1 00:00:01,720 --> 00:00:06,960 Speaker 1: From Bahart where Innovation, money and power Collie in Silicon Valley, Nbon. 2 00:00:07,360 --> 00:00:11,360 Speaker 2: This is Bloomberg Technology with Caroline Hyde and Ed Ludlow. 3 00:00:24,560 --> 00:00:27,520 Speaker 3: I'm Caroline Heinder Bloomswelta Quarters in New York and I'm 4 00:00:27,640 --> 00:00:29,080 Speaker 3: Ed Ludlow in San Francisco. 5 00:00:29,400 --> 00:00:31,400 Speaker 4: This is Bloomberg Technology coming up. 6 00:00:31,440 --> 00:00:34,480 Speaker 3: Yet more earnings courage for you. Ahead will break down 7 00:00:34,520 --> 00:00:36,720 Speaker 3: all you need to know about. Cisco is the largest 8 00:00:36,720 --> 00:00:39,360 Speaker 3: makro of computer networking equipment, and it is tumbling after 9 00:00:39,360 --> 00:00:39,920 Speaker 3: its numbers. 10 00:00:40,960 --> 00:00:43,239 Speaker 5: And we'll have more on Ali Barber's results as the 11 00:00:43,280 --> 00:00:47,440 Speaker 5: e commerce giant falls after abruptly ending a planned spinoff 12 00:00:47,560 --> 00:00:48,480 Speaker 5: of its cloud unit. 13 00:00:48,560 --> 00:00:50,159 Speaker 4: Details ahead class Apex. 14 00:00:50,200 --> 00:00:53,080 Speaker 3: It continues in San Francisco, tex CEO's They Dying with 15 00:00:53,240 --> 00:00:56,880 Speaker 3: China's President will bring you the takeaways from the executive's dinner, 16 00:00:57,240 --> 00:00:59,560 Speaker 3: but first let's check in on these markets. The takeaways 17 00:00:59,560 --> 00:01:02,160 Speaker 3: are what a little bit of moon music shifting In 18 00:01:02,240 --> 00:01:04,160 Speaker 3: terms of the rampant rally, we've seen NASAC off by 19 00:01:04,160 --> 00:01:05,680 Speaker 3: some three tenths of percent on the day. 20 00:01:05,920 --> 00:01:08,120 Speaker 6: We actually had some pretty well. 21 00:01:08,160 --> 00:01:11,520 Speaker 3: Depressing, shall we say, macro economic data. But is that 22 00:01:11,560 --> 00:01:13,520 Speaker 3: good news in terms of whether the federal Reserve will 23 00:01:13,520 --> 00:01:15,480 Speaker 3: go in terms of interest rates, many feeling that the 24 00:01:15,560 --> 00:01:17,639 Speaker 3: jobless claims on the rise, Many feeling that the factory 25 00:01:17,680 --> 00:01:18,720 Speaker 3: output on the downward. 26 00:01:19,080 --> 00:01:19,720 Speaker 4: Well, all of. 27 00:01:19,680 --> 00:01:21,480 Speaker 3: That speaks to the fact that the federal Reserve cannot 28 00:01:21,520 --> 00:01:23,600 Speaker 3: hike yet again, and indeed, maybe we'll see cuts in 29 00:01:23,600 --> 00:01:25,560 Speaker 3: the second half of next year. We therefore see a 30 00:01:25,560 --> 00:01:27,240 Speaker 3: bid coming into the bond market. We're off by some 31 00:01:27,280 --> 00:01:30,800 Speaker 3: six basis points. Looking at Brent crude really down four 32 00:01:30,840 --> 00:01:33,080 Speaker 3: point five percent, let's call it this. As we see 33 00:01:33,120 --> 00:01:35,039 Speaker 3: the inventories build up. That's more of a signal of 34 00:01:35,040 --> 00:01:38,399 Speaker 3: maybe cooling demand. What does that mean about global economic growth? 35 00:01:38,480 --> 00:01:40,039 Speaker 3: Have a look at what's happening in terms of our 36 00:01:40,120 --> 00:01:42,720 Speaker 3: risk asset of choice. I'm looking at bitcoin and still 37 00:01:42,760 --> 00:01:45,720 Speaker 3: we trade within this general thirty six thousand dollars level, 38 00:01:46,000 --> 00:01:48,080 Speaker 3: but we're off by some three percent on the day. 39 00:01:48,160 --> 00:01:49,720 Speaker 6: And what if you've gone in terms of the micro. 40 00:01:50,280 --> 00:01:52,720 Speaker 5: Well, in the context of China, it's both the micro 41 00:01:52,880 --> 00:01:53,520 Speaker 5: and the macro. 42 00:01:53,720 --> 00:01:55,120 Speaker 4: This is shares that Ali Barber. 43 00:01:55,240 --> 00:01:58,640 Speaker 5: The news is that they have decided not to spin 44 00:01:58,680 --> 00:02:02,120 Speaker 5: off their cloud unit. Commentary is that they have been 45 00:02:02,200 --> 00:02:06,720 Speaker 5: impacted by US technology ker export curbs. We're going to 46 00:02:06,760 --> 00:02:08,919 Speaker 5: dig into that later in the program with our reporters 47 00:02:08,960 --> 00:02:09,440 Speaker 5: on both the. 48 00:02:09,400 --> 00:02:10,640 Speaker 4: Macro and micro China. 49 00:02:10,880 --> 00:02:13,640 Speaker 5: For the ADRs of Ali Baba, the US listed shares 50 00:02:13,880 --> 00:02:16,239 Speaker 5: on track for their biggest drop in more than a year. 51 00:02:16,280 --> 00:02:18,799 Speaker 5: We'll get very specific in that later in the show. 52 00:02:18,840 --> 00:02:21,000 Speaker 5: Here in the US, Cisco, that is the name that 53 00:02:21,040 --> 00:02:23,680 Speaker 5: we are looking at. They gave this forecast for the 54 00:02:23,680 --> 00:02:27,519 Speaker 5: fiscal second quarter ending in January that was well below 55 00:02:27,800 --> 00:02:31,520 Speaker 5: street expectations. What Cisco said was, this is not macroeconomic 56 00:02:31,960 --> 00:02:36,040 Speaker 5: pressures or headwinds. They have big enterprise customers working through 57 00:02:36,080 --> 00:02:39,560 Speaker 5: backlogs and networking equipment and that's why they're not ordering. 58 00:02:39,560 --> 00:02:43,880 Speaker 5: But those orders should re accelerate. Do we buy what 59 00:02:43,960 --> 00:02:45,080 Speaker 5: Chuck Robbins is saying? 60 00:02:45,160 --> 00:02:45,760 Speaker 7: Joining us now? 61 00:02:45,800 --> 00:02:50,000 Speaker 5: Pyper Sandler's senior research analyst, Jim Fish neutral rating on 62 00:02:50,040 --> 00:02:52,920 Speaker 5: Cisco fifty dollars price target. I was reading your note and, 63 00:02:52,960 --> 00:02:54,360 Speaker 5: as far as I can tell you, one of the 64 00:02:54,440 --> 00:02:58,720 Speaker 5: few that basically is calling a downturn in this networking 65 00:02:58,760 --> 00:02:59,520 Speaker 5: equipment market. 66 00:02:59,560 --> 00:03:00,400 Speaker 4: What was your takeaway? 67 00:03:01,600 --> 00:03:04,440 Speaker 8: Yeah, Caroline, ed great to chat with you again. It 68 00:03:04,440 --> 00:03:06,280 Speaker 8: feels like it's been only about a month since we 69 00:03:06,360 --> 00:03:10,080 Speaker 8: caught up on Cisco given the splug field. But look, 70 00:03:10,720 --> 00:03:14,000 Speaker 8: I think there's we agreed and we don't agree at 71 00:03:14,040 --> 00:03:16,760 Speaker 8: the same time with what Cisco's saying. Now our checks 72 00:03:16,880 --> 00:03:20,200 Speaker 8: heading into this print and even some of its peers 73 00:03:20,240 --> 00:03:24,720 Speaker 8: on Calendar like Arista and Juniper and F five and 74 00:03:24,760 --> 00:03:27,280 Speaker 8: sort of the networking space overall, we started to see 75 00:03:27,280 --> 00:03:28,639 Speaker 8: a downtick and sort of. 76 00:03:28,560 --> 00:03:31,360 Speaker 9: What enterprises we're looking to order. 77 00:03:31,600 --> 00:03:34,520 Speaker 8: And really the key theme I think for us heading 78 00:03:34,560 --> 00:03:38,960 Speaker 8: into all these prints, including last night, was digestion. 79 00:03:39,760 --> 00:03:41,480 Speaker 9: That's the best word you can use. 80 00:03:42,240 --> 00:03:46,240 Speaker 8: You've had orders from twenty twenty one and twenty twenty 81 00:03:46,280 --> 00:03:50,880 Speaker 8: two pushed into calendar twenty three, and you're just seeing 82 00:03:50,920 --> 00:03:54,440 Speaker 8: that digestion of orders. And meanwhile, when budgets start to 83 00:03:54,440 --> 00:03:57,680 Speaker 8: get tighter, networking tends to be the first thing that 84 00:03:57,720 --> 00:04:01,480 Speaker 8: you try to run, hotter and squeeze as you can 85 00:04:01,920 --> 00:04:02,600 Speaker 8: get away. 86 00:04:02,360 --> 00:04:04,520 Speaker 9: With it for some time. So we're a little bit 87 00:04:04,560 --> 00:04:05,800 Speaker 9: skeptical that we could see. 88 00:04:05,600 --> 00:04:08,880 Speaker 8: At an acceleration again in product orders in their fiscal 89 00:04:08,920 --> 00:04:11,880 Speaker 8: second half, especially when you start to think about budgets 90 00:04:11,920 --> 00:04:15,200 Speaker 8: getting set for calendar twenty four roughly. 91 00:04:14,920 --> 00:04:17,479 Speaker 9: About now with a lot of CIOs and heads of it. 92 00:04:18,120 --> 00:04:20,120 Speaker 3: Jane you mentioned that the last time we were on 93 00:04:20,160 --> 00:04:23,479 Speaker 3: we're talking about the Spunk deal. Does that, therefore thesis 94 00:04:23,520 --> 00:04:27,520 Speaker 3: still make sense, the diversification not just hardware networking gear, 95 00:04:27,560 --> 00:04:29,880 Speaker 3: but getting into the software, getting into sort of longer 96 00:04:30,000 --> 00:04:31,920 Speaker 3: term payments from clients. 97 00:04:33,040 --> 00:04:34,640 Speaker 9: Absolutely, Caroline. 98 00:04:34,760 --> 00:04:39,000 Speaker 8: It's a great part of really why they need systems. 99 00:04:39,000 --> 00:04:44,480 Speaker 8: I'm sorry, why why Cisco needs Splunk. And overall it 100 00:04:44,560 --> 00:04:47,840 Speaker 8: will help with that recurring revenue piece. It'll remove the 101 00:04:47,920 --> 00:04:51,240 Speaker 8: lumpiness of Cisco's current business. But at the end of 102 00:04:51,279 --> 00:04:54,479 Speaker 8: the day, even with Splunk, you're still going to have 103 00:04:54,600 --> 00:04:58,919 Speaker 8: the cyclicality that Cisco has to deal with, given that 104 00:04:59,000 --> 00:05:02,920 Speaker 8: networking piece the biggest part of its business at this point. 