1 00:00:02,520 --> 00:00:14,960 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. Thank you so much 2 00:00:15,000 --> 00:00:18,120 Speaker 1: for joining us for this special edition of Bloomberg Daybreak. 3 00:00:18,200 --> 00:00:21,400 Speaker 1: I'm Nathan Hager. US markets are closed for the fourth 4 00:00:21,400 --> 00:00:24,079 Speaker 1: of July holiday, coming up this hour. Well, what a 5 00:00:24,160 --> 00:00:27,640 Speaker 1: difference three months makes. Back in April, tech stocks were 6 00:00:27,760 --> 00:00:30,960 Speaker 1: hardest hit in the stock market selloff. Now after tumbling 7 00:00:30,960 --> 00:00:33,800 Speaker 1: in some cases more than thirty percent from record highs, 8 00:00:34,000 --> 00:00:37,440 Speaker 1: names you know like Nvidia, Microsoft, and Meta Platforms have 9 00:00:37,520 --> 00:00:39,720 Speaker 1: helped power the Nasdaq and the S and P five 10 00:00:39,800 --> 00:00:43,240 Speaker 1: hundred back into record territory. So what will the rest 11 00:00:43,240 --> 00:00:45,720 Speaker 1: of the year bring. We hope to answer that question 12 00:00:45,760 --> 00:00:48,840 Speaker 1: in this special one hour roundtable with two of Wall 13 00:00:48,880 --> 00:00:53,239 Speaker 1: Street's most influential tech analysts, Gene Munster, managing partner at 14 00:00:53,280 --> 00:00:56,880 Speaker 1: Deepwater Asset Management and Dan Ives, Global head of Tech 15 00:00:56,960 --> 00:01:00,600 Speaker 1: research at Webbush Securities. Kind of becoming a tradition to 16 00:01:00,640 --> 00:01:02,960 Speaker 1: have the three of us together. Thanks so much for 17 00:01:03,000 --> 00:01:05,040 Speaker 1: being here, and I want to start with a look 18 00:01:05,080 --> 00:01:07,319 Speaker 1: back at the last time we got together at the 19 00:01:07,360 --> 00:01:10,840 Speaker 1: start of this year. Dan, you've talked about the time 20 00:01:11,040 --> 00:01:13,319 Speaker 1: it's at in the AI party, so I want to 21 00:01:13,319 --> 00:01:15,800 Speaker 1: remind you what you told us not too long ago. 22 00:01:15,959 --> 00:01:16,760 Speaker 1: On New Year's Day. 23 00:01:16,880 --> 00:01:19,640 Speaker 2: First of there's after parties at five and six am, 24 00:01:20,000 --> 00:01:23,560 Speaker 2: and then even in news you'll have some that fall 25 00:01:23,640 --> 00:01:25,800 Speaker 2: by the waisa. But if you focus on the winners 26 00:01:25,880 --> 00:01:29,080 Speaker 2: and keep the thesis again, we're going to be talking 27 00:01:29,160 --> 00:01:33,840 Speaker 2: about four trillion, five trillion dollar mark aps NASDAK twenty 28 00:01:34,280 --> 00:01:39,039 Speaker 2: twenty two, twenty five k over the next three four 29 00:01:39,440 --> 00:01:40,880 Speaker 2: five years in my opinion. 30 00:01:41,280 --> 00:01:44,360 Speaker 1: So now here we are with talk of Nvidia maybe 31 00:01:44,400 --> 00:01:48,000 Speaker 1: Microsoft becoming the first four trillion dollar company. The Nasdaq's 32 00:01:48,000 --> 00:01:51,480 Speaker 1: already at twenty thousand. So what time is it now, Dan? 33 00:01:52,200 --> 00:01:54,880 Speaker 2: Yeah, Look, I mean it was nine pm in the party. 34 00:01:55,040 --> 00:01:58,080 Speaker 2: Now it's ten pm. But that party goes to four am. 35 00:01:58,160 --> 00:02:03,320 Speaker 2: As we've said, because this SAI revolution, it's just starting 36 00:02:03,360 --> 00:02:05,080 Speaker 2: to hit its next stage. Go ahead in terms of 37 00:02:05,120 --> 00:02:08,519 Speaker 2: the use cases on enterprise, in terms on the consumer. 38 00:02:08,600 --> 00:02:11,639 Speaker 2: You think about physical AI, which obviously Jen's talked a 39 00:02:11,639 --> 00:02:14,839 Speaker 2: ton about, we'll and we'll hit on And that's my view. 40 00:02:14,880 --> 00:02:18,919 Speaker 2: This is a fourth industrial revolution, This tack bull market. 41 00:02:19,360 --> 00:02:22,160 Speaker 2: It's another three years ahead. And that's why I think 42 00:02:22,200 --> 00:02:25,400 Speaker 2: it's get out the popcorn, get the champagne. I's handing 43 00:02:25,480 --> 00:02:26,399 Speaker 2: slowing it down. 44 00:02:26,639 --> 00:02:30,480 Speaker 1: So a slow moving clock at the start of the 45 00:02:30,480 --> 00:02:34,360 Speaker 1: AI party. Potentially, Gene, let's remind everyone what you had 46 00:02:34,440 --> 00:02:35,919 Speaker 1: to say about this at the start of the year 47 00:02:35,919 --> 00:02:36,239 Speaker 1: as well. 48 00:02:36,280 --> 00:02:38,080 Speaker 3: I like dance party analogy is much more of my 49 00:02:38,120 --> 00:02:42,120 Speaker 3: baseball analogies. But I'm at the third inning of this, 50 00:02:42,240 --> 00:02:44,080 Speaker 3: and we think we're in the early stages of a 51 00:02:44,080 --> 00:02:47,120 Speaker 3: three to five year bull market, and I don't I wouldn't. 52 00:02:47,120 --> 00:02:49,520 Speaker 3: Don't worry about the after don't worry about the hangover 53 00:02:49,600 --> 00:02:53,160 Speaker 3: at this point, I think you just embrace that this 54 00:02:53,320 --> 00:02:57,200 Speaker 3: is as the substance will exceed the hype and we've 55 00:02:57,240 --> 00:02:59,239 Speaker 3: got some great years ahead of us from the market. 56 00:03:00,000 --> 00:03:03,720 Speaker 1: This is the question, is the substance succeeding the hype now, Jane, 57 00:03:04,360 --> 00:03:05,119 Speaker 1: I don't even. 58 00:03:04,880 --> 00:03:06,120 Speaker 4: Think we're close to it. 59 00:03:06,160 --> 00:03:09,560 Speaker 3: And I go back a couple months ago, we hosted 60 00:03:09,600 --> 00:03:12,200 Speaker 3: an AI summits and we had all the leaders from 61 00:03:12,680 --> 00:03:15,880 Speaker 3: the big private AI companies there. I mean, these companies 62 00:03:15,919 --> 00:03:20,200 Speaker 3: are just geared towards evangelizing what's going on AI. And 63 00:03:20,240 --> 00:03:24,240 Speaker 3: what surprised me most was they talked about the most 64 00:03:24,280 --> 00:03:29,040 Speaker 3: compelling use cases of AI being coding and customer service. 65 00:03:29,120 --> 00:03:31,440 Speaker 3: These are the same things that we talked about a 66 00:03:31,520 --> 00:03:34,400 Speaker 3: year ago and the reason why that's so bullish. If 67 00:03:34,440 --> 00:03:36,800 Speaker 3: I was going to refine what I said back in January, 68 00:03:36,840 --> 00:03:40,200 Speaker 3: I'd actually say we're in the second inning, and this 69 00:03:40,360 --> 00:03:46,640 Speaker 3: commentary around from these leading AI companies that the use 70 00:03:46,680 --> 00:03:49,640 Speaker 3: cases really haven't taken off. I think to me speaks 71 00:03:49,680 --> 00:03:52,600 Speaker 3: to just how early we are. And then you layer 72 00:03:52,720 --> 00:03:54,560 Speaker 3: on top of that things that are going on with 73 00:03:54,760 --> 00:03:57,400 Speaker 3: Zuck going out and putting these huge bounties. I mean, 74 00:03:57,680 --> 00:04:00,880 Speaker 3: if you believe that he's competent and look at the 75 00:04:00,880 --> 00:04:03,560 Speaker 3: money that's getting put behind this, I think we're still 76 00:04:03,640 --> 00:04:05,840 Speaker 3: very early. So to answer your question, you know, is 77 00:04:05,880 --> 00:04:10,000 Speaker 3: the substance there. It's just starting. But totally agree with 78 00:04:10,600 --> 00:04:14,680 Speaker 3: where where Dan's at and how the trajectory this plays 79 00:04:14,720 --> 00:04:15,840 Speaker 3: out over the next few years. 