1 00:00:01,760 --> 00:00:04,240 Speaker 1: Hello, and a very happy new year to you and 2 00:00:04,280 --> 00:00:07,880 Speaker 1: your family. Welcome to this special edition of Bloomberg Daybreak. 3 00:00:08,200 --> 00:00:11,520 Speaker 1: Markets are closed as we ring in twenty twenty six. 4 00:00:11,800 --> 00:00:14,360 Speaker 1: I'm Nathan Hager coming up at this hour. We're gonna 5 00:00:14,360 --> 00:00:16,560 Speaker 1: look at what's ahead for the sector that has led 6 00:00:16,640 --> 00:00:19,200 Speaker 1: the way for the stock market the last couple of years. 7 00:00:19,960 --> 00:00:24,360 Speaker 1: Big Tech. Twenty twenty five was once again bullish for technology, 8 00:00:24,400 --> 00:00:27,520 Speaker 1: but not without its bumps and bruises. A deep sell 9 00:00:27,560 --> 00:00:30,920 Speaker 1: off in April, followed by a powerful rally, then another 10 00:00:31,000 --> 00:00:33,440 Speaker 1: sell off of many of the biggest names in the 11 00:00:33,440 --> 00:00:36,479 Speaker 1: final quarter. So what could be in store for twenty 12 00:00:36,560 --> 00:00:39,360 Speaker 1: twenty six? Who better to ask than two of the 13 00:00:39,360 --> 00:00:43,000 Speaker 1: most prominent analysts on the street. Gene Monster, managing partner 14 00:00:43,040 --> 00:00:46,160 Speaker 1: in Deepwater Asset Management, is with us along with Dan Ives, 15 00:00:46,200 --> 00:00:49,440 Speaker 1: global head of Tech Research at web Bush Securities. 16 00:00:49,120 --> 00:00:50,040 Speaker 2: For the full hour. 17 00:00:50,120 --> 00:00:52,199 Speaker 1: It is great to have both of you back on 18 00:00:52,240 --> 00:00:56,360 Speaker 1: what has become a semi annual tradition here on Bloomberg Daybreak. 19 00:00:56,400 --> 00:00:59,000 Speaker 1: But before we look ahead to twenty twenty six, let's 20 00:00:59,040 --> 00:01:00,760 Speaker 1: look back at what both that you had to say 21 00:01:00,760 --> 00:01:03,160 Speaker 1: about tech the last time we were all together here 22 00:01:03,600 --> 00:01:07,600 Speaker 1: back on the fourth of July. Gene, let's start with you. 23 00:01:07,600 --> 00:01:09,120 Speaker 1: You were pretty enthusiastic. 24 00:01:09,680 --> 00:01:13,360 Speaker 3: I actually am so bullish on AI. I think that 25 00:01:13,400 --> 00:01:17,600 Speaker 3: it has the power for these companies to continue to 26 00:01:17,600 --> 00:01:20,959 Speaker 3: move higher over the next three to five years, despite 27 00:01:20,959 --> 00:01:23,280 Speaker 3: what is going to happen, what could happen with the 28 00:01:23,280 --> 00:01:25,679 Speaker 3: overall macro And I don't like being out on a 29 00:01:25,720 --> 00:01:29,399 Speaker 3: limb that farart and the right approach is that AI 30 00:01:29,959 --> 00:01:32,039 Speaker 3: is just much more impactful. 31 00:01:32,280 --> 00:01:36,080 Speaker 1: Of course, Gene, that was before the rotation at the 32 00:01:36,200 --> 00:01:39,320 Speaker 1: end of twenty twenty five. Are you still as enthusiastic 33 00:01:39,440 --> 00:01:41,360 Speaker 1: about big tech as you were then? 34 00:01:43,000 --> 00:01:46,280 Speaker 3: Yeah, nothing has changed in that optimism. I still think 35 00:01:46,319 --> 00:01:50,600 Speaker 3: we're going to see the AI trade outperform the Nasdaq 36 00:01:50,680 --> 00:01:52,640 Speaker 3: for next year. I think that the Nasdaq is going 37 00:01:52,720 --> 00:01:56,640 Speaker 3: to be up call it five ten plus percent. So 38 00:01:56,840 --> 00:02:00,240 Speaker 3: still optimistic, still