105 00:05:03,400 --> 00:05:04,680 Speaker 6: Talk op AI a little bit. 106 00:05:04,800 --> 00:05:06,680 Speaker 3: I mean, they did seem to be saying that the 107 00:05:06,680 --> 00:05:09,039 Speaker 3: appetite is there. They're building what a billion dollars of 108 00:05:09,160 --> 00:05:11,680 Speaker 3: orders that they see in their line of sight. Is 109 00:05:11,720 --> 00:05:14,720 Speaker 3: that enough to offset what we see is basically managed 110 00:05:14,760 --> 00:05:17,880 Speaker 3: decline or managed digestion as you say, for the next 111 00:05:17,880 --> 00:05:19,680 Speaker 3: few quarters. 112 00:05:20,040 --> 00:05:23,200 Speaker 8: Yeah, I mean, it's a nice narrative to have, But 113 00:05:23,880 --> 00:05:26,600 Speaker 8: we did this kind of back to basics piece around networking, 114 00:05:27,240 --> 00:05:30,000 Speaker 8: specifically switching and routing not too long ago. 115 00:05:30,560 --> 00:05:32,279 Speaker 9: And you dive deep into. 116 00:05:32,080 --> 00:05:36,719 Speaker 8: You know where could AI spending on switches be, essentially 117 00:05:37,600 --> 00:05:40,200 Speaker 8: and you see estimates out there calling for about ten 118 00:05:40,279 --> 00:05:44,080 Speaker 8: billion ish and even Chuck mentioned that last night, with 119 00:05:44,760 --> 00:05:47,480 Speaker 8: seventy five percent of it expected to be on Ethernet 120 00:05:47,520 --> 00:05:50,520 Speaker 8: as opposed to Navidio's Infinite Band being the. 121 00:05:50,480 --> 00:05:52,440 Speaker 9: Other roughly twenty five percent. 122 00:05:53,040 --> 00:05:56,880 Speaker 8: But even when you talk about, say ten percent of 123 00:05:56,920 --> 00:06:02,120 Speaker 8: Cisco's switching business a few years from now being AI driven, 124 00:06:02,240 --> 00:06:05,600 Speaker 8: that's a small part of Cisco's networking business. When you're 125 00:06:05,600 --> 00:06:09,960 Speaker 8: talking about a thirty billion dollar plus networking business on 126 00:06:10,040 --> 00:06:10,560 Speaker 8: its own. 127 00:06:11,400 --> 00:06:15,039 Speaker 5: You're talking about wide and wireless whatever, connects, devices, news 128 00:06:15,120 --> 00:06:17,200 Speaker 5: data from a to be. But what jumped at me 129 00:06:17,240 --> 00:06:20,920 Speaker 5: about your note versus others is the end customer we're 130 00:06:20,920 --> 00:06:26,920 Speaker 5: talking about in Cisco's argument, big enterprise customers, right, not SMEs. 131 00:06:27,080 --> 00:06:29,320 Speaker 5: And I kind of think of it like the pandemic. 132 00:06:29,400 --> 00:06:31,159 Speaker 5: Right coming out of the pandemic, we all had an 133 00:06:31,200 --> 00:06:35,200 Speaker 5: excess of hand sanitizer and toilet paper. Bear with me, 134 00:06:35,640 --> 00:06:37,520 Speaker 5: but it seems like a lot of these big enterprise 135 00:06:37,600 --> 00:06:40,320 Speaker 5: companies they just have an excess of the networking and 136 00:06:40,400 --> 00:06:44,039 Speaker 5: routing gear. Do you see that as evidence that that 137 00:06:44,120 --> 00:06:45,320 Speaker 5: Chuck Robbins presented. 138 00:06:46,320 --> 00:06:49,000 Speaker 8: Yeah, no, that's definitely showing up in our customer conversations, 139 00:06:49,040 --> 00:06:51,200 Speaker 8: and as Chuck also pointed out, it's also showing up 140 00:06:51,240 --> 00:06:55,000 Speaker 8: with some of the largest channel partners in those conversations 141 00:06:55,040 --> 00:06:58,320 Speaker 8: as well. So, look, you just have a glut of 142 00:06:58,520 --> 00:07:01,480 Speaker 8: equipment sitting there that needs to be deployed, and I 143 00:07:01,520 --> 00:07:03,360 Speaker 8: don't disagree it's going to take at least a couple 144 00:07:03,360 --> 00:07:05,920 Speaker 8: of quarters. And it's more of the concern for US 145 00:07:06,000 --> 00:07:09,320 Speaker 8: is does this start to stem into the SMB commercial 146 00:07:09,400 --> 00:07:13,480 Speaker 8: base as well, where that can be actually more macro 147 00:07:13,600 --> 00:07:17,760 Speaker 8: sensitive as you think about moving ahead, And it doesn't 148 00:07:17,800 --> 00:07:20,960 Speaker 8: really leave a whole lot of wiggle rooms still when 149 00:07:21,000 --> 00:07:23,400 Speaker 8: you think about roughly thirty percent of their businesses that 150 00:07:23,440 --> 00:07:26,720 Speaker 8: commercial line, and we've already seen struggles on the carrier 151 00:07:26,840 --> 00:07:29,000 Speaker 8: side that started popping up earlier this year. 152 00:07:29,400 --> 00:07:29,760 Speaker 9: Cloud. 153 00:07:29,760 --> 00:07:32,440 Speaker 8: It depends a bit on your exposure to which hyperscaler, 154 00:07:32,520 --> 00:07:37,840 Speaker 8: let's say, but overall, enterprise was essentially that last leg 155 00:07:37,840 --> 00:07:39,600 Speaker 8: of the stool that was holding most of the space 156 00:07:39,680 --> 00:07:41,880 Speaker 8: up and it just now you're starting to see that 157 00:07:42,000 --> 00:07:47,120 Speaker 8: down cycle of networking really come about here. And specifically 158 00:07:47,160 --> 00:07:49,480 Speaker 8: add to your comment, on wireless land. Keep in mind, 159 00:07:49,520 --> 00:07:51,640 Speaker 8: this has been wireless land's been one of the strongest 160 00:07:51,640 --> 00:07:54,680 Speaker 8: part of networking over the last year plus. And what 161 00:07:54,720 --> 00:07:58,640 Speaker 8: we're seeing is it's actually twofold one. You've gotten a 162 00:07:58,680 --> 00:08:01,880 Speaker 8: lot of those access point up it's already and so 163 00:08:02,080 --> 00:08:05,320 Speaker 8: Cisco Morocki for example, has really benefited been growing double 164 00:08:05,360 --> 00:08:10,280 Speaker 8: digits for quite a while here. But secondly, when you 165 00:08:10,360 --> 00:08:13,840 Speaker 8: look at why they needed to upgrade those access points, 166 00:08:14,120 --> 00:08:16,640 Speaker 8: it's because of exactly what I'm sitting on right now 167 00:08:16,800 --> 00:08:20,680 Speaker 8: with Zoom or in other cases Microsoft teams, where that 168 00:08:20,880 --> 00:08:23,560 Speaker 8: sucks up so much bandwidth at all these campuses and 169 00:08:23,600 --> 00:08:27,040 Speaker 8: branches that you needed to upgrade those access points. And 170 00:08:27,080 --> 00:08:29,720 Speaker 8: so now you've kind of gone through that, and those 171 00:08:29,760 --> 00:08:32,880 Speaker 8: applications themselves are trying to reduce down their bandwidth by 172 00:08:33,320 --> 00:08:36,280 Speaker 8: over twenty percent in the latest version, so you just 173 00:08:36,320 --> 00:08:37,640 Speaker 8: haven't slow down in that space. 174 00:08:37,679 --> 00:08:41,000 Speaker 5: In particular, it's why I ask if attentions turned to SMBs, 175 00:08:41,000 --> 00:08:43,439 Speaker 5: because loads of folks use SMBs as their kind of 176 00:08:43,520 --> 00:08:46,600 Speaker 5: lead indicator for the health of an economy in this 177 00:08:46,720 --> 00:08:49,800 Speaker 5: In this context, Jim Fish, Phypisandler seeing a research and 178 00:08:49,920 --> 00:08:50,960 Speaker 5: this greates catch up. 179 00:09:00,160 --> 00:09:01,640 Speaker 4: Rocks by US sanctions. 180 00:09:01,720 --> 00:09:04,720 Speaker 5: Huawei unveiled a new smartphone in August with five G 181 00:09:04,840 --> 00:09:08,640 Speaker 5: capabilities and a cutting edge process or. A teardown of 182 00:09:08,679 --> 00:09:11,840 Speaker 5: the May sixty pro revealed the chip powering the device 183 00:09:11,960 --> 00:09:16,040 Speaker 5: was produced by China's Smick. This raised questions about smick 184 00:09:16,120 --> 00:09:21,080 Speaker 5: we s miic's capabilities and the effectiveness of US LED controls. 185 00:09:21,160 --> 00:09:21,720 Speaker 7: Check this out. 186 00:09:25,720 --> 00:09:31,280 Speaker 10: This at first glance is just a smartphone, but once 187 00:09:31,320 --> 00:09:34,520 Speaker 10: you know what's inside, it becomes clear it's so much 188 00:09:34,559 --> 00:09:35,000 Speaker 10: more than that. 189 00:09:35,960 --> 00:09:39,880 Speaker 11: So what really changed everybody's view of this device was 190 00:09:40,000 --> 00:09:42,600 Speaker 11: what was at the heart of it, the microprocessor that 191 00:09:42,840 --> 00:09:46,520 Speaker 11: was designed and manufactured in China. 192 00:09:46,840 --> 00:09:49,400 Speaker 10: It's at the center of tensions between the world's two 193 00:09:49,400 --> 00:09:53,360 Speaker 10: biggest economies. The phone made by Chinese tech giant Huawei 194 00:09:53,520 --> 00:09:57,040 Speaker 10: represents a breakthrough by Beijing as it tries to escape 195 00:09:57,080 --> 00:10:00,960 Speaker 10: Washington's controls on its access to technology and establish a 196 00:10:01,000 --> 00:10:06,480 Speaker 10: self sufficient chip industry. If those US controls had been successful, 197 00:10:06,679 --> 00:10:09,840 Speaker 10: then a smartphone as advances this simply should not be 198 00:10:09,920 --> 00:10:12,439 Speaker 10: possible without important key components. 199 00:10:13,400 --> 00:10:19,560 Speaker 12: China now is more capable than ever of building advanced technologies. 