1 00:00:01,480 --> 00:00:04,840 Speaker 1: From the heart of where Innovation, money and power Collie 2 00:00:05,040 --> 00:00:09,760 Speaker 1: in Silicon Valley, NBR. This is Bloomberg Technology with Caroline 3 00:00:09,840 --> 00:00:26,720 Speaker 1: Hyde and Ed Ludlow. I'm Caroline Hyde at Bloomberg's world 4 00:00:26,760 --> 00:00:29,560 Speaker 1: headquarters in New York. I'm d Ludlow in San Francisco. 5 00:00:29,600 --> 00:00:32,800 Speaker 1: This is Bloomberg Technology coming up the White House, urging 6 00:00:32,920 --> 00:00:37,440 Speaker 1: social media users and platforms to stop circulating classified documents 7 00:00:37,440 --> 00:00:40,120 Speaker 1: as it works to clean up the biggest intelligence leak 8 00:00:40,479 --> 00:00:45,120 Speaker 1: in decades. We'll discuss and Twitter now allowing users to 9 00:00:45,240 --> 00:00:48,520 Speaker 1: charge subscription fees. We'll break down the move as competitors 10 00:00:48,520 --> 00:00:52,000 Speaker 1: look to grab the social giants market share. And we'll 11 00:00:52,040 --> 00:00:55,200 Speaker 1: hear from the CEO of Amazon Web Services as the 12 00:00:55,280 --> 00:00:58,720 Speaker 1: company joins the race for artificial intelligence dominance. All that 13 00:00:59,240 --> 00:01:01,320 Speaker 1: so much more going up. Let's get to it with 14 00:01:01,400 --> 00:01:04,560 Speaker 1: Shinati Bassa, who who's there in early breaking all this 15 00:01:04,640 --> 00:01:07,160 Speaker 1: bank news for us, but told to us about the 16 00:01:07,200 --> 00:01:10,360 Speaker 1: Silicon Valley bank repercussions and really how sticky some of 17 00:01:10,360 --> 00:01:13,280 Speaker 1: these deposits are likely to be. It's really interesting to 18 00:01:13,319 --> 00:01:16,959 Speaker 1: see just the movement. JP Morgan posted a surprise increase 19 00:01:17,000 --> 00:01:20,720 Speaker 1: in deposits after quarters of decreases now they say it's 20 00:01:20,760 --> 00:01:24,840 Speaker 1: not necessarily a sticky phenomenon. They expect deposit outflows or 21 00:01:24,959 --> 00:01:27,839 Speaker 1: deposit pressure really to continue, if you will, because interest 22 00:01:27,880 --> 00:01:30,039 Speaker 1: rates are still going up. Money markets are still very 23 00:01:30,080 --> 00:01:33,000 Speaker 1: attractive here. But when you look at it, they really 24 00:01:33,080 --> 00:01:35,919 Speaker 1: did end up being a big beneficiary of what happened 25 00:01:35,920 --> 00:01:38,520 Speaker 1: in the regional banking system in the last couple of months, 26 00:01:38,520 --> 00:01:41,160 Speaker 1: if you will. Now remember P ANDC also reported today too, 27 00:01:41,319 --> 00:01:43,520 Speaker 1: And the reason that's important is because people were really 28 00:01:43,520 --> 00:01:47,040 Speaker 1: worried about other mid size regional banks, and the deposit 29 00:01:47,120 --> 00:01:49,760 Speaker 1: number there was a little above what analysts expected. So 30 00:01:49,800 --> 00:01:52,800 Speaker 1: as we think about the broader pressures after the wake 31 00:01:52,840 --> 00:01:55,880 Speaker 1: of Silicon Valley Valley banks, real troubles that we've seen, 32 00:01:56,520 --> 00:01:59,280 Speaker 1: our other banks still feeling any pressure, That's where I 33 00:01:59,320 --> 00:02:01,840 Speaker 1: want to go your tweet, what is it? You said, Shinnali? 34 00:02:02,240 --> 00:02:05,560 Speaker 1: What eight hundred Jamie? That's literally what happened after the 35 00:02:05,560 --> 00:02:07,960 Speaker 1: class of Silicon Valley Bank. Isn't it to be fair? 36 00:02:08,240 --> 00:02:13,440 Speaker 1: I stole that from John Farrow, But but it was charming, 37 00:02:13,520 --> 00:02:16,080 Speaker 1: right because seriously they did go to JP Morgan and 38 00:02:16,320 --> 00:02:20,120 Speaker 1: next week, remember Goldman Sachs and Morgan Stanley are reporting 39 00:02:20,160 --> 00:02:24,120 Speaker 1: and presumably they would also have been beneficiaries, particularly Morgan 40 00:02:24,160 --> 00:02:26,639 Speaker 1: Stanley that also looks to bank a lot of these 41 00:02:26,760 --> 00:02:30,079 Speaker 1: as Silicon Valley startup founders, if you will. Ed remember 42 00:02:30,120 --> 00:02:32,000 Speaker 1: we talked earlier in the week with Nishi Somaia over 43 00:02:32,040 --> 00:02:35,399 Speaker 1: at Goldman Sacks, which really targeted a lending opportunity as well. 44 00:02:35,800 --> 00:02:38,240 Speaker 1: JP Morgan said, net interest income is really going to 45 00:02:38,280 --> 00:02:41,760 Speaker 1: expand very meaningfully. Of course, that is picking up some 46 00:02:41,800 --> 00:02:45,400 Speaker 1: business that we're seeing from other firms getting out of 47 00:02:45,400 --> 00:02:48,720 Speaker 1: the market, but also really interestingly here I find this 48 00:02:48,800 --> 00:02:51,120 Speaker 1: to be a tech play, if you will. A lot 49 00:02:51,120 --> 00:02:53,480 Speaker 1: of this net interest income is coming from credit cards. 50 00:02:53,720 --> 00:02:55,840 Speaker 1: So if you think about the payments businesses, the credit 51 00:02:55,840 --> 00:02:59,560 Speaker 1: card businesses, everything that's online, those are the things that 52 00:02:59,600 --> 00:03:03,040 Speaker 1: are really facilitating any of the love you're seeing in 53 00:03:03,080 --> 00:03:05,519 Speaker 1: the banking system. And this is what some point to 54 00:03:05,639 --> 00:03:07,920 Speaker 1: Shnati Bassak on who can do big banks and fintech 55 00:03:07,919 --> 00:03:10,080 Speaker 1: and wrap it all into a kind of a focus 56 00:03:10,120 --> 00:03:13,160 Speaker 1: for us. Let's route it out with what's happening with 57 00:03:13,200 --> 00:03:15,960 Speaker 1: First Republic, for example, at the moment, Shanani, because it's 58 00:03:16,120 --> 00:03:18,839 Speaker 1: interesting actually under pressure, all people were worried about what's 59 00:03:18,880 --> 00:03:21,080 Speaker 1: to come in terms about flows and deposits. Until that 60 00:03:21,160 --> 00:03:24,280 Speaker 1: question is cleared up around First Republic and First Republic remember, 61 00:03:24,400 --> 00:03:27,560 Speaker 1: as we've been talking about has a big California tie. 62 00:03:27,600 --> 00:03:30,639 Speaker 1: They have really banks a lot of the wealthy in California. 63 00:03:30,960 --> 00:03:33,440 Speaker 1: Then there are a lot of questions about how far 64 00:03:33,480 --> 00:03:35,680 Speaker 1: they've gone in places other banks might not have been 65 00:03:35,720 --> 00:03:38,840 Speaker 1: able to, what is left behind as they're under pressure. 66 00:03:39,120 --> 00:03:41,880 Speaker 1: Until they report. Until that's out of the way, it's 67 00:03:41,960 --> 00:03:44,760 Speaker 1: hard to say that the system isn't all clear, but 68 00:03:44,880 --> 00:03:47,720 Speaker 1: it is a promising sign that we're seeing the bank 69 00:03:47,800 --> 00:03:51,280 Speaker 1: earnings start off very cleanly today. But we do still 70 00:03:51,360 --> 00:03:53,880 Speaker 1: have two weeks ahead of us here where we're going 71 00:03:53,960 --> 00:03:56,120 Speaker 1: to get a lot of questions still about the client 72 00:03:56,160 --> 00:03:58,640 Speaker 1: bases that we're talking about here and what kind of 73 00:03:58,680 --> 00:04:01,560 Speaker 1: pressure that the bankings on the heels of those pins 74 00:04:01,600 --> 00:04:05,400 Speaker 1: might feel. I used to be one eight hundred Greg Becker, 75 00:04:05,800 --> 00:04:08,600 Speaker 1: one eight hundred Jamie Diamond. Right now is so interesting 76 00:04:08,640 --> 00:04:11,520 Speaker 1: to see the net result of that SPB collapse Bloomberg 77 00:04:11,560 --> 00:04:13,960 Speaker 1: Shnali Bassett, thank you so much. Let's go over to 78 00:04:14,040 --> 00:04:17,239 Speaker 1: DC in Washington. The White House is urging social media 79 00:04:17,279 --> 00:04:20,880 Speaker 1: companies to prevent the circulation of information that could hurt 80 00:04:21,000 --> 00:04:24,960 Speaker 1: national securities. It works to clean up that intelligence league. 