80 00:04:15,880 --> 00:04:19,479 Speaker 1: Well, let's talk a little bit about where the use 81 00:04:19,560 --> 00:04:22,920 Speaker 1: case is going right now. Over the last several months, 82 00:04:22,920 --> 00:04:25,880 Speaker 1: maybe the last couple of years, we've talked about all 83 00:04:25,960 --> 00:04:29,560 Speaker 1: the spending that's been going on, particularly by the hyperscalers 84 00:04:29,560 --> 00:04:32,120 Speaker 1: in this space. Dan, how do you see the use 85 00:04:32,200 --> 00:04:33,600 Speaker 1: cases developing right now? 86 00:04:34,600 --> 00:04:36,760 Speaker 2: Yeah, and Gene hit on some of them, But I 87 00:04:36,760 --> 00:04:38,640 Speaker 2: think the most important thing too is, like for every 88 00:04:38,720 --> 00:04:42,280 Speaker 2: dollar spent on in video chip, we estimate there's an 89 00:04:42,320 --> 00:04:47,720 Speaker 2: eight to ten dollars multiplier across software, infrastructure energy. That 90 00:04:47,880 --> 00:04:50,120 Speaker 2: speaks the ripple effect. When you think about the use 91 00:04:50,200 --> 00:04:53,440 Speaker 2: cases obviously front and center of the MESSI of AI 92 00:04:53,600 --> 00:04:56,680 Speaker 2: pound tier. I mean we have upwards of eighty four 93 00:04:56,800 --> 00:05:00,160 Speaker 2: use cases today. You go back a year ago mid 94 00:05:00,279 --> 00:05:06,240 Speaker 2: less than five across retail, advertising, marketing, government. And what's 95 00:05:06,240 --> 00:05:09,880 Speaker 2: starting to happen is companies seventy percent of the data 96 00:05:09,920 --> 00:05:14,000 Speaker 2: they've never accessed before. That's why now for any of 97 00:05:14,080 --> 00:05:20,039 Speaker 2: these install based Oracle, Microsoft Salesforce Service now it's a 98 00:05:20,080 --> 00:05:23,919 Speaker 2: bonanza because of the cross SEU opportunities. You know, Gene 99 00:05:24,279 --> 00:05:27,039 Speaker 2: sees so much of the innovative company is also on 100 00:05:27,080 --> 00:05:30,360 Speaker 2: the private side. And I think what you're also seeing 101 00:05:30,400 --> 00:05:35,400 Speaker 2: now is like the innovation that's happening. To me, it's 102 00:05:35,440 --> 00:05:38,240 Speaker 2: the biggest thing that I've ever seen, and when I'm 103 00:05:38,279 --> 00:05:43,359 Speaker 2: surprised every time in a factory floor, whether it's humanoids, robotics, autonomous, 104 00:05:43,560 --> 00:05:47,000 Speaker 2: whether it's in the US, whether it's in Asia, it's 105 00:05:47,160 --> 00:05:50,840 Speaker 2: just starting. It's a golden age for tech ahead. And 106 00:05:50,839 --> 00:05:54,400 Speaker 2: that's why Wes say the Bears and their hibernation caves. 107 00:05:54,880 --> 00:05:57,960 Speaker 2: They can see AI in the spreadsheets. 108 00:05:57,880 --> 00:06:02,360 Speaker 1: Gene In terms of how these large language models are 109 00:06:02,480 --> 00:06:06,040 Speaker 1: developing and the use cases that are being put out there, 110 00:06:06,520 --> 00:06:10,120 Speaker 1: how do you see some of these companies like open AI, 111 00:06:10,480 --> 00:06:13,839 Speaker 1: like Anthropic competing against each other? Is there going to 112 00:06:13,880 --> 00:06:16,640 Speaker 1: be one winner? Are there going to be multiple winners? 113 00:06:17,440 --> 00:06:19,640 Speaker 3: I mean from our perspective, I mean, again, keep the 114 00:06:20,000 --> 00:06:22,839 Speaker 3: groundwork to framework that Dan's laid out, like this is 115 00:06:22,880 --> 00:06:26,680 Speaker 3: going to be bigger than what people can imagine. And 116 00:06:26,720 --> 00:06:29,000 Speaker 3: in that case, you know what is this at the 117 00:06:29,000 --> 00:06:31,240 Speaker 3: core of it? It is that intelligence piece and answer 118 00:06:31,320 --> 00:06:33,440 Speaker 3: question Nathan. I think there's going to be five kind 119 00:06:33,480 --> 00:06:37,600 Speaker 3: of core models that essentially the Western world is going 120 00:06:37,640 --> 00:06:40,479 Speaker 3: to be a run off of. And those are those 121 00:06:40,520 --> 00:06:44,320 Speaker 3: companies that we just that we know so well. There 122 00:06:44,400 --> 00:06:46,960 Speaker 3: is a debate about is this kind of a race 123 00:06:47,000 --> 00:06:49,960 Speaker 3: to the bottom. Eventually, once we hit general intelligence, does 124 00:06:50,040 --> 00:06:53,440 Speaker 3: this AI the powers of the INSIGHT's going to become 125 00:06:53,480 --> 00:06:56,960 Speaker 3: a commodity? And I feel very strongly that that's not 126 00:06:57,040 --> 00:06:59,040 Speaker 3: going to be the case. I think that as more 127 00:06:59,040 --> 00:07:02,600 Speaker 3: and more of our world, basically the world becomes dependent 128 00:07:02,640 --> 00:07:04,719 Speaker 3: on these, I think that there is pricing leverage and 129 00:07:04,800 --> 00:07:08,080 Speaker 3: so to answer your question, I think there is going to. 130 00:07:07,880 --> 00:07:10,280 Speaker 4: Kind of be five key companies. 131 00:07:10,320 --> 00:07:13,160 Speaker 3: There's going to be thousands and thousands, tens of hundreds 132 00:07:13,160 --> 00:07:16,120 Speaker 3: of thousands of models, many of those large language miles 133 00:07:16,160 --> 00:07:17,840 Speaker 3: that are out there, but really five that are going 134 00:07:17,880 --> 00:07:19,760 Speaker 3: to determine this. And you look at a company like 135 00:07:19,840 --> 00:07:23,480 Speaker 3: open Ai, you get a company like Xai. I mean, 136 00:07:23,600 --> 00:07:26,360 Speaker 3: these companies are going to be trillion dollar plus companies 137 00:07:26,400 --> 00:07:26,920 Speaker 3: down the road. 138 00:07:27,080 --> 00:07:29,680 Speaker 1: We're speaking with Gene Munster, managing partner in deep Water 139 00:07:29,800 --> 00:07:32,560 Speaker 1: Asset Management and Dan Ives, global head of Tech research 140 00:07:32,960 --> 00:07:36,920 Speaker 1: at web Bush Securities. Obviously, guys, it hasn't been a 141 00:07:36,960 --> 00:07:40,280 Speaker 1: straight line. We mentioned the selloff at the start of 142 00:07:40,320 --> 00:07:43,400 Speaker 1: the second quarter with some of the tariff rhetoric that 143 00:07:43,480 --> 00:07:46,560 Speaker 1: came around there. Dan, were you concerned at all that 144 00:07:46,880 --> 00:07:50,120 Speaker 1: when we heard some of these high teriff rates announced 145 00:07:50,120 --> 00:07:52,640 Speaker 1: that the party was almost over free. 146 00:07:52,400 --> 00:07:56,520 Speaker 2: I I thought Trump closed the party, the velvet ropes 147 00:07:56,520 --> 00:08:00,520 Speaker 2: were gone. That was a dark few weeks. Look in 148 00:08:00,560 --> 00:08:03,600 Speaker 2: twenty five years doing this, that was the darkest two 149 00:08:03,640 --> 00:08:06,240 Speaker 2: weeks I've seen, even going back to the Financial crisis 150 00:08:06,320 --> 00:08:10,280 Speaker 2: and every other event, Because that, to me was the risk, 151 00:08:10,400 --> 00:08:12,760 Speaker 2: especially when it comes to China and tariffs and the 152 00:08:12,800 --> 00:08:17,160 Speaker 2: supply chain that was gonna cut tech off at the knees. Thankfully, 153 00:08:18,120 --> 00:08:21,480 Speaker 2: we've seen the administration step further and further back from 154 00:08:21,520 --> 00:08:24,480 Speaker 2: the cliff. Cool heads prevailed, the adult in the room, 155 00:08:24,480 --> 00:08:28,080 Speaker 2: investments taken over, and I think that it's a very 156 00:08:28,120 --> 00:08:31,840 Speaker 2: important stage and that the markets kind of gleaned will 157 00:08:31,920 --> 00:08:37,240 Speaker 2: have much more of a digestible tarerf ray and reciprocal tarifray, 158 00:08:37,320 --> 00:08:40,360 Speaker 2: but nothing that was essentially at the time going to 159 00:08:40,440 --> 00:08:45,040 Speaker 2: be an economic army. Gedton and glad and so happy 160 00:08:45,040 --> 00:08:47,000 Speaker 2: that you know those days are a memory. 161 00:08:47,720 --> 00:08:50,839 Speaker 1: Is it just a memory gene or could we see 162 00:08:51,320 --> 00:08:54,160 Speaker 1: more hiccups down the road depending on how policy turns 163 00:08:54,160 --> 00:08:55,000 Speaker 1: out in Washington. 164 00:08:55,600 --> 00:08:58,600 Speaker 3: Unpredictability is kind of part of the strategy today and 165 00:08:58,640 --> 00:09:01,360 Speaker 3: so we have to kind of go with that. I've 166 00:09:02,040 --> 00:09:05,760 Speaker 3: over the past couple of months have had several conversations 167 00:09:05,920 --> 00:09:11,280 Speaker 3: with former US Trade Group and they currently work with 168 00:09:11,440 --> 00:09:14,320 Speaker 3: the Trump administration and help advise on that. And what's 169 00:09:14,360 --> 00:09:17,320 Speaker 3: been very clear about this whole kind of back and 170 00:09:17,360 --> 00:09:20,040 Speaker 3: forth on what's going on and the White House in particular, 171 00:09:20,320 --> 00:09:25,000 Speaker 3: is the center of gravity is the economy. And we 172 00:09:25,040 --> 00:09:27,960 Speaker 3: can look at all the different pieces around AI trade. 173 00:09:27,960 --> 00:09:30,040 Speaker 3: We can look at what's going on in Tarras, but 174 00:09:30,360 --> 00:09:32,040 Speaker 3: at the end of the day, the White House wants 175 00:09:32,080 --> 00:09:34,079 Speaker 3: to maintain the economy. And so Nathan, when I think 176 00:09:34,080 --> 00:09:38,960 Speaker 3: about this crazy pendulum that goes on, I expected to 177 00:09:39,000 --> 00:09:40,200 Speaker 3: continue at some level. 178 00:09:40,520 --> 00:09:42,040 Speaker 4: But as Dan just so. 179 00:09:42,040 --> 00:09:47,839 Speaker 3: Accurately said, this, cool heads will prevail because ultimately the 180 00:09:47,880 --> 00:09:50,640 Speaker 3: economy is what matters most when it comes to politics, 181 00:09:51,240 --> 00:09:53,319 Speaker 3: because that is how you get reelected. 