1 00:00:14,120 --> 00:00:18,320 Speaker 1: I'm Caroline Hyde up Bloomberg's San Francisco studio. Welcome for 2 00:00:18,480 --> 00:00:21,160 Speaker 1: New York. Together back in San Francisco and d Lovelow. 3 00:00:21,239 --> 00:00:23,959 Speaker 1: This is Bloomberg Technology and how nice it is to 4 00:00:24,000 --> 00:00:26,920 Speaker 1: have you here, so many headlines to pass over many 5 00:00:26,960 --> 00:00:29,000 Speaker 1: of the market moving when there's some feel good right 6 00:00:29,000 --> 00:00:31,760 Speaker 1: now around technology, despite layoffs, despite everything that's going on, 7 00:00:31,920 --> 00:00:34,800 Speaker 1: and it is centric to being in San Francisco this 8 00:00:34,800 --> 00:00:36,839 Speaker 1: week with all the earnings to come, first and foremost, 9 00:00:36,840 --> 00:00:39,680 Speaker 1: we talk about valuations here in Silicon Valley. Microsoft's ten 10 00:00:39,760 --> 00:00:42,560 Speaker 1: billion bet on open Ai is just the start of 11 00:00:42,560 --> 00:00:46,280 Speaker 1: the artificial intelligence revolution, is what Microsoft's chief product officer 12 00:00:46,400 --> 00:00:49,520 Speaker 1: is pitching as quote the defining technology of our time 13 00:00:49,920 --> 00:00:53,000 Speaker 1: and more local to us. Elliott's multibillion dollars stake in 14 00:00:53,120 --> 00:00:56,320 Speaker 1: sales Force comes as a way of the activist investors 15 00:00:56,360 --> 00:00:59,720 Speaker 1: pushed companies to act more on behalf of their shareholders. 16 00:01:00,120 --> 00:01:03,560 Speaker 1: And we now know what Apple's mixed reality headset is 17 00:01:03,600 --> 00:01:06,640 Speaker 1: capable of as a company explores a new approach to 18 00:01:06,840 --> 00:01:10,440 Speaker 1: eye and hand tracking controls. But first let's do it. 19 00:01:10,480 --> 00:01:13,080 Speaker 1: Let's get to how the focus on any investment management 20 00:01:13,080 --> 00:01:15,280 Speaker 1: has had us all eyes on the tower that is 21 00:01:15,319 --> 00:01:18,039 Speaker 1: here in San Francisco. Of course, what is Mark Benioff, 22 00:01:18,120 --> 00:01:20,720 Speaker 1: Where is his focus now? And what does the activist 23 00:01:20,760 --> 00:01:24,000 Speaker 1: Steake really mean for his business? Swooping in of course 24 00:01:24,040 --> 00:01:26,760 Speaker 1: after layoffs, after deep stop plunge at the enterprise software 25 00:01:26,760 --> 00:01:29,679 Speaker 1: giant mean Wes Leana Veka is more every New York Leanna, 26 00:01:29,959 --> 00:01:32,119 Speaker 1: As I sit here in San Francisco, and I think 27 00:01:32,480 --> 00:01:35,920 Speaker 1: of initially the worry Mimmi many had for Mark Benioff. 28 00:01:35,920 --> 00:01:39,600 Speaker 1: Perhaps as we've seen some of the other executives shed away, 29 00:01:39,880 --> 00:01:41,679 Speaker 1: many thought maybe that meant he was going to be 30 00:01:41,720 --> 00:01:44,640 Speaker 1: doing more dealmaking, spending more. But does an investor like 31 00:01:44,680 --> 00:01:47,880 Speaker 1: Elliott mean that's off the cards? At this point, we 32 00:01:47,880 --> 00:01:50,480 Speaker 1: don't know exactly what Elliott is pushing for, but we 33 00:01:50,600 --> 00:01:53,680 Speaker 1: have seen their public statement that was pretty complimentary of 34 00:01:53,760 --> 00:01:55,960 Speaker 1: Mark Bennioff, so it doesn't look like it'll be a 35 00:01:56,080 --> 00:02:00,200 Speaker 1: nasty fight. That said, Elliott Management has taken on so 36 00:02:00,360 --> 00:02:03,360 Speaker 1: many big tech companies over time that have made so 37 00:02:03,400 --> 00:02:06,160 Speaker 1: many changes, so there could really be a range of 38 00:02:06,200 --> 00:02:08,760 Speaker 1: things that they would like. I think ultimately they want 39 00:02:08,800 --> 00:02:11,079 Speaker 1: the stock to go up and that they believe there's 40 00:02:11,080 --> 00:02:15,440 Speaker 1: probably ways for shareholder value to be improved, you know, Leona, 41 00:02:16,840 --> 00:02:21,399 Speaker 1: this time around Salesforce, Elliot's name crosses the Bloomberg terminal monthly. 42 00:02:21,480 --> 00:02:24,639 Speaker 1: It seems to me, you know, the cadence of their investments, 43 00:02:24,639 --> 00:02:27,440 Speaker 1: what is their track record on working with companies? Because 44 00:02:27,480 --> 00:02:30,640 Speaker 1: you said you read the statement from the company deep 45 00:02:30,760 --> 00:02:33,560 Speaker 1: respect for Mark Bennioff was the word they used. It 46 00:02:33,600 --> 00:02:36,440 Speaker 1: doesn't seem hostile. It seems they want to work with 47 00:02:36,760 --> 00:02:39,440 Speaker 1: Mr Benioff over at Salesforce Tower. And one of the 48 00:02:39,480 --> 00:02:41,920 Speaker 1: reasons they might be wanting to work in a friendly 49 00:02:41,960 --> 00:02:44,480 Speaker 1: manner with the company is that I've been joking with 50 00:02:44,520 --> 00:02:48,960 Speaker 1: sources that Salesforce is now a hedge fund hotel. There's, uh, 51 00:02:49,080 --> 00:02:52,480 Speaker 1: you know, first there was Starboard, Now there's Elliott, Inclusive Capital, 52 00:02:52,800 --> 00:02:55,480 Speaker 1: Jeff Odden's firm. He used to be a value actors 53 00:02:55,480 --> 00:02:57,680 Speaker 1: in there. And then there's a mystery Activists that we're 54 00:02:57,680 --> 00:03:00,079 Speaker 1: trying to figure out. CNBC, you know, has report it 55 00:03:00,520 --> 00:03:03,240 Speaker 1: on that. So there might be a sense that maybe 56 00:03:03,280 --> 00:03:07,200 Speaker 1: Elliott's the White Knight activists to work with. In twenty nineteen, 57 00:03:07,400 --> 00:03:12,240 Speaker 1: eBay fell in the crosshairs of Elliott and also Starboard, 58 00:03:12,280 --> 00:03:14,680 Speaker 1: and they gave them both board seats. So That's another 59 00:03:14,840 --> 00:03:17,239 Speaker 1: example that we're kind of looking back in history to 60 00:03:17,280 --> 00:03:19,480 Speaker 1: see what could happen here. At this point, we don't 61 00:03:19,480 --> 00:03:22,120 Speaker 1: know if Salesforce is willing to offer those board seats, 62 00:03:22,120 --> 00:03:25,520 Speaker 1: but Jesse Cohen, who is the one leading the investment 63 00:03:25,520 --> 00:03:27,880 Speaker 1: for Ellie Management, he sat on some pretty big boards 64 00:03:29,320 --> 00:03:33,080 Speaker 1: and Leanna just put into perspective twenty twenty two, the 65 00:03:33,160 --> 00:03:36,840 Speaker 1: last quota, we saw so many more activist steaks really 66 00:03:36,880 --> 00:03:40,480 Speaker 1: being built globally worldwide. How many offenses are there? I 67 00:03:40,520 --> 00:03:43,080 Speaker 1: can already think of what Disney's outlet, Intel, how what 68 00:03:43,120 --> 00:03:46,000 Speaker 1: other companies? So you nailed it with Disney. That's kind 69 00:03:46,000 --> 00:03:49,000 Speaker 1: of the big one that the whole activist community is 70 00:03:49,040 --> 00:03:51,400 Speaker 1: watching because that looks like it's headed to an actual 71 00:03:51,440 --> 00:03:55,360 Speaker 1: shareholder vote at some point. Um Elliott doesn't usually get 72 00:03:55,400 --> 00:03:57,760 Speaker 1: to that shareholder vote, so I'd be surprised if that's 73 00:03:57,760 --> 00:04:01,040 Speaker 1: where Salesforce is headed. But right now we're entering this 74 00:04:01,160 --> 00:04:04,800 Speaker 1: what we call proxy season. These nomination windows are starting 75 00:04:04,800 --> 00:04:08,040 Speaker 1: to open at various companies, so we're seeing investors come 76 00:04:08,080 --> 00:04:11,040 Speaker 1: in and say, hey, we want to nominate shareholders. Salesforce's 77 00:04:11,080 --> 00:04:13,480 Speaker 1: window is coming up in February. We'll be watching that 78 00:04:13,560 --> 00:04:17,679 Speaker 1: really closely. All right, Bloomberg's the Aanna Baker who leads 79 00:04:17,680 --> 00:04:20,960 Speaker 1: our deals coverage investor coverage. Thank you so much, Caroline. 80 00:04:21,000 --> 00:04:23,960 Speaker 1: Welcome to San Francisco. If you jump in a cab acuet, 81 00:04:24,400 --> 00:04:28,560 Speaker 1: you go downtown whatever, no preference, but you'll see the 82 00:04:28,560 --> 00:04:30,720 Speaker 1: Salesforce tower. And this is what jumped out at me 83 00:04:30,720 --> 00:04:34,400 Speaker 1: on the Bloomberg terminal earlier, this single chart about salesforces 84 00:04:34,520 --> 00:04:37,679 Speaker 1: marketing spend as a percentage of its sales. You start 85 00:04:37,720 --> 00:04:40,840 Speaker 1: to realize what it is that investors, activists, investors might 86 00:04:40,880 --> 00:04:45,360 Speaker 1: be getting at. They're almost at fifty right of their 87 00:04:45,480 --> 00:04:49,080 Speaker 1: their sales spend being on marketing, which is kind of 88 00:04:49,320 --> 00:04:53,440 Speaker 1: mind blowing a little bit, right, But then they have potential. 89 00:04:53,560 --> 00:04:56,640 Speaker 1: You know, this is a software company margins it also 90 00:04:56,680 --> 00:04:58,880 Speaker 1: though that spend as largs you were on dream Force. 91 00:04:58,960 --> 00:05:00,840 Speaker 1: I think the last time we was. Lenny Kravitz is 92 00:05:00,880 --> 00:05:04,080 Speaker 1: performing there. These big parties. Basically it's a massive music festival. 