81 00:04:25,200 --> 00:04:28,240 Speaker 1: Joining us now from always Bloomberg's NAT Security editor Nick 82 00:04:28,240 --> 00:04:31,479 Speaker 1: Wadham's Nick the b gub article lead says it all, 83 00:04:31,600 --> 00:04:35,040 Speaker 1: how did a twenty one year old with basically just 84 00:04:35,080 --> 00:04:38,440 Speaker 1: a driving license and eighteen months experience get access to 85 00:04:38,520 --> 00:04:43,159 Speaker 1: that data? We've had an arrest. What are the latest details. Well, 86 00:04:43,480 --> 00:04:49,400 Speaker 1: he's been charged now with the unlawful retention and dissemination 87 00:04:49,680 --> 00:04:53,880 Speaker 1: of classified information. I mean, the big question here is 88 00:04:54,040 --> 00:04:57,479 Speaker 1: what the government can really do. And that warning from 89 00:04:57,480 --> 00:05:01,240 Speaker 1: the White House, Hey, if you see classif information online, 90 00:05:01,320 --> 00:05:04,800 Speaker 1: don't share it sort of gets to what a struggle 91 00:05:04,800 --> 00:05:07,039 Speaker 1: they're really going to have. I mean, the issue here 92 00:05:07,120 --> 00:05:09,960 Speaker 1: is that he went on a private chat on discord 93 00:05:10,240 --> 00:05:13,320 Speaker 1: and started spreading this stuff around to his friends, and 94 00:05:13,360 --> 00:05:15,400 Speaker 1: then someone in one of those chats took it and 95 00:05:15,760 --> 00:05:18,839 Speaker 1: amplified it more broadly on the wider net. And so 96 00:05:18,839 --> 00:05:22,360 Speaker 1: far the administration is making clear that it has not 97 00:05:22,440 --> 00:05:25,440 Speaker 1: shown it really knows how to clamp down on something 98 00:05:25,480 --> 00:05:27,440 Speaker 1: like that, and it's going to have a really hard 99 00:05:27,440 --> 00:05:32,000 Speaker 1: time doing so. The responsibility Nick, that was cooled on 100 00:05:32,720 --> 00:05:36,880 Speaker 1: for social media platforms themselves, coming from on the press 101 00:05:36,920 --> 00:05:39,480 Speaker 1: officer over at the White House. Do you think that 102 00:05:39,480 --> 00:05:43,960 Speaker 1: that's in any way or reality. Well, I mean, Discord 103 00:05:44,000 --> 00:05:47,680 Speaker 1: obviously did cooperate with the administration on this, as have 104 00:05:47,880 --> 00:05:52,360 Speaker 1: other companies in the past. So I think in large 105 00:05:52,400 --> 00:05:55,440 Speaker 1: part these companies do not want to have top secret, 106 00:05:55,560 --> 00:05:59,680 Speaker 1: classified information distributed on their platforms. But you know, it 107 00:05:59,720 --> 00:06:02,640 Speaker 1: gets to that broader question again, Okay, what can they do? 108 00:06:02,720 --> 00:06:05,400 Speaker 1: This was a private chat, It was a relatively small 109 00:06:05,440 --> 00:06:08,920 Speaker 1: group of people by all accounts. He was putting information 110 00:06:09,000 --> 00:06:12,719 Speaker 1: on there as far back as last December and then 111 00:06:12,800 --> 00:06:16,760 Speaker 1: switched over from just transcribing information to actually posting the documents. 112 00:06:17,000 --> 00:06:19,320 Speaker 1: So what can they do? How closely do they need 113 00:06:19,360 --> 00:06:22,520 Speaker 1: to be watching these chats? And that's something companies are 114 00:06:22,520 --> 00:06:24,400 Speaker 1: going to have to grapple with, especially with this new 115 00:06:24,440 --> 00:06:28,640 Speaker 1: pressure from the administration. The FBI released an affidavit Friday, 116 00:06:28,640 --> 00:06:32,240 Speaker 1: and I just want to point out that Discord, the platform, 117 00:06:32,320 --> 00:06:35,400 Speaker 1: the social media company, was not named in the affidavit, 118 00:06:35,680 --> 00:06:39,040 Speaker 1: but they did provide the FBI with the records requested 119 00:06:39,279 --> 00:06:42,159 Speaker 1: because they were ordered to do so by the court. 120 00:06:42,800 --> 00:06:45,280 Speaker 1: I just want to go back to the individual involved, Nick, 121 00:06:45,360 --> 00:06:48,479 Speaker 1: if we can, I mean, what happens here. They still 122 00:06:48,520 --> 00:06:51,240 Speaker 1: trying to find out exactly the breadth of information that 123 00:06:52,360 --> 00:06:54,840 Speaker 1: was put out there by him, What are kind of 124 00:06:54,880 --> 00:06:58,760 Speaker 1: illegal procedures going forward. Well, I mean, if you look 125 00:06:58,760 --> 00:07:03,520 Speaker 1: at the arrangement and the charging documents themselves, it appears 126 00:07:03,560 --> 00:07:08,200 Speaker 1: to be fairly clear cut in terms of what he's 127 00:07:08,240 --> 00:07:11,040 Speaker 1: accused of doing and the evidence they have against him. 128 00:07:11,080 --> 00:07:14,760 Speaker 1: That all looks, you know, from a layman's perspective, pretty 129 00:07:14,840 --> 00:07:16,960 Speaker 1: daring strong. But the issue I think that's going to 130 00:07:17,040 --> 00:07:20,520 Speaker 1: happen now is, Okay, how many documents actually were there? 131 00:07:20,520 --> 00:07:22,800 Speaker 1: You know, there are several dozen that we know about 132 00:07:22,880 --> 00:07:25,440 Speaker 1: I think about one hundred now, But there's also this 133 00:07:25,480 --> 00:07:28,160 Speaker 1: whole other element where early on, as we now know, 134 00:07:28,560 --> 00:07:32,480 Speaker 1: he was actually typing out information from previous documents and 135 00:07:32,640 --> 00:07:35,640 Speaker 1: putting that out to his friends, and then decided that 136 00:07:35,680 --> 00:07:37,240 Speaker 1: was too much of a hassle, so he was just 137 00:07:37,280 --> 00:07:39,720 Speaker 1: going to photograph documents and start posting them because that 138 00:07:39,800 --> 00:07:42,160 Speaker 1: was easier and quicker to do. So the big question 139 00:07:42,280 --> 00:07:45,680 Speaker 1: is we still don't know the full extent of what 140 00:07:45,840 --> 00:07:48,640 Speaker 1: was actually leaked. The documents we know about so far 141 00:07:48,680 --> 00:07:52,800 Speaker 1: are extremely damaging, but I think investigators really are going 142 00:07:52,840 --> 00:07:55,160 Speaker 1: to be honing in on that question of whether that's 143 00:07:55,240 --> 00:07:57,600 Speaker 1: it or whether there's much more damage out there that 144 00:07:57,640 --> 00:08:00,640 Speaker 1: they don't yet know about. We thank you, we can 145 00:08:00,680 --> 00:08:03,360 Speaker 1: calling you on these moments. Meanwhile, let's stick with where 146 00:08:03,440 --> 00:08:06,080 Speaker 1: Nick is Washington. Just a little reminder for you, go 147 00:08:06,160 --> 00:08:08,000 Speaker 1: to life. Go if you're like enough to have a terminal. 148 00:08:08,120 --> 00:08:12,440 Speaker 1: Bloomberg's valence is Tom Keene. He's currently on stage interviewing 149 00:08:12,520 --> 00:08:15,720 Speaker 1: a whole raft of central bankers of economists. As you 150 00:08:15,720 --> 00:08:19,200 Speaker 1: see Olivia Bronchard there at the moment. I'm Squito Governorth 151 00:08:19,240 --> 00:08:23,040 Speaker 1: as well back of England Cia ten yo. So just 152 00:08:23,200 --> 00:08:27,240 Speaker 1: stick with this and also worktability. I mean we ever 153 00:08:27,320 --> 00:08:29,600 Speaker 1: sends a very sharp changes in your Twitter. All right, 154 00:08:29,680 --> 00:08:33,600 Speaker 1: coming up? Lauren Schipper hosted the Upload podcast. It's going 155 00:08:33,640 --> 00:08:36,720 Speaker 1: to join us to discuss Twitter's move to allow users 156 00:08:37,160 --> 00:08:40,319 Speaker 1: to start charging for content. We'll get more on the 157 00:08:40,400 --> 00:08:59,440 Speaker 1: social media's landscape. Next. This is Bloomberg. Twitter is now 158 00:08:59,480 --> 00:09:02,720 Speaker 1: allowing you users to charge for access to their own content. 159 00:09:02,920 --> 00:09:06,560 Speaker 1: CEO Elon Musk tweeted the announcement, of course on the platform, 160 00:09:06,920 --> 00:09:11,120 Speaker 1: and even said he'll offer amas for his subscribers. Joining 161 00:09:11,200 --> 00:09:14,319 Speaker 1: us for the latest details Bloomberg. Sarah Freyer, you and 162 00:09:14,440 --> 00:09:16,959 Speaker 1: I discussed this just as the tweet came out, and 163 00:09:17,080 --> 00:09:22,120 Speaker 1: we thought, oh, that's interesting. Essentially, for a twelve month period, 164 00:09:22,840 --> 00:09:28,040 Speaker 1: they are offering interesting terms to content creators. Well, they're saying, 165 00:09:28,160 --> 00:09:30,640 Speaker 1: you're going to get all the money that you make. 166 00:09:31,559 --> 00:09:34,079 Speaker 1: The only cut that we'll have to take from it 167 00:09:34,200 --> 00:09:36,319 Speaker 1: is the money we paid of the app store for 168 00:09:36,520 --> 00:09:39,320 Speaker 1: the first twelve months. After that, who knows it could 169 00:09:39,360 --> 00:09:42,720 Speaker 1: become part of the Twitter's revenue proposition. But in twelve months, 170 00:09:42,760 --> 00:09:44,760 Speaker 1: you can build a community. You could do a lot 171 00:09:45,360 --> 00:09:48,280 Speaker 1: a lot of building of that business and then see 172 00:09:48,360 --> 00:09:51,719 Speaker 1: what happens. I just wonder if if Twitter is a 173 00:09:51,800 --> 00:09:55,719 Speaker 1: place where people feel like they can get that stability 174 00:09:55,880 --> 00:10:00,199 Speaker 1: because there has been so much, so much tension, so 175 00:10:00,280 --> 00:10:04,920 Speaker 1: much tumult between Twitter and its creators um since Must 176 00:10:04,960 --> 00:10:07,920 Speaker 1: took over there, they're losing their their blue check marks. 