200 00:10:19,200 --> 00:10:22,040 Speaker 10: And it worried US officials, who are more concerned about 201 00:10:22,080 --> 00:10:26,760 Speaker 10: advance chips going into military equipment than smartphones. It left 202 00:10:26,760 --> 00:10:30,240 Speaker 10: them wondering how exactly did China do It. 203 00:10:31,840 --> 00:10:34,680 Speaker 3: Can catch that full documentary on the Bloomberg and on 204 00:10:34,720 --> 00:10:39,760 Speaker 3: Bloomberg dot Com tonight five pm and indeed tomorrow on YouTube. Meanwhile, 205 00:10:39,880 --> 00:10:42,360 Speaker 3: let's stay with the theme of China shares of Ali 206 00:10:42,360 --> 00:10:45,160 Speaker 3: Baba actually slepping pretty hard after China's largest e commerce 207 00:10:45,160 --> 00:10:48,480 Speaker 3: company called off a spinoff of its giant cloud business. 208 00:10:48,679 --> 00:10:51,480 Speaker 3: But I mean, in fact, the US is tightening chip cubs. 209 00:10:51,520 --> 00:10:54,080 Speaker 3: Of course, all of this links, but please to welcome 210 00:10:54,080 --> 00:10:56,280 Speaker 3: to the show. Henry ren over in London as well, Lee, 211 00:10:56,320 --> 00:10:58,240 Speaker 3: who sat right next to me here and Henry, I 212 00:10:58,280 --> 00:11:01,160 Speaker 3: start with you. It feels as though its first dividend 213 00:11:01,520 --> 00:11:03,480 Speaker 3: just wasn't enough to offset the fact that now that 214 00:11:03,559 --> 00:11:05,800 Speaker 3: some of the parts perhaps don't look quite so valuable. 215 00:11:07,160 --> 00:11:10,280 Speaker 13: Yes, indeed, so it's a double whammy situation for alibah 216 00:11:10,280 --> 00:11:13,200 Speaker 13: Bau this quarter. So its core business of selling goods 217 00:11:13,600 --> 00:11:18,400 Speaker 13: to Chinese consumers is not posting the exciting revenue that 218 00:11:18,440 --> 00:11:21,439 Speaker 13: we've been seeing for last quarter. But more importantly, as 219 00:11:21,480 --> 00:11:25,400 Speaker 13: you line out that the company scrapped its plan to 220 00:11:26,360 --> 00:11:28,760 Speaker 13: spin up its cloud unit, it's that before that it's 221 00:11:28,800 --> 00:11:32,080 Speaker 13: going to relinquish its control of the cloud unit and 222 00:11:32,160 --> 00:11:34,960 Speaker 13: send out the cloud unit as dividend to shareholders, but 223 00:11:35,120 --> 00:11:38,240 Speaker 13: not materializing for now because the company called off the plan, 224 00:11:38,640 --> 00:11:41,800 Speaker 13: although the company did issue a cash dividend, but it's 225 00:11:42,000 --> 00:11:45,760 Speaker 13: seen as just a minor offset to the disappointment because 226 00:11:45,800 --> 00:11:49,560 Speaker 13: investors were really expecting that the company would issue this 227 00:11:49,880 --> 00:11:53,120 Speaker 13: special dividend after the spinoff, and as we know that 228 00:11:53,160 --> 00:11:56,679 Speaker 13: the cloud is the second biggest segment for Ali Baba, 229 00:11:56,800 --> 00:11:59,880 Speaker 13: So it's definitely a day of disappointment, a double whamy 230 00:12:00,000 --> 00:12:03,520 Speaker 13: situation for Ali Baba Shaholders Today team. 231 00:12:03,840 --> 00:12:06,240 Speaker 5: The timing of this is just extraordinary. We're going to 232 00:12:06,280 --> 00:12:08,760 Speaker 5: go to our reporter at APEC later in the show, 233 00:12:09,480 --> 00:12:13,280 Speaker 5: but you know, a centerpiece of what happened last night 234 00:12:13,480 --> 00:12:16,520 Speaker 5: was President g and Biden talking about kind of closer 235 00:12:16,559 --> 00:12:21,199 Speaker 5: economic cooperation while Biden saying we're going to stay competitive, 236 00:12:22,200 --> 00:12:25,080 Speaker 5: is about what are we learning through these earnings out 237 00:12:25,080 --> 00:12:27,720 Speaker 5: of Ali Baba about the health of the Chinese economy 238 00:12:27,800 --> 00:12:28,200 Speaker 5: right now. 239 00:12:28,520 --> 00:12:30,920 Speaker 14: So this definitely doesn't look good because, as Henry said, 240 00:12:31,000 --> 00:12:33,200 Speaker 14: many were really banking on the breakup of the six 241 00:12:33,280 --> 00:12:36,439 Speaker 14: Baby Baba's optimism, we're surrounding it. They were saying that 242 00:12:36,600 --> 00:12:40,280 Speaker 14: Beijing probably has the approve, Beijing probably gave its approval 243 00:12:40,320 --> 00:12:42,520 Speaker 14: signal because this wouldn't happen. That many dubbed it as 244 00:12:42,520 --> 00:12:45,560 Speaker 14: the most radical change in history. And it even looks 245 00:12:45,600 --> 00:12:48,959 Speaker 14: worse because they cited the US restrictions on as one 246 00:12:48,960 --> 00:12:51,040 Speaker 14: of the reasons why they weren't going to continue this. 247 00:12:51,120 --> 00:12:54,400 Speaker 14: And as we know, President Biden and Presidency has met 248 00:12:54,440 --> 00:12:56,439 Speaker 14: their first time in a one year, and that's as 249 00:12:56,559 --> 00:12:59,320 Speaker 14: relations between the two nations are there. I say, at 250 00:12:59,320 --> 00:13:01,120 Speaker 14: the all time look. Oh and while there were no 251 00:13:01,280 --> 00:13:03,560 Speaker 14: really big major headlines, there were small wins, but no 252 00:13:03,559 --> 00:13:06,480 Speaker 14: one was really expecting a major concession. And some analysts 253 00:13:06,480 --> 00:13:08,760 Speaker 14: told me that the fact that this meeting is happening 254 00:13:09,160 --> 00:13:11,760 Speaker 14: is more than enough because the optics is important. But 255 00:13:11,840 --> 00:13:14,600 Speaker 14: to your point, a lot of investors were really disappointed. 256 00:13:14,600 --> 00:13:17,040 Speaker 14: As Henry said, it's a big disappointment for everyone. And 257 00:13:17,080 --> 00:13:20,120 Speaker 14: if you look at Alibaba ADRs, they're now falling to 258 00:13:20,160 --> 00:13:21,560 Speaker 14: the most in more than one year. 259 00:13:21,679 --> 00:13:24,200 Speaker 3: And I think it's notable given that actually we saw 260 00:13:24,320 --> 00:13:26,760 Speaker 3: JD manage to be, we saw ten Cent managed to 261 00:13:26,800 --> 00:13:30,200 Speaker 3: be even with some stiff competition coming from the social 262 00:13:30,200 --> 00:13:33,400 Speaker 3: apps coming in and the smaller businesses as well. Does 263 00:13:33,480 --> 00:13:36,480 Speaker 3: this really reflect a consumer under pressure or. 264 00:13:36,480 --> 00:13:39,480 Speaker 6: Does this also reflect competition. I think it's both, but. 265 00:13:39,559 --> 00:13:42,000 Speaker 14: It's really more of the tepid demand that we're seeing. 266 00:13:42,120 --> 00:13:45,360 Speaker 14: China hasn't seen the big recovery that they were poping 267 00:13:45,360 --> 00:13:48,240 Speaker 14: on and that global investors are really really banking on 268 00:13:48,480 --> 00:13:50,960 Speaker 14: after the COVID pandemic, and you could see that Presidencies 269 00:13:51,000 --> 00:13:53,600 Speaker 14: even trying his best. He visited the Central Bank of 270 00:13:53,679 --> 00:13:55,600 Speaker 14: China just a few weeks back to show that, you know, 271 00:13:55,760 --> 00:13:58,200 Speaker 14: he's on top of this, but so far, and we 272 00:13:58,240 --> 00:14:01,400 Speaker 14: also have foreign investments in China, but they're really all 273 00:14:01,440 --> 00:14:04,480 Speaker 14: time low. So it's really kind of a complex picture. 274 00:14:04,520 --> 00:14:07,240 Speaker 14: But it's really not a monolith. As you said, ten 275 00:14:07,320 --> 00:14:09,280 Speaker 14: Cent is doing well, JD is doing well at least 276 00:14:09,559 --> 00:14:12,520 Speaker 14: based on last month, but so far, for now, optimism 277 00:14:12,600 --> 00:14:14,520 Speaker 14: is still not evident in Chinese. 278 00:14:14,240 --> 00:14:19,800 Speaker 5: Investors always think about Ali Barbars like analogous with Amazon. Right, 279 00:14:19,800 --> 00:14:22,720 Speaker 5: you got your e commerce component and then the news 280 00:14:22,720 --> 00:14:25,760 Speaker 5: today being the cloud component, and Henry you were writing 281 00:14:26,200 --> 00:14:29,360 Speaker 5: this morning's street rap. Vali Barber, what's the kind of 282 00:14:29,440 --> 00:14:33,560 Speaker 5: cell side specific takeaway? From the numbers, but also the 283 00:14:33,600 --> 00:14:34,640 Speaker 5: different parts of the bids. 284 00:14:35,080 --> 00:14:38,360 Speaker 13: Yeah, so from the numbers perspective, the e commerce part 285 00:14:38,400 --> 00:14:41,560 Speaker 13: of the business is still occupying more than fifty percent 286 00:14:41,600 --> 00:14:43,720 Speaker 13: of Ali Baba's core revenue. 287 00:14:43,760 --> 00:14:46,120 Speaker 7: However that part is slowing. 288 00:14:46,160 --> 00:14:49,040 Speaker 13: So we saw some revival trends in the last quarter, 289 00:14:49,320 --> 00:14:53,200 Speaker 13: which shows that Alibaba might be again its momentum again 290 00:14:53,440 --> 00:14:56,200 Speaker 13: when its competitors like pindle Do or the price aggressor 291 00:14:56,400 --> 00:14:59,120 Speaker 13: as well as live streaming e commerce platforms like going 292 00:14:59,360 --> 00:15:02,360 Speaker 13: like quite a show, or like entering the space and 293 00:15:02,480 --> 00:15:05,960 Speaker 13: grabbing the market share. But it's not it's not happening 294 00:15:06,000 --> 00:15:08,800 Speaker 13: once again this quarter because the sales has been a 295 00:15:08,800 --> 00:15:12,960 Speaker 13: bit disappointing and for analysts it's a disappointment. And on 296 00:15:13,000 --> 00:15:15,880 Speaker 13: the other hand, as we said, it's now scrapping it's 297 00:15:15,920 --> 00:15:18,720 Speaker 13: planned to spin off the cloud unit. It's also scrapping 298 00:15:18,720 --> 00:15:21,520 Speaker 13: its plan to IPO, it's. 299 00:15:21,640 --> 00:15:23,920 Speaker 7: Freshupul, which is a grocery shipping chain. 