93 00:05:04,120 --> 00:05:07,320 Speaker 1: It does a lot for the San Francisco ecosystem as well. 94 00:05:07,360 --> 00:05:10,560 Speaker 1: Those sorts of events they bring people to gatherings, which 95 00:05:10,560 --> 00:05:12,240 Speaker 1: are a city that they're really taking on the road 96 00:05:12,279 --> 00:05:15,080 Speaker 1: to the marketing spenders about being in people and in 97 00:05:15,160 --> 00:05:17,920 Speaker 1: person and sharing ideas. But they're probably going to want 98 00:05:17,960 --> 00:05:19,360 Speaker 1: him to pull back on that. And this is a 99 00:05:19,360 --> 00:05:20,880 Speaker 1: company that has had to pull off on the on 100 00:05:20,880 --> 00:05:24,039 Speaker 1: the layoffs front, you know, in pausing her in other areas, 101 00:05:24,080 --> 00:05:26,480 Speaker 1: and where M and A has been just absolutely right. 102 00:05:26,560 --> 00:05:28,160 Speaker 1: The other big story we're watching here out on the 103 00:05:28,200 --> 00:05:31,200 Speaker 1: West Coast is, of course, Microsoft and open Ai are 104 00:05:31,279 --> 00:05:34,880 Speaker 1: reported ten billion dollar investments set over a number of years, 105 00:05:35,200 --> 00:05:38,919 Speaker 1: which open Aron Microsoft have now confirmed sort of in 106 00:05:38,960 --> 00:05:43,080 Speaker 1: a blog, the company saying Microsoft will involve invest multiple 107 00:05:43,160 --> 00:05:45,479 Speaker 1: billions of dollars. Remember, this is a company that mass 108 00:05:45,560 --> 00:05:48,080 Speaker 1: more than a million users just within days of launch 109 00:05:48,400 --> 00:05:52,040 Speaker 1: back in November, and we've already started the debate where 110 00:05:52,040 --> 00:05:54,040 Speaker 1: does this all fit in with Microsoft strategy? Where does 111 00:05:54,040 --> 00:05:56,560 Speaker 1: it fit in our lives? The use of chat, GPT 112 00:05:56,680 --> 00:05:59,279 Speaker 1: and other AI tours a fascinating one, and also how 113 00:05:59,320 --> 00:06:02,240 Speaker 1: does this help soft gain market share from the likes 114 00:06:02,400 --> 00:06:05,440 Speaker 1: of aws. Now we know that Amazon is the power 115 00:06:05,480 --> 00:06:07,880 Speaker 1: player when it comes to the cloud provision. Overall the 116 00:06:07,920 --> 00:06:11,040 Speaker 1: fact that Microsoft wants to intertwine open Ai into every 117 00:06:11,960 --> 00:06:13,960 Speaker 1: really every part of Azure the business it wants to 118 00:06:14,000 --> 00:06:17,080 Speaker 1: set itself apart as a cloud offering, and open Eye 119 00:06:17,080 --> 00:06:18,880 Speaker 1: is such a clever way to do it. What's so interesting, 120 00:06:18,960 --> 00:06:20,880 Speaker 1: of course, is the open Eye once upon a time 121 00:06:20,960 --> 00:06:24,560 Speaker 1: was an off profit, now as a capped profit right company. 122 00:06:24,720 --> 00:06:27,120 Speaker 1: So this deal, there's ten million that's being invested. It's 123 00:06:27,160 --> 00:06:29,320 Speaker 1: kind of awkwardly done, isn't it, because you're kind of 124 00:06:29,320 --> 00:06:33,560 Speaker 1: being it's offering in kind. Basically open ai is able 125 00:06:33,680 --> 00:06:37,760 Speaker 1: to use the firepower of Microsoft's own cloud provisions, so 126 00:06:37,880 --> 00:06:41,240 Speaker 1: so it's a really significant investment from Microsoft seven days 127 00:06:41,400 --> 00:06:44,919 Speaker 1: after they have laid off ten thousand staff. But the 128 00:06:44,920 --> 00:06:47,640 Speaker 1: closed profit model is where basically any money that open 129 00:06:47,680 --> 00:06:51,280 Speaker 1: Ai mates, which is by licensing the tools to software developers, 130 00:06:51,320 --> 00:06:53,840 Speaker 1: they put back straight into the development because they still 131 00:06:53,839 --> 00:06:56,560 Speaker 1: feel like it's in the nascent stage, after they've paid investors, 132 00:06:56,640 --> 00:06:58,960 Speaker 1: after they've paid their dus, and after they pay their 133 00:06:58,960 --> 00:07:01,279 Speaker 1: own employees. Right, yeah, I mean, we've been trying to 134 00:07:01,320 --> 00:07:03,920 Speaker 1: identify what is the next big company for the next decade, 135 00:07:03,960 --> 00:07:06,320 Speaker 1: the next twenty years. You know, there's a lot of 136 00:07:06,800 --> 00:07:09,960 Speaker 1: debate whether actually open ai is it, and the emphasis 137 00:07:09,960 --> 00:07:11,720 Speaker 1: of them in the news cycles amazing, And you're right, 138 00:07:12,200 --> 00:07:15,120 Speaker 1: Microsoft are already implementing this and as you're cloud for customers. 139 00:07:15,160 --> 00:07:18,200 Speaker 1: You can use chat GPT or even dally on the 140 00:07:18,200 --> 00:07:20,200 Speaker 1: imaging side, So it's out there in the real world. 141 00:07:20,200 --> 00:07:22,400 Speaker 1: You and I have played with it to a lesser extent, 142 00:07:22,960 --> 00:07:26,320 Speaker 1: you know here on the show. But interesting a lot 143 00:07:26,320 --> 00:07:29,520 Speaker 1: of cash math on chat GPT. That was my learning, 144 00:07:29,560 --> 00:07:32,040 Speaker 1: my podcast learning over the course of the weekend. And 145 00:07:32,120 --> 00:07:33,760 Speaker 1: I can't tell you how nice it's about in San 146 00:07:33,760 --> 00:07:37,040 Speaker 1: Francisco known fat that chat GPT wouldn't tell you about 147 00:07:37,080 --> 00:07:40,280 Speaker 1: my family. My son's middle name is Francisco. That's how 148 00:07:40,320 --> 00:07:43,160 Speaker 1: much the city. Because of your time here, well, let's 149 00:07:43,200 --> 00:07:53,160 Speaker 1: make the most of it while you're here. We've might 150 00:07:53,200 --> 00:07:55,360 Speaker 1: have been positive. I'm big deck for I don't know 151 00:07:55,440 --> 00:07:57,520 Speaker 1: a year, a year and a half. We do believe 152 00:07:57,520 --> 00:08:00,200 Speaker 1: that there is still some deflation to come out of 153 00:08:00,200 --> 00:08:03,760 Speaker 1: this market after the exube. I actually think that the 154 00:08:03,800 --> 00:08:06,480 Speaker 1: tech sector is one of the few sectors that is 155 00:08:06,560 --> 00:08:10,040 Speaker 1: really discounting a recession in its outlook. And the longer 156 00:08:10,120 --> 00:08:13,600 Speaker 1: the macro volatilely persists, we do expect early stage and 157 00:08:13,720 --> 00:08:16,040 Speaker 1: seed to start to see that crunch that the late 158 00:08:16,080 --> 00:08:18,160 Speaker 1: stages you see right now, there is going to be 159 00:08:18,200 --> 00:08:22,280 Speaker 1: some amount of normalization of the demand. Uh well, frankly, 160 00:08:22,280 --> 00:08:24,920 Speaker 1: we in the tech industry will also have to get efficient, right. 161 00:08:24,960 --> 00:08:27,480 Speaker 1: It's not about everyone else doing more with less. We 162 00:08:27,520 --> 00:08:31,080 Speaker 1: will have to do more with less. There was just 163 00:08:31,160 --> 00:08:34,360 Speaker 1: some of our recent guests discussing the state of the 164 00:08:34,400 --> 00:08:38,960 Speaker 1: tech sector. And another week, another day, more headlines all 165 00:08:39,000 --> 00:08:42,000 Speaker 1: to do with layoffs. This Monday, Spotify six percent of 166 00:08:42,000 --> 00:08:44,280 Speaker 1: staff six dred and then just as we were getting 167 00:08:44,280 --> 00:08:46,920 Speaker 1: ready for the show, Gemini a second round of ten 168 00:08:46,960 --> 00:08:52,240 Speaker 1: percent and just keeps going un relenting. Really feels like 169 00:08:52,280 --> 00:08:55,320 Speaker 1: the numbers that are coming out ten percent smaller amount 170 00:08:55,320 --> 00:08:57,920 Speaker 1: for Gemini, of course, a sixth cent number layoff over 171 00:08:58,000 --> 00:08:59,800 Speaker 1: Spotify I means six thousand people are going to be 172 00:08:59,800 --> 00:09:03,560 Speaker 1: going this vote again. It's about a CEO trying to 173 00:09:03,600 --> 00:09:06,880 Speaker 1: own the mistakes made, basically saying his words were I 174 00:09:06,920 --> 00:09:08,960 Speaker 1: was too ambitious. They put out a note from Daniel 175 00:09:09,240 --> 00:09:12,160 Speaker 1: talking about the fact that they once again hired too 176 00:09:12,200 --> 00:09:15,120 Speaker 1: many but also invested too far perhaps and the fact 177 00:09:15,160 --> 00:09:17,839 Speaker 1: that the executive changes going on at Spotify they want 178 00:09:17,840 --> 00:09:20,000 Speaker 1: to have more efficiency. That is the watchword. There's a 179 00:09:20,000 --> 00:09:22,720 Speaker 1: debate of how much embassis you put on layoffs announced 180 00:09:22,880 --> 00:09:24,679 Speaker 1: versus laos and acted you know, we have the Challenger 181 00:09:24,760 --> 00:09:27,679 Speaker 1: Christmas data and people say, well, those are just announcements, 182 00:09:27,679 --> 00:09:29,480 Speaker 1: they're not fulfilled. And there are others out there in 183 00:09:29,480 --> 00:09:33,400 Speaker 1: the market who say there's bright spots here. And that's 184 00:09:33,400 --> 00:09:36,160 Speaker 1: why I'm delighted to say we can discuss with Spencer Green, 185 00:09:36,240 --> 00:09:40,320 Speaker 1: managing partner at t s VC, which actually is invested 186 00:09:40,360 --> 00:09:42,360 Speaker 1: in C state companies over the last twelve years. A 187 00:09:42,360 --> 00:09:46,079 Speaker 1: good example, you invested in Zoom eleven before they were 188 00:09:46,080 --> 00:09:49,040 Speaker 1: even had a product, really, you know, and that was 189 00:09:49,120 --> 00:09:53,040 Speaker 1: coming out of a financial crisis or downturn. When you 190 00:09:53,120 --> 00:09:56,640 Speaker 1: see these headlines crossing the Bloombog terminal time and time again, 191 00:09:56,679 --> 00:10:01,760 Speaker 1: Spotify six the latest as somebody who invests in companies 192 00:10:01,800 --> 00:10:05,199 Speaker 1: that actually may still be trying to hire. What's your reaction, Well, 193 00:10:05,240 --> 00:10:07,679 Speaker 1: I mean, nobody roots for a recession, but it's definitely 194 00:10:07,760 --> 00:10:11,000 Speaker 1: good for the seed stage economy. Um, the seed I 195 00:10:11,040 --> 00:10:13,839 Speaker 1: mean you heard, you know, one of your your prior 196 00:10:13,880 --> 00:10:16,600 Speaker 1: guests talking about a crunch and seed we see the opposite. 