1 00:00:01,800 --> 00:00:04,440 Speaker 1: Hello everybody, and thank you so much for joining us 2 00:00:04,440 --> 00:00:07,880 Speaker 1: for this special edition of Bloomberg Daybreak. US markets are 3 00:00:07,920 --> 00:00:11,280 Speaker 1: closed for the President's Day holiday. I'm Nathan Hager. Coming 4 00:00:11,360 --> 00:00:13,239 Speaker 1: up this hour. We'll look ahead to a couple of 5 00:00:13,320 --> 00:00:17,080 Speaker 1: major lawsuits on the docket. Elon Musk's battle against Open 6 00:00:17,120 --> 00:00:20,560 Speaker 1: Ai and the Justice Department's case against Live Nation and 7 00:00:20,680 --> 00:00:22,920 Speaker 1: ticket Master. We'll break them down with two of our 8 00:00:22,920 --> 00:00:26,799 Speaker 1: litigation analysts from Bloomberg Intelligence, Matthew Shettenhelm on big tech 9 00:00:27,040 --> 00:00:29,600 Speaker 1: and Jennifer Ree on Big ticket. Plus, we have a 10 00:00:29,600 --> 00:00:33,040 Speaker 1: big earnings report coming up from AI Behemoth and Nvidia 11 00:00:33,400 --> 00:00:36,159 Speaker 1: BI analyst man Deep Singh and Kunjohn Sapani will be 12 00:00:36,200 --> 00:00:39,159 Speaker 1: along to preview those results. Before that, though, we hear 13 00:00:39,159 --> 00:00:43,200 Speaker 1: from the world's biggest big box retailer this week, Walmart, 14 00:00:43,280 --> 00:00:46,320 Speaker 1: reports earnings on Thursday. Here to get a set for 15 00:00:46,360 --> 00:00:50,040 Speaker 1: that report, our Bloomberg Intelligence senior analyst Jennifer Bartashis who 16 00:00:50,080 --> 00:00:53,800 Speaker 1: covers retail staples, and Punam Goyle, who's got things covered 17 00:00:53,880 --> 00:00:55,800 Speaker 1: on the e commerce side. Thanks to both of you 18 00:00:55,920 --> 00:00:57,600 Speaker 1: for being with us, and you know, coming off the 19 00:00:57,840 --> 00:01:00,960 Speaker 1: flat retail sales report for decent number that we saw 20 00:01:01,080 --> 00:01:04,120 Speaker 1: recently Jennifer, I'll start with you, how does that affect 21 00:01:04,160 --> 00:01:05,960 Speaker 1: what we could see from Walmart when it comes to 22 00:01:06,040 --> 00:01:06,959 Speaker 1: the earnings this week. 23 00:01:07,760 --> 00:01:11,520 Speaker 2: You know what's interesting is that for Walmart, it doesn't 24 00:01:11,520 --> 00:01:13,959 Speaker 2: matter so much what the retail sales do just because 25 00:01:14,040 --> 00:01:17,400 Speaker 2: the trends that are in place have really been conducive 26 00:01:17,480 --> 00:01:20,480 Speaker 2: to their growth and their business. People are seeking value, 27 00:01:20,520 --> 00:01:26,360 Speaker 2: People are seeking, you know, ways to streamline their time 28 00:01:26,400 --> 00:01:29,679 Speaker 2: and find convenience, and Walmart just seems to be gaining 29 00:01:29,720 --> 00:01:34,640 Speaker 2: share based on their ability to offer that to their customers. So, 30 00:01:34,920 --> 00:01:37,800 Speaker 2: regardless of the macro environment, Walmart really seems to be 31 00:01:37,840 --> 00:01:38,720 Speaker 2: thriving at the moment. 32 00:01:39,080 --> 00:01:41,759 Speaker 1: And put them to bring you into the conversation, We're 33 00:01:41,800 --> 00:01:45,720 Speaker 1: seeing a lot of consumers seeking out Walmart's business on 34 00:01:45,920 --> 00:01:48,920 Speaker 1: the e commerce side as well. How could that play 35 00:01:48,960 --> 00:01:50,160 Speaker 1: out into these earnings? 36 00:01:51,040 --> 00:01:53,080 Speaker 3: We think Walmart will continue to do well on the 37 00:01:53,080 --> 00:01:56,600 Speaker 3: e commerce side. If Amazon is any reflection on how 38 00:01:56,600 --> 00:01:59,280 Speaker 3: the consumer is shopping online, they had great numbers on 39 00:01:59,320 --> 00:02:01,800 Speaker 3: the retail side, high single digit sales growth in their 40 00:02:01,840 --> 00:02:05,280 Speaker 3: online business. We expect Walmart to be no different. They've 41 00:02:05,280 --> 00:02:08,480 Speaker 3: put a lot of investment behind their e commerce unit 42 00:02:08,680 --> 00:02:11,799 Speaker 3: and they have been very quickly gaining share. Its over 43 00:02:11,840 --> 00:02:16,280 Speaker 3: one hundred billion dollars in GMB today. That's pretty impressive 44 00:02:16,320 --> 00:02:19,560 Speaker 3: given how little time they've gotten there. So we think 45 00:02:19,600 --> 00:02:22,040 Speaker 3: the e commerce handle for them will play out while 46 00:02:22,200 --> 00:02:23,320 Speaker 3: just like it did for Amazon. 47 00:02:23,560 --> 00:02:27,760 Speaker 1: You know, it's interesting, Jen, Walmart is seeing competition from 48 00:02:27,840 --> 00:02:31,840 Speaker 1: Amazon on multiple fronts, not just on the e commerce side, 49 00:02:31,880 --> 00:02:34,800 Speaker 1: but Amazon is kind of altering its footprint in the 50 00:02:34,800 --> 00:02:38,840 Speaker 1: grocery business as well. How do you see Walmart weathering 51 00:02:38,919 --> 00:02:40,240 Speaker 1: that well? 52 00:02:40,280 --> 00:02:43,320 Speaker 2: I think what's interesting is that, you know, when Amazon 53 00:02:43,360 --> 00:02:45,760 Speaker 2: announced that they were closing their Amazon Fresh stores and 54 00:02:45,800 --> 00:02:48,440 Speaker 2: their Amazon Ghost stores, which was more of a convenience 55 00:02:48,440 --> 00:02:51,480 Speaker 2: store format. You know, people kind of set up and 56 00:02:51,480 --> 00:02:55,200 Speaker 2: took notice, but it's important to remember there were way 57 00:02:55,280 --> 00:02:58,440 Speaker 2: under one hundred of those stores altogether, so it's never 58 00:02:58,520 --> 00:03:03,240 Speaker 2: been the majority of Amazon's grocery footprint. Instead, you know, 59 00:03:03,320 --> 00:03:05,959 Speaker 2: they have a lot of sales that are what you 60 00:03:05,960 --> 00:03:10,440 Speaker 2: would consider grocery category sales that happen through Amazon dot 61 00:03:10,480 --> 00:03:13,760 Speaker 2: Com and through their Amazon Fresh and so those are 62 00:03:13,919 --> 00:03:17,360 Speaker 2: your your fresh items, as your paper towels, things like that. 63 00:03:18,280 --> 00:03:23,240 Speaker 2: Walmart is the biggest grocer in the United States. You know, 64 00:03:23,320 --> 00:03:27,760 Speaker 2: they own almost thirty percent of market share, so they're 65 00:03:27,880 --> 00:03:31,440 Speaker 2: very well entrenched and because they've been investing in their capabilities. 66 00:03:32,160 --> 00:03:34,480 Speaker 2: You know, I think there's room for Amazon to grow, 67 00:03:34,880 --> 00:03:38,080 Speaker 2: but we're not expecting any kind of major, you know, 68 00:03:38,560 --> 00:03:41,280 Speaker 2: change in who's the leader in grocery over the next 69 00:03:41,360 --> 00:03:41,960 Speaker 2: couple of years. 70 00:03:42,360 --> 00:03:44,680 Speaker 1: You got to think to put them that Walmart's got 71 00:03:44,760 --> 00:03:48,440 Speaker 1: room to grow overall on e commerce as well. Although 72 00:03:48,640 --> 00:03:52,040 Speaker 1: Amazon being the behemoth it is, what's the challenge for 73 00:03:52,120 --> 00:03:54,600 Speaker 1: Walmart to compete online? 74 00:03:55,560 --> 00:03:57,880 Speaker 3: I don't think it's really a challenge anymore because they're 75 00:03:57,920 --> 00:04:01,000 Speaker 3: making the right investments. They're investing like just they're investing 76 00:04:01,080 --> 00:04:04,600 Speaker 3: in product and expanding their marketplace. You know, a lot 77 00:04:04,640 --> 00:04:07,520 Speaker 3: of times people tend to think that if Walmart wins, 78 00:04:07,600 --> 00:04:10,600 Speaker 3: Amazon loses, that's not the case. I think both of 79 00:04:10,640 --> 00:04:13,280 Speaker 3: them can grow together. There's a lot of share shifts 80 00:04:13,280 --> 00:04:15,480 Speaker 3: that are taking place in retail where shopping is just 81 00:04:15,520 --> 00:04:19,159 Speaker 3: gradually moving online. We have estimated that twenty five percent 82 00:04:19,160 --> 00:04:22,440 Speaker 3: of total retail sales in the US are online today 83 00:04:22,480 --> 00:04:24,320 Speaker 3: and they're going to be growing to thirty three percent 84 00:04:24,360 --> 00:04:27,640 Speaker 3: in the next few years. So there's plenty of opportunity 85 00:04:28,040 --> 00:04:32,520 Speaker 3: for retailers to capture that growing opportunity and among them, 86 00:04:32,640 --> 00:04:35,960 Speaker 3: Walmart and Amazon are still probably best position to do so. 87 00:04:36,320 --> 00:04:39,200 Speaker 1: And when it comes to the overall business, Jen, is 88 00:04:39,240 --> 00:04:43,560 Speaker 1: it all about grocery for Walmart? Is that where the 89 00:04:43,600 --> 00:04:47,719 Speaker 1: basis for Walmart's businesses right now? Or is it seeing 90 00:04:48,040 --> 00:04:52,440 Speaker 1: the potential for growth across its categories of items that 91 00:04:52,480 --> 00:04:52,960 Speaker 1: it sells? 