300 00:15:24,080 --> 00:15:27,080 Speaker 13: It's another disappointment for analysts as FOP so a lot 301 00:15:27,120 --> 00:15:28,080 Speaker 13: of things to digest. 302 00:15:28,120 --> 00:15:30,120 Speaker 7: FULI Barbi inverstrously. 303 00:15:29,800 --> 00:15:32,600 Speaker 5: And as we pointed out, that disappointment reflected in shares. 304 00:15:32,680 --> 00:15:35,760 Speaker 5: The ADRs down nine percent biggest dropping more than a year, 305 00:15:36,000 --> 00:15:37,920 Speaker 5: and the stock trading at its lowest level since May. 306 00:15:37,960 --> 00:15:41,680 Speaker 5: Bloomberg's Henry Ren and Isabel Lee the dream team back together. 307 00:15:41,800 --> 00:15:43,120 Speaker 4: Thank you now coming up. 308 00:15:43,200 --> 00:15:47,240 Speaker 5: APEC continues here in San Francisco as China's president dines 309 00:15:47,320 --> 00:15:50,160 Speaker 5: with the CEOs of some pretty major firms. We're gonna 310 00:15:50,160 --> 00:16:16,040 Speaker 5: bring you all those details next. This is Bloomberg Technology. Okay, 311 00:16:16,040 --> 00:16:18,280 Speaker 5: time for talking tech and first up. Shares of Hello 312 00:16:18,480 --> 00:16:22,840 Speaker 5: Fresh falling today after the mailkit delivery company shocked investors 313 00:16:23,080 --> 00:16:25,520 Speaker 5: by cutting its twenty twenty three e bit dar Guide 314 00:16:25,520 --> 00:16:28,160 Speaker 5: and HelloFresh was down as much as a record twenty 315 00:16:28,200 --> 00:16:31,800 Speaker 5: four percent eraising nearly seven hundred and eighty million dollars 316 00:16:31,800 --> 00:16:34,400 Speaker 5: of market value. The changes to it outlook come just 317 00:16:34,480 --> 00:16:38,960 Speaker 5: three weeks after it reaffirmed its targets, and Lenovo says 318 00:16:38,960 --> 00:16:41,800 Speaker 5: it expects to see revenue growth this quarter generated from 319 00:16:41,880 --> 00:16:45,640 Speaker 5: personal computer demand in China that the world's largest PC 320 00:16:45,800 --> 00:16:48,400 Speaker 5: maker says it's investing a lot of money into AI 321 00:16:48,560 --> 00:16:52,600 Speaker 5: optimized devices, something that CEO says could drive another round 322 00:16:52,720 --> 00:16:57,160 Speaker 5: of PC replacement. Plus, semiconductor firm Sapien is unveiling its 323 00:16:57,240 --> 00:17:00,960 Speaker 5: latest artificial intelligence chip for Data cent. It's the startup 324 00:17:01,240 --> 00:17:04,679 Speaker 5: backs by South Korean firm sk Group is ramping up 325 00:17:04,680 --> 00:17:06,040 Speaker 5: its offering to compete with. 326 00:17:06,040 --> 00:17:07,639 Speaker 4: The likes of Nvidia and others. 327 00:17:07,680 --> 00:17:11,199 Speaker 5: Sapient will be conducting testing for major customers before it 328 00:17:11,240 --> 00:17:14,080 Speaker 5: begins mass production in the first half of next year. 329 00:17:14,280 --> 00:17:17,120 Speaker 3: Carrot, Well, let's turn attention to what's happening in your 330 00:17:17,119 --> 00:17:17,800 Speaker 3: city at the moment. 331 00:17:17,920 --> 00:17:18,000 Speaker 1: Ed. 332 00:17:18,040 --> 00:17:21,320 Speaker 3: Of course, APEC underwearing way in San Francisco, and Arey 333 00:17:21,359 --> 00:17:24,040 Speaker 3: Horden has been there throughout talking to some big names 334 00:17:24,040 --> 00:17:26,520 Speaker 3: and attendance, and notably there were some big executives and 335 00:17:26,560 --> 00:17:30,520 Speaker 3: attendants at a dinner with Jijingping last night. It's notable 336 00:17:30,520 --> 00:17:32,520 Speaker 3: we've got some reporting at the moment saying that Tesla 337 00:17:32,560 --> 00:17:34,560 Speaker 3: CEO in a Musk is no longer actually going to 338 00:17:34,560 --> 00:17:38,840 Speaker 3: be in today's lineup of speakers at APEX. That's largely 339 00:17:38,880 --> 00:17:41,240 Speaker 3: because he endorsed an anti Semitic post on X his 340 00:17:41,280 --> 00:17:43,639 Speaker 3: own social media site. We'll talk about that later about Marie. 341 00:17:43,640 --> 00:17:46,520 Speaker 3: But who have we seen and why have we seen 342 00:17:46,560 --> 00:17:48,480 Speaker 3: these certain executives with Shijingping. 343 00:17:48,960 --> 00:17:50,960 Speaker 15: Well, I have a full list of who sat at 344 00:17:50,960 --> 00:17:54,919 Speaker 15: Shijingping's table last night where you saw a number of 345 00:17:54,960 --> 00:17:58,040 Speaker 15: ceo stand up and applaud him, the likes of Ray Dalio, 346 00:17:58,240 --> 00:18:01,160 Speaker 15: Larry Fink, Tim Kirk, all of them. You see them 347 00:18:01,160 --> 00:18:04,720 Speaker 15: on the screen there in attendance to meet with Shijingping 348 00:18:04,880 --> 00:18:10,199 Speaker 15: where one Republican official, Mike Gallagher Wisconsin, who chairs the 349 00:18:10,400 --> 00:18:13,480 Speaker 15: China House Select Committee, said when he was at a 350 00:18:13,520 --> 00:18:17,000 Speaker 15: protest against the Chinese Communist Party this weekend, said that 351 00:18:17,040 --> 00:18:19,840 Speaker 15: executives were paying as much as forty thousand dollars or 352 00:18:19,840 --> 00:18:22,200 Speaker 15: a company paying as much as forty thousand dollars for 353 00:18:22,640 --> 00:18:25,359 Speaker 15: their CEO to be able to go to this dinner 354 00:18:25,400 --> 00:18:28,960 Speaker 15: and sit with the President of China. But I think 355 00:18:28,960 --> 00:18:31,199 Speaker 15: more importantly we should also look at what the President 356 00:18:31,240 --> 00:18:34,920 Speaker 15: of China said yesterday. He really struck a more conciliatory, 357 00:18:35,000 --> 00:18:38,480 Speaker 15: duvish tone. Part of this was the fact that he 358 00:18:38,600 --> 00:18:41,720 Speaker 15: is dealing with a fragile economy at home. We've seen 359 00:18:42,160 --> 00:18:45,320 Speaker 15: a huge hit to foreign direct investment into China, and 360 00:18:45,400 --> 00:18:47,480 Speaker 15: it looked like he was trying to set a path 361 00:18:47,520 --> 00:18:50,160 Speaker 15: forward to be more welcoming when it comes to US 362 00:18:50,240 --> 00:18:53,840 Speaker 15: businesses this summer. Gina Ramundo, the Commerce Secretary, when she 363 00:18:53,960 --> 00:18:58,520 Speaker 15: was in China, said that she told Chinese leaders that 364 00:18:58,640 --> 00:19:00,919 Speaker 15: what she hears time and time again from businesses, and 365 00:19:00,960 --> 00:19:03,040 Speaker 15: that China is becoming more uninvestable. 366 00:19:03,240 --> 00:19:04,720 Speaker 6: So Shijingping yesterday. 367 00:19:04,480 --> 00:19:06,960 Speaker 15: Said that he has no plans to unseat the United States, 368 00:19:07,000 --> 00:19:09,120 Speaker 15: and he'd also said that he doesn't want to see 369 00:19:09,200 --> 00:19:11,359 Speaker 15: China in a hot or cold war. 370 00:19:11,440 --> 00:19:12,600 Speaker 6: Now, it remains to be seen. 371 00:19:12,440 --> 00:19:15,119 Speaker 15: If this is going to assuage some of these business concerns. 372 00:19:15,920 --> 00:19:18,560 Speaker 5: So I imaged on the other side of the table 373 00:19:18,600 --> 00:19:23,000 Speaker 5: and the negotiation, President Biden was asked a very specific 374 00:19:23,080 --> 00:19:26,359 Speaker 5: question about whether he viewed Jijiping as a dictator. 375 00:19:27,080 --> 00:19:30,560 Speaker 15: What was his response, Well, Biden has said it before, 376 00:19:30,720 --> 00:19:33,120 Speaker 15: he said it yesterday, and he will probably say it again, 377 00:19:33,240 --> 00:19:35,640 Speaker 15: especially as we get into the November twenty twenty four 378 00:19:35,680 --> 00:19:39,080 Speaker 15: presidential election. He said, Shijingping is a dictator, and then 379 00:19:39,080 --> 00:19:41,280 Speaker 15: he explained it's a very different system in China than 380 00:19:41,320 --> 00:19:42,760 Speaker 15: the one we have here at. 381 00:19:42,680 --> 00:19:43,479 Speaker 4: The United States. 382 00:19:44,320 --> 00:19:47,760 Speaker 15: This comment, though, came after Biden fielded a number of 383 00:19:47,880 --> 00:19:49,800 Speaker 15: questions in the press conference, and then he took some 384 00:19:49,840 --> 00:19:53,160 Speaker 15: ad hoc questions as he was leaving that press conference. 385 00:19:53,359 --> 00:19:56,159 Speaker 15: I think the main takeaway from the White House is 386 00:19:56,359 --> 00:19:59,240 Speaker 15: Biden's k not going to back away. Have asked this again, 387 00:20:00,200 --> 00:20:03,080 Speaker 15: especially as the rhetoric gets heated before November of twenty 388 00:20:03,119 --> 00:20:04,760 Speaker 15: twenty four. But the main takeway from the White House 389 00:20:04,800 --> 00:20:07,400 Speaker 15: is they feel that this was a way a deliverable. 390 00:20:07,560 --> 00:20:10,720 Speaker 15: These two individuals met, and Biden really just wants to 391 00:20:10,720 --> 00:20:12,640 Speaker 15: get the relationship in a better place where he can 392 00:20:12,680 --> 00:20:14,360 Speaker 15: pick up the phone in a time of conflict. 393 00:20:15,359 --> 00:20:17,680 Speaker 5: AMH, real quick? What's left to come on the agenda? 