182 00:09:53,040 --> 00:09:56,280 Speaker 4: And I think that I'm not going to be swayed 183 00:09:56,280 --> 00:09:56,480 Speaker 4: by that. 184 00:09:56,520 --> 00:09:59,240 Speaker 3: And just one other piece related to kind of some 185 00:09:59,280 --> 00:10:02,480 Speaker 3: of these unpredicted what's happened in terms of policy is 186 00:10:03,120 --> 00:10:07,560 Speaker 3: the general view historically is that if the market pulls back, 187 00:10:07,880 --> 00:10:10,960 Speaker 3: it's really difficult for one sector to continue to do well. Like, 188 00:10:11,000 --> 00:10:14,280 Speaker 3: for example, you know, if there's NASAK goes down, it's 189 00:10:14,320 --> 00:10:17,240 Speaker 3: really hard for the AI companies to continue. 190 00:10:16,840 --> 00:10:19,280 Speaker 4: To power forward. And whatever might cause that. 191 00:10:19,840 --> 00:10:22,040 Speaker 3: Slow down in the Nasdaq, whether it's high interest rates 192 00:10:22,679 --> 00:10:26,000 Speaker 3: or whatever it might be. But I actually am so 193 00:10:26,200 --> 00:10:29,360 Speaker 3: bullish on AI. I think that it has the power 194 00:10:30,640 --> 00:10:33,679 Speaker 3: for these companies to continue to move higher over the 195 00:10:33,760 --> 00:10:36,800 Speaker 3: next three to five years, despite what is going to 196 00:10:36,840 --> 00:10:39,599 Speaker 3: happen what could happen with the overall macro and I 197 00:10:39,679 --> 00:10:42,320 Speaker 3: don't like being out on a limb that fart and 198 00:10:42,920 --> 00:10:46,600 Speaker 3: the right approach is that AI is just much more impactful. 199 00:10:46,760 --> 00:10:48,959 Speaker 3: Like Dan said, if it got cut off at the 200 00:10:49,040 --> 00:10:52,040 Speaker 3: knees with trade, that's something that is that would have 201 00:10:52,080 --> 00:10:55,960 Speaker 3: an impact. But assuming the trade piece stays intact, I 202 00:10:55,960 --> 00:10:57,959 Speaker 3: think it's going to be really hard for policy to 203 00:10:58,559 --> 00:10:59,520 Speaker 3: slow this AI train. 204 00:11:00,120 --> 00:11:01,800 Speaker 1: Just to pick up on that point. So much of 205 00:11:01,840 --> 00:11:06,080 Speaker 1: the policy decisions are driven by just the fact that 206 00:11:06,120 --> 00:11:09,080 Speaker 1: this could be seen as an AI race between the 207 00:11:09,240 --> 00:11:11,760 Speaker 1: US and China. I mean, how do you see that 208 00:11:11,840 --> 00:11:15,040 Speaker 1: playing out? Dan, who takes the lead in AI? Is 209 00:11:15,080 --> 00:11:16,920 Speaker 1: it gonna be the US? Is it going to be China? 210 00:11:17,040 --> 00:11:18,880 Speaker 1: How big a deal is that? The deep seek news 211 00:11:18,920 --> 00:11:20,280 Speaker 1: that we saw just a few months back. 212 00:11:21,000 --> 00:11:24,199 Speaker 2: I think the Deep Seek that was a scary moment, 213 00:11:24,320 --> 00:11:27,120 Speaker 2: But the reality is is more came out about that 214 00:11:27,240 --> 00:11:29,320 Speaker 2: in terms of add a few comments to what they 215 00:11:29,320 --> 00:11:32,000 Speaker 2: were spending and next Gen and video are hard where 216 00:11:32,000 --> 00:11:34,720 Speaker 2: they were using. Everyone recognized there's only one chip in 217 00:11:34,720 --> 00:11:37,240 Speaker 2: the world feeling this, and it's it's the godfather of 218 00:11:37,240 --> 00:11:40,400 Speaker 2: a Jensen and video. You'll have other moments like that, 219 00:11:40,520 --> 00:11:43,120 Speaker 2: and China is not just going to sit there on 220 00:11:43,160 --> 00:11:45,600 Speaker 2: a treadmill. They're going to continue narrow the gap. But 221 00:11:45,640 --> 00:11:48,600 Speaker 2: I actually think that's positive because it's a shot across 222 00:11:48,640 --> 00:11:52,440 Speaker 2: about at US big tech, and I think you're seeing 223 00:11:52,480 --> 00:11:56,600 Speaker 2: an acceleration since Deep Seek. But that's an important movement, 224 00:11:56,640 --> 00:11:59,880 Speaker 2: and I think what Gene said is such a great 225 00:11:59,880 --> 00:12:02,080 Speaker 2: one to sum it up in terms of what's happening. 226 00:12:03,400 --> 00:12:06,800 Speaker 2: This is just an unrivaled period and you can go 227 00:12:07,280 --> 00:12:10,720 Speaker 2: if you become myopically focused in some of the headlines, 228 00:12:11,400 --> 00:12:14,720 Speaker 2: you miss what's really a fourth in dust revolution that 229 00:12:14,720 --> 00:12:15,400 Speaker 2: we're living in. 230 00:12:15,760 --> 00:12:18,400 Speaker 3: You know, if all of us investors can channel that 231 00:12:18,520 --> 00:12:21,839 Speaker 3: superpower of just looking at the endgame here, which is 232 00:12:21,880 --> 00:12:25,840 Speaker 3: effectively most parts of the world are going to be 233 00:12:25,960 --> 00:12:27,920 Speaker 3: have a profound impact from AI. If you can stay 234 00:12:27,960 --> 00:12:30,880 Speaker 3: focused on that, I think you can create some wealth 235 00:12:30,880 --> 00:12:32,120 Speaker 3: over the next three to five years. 236 00:12:32,160 --> 00:12:34,040 Speaker 1: And we're going to keep this focus going. Is This 237 00:12:34,240 --> 00:12:37,760 Speaker 1: special one hour round table on the high tech industry 238 00:12:37,800 --> 00:12:42,120 Speaker 1: continues here on Bloomberg Daybreak, with a focus particularly on 239 00:12:42,160 --> 00:12:44,439 Speaker 1: some of the biggest names in the mag seven. So 240 00:12:44,760 --> 00:12:48,079 Speaker 1: stay with us as this special edition of Bloomberg Daybreak 241 00:12:48,360 --> 00:12:51,760 Speaker 1: continues it's twenty minutes past the hour. I'm Nathan Hager, 242 00:12:51,840 --> 00:13:04,400 Speaker 1: and this is Bloomberg. Welcome back to the special edition 243 00:13:04,440 --> 00:13:07,839 Speaker 1: of Bloomberg Daybreak. US markets are closed for the fourth 244 00:13:07,840 --> 00:13:10,160 Speaker 1: of July holiday. I'm Nathan Hager getting you back to 245 00:13:10,200 --> 00:13:12,920 Speaker 1: our high Tech Power Hour. Dan Ives is with US 246 00:13:13,000 --> 00:13:15,920 Speaker 1: global head of Tech Research at web Bush Securities, as 247 00:13:15,920 --> 00:13:20,080 Speaker 1: well as Deepwater Asset Management managing partner Gene Munster Gina. 248 00:13:20,080 --> 00:13:23,160 Speaker 1: I want to focus a little bit on specific names 249 00:13:23,480 --> 00:13:25,760 Speaker 1: in the mag seven we've been talking about in Nvidia, 250 00:13:25,840 --> 00:13:29,280 Speaker 1: So let's talk a little bit more about this powerhouse 251 00:13:29,880 --> 00:13:32,920 Speaker 1: in the AI chip space. There's been talk about it 252 00:13:32,960 --> 00:13:36,440 Speaker 1: getting to a four trillion dollar valuation. We've seen some 253 00:13:36,600 --> 00:13:40,480 Speaker 1: analysts calling for up to a six trillion dollar valuation. 254 00:13:40,880 --> 00:13:43,400 Speaker 1: Where do you see Nvidia going into the second half? 255 00:13:43,920 --> 00:13:46,400 Speaker 3: So at the end of the day, what in Nvidia 256 00:13:46,480 --> 00:13:48,760 Speaker 3: comes down to is what's the growth going to be 257 00:13:48,800 --> 00:13:51,440 Speaker 3: in calendar twenty six and so the street currently has 258 00:13:51,960 --> 00:13:54,640 Speaker 3: estimates for about twenty five percent growth. That's a step 259 00:13:54,679 --> 00:13:58,200 Speaker 3: down from about fifty five percent in calendar twenty five. 260 00:13:58,280 --> 00:14:02,280 Speaker 3: And so I believe that this ultimately that Nvidia is 261 00:14:02,280 --> 00:14:05,760 Speaker 3: going to grow probably somewhere between thirty thirty five percent 262 00:14:05,920 --> 00:14:09,960 Speaker 3: much faster, and this narrative that you just can't rely 263 00:14:10,440 --> 00:14:14,120 Speaker 3: on hardware when it comes to sleep well at night 264 00:14:14,160 --> 00:14:16,440 Speaker 3: for investors. I think that narrative is going to each 265 00:14:16,559 --> 00:14:19,560 Speaker 3: quarter be proved wrong. And the reason is that if 266 00:14:19,600 --> 00:14:22,360 Speaker 3: we are as early as we believe in this whole 267 00:14:22,400 --> 00:14:27,480 Speaker 3: AI transformation, and there is a cost and energy advantage 268 00:14:27,520 --> 00:14:30,440 Speaker 3: of using these invidio chips even ahead of custom silicon 269 00:14:30,520 --> 00:14:33,320 Speaker 3: from these hyperskillers with their building that the world is 270 00:14:33,320 --> 00:14:36,440 Speaker 3: going to continue to depend on in video. So I'm 271 00:14:36,440 --> 00:14:39,800 Speaker 3: a believer that ultimately the stock continues to move higher 272 00:14:40,160 --> 00:14:43,680 Speaker 3: that this on evaluation basis is still despite the big 273 00:14:43,720 --> 00:14:45,880 Speaker 3: move that we've had, one of the most attractive large 274 00:14:45,880 --> 00:14:46,800 Speaker 3: cap tech companies. 