92 00:04:53,560 --> 00:04:57,279 Speaker 2: Now, there's definitely growth across all of the categories. You know, 93 00:04:57,360 --> 00:05:02,920 Speaker 2: grocery categories do you comprise about half of Walmart's total revenue, 94 00:05:02,960 --> 00:05:06,200 Speaker 2: so it is important. But you know, the company does 95 00:05:06,240 --> 00:05:10,520 Speaker 2: a great job of of having that broad assortment be 96 00:05:10,640 --> 00:05:13,680 Speaker 2: tailored to be appealing to customers. And that's in the 97 00:05:13,760 --> 00:05:16,920 Speaker 2: US and that's worldwide. And so you know what we 98 00:05:17,000 --> 00:05:20,000 Speaker 2: see is that, you know, grocery is great because it's 99 00:05:20,040 --> 00:05:23,760 Speaker 2: a frequency category. You buy groceries frequently. It takes you 100 00:05:23,800 --> 00:05:26,640 Speaker 2: to stores, but once you're in the store or once 101 00:05:26,640 --> 00:05:30,200 Speaker 2: you're online, placing that order between either the in store experience, 102 00:05:30,520 --> 00:05:35,479 Speaker 2: the merchandise selection, or the technology that's used from a 103 00:05:35,560 --> 00:05:38,960 Speaker 2: from an interface perspective, it's really helping guide people to 104 00:05:39,040 --> 00:05:42,080 Speaker 2: buy more than just their groceries at Walmart, and so 105 00:05:42,320 --> 00:05:45,559 Speaker 2: you know, they've had strong, much stronger general merchandise sales 106 00:05:45,560 --> 00:05:47,680 Speaker 2: than some of their peers over the last last few 107 00:05:47,760 --> 00:05:48,640 Speaker 2: quarters and. 108 00:05:48,600 --> 00:05:51,240 Speaker 1: Put them how do you see Walmart continuing to grow 109 00:05:51,360 --> 00:05:55,000 Speaker 1: its business on the tech side in terms of developing 110 00:05:55,040 --> 00:05:59,479 Speaker 1: its interfaces integrating artificial intelligence into what it does. 111 00:06:00,320 --> 00:06:03,279 Speaker 3: I think, just like everyone else today, the integration of 112 00:06:03,360 --> 00:06:08,440 Speaker 3: artificial intelligence agentic shopping is key. Walmart's integrated itself into 113 00:06:08,520 --> 00:06:12,600 Speaker 3: chat GBT, so it's clearly opening up avenues to broaden 114 00:06:12,640 --> 00:06:17,000 Speaker 3: its customer base and get a piece of that agentic 115 00:06:17,200 --> 00:06:22,240 Speaker 3: AI shopping driven conversion. We think they're making advancements to 116 00:06:22,360 --> 00:06:26,040 Speaker 3: broaden their customer base beyond you know, when you think 117 00:06:26,080 --> 00:06:28,720 Speaker 3: about the Walmart customers, it is broad and it is 118 00:06:29,400 --> 00:06:32,479 Speaker 3: a customer predominantly that's seeking value. But they're trying to 119 00:06:32,560 --> 00:06:35,040 Speaker 3: expand that and they have to some extent, and Jen 120 00:06:35,080 --> 00:06:37,919 Speaker 3: could talk about this, have really expanded that through the 121 00:06:37,920 --> 00:06:41,720 Speaker 3: Walmart Plus membership. But in using AI and agentic shopping 122 00:06:41,760 --> 00:06:46,360 Speaker 3: and just technology robotics automation, we think they are making 123 00:06:46,839 --> 00:06:49,279 Speaker 3: progress and they will continue to invest in that front 124 00:06:49,279 --> 00:06:52,120 Speaker 3: to move forward in retail because if they don't, quite honestly, 125 00:06:52,200 --> 00:06:54,080 Speaker 3: they won't be able to continue to gain share. 126 00:06:55,000 --> 00:06:59,320 Speaker 1: I'm speaking with Punum Goyle and Jen Bartascius of Bloomberg Intelligence. 127 00:06:59,400 --> 00:07:02,560 Speaker 1: Jen pickop to that point that Punam raised there in 128 00:07:02,640 --> 00:07:06,440 Speaker 1: terms of the Walmart Plus business, there has been this 129 00:07:06,560 --> 00:07:10,360 Speaker 1: push into more subscriber fed business. How is that paying 130 00:07:10,400 --> 00:07:11,200 Speaker 1: off for Walmart? 131 00:07:12,200 --> 00:07:15,040 Speaker 2: Yeah, it's it's a it's a great program for Walmart. 132 00:07:15,440 --> 00:07:18,080 Speaker 2: When you think about what Walmart has been talking about 133 00:07:18,120 --> 00:07:20,720 Speaker 2: and over the past several quarters, they've been bringing in 134 00:07:20,760 --> 00:07:24,160 Speaker 2: more higher income households into their ecosystem. Now, part of 135 00:07:24,200 --> 00:07:27,760 Speaker 2: that is people seeking value, but the Walmart Plus program, 136 00:07:27,800 --> 00:07:31,720 Speaker 2: when they get people engaged with that, that makes people sticky. 137 00:07:32,440 --> 00:07:35,680 Speaker 2: And so historically, when the economy has been weak, Walmart 138 00:07:35,720 --> 00:07:38,920 Speaker 2: gains people, they gain shoppers, but then as the economy 139 00:07:38,920 --> 00:07:42,120 Speaker 2: gets better, some of those customers bleed away. What Walmart 140 00:07:42,160 --> 00:07:44,960 Speaker 2: Plus does is it helps keep all of those customers 141 00:07:45,000 --> 00:07:48,400 Speaker 2: sticky and in the in the Walmart universe, and through 142 00:07:48,560 --> 00:07:52,040 Speaker 2: the offering of convenience of being able to have things 143 00:07:52,040 --> 00:07:54,240 Speaker 2: delivered to your house or even into your house and 144 00:07:54,280 --> 00:07:57,760 Speaker 2: into your refrigerator directly, or being able to pick things 145 00:07:57,840 --> 00:08:00,040 Speaker 2: up at the at the curb side, and all the 146 00:08:00,000 --> 00:08:03,520 Speaker 2: their perks and benefits that they offer via that membership program. 147 00:08:04,160 --> 00:08:09,160 Speaker 2: It really helps keep those customers you know, engaged, and 148 00:08:09,320 --> 00:08:13,239 Speaker 2: it provides a recurring revenue source in terms of membership fee. 149 00:08:13,600 --> 00:08:15,560 Speaker 2: So there's there's lots of levels to the win of 150 00:08:15,640 --> 00:08:18,160 Speaker 2: having a robust program like Walmart Plus. 151 00:08:17,880 --> 00:08:22,120 Speaker 1: And in terms of the value seeking customer getting into 152 00:08:22,160 --> 00:08:25,600 Speaker 1: that engagement as well. Poonam, do you see that trend 153 00:08:25,680 --> 00:08:29,360 Speaker 1: continuing having some of these more higher middle income consumers 154 00:08:29,360 --> 00:08:32,840 Speaker 1: getting driven more into Walmart to seek that value. 155 00:08:33,280 --> 00:08:35,480 Speaker 3: Yeah. I don't think that changes much for the lower 156 00:08:35,559 --> 00:08:37,120 Speaker 3: end customer. I mean, at the end of the day, 157 00:08:37,200 --> 00:08:41,840 Speaker 3: Walmart stands for value, so everyone wants to find things cheaper. 