177 00:10:08,000 --> 00:10:12,239 Speaker 1: That it's become more confusing how to figure out the algorithm. 178 00:10:12,760 --> 00:10:14,600 Speaker 1: So there are a lot of factors consider if you're 179 00:10:14,600 --> 00:10:16,800 Speaker 1: going to build that business. And Sarah, what's interesting is 180 00:10:16,920 --> 00:10:19,679 Speaker 1: slowly but surely sub Stock and Twitter seem to be 181 00:10:19,760 --> 00:10:23,000 Speaker 1: trying to move into one another, and that is that's 182 00:10:23,040 --> 00:10:25,560 Speaker 1: what the sub Stack CEO said we should expect when 183 00:10:25,600 --> 00:10:27,800 Speaker 1: he was on your program recently. I mean, this is 184 00:10:28,080 --> 00:10:31,360 Speaker 1: this is the thing is you know, when you're trying 185 00:10:31,400 --> 00:10:34,080 Speaker 1: to build new revenue models, you're you're going to build 186 00:10:34,120 --> 00:10:37,040 Speaker 1: in all directions, and advertising is not working for Twitter 187 00:10:37,200 --> 00:10:38,800 Speaker 1: right now. They have to come up with something else. 188 00:10:39,280 --> 00:10:42,359 Speaker 1: So they're they're going to throw a lot of spaghetti 189 00:10:42,440 --> 00:10:46,000 Speaker 1: on the wall in the next few weeks, months, years. 190 00:10:46,480 --> 00:10:49,480 Speaker 1: We saw subscriptions here, but they also said you're going 191 00:10:49,520 --> 00:10:51,480 Speaker 1: to start to be able to buy and trade stocks 192 00:10:51,559 --> 00:10:53,920 Speaker 1: via Twitter. I mean, all sorts of ideas are going 193 00:10:53,960 --> 00:10:57,400 Speaker 1: to be thrown at us. And in meanwhile, Twitter Blue 194 00:10:57,559 --> 00:11:01,160 Speaker 1: their first idea in the sort of new money making category. 195 00:11:01,200 --> 00:11:03,760 Speaker 1: It hasn't seemed to be doing so well. Only one 196 00:11:03,840 --> 00:11:06,920 Speaker 1: percent of Twitter users actually I think less than one 197 00:11:07,000 --> 00:11:10,000 Speaker 1: percent so far based on estimates, have signed out to 198 00:11:10,160 --> 00:11:12,880 Speaker 1: pay eight dollars a month to Musk for that Satify 199 00:11:13,240 --> 00:11:15,280 Speaker 1: breaking it down. We thank you so much of Bloomberg 200 00:11:15,320 --> 00:11:17,280 Speaker 1: and letstick on all of this. Laurence Snipp has with 201 00:11:17,360 --> 00:11:20,120 Speaker 1: US vice president of corporate Development and Jelly Smackets, a 202 00:11:20,160 --> 00:11:23,600 Speaker 1: company actually focused on amplifying content creators. Lauren, you also 203 00:11:23,800 --> 00:11:26,439 Speaker 1: host a create an upload podcast or previously rank created 204 00:11:26,480 --> 00:11:29,199 Speaker 1: partnerships over it on the Artists formerly known as Facebook. 205 00:11:29,240 --> 00:11:32,079 Speaker 1: And I'm interested, And do you think this will work? 206 00:11:32,160 --> 00:11:34,559 Speaker 1: Will content creators that you try and amplify want to 207 00:11:34,640 --> 00:11:38,000 Speaker 1: go via Twitter in this way? I mean, right now, no, 208 00:11:38,360 --> 00:11:40,920 Speaker 1: I don't think it will work, mainly because I don't 209 00:11:41,000 --> 00:11:43,920 Speaker 1: think this is a platform that creators can sort of trust, right, 210 00:11:44,040 --> 00:11:45,439 Speaker 1: Like it was just you guys were just sort of 211 00:11:45,520 --> 00:11:48,080 Speaker 1: talking about that, right. There's been so much tumult at 212 00:11:48,200 --> 00:11:51,839 Speaker 1: Twitter in the past few months since Elan's taken over. 213 00:11:52,600 --> 00:11:55,160 Speaker 1: If you look at the thread where Elon tweeted this, 214 00:11:55,600 --> 00:11:58,559 Speaker 1: half of the comments on are talking about parts of 215 00:11:59,000 --> 00:12:01,960 Speaker 1: Twitter that is broke, that are broken. And So if 216 00:12:02,040 --> 00:12:05,280 Speaker 1: I'm a creator thinking about where to kind of launch 217 00:12:05,360 --> 00:12:08,320 Speaker 1: a business, which effectively this is, I would be very 218 00:12:08,440 --> 00:12:11,760 Speaker 1: suspect about doing that on Twitter. I mean, I just 219 00:12:11,840 --> 00:12:13,640 Speaker 1: feel like you can't trust this product. I mean they've 220 00:12:13,679 --> 00:12:16,640 Speaker 1: lost most of their employees and talk about security, talk 221 00:12:16,679 --> 00:12:20,040 Speaker 1: about you know, just a reliability of a product. I 222 00:12:20,120 --> 00:12:22,120 Speaker 1: would be very I would be as a creator, would 223 00:12:22,120 --> 00:12:24,200 Speaker 1: be very reticent to do this on Twitter. Right now, 224 00:12:24,840 --> 00:12:26,559 Speaker 1: I think this is a good opportunity to also talk 225 00:12:26,559 --> 00:12:30,280 Speaker 1: about how the content creator ecosystem works, right that you 226 00:12:30,720 --> 00:12:33,679 Speaker 1: need a following. And I guess a question I had 227 00:12:33,800 --> 00:12:36,560 Speaker 1: is it does this move by Elon Musk bring content 228 00:12:36,640 --> 00:12:40,400 Speaker 1: creators from other platforms like TikTok and YouTube where they 229 00:12:40,480 --> 00:12:43,839 Speaker 1: already have an established following and may not have one 230 00:12:44,200 --> 00:12:48,520 Speaker 1: on Twitter. I don't think this is compelling enough of 231 00:12:48,559 --> 00:12:51,000 Speaker 1: an offer to bring people over to Twitter. What I 232 00:12:51,080 --> 00:12:53,679 Speaker 1: think this is more about are the content creators on 233 00:12:53,840 --> 00:12:57,720 Speaker 1: Twitter that have amassed huge followings, of which there are many, 234 00:12:58,120 --> 00:13:00,640 Speaker 1: many of whom have built businesses off of that, just 235 00:13:00,760 --> 00:13:03,719 Speaker 1: putting in elsewhere, And if I'm there, I'm struggling of like, 236 00:13:03,800 --> 00:13:05,800 Speaker 1: oh my gosh, I've got all these followers here and 237 00:13:05,880 --> 00:13:07,800 Speaker 1: now I can capitalize on that here. But I don't 238 00:13:07,840 --> 00:13:10,120 Speaker 1: trust this product. Do I think this is bringing creators 239 00:13:10,160 --> 00:13:12,360 Speaker 1: over to Twitter? No? I think there's other options to 240 00:13:12,800 --> 00:13:16,760 Speaker 1: provide subscription Obviously, Patreon comes to mind. Even Meta has 241 00:13:16,800 --> 00:13:19,280 Speaker 1: a subscription offering, So there's other places to build a 242 00:13:19,360 --> 00:13:23,280 Speaker 1: subscription service. You know, Lauren with your jelly Smack corporate 243 00:13:23,320 --> 00:13:26,360 Speaker 1: development hat on, create an upload podcast hat or even 244 00:13:26,440 --> 00:13:30,480 Speaker 1: your former Facebook now meta hat. How do you quantify 245 00:13:30,600 --> 00:13:35,680 Speaker 1: the Elon Musk effect because he has one. Oh my gosh, 246 00:13:35,880 --> 00:13:37,480 Speaker 1: that's I don't know if we have enough time for that. 247 00:13:37,720 --> 00:13:41,360 Speaker 1: Here's what I'll say about this. You know, you can't 248 00:13:41,360 --> 00:13:43,480 Speaker 1: deny you've got an innovator there, right, Like I think 249 00:13:43,480 --> 00:13:47,040 Speaker 1: about payments just in itself. Right, You've got his PayPal background, right, 250 00:13:47,080 --> 00:13:49,720 Speaker 1: So you've got this, and I think he has despite 251 00:13:49,760 --> 00:13:52,240 Speaker 1: everything that's gone on, I think he's got this lure 252 00:13:52,280 --> 00:13:55,520 Speaker 1: about him. People still, you know, sort of worship him 253 00:13:55,559 --> 00:13:57,559 Speaker 1: in terms of what he's built. You can't you cannot 254 00:13:57,640 --> 00:14:00,800 Speaker 1: deny him as an innovator. So there's gonna be those 255 00:14:00,840 --> 00:14:04,640 Speaker 1: folks that are going to follow him wherever he goes. Right. 256 00:14:04,760 --> 00:14:07,000 Speaker 1: I think that there's that, and I think that that 257 00:14:07,320 --> 00:14:10,839 Speaker 1: is sort of invaluable in a certain sense, and why 258 00:14:10,880 --> 00:14:13,280 Speaker 1: Twitter still has legs and people are still hanging on. 259 00:14:13,440 --> 00:14:15,160 Speaker 1: That's why we're talking about him right now, right, It's 260 00:14:15,160 --> 00:14:16,920 Speaker 1: why we're hanging on to every word because we know 261 00:14:17,200 --> 00:14:19,680 Speaker 1: there's genius there. It's just that he's never run a 262 00:14:19,720 --> 00:14:23,240 Speaker 1: platform like this, and having been at a platform obviously similar. 