believe we're I'd put it in the 39 00:02:00,280 --> 00:02:03,480 Speaker 3: second inning of all this and understand that that may 40 00:02:03,600 --> 00:02:08,359 Speaker 3: come across as seemingly out of touch with reality, given 41 00:02:08,480 --> 00:02:10,639 Speaker 3: I think some of the towards the end of the year, 42 00:02:10,760 --> 00:02:13,120 Speaker 3: some of that, some of that concern that has poked 43 00:02:13,160 --> 00:02:17,040 Speaker 3: its head up around the AI trade, some issues that 44 00:02:17,120 --> 00:02:19,880 Speaker 3: investors have had about the amount of investment that have 45 00:02:19,919 --> 00:02:22,839 Speaker 3: been made in the market at times just shrugging off 46 00:02:22,880 --> 00:02:26,760 Speaker 3: good news. But Ayden, I think that this is still intact. 47 00:02:26,760 --> 00:02:30,360 Speaker 3: I think the transformation really hasn't even begun, and I 48 00:02:30,360 --> 00:02:33,280 Speaker 3: think that patients will pay off when it comes to 49 00:02:33,480 --> 00:02:35,400 Speaker 3: wealth creation over the next few years. 50 00:02:35,720 --> 00:02:37,560 Speaker 1: All Right, I want to turn down to you, Dan 51 00:02:37,680 --> 00:02:40,320 Speaker 1: over at Wedbush. I think I have a feeling what 52 00:02:40,400 --> 00:02:42,760 Speaker 1: you might say. But let's listen back to what you 53 00:02:42,840 --> 00:02:44,239 Speaker 1: told us back in July. 54 00:02:44,600 --> 00:02:48,919 Speaker 2: This is a fourth Industrial revolution, this tact bull market. 55 00:02:49,080 --> 00:02:51,880 Speaker 2: It's another three years ahead. And that's why I think 56 00:02:51,919 --> 00:02:55,880 Speaker 2: it's the popcorn get the Champagne Islands handing slowing it down. 57 00:02:56,440 --> 00:02:58,200 Speaker 1: Do you see anything slowing it down since then? 58 00:02:58,280 --> 00:03:03,040 Speaker 2: Dan, Look, I'm more bullish on the theme today than 59 00:03:03,040 --> 00:03:06,760 Speaker 2: I was back in the summer, given my monization, given 60 00:03:06,800 --> 00:03:11,840 Speaker 2: what we've seen with the spend, given themes like Pallentier 61 00:03:11,880 --> 00:03:14,240 Speaker 2: and others. Is the use cases are built out and 62 00:03:14,280 --> 00:03:18,560 Speaker 2: now going into robotics and autonomous. To me, look, it's 63 00:03:18,600 --> 00:03:20,839 Speaker 2: two more years left this technical market. I'm not gonna 64 00:03:20,840 --> 00:03:22,360 Speaker 2: say we're not gonna have white knuckles as me and 65 00:03:22,400 --> 00:03:26,880 Speaker 2: you always talk about. But nothing in any way makes 66 00:03:26,960 --> 00:03:30,240 Speaker 2: me get off as AI train to some extend. It's 67 00:03:30,320 --> 00:03:31,000 Speaker 2: more in bolden. 68 00:03:32,280 --> 00:03:34,839 Speaker 1: I want to turn back to you, Gene. You say 69 00:03:34,840 --> 00:03:38,839 Speaker 1: it's the second inning in the AI trade. I think 70 00:03:38,840 --> 00:03:41,960 Speaker 1: in the times that we've spoken before, it's kind of 71 00:03:42,000 --> 00:03:45,480 Speaker 1: been where it's been before, right, I mean, I think 72 00:03:45,520 --> 00:03:47,120 Speaker 1: I've heard you say we're in the second inning for 73 00:03:47,480 --> 00:03:49,720 Speaker 1: quite some time. When do we get to the third? 