197 00:10:16,640 --> 00:10:20,640 Speaker 1: We see that brand new company formations are booming and 198 00:10:20,760 --> 00:10:23,319 Speaker 1: it's become much easier to hire staff, to hire staff, 199 00:10:23,320 --> 00:10:26,040 Speaker 1: to hire talent. Um. We had a year ago, what 200 00:10:26,080 --> 00:10:28,880 Speaker 1: I would call it double whammy that it was hard 201 00:10:28,880 --> 00:10:31,520 Speaker 1: to hire people, and also these big companies were investing 202 00:10:31,559 --> 00:10:34,720 Speaker 1: in some of these innovative projects. As they cut their investments, 203 00:10:34,720 --> 00:10:37,280 Speaker 1: they leave room for competitors and they put more talent 204 00:10:37,320 --> 00:10:39,120 Speaker 1: on the street spent. So we delight to have you 205 00:10:39,120 --> 00:10:41,240 Speaker 1: in the studio, Caroline and I while we're together in 206 00:10:41,280 --> 00:10:44,760 Speaker 1: San Francisco. It feels like the story is not just 207 00:10:44,800 --> 00:10:46,440 Speaker 1: playing out here. But the reason you hear is, I 208 00:10:46,440 --> 00:10:49,079 Speaker 1: tweeted over the weekend, hold on, is there anyone that's 209 00:10:49,120 --> 00:10:50,920 Speaker 1: kind of actively trying to go out there and hire 210 00:10:50,960 --> 00:10:53,559 Speaker 1: all these people? Because we do hear that, but we're 211 00:10:53,559 --> 00:10:56,199 Speaker 1: looking for some concrete evidence that it's true. I mean, 212 00:10:56,240 --> 00:10:59,000 Speaker 1: are you saying to your portfolio companies, Hey, now's a 213 00:10:59,000 --> 00:11:01,480 Speaker 1: great chance to get top to absolutely. And we have 214 00:11:01,520 --> 00:11:03,959 Speaker 1: portfolio companies. We have one here in San Francisco called 215 00:11:04,040 --> 00:11:07,360 Speaker 1: Zoom Transportation that runs electric school bus services for San 216 00:11:07,400 --> 00:11:10,520 Speaker 1: Francisco and for Oakland and for Los Angeles and so forth. 217 00:11:10,880 --> 00:11:13,280 Speaker 1: They're hiring. We have a recent company we funded called 218 00:11:13,320 --> 00:11:18,400 Speaker 1: Ebots that does assembly robots for electronics. They're hiring. Angle 219 00:11:18,440 --> 00:11:21,040 Speaker 1: Health is hiring. You know, lots of our portfolio companies 220 00:11:21,040 --> 00:11:24,160 Speaker 1: are hiring and a year ago it was much more 221 00:11:24,160 --> 00:11:27,079 Speaker 1: difficult for them. It's interesting, and I suppose in many 222 00:11:27,080 --> 00:11:30,319 Speaker 1: ways this is why the relentless headlines that we talk 223 00:11:30,360 --> 00:11:32,840 Speaker 1: about the hundred tens of thousands being let go at 224 00:11:32,880 --> 00:11:35,200 Speaker 1: Metro and they're like on't showing up in the federal 225 00:11:35,280 --> 00:11:38,880 Speaker 1: data because many would say anninkdotally, they're snapped up very quickly. 226 00:11:38,880 --> 00:11:40,720 Speaker 1: They get great severance and then they move on either 227 00:11:40,760 --> 00:11:43,280 Speaker 1: to be become a talent at Zoom one of your 228 00:11:43,320 --> 00:11:46,720 Speaker 1: new ventures and the transport company, or are they becoming 229 00:11:46,800 --> 00:11:49,800 Speaker 1: entrepreneurs themselves and yet to see any sort of charts 230 00:11:49,840 --> 00:11:52,319 Speaker 1: on new business formation. Are you starting to hear from 231 00:11:52,360 --> 00:11:55,960 Speaker 1: these people getting great severance packages. I know they probably 232 00:11:55,960 --> 00:11:58,200 Speaker 1: want to remain at a company and employed, but if 233 00:11:58,240 --> 00:11:59,760 Speaker 1: they are let go, are they willing to take on 234 00:11:59,800 --> 00:12:02,079 Speaker 1: a can build something? You know, It's it's a huge 235 00:12:02,080 --> 00:12:05,600 Speaker 1: point and I think it's definitely fueling a lot of 236 00:12:05,600 --> 00:12:08,360 Speaker 1: the entrepreneurial activity because what you have is, you know, 237 00:12:08,440 --> 00:12:10,120 Speaker 1: as you said, folks who maybe have a little bit 238 00:12:10,120 --> 00:12:12,679 Speaker 1: of money, they've gotten a severance, they've been doing very 239 00:12:12,720 --> 00:12:14,880 Speaker 1: well over the last few years working for these larger 240 00:12:14,920 --> 00:12:18,120 Speaker 1: companies and in some cases, you know, the Silicon Valley 241 00:12:18,320 --> 00:12:21,719 Speaker 1: spree and what's happening in San Francisco has always I mean, 242 00:12:22,280 --> 00:12:24,240 Speaker 1: so many people that you meet here they have another 243 00:12:24,280 --> 00:12:26,840 Speaker 1: startup going on on the side, right, So there are 244 00:12:26,840 --> 00:12:28,480 Speaker 1: people who are and so if you think about, like 245 00:12:28,520 --> 00:12:30,680 Speaker 1: who's going to get laid off some of these people, 246 00:12:30,800 --> 00:12:33,040 Speaker 1: maybe you were not rated as the best employees by 247 00:12:33,040 --> 00:12:35,760 Speaker 1: their big company employers because they were giving half of 248 00:12:35,800 --> 00:12:37,520 Speaker 1: their time to the company and half of the time 249 00:12:37,520 --> 00:12:40,120 Speaker 1: to their startup. So now you say, well, I've got 250 00:12:40,160 --> 00:12:42,360 Speaker 1: a little extra cash, I've got all my day free 251 00:12:42,360 --> 00:12:45,800 Speaker 1: to work on my startup. Not a bad situation. Is 252 00:12:45,840 --> 00:12:49,480 Speaker 1: there an element that you're seeing this worldwide? This is 253 00:12:49,600 --> 00:12:52,760 Speaker 1: very much where are the talent that you're currently hiring 254 00:12:52,920 --> 00:12:55,959 Speaker 1: and seeing hiring from? Do people want to remain remote? 255 00:12:55,960 --> 00:12:57,920 Speaker 1: Are you seeing some of your startups that are SF 256 00:12:58,000 --> 00:13:00,920 Speaker 1: based hiring talent for being let go in Austin Miami? 257 00:13:01,240 --> 00:13:03,160 Speaker 1: Where is this all going on at the moment? It 258 00:13:03,320 --> 00:13:05,080 Speaker 1: is much more remote than what it used to be. 259 00:13:05,240 --> 00:13:06,600 Speaker 1: You know, we we've been in you know, I've been 260 00:13:06,640 --> 00:13:10,640 Speaker 1: in Silicon Valley since the nineties and it was definitely 261 00:13:10,679 --> 00:13:14,319 Speaker 1: you know, you'd set up a facility, everybody would come there. Um, 262 00:13:14,360 --> 00:13:16,680 Speaker 1: you even had, of course, you know, companies like Facebook 263 00:13:16,679 --> 00:13:19,640 Speaker 1: where they were relocated by their investors to Silicon Valley 264 00:13:19,679 --> 00:13:22,040 Speaker 1: because the story was, oh, yeah, we love you, but 265 00:13:22,160 --> 00:13:24,679 Speaker 1: you can't do it from where you are. It's not 266 00:13:24,760 --> 00:13:27,319 Speaker 1: so much a destination for companies. I think a lot 267 00:13:27,360 --> 00:13:31,079 Speaker 1: of companies are formed here still, and the companies that 268 00:13:31,120 --> 00:13:33,720 Speaker 1: are formed here have done so much more with remote talent, 269 00:13:33,920 --> 00:13:35,800 Speaker 1: and some of it's offshore. More of it now is 270 00:13:35,800 --> 00:13:39,080 Speaker 1: actually on shore, but outside of the area. The conversation 271 00:13:39,120 --> 00:13:42,600 Speaker 1: that Caroline keep having is that across the startup curve, 272 00:13:43,280 --> 00:13:46,760 Speaker 1: the opportunity of three is going to be seed stage, 273 00:13:46,800 --> 00:13:50,600 Speaker 1: earlier stage investments, and actually it's the growth stage funds 274 00:13:50,720 --> 00:13:52,600 Speaker 1: keeping their power to dry even though they raised all 275 00:13:52,640 --> 00:13:55,360 Speaker 1: that capital over the last two years. Is that a 276 00:13:55,400 --> 00:13:59,240 Speaker 1: fair interpretation of where the industry sits. Certainly? I think 277 00:13:59,280 --> 00:14:01,720 Speaker 1: something it ts. You see, we do seed stage primarily, 278 00:14:01,760 --> 00:14:03,839 Speaker 1: and we feel like the markets coming to us because 279 00:14:03,840 --> 00:14:06,320 Speaker 1: they need. Um. Well, the market is coming to us 280 00:14:06,320 --> 00:14:07,920 Speaker 1: in the sense that it's just hard to make money 281 00:14:07,920 --> 00:14:10,040 Speaker 1: at late stage right now. Um, if you have a 282 00:14:10,080 --> 00:14:12,840 Speaker 1: company that was overfunded at too high of evaluation a 283 00:14:12,880 --> 00:14:15,640 Speaker 1: year or two ago. Yes, you can do a down round, 284 00:14:15,720 --> 00:14:18,560 Speaker 1: you can get a better price, but then the employees 285 00:14:18,600 --> 00:14:21,240 Speaker 1: are not happy, so you lose momentum in the business. 