394 00:20:17,800 --> 00:20:19,960 Speaker 5: While Biden's in town well waiting. 395 00:20:19,720 --> 00:20:21,960 Speaker 15: To hear from Biden, he's going to be addressing apex 396 00:20:22,000 --> 00:20:25,280 Speaker 15: CEO's there'll be a family photo and then this evening 397 00:20:25,359 --> 00:20:26,960 Speaker 15: he's going to be looking a little bit more forward 398 00:20:27,000 --> 00:20:32,320 Speaker 15: to the iPath, which is this water down trade deal, 399 00:20:32,520 --> 00:20:37,159 Speaker 15: not the DPP but iPath, the Indo Pacific Economic Framework. 400 00:20:37,280 --> 00:20:39,880 Speaker 15: One thing to note about this is potentially some pushback 401 00:20:39,920 --> 00:20:42,119 Speaker 15: that Biden administration is going to see because the trade 402 00:20:42,200 --> 00:20:44,840 Speaker 15: pillar has been ditched. It was potentially going to be 403 00:20:44,880 --> 00:20:47,239 Speaker 15: announced at this forum and it's not all right. 404 00:20:47,240 --> 00:20:51,280 Speaker 5: Bloomberg'sa Marie hoarding over from DC in San Francisco for apeg. 405 00:20:58,520 --> 00:21:00,000 Speaker 6: Wellcome out to bloom teen onogym. 406 00:21:00,160 --> 00:21:02,359 Speaker 5: I hid in New York and I'm ed Lovelow in 407 00:21:02,400 --> 00:21:03,080 Speaker 5: San Francisco. 408 00:21:03,119 --> 00:21:03,600 Speaker 4: Two movers. 409 00:21:03,640 --> 00:21:05,199 Speaker 5: I want to check back in on one for the 410 00:21:05,240 --> 00:21:07,760 Speaker 5: first time. Palo Alto Networks, a name that we've not 411 00:21:08,359 --> 00:21:12,520 Speaker 5: mentioned yet. We're talking about largely software in Palo Alto 412 00:21:12,600 --> 00:21:15,000 Speaker 5: Networks case, it's trying to jump on this AI bandwagon, 413 00:21:15,000 --> 00:21:18,040 Speaker 5: but it missed estimates in its fiscal first quarter and 414 00:21:18,080 --> 00:21:20,639 Speaker 5: lowered its full year guidance, which has hit the shares 415 00:21:20,760 --> 00:21:24,320 Speaker 5: you can see down almost six percent. And revisiting Cisco right, 416 00:21:24,359 --> 00:21:26,439 Speaker 5: We've covered it in debt furlier in the show, but 417 00:21:26,440 --> 00:21:29,000 Speaker 5: the stock is down more than eleven percent, on track 418 00:21:29,040 --> 00:21:31,760 Speaker 5: for its biggest drop in almost eighteen months. And the 419 00:21:31,880 --> 00:21:34,400 Speaker 5: concern here is that its outlook for its fiscal second 420 00:21:34,480 --> 00:21:37,440 Speaker 5: quarter came in well below what the street was expecting. 421 00:21:37,720 --> 00:21:40,960 Speaker 5: The answer from Cisco customers are working through a backlog 422 00:21:40,960 --> 00:21:44,199 Speaker 5: on networking equipment. The concern from the cell side hold on, 423 00:21:44,680 --> 00:21:46,760 Speaker 5: We're worried about the health of that market and what 424 00:21:46,760 --> 00:21:50,560 Speaker 5: the mecroeconomic conditions are. But two big movers, similar spaces 425 00:21:51,000 --> 00:21:52,800 Speaker 5: and those having an impact on the broader market. 426 00:21:53,040 --> 00:21:54,280 Speaker 4: This Thursday, carrac. 427 00:21:54,320 --> 00:21:56,560 Speaker 6: Yeah, and we want to dig in on the broader market. 428 00:21:56,600 --> 00:21:58,920 Speaker 3: The appetite of corporate spending, right, now, particularly when it 429 00:21:58,960 --> 00:22:00,359 Speaker 3: comes to the application. 430 00:22:00,280 --> 00:22:02,240 Speaker 6: Of cybersecurity, of defense, and. 431 00:22:02,160 --> 00:22:05,480 Speaker 3: Indeed in a world where AI is helping and hindering. 432 00:22:05,600 --> 00:22:07,920 Speaker 3: With all of that, we want to talk with Lane 433 00:22:07,960 --> 00:22:11,440 Speaker 3: mess CEO at Deep Instinct, and of course you yourself 434 00:22:11,680 --> 00:22:14,119 Speaker 3: were former CEO of Palo Alto Networks. We were just 435 00:22:14,160 --> 00:22:17,240 Speaker 3: hearing about some of the PATS earnings that aren't living 436 00:22:17,320 --> 00:22:19,600 Speaker 3: up to expectations, even though there seems to be this 437 00:22:19,680 --> 00:22:23,159 Speaker 3: rampant demand for cyber protection in the here and now. 438 00:22:23,520 --> 00:22:25,720 Speaker 3: What do you make of the fact that Palo Alto Networks, 439 00:22:25,720 --> 00:22:29,920 Speaker 3: for example, isn't managing to lean into perhaps that growth 440 00:22:29,960 --> 00:22:31,200 Speaker 3: in that particular area. 441 00:22:31,280 --> 00:22:34,040 Speaker 2: Well, I can't say that they're not leaning into the growth. 442 00:22:34,280 --> 00:22:36,600 Speaker 2: First of all, I have to commend Nikesh and the 443 00:22:36,640 --> 00:22:39,520 Speaker 2: team there. What they've done with the company post my 444 00:22:39,800 --> 00:22:44,240 Speaker 2: time there has been very good. The focus of palow 445 00:22:44,240 --> 00:22:47,960 Speaker 2: out there was a platform play, and the platform play 446 00:22:48,080 --> 00:22:52,320 Speaker 2: is to really give you a protection around accessing your 447 00:22:52,359 --> 00:22:55,040 Speaker 2: infrastructure and the threats that might hit it. 448 00:22:56,040 --> 00:22:59,040 Speaker 1: The other aspects are how do you guard the door? 449 00:23:00,000 --> 00:23:03,600 Speaker 2: Platform players are going broad, they're not going deep, and 450 00:23:03,640 --> 00:23:06,880 Speaker 2: that's where the AI focus needs to come in. Deep 451 00:23:07,000 --> 00:23:11,960 Speaker 2: Instinct goes deep and as you can appreciate, I got 452 00:23:11,960 --> 00:23:14,600 Speaker 2: off my bench to do this because the challenge of 453 00:23:14,640 --> 00:23:17,240 Speaker 2: AI is really becoming paramount. 454 00:23:17,480 --> 00:23:21,560 Speaker 5: One thing we've reflected on this year is that when 455 00:23:21,560 --> 00:23:25,240 Speaker 5: we're talking about AI and the context of cybersecurity, it's 456 00:23:25,280 --> 00:23:29,640 Speaker 5: as much a tool for the threat actors as it 457 00:23:29,760 --> 00:23:33,080 Speaker 5: is for your customers. Right, people trying to ward against 458 00:23:33,359 --> 00:23:37,720 Speaker 5: cyber threats. Who is making the most progress the threat 459 00:23:37,760 --> 00:23:40,080 Speaker 5: actors or those trying to defend against them. 460 00:23:40,280 --> 00:23:42,440 Speaker 2: Well, I think a lot of people were caught off guard. 461 00:23:42,720 --> 00:23:46,399 Speaker 2: Many of the platform players have machine learning models, but 462 00:23:46,520 --> 00:23:49,560 Speaker 2: to really get ahead of the threat actors, you have 463 00:23:49,640 --> 00:23:52,680 Speaker 2: to have the more sophisticated technology. It's a think called 464 00:23:52,800 --> 00:23:55,800 Speaker 2: deep learning, and I won't get into the specific science 465 00:23:55,840 --> 00:23:58,119 Speaker 2: of it, but it acts similar to a brain in 466 00:23:58,160 --> 00:24:00,640 Speaker 2: the fact that you've got to count this in fact 467 00:24:00,760 --> 00:24:04,200 Speaker 2: infinity parameters that you're checking against, so you can create 468 00:24:04,200 --> 00:24:08,040 Speaker 2: a predictive capability and get out ahead of the actors. Now, 469 00:24:08,080 --> 00:24:11,280 Speaker 2: Deep Instinct has been developing this capability for ten years. 470 00:24:11,760 --> 00:24:14,520 Speaker 1: So when AI became in vogue. 471 00:24:14,119 --> 00:24:16,080 Speaker 2: In terms of the things you could do from a 472 00:24:16,119 --> 00:24:22,320 Speaker 2: salesforce enhancement, customer support enhancement, a lot of the security companies, 473 00:24:22,359 --> 00:24:25,120 Speaker 2: including some of the ones you noted, were still focused 474 00:24:25,160 --> 00:24:28,480 Speaker 2: on broadening their coverage but not going deep into the 475 00:24:28,480 --> 00:24:32,600 Speaker 2: more advanced sophisticated deep learning algorithms. That's what we do 476 00:24:32,680 --> 00:24:36,200 Speaker 2: with the ninety nine percent efficacy. But the main challenge 477 00:24:36,280 --> 00:24:40,160 Speaker 2: right now is protecting data. So everybody's looking to protect data, 478 00:24:40,680 --> 00:24:44,320 Speaker 2: everybody's looking to attack the data. You can't fight fire 479 00:24:44,840 --> 00:24:48,240 Speaker 2: unless you have fire to fight fire, and deep learning 480 00:24:48,320 --> 00:24:50,199 Speaker 2: is going to be the answer that most of the 481 00:24:50,320 --> 00:24:53,520 Speaker 2: security companies and platform players are going to have to 482 00:24:53,520 --> 00:24:56,600 Speaker 2: focus on. That's what we focus from ground up one 483 00:24:56,680 --> 00:24:57,359 Speaker 2: hundred percent. 484 00:24:57,600 --> 00:25:01,720 Speaker 5: Your choice of words. That very interesting. Twenty four hours 485 00:25:01,720 --> 00:25:05,119 Speaker 5: ago we had the Rubric CEO, your industry colleague on 486 00:25:05,840 --> 00:25:07,360 Speaker 5: people sitting here on the show. 487 00:25:07,240 --> 00:25:07,919 Speaker 7: Have a listener to what. 488 00:25:09,440 --> 00:25:13,960 Speaker 16: I know people will cyber attacks have gone beyond human comprehension. 