74 00:03:51,440 --> 00:03:53,360 Speaker 3: Well, earlier in the year, I guess at the beginning 75 00:03:53,360 --> 00:03:55,280 Speaker 3: of twenty five, I thought we're in the third inning, 76 00:03:55,920 --> 00:03:59,440 Speaker 3: and so I guess what happened to make me believe 77 00:03:59,440 --> 00:04:01,560 Speaker 3: that we're in this second inning? Just like to put 78 00:04:01,600 --> 00:04:03,920 Speaker 3: some specifics on it, and it's this is what I 79 00:04:03,960 --> 00:04:06,680 Speaker 3: love about this the year end is we can look 80 00:04:06,720 --> 00:04:08,520 Speaker 3: back and just look at the kind of the arc 81 00:04:08,560 --> 00:04:11,480 Speaker 3: of what's happened. At the beginning of the year, the 82 00:04:11,520 --> 00:04:15,240 Speaker 3: street was looking for in Vidia to have eighteen percent 83 00:04:15,320 --> 00:04:18,600 Speaker 3: growth for calendar twenty six. If you look at what 84 00:04:18,600 --> 00:04:22,640 Speaker 3: they said at the end of November. This excludes anything 85 00:04:22,720 --> 00:04:26,240 Speaker 3: from the H two hundreds in China, but they're going 86 00:04:26,320 --> 00:04:29,880 Speaker 3: to do somewhere around the mid sixty percent growth. So 87 00:04:30,760 --> 00:04:33,800 Speaker 3: this is a company that this is not a one 88 00:04:33,800 --> 00:04:36,400 Speaker 3: to two billion dollar revenue company. This is a two 89 00:04:36,480 --> 00:04:38,760 Speaker 3: hundred and fifty three hundred billion dollar company that's seen 90 00:04:39,200 --> 00:04:42,640 Speaker 3: an acceleration. And why in Vidia, of course is so 91 00:04:42,760 --> 00:04:45,599 Speaker 3: important when it comes to kind of gauging what inning 92 00:04:45,640 --> 00:04:48,479 Speaker 3: we're in is this is the brain that think of 93 00:04:48,520 --> 00:04:51,320 Speaker 3: the hardware piece, what in Vidia powers is the size 94 00:04:51,360 --> 00:04:55,000 Speaker 3: of the brain. And when you think about this accelerating 95 00:04:55,120 --> 00:04:58,120 Speaker 3: spend around the size of the brain, it makes me 96 00:04:58,160 --> 00:05:01,800 Speaker 3: more optimistic that the output, this is the critical piece, 97 00:05:02,360 --> 00:05:06,080 Speaker 3: the utility that brain will kick out eventually will be 98 00:05:06,279 --> 00:05:09,640 Speaker 3: more powerful, which makes me have higher confidence that were 99 00:05:09,680 --> 00:05:11,760 Speaker 3: earlier than what I thought at the beginning of the year. 100 00:05:12,480 --> 00:05:14,400 Speaker 1: I want to ask you Dan, where you think we 101 00:05:14,520 --> 00:05:16,840 Speaker 1: are in the AI race, and to talk a little 102 00:05:16,880 --> 00:05:19,920 Speaker 1: bit more about in Nvidia, because just in the last 103 00:05:19,960 --> 00:05:22,360 Speaker 1: few months, we've seen I think it's safe to say 104 00:05:22,480 --> 00:05:25,599 Speaker 1: quite a bit more at least chipping away or at 105 00:05:25,680 --> 00:05:29,520 Speaker 1: least attempts to at Nvidia's dominance. When you think about 106 00:05:30,200 --> 00:05:36,159 Speaker 1: Google's TPUs and this investment by open ai or by 107 00:05:36,360 --> 00:05:40,400 Speaker 1: Amazon into open Ai, with its potential competitor to the 108 00:05:40,520 --> 00:05:45,000 Speaker 1: Nvidia chip, does in Nvidia continue to keep this motor 109 00:05:45,040 --> 00:05:47,640 Speaker 1: around itself that it's had over the last couple of 110 00:05:47,720 --> 00:05:49,680 Speaker 1: years now in the AI chip space. 