263 00:14:23,680 --> 00:14:27,200 Speaker 1: You know, I was shocked how much Facebook can break 264 00:14:27,320 --> 00:14:28,880 Speaker 1: when I was there, I was like, what do you mean, 265 00:14:29,000 --> 00:14:31,560 Speaker 1: it doesn't work sometimes these platforms are so buggy and 266 00:14:31,600 --> 00:14:33,120 Speaker 1: they break all the time, and he's gotten rid of 267 00:14:33,200 --> 00:14:36,640 Speaker 1: all of the infrastructure there by which to support this basically, 268 00:14:37,000 --> 00:14:39,240 Speaker 1: and so I feel like there's just some basic, fundamental 269 00:14:39,320 --> 00:14:40,960 Speaker 1: things that he needs to do before he builds this. 270 00:14:41,040 --> 00:14:43,680 Speaker 1: But I want in some ways, I want this to 271 00:14:43,720 --> 00:14:47,280 Speaker 1: work because I think that he is such a genius 272 00:14:47,360 --> 00:14:49,000 Speaker 1: that he could bring to this product. It's just a 273 00:14:49,040 --> 00:14:52,000 Speaker 1: matter of whether or not they can support it. So quantifiable, 274 00:14:52,120 --> 00:14:57,760 Speaker 1: I mean, I think it's in some ways invaluable and undetermined. Caroline. 275 00:14:57,800 --> 00:15:00,280 Speaker 1: One thing that really sit out to me, and that's bass. 276 00:15:00,560 --> 00:15:03,360 Speaker 1: The other night is Elon Musk talking about how the 277 00:15:03,440 --> 00:15:07,440 Speaker 1: ad slowdown was impacting their competitors, not just Twitter, and 278 00:15:07,560 --> 00:15:09,960 Speaker 1: he kind of really labored that point. And on this show, 279 00:15:10,040 --> 00:15:13,800 Speaker 1: right Caroline, think substack, Yeah, we see people making moves 280 00:15:14,040 --> 00:15:16,600 Speaker 1: And to that point, Lauren, we made the idea with 281 00:15:16,720 --> 00:15:19,520 Speaker 1: Sarah that substacks going into notes, they're looking more like 282 00:15:19,600 --> 00:15:24,000 Speaker 1: Twitter Twitters in some way sort of shadow banning people 283 00:15:24,040 --> 00:15:28,440 Speaker 1: who put substack links in. And where are your people 284 00:15:28,560 --> 00:15:31,360 Speaker 1: wanting to build community? Is it all about substack? Is 285 00:15:31,520 --> 00:15:34,320 Speaker 1: what do you need to be across all platforms. Well, 286 00:15:34,520 --> 00:15:36,840 Speaker 1: I mean that's fundamentally what Jolly Smacks are offering is right, 287 00:15:36,880 --> 00:15:38,600 Speaker 1: Like most creators at the end of the day are 288 00:15:38,960 --> 00:15:41,680 Speaker 1: experts in one, maybe two platforms, but they recognize that 289 00:15:41,760 --> 00:15:43,560 Speaker 1: there's a huge audience out there that may not be 290 00:15:43,720 --> 00:15:46,720 Speaker 1: just sort of servicing. So there's we are interested. You know, 291 00:15:47,320 --> 00:15:49,920 Speaker 1: we're really video focused, so we're really focused on more 292 00:15:50,040 --> 00:15:51,760 Speaker 1: the creators that I sort of we've sort of worked 293 00:15:51,800 --> 00:15:53,720 Speaker 1: with or really focus on the video platforms. I understand 294 00:15:53,760 --> 00:15:55,840 Speaker 1: that Twitter that supposedly, I mean he said, you could 295 00:15:55,840 --> 00:15:58,480 Speaker 1: be doing our sorts of things, including video on this subscription, 296 00:15:58,520 --> 00:16:02,640 Speaker 1: but it's really thinking about from Pinterest and Spotify. Those 297 00:16:02,680 --> 00:16:05,440 Speaker 1: we're seeing a lot of interest in as they seem 298 00:16:05,560 --> 00:16:10,280 Speaker 1: much more stable and the opportunity is really exciting on 299 00:16:10,520 --> 00:16:11,920 Speaker 1: those kind of platforms, and we're single a lot of 300 00:16:12,000 --> 00:16:17,360 Speaker 1: interest there. Friendly too, dare I say, la, thank you 301 00:16:17,720 --> 00:16:21,120 Speaker 1: nice people. You know, we thank you for being a 302 00:16:21,240 --> 00:16:31,920 Speaker 1: nice person on our show. We appreciate it. Amazon Web 303 00:16:32,000 --> 00:16:35,280 Speaker 1: Services is making good on its missions bring Januative AI 304 00:16:35,560 --> 00:16:38,640 Speaker 1: to cloud customers. I spoke to CEO Adam Slipski about 305 00:16:38,680 --> 00:16:41,880 Speaker 1: AI integration on AWS and Y. There's such an emphasis 306 00:16:41,920 --> 00:16:44,560 Speaker 1: on the price performance of this tech before it's launched. 307 00:16:44,720 --> 00:16:48,080 Speaker 1: So we're confident that the Amazon Titan models that we 308 00:16:48,120 --> 00:16:53,120 Speaker 1: announced today, which are Amazon's own branded foundation models, which 309 00:16:53,160 --> 00:16:56,440 Speaker 1: of course will be available as part of Amazon Bedrock 310 00:16:56,520 --> 00:17:01,120 Speaker 1: along with leading third party startups, that the Amazon Titan 311 00:17:01,200 --> 00:17:03,480 Speaker 1: models will be really exciting and are going to power 312 00:17:03,760 --> 00:17:07,280 Speaker 1: both Amazon internal use cases as well as being available 313 00:17:07,440 --> 00:17:11,720 Speaker 1: to our external customers to build a generative AI solutions 314 00:17:11,800 --> 00:17:15,919 Speaker 1: and applications on top of us. Adam, you've played your 315 00:17:15,960 --> 00:17:18,120 Speaker 1: hand in the field of generative AI. On the same 316 00:17:18,280 --> 00:17:20,879 Speaker 1: day that Andy Jats, CEO of The Broader Company, has 317 00:17:20,920 --> 00:17:23,240 Speaker 1: given his kind of outlook on the world, he talked 318 00:17:23,280 --> 00:17:27,800 Speaker 1: about AWS facing short term headwinds. How are you managing 319 00:17:27,880 --> 00:17:30,360 Speaker 1: those short term headwinds? What is the Adam Selipsky view 320 00:17:30,400 --> 00:17:33,040 Speaker 1: of the world macro speaking right now? Well, I don't 321 00:17:33,080 --> 00:17:36,240 Speaker 1: think it's any secret that there have been macroeconomic headwinds. 322 00:17:37,040 --> 00:17:41,720 Speaker 1: Companies and all sorts of different industries have seen slowdowns 323 00:17:41,800 --> 00:17:44,720 Speaker 1: or as you put a headwinds of different varieties. You know, 324 00:17:44,800 --> 00:17:48,159 Speaker 1: we're we're very confident in the kind of long term 325 00:17:48,200 --> 00:17:53,720 Speaker 1: outlook for AWS. Demand for the cloud remains strong. Customers 326 00:17:53,800 --> 00:17:56,360 Speaker 1: tell us that we remain as we always have been, 327 00:17:57,040 --> 00:17:59,560 Speaker 1: the leading cloud with the broadest set of capabilities and 328 00:17:59,640 --> 00:18:02,480 Speaker 1: the d set of features within each of our services, 329 00:18:03,240 --> 00:18:07,480 Speaker 1: with the leading security, leading operational performance of any cloud 330 00:18:07,520 --> 00:18:10,639 Speaker 1: in the world. So we feel very confident that we're 331 00:18:10,680 --> 00:18:13,479 Speaker 1: going to remain on a long term road to providing value, 332 00:18:13,480 --> 00:18:16,600 Speaker 1: and in the short term, we're really focused on continuing 333 00:18:16,680 --> 00:18:19,160 Speaker 1: to innovate in the areas that matter most to our customers, 334 00:18:19,400 --> 00:18:22,080 Speaker 1: such as general AI and such as bringing choice and 335 00:18:22,200 --> 00:18:26,000 Speaker 1: democrat democratization to that area, just like AWS it's always 336 00:18:26,040 --> 00:18:29,440 Speaker 1: done for Compute has always done for it, and of 337 00:18:29,560 --> 00:18:33,760 Speaker 1: course on helping our customers as they try and be 338 00:18:33,880 --> 00:18:36,760 Speaker 1: cost efficient and they try and tighten their ballots. We 339 00:18:36,880 --> 00:18:39,119 Speaker 1: don't mean away from that. We lean into that and 340 00:18:39,240 --> 00:18:41,359 Speaker 1: we say, let us work with you to help you 341 00:18:41,440 --> 00:18:43,880 Speaker 1: lower your costs because we know you need this right now. 342 00:18:44,600 --> 00:18:46,960 Speaker 1: Such great conversation and we thank you for that. And 343 00:18:47,000 --> 00:18:49,480 Speaker 1: it's time now for talking tech, because let's go broad 344 00:18:49,520 --> 00:18:53,000 Speaker 1: and let's look to Asia. Chinese President jijimpaing and reaffirming 345 00:18:53,119 --> 00:18:55,359 Speaker 1: is cool for China to be more self relying across 346 00:18:55,400 --> 00:18:58,080 Speaker 1: the range of industries, including science and technology. During a 347 00:18:58,160 --> 00:19:01,400 Speaker 1: trip to Southeast China with officials and called for quote 348 00:19:01,600 --> 00:19:06,359 Speaker 1: further steps to enhance independent innovation. Also in China, Blue Focus. 