158 00:08:41,880 --> 00:08:43,959 Speaker 3: I don't think a higher income consumer would go out 159 00:08:44,000 --> 00:08:46,400 Speaker 3: and say I'm willing to pay more unless there's a 160 00:08:46,400 --> 00:08:49,000 Speaker 3: service element to it, or there's an aesthetic involved or 161 00:08:49,000 --> 00:08:52,320 Speaker 3: a better brand involved. But I think having a broad 162 00:08:52,559 --> 00:08:56,280 Speaker 3: array of customers which Walmart is now targeting to expand 163 00:08:56,280 --> 00:08:59,200 Speaker 3: that upper end of the funnel, it doesn't hurt them. 164 00:08:59,360 --> 00:09:02,880 Speaker 3: And it's an easy way to do that because when 165 00:09:02,880 --> 00:09:06,520 Speaker 3: you're on an online platform, the experience is similar to 166 00:09:06,600 --> 00:09:09,440 Speaker 3: all versus you know, people would argue in the past 167 00:09:09,440 --> 00:09:12,160 Speaker 3: when you walk into a Walmart store, the experience is 168 00:09:12,280 --> 00:09:14,560 Speaker 3: very different. Than when you were to walk into a 169 00:09:14,559 --> 00:09:17,600 Speaker 3: whole food store, right, But if you're shopping online for 170 00:09:17,760 --> 00:09:21,520 Speaker 3: paper towels, it's wherever you're used to going. And that's 171 00:09:21,520 --> 00:09:24,000 Speaker 3: what Jen talked about the stickiness of it. Right when 172 00:09:24,160 --> 00:09:26,720 Speaker 3: you're a Prime member, you're a Walmart Plus member, because 173 00:09:26,760 --> 00:09:29,520 Speaker 3: you're paying for this membership, you want to utilize it. 174 00:09:29,559 --> 00:09:31,280 Speaker 3: And once you begin to utilize it and see the 175 00:09:31,360 --> 00:09:33,839 Speaker 3: value in it, that's just a natural place that you're 176 00:09:33,880 --> 00:09:34,920 Speaker 3: going to go to next. 177 00:09:35,400 --> 00:09:37,400 Speaker 1: You know, Jen, this is an interesting time in the 178 00:09:37,800 --> 00:09:42,720 Speaker 1: big retail business with a lot of these sort of 179 00:09:43,200 --> 00:09:45,440 Speaker 1: businesses that we think of as catering to the lower 180 00:09:45,520 --> 00:09:48,560 Speaker 1: end consumer, like Dollar Tree, Dollar General moving into some 181 00:09:48,600 --> 00:09:52,000 Speaker 1: of these bigger markets and target continuing to try to 182 00:09:52,080 --> 00:09:55,240 Speaker 1: find a direction. How do you see Walmart sort of 183 00:09:55,320 --> 00:10:00,480 Speaker 1: navigating some of that perhaps increased competition from the lower 184 00:10:00,559 --> 00:10:01,320 Speaker 1: end retailers. 185 00:10:02,320 --> 00:10:04,440 Speaker 2: Yeah, it's it's a it's a very good question. You know, 186 00:10:04,520 --> 00:10:08,679 Speaker 2: when when you look at the customer that the the 187 00:10:08,800 --> 00:10:12,400 Speaker 2: organizations that target the lower end consumers, like your dollar stores, 188 00:10:13,200 --> 00:10:16,320 Speaker 2: you know, in terms of store base, those those companies 189 00:10:16,320 --> 00:10:19,440 Speaker 2: tend to be located in greater proximity to some of 190 00:10:19,480 --> 00:10:22,120 Speaker 2: the you know, to some of those customers. So you know, 191 00:10:22,240 --> 00:10:25,520 Speaker 2: it's about it's about trip frequency. So dollar stores are 192 00:10:25,559 --> 00:10:28,880 Speaker 2: really favored when people are doing kind of quick fill 193 00:10:28,920 --> 00:10:32,960 Speaker 2: in trips in between larger shops. Where Walmart comes into 194 00:10:32,960 --> 00:10:35,600 Speaker 2: place is for that larger shop when people are planning, 195 00:10:35,880 --> 00:10:38,640 Speaker 2: you know, multiple meals in advance. They're planning, you know, 196 00:10:39,200 --> 00:10:42,680 Speaker 2: for a larger event or something like that. And so 197 00:10:43,160 --> 00:10:46,520 Speaker 2: you know, as we've seen you know, some uh some 198 00:10:46,520 --> 00:10:49,959 Speaker 2: some consolidation happening in the in the dollar store industry. 199 00:10:50,000 --> 00:10:51,800 Speaker 2: You know, we saw ninety nine cent stores go out 200 00:10:51,840 --> 00:10:55,080 Speaker 2: of business. You know, we saw a party city collapse. 201 00:10:55,720 --> 00:10:58,760 Speaker 2: That offers opportunity to ev for everybody, and and Walmart 202 00:10:58,800 --> 00:10:59,880 Speaker 2: is included in that mix. 203 00:11:00,320 --> 00:11:02,520 Speaker 1: And Jen, just to close this out, I think this 204 00:11:02,600 --> 00:11:05,640 Speaker 1: is going to be the first earnings report under Walmart's 205 00:11:05,679 --> 00:11:09,400 Speaker 1: new CEO, John Ferner, Right, Uh, what what's the pressure 206 00:11:09,440 --> 00:11:12,440 Speaker 1: on him, uh to keep up the momentum that we've 207 00:11:12,440 --> 00:11:14,760 Speaker 1: seen under Doug McMillan over the years. 208 00:11:15,800 --> 00:11:17,840 Speaker 2: I think that they certainly there's there's going to be 209 00:11:17,880 --> 00:11:21,520 Speaker 2: expectations that he continues with the things that have really 210 00:11:21,520 --> 00:11:24,840 Speaker 2: benefited Walmart in recent years, which is that willingness to 211 00:11:25,160 --> 00:11:30,800 Speaker 2: experiment and and fail. So experiment, adapt what what works, 212 00:11:31,000 --> 00:11:33,640 Speaker 2: you know, roll it up quickly. If something doesn't work, 213 00:11:33,920 --> 00:11:36,360 Speaker 2: walk away. You know, I think that he's you know, 214 00:11:36,400 --> 00:11:39,280 Speaker 2: he's been with Walmart for a while, so you know, 215 00:11:39,320 --> 00:11:43,000 Speaker 2: he certainly has the perspective of what the company has 216 00:11:43,040 --> 00:11:46,280 Speaker 2: been doing. But I think all eyes will be on whether, 217 00:11:46,559 --> 00:11:50,840 Speaker 2: you know, he finds new opportunities to kind of supplement 218 00:11:50,840 --> 00:11:54,079 Speaker 2: the ecosystem that Walmart has been building. That said, we're 219 00:11:54,080 --> 00:11:56,600 Speaker 2: not expecting any major pivots and strategy in the short 220 00:11:56,679 --> 00:12:01,520 Speaker 2: term because the the the this is working quite well 221 00:12:01,559 --> 00:12:03,600 Speaker 2: for Walmart at the moment, and they continue to gain 222 00:12:03,640 --> 00:12:06,120 Speaker 2: share and they continue to put on new customers. 223 00:12:05,960 --> 00:12:08,560 Speaker 1: Really appreciate this as we look ahead to these earnings 224 00:12:08,559 --> 00:12:12,920 Speaker 1: from Walmart on Thursday. That's Jen Bartashis and Punam Goyle, 225 00:12:13,160 --> 00:12:16,560 Speaker 1: retail analysts for Bloomberg Intelligence. And up next, we're going 226 00:12:16,600 --> 00:12:18,200 Speaker 1: to stick with the earnings theme and look at what 227 00:12:18,280 --> 00:12:21,640 Speaker 1: to expect from Chip Giant in Vidia. It's twenty minutes 228 00:12:21,679 --> 00:12:25,000 Speaker 1: past the hour. I'm Nathan Hager, and this is Bloomberg. 229 00:12:35,320 --> 00:12:38,520 Speaker 1: Welcome back to this special edition of Bloomberg Daybreak. US 230 00:12:38,520 --> 00:12:41,720 Speaker 1: markets are closed for the President's holiday. I'm Nathan Hager, 231 00:12:41,720 --> 00:12:45,559 Speaker 1: and we continue our focus on earnings. Nvidia reports its 232 00:12:45,640 --> 00:12:48,920 Speaker 1: latest quarterly numbers next week. From what we can expect 233 00:12:48,920 --> 00:12:51,600 Speaker 1: from the chip behemoth, let's bring in Man Deep Saying, 234 00:12:51,640 --> 00:12:54,640 Speaker 1: global head of tech research for Bloomberg Intelligence, and BI 235 00:12:54,800 --> 00:12:58,640 Speaker 1: senior Semiconductors analyst Kunjohn Sabani. Thanks so much to both 236 00:12:58,679 --> 00:13:00,760 Speaker 1: of you for being with us, and many people start 237 00:13:00,800 --> 00:13:02,720 Speaker 1: with you because it seems like the bar keeps getting 238 00:13:02,760 --> 00:13:06,640 Speaker 1: set higher and higher for Nvidia quarter in and quarter out. 239 00:13:07,160 --> 00:13:08,840 Speaker 1: Do you agree with that and how high is the 240 00:13:08,840 --> 00:13:09,560 Speaker 1: bar this time? 241 00:13:10,080 --> 00:13:12,600 Speaker 4: Well, so, in the last couple of years, what we 242 00:13:12,679 --> 00:13:18,640 Speaker 4: have seen is in Vidia's top line growth actually tracks 243 00:13:19,440 --> 00:13:23,600 Speaker 4: the hyperscale capex changes. And what we have seen here 244 00:13:23,640 --> 00:13:29,200 Speaker 4: today is all these hyperscalers raising their capex expectations for 245 00:13:29,280 --> 00:13:33,480 Speaker 4: twenty twenty six and we're talking about another year of 246 00:13:33,559 --> 00:13:38,240 Speaker 4: a sixty percent increase in total capex. And so if 247 00:13:38,320 --> 00:13:42,040 Speaker 4: that's tracking, you know, in Vidia's top line growth and 