111 00:05:50,480 --> 00:05:52,719 Speaker 2: Look, I love what how Gene puts it with the 112 00:05:52,760 --> 00:05:55,200 Speaker 2: brain and the utility, because I think that's so true 113 00:05:55,800 --> 00:05:59,720 Speaker 2: in terms of where in Vidia. Please look, coming back 114 00:05:59,720 --> 00:06:03,400 Speaker 2: from me three weeks there demand the supplies twelve to 115 00:06:03,480 --> 00:06:06,960 Speaker 2: one for in video chips. The reality is Nathan like, 116 00:06:08,120 --> 00:06:11,000 Speaker 2: customers can't get enough that they have to go, whether 117 00:06:11,200 --> 00:06:14,800 Speaker 2: it's AMD, whether it's Google on TPU, whether it's others. 118 00:06:15,040 --> 00:06:17,800 Speaker 2: But that's not a bad thing. It speaks to our 119 00:06:17,920 --> 00:06:21,320 Speaker 2: view that like the lms are going to get cheaper. 120 00:06:21,640 --> 00:06:25,000 Speaker 2: You got more competition when it comes to AI chips, 121 00:06:25,720 --> 00:06:27,480 Speaker 2: but at the end of the day, in video continues 122 00:06:27,520 --> 00:06:30,159 Speaker 2: to be three to four years maybe, you know, like 123 00:06:30,279 --> 00:06:32,880 Speaker 2: in terms of a head of competition, and that's why 124 00:06:32,920 --> 00:06:35,120 Speaker 2: I think it's still a very cheap stock. Two fifty 125 00:06:35,240 --> 00:06:38,680 Speaker 2: two seventy five, you know, twenty twenty six is where 126 00:06:38,720 --> 00:06:40,560 Speaker 2: I see this stock playing out. 127 00:06:40,920 --> 00:06:43,520 Speaker 1: We're speaking with Dan Ives, global head of Tech Research 128 00:06:43,560 --> 00:06:47,200 Speaker 1: at web Bush Securities and deep Water Asset Management Managing 129 00:06:47,279 --> 00:06:51,479 Speaker 1: Director Gene Munster. Gene, that's a very interesting point that 130 00:06:51,560 --> 00:06:53,839 Speaker 1: Dan just made there. The idea of Nvidia being a 131 00:06:53,960 --> 00:06:57,880 Speaker 1: cheap stock because there has been all this discussion over 132 00:06:57,880 --> 00:07:02,279 Speaker 1: the last few months about the value of the Magnificent seven, 133 00:07:02,480 --> 00:07:05,760 Speaker 1: How do you view Nvidia's valuation right now along with 134 00:07:05,839 --> 00:07:09,920 Speaker 1: the rest of the mag seven? Are these still stocks 135 00:07:09,960 --> 00:07:13,480 Speaker 1: that can keep getting into these sky high valuations? 136 00:07:14,840 --> 00:07:16,480 Speaker 3: I mean Dan's doing the right thing. I mean he's 137 00:07:16,520 --> 00:07:21,160 Speaker 3: looking beyond the appreciation that we've had and asking the 138 00:07:21,280 --> 00:07:24,800 Speaker 3: question like what is on the come And ultimately that's 139 00:07:24,840 --> 00:07:27,760 Speaker 3: the question, the central question we all have to answer. 140 00:07:28,400 --> 00:07:31,080 Speaker 3: And I think when we get to the question about 141 00:07:31,320 --> 00:07:35,240 Speaker 3: like valuation and where this market potentially go, it can 142 00:07:35,320 --> 00:07:38,840 Speaker 3: boil down to something as simple as your just your 143 00:07:38,960 --> 00:07:42,040 Speaker 3: view on how the utility of AI will play out. 144 00:07:42,120 --> 00:07:45,840 Speaker 3: So if you take the perspective that we've had a 145 00:07:45,840 --> 00:07:48,160 Speaker 3: good run and that AI is going to be impactful, 146 00:07:48,160 --> 00:07:50,680 Speaker 3: but it's not going to be a total game changer, 147 00:07:50,760 --> 00:07:53,600 Speaker 3: it's not going to exceed the high expectations that are 148 00:07:53,600 --> 00:07:55,080 Speaker 3: out there in terms of how it's going to impact 149 00:07:55,080 --> 00:07:57,800 Speaker 