275 00:14:47,040 --> 00:14:50,840 Speaker 1: Yeah, it's been breathtaking, Dan, seeing the outperformance that in 276 00:14:50,960 --> 00:14:54,280 Speaker 1: Vidia manages to put out their quarter after quarter. Do 277 00:14:54,320 --> 00:14:59,239 Speaker 1: you see double digit percentage growth for this company continuing 278 00:14:59,320 --> 00:15:00,320 Speaker 1: into quarters to come. 279 00:15:01,360 --> 00:15:03,800 Speaker 2: Look, I think, and Gene hit on it a little. 280 00:15:04,640 --> 00:15:07,080 Speaker 2: I think there's a better chance to me batting in 281 00:15:07,120 --> 00:15:10,560 Speaker 2: front Aaron Judge than these numbers being real and there 282 00:15:10,800 --> 00:15:14,320 Speaker 2: I think in video these are samdbag numbers that the 283 00:15:14,360 --> 00:15:17,200 Speaker 2: street has they're probably gonna beat it anywhere from five 284 00:15:17,320 --> 00:15:20,680 Speaker 2: hundred to eight hundred BIPs. And I think that's the reality, 285 00:15:20,840 --> 00:15:25,920 Speaker 2: is that the street is underestimating growth because there's only 286 00:15:25,960 --> 00:15:28,359 Speaker 2: one ship in the world fueling this, and the sovereigns 287 00:15:28,760 --> 00:15:30,680 Speaker 2: and the rest of the world haven't even started down 288 00:15:30,680 --> 00:15:33,160 Speaker 2: the path. That's why when I look at a video 289 00:15:33,400 --> 00:15:36,600 Speaker 2: four trillion, they get into the first in that club, 290 00:15:36,640 --> 00:15:40,400 Speaker 2: and then Microsoft gets in, then the path to five trillion, 291 00:15:40,600 --> 00:15:46,000 Speaker 2: ultimately six trillion. Because this is just the start. Jane 292 00:15:46,040 --> 00:15:48,240 Speaker 2: talks about second inning to about ten pm and a 293 00:15:48,280 --> 00:15:51,640 Speaker 2: party that goes to four am. They'll be headlines, they'll 294 00:15:51,680 --> 00:15:54,200 Speaker 2: be rich, stocks will sell off. But that's why we're 295 00:15:54,200 --> 00:15:58,760 Speaker 2: gonna be throwing about NASDAK twenty two thousand, twenty five thousand, 296 00:15:59,320 --> 00:16:02,200 Speaker 2: and when we're doing this again, at one point we're 297 00:16:02,200 --> 00:16:04,080 Speaker 2: going to be twin in NAZAC thirty thousand over the 298 00:16:04,120 --> 00:16:06,120 Speaker 2: coming year. That's where this market's going. 299 00:16:06,840 --> 00:16:11,520 Speaker 1: Does it depend for Nvidia gene on the company diversifying 300 00:16:11,520 --> 00:16:15,360 Speaker 1: its customer base, getting that sovereign business to get it there? 301 00:16:15,520 --> 00:16:17,360 Speaker 1: Can it depend just on the hyperscalers? 302 00:16:18,640 --> 00:16:21,360 Speaker 3: I mean, eventually no, but I think over the next 303 00:16:21,360 --> 00:16:24,560 Speaker 3: couple of years. There's still much more to spend, much 304 00:16:24,560 --> 00:16:28,560 Speaker 3: more spending than people anticipate from the hyperscalers. And yes 305 00:16:28,640 --> 00:16:31,240 Speaker 3: we have those other chapters Dan mentioned the sovereign. That's 306 00:16:31,240 --> 00:16:33,000 Speaker 3: a huge deal. I mean governments are going to be 307 00:16:33,040 --> 00:16:37,120 Speaker 3: dependent upon AI companies, industries. But to answer your question, Nathan, 308 00:16:37,160 --> 00:16:39,760 Speaker 3: eventually you do have to to kind of move beyond that. 309 00:16:40,360 --> 00:16:42,960 Speaker 3: The move isn't just. The reason why there's still more 310 00:16:43,480 --> 00:16:48,440 Speaker 3: room to go is that these hyperscalers recognize that the 311 00:16:48,520 --> 00:16:51,440 Speaker 3: demand on this is growing exponentially. Just to quickly frame 312 00:16:51,480 --> 00:16:55,040 Speaker 3: in one example of how demand is exponentially growing, if 313 00:16:55,040 --> 00:16:57,960 Speaker 3: you look at GPT usage on they give it on 314 00:16:58,000 --> 00:17:02,440 Speaker 3: a weekly basis, thea that it is accelerating, it's doubling 315 00:17:02,560 --> 00:17:06,080 Speaker 3: in shorter amounts of time. So when you have this 316 00:17:06,160 --> 00:17:09,600 Speaker 3: kind of hockey stick, they need to keep up with that. 317 00:17:09,600 --> 00:17:13,480 Speaker 3: That means that the need is accelerating. They're not making 318 00:17:13,560 --> 00:17:17,040 Speaker 3: progress towards the getting their arms around it. And so yes, 319 00:17:17,080 --> 00:17:19,919 Speaker 3: we still have a few years left. Yes, eventually they 320 00:17:19,960 --> 00:17:21,800 Speaker 3: need to go beyond the hyperscalers. But I don't think 321 00:17:21,800 --> 00:17:23,000 Speaker 3: investors need to worry about that. 322 00:17:23,800 --> 00:17:27,880 Speaker 1: Are there certain risks that investors do need to worry about, Dan, 323 00:17:28,000 --> 00:17:31,560 Speaker 1: in terms of in Nvidia, I'm thinking about, you know, 324 00:17:31,680 --> 00:17:36,200 Speaker 1: keeping up with the demand for those Blackwell chips, innovating 325 00:17:36,240 --> 00:17:40,399 Speaker 1: even further on some of the highest tech AI chips 326 00:17:40,400 --> 00:17:42,320 Speaker 1: that in Nvidia puts out there. Can it continue to 327 00:17:42,400 --> 00:17:43,560 Speaker 1: keep up with that demand? 328 00:17:44,520 --> 00:17:46,720 Speaker 2: Look, they're a risk, I mean China is a risk 329 00:17:46,840 --> 00:17:49,160 Speaker 2: right in terms of the tree and negotiations to make 330 00:17:49,200 --> 00:17:52,240 Speaker 2: sure because of the each twenty chip that got restricted, 331 00:17:52,320 --> 00:17:56,240 Speaker 2: they're not handing Quai eight billion a quarter, so to 332 00:17:56,280 --> 00:17:58,800 Speaker 2: make sure they're able to sell into China. That is 333 00:17:58,840 --> 00:18:01,800 Speaker 2: a risk because the react these chins that just sitting 334 00:18:01,960 --> 00:18:05,880 Speaker 2: still the supply demand right now, demand the supply still 335 00:18:05,960 --> 00:18:09,400 Speaker 2: ten to one, so they have to continue to keep 336 00:18:09,480 --> 00:18:11,359 Speaker 2: up with that and that is a risk as well. 337 00:18:11,680 --> 00:18:14,600 Speaker 2: And competition is going to come, you know, from AMD 338 00:18:14,840 --> 00:18:18,800 Speaker 2: and others and across chips. But the reality is there's 339 00:18:18,800 --> 00:18:22,840 Speaker 2: only one Gensen. He along with the Dell and others, 340 00:18:23,000 --> 00:18:26,800 Speaker 2: understand the AI revolution better than animals. And that's why 341 00:18:26,800 --> 00:18:29,720 Speaker 2: there's only one godfather of AI. He's wearing a black 342 00:18:30,080 --> 00:18:31,680 Speaker 2: weather jacket. His name of Gensen. 343 00:18:32,440 --> 00:18:34,800 Speaker 1: We're speaking with Dan Ives, the Global head of Tech 344 00:18:34,840 --> 00:18:38,800 Speaker 1: Research at Wedbush Securities. And Gene Munster, managing partner at 345 00:18:38,840 --> 00:18:43,000 Speaker 1: Deepwater Asset Management. Let's move on from Nvidia to Microsoft, 346 00:18:43,000 --> 00:18:45,080 Speaker 1: because it does seem like these are the companies that 347 00:18:45,119 --> 00:18:47,800 Speaker 1: are that are in the race for the four trillion 348 00:18:47,880 --> 00:18:52,800 Speaker 1: dollar valuation potentially. Microsoft has been really aggressive with the 349 00:18:52,840 --> 00:18:55,600 Speaker 1: AI spend, cutting costs to do it as well. They've 350 00:18:55,600 --> 00:19:01,040 Speaker 1: gone through thousands of job cuts over the last few months. Gene, 351 00:19:01,040 --> 00:19:03,800 Speaker 1: what do you make of the strategy under Sacha Nadella 352 00:19:03,960 --> 00:19:04,800 Speaker 1: over at Microsoft. 353 00:19:05,680 --> 00:19:07,840 Speaker 3: I mean, they're doing a great job of being there early, 354 00:19:08,200 --> 00:19:12,040 Speaker 3: of course, and also navigating a changing relationship with open AI. 355 00:19:12,840 --> 00:19:15,960 Speaker 3: And the way this all kind of plays forward is 356 00:19:16,000 --> 00:19:17,600 Speaker 3: that if you look at the growth rates that the 357 00:19:17,600 --> 00:19:20,720 Speaker 3: streets expecting for this year, next year, last few quarters, 358 00:19:20,960 --> 00:19:24,359 Speaker 3: it just hovers around this eleven, twelve, thirteen, fourteen percent. 