286 00:14:21,320 --> 00:14:24,800 Speaker 1: So even though you might normalize or rationalize the pricing 287 00:14:24,800 --> 00:14:26,840 Speaker 1: of the company, that doesn't mean that it's going to 288 00:14:26,920 --> 00:14:28,760 Speaker 1: take off and be successful. So I would hate to 289 00:14:28,760 --> 00:14:30,760 Speaker 1: be writing Hunter million dollar checks right now. I think 290 00:14:30,760 --> 00:14:34,040 Speaker 1: it's it's a difficult time. We write a million dollar 291 00:14:34,120 --> 00:14:36,640 Speaker 1: checks into early companies and you think about something like Zoom. 292 00:14:36,640 --> 00:14:38,440 Speaker 1: There's a photograph which I wish I had with us, 293 00:14:38,480 --> 00:14:41,720 Speaker 1: but photograph of the of the assume founder er qu 294 00:14:41,920 --> 00:14:45,040 Speaker 1: N two engineers in our offices in two thousand eleven. 295 00:14:45,600 --> 00:14:48,520 Speaker 1: That was the company. It was himself and two engineers 296 00:14:48,520 --> 00:14:53,000 Speaker 1: a power point deck. Right, fantastic ambitions. Um, those are 297 00:14:53,000 --> 00:14:54,840 Speaker 1: the kinds of folks that we're funding right now. Tweet 298 00:14:54,880 --> 00:14:57,400 Speaker 1: ask off to the show you when you've done Absolutely yeah, 299 00:14:57,560 --> 00:15:00,280 Speaker 1: and Ginko Bio Works and and Cata they I haven't 300 00:15:00,280 --> 00:15:03,560 Speaker 1: been a one trick plony TSPC managing partner. He's a 301 00:15:03,600 --> 00:15:06,040 Speaker 1: coal spencer green. What joy having him right here in 302 00:15:06,080 --> 00:15:07,760 Speaker 1: the studio with us. Nice tweeting from you had to 303 00:15:07,760 --> 00:15:10,480 Speaker 1: get him on as well, meanwhile, coming up Apple's headset, 304 00:15:10,760 --> 00:15:13,720 Speaker 1: it's going to be controlled by your hands, by your eyes. 305 00:15:14,080 --> 00:15:16,240 Speaker 1: More details on the mixed reality device next, and it's 306 00:15:16,280 --> 00:15:28,160 Speaker 1: price point. Li's a Blien Bug New Day, New Week 307 00:15:28,160 --> 00:15:30,040 Speaker 1: News scoop for one Mark Gum and let's talk about 308 00:15:30,040 --> 00:15:32,880 Speaker 1: new details that are out about the highly anticipated three 309 00:15:33,000 --> 00:15:36,440 Speaker 1: thousand dollar mixed reality headset by Apple. Of course, it's 310 00:15:36,440 --> 00:15:39,520 Speaker 1: according to sources, which boast an eye and a hand 311 00:15:39,520 --> 00:15:42,760 Speaker 1: tracking system that could set the technology pretty much apart 312 00:15:42,760 --> 00:15:45,440 Speaker 1: from rivals. Right, Mark, you've got this new story and 313 00:15:45,480 --> 00:15:47,840 Speaker 1: just tell us about how this one's going to be 314 00:15:47,840 --> 00:15:50,560 Speaker 1: different from the other ones in the market. Yeah, that's 315 00:15:50,560 --> 00:15:53,040 Speaker 1: exactly right. So this is Apple's next big thing. They've 316 00:15:53,040 --> 00:15:55,120 Speaker 1: been working on it for north of seven years. At 317 00:15:55,120 --> 00:15:59,440 Speaker 1: this point. They have well over engineers on the project. 318 00:15:59,520 --> 00:16:01,480 Speaker 1: They're getting ready to unveil it in the next couple 319 00:16:01,520 --> 00:16:04,040 Speaker 1: of months and put on sale later this year. The 320 00:16:04,080 --> 00:16:06,400 Speaker 1: factories are going to start churning them out starting at 321 00:16:06,400 --> 00:16:08,800 Speaker 1: the end of next month in China. But the eye 322 00:16:08,880 --> 00:16:11,720 Speaker 1: in hand control, right, some devices on the market area 323 00:16:11,720 --> 00:16:14,320 Speaker 1: now already can read your eyes and have hand control, 324 00:16:14,800 --> 00:16:17,400 Speaker 1: but with Apple's device, it's the way they work together. 325 00:16:17,520 --> 00:16:20,000 Speaker 1: That makes it so special. If you remember the touch 326 00:16:20,040 --> 00:16:22,880 Speaker 1: screen on the first iPhone, that was a big differentiator, 327 00:16:22,920 --> 00:16:25,240 Speaker 1: the crown on the watch. For this, it's eye in 328 00:16:25,280 --> 00:16:27,040 Speaker 1: hand control. So let me give you an example. The 329 00:16:27,080 --> 00:16:29,120 Speaker 1: way you control the device is you can just look 330 00:16:29,160 --> 00:16:31,560 Speaker 1: at something, whether you want to launch an app, whether 331 00:16:31,600 --> 00:16:34,400 Speaker 1: you want to swipe through a list or toggle a setting. Right, 332 00:16:34,680 --> 00:16:37,840 Speaker 1: you look at it and then you pinch your thumb 333 00:16:37,840 --> 00:16:40,760 Speaker 1: and your index finger together when you're looking at it 334 00:16:40,800 --> 00:16:43,840 Speaker 1: to launch it. Just like on a touch screen you 335 00:16:43,880 --> 00:16:46,280 Speaker 1: tap what you want or on a mouse, you point 336 00:16:46,320 --> 00:16:48,520 Speaker 1: the cursor toward it and then you click. This is 337 00:16:48,560 --> 00:16:53,520 Speaker 1: you look and tap your fingers together. So pretty nifty. 338 00:16:53,960 --> 00:16:55,280 Speaker 1: I guess. The question is how do we get to 339 00:16:55,320 --> 00:16:57,200 Speaker 1: a three thousands of the price point? Right? How does 340 00:16:57,240 --> 00:17:01,360 Speaker 1: this headset differentiates itself from metas quest? The other real 341 00:17:01,400 --> 00:17:03,200 Speaker 1: question I have to you is like, as an iPhone 342 00:17:03,280 --> 00:17:06,760 Speaker 1: user and thinking about emoji or emojis and and emojis 343 00:17:06,800 --> 00:17:08,640 Speaker 1: right where you use the camera to kind of map 344 00:17:08,680 --> 00:17:11,320 Speaker 1: your face and interact with that technology. Is this the 345 00:17:11,359 --> 00:17:14,639 Speaker 1: kind of extension of that. Yes. So in terms of 346 00:17:14,640 --> 00:17:17,280 Speaker 1: the price point, well, it has fourteen cameras, right, you 347 00:17:17,359 --> 00:17:20,000 Speaker 1: have a bunch of cameras outside. You need cameras that 348 00:17:20,000 --> 00:17:21,760 Speaker 1: can look forward, you need cameras that can look up, 349 00:17:21,760 --> 00:17:24,520 Speaker 1: and need cameras that could look down, right down to 350 00:17:24,560 --> 00:17:26,680 Speaker 1: see what your legs look like and what your body 351 00:17:26,760 --> 00:17:28,960 Speaker 1: looks like in order to recreate what you look like 352 00:17:29,000 --> 00:17:32,600 Speaker 1: in virtual reality. For that feature you alluded to in FaceTime, 353 00:17:32,800 --> 00:17:35,159 Speaker 1: there's also cameras and sensors inside the device to be 354 00:17:35,200 --> 00:17:37,800 Speaker 1: able to read where your eyes are looking at. In addition, 355 00:17:37,840 --> 00:17:40,160 Speaker 1: there's two four K displays, right you know the four 356 00:17:40,240 --> 00:17:42,680 Speaker 1: KTV you have maybe in your living room. Well, there's 357 00:17:42,720 --> 00:17:46,520 Speaker 1: two of them, many ones inside of the headset to 358 00:17:46,720 --> 00:17:50,200 Speaker 1: perform virtual reality. The cameras also, in addition to being 359 00:17:50,240 --> 00:17:52,920 Speaker 1: sensors to see what everything looks like, it's a way 360 00:17:52,960 --> 00:17:56,600 Speaker 1: to create augmented reality. Right. Are usually uses clear lenses, 361 00:17:56,640 --> 00:17:58,679 Speaker 1: but in this case it's going to use cameras to 362 00:17:58,760 --> 00:18:01,119 Speaker 1: create sort of a fake of a r VR mixed 363 00:18:01,160 --> 00:18:05,200 Speaker 1: reality reality effect. It's a pretty cool and practice, I'm told. 364 00:18:05,440 --> 00:18:07,760 Speaker 1: The other interesting thing to your point is you're going 365 00:18:07,800 --> 00:18:09,520 Speaker 1: to be able to replicate a lot of the features 366 00:18:09,520 --> 00:18:12,280 Speaker 1: of an iPad on here, right, So you'll get Safari 367 00:18:12,320 --> 00:18:16,960 Speaker 1: mail maps, calendar, health tracking, even there's also a feature 368 00:18:16,960 --> 00:18:18,640 Speaker 1: where you can hook it up to your Mac and 369 00:18:18,800 --> 00:18:21,679 Speaker 1: you sort of can control your Mac and then you 370 00:18:21,720 --> 00:18:23,919 Speaker 1: can see what your Mac stream looks like in virtual 371 00:18:23,960 --> 00:18:28,640 Speaker 1: reality while using your keyboard, mouse, and track pad. Mark 372 00:18:28,840 --> 00:18:31,720 Speaker 1: very briefly, how much is this moving the needle for 373 00:18:31,800 --> 00:18:36,000 Speaker 1: Apple valuation perspective from an analyst perspective to people ultimately 374 00:18:36,000 --> 00:18:38,520 Speaker 1: think this is gonna be a game change for them. 375 00:18:38,560 --> 00:18:40,199 Speaker 1: So in year one they want to sell about a 376 00:18:40,200 --> 00:18:43,399 Speaker 1: million units at three thousand dollars, right, and I believe 377 00:18:43,480 --> 00:18:46,200 Speaker 1: that's about three billion dollars. So in terms of overall 378 00:18:46,240 --> 00:18:48,679 Speaker 1: revenue for Apple, it's not going to move the needle, 379 00:18:49,119 --> 00:18:51,760 Speaker 1: uh in the short term, But long term this could 380 00:18:51,760 --> 00:18:54,680 Speaker 1: be a multi hundred billion dollar market and Apple, given 381 00:18:54,680 --> 00:18:57,040 Speaker 1: the layoffs at Meta and the hardware changes that Google 382 00:18:57,040 --> 00:18:59,320 Speaker 1: and Amazon as well, they seem to have a clear 383 00:18:59,400 --> 00:19:02,600 Speaker 1: runway not only VR but other hardware products in the future. 