3: the world. If you take that approach, there's little that 150 00:07:58,320 --> 00:08:00,600 Speaker 3: I think anybody could say that is to get you 151 00:08:00,680 --> 00:08:04,200 Speaker 3: optimistic about where this is ultimately going to go. If 152 00:08:04,200 --> 00:08:07,560 Speaker 3: you're in the camp where you believe that these companies 153 00:08:08,160 --> 00:08:11,000 Speaker 3: you know, Dan mentioned Comes like Palenteer. You think about 154 00:08:11,280 --> 00:08:13,400 Speaker 3: some of the MAG seven, some of the small caps 155 00:08:13,440 --> 00:08:17,560 Speaker 3: as well. If you believe that ultimately that that we're 156 00:08:17,600 --> 00:08:22,440 Speaker 3: still early, therefore their their valuations are are going to 157 00:08:23,120 --> 00:08:24,840 Speaker 3: be lower in the future because they're going to have 158 00:08:24,920 --> 00:08:29,000 Speaker 3: faster earnings growth. And so that's I mean, is I mean, 159 00:08:29,000 --> 00:08:32,959 Speaker 3: that's effectively what we're faced with is this question about 160 00:08:33,760 --> 00:08:36,439 Speaker 3: the degree the pace of this and how it impacts. 161 00:08:36,440 --> 00:08:38,440 Speaker 3: If you look at NATA, just the numbers, like let's 162 00:08:38,480 --> 00:08:40,360 Speaker 3: let's forget about that and forget about where we're going 163 00:08:40,400 --> 00:08:42,680 Speaker 3: and just look at where the stocks are. They are 164 00:08:42,720 --> 00:08:46,280 Speaker 3: trading higher than a normal if you look at, for example, 165 00:08:46,320 --> 00:08:49,320 Speaker 3: the MAG seven kind of over the next twelve months 166 00:08:49,320 --> 00:08:53,880 Speaker 3: trading around a twenty seven times multiple excluding Tesla, that's 167 00:08:54,000 --> 00:08:55,240 Speaker 3: as a. 168 00:08:54,880 --> 00:08:56,200 Speaker 2: One hundred plus multiple. 169 00:08:56,720 --> 00:09:00,600 Speaker 3: But so they are higher, but it's not like easy high. 170 00:09:00,840 --> 00:09:05,240 Speaker 3: As a reminder, back in two thousand, the Nasdaq was 171 00:09:05,280 --> 00:09:08,840 Speaker 3: trained at one hundred times next twelve months. Now, the 172 00:09:09,000 --> 00:09:12,160 Speaker 3: dynamic of the market's different today because these megacaps were 173 00:09:12,160 --> 00:09:15,480 Speaker 3: not going to ever unlikely we'll ever see that hundred x. 174 00:09:16,000 --> 00:09:19,960 Speaker 3: But I think it's reasonable that a twenty seven x 175 00:09:20,040 --> 00:09:24,280 Speaker 3: on what potentially could be multiple years of fifteen twenty 176 00:09:24,280 --> 00:09:25,680 Speaker 3: percent growth is positive. 177 00:09:26,559 --> 00:09:29,200 Speaker 1: Dan, how do you answer some of the critics who 178 00:09:29,679 --> 00:09:33,559 Speaker 1: point out a lot of these companies, you know, spending 179 00:09:33,679 --> 00:09:39,840 Speaker 1: hundreds of billions of dollars into this technology that is 180 00:09:40,040 --> 00:09:45,439 Speaker 1: then getting you know, more circularly invested into the companies themselves. 181 00:09:45,440 --> 00:09:48,600 Speaker 1: The idea that you know, open Ai and others are 182 00:09:49,160 --> 00:09:52,080 Speaker 1: getting all this investment from companies that are going to 183 00:09:52,120 --> 00:09:56,040 Speaker 1: be benefiting from their business, like the hyperscalers. 