359 00:19:24,400 --> 00:19:25,880 Speaker 4: It's really a tight range. 360 00:19:26,240 --> 00:19:29,080 Speaker 3: And so at the core, what they're doing right is 361 00:19:29,119 --> 00:19:32,080 Speaker 3: recognizing that they can increase the value of their products 362 00:19:32,160 --> 00:19:33,720 Speaker 3: by injecting AI into it. 363 00:19:33,760 --> 00:19:35,800 Speaker 4: They're the first with Copilot. 364 00:19:35,280 --> 00:19:39,560 Speaker 3: Around that, and it's something I think for the negative 365 00:19:39,680 --> 00:19:43,160 Speaker 3: is you're not going to see an acceleration of Microsoft's 366 00:19:43,200 --> 00:19:45,320 Speaker 3: business to grow in like twenty five percent. That's not 367 00:19:45,359 --> 00:19:48,760 Speaker 3: going to happen. But what you will see is a 368 00:19:48,800 --> 00:19:52,160 Speaker 3: company that's just going to continue to knock it out 369 00:19:52,320 --> 00:19:55,120 Speaker 3: quarter on quarter on quarter on quarter of this kind 370 00:19:55,160 --> 00:19:58,720 Speaker 3: of low double digit growth. And when you do that, 371 00:19:59,000 --> 00:20:01,640 Speaker 3: investors sleep well at night. That's good for the multiple. 372 00:20:02,800 --> 00:20:07,720 Speaker 1: How do you view dan the evolving relationship between Microsoft 373 00:20:07,760 --> 00:20:10,360 Speaker 1: and open Ai. It has been interesting to watch over 374 00:20:10,359 --> 00:20:11,280 Speaker 1: the last few months. 375 00:20:11,760 --> 00:20:15,240 Speaker 2: Look neither I viewed it. It was a training wheel 376 00:20:15,320 --> 00:20:18,159 Speaker 2: situation with the open Ai and the Della and Microsoft 377 00:20:18,200 --> 00:20:23,040 Speaker 2: going back to early twenty three. Training wheels are off Della. 378 00:20:23,640 --> 00:20:28,720 Speaker 2: He's taken Microsoft down the side of a mountain and 379 00:20:28,760 --> 00:20:32,159 Speaker 2: not looking back. The point is that they're just in 380 00:20:32,280 --> 00:20:35,919 Speaker 2: the next stage of the AI revolution and they are 381 00:20:36,040 --> 00:20:39,399 Speaker 2: in the backyard of Microsoft. So I don't when I 382 00:20:39,440 --> 00:20:43,160 Speaker 2: look at OpenAI that would be called competition, say partner, 383 00:20:43,600 --> 00:20:45,920 Speaker 2: but I don't really concern myself with that, just given 384 00:20:45,960 --> 00:20:48,879 Speaker 2: where Microsoft is and they're just gaining more and more momentum. 385 00:20:49,040 --> 00:20:51,119 Speaker 2: I mean to give you example, we think based on 386 00:20:51,160 --> 00:20:53,600 Speaker 2: all of our survey work, for every one hundred dollars 387 00:20:53,960 --> 00:20:58,119 Speaker 2: A customers spent with Microsoft in their lifetime, there's now 388 00:20:58,600 --> 00:21:01,720 Speaker 2: forty to upwards of fifty furs for every one hundred 389 00:21:01,840 --> 00:21:06,960 Speaker 2: dollars they've spent from AI modization opportunity. That basically speaks 390 00:21:06,960 --> 00:21:12,600 Speaker 2: to almost another Microsoft being built within Microsoft. And that's 391 00:21:12,600 --> 00:21:18,520 Speaker 2: why the market is recognizing further and further that stockje. 392 00:21:18,520 --> 00:21:22,600 Speaker 1: Of course, there's so much competition in the cloud, Microsoft, Azure, 393 00:21:22,880 --> 00:21:28,040 Speaker 1: You've got Amazon Web Services, Google Cloud as well. How 394 00:21:28,040 --> 00:21:30,080 Speaker 1: do you see that competition shaking out? 395 00:21:30,520 --> 00:21:33,879 Speaker 3: You know, I think that the competitively, if you think 396 00:21:33,880 --> 00:21:37,400 Speaker 3: it like market share, you're going to see AWS continue 397 00:21:37,440 --> 00:21:39,800 Speaker 3: to lose share. I mean, this is just a math game. Essentially, 398 00:21:39,880 --> 00:21:43,000 Speaker 3: Their AWS is growing high teens and if you look 399 00:21:43,040 --> 00:21:46,160 Speaker 3: at Azure and Google Cloud, it's kind of high twenties, 400 00:21:46,200 --> 00:21:48,320 Speaker 3: low thirties. And so there's just a math game going 401 00:21:48,400 --> 00:21:53,159 Speaker 3: on there. But ultimately is that these three are in 402 00:21:53,280 --> 00:21:56,679 Speaker 3: just such a great position. There is one dynamic that 403 00:21:56,720 --> 00:21:59,560 Speaker 3: I haven't quite figured out how to factor in because 404 00:21:59,600 --> 00:22:01,879 Speaker 3: these are like the pressure points. And you of course 405 00:22:02,200 --> 00:22:05,480 Speaker 3: Amazon trades on that AWS number. Google has a big 406 00:22:05,480 --> 00:22:08,639 Speaker 3: impact on how Google Cloud does, you know, But what 407 00:22:08,760 --> 00:22:12,000 Speaker 3: does as we hear more from Nvidia about a cloud business, 408 00:22:12,240 --> 00:22:14,240 Speaker 3: their cloud businesses, they're starting to build that out. 409 00:22:14,240 --> 00:22:15,000 Speaker 4: What does that mean? 410 00:22:15,400 --> 00:22:19,720 Speaker 3: And ultimately does Meta get into a cloud type of business. 411 00:22:20,160 --> 00:22:23,480 Speaker 3: I still believe Apple also is in a great position to. 412 00:22:24,080 --> 00:22:26,159 Speaker 3: It blows my mind away that they don't have a 413 00:22:26,200 --> 00:22:30,120 Speaker 3: competitor to that, and they have secure this great relationship 414 00:22:30,160 --> 00:22:33,520 Speaker 3: around consumer data. They've done so much with iCloud and backup, 415 00:22:33,560 --> 00:22:35,960 Speaker 3: and I think that there's an opportunity for them to 416 00:22:36,000 --> 00:22:38,919 Speaker 3: get there. And to say it in a more simple 417 00:22:39,440 --> 00:22:41,359 Speaker 3: way is that these companies are in a great place, 418 00:22:41,920 --> 00:22:44,000 Speaker 3: but this is still such a juicy market. I think 419 00:22:44,040 --> 00:22:45,960 Speaker 3: you're going to see more competition from the likes of 420 00:22:46,000 --> 00:22:49,719 Speaker 3: Apple and in video and Meta on the cloud side. 421 00:22:50,000 --> 00:22:53,280 Speaker 1: Interesting point, Dan, how do you see the cloud business 422 00:22:53,520 --> 00:22:57,280 Speaker 1: shaking out among all these mag seven names and how 423 00:22:57,280 --> 00:23:00,240 Speaker 1: does AI play into that book? 424 00:23:00,280 --> 00:23:02,680 Speaker 2: I think AI is the catalyst because you still have 425 00:23:02,800 --> 00:23:05,359 Speaker 2: less than fifty percent of workows they're in the cloud today, 426 00:23:05,760 --> 00:23:08,680 Speaker 2: and also more and more they're hybrid environments, which basically 427 00:23:08,720 --> 00:23:13,199 Speaker 2: means these enterprises that have Azure GCP from Google as 428 00:23:13,200 --> 00:23:17,320 Speaker 2: well as AWS from Amazon, so hybrid environments. It actually 429 00:23:17,359 --> 00:23:21,200 Speaker 2: creates more and more demand across his AI stack because 430 00:23:21,200 --> 00:23:23,280 Speaker 2: the use cases are all being built in the cloud. 431 00:23:23,880 --> 00:23:27,359 Speaker 2: So that's a huge opportunity for Google and Curran is 432 00:23:27,440 --> 00:23:30,440 Speaker 2: obviously taking that mantle. You look at Jasie what he's 433 00:23:30,520 --> 00:23:32,880 Speaker 2: on AWS side. More and more, I think the market's 434 00:23:32,920 --> 00:23:37,080 Speaker 2: going to recognize even though those see share, as Gene said, 435 00:23:37,080 --> 00:23:41,240 Speaker 2: to Microsoft, the opportunity when it comes to AI, that 436 00:23:41,440 --> 00:23:43,600 Speaker 2: just gives them more and more modernization. So it is 437 00:23:43,680 --> 00:23:46,480 Speaker 2: a rising tidal lifts all boots, although the one at 438 00:23:46,520 --> 00:23:48,800 Speaker 2: the top of the mound continues to be Microsoft. 