349 00:19:06,440 --> 00:19:08,800 Speaker 1: It's one of the country's best known media agencies and 350 00:19:08,840 --> 00:19:13,240 Speaker 1: actually plans to replace third party copywriters graphic designers the 351 00:19:13,320 --> 00:19:16,960 Speaker 1: chat chpt style AI system. It's happening. People. Reports say 352 00:19:17,000 --> 00:19:19,600 Speaker 1: that company has already reached out to local tech firms 353 00:19:19,920 --> 00:19:24,080 Speaker 1: to explore licensing technology, and the Justice Department is saying 354 00:19:24,119 --> 00:19:26,879 Speaker 1: that generative AI and other tech innovations may have been 355 00:19:26,920 --> 00:19:29,320 Speaker 1: released years ago in the United States if it wasn't 356 00:19:29,359 --> 00:19:32,880 Speaker 1: for Google's monopolized presence as a search engine. This comes 357 00:19:32,880 --> 00:19:35,800 Speaker 1: ahead of an antitrust suit against Google schedule to go 358 00:19:35,840 --> 00:19:46,000 Speaker 1: to trial in September. I'll come back to Blue Beag 359 00:19:46,040 --> 00:19:48,959 Speaker 1: Technology Caroline Hyde in New York alongside Ed Ludlover over 360 00:19:49,000 --> 00:19:51,360 Speaker 1: there in San Francisco. Let's check out on the market, said, 361 00:19:51,440 --> 00:19:54,400 Speaker 1: because we are seeing just the moon music, dialing back 362 00:19:54,440 --> 00:19:56,560 Speaker 1: on tech but ramping up in terms of the banking sector. 363 00:19:56,560 --> 00:19:58,280 Speaker 1: We're seeing now that's like one hundred off by eight 364 00:19:58,359 --> 00:20:00,240 Speaker 1: tenths of a percent. This is more about the acro 365 00:20:00,400 --> 00:20:04,920 Speaker 1: picture once again, some resiliently unfortunately in the pricing of 366 00:20:05,040 --> 00:20:07,560 Speaker 1: certain goods. The inflation not dialing back as quickly as 367 00:20:07,600 --> 00:20:09,680 Speaker 1: we'd hope, the Federal Reserve likely to have to keep 368 00:20:09,760 --> 00:20:11,960 Speaker 1: on looking at the US economy and flowing it down. 369 00:20:12,000 --> 00:20:14,320 Speaker 1: That's what the retail data showed us today. That of 370 00:20:14,359 --> 00:20:16,600 Speaker 1: course affects technology stocks. There's some people I've found a 371 00:20:16,600 --> 00:20:19,000 Speaker 1: financials up because JP Morgan came out with its numbers 372 00:20:19,160 --> 00:20:21,720 Speaker 1: and really benefited deposits coming in coming from the likes 373 00:20:21,760 --> 00:20:24,639 Speaker 1: of Silicon Valley Bank. Ultimately these banks doing better than 374 00:20:24,720 --> 00:20:26,680 Speaker 1: had been feared. We see a lift and I think 375 00:20:26,720 --> 00:20:29,840 Speaker 1: JP Morgan's up about seven percent two year yield rising. 376 00:20:29,880 --> 00:20:32,280 Speaker 1: I mean that also helps banks, doesn't it. Borrowing costs 377 00:20:32,320 --> 00:20:34,600 Speaker 1: on the rise. But this is a thirteen basis point move. 378 00:20:34,680 --> 00:20:37,359 Speaker 1: We're then still really pricing in what the Federal Reserve 379 00:20:37,480 --> 00:20:38,760 Speaker 1: is going to do. How much does it has to 380 00:20:38,840 --> 00:20:41,720 Speaker 1: tackle inflation? Move it on because I thought it was 381 00:20:41,800 --> 00:20:43,960 Speaker 1: inflationary hedge once upon a time, but ain't at the moment. 382 00:20:44,000 --> 00:20:45,480 Speaker 1: This is a risk, as said, But even as we 383 00:20:45,520 --> 00:20:47,400 Speaker 1: see tech stops coming off the boil, we don't see 384 00:20:47,440 --> 00:20:48,920 Speaker 1: that in the likes of eth We're still seeing it 385 00:20:49,000 --> 00:20:50,760 Speaker 1: holding up to its gains of the day. We're still 386 00:20:50,760 --> 00:20:53,320 Speaker 1: at the highest level since May twenty twenty two. All 387 00:20:53,400 --> 00:20:56,080 Speaker 1: of this coming after that all important upgrade earlier this weekend. 388 00:20:56,920 --> 00:20:59,480 Speaker 1: All right, Karl, let's bring in tag Incline co founder 389 00:20:59,520 --> 00:21:01,560 Speaker 1: in chief is as officer of Edge and Note, a 390 00:21:01,640 --> 00:21:05,920 Speaker 1: software development company behind the graph and indexing and query protocol, 391 00:21:06,080 --> 00:21:10,399 Speaker 1: organizing the world's open blockchain data and making open data 392 00:21:10,840 --> 00:21:16,440 Speaker 1: a public good. You are an instrumental name in blockchain industry, 393 00:21:17,119 --> 00:21:20,199 Speaker 1: regarded in terms of your understanding the underlying technology. Carriages 394 00:21:20,280 --> 00:21:23,760 Speaker 1: showed us one digital asset. What I'd like to ask 395 00:21:23,840 --> 00:21:26,320 Speaker 1: you is to explain to us the momentum right now 396 00:21:26,680 --> 00:21:30,760 Speaker 1: that is in bitcoin ether is that coming from a 397 00:21:30,880 --> 00:21:36,200 Speaker 1: renewed enthusiasm that the underlying blockchain technology is working, is progressing, 398 00:21:36,359 --> 00:21:40,399 Speaker 1: is moving forward. Absolutely, And with the Shanghai update that 399 00:21:40,480 --> 00:21:43,080 Speaker 1: we just saw, this is a massive milestone and that's 400 00:21:43,119 --> 00:21:45,840 Speaker 1: been in the works for seven years ad Proline, and 401 00:21:46,520 --> 00:21:48,960 Speaker 1: it's really is kind of a paradigm shift that we're seeing. 402 00:21:49,119 --> 00:21:52,240 Speaker 1: We're changing the way we coordinate and we incentivize that 403 00:21:52,320 --> 00:21:57,240 Speaker 1: coordination online and with this upgrade, it's just a massive 404 00:21:57,320 --> 00:22:01,480 Speaker 1: proof to the industry on what is past and it's 405 00:22:01,520 --> 00:22:03,879 Speaker 1: really exciting to see. But to your point, there are 406 00:22:04,000 --> 00:22:08,160 Speaker 1: so many different projects in the ecosystem. I think bitcoins 407 00:22:08,280 --> 00:22:11,280 Speaker 1: has very much proven itself in terms of a new 408 00:22:12,160 --> 00:22:15,600 Speaker 1: paradigm when it comes to monetary policy, a new system, 409 00:22:16,240 --> 00:22:18,520 Speaker 1: and Ethereum and the graph are very much in the 410 00:22:19,040 --> 00:22:23,639 Speaker 1: Web three decentralized Internet category. Before we dive into the 411 00:22:23,720 --> 00:22:27,479 Speaker 1: graph your first protocol, talk to us a little bit 412 00:22:27,560 --> 00:22:31,320 Speaker 1: about who's being drawn back in to the eight in particular. 413 00:22:31,720 --> 00:22:35,119 Speaker 1: Is it retail that's being tempted as an institutional interest, 414 00:22:35,280 --> 00:22:38,040 Speaker 1: is it just people are already committed, but you know, 415 00:22:38,320 --> 00:22:41,440 Speaker 1: helping amid pretty low liquidity at the moment. Yeah, So 416 00:22:41,560 --> 00:22:43,639 Speaker 1: many of us building in the industry, we kind of 417 00:22:43,840 --> 00:22:46,479 Speaker 1: look away from the market and we just focus on building. 418 00:22:46,600 --> 00:22:49,600 Speaker 1: And I think that this milestone accomplished with the Shanghai 419 00:22:49,800 --> 00:22:53,159 Speaker 1: upgrade and us moving to proof upstake with Ethereum is 420 00:22:53,200 --> 00:22:56,879 Speaker 1: a great example of that. So the builders have kept building. 421 00:22:57,359 --> 00:23:00,720 Speaker 1: Development is at an all time high. Now you're seeing 422 00:23:00,840 --> 00:23:02,240 Speaker 1: head of the market. There was a lot of fud 423 00:23:02,359 --> 00:23:06,080 Speaker 1: around because there was fifteen percent of eighth that was 424 00:23:06,160 --> 00:23:08,280 Speaker 1: state in the beacon chain that was not liquid. You 425 00:23:08,320 --> 00:23:11,479 Speaker 1: could not withdraw that. And now with this update, there 426 00:23:11,600 --> 00:23:13,280 Speaker 1: was a lot of fud around, a lot of people 427 00:23:13,280 --> 00:23:15,560 Speaker 1: would be dumping those coins, and actually block works were 428 00:23:15,680 --> 00:23:20,159 Speaker 1: ported today that deposits are actually higher than withdraws, with 429 00:23:20,960 --> 00:23:26,200 Speaker 1: eighteen thousand, five hundred eight being deposited more than withdraws. 