489 00:25:14,600 --> 00:25:18,600 Speaker 16: You have to fight fire with fire, and as attackers 490 00:25:18,640 --> 00:25:22,880 Speaker 16: are leveraging AI to generate more codes to actually attack you, 491 00:25:22,880 --> 00:25:25,880 Speaker 16: you have to apply AI to understand what the heck 492 00:25:25,960 --> 00:25:26,840 Speaker 16: is really going on. 493 00:25:28,320 --> 00:25:34,080 Speaker 2: You guys are changing notes or the no, no, actually, Bipple, 494 00:25:35,520 --> 00:25:38,360 Speaker 2: he's a very good friend. In fact, I'm an investor 495 00:25:38,400 --> 00:25:42,040 Speaker 2: in Rubrics, so and they're addressing the very big challenge 496 00:25:42,280 --> 00:25:46,359 Speaker 2: storage recovery, and it's something that went unnoticed for a 497 00:25:46,400 --> 00:25:49,399 Speaker 2: long time. It's something we focus heavily on. There are 498 00:25:49,400 --> 00:25:53,520 Speaker 2: people are focusing on the eder, the endpoint, CrowdStrike, Sentinel one. 499 00:25:53,960 --> 00:25:56,600 Speaker 2: They almost accept the fact that you're going to have 500 00:25:57,119 --> 00:25:59,520 Speaker 2: a breach, and then they help you clean it up. 501 00:25:59,840 --> 00:26:02,760 Speaker 2: But you cannot accept the breach anymore. You have to 502 00:26:02,760 --> 00:26:05,680 Speaker 2: get out ahead of it. And I and Dipple share 503 00:26:05,720 --> 00:26:08,119 Speaker 2: a lot of views. But the secret is in the 504 00:26:08,200 --> 00:26:12,280 Speaker 2: technology and the uniqueness of the deep learning framework work. 505 00:26:13,040 --> 00:26:16,600 Speaker 3: And let's talk about therefore prevention having to take center 506 00:26:16,680 --> 00:26:19,840 Speaker 3: stage rather than just be dealing with the aftermath Lane. 507 00:26:20,080 --> 00:26:22,520 Speaker 3: We are at our hearts a technology show. What is 508 00:26:22,520 --> 00:26:25,520 Speaker 3: it about deep learning that can go there? Unlike other 509 00:26:25,600 --> 00:26:28,600 Speaker 3: applications that we're seeing from rivals or indeed AI more. 510 00:26:28,520 --> 00:26:34,320 Speaker 2: Broadly, Yes, rivals and most security companies are using the 511 00:26:34,359 --> 00:26:37,600 Speaker 2: AI term very loosely, and they focus on machine learning. 512 00:26:38,240 --> 00:26:41,240 Speaker 2: These are models that are made by humans and trained, 513 00:26:41,520 --> 00:26:45,480 Speaker 2: trained on millions of feeds. But at the end of 514 00:26:45,520 --> 00:26:48,440 Speaker 2: the day, the models are only sophisticated as a people 515 00:26:48,480 --> 00:26:52,679 Speaker 2: who design them. The algorithms are not sophisticated. And the 516 00:26:52,720 --> 00:26:58,240 Speaker 2: best comparison is compare if you would chat GPT to 517 00:26:58,600 --> 00:27:03,880 Speaker 2: text learning Deep Instinct to cybersecurity. 518 00:27:03,920 --> 00:27:05,680 Speaker 1: It's that level of quantum leap. 519 00:27:06,920 --> 00:27:10,760 Speaker 3: Interesting use of analogies there. We really appreciate some of 520 00:27:10,760 --> 00:27:13,480 Speaker 3: the time that we've just had with you in Deep Instinct, 521 00:27:13,520 --> 00:27:17,399 Speaker 3: CEO and similarly investor in all areas of cybersecurity and 522 00:27:17,520 --> 00:27:18,480 Speaker 3: air applications. 523 00:27:18,560 --> 00:27:19,880 Speaker 6: We thank you so much for your time. 524 00:27:20,240 --> 00:27:22,160 Speaker 3: Wean while coming up, we're going to talk about more 525 00:27:22,160 --> 00:27:24,640 Speaker 3: of investment, particularly in the world of AI men and adventures, 526 00:27:24,720 --> 00:27:28,960 Speaker 3: raising one point three billion dollars to advance oftificial intelligence startups. 527 00:27:29,480 --> 00:27:32,480 Speaker 6: On that next with partner Matt Murphy ed. 528 00:27:32,480 --> 00:27:35,640 Speaker 5: What have you got, Let's go to space real quick. 529 00:27:35,640 --> 00:27:38,280 Speaker 5: I'm looking at shares of Amazon modestly lower ten to 530 00:27:38,320 --> 00:27:41,399 Speaker 5: one percent, But the company actually confirmed this morning that 531 00:27:41,480 --> 00:27:46,359 Speaker 5: the two prototype Kuyper satellites it currently has in orbit 532 00:27:46,520 --> 00:27:50,359 Speaker 5: are functioning one hundred percent is intended. That is important 533 00:27:50,359 --> 00:27:53,600 Speaker 5: because they now can start a broader mass production pro 534 00:27:53,680 --> 00:27:57,199 Speaker 5: program to build out the constellation literally make the satellites 535 00:27:57,400 --> 00:27:59,399 Speaker 5: and then get them into orbit. Remember, this is a 536 00:28:00,200 --> 00:28:03,160 Speaker 5: be competitors to SpaceX is Starlink, which we've talked about 537 00:28:03,160 --> 00:28:05,480 Speaker 5: a lot on the show this week, but all going 538 00:28:05,520 --> 00:28:09,240 Speaker 5: well so far. For Amazon's own satellite based internet future. 539 00:28:09,600 --> 00:28:29,040 Speaker 5: This has been botechnology one point three five billion. That's 540 00:28:29,080 --> 00:28:32,280 Speaker 5: how much Menlo Ventures has raised in new capital to 541 00:28:32,400 --> 00:28:35,960 Speaker 5: fund promising AIS startups. This new capital will be invested 542 00:28:36,000 --> 00:28:40,000 Speaker 5: by its flagship venture fund, Menlo sixteen, as well as 543 00:28:40,040 --> 00:28:44,280 Speaker 5: Menlo Inflection three and affiliated funds. Melo Ventures partner Matt 544 00:28:44,360 --> 00:28:47,560 Speaker 5: Murphy joins us now for more. Matt, I think you'd 545 00:28:47,720 --> 00:28:50,320 Speaker 5: argue that you've got a good track record both of 546 00:28:50,440 --> 00:28:55,320 Speaker 5: investing in AI and early stage right, but there's clearly 547 00:28:55,760 --> 00:28:59,800 Speaker 5: some near term momentum here. Explain how quickly you raise 548 00:28:59,840 --> 00:29:01,640 Speaker 5: the funds and where you raise them from. 549 00:29:03,320 --> 00:29:07,120 Speaker 17: It was mainly our standard LPs been good long term 550 00:29:07,120 --> 00:29:11,320 Speaker 17: partners with us. We had positive net dollar retention, which 551 00:29:11,320 --> 00:29:13,760 Speaker 17: in kind of the world assassin means that you raised more, 552 00:29:13,840 --> 00:29:16,680 Speaker 17: you increased your base of capital from those who were 553 00:29:16,680 --> 00:29:17,280 Speaker 17: already with you. 554 00:29:17,320 --> 00:29:19,920 Speaker 1: But we did add a number of additional LPs. 555 00:29:20,280 --> 00:29:22,640 Speaker 17: I think the reality is that we've been through kind 556 00:29:22,680 --> 00:29:25,320 Speaker 17: of a bumpy time in the venture business. But if 557 00:29:25,360 --> 00:29:29,560 Speaker 17: one can promise the kind of focus around this opportunity, 558 00:29:29,600 --> 00:29:32,640 Speaker 17: the ability to win be in great companies and build 559 00:29:32,680 --> 00:29:35,960 Speaker 17: a portfolio around AI. It's very compelling to new investors 560 00:29:36,080 --> 00:29:37,200 Speaker 17: and existing investors. 561 00:29:37,320 --> 00:29:40,760 Speaker 3: What's been so interesting is instead of VC money going 562 00:29:40,760 --> 00:29:43,760 Speaker 3: into a lot of these AI startups, particularly the foundational 563 00:29:43,800 --> 00:29:46,800 Speaker 3: model types, we've seen money come from big tech. 564 00:29:47,080 --> 00:29:49,840 Speaker 6: Ultimately, how have you discerned. 565 00:29:49,360 --> 00:29:51,720 Speaker 3: What is the right sort of reward structure that you 566 00:29:51,760 --> 00:29:54,320 Speaker 3: need to see from companies that are sort of wrapping 567 00:29:54,400 --> 00:29:58,720 Speaker 3: around AI, perhaps not building their own models, or indeed 568 00:29:58,760 --> 00:30:01,240 Speaker 3: whether it's those that are building, how do you discern 569 00:30:01,320 --> 00:30:03,440 Speaker 3: what is the best VC backed company? 570 00:30:04,840 --> 00:30:07,440 Speaker 17: Yeah, I mean, I think there's really two massive opportunities 571 00:30:07,520 --> 00:30:07,840 Speaker 17: right now. 572 00:30:07,880 --> 00:30:10,560 Speaker 1: One is kind of this generative AI stack. 573 00:30:10,800 --> 00:30:13,640 Speaker 17: So in technology trends, like when a bunch of companies 574 00:30:13,640 --> 00:30:16,320 Speaker 17: moved to the cloud, we had a whole rebuilding of infrastructure, 575 00:30:16,560 --> 00:30:19,040 Speaker 17: and that's exactly what is going on here in AI. 576 00:30:19,360 --> 00:30:21,640 Speaker 17: And then you look at the application layer and we 577 00:30:21,680 --> 00:30:24,200 Speaker 17: feel like the application layer is a ten year trend. 578 00:30:24,240 --> 00:30:26,280 Speaker 1: There are a bunch of companies that are i mean. 579 00:30:26,400 --> 00:30:29,040 Speaker 17: The entire portfolio you mentioned a lot of big companies 580 00:30:29,400 --> 00:30:32,280 Speaker 17: or at this like perfect intersection of technology readiness and 581 00:30:32,360 --> 00:30:35,880 Speaker 17: kind of CEO company readiness. There's this real move to 582 00:30:35,960 --> 00:30:38,800 Speaker 17: kind of adopt AI as fast as possible. We'd say 583 00:30:38,800 --> 00:30:41,720 Speaker 17: that the application opportunity is really a ten year opportunity, 584 00:30:41,760 --> 00:30:44,080 Speaker 17: and maybe even some of the best applications will be 585 00:30:44,080 --> 00:30:46,920 Speaker 17: built in a couple few years. Is the technology matures 586 00:30:46,920 --> 00:30:52,200 Speaker 17: and entrepreneurs imagination and comfort with deploying these technologies evolves. 