384 00:19:03,240 --> 00:19:05,959 Speaker 1: Right Bloomberg s Mark German another day, another big scoop, 385 00:19:06,280 --> 00:19:18,159 Speaker 1: As Carrow said, welcome back to Bloomberg Technology right here 386 00:19:18,160 --> 00:19:20,240 Speaker 1: from San Francisco and Caroline High and I med lovel 387 00:19:20,359 --> 00:19:22,800 Speaker 1: and it is a pleasure to have you back out West, 388 00:19:22,840 --> 00:19:25,600 Speaker 1: back in the Bay Area. We've got to talk about 389 00:19:25,600 --> 00:19:27,600 Speaker 1: social media, and we've got to talk about regulation. Has 390 00:19:27,600 --> 00:19:29,399 Speaker 1: been a big theme in the show. For a number 391 00:19:29,440 --> 00:19:32,560 Speaker 1: of days now. The federal government and several states have 392 00:19:32,680 --> 00:19:37,080 Speaker 1: raised cybersecurity concerns as you know carry around Chinese own TikTok, 393 00:19:37,320 --> 00:19:40,119 Speaker 1: and as we reported last week, dozens of U S 394 00:19:40,119 --> 00:19:43,840 Speaker 1: schools and US universities had moved to ban the app 395 00:19:43,880 --> 00:19:47,400 Speaker 1: from campuses, hoping to prevent it from spying on students, 396 00:19:47,440 --> 00:19:52,520 Speaker 1: asserting the Chinese government could access the private information of 397 00:19:52,560 --> 00:19:55,240 Speaker 1: its users. Let's bring in Mickey Bowland to talk about 398 00:19:55,240 --> 00:19:59,320 Speaker 1: the potential risks associated with the Actually is global cybersecurity 399 00:19:59,440 --> 00:20:04,160 Speaker 1: architect and security evangelist over at Checkpoint Software Technologies, which 400 00:20:04,200 --> 00:20:08,440 Speaker 1: is a cybersecurity solutions provider. I mean you heard the backstory. 401 00:20:08,880 --> 00:20:10,840 Speaker 1: Caroline and I have been trying to make sense of 402 00:20:10,880 --> 00:20:14,480 Speaker 1: this for a number of days now. Campuses moved to 403 00:20:14,560 --> 00:20:17,720 Speaker 1: remove the ability to access TikTok while on campus through 404 00:20:17,720 --> 00:20:21,160 Speaker 1: the WiFi network. What we're hearing from the users is 405 00:20:21,520 --> 00:20:25,440 Speaker 1: they don't understand the risk that is being warned about here. 406 00:20:25,960 --> 00:20:29,800 Speaker 1: Is there a risk? Yes? Yes. Um. First, I want 407 00:20:29,800 --> 00:20:32,240 Speaker 1: to say thank you so much for having me in checkpoint. 408 00:20:32,320 --> 00:20:35,960 Speaker 1: We believe that everyone deserves the best cybersecurity. So I 409 00:20:36,000 --> 00:20:39,440 Speaker 1: will say this for for end users that are unsuspecting 410 00:20:39,600 --> 00:20:42,720 Speaker 1: or really don't understand the risk, Yes there is risk, 411 00:20:43,040 --> 00:20:48,160 Speaker 1: and this is why we're seeing organizations come together, so agencies, 412 00:20:48,400 --> 00:20:54,640 Speaker 1: enterprise UM like nonprofits for actually doing a joint responsibility 413 00:20:54,680 --> 00:20:57,560 Speaker 1: for risk. Right, So we need to approach risk. Is 414 00:20:57,600 --> 00:21:00,399 Speaker 1: that we have privacy and we have security. We have 415 00:21:00,520 --> 00:21:04,679 Speaker 1: privacy for data, for protected data, for privacy and end 416 00:21:04,760 --> 00:21:09,280 Speaker 1: user data endpoints, also for corporate assets. We also have 417 00:21:09,280 --> 00:21:12,360 Speaker 1: to protect our network. So people are writing the networks 418 00:21:12,359 --> 00:21:16,280 Speaker 1: to get to these applications, and our networks are vulnerable 419 00:21:16,320 --> 00:21:20,200 Speaker 1: to attack by militia's actors and malicious spread of malware. 420 00:21:20,840 --> 00:21:23,679 Speaker 1: Uh so, and then we have corporate assets and university 421 00:21:23,720 --> 00:21:26,280 Speaker 1: assets in this case to protect. So it is a 422 00:21:26,359 --> 00:21:29,840 Speaker 1: joint responsibility, and we do need to help students understand 423 00:21:30,280 --> 00:21:34,840 Speaker 1: the risk and and really educate everyone. Mickey, going back 424 00:21:34,840 --> 00:21:40,720 Speaker 1: to basics, the argument is that ultimately uh personnel in 425 00:21:40,840 --> 00:21:45,639 Speaker 1: mainland China might be able to access the personal data 426 00:21:45,880 --> 00:21:49,080 Speaker 1: of TikTok users in the United States. The proposed solution 427 00:21:49,640 --> 00:21:53,280 Speaker 1: from TikTok is to house the data of US users 428 00:21:53,359 --> 00:21:57,560 Speaker 1: on Oracle servers based here in the United States. Is 429 00:21:57,600 --> 00:22:01,960 Speaker 1: that an acceptable mitigation of risk for industry professionals like yourself? 430 00:22:03,440 --> 00:22:06,119 Speaker 1: I think I I hate to speculate about that, but 431 00:22:06,160 --> 00:22:09,520 Speaker 1: I will tell you that our Checkpoint research we actually 432 00:22:09,520 --> 00:22:13,840 Speaker 1: did extensive testing. We're super curious back in about was 433 00:22:13,920 --> 00:22:19,040 Speaker 1: TikTok Um. Were they delivering consistent policy and security privacy 434 00:22:19,080 --> 00:22:22,679 Speaker 1: and security rather And we did find several vulnerabilities. Our 435 00:22:22,800 --> 00:22:27,520 Speaker 1: research team found cross site scripting for their ads um. 436 00:22:27,560 --> 00:22:31,240 Speaker 1: We actually found a way to kind of circumvent um 437 00:22:31,359 --> 00:22:34,959 Speaker 1: registration using a mobile device and use SMS, you know, 438 00:22:35,040 --> 00:22:40,280 Speaker 1: spoofing or registration. Uh, there was API vulnerability. So I 439 00:22:40,320 --> 00:22:43,160 Speaker 1: guess ultimately what I'm saying is we need to demand 440 00:22:43,359 --> 00:22:48,639 Speaker 1: of organizations that are offering the social media applications and 441 00:22:48,720 --> 00:22:52,439 Speaker 1: other applications, primarily for mobile devices, that they actually have 442 00:22:52,480 --> 00:22:57,400 Speaker 1: a consistent security and privacy policy that we can actually address. 443 00:22:58,760 --> 00:23:04,080 Speaker 1: Can compare TikTok to other viraly growing social media companies 444 00:23:04,080 --> 00:23:08,080 Speaker 1: of old? How many vulnerabilities does it have visaving competitors? 445 00:23:09,560 --> 00:23:11,760 Speaker 1: I really, I mean across the board. I'd refer to 446 00:23:11,800 --> 00:23:15,840 Speaker 1: our research team for that. I think that they TikTok 447 00:23:15,960 --> 00:23:20,080 Speaker 1: to their um to justice to TikTok, they actually did 448 00:23:20,200 --> 00:23:24,440 Speaker 1: fix the vulnerabilities that Checkpoint Research team presented to them, 449 00:23:24,520 --> 00:23:28,000 Speaker 1: and indeed we work together in one to help them 450 00:23:28,359 --> 00:23:32,720 Speaker 1: fantast these vulnerabilities. I think that from uh, I guess 451 00:23:32,760 --> 00:23:35,960 Speaker 1: just ultimately what we understand is from an attack surface, 452 00:23:36,320 --> 00:23:40,639 Speaker 1: these applications are going viral. I think, TikTok, Now I 453 00:23:40,720 --> 00:23:43,240 Speaker 1: just install it again to test this. Over a billion 454 00:23:43,280 --> 00:23:46,680 Speaker 1: installs or downloads, there's a u S I read there's 455 00:23:46,760 --> 00:23:51,040 Speaker 1: now currently over a hundred million active users and globally 456 00:23:51,080 --> 00:23:53,800 Speaker 1: it's billions of people. Right, So I think that we 457 00:23:53,960 --> 00:23:58,520 Speaker 1: have to uh think that these these um social media 458 00:23:58,600 --> 00:24:01,359 Speaker 1: platforms are going to be like a huge tasty attack 459 00:24:01,440 --> 00:24:05,560 Speaker 1: surface for malicious actors. Uh. We also have to take 460 00:24:05,600 --> 00:24:09,760 Speaker 1: responsibility for our own personal data. When Mickey told to 461 00:24:09,840 --> 00:24:12,240 Speaker 1: us about that, because you say you're a self proclaimed 462 00:24:12,240 --> 00:24:15,480 Speaker 1: global cybersecurity warrior, be a warrior for us. If I 463 00:24:15,480 --> 00:24:17,080 Speaker 1: can't leave it up to TikTok, what do I do 464 00:24:17,119 --> 00:24:20,080 Speaker 1: to prospect myself? Thank you so much. I am a 465 00:24:20,080 --> 00:24:22,159 Speaker 1: warrior and I wish everyone would be. And we were 466 00:24:22,200 --> 00:24:24,680 Speaker 1: asking more people to join the way your vandreg and 467 00:24:24,760 --> 00:24:26,960 Speaker 1: souff please do. But what you need to do. First 468 00:24:27,000 --> 00:24:31,040 Speaker 1: of all, when you download anyone, I mean from anyone. 469 00:24:31,119 --> 00:24:33,280 Speaker 1: If you go to the app store and you download 470 00:24:33,359 --> 00:24:36,800 Speaker 1: social media applications, go read the details. What is their 471 00:24:36,800 --> 00:24:40,240 Speaker 1: security policy and their privacy policy? What kind of data 472 00:24:40,240 --> 00:24:43,280 Speaker 1: are they collecting on you? And then are you actively 473 00:24:43,440 --> 00:24:46,720 Speaker 1: you know, looking at the permissions that you're granting to 474 00:24:46,800 --> 00:24:49,800 Speaker 1: this application when you install it. If it's like click click, 475 00:24:49,920 --> 00:24:52,880 Speaker 1: test you know, touch, touch, and I just gave access 476 00:24:52,920 --> 00:24:55,440 Speaker 1: to my phone, my camera which you know you're doing 477 00:24:55,520 --> 00:25:00,880 Speaker 1: videos on TikTok and other applications. Um, your camera, you're microphone, 478 00:25:01,000 --> 00:25:04,520 Speaker 1: your you know location, all your contexts, I think your calendar. 