184 00:09:57,160 --> 00:09:59,280 Speaker 2: Yeah, but I would say, and G and I have 185 00:09:59,360 --> 00:10:02,800 Speaker 2: talked about a bunge. I don't view this like a 186 00:10:02,920 --> 00:10:06,280 Speaker 2: vendor financing circular financing late nineties that we both saw. 187 00:10:06,360 --> 00:10:10,319 Speaker 2: I mean, my view is open Ai for every dour 188 00:10:10,440 --> 00:10:14,880 Speaker 2: that they invest, every dour and video vest, they're getting ten, twelve, 189 00:10:14,960 --> 00:10:18,080 Speaker 2: fifteen dollars back over the course of the next five 190 00:10:18,200 --> 00:10:21,120 Speaker 2: ten years. And that's a bet that they'll meet because look, 191 00:10:21,520 --> 00:10:24,679 Speaker 2: they're building out a new economy for consumers and new 192 00:10:24,720 --> 00:10:28,160 Speaker 2: economy for enterprises. So I don't view it as sinister 193 00:10:28,400 --> 00:10:33,920 Speaker 2: red flag the circular financing concept to some extent, I 194 00:10:34,040 --> 00:10:36,720 Speaker 2: view it as you want to be associated with open Ai, 195 00:10:37,559 --> 00:10:40,280 Speaker 2: not away from them. And even though right now those 196 00:10:40,320 --> 00:10:43,680 Speaker 2: stocks are you know, really have a huge sort of 197 00:10:43,720 --> 00:10:48,440 Speaker 2: black cloud over them. It's like is it bad. No, 198 00:10:48,800 --> 00:10:51,000 Speaker 2: it's actually good because they are at the epicenter of 199 00:10:51,000 --> 00:10:51,960 Speaker 2: this AI build out. 200 00:10:52,800 --> 00:10:56,840 Speaker 1: Is it important, though, Gene, for open Ai to turn 201 00:10:56,880 --> 00:11:00,760 Speaker 1: a profit in twenty twenty six to justify all this spend. 202 00:11:01,840 --> 00:11:04,080 Speaker 3: No, it has I mean, this is the beauty of 203 00:11:04,160 --> 00:11:07,960 Speaker 3: everything that's going on is that you have very rational 204 00:11:08,000 --> 00:11:11,160 Speaker 3: people that say profit is important, and there's other rational 205 00:11:11,160 --> 00:11:13,840 Speaker 3: people that say it's just about building the framework. And 206 00:11:13,920 --> 00:11:17,640 Speaker 3: so the key question about this cash burn with opening 207 00:11:17,720 --> 00:11:21,000 Speaker 3: and we can talk about the rumor around this eight 208 00:11:21,080 --> 00:11:23,800 Speaker 3: hundred and thirty billion dollars round that's rumored to be 209 00:11:23,840 --> 00:11:28,480 Speaker 3: going on, but the key question ultimately is eventually call 210 00:11:28,520 --> 00:11:31,200 Speaker 3: it twenty thirty, can they be profitable? And part of 211 00:11:31,240 --> 00:11:33,960 Speaker 3: that is to dance point like can they continue to 212 00:11:34,480 --> 00:11:40,679 Speaker 3: raise money to fund this impressive expansion and impressive expansion 213 00:11:40,679 --> 00:11:42,160 Speaker 3: I just want to put some numbers around it. It's 214 00:11:42,160 --> 00:11:45,600 Speaker 3: one hundred percent growth expected next year, in the year 215 00:11:45,640 --> 00:11:47,400 Speaker 3: after and the year after for the next three years. 