587 00:30:52,280 --> 00:30:54,400 Speaker 17: But right here now we feel like there's the biggest 588 00:30:54,400 --> 00:30:56,440 Speaker 17: opportunity in picks and shovels. So it's those kind of 589 00:30:56,480 --> 00:31:01,840 Speaker 17: infrastructure building blocks obviously in nvidial like anthropic and open AI. 590 00:31:01,960 --> 00:31:04,960 Speaker 17: But there's a whole big middle there that has to 591 00:31:05,040 --> 00:31:08,800 Speaker 17: happen well for applications to be built. So it's picking models, 592 00:31:08,840 --> 00:31:13,080 Speaker 17: training models, observing models, optimizing models. There's just a whole 593 00:31:13,080 --> 00:31:15,720 Speaker 17: big body of work that's coming together right now that's 594 00:31:15,760 --> 00:31:18,560 Speaker 17: going to make all of this easier and accelerate the 595 00:31:18,560 --> 00:31:21,120 Speaker 17: application innovation even more so. 596 00:31:21,640 --> 00:31:23,720 Speaker 3: Of course, I mean Meno aventures itself one of the 597 00:31:23,720 --> 00:31:27,200 Speaker 3: oldest vcs from the Bay Area. I mean, is the 598 00:31:27,920 --> 00:31:31,000 Speaker 3: founder you want to backcoming from the West coast? Is 599 00:31:31,000 --> 00:31:34,760 Speaker 3: it now dispersed throughout global opportunities? 600 00:31:34,800 --> 00:31:40,040 Speaker 17: Now the venture business has gotten more global, but San 601 00:31:40,040 --> 00:31:43,240 Speaker 17: Francisco's definitely having another renaissance. 602 00:31:43,320 --> 00:31:43,960 Speaker 7: The Bay Area. 603 00:31:44,120 --> 00:31:47,520 Speaker 17: We have the most AI talent, i'd say, in the world, 604 00:31:47,600 --> 00:31:50,080 Speaker 17: and people are kind of flocking back to be part 605 00:31:50,120 --> 00:31:52,960 Speaker 17: of a lot of these companies. So there are many 606 00:31:53,000 --> 00:31:55,800 Speaker 17: pockets of venture capital these days. Obviously New York's been 607 00:31:55,840 --> 00:31:59,440 Speaker 17: a big hub. Some good infrastructure opportunities and application companies 608 00:31:59,480 --> 00:32:03,160 Speaker 17: there La Seattle, Austin, et cetera, Boston. 609 00:32:03,320 --> 00:32:06,000 Speaker 1: But San Francisco for AI is definitely the upper center. 610 00:32:07,400 --> 00:32:08,800 Speaker 5: I want to go back real quick to that that 611 00:32:08,920 --> 00:32:12,280 Speaker 5: kind of ten year time horizon that you're outlining. It's 612 00:32:12,360 --> 00:32:15,920 Speaker 5: kind of like bench capital one oh one. But across 613 00:32:15,960 --> 00:32:18,600 Speaker 5: the startup curve, loads of folks come on this show 614 00:32:18,640 --> 00:32:23,000 Speaker 5: and say the reality is ninety percent of these startups 615 00:32:23,040 --> 00:32:26,880 Speaker 5: are going to fail. AI startups nine zero percent. Do 616 00:32:27,000 --> 00:32:29,200 Speaker 5: you share that kind of outlook. 617 00:32:30,760 --> 00:32:34,400 Speaker 17: Well, I think that the numbers are a bit better 618 00:32:34,440 --> 00:32:36,920 Speaker 17: than that. I mean, I think about fifty percent of 619 00:32:36,960 --> 00:32:41,160 Speaker 17: companies you know failed, don't don't don't return capital. There 620 00:32:41,240 --> 00:32:43,440 Speaker 17: is a gold rush right now and rightfully because the 621 00:32:43,480 --> 00:32:45,440 Speaker 17: opportunity is so big, I mean, and just to put 622 00:32:45,440 --> 00:32:48,240 Speaker 17: that in perspective for you, Historically in venture if you 623 00:32:48,680 --> 00:32:51,040 Speaker 17: went from zero to one the first year, one to three, 624 00:32:51,240 --> 00:32:53,880 Speaker 17: three to ten to third year, that's really good by 625 00:32:54,200 --> 00:32:56,920 Speaker 17: you know, classic venture standards. We're seeing companies in our 626 00:32:56,960 --> 00:32:59,960 Speaker 17: own portfolio not to be named, but going from zero 627 00:33:00,120 --> 00:33:02,560 Speaker 17: to twenty and zero to one hundred in one year. 628 00:33:02,960 --> 00:33:06,080 Speaker 17: So rightfully, there's a gold rush around this market, and 629 00:33:06,200 --> 00:33:08,440 Speaker 17: there will of course be some things that don't stand 630 00:33:08,480 --> 00:33:10,520 Speaker 17: the test of time, but we're more leaning into it 631 00:33:10,560 --> 00:33:14,040 Speaker 17: optimisticly that we're seeing signals that this is the fastest 632 00:33:14,040 --> 00:33:15,480 Speaker 17: moving ecosystem we've ever seen. 633 00:33:15,520 --> 00:33:17,440 Speaker 1: Adventure Matt. 634 00:33:17,480 --> 00:33:20,800 Speaker 5: When a founder comes to you with the pitch deck 635 00:33:20,920 --> 00:33:25,360 Speaker 5: and it's super shiny and exciting, how much emphasis do 636 00:33:25,440 --> 00:33:29,160 Speaker 5: you put on their access to compute? You know, like 637 00:33:29,240 --> 00:33:33,040 Speaker 5: capital is one thing, but their ability to actually you 638 00:33:33,200 --> 00:33:36,000 Speaker 5: get the resources to build the thing that they tell 639 00:33:36,040 --> 00:33:36,920 Speaker 5: you they're going to build. 640 00:33:38,360 --> 00:33:40,520 Speaker 17: Yeah, I feel like that problem has been a little 641 00:33:40,520 --> 00:33:44,040 Speaker 17: bit overhyped. I feel like Jensen's going to ramp up 642 00:33:44,320 --> 00:33:46,760 Speaker 17: production and a number of other companies are come forward, 643 00:33:46,800 --> 00:33:51,360 Speaker 17: coming forward with GPU GPU capabilities. The main issue right 644 00:33:51,360 --> 00:33:54,080 Speaker 17: now is people really figuring out the way to do 645 00:33:54,160 --> 00:33:58,160 Speaker 17: something innovative. I think the application layer especially, there's a 646 00:33:58,160 --> 00:34:00,480 Speaker 17: lot of bolt on things, and there should be because 647 00:34:00,520 --> 00:34:03,240 Speaker 17: you can take a current application, apply an LLM to 648 00:34:03,280 --> 00:34:05,680 Speaker 17: it and makes the application smarter better when in the 649 00:34:05,720 --> 00:34:09,200 Speaker 17: history we had this opportunity for a computer to do 650 00:34:09,280 --> 00:34:12,319 Speaker 17: reasoning and writing at the level that it's doing right now. 651 00:34:12,480 --> 00:34:14,919 Speaker 17: So all those things are super exciting, but there's kind 652 00:34:14,920 --> 00:34:18,680 Speaker 17: of early stages for imagination of what's possible, and that's 653 00:34:18,719 --> 00:34:20,719 Speaker 17: really what we're going to see involve and accelerate over 654 00:34:20,760 --> 00:34:22,640 Speaker 17: the next couple of years. So I'd say as we 655 00:34:22,680 --> 00:34:25,440 Speaker 17: look at entrepreneurs, it's less about can you get access 656 00:34:25,440 --> 00:34:25,960 Speaker 17: to compute? 657 00:34:26,000 --> 00:34:27,440 Speaker 1: I feel like that'll be solved. 658 00:34:27,480 --> 00:34:29,920 Speaker 17: It's more about what are you doing that's distinctive that 659 00:34:29,960 --> 00:34:31,520 Speaker 17: others can't do well? 660 00:34:31,560 --> 00:34:34,880 Speaker 3: You made the right bets in the past. I think Ruber, Roku, Poshmark, 661 00:34:34,920 --> 00:34:36,319 Speaker 3: to name but a few. We thank you so much, 662 00:34:36,360 --> 00:34:38,399 Speaker 3: Matt Murphy for bringing on where you see the next 663 00:34:38,400 --> 00:34:47,279 Speaker 3: sort of opportunities for menlo ventures. 664 00:34:49,400 --> 00:34:53,799 Speaker 5: Billionaire Elon Musk endorsed an anti Semitic post on x 665 00:34:53,880 --> 00:34:57,360 Speaker 5: that attacked members of the Jewish community for pushing quote 666 00:34:57,400 --> 00:35:01,480 Speaker 5: hatred against white people. Also point out that we've heard 667 00:35:01,520 --> 00:35:04,600 Speaker 5: in the last hour that Musk's name is no longer 668 00:35:04,640 --> 00:35:07,719 Speaker 5: on the lineup as speakers at apex here in San Francisco. 669 00:35:08,120 --> 00:35:11,319 Speaker 5: We do not know the reason why his name is 670 00:35:11,360 --> 00:35:13,719 Speaker 5: no longer on that list of speakers, and here at 671 00:35:13,760 --> 00:35:16,279 Speaker 5: Bloomberg News we will chase that throughout the day. Let's 672 00:35:16,280 --> 00:35:20,839 Speaker 5: bring in Bloomberg's big tech editors, Sarah Freyer. What do 673 00:35:20,920 --> 00:35:24,120 Speaker 5: we know about this post and Musk's response to it? 674 00:35:24,760 --> 00:35:29,080 Speaker 12: Well, this has this post had echoes of the great 675 00:35:29,120 --> 00:35:32,480 Speaker 12: replacement theory, one of the things that has motivated some 676 00:35:32,560 --> 00:35:37,320 Speaker 12: of the shootings in the Jewish community of past years. 677 00:35:38,520 --> 00:35:42,960 Speaker 12: And Musk responded to it saying that it was the truth. 678 00:35:43,520 --> 00:35:47,399 Speaker 12: And then he built on his comments. He related them 679 00:35:47,480 --> 00:35:53,000 Speaker 12: to his dissatisfaction with the d L, the Anti Defamation League, 680 00:35:53,000 --> 00:35:57,960 Speaker 12: which is a group that is probably the biggest fighter 681 00:35:58,000 --> 00:36:02,960 Speaker 12: of anti anti Semitism in the world, a nonprofit, and 682 00:36:03,000 --> 00:36:05,239 Speaker 12: then he brought into his comments back and said, you know, 683 00:36:05,280 --> 00:36:08,080 Speaker 12: I'm not just talking about the ADL, but anyone who 684 00:36:08,200 --> 00:36:13,719 Speaker 12: espouses anti white rhetoric and anti Asian rhetoric. So I 685 00:36:13,760 --> 00:36:17,719 Speaker 12: think we have seen a bit more from Musk his 686 00:36:17,880 --> 00:36:21,239 Speaker 12: concern about anti white rhetoric. And of course this is 687 00:36:21,280 --> 00:36:25,800 Speaker 12: a very charged time to be saying those sorts of things. 