479 00:25:04,920 --> 00:25:08,720 Speaker 1: This is probably too much information to share. Then you 480 00:25:08,800 --> 00:25:12,280 Speaker 1: also have the need to redefined bying print. What are 481 00:25:12,280 --> 00:25:15,480 Speaker 1: they saying they're doing with analytics that are that are 482 00:25:15,520 --> 00:25:18,800 Speaker 1: being collected from you? And then who do you trust? Right? 483 00:25:18,880 --> 00:25:22,160 Speaker 1: Ultimately you have to have a trust in the application, 484 00:25:22,960 --> 00:25:26,639 Speaker 1: any software key and be exploited. They're never going to 485 00:25:26,720 --> 00:25:31,280 Speaker 1: be perfect. Mickey Boland, keep worrying and being a work 486 00:25:31,680 --> 00:25:35,040 Speaker 1: checkpoint global cubersecurity architect. Great tous in time with you. Meanwhile, 487 00:25:35,320 --> 00:25:37,639 Speaker 1: well let's head down to DC now because we're going 488 00:25:37,720 --> 00:25:40,000 Speaker 1: to talk much more about regulation of social media the 489 00:25:40,080 --> 00:25:42,439 Speaker 1: US Supreme Court in this instance, because actually ask the 490 00:25:42,440 --> 00:25:45,840 Speaker 1: Biden administration for input on Florida on Texas laws that 491 00:25:45,920 --> 00:25:50,160 Speaker 1: could sharply restrict the editorial discretion of social media platforms. 492 00:25:50,359 --> 00:25:53,480 Speaker 1: Greenberg's Greg Store has the latest for us on basically 493 00:25:53,800 --> 00:25:57,280 Speaker 1: censorship concerns on either side of the aisle. Greg, just 494 00:25:57,320 --> 00:26:00,840 Speaker 1: talk us through what in fact the Intreeen Court wants 495 00:26:00,840 --> 00:26:04,400 Speaker 1: to hear from the administration. Well, the Supreme Court wants 496 00:26:04,440 --> 00:26:07,480 Speaker 1: to hear advice on should we take up these appeals. 497 00:26:07,520 --> 00:26:10,040 Speaker 1: There are appeals from both sides. There are two cases, 498 00:26:10,320 --> 00:26:14,280 Speaker 1: one involving Texas, one involving Florida, And basically these are 499 00:26:14,400 --> 00:26:17,840 Speaker 1: laws where the conservative governors and the conservative lawmakers of 500 00:26:17,840 --> 00:26:21,600 Speaker 1: those states are saying, we're worried that social media companies 501 00:26:21,640 --> 00:26:26,080 Speaker 1: are discriminating against conservatives, silence and conservative voices. So we're 502 00:26:26,080 --> 00:26:29,800 Speaker 1: gonna get in there and we're gonna oversee their content, 503 00:26:29,920 --> 00:26:34,240 Speaker 1: their content management, uh, and uh say, you know, impose 504 00:26:34,280 --> 00:26:36,879 Speaker 1: a lot of new requirements on them. And the social 505 00:26:36,920 --> 00:26:40,440 Speaker 1: media companies are saying that's a violation of our First 506 00:26:40,480 --> 00:26:44,760 Speaker 1: Amendment rights. Greg look at your reporting on the Bloomberg terminal. 507 00:26:45,160 --> 00:26:48,520 Speaker 1: You know, you have this Texas set of laws and 508 00:26:48,560 --> 00:26:52,480 Speaker 1: the Florida set of laws. The Texas set seemed to 509 00:26:52,480 --> 00:26:54,840 Speaker 1: be the most sort of sweeping in terms of the 510 00:26:54,880 --> 00:26:58,560 Speaker 1: actions they take against social media platforms. Tell us what 511 00:26:58,680 --> 00:27:01,639 Speaker 1: they're based on. What do they quiet social media platforms 512 00:27:01,680 --> 00:27:05,800 Speaker 1: to do? Sure, the biggest provision in the Texas law 513 00:27:05,840 --> 00:27:09,159 Speaker 1: would say that you that social media companies can't discriminate 514 00:27:09,200 --> 00:27:11,520 Speaker 1: on the basis of viewpoint. Now, there are a few 515 00:27:11,520 --> 00:27:15,000 Speaker 1: exceptions to that, but basically the idea is, you can't 516 00:27:15,000 --> 00:27:17,520 Speaker 1: take something down if it's coming from a conservative voice, 517 00:27:17,520 --> 00:27:20,359 Speaker 1: if you wouldn't take something uh down coming from a 518 00:27:20,359 --> 00:27:23,879 Speaker 1: liberal voice, And the social media companies say, hey, that 519 00:27:23,880 --> 00:27:26,359 Speaker 1: that might make it impossible for us to stop bullying, 520 00:27:26,600 --> 00:27:31,000 Speaker 1: to stop spam things like that. Uh. There are a 521 00:27:31,040 --> 00:27:35,760 Speaker 1: number of other provisions involving disclosure and operational requirements as well, 522 00:27:36,200 --> 00:27:39,720 Speaker 1: and the Florida law has a whole series of particular 523 00:27:39,800 --> 00:27:42,199 Speaker 1: requirements that are in some cases the same, in some 524 00:27:42,240 --> 00:27:45,600 Speaker 1: cases different. One of the ones that a federal appeals 525 00:27:45,640 --> 00:27:49,359 Speaker 1: court struck down or at least blocked, said that social 526 00:27:49,400 --> 00:27:52,760 Speaker 1: media companies have to provide a thorough rationale every time 527 00:27:52,800 --> 00:27:57,439 Speaker 1: they make some sort of content management decision. And to 528 00:27:57,560 --> 00:28:00,720 Speaker 1: that end, thus far these laws have been to put 529 00:28:00,720 --> 00:28:02,879 Speaker 1: on ice. Shall we say, Greg, what's the next step? 530 00:28:03,000 --> 00:28:06,840 Speaker 1: When do we hear ultimately from the Supreme Court? Yeah, 531 00:28:06,840 --> 00:28:10,440 Speaker 1: they are on ice. Although a federal appeals court upheld 532 00:28:10,480 --> 00:28:13,400 Speaker 1: the Texas laws, of the Supreme Court turns away that case, 533 00:28:13,520 --> 00:28:15,800 Speaker 1: that law will go into effect. So right now we 534 00:28:15,880 --> 00:28:18,399 Speaker 1: wait for the Biden administration and will probably take several 535 00:28:18,440 --> 00:28:21,960 Speaker 1: months to say, you know what it thinks the Supreme 536 00:28:22,000 --> 00:28:25,159 Speaker 1: Court should do, and then probably possibly at the end 537 00:28:25,200 --> 00:28:27,720 Speaker 1: of the Court's term in June, but more likely I 538 00:28:27,760 --> 00:28:30,159 Speaker 1: would say when they come back in October for the 539 00:28:30,200 --> 00:28:32,239 Speaker 1: next term, the Court will tell us whether it's going 540 00:28:32,280 --> 00:28:35,520 Speaker 1: to take up these cases. Because of the widespread impact 541 00:28:35,560 --> 00:28:39,000 Speaker 1: because of the lower court divide over these issues, there's 542 00:28:39,040 --> 00:28:40,800 Speaker 1: a pretty good chance the Court will take it up, 543 00:28:40,800 --> 00:28:44,440 Speaker 1: and then then those will be huge cases for next term. Greg, 544 00:28:44,480 --> 00:28:46,680 Speaker 1: still a lot of work cut out, it would seem. 545 00:28:46,680 --> 00:28:48,880 Speaker 1: We thank you for your time, and we'll continue this 546 00:28:49,040 --> 00:28:51,800 Speaker 1: really important conversation later this week. We're gonna be having 547 00:28:51,840 --> 00:28:54,600 Speaker 1: none of them. The SEC Commissioner Brendon car all about 548 00:28:54,640 --> 00:28:57,000 Speaker 1: of course, I focus on TikTok, I focus on social 549 00:28:57,040 --> 00:29:00,320 Speaker 1: media hire in the United States. That's Thursday, well and 550 00:29:00,440 --> 00:29:03,880 Speaker 1: coming up, how one startup managed to raise funds and 551 00:29:03,920 --> 00:29:08,120 Speaker 1: secure a multi billion dollar valuation, spice and down rounds 552 00:29:08,160 --> 00:29:11,440 Speaker 1: to spite a tough market for startups over the last year. 553 00:29:11,800 --> 00:29:24,320 Speaker 1: This is Bloomberg. Welcome back to blom Meg Technology and 554 00:29:24,360 --> 00:29:26,719 Speaker 1: we do so much in terms of public market coverage. 555 00:29:26,720 --> 00:29:28,800 Speaker 1: But ed, you're so smart giving us up to speed 556 00:29:28,800 --> 00:29:31,040 Speaker 1: in the world of VC venture capital startups. Get us 557 00:29:31,120 --> 00:29:33,480 Speaker 1: up with what's happening this weekend? Yeah, I think talking tech, 558 00:29:33,520 --> 00:29:35,240 Speaker 1: we need to focus on what's happening in that part 559 00:29:35,240 --> 00:29:37,480 Speaker 1: of the world because there are so many headlines. Starting 560 00:29:37,480 --> 00:29:40,880 Speaker 1: with Sequoias Regional arm in South and Southeast Asia. It's 561 00:29:40,880 --> 00:29:43,680 Speaker 1: weighing up special audits of several of its investments in 562 00:29:43,680 --> 00:29:48,400 Speaker 1: the region following allegations of financial irregularity some portfolio companies, 563 00:29:48,520 --> 00:29:52,400 Speaker 1: including ze Lingo and go Mechanic. Over In Europe, Highland 564 00:29:52,440 --> 00:29:55,200 Speaker 1: has raised a new one billion euro fund that aims 565 00:29:55,240 --> 00:29:59,120 Speaker 1: to invest in private software and consumer internet companies in Europe. 