248 00:13:42,120 --> 00:13:44,160 Speaker 4: it's a it's a good proxy for that, then we 249 00:13:44,240 --> 00:13:47,160 Speaker 4: can expect something similar and that's where the estimates keep 250 00:13:47,200 --> 00:13:52,280 Speaker 4: getting revised upward. And now you know, consensus is forecasting 251 00:13:52,320 --> 00:13:55,760 Speaker 4: almost a sixty percent increase in in Vidio's top line 252 00:13:55,800 --> 00:13:56,840 Speaker 4: for twenty twenty six. 253 00:13:57,440 --> 00:14:02,080 Speaker 1: My eyebrowser already hurting just thinking about that, Kunjon. To 254 00:14:02,240 --> 00:14:05,920 Speaker 1: that point, six hundred and fifty billion dollars over the 255 00:14:05,960 --> 00:14:08,360 Speaker 1: next year is the number we keep hearing from the 256 00:14:08,720 --> 00:14:13,640 Speaker 1: four hyper scalers in terms of their AI plans. How 257 00:14:13,640 --> 00:14:18,480 Speaker 1: do you think that plays out for Nvidia's results, Well. 258 00:14:18,320 --> 00:14:22,720 Speaker 5: That should be a definite tailwind. Remember sometime in three 259 00:14:22,880 --> 00:14:26,960 Speaker 5: Q calendar three Q last year, Jensen gave out a 260 00:14:27,160 --> 00:14:30,600 Speaker 5: five hundred billion dollar This is Nvidia's revenue, not the 261 00:14:30,680 --> 00:14:33,680 Speaker 5: hyperscale care PACs, but five hundred billion dollar of a 262 00:14:33,880 --> 00:14:38,000 Speaker 5: pipeline of a backlog for both its Blackwell and upcoming 263 00:14:38,440 --> 00:14:41,480 Speaker 5: Rubin which will be in second half twenty six through 264 00:14:41,560 --> 00:14:46,720 Speaker 5: twenty twenty six. Since then, as Mandeep mentioned, the estimates 265 00:14:46,760 --> 00:14:49,920 Speaker 5: for these hyper scalers have gone up in some cases 266 00:14:50,280 --> 00:14:52,600 Speaker 5: like Google and Amazon has gone up close to forty 267 00:14:52,680 --> 00:14:56,640 Speaker 5: fifty percent, So those a significant portion of that increase 268 00:14:56,800 --> 00:15:00,160 Speaker 5: should definitely go in Vida's way. So that should now 269 00:15:00,680 --> 00:15:04,120 Speaker 5: raise the estimates even more. Since off of that three 270 00:15:04,200 --> 00:15:06,520 Speaker 5: QI billion pipeline. 271 00:15:06,160 --> 00:15:09,720 Speaker 1: Number, Mandy, do you see in Vidia keeping up with 272 00:15:09,840 --> 00:15:13,200 Speaker 1: the demand that that kind of spending entails. 273 00:15:13,720 --> 00:15:13,920 Speaker 2: Yeah. 274 00:15:13,960 --> 00:15:17,520 Speaker 4: In fact, I was at CEES this year and then 275 00:15:17,960 --> 00:15:22,240 Speaker 4: at Davos as well, and Jensen said demand is really 276 00:15:22,320 --> 00:15:26,920 Speaker 4: strong at least ten times you know, during those big events. 277 00:15:26,920 --> 00:15:31,840 Speaker 4: So clearly he anticipated this and Nvidia has been preparing 278 00:15:32,000 --> 00:15:35,120 Speaker 4: for this kind of step up and demand. The one 279 00:15:35,200 --> 00:15:38,480 Speaker 4: caveat here is what we are hearing from companies about 280 00:15:38,520 --> 00:15:42,360 Speaker 4: memory prices, and every company that has reported so far 281 00:15:42,440 --> 00:15:45,800 Speaker 4: on the hardware side has called out, you know, memory 282 00:15:45,840 --> 00:15:49,880 Speaker 4: pricing being a challenge. I think Nvidia, given their scale, 283 00:15:50,840 --> 00:15:54,200 Speaker 4: has probably managed it far better than some of the 284 00:15:54,400 --> 00:15:58,920 Speaker 4: smaller companies. But there's no doubt that memory is having 285 00:15:58,960 --> 00:16:03,360 Speaker 4: an impact on the supply chain this quarter and most 286 00:16:03,440 --> 00:16:05,520 Speaker 4: likely for the next couple of quarters at least. 287 00:16:05,600 --> 00:16:07,600 Speaker 1: Now give us your view on that, Coon, John, because 288 00:16:07,800 --> 00:16:10,000 Speaker 1: to man Deep's point, that is something that we've been 289 00:16:10,040 --> 00:16:14,360 Speaker 1: hearing a lot from many companies, even outside the hyperscalers, 290 00:16:14,360 --> 00:16:18,560 Speaker 1: that these memory prices are potential crimp to their margins. 291 00:16:19,280 --> 00:16:21,880 Speaker 5: Yeah, I mean that is true, and as an industry 292 00:16:21,920 --> 00:16:24,360 Speaker 5: they just have to deal with it. But given you know, 293 00:16:24,520 --> 00:16:27,240 Speaker 5: in the terms of stack of priority, look and media 294 00:16:27,280 --> 00:16:30,080 Speaker 5: is of course going to get the first priority. We 295 00:16:30,240 --> 00:16:33,560 Speaker 5: have seen, including Nvidia, but we have seen from the 296 00:16:33,640 --> 00:16:38,880 Speaker 5: memory players that they are reprioritizing key markets, which is 297 00:16:38,920 --> 00:16:41,720 Speaker 5: the data center, which is the latest and greatest servers, 298 00:16:41,760 --> 00:16:43,880 Speaker 5: because that's where they get the most profit and the 299 00:16:43,920 --> 00:16:49,520 Speaker 5: most dollar. And Nvidia also has prioritized and has actually 300 00:16:49,560 --> 00:16:53,840 Speaker 5: announced that they're going to not ship enough gaming GPUs 301 00:16:53,840 --> 00:16:56,760 Speaker 5: because they want to prioritize the memory that goes to 302 00:16:56,800 --> 00:16:59,800 Speaker 5: the server GPUs. So we think Nvidia should be okay. 303 00:17:00,200 --> 00:17:05,760 Speaker 5: The smaller, much more not sophisticated players and players outside 304 00:17:05,760 --> 00:17:09,159 Speaker 5: of the data center will see some impact of taking 305 00:17:09,320 --> 00:17:12,000 Speaker 5: allogation away from them or not getting the key allogation, 306 00:17:12,119 --> 00:17:15,280 Speaker 5: but Nvidia and hyperscalers should mostly be okay. 307 00:17:15,720 --> 00:17:19,119 Speaker 1: Now we know that in Video is an industry leader 308 00:17:19,200 --> 00:17:21,360 Speaker 1: in the GPUs, but we hear all this talk as 309 00:17:21,400 --> 00:17:26,679 Speaker 1: well about TPUs. How could that be playing out in 310 00:17:26,720 --> 00:17:28,359 Speaker 1: the earnings when they report. 311 00:17:28,920 --> 00:17:32,600 Speaker 4: Yeah, I think what we saw from Google is one 312 00:17:33,280 --> 00:17:38,280 Speaker 4: they expect, you know again fifty percent of their deployments 313 00:17:38,320 --> 00:17:42,160 Speaker 4: to go towards their cloud business, and the cloud business 314 00:17:42,200 --> 00:17:45,840 Speaker 4: seems to be accelerating. We saw a quarter with forty 315 00:17:45,880 --> 00:17:50,159 Speaker 4: eight percent cloud growth, which is far better than the 316 00:17:50,240 --> 00:17:55,320 Speaker 4: other hyperscalers and with you know, better margins. So I 317 00:17:55,359 --> 00:17:59,160 Speaker 4: think where the TPUs story is really solid for someone 318 00:17:59,280 --> 00:18:03,159 Speaker 4: like Google is the fact that one it's vertical stack 319 00:18:03,240 --> 00:18:07,800 Speaker 4: integration that gives them a much better you know, token 320 00:18:07,880 --> 00:18:11,159 Speaker 4: per what sort of a metric compared to other hyperscalers. 321 00:18:11,200 --> 00:18:16,400 Speaker 4: And also, I think in terms of kapex efficiency, Google 322 00:18:16,520 --> 00:18:20,520 Speaker 4: probably is the best position when it comes to the hyperscaler. 323 00:18:20,600 --> 00:18:24,480 Speaker 4: So it'll be interesting to see, you know, what Microsoft 324 00:18:24,680 --> 00:18:27,800 Speaker 4: and Meta end up doing, given Amazon has also talked 325 00:18:27,800 --> 00:18:31,920 Speaker 4: about ramping up their Traanium chips their own A six. 326 00:18:32,040 --> 00:18:37,040 Speaker 4: So both Amazon and Google are a tailwind for someone 327 00:18:37,160 --> 00:18:40,320 Speaker 4: like Broadcom, which Kunjin can talk more about. But clearly 328 00:18:41,160 --> 00:18:44,480 Speaker 4: I think Microsoft and Meta are probably more reliant on 329 00:18:44,600 --> 00:18:46,840 Speaker 4: Nvidia at this point than the other hyperscalers. 330 00:18:46,960 --> 00:18:49,760 Speaker 1: We're speaking with Mandeep Saying, Global head of Tech research 331 00:18:49,760 --> 00:18:54,480 Speaker 1: at Bloomberg Intelligence, and BI Senior Semiconductor's analyst Kunjohn Sabani. 