688 00:36:25,840 --> 00:36:28,720 Speaker 12: There is ongoing violence in the world. He is running 689 00:36:28,800 --> 00:36:32,680 Speaker 12: a massive communication platform. He has more than one hundred 690 00:36:32,680 --> 00:36:36,560 Speaker 12: and forty million followers himself. So I do think that 691 00:36:37,239 --> 00:36:39,520 Speaker 12: you know, when he does this, it is news and. 692 00:36:40,080 --> 00:36:43,000 Speaker 3: Talk about of course, that this isn't the first time. 693 00:36:43,080 --> 00:36:45,960 Speaker 3: It was last year the American Jewish Committee actually sort 694 00:36:46,000 --> 00:36:50,920 Speaker 3: of really pushed on Musk to apologize previously for a 695 00:36:51,040 --> 00:36:55,080 Speaker 3: deleted controversial tweet as they were then known post once 696 00:36:55,120 --> 00:36:58,520 Speaker 3: again that made satirical comparisons at the time. And I'm 697 00:36:58,560 --> 00:37:01,000 Speaker 3: interested in the fact that he in particular has been 698 00:37:01,200 --> 00:37:04,200 Speaker 3: sort of blaming the ADL, the Anti Defamation League for 699 00:37:04,239 --> 00:37:06,200 Speaker 3: a slump in his own advertising right. 700 00:37:06,280 --> 00:37:08,080 Speaker 6: And I wonder to this end. 701 00:37:08,040 --> 00:37:11,160 Speaker 3: Like what how we try and balance Mosque says is 702 00:37:12,040 --> 00:37:15,120 Speaker 3: pro free speech, and actually he said at the time 703 00:37:15,160 --> 00:37:18,879 Speaker 3: against Annie's anti semitism in of any kind, but yet 704 00:37:18,920 --> 00:37:22,359 Speaker 3: he continues to perhaps walk a very difficult line. 705 00:37:23,680 --> 00:37:26,760 Speaker 12: Yeah, I think I think when people hear the words 706 00:37:26,760 --> 00:37:30,000 Speaker 12: anti semitism, they sort of cringe and say, oh, that's 707 00:37:30,040 --> 00:37:32,239 Speaker 12: not that's not me. But then when you look at 708 00:37:32,239 --> 00:37:36,560 Speaker 12: the actual content of his tweets and the people that 709 00:37:36,600 --> 00:37:40,040 Speaker 12: he has been responding to, remember on Twitter, who you 710 00:37:40,120 --> 00:37:44,640 Speaker 12: respond to actually affects the algorithm to the weight of 711 00:37:44,680 --> 00:37:48,160 Speaker 12: his following where he replies to people even to say 712 00:37:48,239 --> 00:37:53,239 Speaker 12: things like hm or interesting that can then amplify those voices, 713 00:37:53,320 --> 00:37:55,360 Speaker 12: and we've seen him do that a number of times. 714 00:37:55,600 --> 00:37:57,960 Speaker 12: I would say this most recent post is maybe the 715 00:37:58,000 --> 00:38:03,560 Speaker 12: most explicit that he's been so far about his concern 716 00:38:03,600 --> 00:38:07,600 Speaker 12: over anti white sentiment. But I do think that it's 717 00:38:07,640 --> 00:38:09,800 Speaker 12: something that is affecting his company. 718 00:38:10,040 --> 00:38:11,240 Speaker 6: Like you said, more than. 719 00:38:11,440 --> 00:38:16,040 Speaker 12: Half of advertisers are off the platform. He is wholeheartedly 720 00:38:16,080 --> 00:38:18,960 Speaker 12: blaming the anti deformation leaf for that. They had a 721 00:38:18,960 --> 00:38:22,920 Speaker 12: bit of a patching up since then, but now it 722 00:38:23,040 --> 00:38:26,399 Speaker 12: sounds like he's back to criticizing. 723 00:38:25,840 --> 00:38:27,080 Speaker 6: Them so far. 724 00:38:27,560 --> 00:38:30,400 Speaker 3: Thank you for breaking that particular news point down. And 725 00:38:30,640 --> 00:38:32,640 Speaker 3: we want to keep on discussing the fact that ad 726 00:38:32,920 --> 00:38:37,040 Speaker 3: advertising revenue has been under pressure at X more and 727 00:38:37,160 --> 00:38:40,359 Speaker 3: most broadly, and let's talk about that with Rachel Timographs course, 728 00:38:40,440 --> 00:38:45,200 Speaker 3: founderacy of e Commerce Enablement and analytics software provider Makemac 729 00:38:45,320 --> 00:38:49,920 Speaker 3: and Rachel Ultimately, are you hearing from any of those 730 00:38:49,960 --> 00:38:53,280 Speaker 3: clients and discussion that you're having that people are willing 731 00:38:53,320 --> 00:38:56,600 Speaker 3: to come back to X in its current form, in 732 00:38:56,640 --> 00:38:58,319 Speaker 3: the current environment in which we see it. 733 00:38:59,680 --> 00:39:03,680 Speaker 12: So Ever, since Musk took ownership of Twitter last fall 734 00:39:03,760 --> 00:39:06,960 Speaker 12: in twenty twenty two, at MCMAC, we've essentially seen a 735 00:39:07,200 --> 00:39:11,960 Speaker 12: ninety percent decline in brand traffic. In May of twenty 736 00:39:12,000 --> 00:39:15,719 Speaker 12: to twenty three, when Linda Racirino was stepping in, we 737 00:39:15,880 --> 00:39:20,000 Speaker 12: actually saw some hope where brands were like, Okay, here's 738 00:39:20,080 --> 00:39:24,560 Speaker 12: someone who understands brand safety, and we're going to try 739 00:39:24,600 --> 00:39:27,440 Speaker 12: a few dollars, not five hundred thousand, not a million 740 00:39:27,480 --> 00:39:30,200 Speaker 12: dollars in advertising buy. But I'm talking about publicly traded 741 00:39:30,200 --> 00:39:32,760 Speaker 12: companies saying hey, we'll try fifty thousand dollars in Twitter 742 00:39:32,800 --> 00:39:34,080 Speaker 12: ad spend and see how it works. 743 00:39:35,800 --> 00:39:37,040 Speaker 7: But Musk is voltile. 744 00:39:37,680 --> 00:39:39,640 Speaker 4: Yep, I'll I'm sorry to intrup. He's keep going. 745 00:39:40,600 --> 00:39:43,720 Speaker 12: Musk is Boltle, and every single time he does something 746 00:39:43,800 --> 00:39:47,880 Speaker 12: like this, we see a massive decline in Twitter traffic. 747 00:39:48,400 --> 00:39:52,839 Speaker 12: So there is a direct correlation to his activities and 748 00:39:52,960 --> 00:39:53,960 Speaker 12: brand AdSpend. 749 00:39:56,200 --> 00:39:58,319 Speaker 5: Rachel, one of the things we've been been tracking on 750 00:39:58,360 --> 00:40:01,839 Speaker 5: the X platform from a technol perspective is a world 751 00:40:01,920 --> 00:40:04,560 Speaker 5: you know well, which is video. They put a huge 752 00:40:04,600 --> 00:40:08,840 Speaker 5: emphasis on video as a strategy to bring back creators 753 00:40:08,840 --> 00:40:11,040 Speaker 5: and then bring back advertisers. 754 00:40:11,960 --> 00:40:15,080 Speaker 12: How do you see that going? So this is the 755 00:40:15,120 --> 00:40:18,279 Speaker 12: interesting thing. When we saw brands retest the water with 756 00:40:18,360 --> 00:40:21,759 Speaker 12: Twitter essentially around May and June of twenty twenty three, 757 00:40:22,520 --> 00:40:25,960 Speaker 12: we actually saw strong results. So I can tell you 758 00:40:26,080 --> 00:40:28,319 Speaker 12: that the investments that they have made in their ad 759 00:40:28,320 --> 00:40:32,920 Speaker 12: products aren't improving the ad products, but it's not enough 760 00:40:33,400 --> 00:40:36,600 Speaker 12: for these brands to want to be associated with his 761 00:40:36,760 --> 00:40:42,399 Speaker 12: volatile behavior. Brand safety trumps any investments that they're making 762 00:40:42,440 --> 00:40:43,400 Speaker 12: in their ad products. 763 00:40:43,719 --> 00:40:47,000 Speaker 3: And to reflect on Linda Yakarino, she has really been 764 00:40:47,040 --> 00:40:50,600 Speaker 3: trying to ampart the focus on brand safety. Have any 765 00:40:50,600 --> 00:40:52,719 Speaker 3: of the moves they've made thus far made a mark 766 00:40:52,800 --> 00:40:53,440 Speaker 3: on the clients? 767 00:40:54,840 --> 00:40:55,600 Speaker 7: Unfortunately? 768 00:40:56,080 --> 00:41:01,359 Speaker 12: I feel that Elon's brand is bigger than brand and 769 00:41:01,520 --> 00:41:04,759 Speaker 12: anything that he does puts a heart to the advancements 770 00:41:04,760 --> 00:41:05,600 Speaker 12: that they're trying to make. 771 00:41:07,239 --> 00:41:09,200 Speaker 3: We want to thank you McK macfounder always so to 772 00:41:09,239 --> 00:41:11,319 Speaker 3: the point and also bring us real data on all 773 00:41:11,320 --> 00:41:13,759 Speaker 3: of it. Found our CEO Rachel Photographs. We thank you 774 00:41:13,800 --> 00:41:15,920 Speaker 3: so much from Brooklyn. Meanwhile, that does it for this 775 00:41:16,040 --> 00:41:18,359 Speaker 3: edition of Bloomberg Technology YEP. 776 00:41:18,440 --> 00:41:20,680 Speaker 5: Recap the show on the podcast, and thank you again 777 00:41:20,760 --> 00:41:23,200 Speaker 5: everyone that tunes into the podcast wherever you get them. 778 00:41:23,239 --> 00:41:27,000 Speaker 5: Apple Spotify, iHeart, and of course we publish the podcast 779 00:41:27,400 --> 00:41:29,680 Speaker 5: to all of the Bloomberg platforms. It's been a really 780 00:41:29,680 --> 00:41:32,120 Speaker 5: great way to keep some of you connected with the show. 781 00:41:32,440 --> 00:41:35,439 Speaker 5: From San Francisco going out in New York City four 782 00:41:35,520 --> 00:41:45,719 Speaker 5: days in the week. This is Bloomberg Technology.