566 00:29:59,120 --> 00:30:01,960 Speaker 1: The firm going to focus on growth stage companies. Interesting 567 00:30:02,200 --> 00:30:04,160 Speaker 1: that they've raised and closed that in this environment, and 568 00:30:04,200 --> 00:30:07,760 Speaker 1: finally fintech to HR outfit. Deal says it's reached two 569 00:30:08,640 --> 00:30:11,560 Speaker 1: million dollars in annual recurring revenue by the end of 570 00:30:11,600 --> 00:30:13,520 Speaker 1: two but that was a jump of more than four 571 00:30:14,640 --> 00:30:18,200 Speaker 1: from the end of the company also confirming its valuation 572 00:30:18,440 --> 00:30:22,840 Speaker 1: has reached twelve billion US dollars. Carr. Fascinating that we're 573 00:30:22,840 --> 00:30:25,840 Speaker 1: getting more focused on valuations where they're being held out 574 00:30:25,880 --> 00:30:28,719 Speaker 1: after the funding from last year. Let's talk about it 575 00:30:28,840 --> 00:30:31,880 Speaker 1: with the co founder, the CEO, Alex Boss. Alex is 576 00:30:31,880 --> 00:30:33,720 Speaker 1: great to have you on from Deal and I was 577 00:30:33,760 --> 00:30:36,880 Speaker 1: on the website everything you need to scale a global team. 578 00:30:36,920 --> 00:30:39,520 Speaker 1: Just talk to us about the need for your services 579 00:30:39,720 --> 00:30:42,960 Speaker 1: in an environment where unfortunately talking more about layoffs than scaling. 580 00:30:43,280 --> 00:30:47,360 Speaker 1: How is your HR offering being well scaled in and 581 00:30:47,360 --> 00:30:50,520 Speaker 1: of itself by other companies right now? Of course? Well, 582 00:30:50,560 --> 00:30:52,440 Speaker 1: first of all, Caroline, thank you so much for having 583 00:30:52,480 --> 00:30:55,480 Speaker 1: you today. Are very excited to be here. Um. You know, 584 00:30:55,600 --> 00:30:59,200 Speaker 1: Deal started as a company that enables you to hire globinly, 585 00:30:59,200 --> 00:31:01,400 Speaker 1: so let's say too more. Bloomberg wants to hire someone 586 00:31:01,440 --> 00:31:03,640 Speaker 1: in South Korea and they don't have the structure to 587 00:31:03,640 --> 00:31:05,800 Speaker 1: do that just yet. There we'll enable you to hire 588 00:31:05,880 --> 00:31:08,080 Speaker 1: someone as an employee there and give them the best 589 00:31:08,080 --> 00:31:11,320 Speaker 1: benefits in a day. As the company kind of grew, 590 00:31:11,360 --> 00:31:13,160 Speaker 1: we realized that we could do so much more right. 591 00:31:13,360 --> 00:31:16,520 Speaker 1: Expanding globally as a company is so key and right 592 00:31:16,520 --> 00:31:18,720 Speaker 1: now with the latest readings, we basically become the full 593 00:31:18,720 --> 00:31:22,120 Speaker 1: sta HR solution for you to really go global. I'm 594 00:31:22,120 --> 00:31:25,760 Speaker 1: looking at the global companies cabin Klein, Nike, they're all 595 00:31:25,840 --> 00:31:29,040 Speaker 1: US space, but we've also got private twenty one Shopify 596 00:31:29,160 --> 00:31:33,280 Speaker 1: Canadian business. Where for you do you look to increase 597 00:31:33,360 --> 00:31:37,400 Speaker 1: your own footprint and and econ economy the worldwide is 598 00:31:37,520 --> 00:31:40,440 Speaker 1: slowing down right now? Yeah, I mean, you know, we've 599 00:31:40,440 --> 00:31:43,320 Speaker 1: always been genuine agnostic when it comes to regions, right 600 00:31:43,320 --> 00:31:45,240 Speaker 1: we want to have the best companies obviously, I think 601 00:31:45,360 --> 00:31:48,280 Speaker 1: over fifty of our business comes from the United States, 602 00:31:48,640 --> 00:31:51,000 Speaker 1: and then you know, we really have a global footprint 603 00:31:51,040 --> 00:31:53,560 Speaker 1: and heads of countries in every country actually and really 604 00:31:53,560 --> 00:31:55,840 Speaker 1: has a global business, you know, being European, myself and 605 00:31:55,880 --> 00:31:58,760 Speaker 1: my co founder being Chinese, right, we really wanted to 606 00:31:58,840 --> 00:32:00,840 Speaker 1: be able to cover most of the companies from the 607 00:32:00,840 --> 00:32:02,360 Speaker 1: get go, and that's what we've been able to do 608 00:32:02,400 --> 00:32:04,240 Speaker 1: so far. So to do you have us companies, but 609 00:32:04,280 --> 00:32:06,040 Speaker 1: you have companies from all over the world and across 610 00:32:06,080 --> 00:32:09,440 Speaker 1: all segments using them. Alex, I want to go back 611 00:32:09,480 --> 00:32:11,440 Speaker 1: some of the numbers and the timeline of this. There 612 00:32:11,440 --> 00:32:15,640 Speaker 1: are reports last May they were raising funds. You close 613 00:32:15,760 --> 00:32:18,600 Speaker 1: that deal, I believe over the summer you've announced today 614 00:32:18,720 --> 00:32:21,920 Speaker 1: evaluation of twelve billion dollars. That is completely at odds 615 00:32:22,280 --> 00:32:24,600 Speaker 1: with what Caroline and I are hearing every day on 616 00:32:24,640 --> 00:32:27,960 Speaker 1: this show, founders finding it hard to raise money down 617 00:32:28,080 --> 00:32:31,920 Speaker 1: rounds being more common, the evaluations growing. Was it a 618 00:32:31,920 --> 00:32:35,600 Speaker 1: difficult environment for you? I mean, you know for us 619 00:32:35,640 --> 00:32:38,720 Speaker 1: we closed that around in June. Really they do was 620 00:32:38,760 --> 00:32:40,920 Speaker 1: not to raise money for the capital, but you know, 621 00:32:40,960 --> 00:32:42,920 Speaker 1: we get to to work with the team at Emerson, 622 00:32:43,120 --> 00:32:45,080 Speaker 1: which is very impact driven, right, and that's what we 623 00:32:45,120 --> 00:32:47,440 Speaker 1: wanted to do a deal. The mission of the companies 624 00:32:47,440 --> 00:32:49,360 Speaker 1: to have hundreds of millions of people get to work 625 00:32:49,400 --> 00:32:51,200 Speaker 1: for the best companies in the world. So it was 626 00:32:51,280 --> 00:32:53,320 Speaker 1: less about the money, but more about the people. And 627 00:32:53,400 --> 00:32:55,240 Speaker 1: that's why the valuation was a bit easier to get to. 628 00:32:55,720 --> 00:32:57,520 Speaker 1: And we've been really focused on the business itself. You know, 629 00:32:57,520 --> 00:33:00,360 Speaker 1: we announced that from September we actually started being being 630 00:33:00,400 --> 00:33:02,760 Speaker 1: a bit depositive, so we have a lot of money 631 00:33:02,800 --> 00:33:05,120 Speaker 1: in the bank, and really it was about getting to 632 00:33:05,160 --> 00:33:06,920 Speaker 1: the right number for us and bringing the right people. 633 00:33:07,680 --> 00:33:10,400 Speaker 1: That's interesting, So you're saying essentially that you know, from 634 00:33:10,560 --> 00:33:14,360 Speaker 1: very recently you started to be profitable. The other financial 635 00:33:14,400 --> 00:33:17,600 Speaker 1: that you disclosed is that your and your average revenue 636 00:33:17,840 --> 00:33:21,000 Speaker 1: growth essentially jump from at the end of twenty one 637 00:33:21,080 --> 00:33:24,560 Speaker 1: to the end of last year. Are you worried now 638 00:33:24,560 --> 00:33:30,240 Speaker 1: that when you see layoffs freezing of expenditures in this environment, 639 00:33:30,360 --> 00:33:32,800 Speaker 1: that you might see a delayed response from your customer 640 00:33:32,840 --> 00:33:35,960 Speaker 1: base as well. Well, not exactly, because the way we 641 00:33:36,040 --> 00:33:38,080 Speaker 1: think about it is there's kind of two trends that 642 00:33:38,120 --> 00:33:40,960 Speaker 1: are happening. The first one is more and more companies 643 00:33:41,000 --> 00:33:43,280 Speaker 1: are cutting custs on software and they want to consolidate 644 00:33:43,280 --> 00:33:45,920 Speaker 1: their HR infrastructure, and we've this new product that we 645 00:33:45,960 --> 00:33:48,480 Speaker 1: are on today will help them by being the HR 646 00:33:48,480 --> 00:33:51,600 Speaker 1: infrastructure and the Falce life solution, not just global hiring, 647 00:33:51,600 --> 00:33:54,680 Speaker 1: but really everything for them. The second part is, as 648 00:33:54,720 --> 00:33:57,520 Speaker 1: a lot of businesses starting to grow global, they realize 649 00:33:57,560 --> 00:33:59,800 Speaker 1: that a lot of their custom San Francisco right hiring 650 00:33:59,800 --> 00:34:02,160 Speaker 1: in there's that five hundred K didn't make a lot 651 00:34:02,160 --> 00:34:04,320 Speaker 1: of sense for their business and for their unit economics. 652 00:34:04,400 --> 00:34:07,480 Speaker 1: So thinking about expending their footprint and hiring people in 653 00:34:07,520 --> 00:34:10,160 Speaker 1: location where it's a bit more affordable is definitely your trend. 654 00:34:10,160 --> 00:34:12,200 Speaker 1: We're seeing from most companies, and some of the largest 655 00:34:12,200 --> 00:34:13,840 Speaker 1: one are coming to us to understand what is the 656 00:34:13,880 --> 00:34:17,960 Speaker 1: best way to do So what is a globally focused 657 00:34:18,000 --> 00:34:21,600 Speaker 1: business right now? Alex because many would say the economies 658 00:34:21,600 --> 00:34:24,480 Speaker 1: are splitting in two and particularly as we see a 659 00:34:24,600 --> 00:34:28,160 Speaker 1: more geopolitical tension, whether it's your versus Russia, whether it's 660 00:34:28,440 --> 00:34:30,960 Speaker 1: China versus the US. You said your co founder is 661 00:34:31,000 --> 00:34:33,640 Speaker 1: from China. How do you see companies wanting to scale 662 00:34:33,640 --> 00:34:35,680 Speaker 1: their footprint at the moment. Are we being limited to 663 00:34:35,719 --> 00:34:40,000 Speaker 1: certain spares? Not really. I think you know, she's American 664 00:34:40,080 --> 00:34:42,200 Speaker 1: but originally was born in China. And you know, the 665 00:34:42,239 --> 00:34:44,880 Speaker 1: way we look at the world, whether it's her or myself, 666 00:34:45,000 --> 00:34:47,920 Speaker 1: is that it's it's less about the geos, It's more 667 00:34:47,960 --> 00:34:50,120 Speaker 1: about the talent. Right. You just want as a company 668 00:34:50,239 --> 00:34:52,279 Speaker 1: to be able to hire the best people wherever they 669 00:34:52,280 --> 00:34:55,520 Speaker 1: are and bring them to your company. Right. So, I've 670 00:34:55,640 --> 00:34:57,879 Speaker 1: not seen people think about regions apart when it comes 671 00:34:57,920 --> 00:34:59,719 Speaker 1: from to time zone, right, And how you want to 672 00:34:59,719 --> 00:35:01,480 Speaker 1: build a culture of the company, and how do you 673 00:35:01,480 --> 00:35:03,960 Speaker 1: want to be very sus in office and not in office. 