332 00:18:54,720 --> 00:18:57,720 Speaker 1: Kenjohn Let's pick up off of Mandeep's point about how 333 00:18:57,920 --> 00:19:01,240 Speaker 1: Nvidia is weathering the competition and from some of these 334 00:19:01,320 --> 00:19:04,360 Speaker 1: other chip players, not just the TPUs but the likes 335 00:19:04,359 --> 00:19:06,440 Speaker 1: of Broadcom, AMD, Micron. 336 00:19:08,960 --> 00:19:11,840 Speaker 5: Yeah, I mean Look, there is no doubt and we 337 00:19:12,560 --> 00:19:15,840 Speaker 5: have a forecast in our latest AI chip Deep Type 338 00:19:15,840 --> 00:19:18,360 Speaker 5: that we are published, But there is no doubt that 339 00:19:18,520 --> 00:19:21,359 Speaker 5: a six R, which is the likes of a TPU 340 00:19:21,400 --> 00:19:24,480 Speaker 5: and a trainium are going to grow fast and to 341 00:19:24,600 --> 00:19:29,040 Speaker 5: some degree definitely take share away from in Media. It's 342 00:19:29,240 --> 00:19:33,240 Speaker 5: GPU competitor, which is from AMD, is also getting ready 343 00:19:33,280 --> 00:19:36,800 Speaker 5: to ship its first server level solution in second half 344 00:19:36,800 --> 00:19:40,160 Speaker 5: twenty six. So look, competition is coming from all angles. 345 00:19:40,640 --> 00:19:42,960 Speaker 5: Having said that, though you know, and Media is also 346 00:19:43,760 --> 00:19:47,359 Speaker 5: not sitting on his heels. They have been trying to 347 00:19:47,440 --> 00:19:51,520 Speaker 5: explore different areas and markets. One example is they have 348 00:19:51,600 --> 00:19:54,600 Speaker 5: announced they are going to start selling their best in 349 00:19:54,680 --> 00:19:57,960 Speaker 5: class ARM based CPU as a stand alone chips, so 350 00:19:58,480 --> 00:20:00,679 Speaker 5: entering into a brand new TAM that they didn't have 351 00:20:00,760 --> 00:20:03,840 Speaker 5: access to it in the past. And we think, you know, 352 00:20:03,880 --> 00:20:07,280 Speaker 5: beyond just server GPUs, they will be making forays into 353 00:20:07,320 --> 00:20:10,960 Speaker 5: a lot more other areas of AI, whether it's automotive, 354 00:20:10,960 --> 00:20:14,720 Speaker 5: whether it's physical AI. So right now the demand is 355 00:20:14,760 --> 00:20:18,359 Speaker 5: so high that despite such high competition that I talked about, 356 00:20:18,520 --> 00:20:21,480 Speaker 5: in Media can still continue growing really handsomely, at least 357 00:20:21,480 --> 00:20:22,960 Speaker 5: for the next two to three years. 358 00:20:23,320 --> 00:20:27,520 Speaker 1: Matthew how do you see Video's growth rejectory at this point, 359 00:20:27,880 --> 00:20:31,520 Speaker 1: not just on the chips, but growing into other markets. 360 00:20:31,240 --> 00:20:34,160 Speaker 1: Does Video even need to grow into other markets? When 361 00:20:34,400 --> 00:20:36,720 Speaker 1: the hyperscalers you're talking about the kind of spending that 362 00:20:36,760 --> 00:20:37,320 Speaker 1: they are. 363 00:20:37,800 --> 00:20:40,720 Speaker 4: Well, you have to think, you know, one or two 364 00:20:40,800 --> 00:20:43,760 Speaker 4: years ahead, because the kind of levels we are seeing 365 00:20:43,800 --> 00:20:46,760 Speaker 4: with capex and you know, as I said, we'll see 366 00:20:46,800 --> 00:20:49,680 Speaker 4: another year of sixty percent growth. We already had two 367 00:20:49,720 --> 00:20:54,160 Speaker 4: years of sixty to seventy percent CAPEX growth. These kind 368 00:20:54,200 --> 00:20:57,000 Speaker 4: of growth levels are not sustainable. I mean, there is 369 00:20:57,080 --> 00:21:01,119 Speaker 4: no doubt that growth in CAPEX will taper off. And 370 00:21:01,280 --> 00:21:04,720 Speaker 4: you know we are already talking about trillion dollars plus 371 00:21:04,720 --> 00:21:07,680 Speaker 4: in CAPEX. So from this point on, you know, six 372 00:21:07,800 --> 00:21:10,879 Speaker 4: hundred and fifty billion, you will see a deceleration in 373 00:21:10,960 --> 00:21:14,119 Speaker 4: capex grud. So the question for Nvidia is if there 374 00:21:14,160 --> 00:21:17,679 Speaker 4: is competition coming, do they want to move up the stack, 375 00:21:17,720 --> 00:21:20,760 Speaker 4: which they've already done with the release of a foundational 376 00:21:20,800 --> 00:21:24,119 Speaker 4: model on the autonomous driving side, the Alpmyle model that 377 00:21:24,160 --> 00:21:27,720 Speaker 4: they've released, And that's where you know, they'll have to 378 00:21:27,800 --> 00:21:30,640 Speaker 4: pick their spots in terms of what are the areas 379 00:21:30,720 --> 00:21:34,800 Speaker 4: where they feel like They've got a lot in terms 380 00:21:34,840 --> 00:21:38,760 Speaker 4: of the adjacent capabilities. They've already have a very sizable 381 00:21:38,800 --> 00:21:42,520 Speaker 4: networking business. Then that Kunjin can talk about. But to me, 382 00:21:42,680 --> 00:21:46,920 Speaker 4: the key is what kind of advantage these foundational models 383 00:21:46,960 --> 00:21:50,639 Speaker 4: that are trained on the latest Blackwell architecture can show 384 00:21:50,760 --> 00:21:53,560 Speaker 4: versus the A six and how big that gap is, 385 00:21:53,640 --> 00:21:56,480 Speaker 4: Because at the end of the day, companies that are 386 00:21:56,600 --> 00:22:00,200 Speaker 4: using the Nvidia clusters want to see, you know, whether 387 00:22:00,280 --> 00:22:04,679 Speaker 4: it's performance in terms of tokens for what, or you know, 388 00:22:04,720 --> 00:22:08,680 Speaker 4: the intelligence layer being better versus some of the other 389 00:22:08,720 --> 00:22:11,840 Speaker 4: foundational models that are not trained on Invidia chips and 390 00:22:11,880 --> 00:22:15,080 Speaker 4: that sort of distinction is very important to keep, you know, 391 00:22:15,119 --> 00:22:18,440 Speaker 4: the gross margins that Nvidia has versus the competition. 392 00:22:18,680 --> 00:22:20,439 Speaker 1: I pick up on that, kin John, how do you 393 00:22:20,480 --> 00:22:23,960 Speaker 1: see in Nvidia sort of growing into some of that story. 394 00:22:25,640 --> 00:22:28,639 Speaker 5: Yeah, I mean, look mentioned about networking, just to just 395 00:22:28,680 --> 00:22:31,399 Speaker 5: give a point of reference, This is not an area 396 00:22:31,760 --> 00:22:36,400 Speaker 5: Nvidia was playing up until even just two years back. Today, 397 00:22:36,520 --> 00:22:39,960 Speaker 5: the revenues from networking are going to run close to 398 00:22:40,680 --> 00:22:44,600 Speaker 5: thirty billion figure for the full year. Nvidia was not 399 00:22:44,640 --> 00:22:48,200 Speaker 5: even doing thirty billion as a whole company up back 400 00:22:48,200 --> 00:22:51,640 Speaker 5: in until twenty twenty three, So that's just to set 401 00:22:51,680 --> 00:22:55,120 Speaker 5: an example of that they have been mentioning into new 402 00:22:55,160 --> 00:22:59,240 Speaker 5: areas moving up the stack, whether it is hardware, whether 403 00:22:59,359 --> 00:23:03,480 Speaker 5: going beyond GPUs into networking and CPUs, or whether going 404 00:23:03,520 --> 00:23:08,560 Speaker 5: into software ecosystem, whether it's through NIMS, through models, through 405 00:23:08,600 --> 00:23:11,479 Speaker 5: their Omniverus software stack. So they've shown a lot of 406 00:23:11,480 --> 00:23:15,080 Speaker 5: success in terms of expanding these businesses from nothing to 407 00:23:15,200 --> 00:23:16,359 Speaker 5: billions of dollars today. 