439 00:23:49,720 --> 00:23:54,000 Speaker 1: Interesting Gene, speaking of some of the headlines, we just 440 00:23:54,040 --> 00:23:56,639 Speaker 1: got the headline this week when it comes to Amazon 441 00:23:57,240 --> 00:24:02,640 Speaker 1: that their warehouses might have as many robots now as 442 00:24:02,680 --> 00:24:05,199 Speaker 1: they do humans. Does that play into some of the 443 00:24:05,280 --> 00:24:08,639 Speaker 1: use case, not just for Amazon but across industries. Is 444 00:24:08,680 --> 00:24:11,560 Speaker 1: that where things are going here in terms of AI. 445 00:24:12,760 --> 00:24:16,479 Speaker 3: I mean, this is like watching a glacier move and 446 00:24:16,600 --> 00:24:19,760 Speaker 3: everyone can see it happening. We saw it five years ago, 447 00:24:20,480 --> 00:24:23,680 Speaker 3: I guess thirteen years ago when they bought Kiva and 448 00:24:24,160 --> 00:24:25,720 Speaker 3: we knew that they were going to do more. We 449 00:24:25,800 --> 00:24:28,520 Speaker 3: knew that this was a massive opportunity for Amazon because 450 00:24:28,520 --> 00:24:30,200 Speaker 3: they got the lowest margins of any of the big 451 00:24:30,240 --> 00:24:33,160 Speaker 3: tech company and they have the most opportunity because they've 452 00:24:33,160 --> 00:24:36,200 Speaker 3: got over a million out a million robots, right now 453 00:24:36,200 --> 00:24:39,480 Speaker 3: they've got one point six million total people call it 454 00:24:39,600 --> 00:24:43,760 Speaker 3: one point two working in their fulfillment centers and doing delivery. 455 00:24:44,200 --> 00:24:47,399 Speaker 3: And so I think that you know, we've seen this 456 00:24:47,520 --> 00:24:48,680 Speaker 3: happen when you. 457 00:24:48,560 --> 00:24:49,160 Speaker 4: Put it together. 458 00:24:49,200 --> 00:24:52,479 Speaker 3: If you look at their operating margin, Amazon's operating margins 459 00:24:52,560 --> 00:24:55,000 Speaker 3: right now are up around ten to eleven percent that 460 00:24:55,119 --> 00:24:55,879 Speaker 3: record highs. 461 00:24:56,440 --> 00:24:57,040 Speaker 4: But you're going to. 462 00:24:57,080 --> 00:25:00,440 Speaker 3: See those just continue to inch higher. Robots don't sick, 463 00:25:01,200 --> 00:25:06,280 Speaker 3: Robots don't ask for wage increases, and I think that 464 00:25:06,880 --> 00:25:12,679 Speaker 3: ultimately this idea around Amazon being a margin expansion story 465 00:25:12,760 --> 00:25:15,480 Speaker 3: based on robotics is going to become kind of a 466 00:25:15,520 --> 00:25:18,200 Speaker 3: center theme on the Amazon investment case in the years 467 00:25:18,240 --> 00:25:18,600 Speaker 3: to come. 468 00:25:19,359 --> 00:25:21,719 Speaker 1: Stay with us. We're going to talk even more about 469 00:25:21,880 --> 00:25:24,919 Speaker 1: robotics with two of the names that both of you follow, 470 00:25:25,320 --> 00:25:28,200 Speaker 1: probably closest of all, I want to talk about Tesla 471 00:25:28,680 --> 00:25:31,360 Speaker 1: and Apple on the other side of this break as 472 00:25:31,400 --> 00:25:36,480 Speaker 1: our special edition of a Bloomberg Daybreak, the Tech Edition continues. 473 00:25:36,600 --> 00:25:39,320 Speaker 1: It's thirty seven minutes past the hour. I'm Nathan Hager, 474 00:25:39,400 --> 00:25:55,280 Speaker 1: and this is Bloomberg. Thanks for being with us on 475 00:25:55,359 --> 00:25:58,720 Speaker 1: this special edition of Bloomberg Daybreak. I'm Nathan Hager, and 476 00:25:58,920 --> 00:26:02,040 Speaker 1: US markets are closed for the Independence Day holiday. It's 477 00:26:02,040 --> 00:26:04,760 Speaker 1: time to wrap up our high tech roundtable. We've been 478 00:26:04,800 --> 00:26:08,280 Speaker 1: spending this entire hour with Gene Munster, managing partner at 479 00:26:08,280 --> 00:26:12,400 Speaker 1: Deepwater Asset Management, and Wedbush Securities Global head of Tech Research, 480 00:26:12,920 --> 00:26:17,560 Speaker 1: Dan ives Dan. Whenever we talk, I gotta talk about Tesla. 481 00:26:17,960 --> 00:26:22,080 Speaker 1: There's been so much drama around this stock this year. 482 00:26:22,800 --> 00:26:24,919 Speaker 1: Do you look past it? How do you look past it? 483 00:26:25,640 --> 00:26:28,399 Speaker 2: Look, it's been and obviously you know, knowing and covering 484 00:26:28,520 --> 00:26:30,439 Speaker 2: Musk from the beginning. I mean this has been a 485 00:26:30,480 --> 00:26:34,600 Speaker 2: soap opera, right because the BFF situation Musk and Trump, 486 00:26:35,200 --> 00:26:39,159 Speaker 2: it's now turned into a junior high school friendship gone bad. 487 00:26:39,880 --> 00:26:45,640 Speaker 2: And this enemy situation that continues to be the overhang 488 00:26:45,800 --> 00:26:51,520 Speaker 2: because Tesla is going into its biggest chapter growth autonomous robotics, 489 00:26:51,520 --> 00:26:54,760 Speaker 2: but especially when it comes to cyber cabin road attacks 490 00:26:54,760 --> 00:26:58,000 Speaker 2: and our team was Aaron Austin. The last thing you 491 00:26:58,160 --> 00:27:01,919 Speaker 2: want is Trump being more hawkish when it comes to 492 00:27:01,920 --> 00:27:05,920 Speaker 2: the regulatory landscape around autonomous and Tesla. Now, look, I 493 00:27:06,000 --> 00:27:09,159 Speaker 2: ultimately believe it will settle. And at the end of 494 00:27:09,200 --> 00:27:13,240 Speaker 2: the day, Trump needs Musk, must needs Trump, and Tesla 495 00:27:13,359 --> 00:27:16,200 Speaker 2: continues to be especially on the autonomous side the best 496 00:27:16,200 --> 00:27:18,600 Speaker 2: way to compete with China. But with that said, it's 497 00:27:18,600 --> 00:27:20,520 Speaker 2: like you just have to get you and Gen always 498 00:27:20,560 --> 00:27:22,720 Speaker 2: talks about this as well, and those are so great. 499 00:27:23,359 --> 00:27:26,720 Speaker 2: You have to just navigate through headlines. He far through 500 00:27:26,760 --> 00:27:30,400 Speaker 2: the trees. You're dealing Muster to Trump. It's a BFF 501 00:27:30,480 --> 00:27:33,400 Speaker 2: situation gone bad, But it doesn't change our bullet view 502 00:27:33,880 --> 00:27:38,240 Speaker 2: that Automas is worth a trillion dollars alone to Tesla's stock. 503 00:27:39,520 --> 00:27:43,840 Speaker 1: How do you see the integration of Xai with Tesla 504 00:27:44,200 --> 00:27:47,119 Speaker 1: affecting things? Does that play into your bookcase as well? 505 00:27:47,520 --> 00:27:50,040 Speaker 2: Yeah? I mean, look, my view is down the reard. 506 00:27:50,560 --> 00:27:53,240 Speaker 2: There's a good chance that it all gets integrated into 507 00:27:53,280 --> 00:27:58,320 Speaker 2: one holding structure, from Xai to x to Tesla, you know, 508 00:27:58,359 --> 00:28:01,120 Speaker 2: and maybe even a piece of space, because that's all 509 00:28:01,280 --> 00:28:05,520 Speaker 2: part of I think, the broader vision, especially when it 510 00:28:05,520 --> 00:28:10,520 Speaker 2: comes to AI. So look, this is one where sentiment 511 00:28:10,640 --> 00:28:14,040 Speaker 2: continues to be very negative on Tessa, but I believe 512 00:28:14,080 --> 00:28:17,520 Speaker 2: when it comes to pure physical AI, the two best 513 00:28:17,520 --> 00:28:21,480 Speaker 2: physical AI plays are Nvidia Tessa. When you to male 514 00:28:21,640 --> 00:28:22,960 Speaker 2: Thomas and Robotics. 515 00:28:23,280 --> 00:28:25,560 Speaker 1: The sentiment matters though, doesn't it. And Gene, I'd like 516 00:28:25,600 --> 00:28:27,359 Speaker 1: you to weigh in on this as well, whether the 517 00:28:27,359 --> 00:28:31,879 Speaker 1: brand has been attainted too much over the last few months. 518 00:28:32,359 --> 00:28:34,879 Speaker 3: I mean, it's it's taking a huge hit, but people 519 00:28:34,920 --> 00:28:38,360 Speaker 3: forget it's something else. And it's pretty clear that Elon's 520 00:28:38,360 --> 00:28:41,920 Speaker 3: trying to strike some middle ground. And I think that 521 00:28:41,960 --> 00:28:44,480 Speaker 3: if you fast forward a year from now, I think 522 00:28:44,520 --> 00:28:46,920 Speaker 3: the whole brand damage thing is going to be in 523 00:28:46,960 --> 00:28:50,040 Speaker 3: the rooview mirror and at the core, the numbers this 524 00:28:50,120 --> 00:28:52,400 Speaker 3: year are going to be ugly. The delivery numbers for 525 00:28:52,440 --> 00:28:53,960 Speaker 3: the full year are going to fall below where the 526 00:28:53,960 --> 00:28:56,080 Speaker 3: streets at. They're probably going to be down ten percent 527 00:28:56,160 --> 00:28:58,560 Speaker 3: something like that. But we're gonna see a nice bounce 528 00:28:58,640 --> 00:29:00,320 Speaker 3: back next year because the brand am I'm just going 529 00:29:00,360 --> 00:29:02,440 Speaker 3: to go away. We're probably going to grow deliveries twenty 530 00:29:02,480 --> 00:29:04,480 Speaker 3: percent that new moral affordable model. 