674 00:35:04,320 --> 00:35:06,560 Speaker 1: But when it comes to those deos, we've seen maybe 675 00:35:06,640 --> 00:35:10,399 Speaker 1: Rush I get less less less hires at the moment, 676 00:35:10,400 --> 00:35:13,200 Speaker 1: but in general, most people have been very geoagnostic when 677 00:35:13,200 --> 00:35:15,960 Speaker 1: it comes to town. Alex, what about your own company 678 00:35:16,000 --> 00:35:18,440 Speaker 1: and its health? You know, Caroline and I are talking 679 00:35:18,480 --> 00:35:23,480 Speaker 1: about tens of thousands of talented people in technology being 680 00:35:23,560 --> 00:35:27,680 Speaker 1: laid off. Are you one of those companies that's currently hiring? Yeah, 681 00:35:27,680 --> 00:35:29,560 Speaker 1: I mean for sure, we are two thousand people across 682 00:35:29,560 --> 00:35:32,239 Speaker 1: a hundred plus locations. You know, we've always been as 683 00:35:32,239 --> 00:35:34,520 Speaker 1: efficient as we could, and being a bit depositive now 684 00:35:34,600 --> 00:35:37,000 Speaker 1: enabled us to really be able to scale further. So 685 00:35:37,080 --> 00:35:39,200 Speaker 1: you know, we have over I think five D plus 686 00:35:39,239 --> 00:35:41,560 Speaker 1: million dollars in the bank. We're generating money now, so 687 00:35:41,600 --> 00:35:44,239 Speaker 1: we'll keep hiring to really bring the message transflution to 688 00:35:44,320 --> 00:35:46,600 Speaker 1: market and really help companies go global. So if you 689 00:35:46,719 --> 00:35:50,000 Speaker 1: know great people, send them send them away. Alright. Deal 690 00:35:50,080 --> 00:35:53,600 Speaker 1: co founder and CEO Alex Bozis, thank you so much 691 00:35:53,680 --> 00:35:56,880 Speaker 1: for sharing Evaluation news but also getting insight into what 692 00:35:56,960 --> 00:35:58,880 Speaker 1: it's like to run a company right now. For me, 693 00:35:59,320 --> 00:36:01,160 Speaker 1: that's the take. It's all well and good having the 694 00:36:01,280 --> 00:36:04,600 Speaker 1: vcs on the public market, investors, the activists talking about 695 00:36:04,640 --> 00:36:06,520 Speaker 1: what they want from a company. When you're at the 696 00:36:06,560 --> 00:36:10,040 Speaker 1: helm trying to raise money, trying to make decisions. It's 697 00:36:10,080 --> 00:36:12,839 Speaker 1: interesting to see somebody so confident and there's a lot 698 00:36:12,840 --> 00:36:15,240 Speaker 1: of negativecy out there. Well, I mean a bootstrap business 699 00:36:15,280 --> 00:36:18,960 Speaker 1: to begin with, a why combinator, well known Silicon Valley 700 00:36:19,040 --> 00:36:23,800 Speaker 1: focused startup culture. I'm interested that he was talking already 701 00:36:23,840 --> 00:36:27,000 Speaker 1: all the Lexican that investors, public investors and private investors 702 00:36:27,040 --> 00:36:31,840 Speaker 1: want to hear. Ebitdre positive efficiencies, hiring across the world 703 00:36:31,880 --> 00:36:35,040 Speaker 1: to ensure that they're basically making sure that they're efficient 704 00:36:35,120 --> 00:36:38,680 Speaker 1: right now, that they're not over scaling, over hiring, over indulging, 705 00:36:38,960 --> 00:36:40,440 Speaker 1: which is what so many of the big companies have 706 00:36:40,520 --> 00:36:42,719 Speaker 1: been doing basically and having to rewind them to be fair. 707 00:36:42,760 --> 00:36:44,800 Speaker 1: The other big theme that we've heard is that investors 708 00:36:44,840 --> 00:36:48,240 Speaker 1: look for quality in times like these where okay, actually 709 00:36:48,280 --> 00:36:50,920 Speaker 1: being profitable for many companies as a distant dream right 710 00:36:50,920 --> 00:36:53,759 Speaker 1: now could be an attractive investment. But if you're scaling 711 00:36:53,800 --> 00:36:56,080 Speaker 1: a revenue at four with the many years time so 712 00:36:56,280 --> 00:37:07,200 Speaker 1: they're doing now with us both stood right here in 713 00:37:07,239 --> 00:37:10,240 Speaker 1: San Francisco. Let's do something very local for going viral, 714 00:37:10,320 --> 00:37:13,360 Speaker 1: because the Tesla fraud trial is underway right here in 715 00:37:13,360 --> 00:37:16,200 Speaker 1: this city. And look Elon Musk continuing his testimony right 716 00:37:16,239 --> 00:37:19,080 Speaker 1: on Monday, and he said, what the saludo ABIs sovereign 717 00:37:19,120 --> 00:37:22,720 Speaker 1: well fund quote unequivocally wanted to give him the money, 718 00:37:23,000 --> 00:37:25,719 Speaker 1: But there was no email about it. He just said 719 00:37:25,719 --> 00:37:27,480 Speaker 1: it was their word was as good as that. But 720 00:37:27,520 --> 00:37:29,480 Speaker 1: of course it's all in defenses and tweets here sent back. 721 00:37:30,239 --> 00:37:32,640 Speaker 1: That's part one of the defense. The other thing, and 722 00:37:32,719 --> 00:37:35,640 Speaker 1: it extends from Friday, is that Elon Musk kind of 723 00:37:35,640 --> 00:37:39,520 Speaker 1: rejected the idea that his tweets influenced Tesla's share price, 724 00:37:39,560 --> 00:37:43,640 Speaker 1: and actually he questioned how seriously anyone took his tweets. 725 00:37:43,680 --> 00:37:46,520 Speaker 1: But having since bought Twitter, he talked about Twitter being 726 00:37:47,160 --> 00:37:51,319 Speaker 1: a very trustworthy, reliable sort of news in journalism. Yeah, well, 727 00:37:51,360 --> 00:37:52,719 Speaker 1: we did what we always do on this show. We 728 00:37:52,760 --> 00:37:56,319 Speaker 1: asked our audience to react to the quote that he 729 00:37:56,440 --> 00:38:00,000 Speaker 1: put about whether or not his tweets should be trust 730 00:38:00,080 --> 00:38:02,640 Speaker 1: did He said, just because I tweet about something doesn't 731 00:38:02,680 --> 00:38:05,560 Speaker 1: mean people believe it will act accordingly, do you agree 732 00:38:06,560 --> 00:38:11,200 Speaker 1: negative say that's insane? Of course, they felt that he 733 00:38:11,280 --> 00:38:14,520 Speaker 1: puts out tweets that people believe that act on. I mean, 734 00:38:14,760 --> 00:38:16,880 Speaker 1: there has been criticism time and time again of the 735 00:38:16,920 --> 00:38:20,040 Speaker 1: way in which he's perhaps talked up certain companies, certain 736 00:38:20,360 --> 00:38:23,120 Speaker 1: crypto assets. Goodness knows what. But people move and they 737 00:38:23,200 --> 00:38:25,920 Speaker 1: make asset allocation decisions of what he tweets. Yeah, and 738 00:38:25,920 --> 00:38:28,320 Speaker 1: why he doesn't use a regulatory filing instead of the tweet? 739 00:38:28,440 --> 00:38:32,680 Speaker 1: Tweet is his method of choice? Yeah, many politicians would agree. 740 00:38:32,840 --> 00:38:34,879 Speaker 1: Was it a tweet that almost broke the internet today 741 00:38:34,920 --> 00:38:37,680 Speaker 1: as well? Is then an m using not Eminem the rapper, 742 00:38:38,040 --> 00:38:41,200 Speaker 1: Eminem's when you eat, look at this, we'll bring it 743 00:38:41,280 --> 00:38:43,239 Speaker 1: up on the screen and just a moment, Eminem's is 744 00:38:43,320 --> 00:38:47,960 Speaker 1: reconsidering It's spokes candies. You see the former spokes candies 745 00:38:47,960 --> 00:38:50,919 Speaker 1: along the bottom there. They have a new spokesperson. Yeah, 746 00:38:50,960 --> 00:38:53,880 Speaker 1: and apparently everyone can rally behind her. Is kind of 747 00:38:53,920 --> 00:38:56,319 Speaker 1: what they say, Maya Rudolph, They say, we're confident Mss 748 00:38:56,360 --> 00:38:59,160 Speaker 1: Rudolph will champion the power of fun to create a 749 00:38:59,160 --> 00:39:02,239 Speaker 1: world where everyone feels they belong. Of course, many think 750 00:39:02,320 --> 00:39:04,200 Speaker 1: this might be about the Super Bowl rather went out 751 00:39:04,200 --> 00:39:05,960 Speaker 1: from the Super Bowl. Let's wait and see if this 752 00:39:06,040 --> 00:39:08,640 Speaker 1: is real life. Eminem's are determined to break the Internet. 753 00:39:08,880 --> 00:39:10,799 Speaker 1: We didn't break the Internet. We talked all about it. 754 00:39:10,800 --> 00:39:13,400 Speaker 1: That that does it for this edition of Bloomberg Technology Tuesday. 755 00:39:13,600 --> 00:39:15,680 Speaker 1: We've got so much more in terms of interactive advertising. 756 00:39:15,680 --> 00:39:17,520 Speaker 1: Ber O c O David Cohen's going to be joining. 757 00:39:17,680 --> 00:39:21,160 Speaker 1: Don't forget, you've got to recap everything on the podcast Spotify. 758 00:39:21,440 --> 00:39:22,320 Speaker 1: This is Bloomberg