408 00:23:16,560 --> 00:23:21,879 Speaker 1: Mandi Kunjohn mentioned earlier that Jensen Wang talked about the 409 00:23:21,960 --> 00:23:25,360 Speaker 1: Rubin chip getting introduced in the second half of this year. 410 00:23:25,400 --> 00:23:28,600 Speaker 1: Do you expect to hear more clarity from Jensen Wang 411 00:23:28,640 --> 00:23:31,040 Speaker 1: when it comes to that next generationship in the earnings 412 00:23:31,200 --> 00:23:31,920 Speaker 1: next week. 413 00:23:31,960 --> 00:23:34,800 Speaker 4: Yeah, earnings as well as they have their GtC event 414 00:23:34,920 --> 00:23:37,919 Speaker 4: coming up in March, so clearly, you know, there was 415 00:23:37,960 --> 00:23:41,719 Speaker 4: a reason why Jensen pulled forward that announcement of the 416 00:23:41,800 --> 00:23:46,240 Speaker 4: new chip to CES just to set expectations that they're 417 00:23:46,320 --> 00:23:51,320 Speaker 4: really aggressive about pushing out the new architecture and introduce 418 00:23:51,400 --> 00:23:54,199 Speaker 4: that in the second half. And I do expect, you know, 419 00:23:54,280 --> 00:23:57,840 Speaker 4: the performance gains to be a big part of how 420 00:23:57,880 --> 00:24:00,800 Speaker 4: they continue to show that they are ahead of competition, 421 00:24:00,960 --> 00:24:04,880 Speaker 4: including a MD and the A six provider. So, as 422 00:24:04,880 --> 00:24:07,719 Speaker 4: I said, in the end, it comes down to you 423 00:24:07,760 --> 00:24:12,280 Speaker 4: know how, and Vidia's chips are helping address the power 424 00:24:12,320 --> 00:24:15,480 Speaker 4: greed times. For everything that we are dealing with right now, 425 00:24:15,920 --> 00:24:19,760 Speaker 4: power has the longest lead time. And if Nvidia can 426 00:24:19,960 --> 00:24:23,720 Speaker 4: address that power constraint and maximize you know, the throughput 427 00:24:24,080 --> 00:24:26,919 Speaker 4: per unit of power, then they will continue to command 428 00:24:26,920 --> 00:24:29,320 Speaker 4: premium pricing, which has been their page all along. 429 00:24:29,640 --> 00:24:33,199 Speaker 1: And Kun John, what's the most important question that Jensen 430 00:24:33,240 --> 00:24:35,720 Speaker 1: Wong needs to answer in the earnings call next week? 431 00:24:36,119 --> 00:24:38,880 Speaker 5: And it will be two questions. One is everyone's going 432 00:24:38,920 --> 00:24:42,800 Speaker 5: to try and figure out the shape or increase of 433 00:24:42,920 --> 00:24:45,960 Speaker 5: that five hundred billion pipeline that he had mentioned, So 434 00:24:46,080 --> 00:24:48,840 Speaker 5: that's going to be most of the analysts. 435 00:24:48,880 --> 00:24:51,399 Speaker 1: Goal really appreciate this. Thanks to both of you for 436 00:24:51,480 --> 00:24:54,200 Speaker 1: being with us. That's Kun John Sabani and man Deep 437 00:24:54,240 --> 00:24:58,600 Speaker 1: Sing of Bloomberg Intelligence. And up next, the World's Richest 438 00:24:58,640 --> 00:25:01,080 Speaker 1: Man goes After open A, we'll get an update on 439 00:25:01,160 --> 00:25:05,160 Speaker 1: Elon Musk's lawsuit against the maker of chat GPT. It's 440 00:25:05,200 --> 00:25:08,400 Speaker 1: thirty seven minutes past the hour. I'm Nathan Hager and 441 00:25:08,440 --> 00:25:21,000 Speaker 1: this is Bloomberg. Thank you so much for joining us. 442 00:25:21,040 --> 00:25:24,320 Speaker 1: On this special edition of Bloomberg Daybreak. US markets are 443 00:25:24,359 --> 00:25:27,639 Speaker 1: closed for the President's Day holiday. I'm Nathan Hager. We 444 00:25:27,720 --> 00:25:30,959 Speaker 1: turned out to a couple high profile legal cases. The 445 00:25:31,000 --> 00:25:35,119 Speaker 1: world's richest man, Elon Musk, is suing open Ai, a 446 00:25:35,200 --> 00:25:38,440 Speaker 1: company he co founded. That trial set to begin in April. 447 00:25:38,800 --> 00:25:43,400 Speaker 1: For more, We're joined by Bloomberg Intelligence litigation analyst Matthew Shettenhelm. Matt, 448 00:25:43,400 --> 00:25:46,240 Speaker 1: thanks for coming on with us. Remind us first off, 449 00:25:46,280 --> 00:25:48,680 Speaker 1: on the background of this case. Why is Elon Musk 450 00:25:48,720 --> 00:25:49,520 Speaker 1: suing open Ai. 451 00:25:49,840 --> 00:25:53,480 Speaker 6: Yeah, this goes back to Open Eyes founding about ten 452 00:25:53,560 --> 00:25:57,560 Speaker 6: years ago, when Elon Musk was one of the principal 453 00:25:57,720 --> 00:26:03,840 Speaker 6: contributors to the funding of its startup. And the allegation 454 00:26:04,240 --> 00:26:07,520 Speaker 6: that Musk is making in this lawsuit is that when 455 00:26:07,760 --> 00:26:12,280 Speaker 6: when open ai was created, it was under the idea 456 00:26:12,480 --> 00:26:15,840 Speaker 6: that it would remain a non profit and that it 457 00:26:15,840 --> 00:26:20,439 Speaker 6: would be focused on contributing to the good of the world, 458 00:26:21,119 --> 00:26:26,560 Speaker 6: not contributing to private profits. And and so the the 459 00:26:26,600 --> 00:26:30,960 Speaker 6: basic claim that Musk is making now some ten years 460 00:26:31,040 --> 00:26:37,800 Speaker 6: later is that basically he was deceived in contributing what 461 00:26:38,200 --> 00:26:42,240 Speaker 6: adds up to about thirty eight million dollars in startup 462 00:26:42,280 --> 00:26:50,679 Speaker 6: contributions that open ai and Microsoft basically misrepresented how the 463 00:26:50,720 --> 00:26:54,080 Speaker 6: company would operate, and so Musk he threw the whole 464 00:26:54,160 --> 00:26:57,280 Speaker 6: kitchen sink at the companies in his complaint. But it's 465 00:26:57,320 --> 00:27:01,119 Speaker 6: been narrowed down now to two or three claims that 466 00:27:01,119 --> 00:27:04,680 Speaker 6: that basically say one that that that the companies were 467 00:27:04,720 --> 00:27:10,359 Speaker 6: fraudulent in in in pursuing now a shift to a 468 00:27:10,400 --> 00:27:16,520 Speaker 6: for profit model, and they the companies were unjustly enriched, 469 00:27:16,640 --> 00:27:19,800 Speaker 6: and that the companies created a charitable trust and now 470 00:27:19,800 --> 00:27:22,960 Speaker 6: they've reached that charitable trust and we're now on track 471 00:27:23,000 --> 00:27:24,879 Speaker 6: for a trial on those issues. 472 00:27:25,400 --> 00:27:28,680 Speaker 1: Well, Elon Musk is asking for a lot more though 473 00:27:28,760 --> 00:27:31,760 Speaker 1: than just his thirty eight million dollars back, right, I mean, 474 00:27:31,800 --> 00:27:35,040 Speaker 1: he's seeking tens of billions from these companies. 475 00:27:35,520 --> 00:27:39,360 Speaker 6: Yeah, that's That's the really interesting piece here is that 476 00:27:40,560 --> 00:27:44,200 Speaker 6: in January Musk made a filing in the case because 477 00:27:44,240 --> 00:27:47,280 Speaker 6: it hasn't been clear exactly what would be the remedy, 478 00:27:47,359 --> 00:27:51,840 Speaker 6: say Musk wins here it does the court just refocus 479 00:27:52,000 --> 00:27:55,400 Speaker 6: the company back to a charitable purpose or is there 480 00:27:55,480 --> 00:28:00,760 Speaker 6: monetary risk as well? To open ai and Microsoft and 481 00:28:01,119 --> 00:28:03,919 Speaker 6: Must pushed hard on that last piece and made a 482 00:28:03,960 --> 00:28:06,720 Speaker 6: filing that said, I'm not just seeking my thirty eight 483 00:28:06,760 --> 00:28:11,000 Speaker 6: million dollars back here. Open ai was unjustly enriched and 484 00:28:11,280 --> 00:28:14,840 Speaker 6: and owes me in the numbers he put in sixty 485 00:28:14,920 --> 00:28:17,960 Speaker 6: five to one hundred and nine billion dollars from open 486 00:28:18,000 --> 00:28:23,200 Speaker 6: Ai from Microsoft thirteen billion to twenty five billion dollars 487 00:28:23,240 --> 00:28:27,560 Speaker 6: that he's seeking as a remedy here. So that's, you know, 488 00:28:27,720 --> 00:28:31,000 Speaker 6: obviously a number that the companies have to take seriously. 