531 00:29:04,520 --> 00:29:05,760 Speaker 4: Yes, we lose the tax. 532 00:29:05,560 --> 00:29:07,240 Speaker 3: Credit, but I think when you put all this together, 533 00:29:07,560 --> 00:29:10,600 Speaker 3: we're going to see some nice growth next year. And ultimately, 534 00:29:10,600 --> 00:29:13,520 Speaker 3: when we talk about the psychology about this for investors, 535 00:29:14,240 --> 00:29:16,520 Speaker 3: is that this autonomy thing I think I don't think 536 00:29:16,560 --> 00:29:19,080 Speaker 3: people can even begin to grasp. I have a hard 537 00:29:19,080 --> 00:29:21,040 Speaker 3: time beginning, and I think about this all day long, 538 00:29:21,440 --> 00:29:23,840 Speaker 3: how big of a deal this is in terms of autonomy, 539 00:29:23,920 --> 00:29:26,280 Speaker 3: and I just want to highlight one piece, one of 540 00:29:27,400 --> 00:29:30,120 Speaker 3: a maddening piece to me on this is why why 541 00:29:30,160 --> 00:29:33,760 Speaker 3: do legislators slow the adoption of this? These vehicles are 542 00:29:33,920 --> 00:29:37,920 Speaker 3: infinitely more safe than human drivers. Humans are amazing drivers 543 00:29:37,960 --> 00:29:40,640 Speaker 3: when they're not distracted, but that's becoming more and more difficult. 544 00:29:41,080 --> 00:29:42,680 Speaker 3: And so at the end of the day, I think 545 00:29:42,680 --> 00:29:46,640 Speaker 3: that we're going to see these autonomous systems. There's really 546 00:29:46,680 --> 00:29:48,840 Speaker 3: two companies that are there, and I think that if 547 00:29:48,840 --> 00:29:52,480 Speaker 3: you fast forward twenty six, twenty seven to twenty eight, yes, 548 00:29:52,520 --> 00:29:55,120 Speaker 3: it will take longer than anything, but eventually I think 549 00:29:55,160 --> 00:29:58,160 Speaker 3: the psychology are on Tesla is going to be anchored 550 00:29:58,160 --> 00:30:02,000 Speaker 3: in that autonomy physical AI, and like Dan said, there 551 00:30:02,040 --> 00:30:05,520 Speaker 3: really is really two companies that are going after that. 552 00:30:06,400 --> 00:30:09,640 Speaker 1: Sticking with you, Jane, let's turn to a stock that you, 553 00:30:09,760 --> 00:30:14,320 Speaker 1: of course follow very closely. That would be Apple. It's 554 00:30:14,360 --> 00:30:17,560 Speaker 1: been kind of an interesting year for Apple so far, 555 00:30:18,400 --> 00:30:21,560 Speaker 1: a lot of underwhelming sentiment, I think we could say 556 00:30:21,880 --> 00:30:24,760 Speaker 1: coming out of the latest Worldwide Developers Conference. Now the 557 00:30:24,800 --> 00:30:27,240 Speaker 1: news just this week that the iPhone makers thinking of 558 00:30:27,320 --> 00:30:32,600 Speaker 1: going outside its ecosystem to power the AI backed serie. 559 00:30:33,280 --> 00:30:34,680 Speaker 1: How do you view Apple right now. 560 00:30:35,200 --> 00:30:36,800 Speaker 3: I think this is going to be a great back 561 00:30:36,840 --> 00:30:39,000 Speaker 3: half of the year for the stock. It seems like 562 00:30:39,120 --> 00:30:42,360 Speaker 3: I'm disconnected from reality. But a couple of things to consider. 563 00:30:42,920 --> 00:30:45,960 Speaker 3: Number one is the bar for AI could be lower. 564 00:30:46,000 --> 00:30:46,520 Speaker 2: For Apple. 565 00:30:46,720 --> 00:30:49,560 Speaker 3: They basically went on a media blitz right after WWDC 566 00:30:49,720 --> 00:30:52,240 Speaker 3: Federini Jaws went out and said it's not going to 567 00:30:52,280 --> 00:30:54,240 Speaker 3: be till spring of next year until you see anything 568 00:30:54,320 --> 00:30:56,960 Speaker 3: in substance with a new SERI. And then second, if 569 00:30:56,960 --> 00:30:59,440 Speaker 3: you look at the iPhone numbers, they're looking for the 570 00:30:59,480 --> 00:31:02,400 Speaker 3: streets looking for one percent growth this fiscal year four 571 00:31:02,520 --> 00:31:05,800 Speaker 3: next year, and come let's come back to where we 572 00:31:05,800 --> 00:31:08,640 Speaker 3: were a year year and a half ago. Remember thirty 573 00:31:08,760 --> 00:31:12,560 Speaker 3: nine percent iPhone growth in twenty twenty one. That's a 574 00:31:12,760 --> 00:31:15,720 Speaker 3: massive year. You're gonna get some of those upgrades. I 575 00:31:15,760 --> 00:31:18,560 Speaker 3: think they actually beat the iPhone number the streets looking 576 00:31:18,600 --> 00:31:22,040 Speaker 3: for a flat iPhone in the September quarter. I think 577 00:31:22,120 --> 00:31:23,800 Speaker 3: the guide that they're going to give when they report 578 00:31:23,840 --> 00:31:25,800 Speaker 3: the June quarter is going to be a positive. I 579 00:31:25,880 --> 00:31:27,560 Speaker 3: expect this stock to respond accordingly. 580 00:31:27,760 --> 00:31:30,280 Speaker 1: We're speaking with Dan Ives, the global head of Tech 581 00:31:30,320 --> 00:31:35,120 Speaker 1: Research at Wedbush Securities, and Gene Munster, managing partner at 582 00:31:35,160 --> 00:31:40,440 Speaker 1: Deepwater Asset Management. Let's talk about some other big names 583 00:31:40,520 --> 00:31:44,560 Speaker 1: in the mag seven meta platforms. There's been all this 584 00:31:44,640 --> 00:31:50,960 Speaker 1: talk about the super intelligence team Mark Zuckerberg's putting together Gene. 585 00:31:50,960 --> 00:31:53,160 Speaker 1: What do you make of that comes back? 586 00:31:53,200 --> 00:31:56,000 Speaker 3: Do you think that Zuckerberg is competent? I think he is. 587 00:31:56,040 --> 00:31:57,840 Speaker 3: I think he understands where things are going. And what 588 00:31:57,880 --> 00:32:00,520 Speaker 3: I make of it is it's a tell how early 589 00:32:00,560 --> 00:32:03,000 Speaker 3: we are in this AI that they are recognizing that 590 00:32:03,480 --> 00:32:05,760 Speaker 3: there still is a lot to be, a lot to 591 00:32:05,840 --> 00:32:09,560 Speaker 3: happen here and what's had steak. I mean we're talking 592 00:32:09,560 --> 00:32:13,479 Speaker 3: about ten fifty one hundred million dollar bounties. I mean 593 00:32:13,480 --> 00:32:15,920 Speaker 3: these make pro athletes look like chump change some of 594 00:32:16,000 --> 00:32:19,959 Speaker 3: their pay packages. And the reason what we make of it, Nathan, 595 00:32:20,080 --> 00:32:23,480 Speaker 3: is that if in fact these tech companies are competent 596 00:32:23,840 --> 00:32:27,000 Speaker 3: and they're recognizing investing in individuals that are worth one 597 00:32:27,080 --> 00:32:30,600 Speaker 3: hundred million dollar bonuses, I think that that really speaks 598 00:32:30,640 --> 00:32:32,720 Speaker 3: to the bigger pictures. So when I see what's going 599 00:32:32,760 --> 00:32:35,920 Speaker 3: on with their metas and their superintelligence, I just think 600 00:32:35,960 --> 00:32:39,400 Speaker 3: I just can't stop but thinking about the big picture 601 00:32:39,720 --> 00:32:42,000 Speaker 3: about what's at steak here with AI. 602 00:32:42,160 --> 00:32:45,040 Speaker 1: And it is really interesting though, Dan to see, you know, 603 00:32:45,120 --> 00:32:49,880 Speaker 1: meta platforms making this big, high profile move around staffing 604 00:32:50,000 --> 00:32:52,400 Speaker 1: up on AI and then just to go back to 605 00:32:52,440 --> 00:32:57,120 Speaker 1: the conversation about Apple maybe looking outside its own ecosystem 606 00:32:57,160 --> 00:33:00,880 Speaker 1: to power its own AI. Can these two names that 607 00:33:01,040 --> 00:33:03,240 Speaker 1: had been so big just a couple of years ago, 608 00:33:03,840 --> 00:33:05,840 Speaker 1: can they play catch up with with some of the 609 00:33:05,880 --> 00:33:06,760 Speaker 1: others in the space. 610 00:33:07,720 --> 00:33:09,720 Speaker 2: Well, I think they can because it all comes down 611 00:33:09,760 --> 00:33:13,320 Speaker 2: to install base and resources and developers. You know, when 612 00:33:13,360 --> 00:33:15,520 Speaker 2: you look good, go say like a meta I mean 613 00:33:15,640 --> 00:33:19,040 Speaker 2: Zuckerberg basically it's called like a wartime CEO in terms 614 00:33:19,080 --> 00:33:20,959 Speaker 2: of what he's doing, and I think going to more 615 00:33:21,000 --> 00:33:25,360 Speaker 2: and more monetize when you've got consumer AI revolution, not 616 00:33:25,520 --> 00:33:30,120 Speaker 2: enterprise with Nvidia and obviously the hyperscalers. Consumer AI revolution 617 00:33:30,320 --> 00:33:35,560 Speaker 2: runs through Apple, Meta and Alphabet. So I just view 618 00:33:35,600 --> 00:33:40,680 Speaker 2: it as it's all just about making the right strategic moves. 