430 00:23:26,240 --> 00:23:29,520 Speaker 1: So that's an exciting moment. So I think, you know, 431 00:23:29,560 --> 00:23:33,159 Speaker 1: when we saw eight slash BTC down twenty percent ahead 432 00:23:33,160 --> 00:23:36,280 Speaker 1: of this upgrade, so it's kind of the industry proving 433 00:23:36,440 --> 00:23:38,520 Speaker 1: proving a lot of people wrong take and you sort 434 00:23:38,560 --> 00:23:41,880 Speaker 1: of said you look away from prices, and I'm afraid 435 00:23:41,880 --> 00:23:43,359 Speaker 1: to say you probably have to look away from your 436 00:23:43,400 --> 00:23:45,440 Speaker 1: own token price to a certain degree GLT, because it 437 00:23:45,560 --> 00:23:48,120 Speaker 1: is swell off its highs and more than two dollars 438 00:23:48,160 --> 00:23:49,960 Speaker 1: all the way back in February twenty twenty one. I'm 439 00:23:49,960 --> 00:23:52,280 Speaker 1: sure many would say that was an extraordinary period in time. 440 00:23:52,400 --> 00:23:54,960 Speaker 1: But how much does it matter that olt coins perhaps 441 00:23:55,000 --> 00:23:57,080 Speaker 1: aren't participating in some of the rally that we've seen 442 00:23:57,160 --> 00:24:00,840 Speaker 1: of late in eighth in bitcoin? And what do you do? 443 00:24:01,200 --> 00:24:03,840 Speaker 1: Does it matter about the price of one's token when 444 00:24:03,840 --> 00:24:06,920 Speaker 1: you're trying to build an ecosystem. No, I think that 445 00:24:07,119 --> 00:24:09,960 Speaker 1: what's you know, GRT is a work utility token. So 446 00:24:10,119 --> 00:24:13,440 Speaker 1: the concept is that you actually buy it only to 447 00:24:13,560 --> 00:24:16,399 Speaker 1: use it in the network, and there's different roles and 448 00:24:16,480 --> 00:24:20,159 Speaker 1: again this comes back to the incentive around coordination and 449 00:24:20,240 --> 00:24:23,560 Speaker 1: coordinating online. So there are many different participants. You know, 450 00:24:23,960 --> 00:24:26,520 Speaker 1: hundreds of thousands of people across the ecosystem that are 451 00:24:26,560 --> 00:24:30,320 Speaker 1: participating in these protocols, and they're being compensated commensurate to 452 00:24:30,359 --> 00:24:32,560 Speaker 1: the value that they're putting in. And that's one of 453 00:24:32,600 --> 00:24:35,560 Speaker 1: the really powerful pieces beyond just kind of looking at 454 00:24:35,600 --> 00:24:38,440 Speaker 1: the market or the prices. Of course, these sorts of 455 00:24:38,480 --> 00:24:40,600 Speaker 1: protocols and you talk about the thousands using it and 456 00:24:41,280 --> 00:24:44,320 Speaker 1: the integration within depths such as unite walk and a 457 00:24:44,440 --> 00:24:47,040 Speaker 1: lot of this. The protocols is about access, isn't it 458 00:24:47,080 --> 00:24:51,560 Speaker 1: at the moment democratization. Yeah, so you've basically taken through 459 00:24:51,600 --> 00:24:53,320 Speaker 1: the graph. I want you to explain to us what 460 00:24:53,480 --> 00:24:56,000 Speaker 1: that is that you want people to be able to 461 00:24:57,200 --> 00:25:00,720 Speaker 1: publish open APIs contribute to the next work for it 462 00:25:00,840 --> 00:25:05,920 Speaker 1: to be I guess, an open access platform exactly. So 463 00:25:06,040 --> 00:25:08,960 Speaker 1: the graph is a marketplace where public data. So you 464 00:25:09,040 --> 00:25:11,639 Speaker 1: think in Web two you have one Google. In the 465 00:25:11,680 --> 00:25:14,600 Speaker 1: graph network, you have over four hundred quote unquote Googles 466 00:25:14,640 --> 00:25:17,920 Speaker 1: there's four hundred different companies all around the world operating 467 00:25:17,960 --> 00:25:21,119 Speaker 1: independently to serve queries. And when I say query, you 468 00:25:21,119 --> 00:25:24,840 Speaker 1: can think of search in the graph network for these applications. 469 00:25:24,960 --> 00:25:28,199 Speaker 1: And there's over seven hundred applications on the graph network 470 00:25:28,280 --> 00:25:31,000 Speaker 1: today and you pay for the usage of these applications 471 00:25:31,119 --> 00:25:34,480 Speaker 1: in GRT, and that is the point of GRT to 472 00:25:34,640 --> 00:25:37,800 Speaker 1: be used across these applications. And it's exciting to see 473 00:25:38,160 --> 00:25:42,119 Speaker 1: how many people are using these applications and it's at 474 00:25:42,160 --> 00:25:45,600 Speaker 1: all time high taken. I think one of the reasons 475 00:25:45,640 --> 00:25:47,480 Speaker 1: people are really excited about this is it's kind of 476 00:25:47,520 --> 00:25:51,320 Speaker 1: at the intersection of AI and crypto U and AI 477 00:25:52,320 --> 00:25:56,240 Speaker 1: startup an AI entrepreneur in that respect, I wouldn't say 478 00:25:56,280 --> 00:25:58,400 Speaker 1: that the graph is a quote unquote AI project. It's 479 00:25:58,520 --> 00:26:01,800 Speaker 1: very much about open data. But what's exciting around AI 480 00:26:02,040 --> 00:26:04,760 Speaker 1: and the intersection with the graph and Web three is 481 00:26:04,800 --> 00:26:07,760 Speaker 1: that you could imagine having like a chat GPT on 482 00:26:07,960 --> 00:26:11,800 Speaker 1: top of the graph with verifiable data and information. And 483 00:26:11,960 --> 00:26:16,720 Speaker 1: that's really an exciting opportunity because garbage in garbage out 484 00:26:16,800 --> 00:26:18,720 Speaker 1: even with AI, and now we can have really great 485 00:26:18,800 --> 00:26:22,399 Speaker 1: arguments around the garbage using AI technology. So if we 486 00:26:22,480 --> 00:26:25,760 Speaker 1: can verify that information, that's when it becomes really exciting. 487 00:26:25,840 --> 00:26:28,680 Speaker 1: And so that's something that the Semiotic team, one of 488 00:26:28,720 --> 00:26:31,720 Speaker 1: the core developers within the graph ecosystem, is actually looking 489 00:26:31,760 --> 00:26:35,080 Speaker 1: at and working on. But within the graph the indexers 490 00:26:35,119 --> 00:26:38,560 Speaker 1: do use many of them use machine learning today around 491 00:26:38,760 --> 00:26:42,960 Speaker 1: pricing queries. Caroline, I think on this program, you and I, 492 00:26:43,600 --> 00:26:46,359 Speaker 1: because we're in the markets, we're tracking the value of 493 00:26:46,400 --> 00:26:49,359 Speaker 1: any given time of a DUS asset, right. But actually, 494 00:26:49,440 --> 00:26:53,320 Speaker 1: what we've learned this week watch parties for Etherium is 495 00:26:53,400 --> 00:26:56,720 Speaker 1: that actually people are really closely following the technology, the 496 00:26:56,840 --> 00:27:00,679 Speaker 1: developments in the underlying technology, and that convers stations startings 497 00:27:00,720 --> 00:27:02,840 Speaker 1: creep back in. That's what this show is all about 498 00:27:02,920 --> 00:27:06,000 Speaker 1: as well, underlying technology and taken to that point, how 499 00:27:06,760 --> 00:27:09,879 Speaker 1: much does a regulatory environment impede some of the conversation 500 00:27:09,960 --> 00:27:14,040 Speaker 1: about underlying technology, particularly here in the US. Yeah, it's 501 00:27:14,080 --> 00:27:16,840 Speaker 1: definitely interesting to see the way the US has been 502 00:27:16,840 --> 00:27:20,560 Speaker 1: approaching the regulatory market. I think that they are there's 503 00:27:20,600 --> 00:27:23,760 Speaker 1: a chance that they are stifling innovation and pushing that overseas. 504 00:27:23,840 --> 00:27:25,639 Speaker 1: But I think one of the positives with some of 505 00:27:25,720 --> 00:27:30,880 Speaker 1: the regulatory crackdown is that it's pushing people towards transparent systems, 506 00:27:31,000 --> 00:27:35,880 Speaker 1: towards further decentralization, towards further censorship resistance, because this industry, 507 00:27:35,920 --> 00:27:39,320 Speaker 1: it's all about giving power and control back to individuals 508 00:27:39,440 --> 00:27:41,320 Speaker 1: as opposed to kind of locking it up in a 509 00:27:41,440 --> 00:27:44,440 Speaker 1: centralized company. And that's really powerful and I think the 510 00:27:44,600 --> 00:27:47,240 Speaker 1: faster we can get there, the better. And so the 511 00:27:47,359 --> 00:27:50,520 Speaker 1: regulatory environment is actually pushing the industry in that direction, 512 00:27:50,600 --> 00:27:53,280 Speaker 1: which is a positive. Taking great to have some time 513 00:27:53,320 --> 00:27:55,520 Speaker 1: with you, Thank you, thank you so much for having 514 00:27:55,640 --> 00:27:58,440 Speaker 1: taken find co founder and chief business officer over the 515 00:27:58,560 --> 00:28:04,600 Speaker 1: edge and node Ian well yep, coming up observa observability platform. 516 00:28:05,200 --> 00:28:08,800 Speaker 1: Sorry about that one. Honeycomb raises fifty million dollars even 517 00:28:08,840 --> 00:28:11,280 Speaker 1: as the VC landscape still rolling a little bit from 518 00:28:11,320 --> 00:28:14,480 Speaker 1: that SPB collapse and a broader downturn. More in that 519 00:28:14,640 --> 00:28:17,840 Speaker 1: next with CEO Christine Yen, ort to take a really 520 00:28:17,920 --> 00:28:20,320 Speaker 1: quick look at semi conductors. The socks off five pounds, 521 00:28:20,560 --> 00:28:23,080 Speaker 1: seven tenths of one percent. It is heading for a 522 00:28:23,160 --> 00:28:27,240 Speaker 1: second consecutive weekly decline. Mixed stories here right, there's optimism 523 00:28:27,320 --> 00:28:30,960 Speaker 1: in the commoditized memory space that we're addressing the glost. 524 00:28:31,280 --> 00:28:34,679 Speaker 1: But now with the run up Nvidia an aipowered rallies. 