489 00:28:31,359 --> 00:28:34,960 Speaker 6: I think it's a different question whether the court would 490 00:28:34,960 --> 00:28:39,840 Speaker 6: would really consider that as as a realistic remedy or 491 00:28:39,880 --> 00:28:42,320 Speaker 6: if that's more of a play here for leverage and 492 00:28:42,640 --> 00:28:47,720 Speaker 6: potentially shaping some sort of settlements to threaten numbers on 493 00:28:47,760 --> 00:28:50,920 Speaker 6: that scale. Must calculates those through an expert based on 494 00:28:50,960 --> 00:28:55,160 Speaker 6: the valuation of open Ai, not on any actual returns 495 00:28:55,320 --> 00:28:58,400 Speaker 6: for the company that that that have been unjustly received it, 496 00:28:58,520 --> 00:29:00,280 Speaker 6: And I think a court's going to have a real 497 00:29:00,360 --> 00:29:05,520 Speaker 6: concern with calculating any sort of damages on valuation as 498 00:29:05,680 --> 00:29:08,480 Speaker 6: Must does, so I bring a lot of skepticism to 499 00:29:08,560 --> 00:29:11,800 Speaker 6: that number. I think potentially the bigger risk for open 500 00:29:11,840 --> 00:29:15,440 Speaker 6: i and Microsoft might be the changes to its model 501 00:29:15,480 --> 00:29:18,400 Speaker 6: going forward if the court insists that it needs to 502 00:29:18,440 --> 00:29:23,200 Speaker 6: be focused on a charitable purpose. That could be, you know, 503 00:29:23,440 --> 00:29:28,640 Speaker 6: substantial changes to the contracts and the model that the 504 00:29:28,640 --> 00:29:32,880 Speaker 6: companies are pursuing now, and Microsoft's made a substantial investment 505 00:29:33,120 --> 00:29:36,480 Speaker 6: in open Ai. Open Ai might be exploring an IPO. 506 00:29:38,080 --> 00:29:41,680 Speaker 6: Potential disruption there, to me is probably the bigger risk 507 00:29:41,760 --> 00:29:44,680 Speaker 6: than these gigantic numbers that Musk is throwing around. 508 00:29:44,920 --> 00:29:47,280 Speaker 1: So how are you thinking this is going to potentially 509 00:29:47,320 --> 00:29:47,800 Speaker 1: play out? 510 00:29:47,840 --> 00:29:48,040 Speaker 2: Here? 511 00:29:48,200 --> 00:29:50,560 Speaker 1: Is a settlement? What you're thinking is going to be 512 00:29:50,600 --> 00:29:52,920 Speaker 1: the most likely outcome? And what would a settlement potentially 513 00:29:52,920 --> 00:29:53,280 Speaker 1: look like? 514 00:29:54,160 --> 00:29:56,840 Speaker 6: Yeah, so you know, so we're headed towards a trial 515 00:29:57,080 --> 00:30:00,000 Speaker 6: in April twenty seventh. A jury trial and ury ty 516 00:30:00,360 --> 00:30:05,640 Speaker 6: are inherently risky, and you you have potentially big numbers here. 517 00:30:06,000 --> 00:30:10,120 Speaker 6: You know, settlements are are are always a real possibility. 518 00:30:10,360 --> 00:30:13,560 Speaker 6: At the same time, I think open Ai and Microsoft 519 00:30:14,000 --> 00:30:16,800 Speaker 6: think they have pretty strong legal arguments that this case 520 00:30:16,920 --> 00:30:19,680 Speaker 6: never should have even reached this point, that it should 521 00:30:19,720 --> 00:30:21,680 Speaker 6: never even be going to a jury. The judge has 522 00:30:22,360 --> 00:30:27,520 Speaker 6: repeatedly refused to stop the case they reject. She rejected 523 00:30:27,520 --> 00:30:31,480 Speaker 6: the motion for dismissal, the motion for summary judgment. I 524 00:30:31,480 --> 00:30:34,200 Speaker 6: think the companies might want to try you know, to 525 00:30:34,240 --> 00:30:36,920 Speaker 6: appeal this and and to challenge those rulings. But the 526 00:30:36,960 --> 00:30:39,440 Speaker 6: problem for them is they can't do it before this 527 00:30:39,480 --> 00:30:42,600 Speaker 6: goes to the jury. So it's a tough call to 528 00:30:42,640 --> 00:30:45,120 Speaker 6: see how this plays out. There's a chance the companies say, look, 529 00:30:45,120 --> 00:30:46,600 Speaker 6: you know, let's roll the dice with the jury and 530 00:30:46,640 --> 00:30:50,360 Speaker 6: we can always appeal it afterwards, especially if the jury 531 00:30:50,400 --> 00:30:53,160 Speaker 6: isn't asked to go to to remedy, it's just to 532 00:30:53,240 --> 00:30:54,880 Speaker 6: go to to liability. 533 00:30:55,120 --> 00:30:56,200 Speaker 2: So we'll see. 534 00:30:56,360 --> 00:31:00,800 Speaker 6: It's really hard to say what a settlement looks like here. 535 00:31:00,880 --> 00:31:06,960 Speaker 6: Given you the unprecedented nature of this suit, it's hard 536 00:31:07,000 --> 00:31:09,800 Speaker 6: to see a concrete framework. I'm skeptical that those big 537 00:31:09,920 --> 00:31:14,520 Speaker 6: dollar amounts come into play in any sort of settlement. 538 00:31:14,800 --> 00:31:18,080 Speaker 6: But you know, you have big personalities here, obviously with 539 00:31:18,160 --> 00:31:20,880 Speaker 6: Elon Musk and Sam Altman, who don't get along very well, 540 00:31:21,200 --> 00:31:24,760 Speaker 6: and so to try to envision in an exact way 541 00:31:24,800 --> 00:31:28,360 Speaker 6: that they would structure a settlement, it's too early to say. 542 00:31:28,800 --> 00:31:30,800 Speaker 1: Thanks for this, Matt, great having you on with us. 543 00:31:30,880 --> 00:31:35,200 Speaker 1: That's Bloomberg Intelligence litigation analyst Matthew Shettenhelm. Another case in 544 00:31:35,240 --> 00:31:38,320 Speaker 1: the National Spotlight is set for next month. The Justice 545 00:31:38,320 --> 00:31:43,040 Speaker 1: Departments antitrust lawsuit against Live Nation and Ticketmaster. For more 546 00:31:43,080 --> 00:31:46,040 Speaker 1: on this, we're joined by Bloomberg Intelligence senior litigation analyst 547 00:31:46,160 --> 00:31:48,720 Speaker 1: Jennifer ree. Jen give us the background on this one. 548 00:31:48,800 --> 00:31:51,840 Speaker 1: Is this just about how much we're paying for tickets 549 00:31:51,960 --> 00:31:53,440 Speaker 1: to go to concerts and things? 550 00:31:54,200 --> 00:31:56,680 Speaker 7: Well, that's part of it. I mean, the allegations are 551 00:31:56,720 --> 00:32:00,280 Speaker 7: that those fees that get tacked onto tickets for consorts 552 00:32:00,320 --> 00:32:03,120 Speaker 7: that we all know so well are a result of 553 00:32:03,480 --> 00:32:07,040 Speaker 7: Live Nation just essentially having too much dominance in control 554 00:32:07,280 --> 00:32:11,320 Speaker 7: sort of across the entire ecosystem for large concerts. You know, 555 00:32:11,520 --> 00:32:15,200 Speaker 7: it's in promotions, it manages artists, it owns venues, and 556 00:32:15,240 --> 00:32:18,200 Speaker 7: it owns ticket Master, which it acquired in twenty ten. 557 00:32:18,760 --> 00:32:21,240 Speaker 7: And what's been alleged here by the Department of Justice 558 00:32:21,280 --> 00:32:23,280 Speaker 7: and a large group of states, by the way, forty 559 00:32:23,320 --> 00:32:26,000 Speaker 7: of them have joined this case, is that the company 560 00:32:26,080 --> 00:32:29,040 Speaker 7: has kind of engaged in this long laundry list of 561 00:32:30,040 --> 00:32:34,920 Speaker 7: exclusionary conduct intended to maintain its monopoly positions in a 562 00:32:34,960 --> 00:32:39,280 Speaker 7: couple different markets. You know, under anti trust laws, it's 563 00:32:39,280 --> 00:32:41,480 Speaker 7: not really good enough just to have a monopoly position. 564 00:32:41,760 --> 00:32:44,680 Speaker 7: But if you're in a monopoly position, meaning like maybe 565 00:32:44,720 --> 00:32:47,760 Speaker 7: seventy percent or more market share in a market, if 566 00:32:47,800 --> 00:32:51,160 Speaker 7: you engage in conduct intended to exclude your competitors and 567 00:32:51,200 --> 00:32:53,760 Speaker 7: to maintain that position in kind of in an unfair way, 568 00:32:54,200 --> 00:32:56,800 Speaker 7: that's where you get across the anti trust lines. And 569 00:32:56,840 --> 00:32:58,960 Speaker 7: so that's what they're accusing Live Nation of here. 570 00:32:59,600 --> 00:33:03,920 Speaker 1: So based on your analysis, what's the thinking about whether 571 00:33:04,160 --> 00:33:08,200 Speaker 1: that type of behavior has been displayed by Live Nation 572 00:33:08,280 --> 00:33:09,000 Speaker 1: and Ticketmaster. 573 00:33:09,960 --> 00:33:12,360 Speaker 7: Well, based on what I've seen so far, the facts 574 00:33:12,360 --> 00:33:14,800 Speaker 7: that are in the complaint and whatever they've allowed us 575 00:33:14,840 --> 00:33:17,040 Speaker 7: to see publicly because quite a lot is redacted, it 576 00:33:17,080 --> 00:33:19,720 Speaker 7: looks like the Department of Justice has some really good 577 00:33:19,760 --> 00:33:23,680 Speaker 7: evidence and I believe has a strong case here. This 578 00:33:23,720 --> 00:33:26,320 Speaker 7: will go before a jury, and so it would be 579 00:33:26,320 --> 00:33:29,120 Speaker 7: a jury that would decide on liability. A judge would 580 00:33:29,120 --> 00:33:31,800 Speaker 7: decide on remedy, but a jury would look at what 581 00:33:31,840 --> 00:33:34,720 Speaker 7: the evidence the Department of Justice puts in front of it. 582 00:33:35,280 --> 00:33:39,000 Speaker 7: But Nathan, there is some possibility that this case would 583 00:33:39,000 --> 00:33:42,960 Speaker 7: not get there because there is a possibility that the 584 00:33:43,000 --> 00:33:45,680 Speaker 7: company could settle with the Department of Justice before they 585 00:33:45,720 --> 00:33:46,600 Speaker 7: get to that trial. 