've got 705 00:38:04,320 --> 00:38:07,400 Speaker 1: Lemonade CEO Daniel Schreiber with us to talk about their results, 706 00:38:07,520 --> 00:38:11,359 Speaker 1: plus how inflation is weighing on consumers. And don't forget 707 00:38:11,400 --> 00:38:14,440 Speaker 1: to check out our podcast wherever you get your podcasts. 708 00:38:14,440 --> 00:38:16,160 Speaker 1: I'm Emily Chang in San Francisco.