619 00:33:40,720 --> 00:33:44,280 Speaker 2: Sometimes you're late, but because the install based that all 620 00:33:44,320 --> 00:33:46,320 Speaker 2: of that matters that you end up being right. You 621 00:33:46,320 --> 00:33:49,960 Speaker 2: can lose the first second round, you win the last ten, 622 00:33:50,080 --> 00:33:52,080 Speaker 2: you win the match, right, And I think that's sort 623 00:33:52,080 --> 00:33:54,160 Speaker 2: of where they are, and I think that's why I 624 00:33:54,440 --> 00:33:57,600 Speaker 2: continue to include them Core. You know, when we've used 625 00:33:57,600 --> 00:34:00,520 Speaker 2: the ives AI thirty in terms of really who the 626 00:34:00,560 --> 00:34:01,960 Speaker 2: winners are when it comes to AI. 627 00:34:02,960 --> 00:34:08,040 Speaker 1: Interesting to think about the consumer case for artificial intelligence 628 00:34:08,080 --> 00:34:11,800 Speaker 1: when you think about what it's doing in terms of productivity, 629 00:34:12,120 --> 00:34:15,880 Speaker 1: how companies are thinking about, you know, their job structures, 630 00:34:15,920 --> 00:34:19,160 Speaker 1: that sort of thing. When in the consumer space, we've 631 00:34:19,200 --> 00:34:24,839 Speaker 1: seen a lot of interesting videos, pictures, images that might 632 00:34:24,880 --> 00:34:29,439 Speaker 1: potentially fool people down the line as well. Gene, talk 633 00:34:29,480 --> 00:34:32,160 Speaker 1: a little bit about how you're thinking in terms of 634 00:34:32,239 --> 00:34:36,320 Speaker 1: an analyst of this space, about how AI is shaping 635 00:34:36,400 --> 00:34:38,359 Speaker 1: up for the consumer. 636 00:34:38,640 --> 00:34:41,640 Speaker 3: With Tail two Cities, I mean, there's what's going on 637 00:34:41,800 --> 00:34:45,439 Speaker 3: with AI. Agree with Dan's view about Coupertino and all 638 00:34:45,480 --> 00:34:48,799 Speaker 3: things run through when it comes to consumer with Apple Zoom, 639 00:34:48,840 --> 00:34:51,440 Speaker 3: I think there's another piece to it that isn't necessarily 640 00:34:51,520 --> 00:34:53,160 Speaker 3: an analyst piece to it, but more of just like 641 00:34:53,200 --> 00:34:55,520 Speaker 3: a human side to this is I think what we're 642 00:34:55,520 --> 00:34:59,120 Speaker 3: going to see around consumer and AI is going to 643 00:34:59,200 --> 00:35:03,080 Speaker 3: be a massive acceleration in terms of what we saw 644 00:35:03,200 --> 00:35:05,239 Speaker 3: was social over the last fifteen years. In terms of 645 00:35:05,280 --> 00:35:09,279 Speaker 3: how it changes I think human's ability to engage in. 646 00:35:09,320 --> 00:35:09,880 Speaker 2: The real world. 647 00:35:10,400 --> 00:35:13,120 Speaker 3: In other words, when I think about all the good 648 00:35:13,120 --> 00:35:15,120 Speaker 3: things that are going to happen, and I want to 649 00:35:15,160 --> 00:35:18,839 Speaker 3: make sure that people understand how the positive for us 650 00:35:18,880 --> 00:35:21,880 Speaker 3: that I think AI overwhelmingly will be. But on the 651 00:35:21,920 --> 00:35:26,799 Speaker 3: consumer side, I do I fear that we are the 652 00:35:26,840 --> 00:35:30,200 Speaker 3: ability for the machine. It just hit that video exactly 653 00:35:30,239 --> 00:35:32,880 Speaker 3: at the right time when you're vulnerable to keep watching 654 00:35:32,920 --> 00:35:34,279 Speaker 3: more and more of them. I think that that's a 655 00:35:34,320 --> 00:35:37,680 Speaker 3: piece that really we haven't as a society come to 656 00:35:37,719 --> 00:35:39,680 Speaker 3: grips with in terms of how powerful this is going 657 00:35:39,760 --> 00:35:39,920 Speaker 3: to be. 658 00:35:40,440 --> 00:35:42,840 Speaker 1: In our last couple of minutes, Dan, I'd like to 659 00:35:42,880 --> 00:35:46,839 Speaker 1: get your thoughts on outside the mag seven, what you're 660 00:35:46,840 --> 00:35:50,400 Speaker 1: looking at in terms of opportunities in the tech space. 661 00:35:50,600 --> 00:35:52,000 Speaker 1: What are some of your favorites. 662 00:35:52,320 --> 00:35:54,800 Speaker 2: Yeah, and also let me say, Gene, you know, anyone 663 00:35:54,840 --> 00:35:57,840 Speaker 2: that follows him on social or obviously you know publicly, 664 00:35:58,320 --> 00:36:00,600 Speaker 2: you know he dives so deep in to some of 665 00:36:00,640 --> 00:36:03,279 Speaker 2: these trends, which I think is very important for investors 666 00:36:03,640 --> 00:36:07,640 Speaker 2: to understand what's actually making up this growth demand in 667 00:36:07,719 --> 00:36:11,719 Speaker 2: AI across consumer and across the enterprise. And look, and 668 00:36:11,880 --> 00:36:14,360 Speaker 2: I would just say like to me outside maxim like 669 00:36:14,800 --> 00:36:18,200 Speaker 2: cybersecurity is going to be a huge beneficiary CrowdStrike pal 670 00:36:18,320 --> 00:36:21,400 Speaker 2: out to z Scalar, you know, being our favorites there, 671 00:36:22,080 --> 00:36:24,200 Speaker 2: you know, especially as more and more moves to the cloud. 672 00:36:24,560 --> 00:36:26,960 Speaker 2: It's led by from a use case perspective, what I 673 00:36:27,000 --> 00:36:30,440 Speaker 2: believe the probably the best software use case out there 674 00:36:30,520 --> 00:36:32,839 Speaker 2: is Palenteered and that's a trillion dollar mark cap next 675 00:36:32,880 --> 00:36:36,720 Speaker 2: two to three years, as well as names like Snowflake, Mango, 676 00:36:36,800 --> 00:36:39,560 Speaker 2: dB and others. You know, you go, you focus on 677 00:36:39,640 --> 00:36:43,160 Speaker 2: who are the second third derivatives of AI? 678 00:36:44,040 --> 00:36:46,280 Speaker 1: And how about Eugene, what are you looking at outside 679 00:36:46,360 --> 00:36:49,560 Speaker 1: the mag seven? Where would you steer clear as well? 680 00:36:49,719 --> 00:36:52,479 Speaker 3: Well, I got I mean within this one's a six 681 00:36:52,520 --> 00:36:56,640 Speaker 3: billion dollar market camp but Box as in not drop Box, 682 00:36:56,680 --> 00:36:59,960 Speaker 3: but Box. And this is a company that's growing at 683 00:37:00,239 --> 00:37:03,360 Speaker 3: seven percent next year, nine percent this year. But what 684 00:37:03,400 --> 00:37:06,600 Speaker 3: they're doing around basically talk about the consumer side of it, 685 00:37:06,640 --> 00:37:09,239 Speaker 3: basically taking your consumer all the files that you have 686 00:37:09,560 --> 00:37:11,640 Speaker 3: and be able to use an agent on top of 687 00:37:11,680 --> 00:37:14,840 Speaker 3: it to ask, you know, where different things are insights 688 00:37:14,840 --> 00:37:17,040 Speaker 3: around the data that you have. So I think that's 689 00:37:17,080 --> 00:37:20,239 Speaker 3: one we own it and our fund that is off 690 00:37:20,280 --> 00:37:24,480 Speaker 3: the beaten path that we're really bullish on as far 691 00:37:24,560 --> 00:37:29,040 Speaker 3: as where to avoid the rising tide is so powerful. 692 00:37:29,080 --> 00:37:31,279 Speaker 3: I don't have a good answer to that, and I 693 00:37:31,320 --> 00:37:34,520 Speaker 3: think that maybe set a different way. My biggest concern 694 00:37:35,200 --> 00:37:38,040 Speaker 3: about everything that's going on is I have a hard 695 00:37:38,080 --> 00:37:40,319 Speaker 3: time coming up with a concern, and that concerns me. 696 00:37:40,360 --> 00:37:41,360 Speaker 4: If that makes any sense. 697 00:37:41,560 --> 00:37:44,520 Speaker 3: Yeah, And so I think that you know, to bet 698 00:37:44,560 --> 00:37:46,600 Speaker 3: against the names that Dan and I spend so much 699 00:37:46,600 --> 00:37:49,040 Speaker 3: time with, I mean, the broader theme, this rising tide, 700 00:37:50,120 --> 00:37:51,760 Speaker 3: would I would stay with the trend? 701 00:37:52,520 --> 00:37:54,160 Speaker 1: Are there any that you'd steer clear of? 702 00:37:54,239 --> 00:37:54,439 Speaker 2: Dan? 703 00:37:54,560 --> 00:37:55,040 Speaker 1: Just quickly? 704 00:37:56,400 --> 00:37:58,640 Speaker 2: I mean to me, it's some of the legacy players. 705 00:37:58,760 --> 00:38:01,920 Speaker 2: This just goes to each peas the Dell's, have you 706 00:38:02,040 --> 00:38:05,279 Speaker 2: them at shared donors? So those are the ones that 707 00:38:05,320 --> 00:38:07,440 Speaker 2: we're definitely less positive on. 708 00:38:08,480 --> 00:38:11,080 Speaker 1: All right, Well, we'll leave it there until next time. 709 00:38:11,239 --> 00:38:13,640 Speaker 1: Thanks so much to both of you for being with 710 00:38:13,719 --> 00:38:17,960 Speaker 1: us on this special high tech based edition of Bloomberg Daybreak. 711 00:38:18,000 --> 00:38:21,959 Speaker 1: Gene Munster, managing partner at Deepwater Asset Management, and Dan Ives, 712 00:38:22,000 --> 00:38:25,319 Speaker 1: Global head of Tech Research at Webbush Securities. Thanks to 713 00:38:25,360 --> 00:38:27,840 Speaker 1: you as well for taking time out on this holiday. 714 00:38:28,160 --> 00:38:30,760 Speaker 1: I'm Nathan Hager inviting you to stay with us. Today's 715 00:38:30,800 --> 00:38:34,600 Speaker 1: top stories and global business headlines are coming up right now.