525 00:28:34,720 --> 00:28:37,919 Speaker 1: For example, We're starting to question valuations. We're pulling back 526 00:28:37,960 --> 00:28:40,280 Speaker 1: a little bit, down seven tenths to one percent on 527 00:28:40,360 --> 00:28:59,080 Speaker 1: the Philadelphia Semiconductor Index. This is Bloomberg all right. Time 528 00:28:59,120 --> 00:29:02,280 Speaker 1: for the vcuund up crypto startup cheer Network, which was 529 00:29:02,360 --> 00:29:05,400 Speaker 1: valued at about five hundred million dollars in twenty twenty one, 530 00:29:05,480 --> 00:29:08,440 Speaker 1: says it has moved a step closer to a USIPO 531 00:29:08,720 --> 00:29:12,560 Speaker 1: and confidentially submitted a draft registration statement to the SEC. 532 00:29:12,760 --> 00:29:16,840 Speaker 1: The IPO size and price range has not been determined yet. 533 00:29:17,120 --> 00:29:20,880 Speaker 1: And Astranis, the startup that builds geostationary satellites, has just 534 00:29:21,000 --> 00:29:24,160 Speaker 1: raised two hundred million dollars in a financing deal, valuing 535 00:29:24,200 --> 00:29:27,800 Speaker 1: the company at one point six billion dollars. That in 536 00:29:27,880 --> 00:29:30,360 Speaker 1: a round led by the growth fund of Andrews and Horowitz. 537 00:29:30,440 --> 00:29:33,200 Speaker 1: That's all according to a Bloomberg source. Meanwhile, the company 538 00:29:33,560 --> 00:29:37,920 Speaker 1: is preparing for its first ever launch this Saturday. And Carrow, 539 00:29:38,080 --> 00:29:41,480 Speaker 1: I've got a Friday treat for you. A chart, brand 540 00:29:41,760 --> 00:29:44,800 Speaker 1: new data set. Okay, this is the white line. The 541 00:29:44,920 --> 00:29:48,320 Speaker 1: Refinitive VC Index. Think of it as a proxy index 542 00:29:48,760 --> 00:29:52,840 Speaker 1: for VC companies investing in private startups, the valuation of 543 00:29:52,920 --> 00:29:55,440 Speaker 1: private startups, and this is some research that came out 544 00:29:55,440 --> 00:29:59,320 Speaker 1: from Bloomberg Intelligence overnight. Basically, when you look at the 545 00:29:59,400 --> 00:30:02,200 Speaker 1: lows of twenty eighteen and twenty twenty on the Nasdaq 546 00:30:02,240 --> 00:30:05,400 Speaker 1: one hundred, the public markets for the tech sector, we 547 00:30:05,600 --> 00:30:09,680 Speaker 1: see that VC index outperform. But something has changed year 548 00:30:09,720 --> 00:30:12,800 Speaker 1: to date where the NAZAC one hundred is up pretty 549 00:30:12,800 --> 00:30:17,040 Speaker 1: significantly sixteen seventeen percent, and that VC Refinitive Index is 550 00:30:17,120 --> 00:30:20,480 Speaker 1: trailing behind. I think that's really interesting that we've broken 551 00:30:20,560 --> 00:30:22,680 Speaker 1: away from that trend at a time where we have 552 00:30:23,080 --> 00:30:27,520 Speaker 1: kind of questioned financial conditions for private companies, valuations coming down, 553 00:30:27,840 --> 00:30:29,760 Speaker 1: the prospect of doing a down round. But it's a 554 00:30:29,800 --> 00:30:32,120 Speaker 1: brand new index. I love this chart. You can check 555 00:30:32,160 --> 00:30:35,680 Speaker 1: it out g hashtag BTV on the terminal and always 556 00:30:35,720 --> 00:30:39,280 Speaker 1: on bloom the Technology. Yeah. Well, let's continue with that 557 00:30:39,400 --> 00:30:41,680 Speaker 1: sort of juxtaposition between public and private and we can 558 00:30:41,760 --> 00:30:43,680 Speaker 1: dig a little bit deeper now and into the venture 559 00:30:43,760 --> 00:30:47,280 Speaker 1: capital era. You say is lagging behind tech, but some 560 00:30:47,680 --> 00:30:49,880 Speaker 1: people and then you just run through a few are 561 00:30:49,920 --> 00:30:52,480 Speaker 1: still managing to get their funding in in spite of 562 00:30:52,520 --> 00:30:55,160 Speaker 1: this economic termol For today's VC spotlight that's bringing in 563 00:30:55,240 --> 00:30:58,240 Speaker 1: Honeycomb CEO Christine Yen, who's on to talk about a 564 00:30:58,320 --> 00:31:00,920 Speaker 1: series dfunding round that you did fifty million dollars in 565 00:31:00,960 --> 00:31:05,240 Speaker 1: the bank, and what exactly how hard was the environment 566 00:31:05,280 --> 00:31:09,760 Speaker 1: you brought on investors that you hadn't passed insight for example, 567 00:31:10,160 --> 00:31:12,800 Speaker 1: were they willing to be writing checks for companies such 568 00:31:12,840 --> 00:31:16,920 Speaker 1: as yours in this environment? Short enter, Yes, they're absolutely 569 00:31:16,960 --> 00:31:22,479 Speaker 1: willing to. I recognize tricky environment right now, not one 570 00:31:22,520 --> 00:31:25,760 Speaker 1: where i'd recommend folks go, you know, running out there 571 00:31:25,800 --> 00:31:28,240 Speaker 1: to try to raise around. But the fact of the 572 00:31:28,320 --> 00:31:32,240 Speaker 1: matter is we were growing company in a huge space. 573 00:31:33,440 --> 00:31:36,200 Speaker 1: Last year really was the year where it was clears 574 00:31:36,200 --> 00:31:38,160 Speaker 1: of ability was hitting the mainstream and we were the 575 00:31:38,240 --> 00:31:42,760 Speaker 1: leaders in this space. And so for us, the round honestly, 576 00:31:42,840 --> 00:31:47,760 Speaker 1: it's an opportunistic round and came together quite quickly and 577 00:31:48,360 --> 00:31:51,160 Speaker 1: religious makes me grateful for the continued support from our 578 00:31:51,280 --> 00:31:55,000 Speaker 1: existing investors. Scale bench is another one headline as well, 579 00:31:55,160 --> 00:31:57,320 Speaker 1: So I love that you sort of tell us that 580 00:31:57,400 --> 00:32:00,760 Speaker 1: this was opportunistic, opportunistic to what you say is the 581 00:32:00,840 --> 00:32:04,640 Speaker 1: best observability tooling for your software engineering teams. So what 582 00:32:04,800 --> 00:32:06,920 Speaker 1: exactly do you do? How are you helping the customers 583 00:32:06,960 --> 00:32:10,120 Speaker 1: that were currently shining light on Slack and head of Fresh. Yeah. 584 00:32:10,200 --> 00:32:14,360 Speaker 1: In the simplest terms, we help engineering teams understand why 585 00:32:14,480 --> 00:32:17,280 Speaker 1: their software is not behaving the way that they expect. 586 00:32:18,480 --> 00:32:22,080 Speaker 1: You flash some great logos up there, thank you. Vanguard, 587 00:32:22,160 --> 00:32:26,480 Speaker 1: for example, used us to help figure out why the 588 00:32:26,720 --> 00:32:29,480 Speaker 1: one of the one of their pages on their personal Investors' 589 00:32:29,480 --> 00:32:33,520 Speaker 1: website was not loading. Slack uses us to figure out 590 00:32:33,640 --> 00:32:37,479 Speaker 1: why some of their their fixes don't get released as 591 00:32:37,520 --> 00:32:42,240 Speaker 1: quickly as they expect. In software, there's always a slight 592 00:32:42,360 --> 00:32:44,960 Speaker 1: difference between the way that you code, you think that 593 00:32:45,080 --> 00:32:47,520 Speaker 1: code will behave when you have it in your head, 594 00:32:48,040 --> 00:32:50,240 Speaker 1: versus what it's like in front of real users. And 595 00:32:50,440 --> 00:32:54,160 Speaker 1: we help all these engineering teams shorten that shorten that 596 00:32:54,240 --> 00:32:56,720 Speaker 1: distance and make sure that what they think they're putting 597 00:32:56,720 --> 00:33:00,480 Speaker 1: out there is what their users are experiencing. Hey, Christine 598 00:33:00,520 --> 00:33:02,520 Speaker 1: and our audience on bloom Bag Technology. There are so 599 00:33:02,640 --> 00:33:05,600 Speaker 1: many founders out there with companies much smaller than yours, 600 00:33:05,680 --> 00:33:08,320 Speaker 1: and they'll see that you were able to raise this money. 601 00:33:08,400 --> 00:33:11,800 Speaker 1: You've just explained the problem that you're working on in 602 00:33:11,880 --> 00:33:15,480 Speaker 1: the addressable market. How do you use the funds? Tell 603 00:33:15,560 --> 00:33:17,280 Speaker 1: us about the size of your business, how are you 604 00:33:17,360 --> 00:33:22,959 Speaker 1: going to manage your longevity and runway? We are about 605 00:33:23,520 --> 00:33:27,200 Speaker 1: size of the business, solid growth stage. In terms of headcount, 606 00:33:27,240 --> 00:33:28,880 Speaker 1: we have maybe one hundred and sixty one hundred and 607 00:33:28,920 --> 00:33:32,800 Speaker 1: seventy folks. You know, looking forward, we're really excited to 608 00:33:32,880 --> 00:33:36,520 Speaker 1: use some of this capital to expand Geo's investment ecosystem 609 00:33:37,680 --> 00:33:40,880 Speaker 1: and really just be able to continue committing to staying 610 00:33:40,920 --> 00:33:43,960 Speaker 1: on the bleeding edge of what's possible in the space 611 00:33:44,040 --> 00:33:48,440 Speaker 1: by investing in new exciting tech frontiers. You know. Really, 612 00:33:48,640 --> 00:33:52,840 Speaker 1: I think we as a company tend to be fairly 613 00:33:52,920 --> 00:33:57,080 Speaker 1: pragmatic in our spend. That is really what helped us 614 00:33:57,120 --> 00:34:01,920 Speaker 1: weather the last couple of years, not just chasing high 615 00:34:01,960 --> 00:34:05,840 Speaker 1: valuations and running the risk of a down round. This 616 00:34:06,000 --> 