586 00:33:46,840 --> 00:33:48,360 Speaker 1: Okay, what has you think in that. 587 00:33:49,640 --> 00:33:53,520 Speaker 7: Well, this is mostly coming from news reports and from 588 00:33:53,600 --> 00:33:56,440 Speaker 7: a pattern that we're beginning to see at the Department 589 00:33:56,520 --> 00:33:59,000 Speaker 7: of Justice. You know, it has a division called the 590 00:33:59,000 --> 00:34:02,040 Speaker 7: Antitrust Division, and that is staffed with those people who 591 00:34:02,080 --> 00:34:05,960 Speaker 7: are anti trust experts. They are anti trust lawyers, economists, 592 00:34:06,120 --> 00:34:08,520 Speaker 7: They understand that area and the law, but they are 593 00:34:08,680 --> 00:34:13,800 Speaker 7: overseen by the Attorney General's Office, who aren't necessarily attorneys 594 00:34:13,800 --> 00:34:17,680 Speaker 7: with anti trust experience, but can override the decisions of 595 00:34:17,719 --> 00:34:21,439 Speaker 7: the division. And we have what has been alleged, because 596 00:34:21,480 --> 00:34:24,160 Speaker 7: I have no firsthand knowledge, but what has been reported 597 00:34:24,800 --> 00:34:29,560 Speaker 7: is that some very well connected Republican lobbyists, or I 598 00:34:29,560 --> 00:34:31,920 Speaker 7: should say sort of in the MAGA side of the 599 00:34:31,960 --> 00:34:36,359 Speaker 7: Republican Party lobbyists have successfully been able to go over 600 00:34:36,400 --> 00:34:39,200 Speaker 7: the heads of the Anti trust Division lawyers and procure 601 00:34:39,200 --> 00:34:43,120 Speaker 7: settlements for their clients against the will of the anti 602 00:34:43,120 --> 00:34:46,320 Speaker 7: trust experts at the DOJ. And there is a suggestion 603 00:34:46,440 --> 00:34:49,000 Speaker 7: that Live Nation is trying to that strategy here too, 604 00:34:49,040 --> 00:34:51,600 Speaker 7: that they've hired quite a few people that are very 605 00:34:51,600 --> 00:34:55,080 Speaker 7: influential with the Trump administration. For instance, Kelly an Conway 606 00:34:55,760 --> 00:35:00,680 Speaker 7: is one. They put Richard Grinnell, who is a Trump confidant, 607 00:35:01,280 --> 00:35:05,160 Speaker 7: on the board of and who is running the Kennedy Center, 608 00:35:05,320 --> 00:35:08,440 Speaker 7: they put him on their board, and apparently, according to 609 00:35:08,480 --> 00:35:11,319 Speaker 7: news reports, they have lobbyists roaming the halls of the 610 00:35:11,320 --> 00:35:14,640 Speaker 7: Department of Justice on a pretty consistent basis. So they're 611 00:35:14,640 --> 00:35:19,080 Speaker 7: working hard, I think, to get to a settlement. And 612 00:35:19,280 --> 00:35:23,480 Speaker 7: we have seen this tactic has success in the past, 613 00:35:23,840 --> 00:35:27,320 Speaker 7: namely with respect to Hewlett Packard in its attempt to 614 00:35:27,320 --> 00:35:30,399 Speaker 7: acquire Juniper that was first challenged by the DOJ Anti 615 00:35:30,440 --> 00:35:33,040 Speaker 7: Trust lawyers, and also with respect to a deal between 616 00:35:33,080 --> 00:35:36,959 Speaker 7: Compass and Anywhere Real Estate where the DOJ Anti Trust 617 00:35:37,000 --> 00:35:40,840 Speaker 7: Division was discouraged from opening an in depth investigation and 618 00:35:41,000 --> 00:35:43,279 Speaker 7: the deal was allowed to clear without much of a 619 00:35:43,320 --> 00:35:44,160 Speaker 7: deep look into it. 620 00:35:44,320 --> 00:35:46,160 Speaker 1: Well, do you have a sense of what kind of 621 00:35:46,360 --> 00:35:48,600 Speaker 1: settlement would satisfy the Justice Department? 622 00:35:50,239 --> 00:35:52,800 Speaker 7: So I think you know. Live Nation has been operating 623 00:35:52,880 --> 00:35:55,960 Speaker 7: under a DOJ consent order for years, since twenty ten. 624 00:35:56,040 --> 00:35:59,000 Speaker 7: That basically means an agreement, you know, a legal agreement 625 00:35:59,040 --> 00:36:01,479 Speaker 7: that they'll behave and their business in a certain way. 626 00:36:01,760 --> 00:36:04,120 Speaker 7: They had to enter that order in order to acquire 627 00:36:04,160 --> 00:36:06,960 Speaker 7: ticket Master. That was the agreement, and there have been 628 00:36:07,120 --> 00:36:11,279 Speaker 7: investigations since, analegations and a finding by the DOJ that 629 00:36:11,800 --> 00:36:14,480 Speaker 7: Live Nation did not comply with the terms of that 630 00:36:14,520 --> 00:36:17,880 Speaker 7: consent order, and it had a lot of elements to it, 631 00:36:17,960 --> 00:36:21,440 Speaker 7: but in particular, it wasn't supposed to strong arm venues 632 00:36:21,480 --> 00:36:24,319 Speaker 7: into using Ticketmaster as its ticketing agent, and it was 633 00:36:24,400 --> 00:36:27,200 Speaker 7: in fact doing that, So that consent order was kind 634 00:36:27,200 --> 00:36:31,719 Speaker 7: of bolstered and extended in twenty nineteen during Trump's first administration, 635 00:36:31,840 --> 00:36:34,880 Speaker 7: it just expired. So one of the things obviously that 636 00:36:34,880 --> 00:36:36,680 Speaker 7: the DJ could do is just go back to that 637 00:36:36,719 --> 00:36:41,239 Speaker 7: consent order bolster its terms further, since apparently Live Nation 638 00:36:41,320 --> 00:36:44,120 Speaker 7: hasn't really complied with those terms to begin with, and 639 00:36:44,239 --> 00:36:47,560 Speaker 7: extend that, let's say for another ten years. These would 640 00:36:47,560 --> 00:36:51,000 Speaker 7: be things like you cannot enter long term exclusive agreements 641 00:36:51,000 --> 00:36:54,839 Speaker 7: with venues you don't own. For Ticketmaster to be the 642 00:36:54,880 --> 00:36:57,480 Speaker 7: exclusive agent, you know, you have to allow other ticketing 643 00:36:57,480 --> 00:37:00,360 Speaker 7: agents to come in there and vuy for that for 644 00:37:00,440 --> 00:37:04,479 Speaker 7: that position for certain concerts. That obviously stop strong arming 645 00:37:04,560 --> 00:37:08,440 Speaker 7: venues and artists. And one of the allegations here is 646 00:37:08,440 --> 00:37:11,839 Speaker 7: that artists cannot play in the amphitheaters owned by Live 647 00:37:11,920 --> 00:37:15,600 Speaker 7: Nation unless they agreed to have Live Nation promote their tour. 648 00:37:16,000 --> 00:37:19,080 Speaker 7: So there would be something like, you know, you cannot 649 00:37:19,440 --> 00:37:21,520 Speaker 7: engage in that kind of conduct. You have to let 650 00:37:21,640 --> 00:37:24,239 Speaker 7: artists use your amphitheaters, but be free to pick their 651 00:37:24,239 --> 00:37:29,120 Speaker 7: own promoter. I think terms like that could possibly be 652 00:37:29,200 --> 00:37:32,040 Speaker 7: in a consent order that would allow for a settlement here. 653 00:37:32,239 --> 00:37:34,319 Speaker 1: All right, well we'll see how things go. Understand, this 654 00:37:34,360 --> 00:37:37,600 Speaker 1: is going to be hitting the courts rather quickly. That's 655 00:37:37,920 --> 00:37:42,360 Speaker 1: Jen Bartash is a senior litigation analyst for Bloomberg Intelligence. 656 00:37:42,680 --> 00:37:46,160 Speaker 1: Thanks as well to Bloomberg Intelligence as Matthew schttenhelm Man, 657 00:37:46,200 --> 00:37:49,960 Speaker 1: Deep Singh, Kun, John Sabani, Jen Bartashes, and Hunum Goyle. 658 00:37:50,560 --> 00:37:52,160 Speaker 1: Thanks to you as well for being with us on 659 00:37:52,280 --> 00:37:55,640 Speaker 1: this President Day holiday. I'm Nathan Hager. Stay with us. 660 00:37:55,680 --> 00:37:58,399 Speaker 1: Top stories and global business at lines are coming up 661 00:37:58,920 --> 00:37:59,719 Speaker 1: right now.