00:34:07,800 Speaker 1: is an upround, which we're all very happy about it. 617 00:34:08,600 --> 00:34:13,560 Speaker 1: And I think our focus has always been build a 618 00:34:13,600 --> 00:34:16,840 Speaker 1: great product, build a strong business, build a company our 619 00:34:16,880 --> 00:34:18,920 Speaker 1: people are proud to have been a part of. And 620 00:34:21,120 --> 00:34:22,920 Speaker 1: it is a little too glib to say that the 621 00:34:22,960 --> 00:34:26,040 Speaker 1: rest will follow, but if you keep your focus on 622 00:34:26,120 --> 00:34:31,080 Speaker 1: those things that the market is just another tool to 623 00:34:31,239 --> 00:34:36,960 Speaker 1: continue achieving those goals. Christine, you formerly were a senior 624 00:34:37,040 --> 00:34:40,759 Speaker 1: software engineer at Facebook now known as a lecture of course, 625 00:34:40,840 --> 00:34:43,680 Speaker 1: and when I was at startup Grind earlier this week, 626 00:34:43,800 --> 00:34:48,480 Speaker 1: we were discussing layoffs and the opportunity that layoffs can 627 00:34:48,760 --> 00:34:51,080 Speaker 1: can offer. Are you going out there to kind of 628 00:34:51,200 --> 00:34:54,759 Speaker 1: hire some talent from your former employer that may now 629 00:34:54,880 --> 00:34:59,279 Speaker 1: be on the market given that money you raised. Yes, some, 630 00:35:00,360 --> 00:35:03,640 Speaker 1: but as with everyone, we are doing it pragmatically, thoughtfully 631 00:35:04,120 --> 00:35:07,400 Speaker 1: with an eye to managing cost and efficiency. But we are, 632 00:35:07,920 --> 00:35:10,719 Speaker 1: we are hiring. We're continuing to do really exciting work 633 00:35:10,920 --> 00:35:15,360 Speaker 1: on the bleeding edge of observability and these technology and 634 00:35:15,480 --> 00:35:17,680 Speaker 1: we make a real impact in the lives of our 635 00:35:17,719 --> 00:35:21,960 Speaker 1: customers and their software engineering practices. So you know, every 636 00:35:23,000 --> 00:35:25,840 Speaker 1: door open. When the door closes, another door opens, and 637 00:35:25,960 --> 00:35:28,360 Speaker 1: we're really excited to continue building the best team that 638 00:35:28,440 --> 00:35:30,560 Speaker 1: we can to build the breast product and service that 639 00:35:30,600 --> 00:35:33,600 Speaker 1: we can. Caroline is so interesting to get the real 640 00:35:33,840 --> 00:35:36,800 Speaker 1: term perspectives of a founder CEO. The other thing that 641 00:35:36,920 --> 00:35:38,800 Speaker 1: you know, I was discussing as startup Grind is the 642 00:35:38,920 --> 00:35:41,640 Speaker 1: idea that not everyone is in San Francisco or the 643 00:35:41,680 --> 00:35:44,399 Speaker 1: Bay Area. People were there from all around the world. Yeah, 644 00:35:44,400 --> 00:35:48,080 Speaker 1: and nook. Christina satin Reno right now, how are you 645 00:35:48,239 --> 00:35:50,680 Speaker 1: building a team? Are you building it in person? Are 646 00:35:50,719 --> 00:35:54,000 Speaker 1: you're building it in Reno, You're building it globally? How 647 00:35:54,080 --> 00:35:56,000 Speaker 1: do you see the new world in which we live 648 00:35:56,040 --> 00:35:58,959 Speaker 1: in and ultimately waiting up at the best engineering talent. 649 00:36:00,120 --> 00:36:03,239 Speaker 1: We are largely concentrated in the US and Canada. We've 650 00:36:03,320 --> 00:36:07,560 Speaker 1: got some folks in the UK. When we were actually 651 00:36:07,560 --> 00:36:09,879 Speaker 1: we actually had aspirations to be a distributed company even 652 00:36:09,920 --> 00:36:14,000 Speaker 1: before COVID and the you know, shifting to remote work 653 00:36:14,560 --> 00:36:18,000 Speaker 1: was just hitting an accelerator on plans that we already 654 00:36:18,000 --> 00:36:21,440 Speaker 1: had in place. I actually looked recently and I'm surprised 655 00:36:21,520 --> 00:36:25,080 Speaker 1: to find that two thirds of our company are located 656 00:36:25,200 --> 00:36:29,160 Speaker 1: out of traditional tech hubs, sorry, outside of traditional tech hubs. 657 00:36:30,080 --> 00:36:32,680 Speaker 1: And it means that when we are able to come together, 658 00:36:32,800 --> 00:36:39,120 Speaker 1: it's folks from Utah and Tennessee and Ohio. And it's 659 00:36:39,320 --> 00:36:42,640 Speaker 1: wonderful to be able to tap into a talent pool. 660 00:36:42,719 --> 00:36:45,520 Speaker 1: That is, it doesn't have to be concentrated in a 661 00:36:45,560 --> 00:36:48,640 Speaker 1: particular GEO. Time zones are a little harder. We're working 662 00:36:48,680 --> 00:36:53,800 Speaker 1: around that, but I think remote work is certainly what 663 00:36:54,560 --> 00:36:58,640 Speaker 1: we're committing on committing to Christine, you founded this business 664 00:36:58,719 --> 00:37:01,360 Speaker 1: because your time at face that you recognize the IT 665 00:37:01,719 --> 00:37:04,200 Speaker 1: landscape was changing. I want to end on asking you 666 00:37:04,360 --> 00:37:07,279 Speaker 1: what's changing in technology right now that's a drive for 667 00:37:07,360 --> 00:37:10,120 Speaker 1: your company? Is it AI for example, and all the 668 00:37:10,239 --> 00:37:14,640 Speaker 1: data conversation about the inputs I think in terms of 669 00:37:14,840 --> 00:37:18,480 Speaker 1: driving the company. The way that we build software has 670 00:37:18,600 --> 00:37:21,480 Speaker 1: changed dramatically in the last five or ten years. With 671 00:37:22,040 --> 00:37:26,960 Speaker 1: trends like Cabernetti's microservices server lest technologies. You have this 672 00:37:27,120 --> 00:37:31,480 Speaker 1: explosion of complexity in any sort of architecture diagram on 673 00:37:31,640 --> 00:37:35,040 Speaker 1: how logic flows through a system. With that increase in 674 00:37:35,080 --> 00:37:39,319 Speaker 1: complexity comes with a different set of expectations for any 675 00:37:39,360 --> 00:37:42,440 Speaker 1: tools like ours that are meant to make sense of 676 00:37:42,560 --> 00:37:45,920 Speaker 1: that for a selfware engineering team. So that trend, those 677 00:37:45,960 --> 00:37:52,920 Speaker 1: trends continuing to grow, crest and make selfware engineering teams 678 00:37:53,280 --> 00:37:57,799 Speaker 1: life's difficult. AI is definitely an interesting area we've got 679 00:37:57,880 --> 00:38:01,799 Speaker 1: our ion. I think that there are as with any 680 00:38:01,840 --> 00:38:06,759 Speaker 1: technology it could be there are cases where it can 681 00:38:06,800 --> 00:38:08,640 Speaker 1: be misapplied, and there are cases where it can be 682 00:38:08,760 --> 00:38:12,680 Speaker 1: perfectly applied. And you know, in our world, if we 683 00:38:12,800 --> 00:38:17,440 Speaker 1: make a wrong if our AI attempts make a wrong choice, 684 00:38:18,480 --> 00:38:21,560 Speaker 1: it either risks not waking in an engineer up when 685 00:38:21,640 --> 00:38:23,400 Speaker 1: the software is burning down in the middle of the night. 686 00:38:23,880 --> 00:38:27,960 Speaker 1: Um or it risks waking engineers up in the middle 687 00:38:27,960 --> 00:38:29,279 Speaker 1: of the night when they don't need to be in 688 00:38:29,400 --> 00:38:32,600 Speaker 1: burning them out. So we are trying to be very 689 00:38:32,680 --> 00:38:37,960 Speaker 1: thoughtful about where we where we ask software to make 690 00:38:38,040 --> 00:38:41,360 Speaker 1: decisions and instead are more interested in how can we 691 00:38:41,760 --> 00:38:46,640 Speaker 1: help humans be better versions of themselves? Y mantra. One 692 00:38:46,680 --> 00:38:50,000 Speaker 1: of our one of our folks that I'm borrowing is 693 00:38:50,120 --> 00:38:54,080 Speaker 1: we want to build mecca suits, not robots, and I 694 00:38:54,239 --> 00:38:58,720 Speaker 1: that augmented. I'm calling the conversation. Thank you, hunting Kime Ceo, 695 00:38:58,880 --> 00:39:03,440 Speaker 1: Christine Enna. It is going viral. The Coachella Festival is 696 00:39:03,560 --> 00:39:06,440 Speaker 1: upon us, Bad Bunny and Black Pink. Frank Ocean from 697 00:39:06,480 --> 00:39:09,160 Speaker 1: hersonal Favorite headlining the festival. There's actually at a polo 698 00:39:09,239 --> 00:39:11,239 Speaker 1: club in California, But it's not all about the music 699 00:39:11,320 --> 00:39:13,680 Speaker 1: in my life, right, Yeah, you don't even need to go. 700 00:39:13,840 --> 00:39:16,240 Speaker 1: If you're a fortnight player, you can experience it virtually 701 00:39:16,320 --> 00:39:18,600 Speaker 1: this year. Yeah, what about YouTube? If you've seen this, 702 00:39:18,760 --> 00:39:22,239 Speaker 1: they're dubbing it couchella. You're going to do that couchella 703 00:39:23,239 --> 00:39:26,160 Speaker 1: that does it. From this edition of Bloomberg Technology from 704 00:39:26,239 --> 00:39:28,360 Speaker 1: New York. From San Francisco. This is Bloomberg.