216 00:11:47,840 --> 00:11:50,920 Speaker 3: And so I think that when you think about the 217 00:11:50,920 --> 00:11:54,000 Speaker 3: profitability question when it comes to Opening Eye, like that 218 00:11:54,000 --> 00:11:56,920 Speaker 3: that really doesn't matter. What matters is do they ultimately 219 00:11:57,000 --> 00:12:00,680 Speaker 3: can they get enough financing? Can they raise enough equity 220 00:12:01,440 --> 00:12:03,439 Speaker 3: to the tune of about one hundred to one hundred 221 00:12:03,440 --> 00:12:06,480 Speaker 3: and fifty billion of the next three years to continue 222 00:12:06,480 --> 00:12:09,360 Speaker 3: to build out to get to that profitability piece in 223 00:12:09,360 --> 00:12:11,760 Speaker 3: twenty thirty And I think the answer is overwhelmingly yes. 224 00:12:11,760 --> 00:12:15,600 Speaker 3: It's just too big of a prize. And you know, 225 00:12:15,720 --> 00:12:17,280 Speaker 3: Dan and I are well ware what's going on in 226 00:12:17,320 --> 00:12:21,120 Speaker 3: the private markets. There's just a ton of investor demand 227 00:12:21,679 --> 00:12:24,320 Speaker 3: to participate in this, and so they're going to be 228 00:12:24,320 --> 00:12:27,959 Speaker 3: able to have the money to power through this cash 229 00:12:27,960 --> 00:12:29,640 Speaker 3: burn that they're going to have for the next few years. 230 00:12:29,800 --> 00:12:32,640 Speaker 1: We're going to continue this conversation take an even closer 231 00:12:32,640 --> 00:12:36,560 Speaker 1: look at the Magnificent seven stocks as this special New 232 00:12:36,640 --> 00:12:41,560 Speaker 1: Year's Day Tech Hour continues with Gene Munster, Managing Partner, 233 00:12:41,600 --> 00:12:45,960 Speaker 1: Deepwater Asset Management and Webbush Securities Global Head of Tech Research, 234 00:12:46,120 --> 00:12:49,679 Speaker 1: Dan Ives on the special edition of Bloomberg Daybreak for 235 00:12:49,920 --> 00:12:54,080 Speaker 1: the New Year. I'm Nathan Hager, and this is Bloomberg. 236 00:13:04,760 --> 00:13:07,840 Speaker 1: Welcome back to the special New Year's edition of Bloomberg Daybreak. 237 00:13:07,840 --> 00:13:10,600 Speaker 1: I'm Nathan Hager, and even though markets are closed. On 238 00:13:10,600 --> 00:13:12,640 Speaker 1: this first day of twenty twenty six, we got a 239 00:13:12,679 --> 00:13:15,880 Speaker 1: high tech power Hour going. We're speaking with Dan Ives, 240 00:13:15,960 --> 00:13:18,720 Speaker 1: global head of Tech Research at wet Bush Securities and 241 00:13:18,800 --> 00:13:22,840 Speaker 1: Gene Monster, managing partner at Deepwater Asset Management. Dan, let's 242 00:13:22,840 --> 00:13:24,640 Speaker 1: pick up where we left off in the last segment 243 00:13:24,679 --> 00:13:27,840 Speaker 1: talking about some of the valuations, some of the financing 244 00:13:27,880 --> 00:13:32,400 Speaker 1: that's going into these startups that are possibly getting into 245 00:13:32,640 --> 00:13:36,200 Speaker 1: really really big valuations like open Ai. Do you see 246 00:13:36,320 --> 00:13:39,720 Speaker 1: that continuing when you know there is still so much 247 00:13:39,760 --> 00:13:43,199 Speaker 1: competition along among some of these large language models that 248 00:13:43,240 --> 00:13:44,320 Speaker 1: are competing with open Ai. 249 00:13:44,679 --> 00:13:48,360 Speaker 2: Look, I'm not saying that you won't have a bubble 250 00:13:48,480 --> 00:13:51,720 Speaker 2: or maybe frof in ensuring the areas of the market 251 00:13:51,760 --> 00:13:56,520 Speaker 2: over the next twelve eighty months. But to look at 252 00:13:55,840 --> 00:14:00,640 Speaker 2: the core winners and to say that they're expensive and 253 00:14:00,760 --> 00:14:03,400 Speaker 2: just kind of painted with a brush, I think's the 254 00:14:03,440 --> 00:14:05,400 Speaker 2: wrong way to view it. Because my view is like, look, 255 00:14:05,440 --> 00:14:07,720 Speaker 2: I have three to four trillion being spent next few 256 00:14:07,800 --> 00:14:10,560 Speaker 2: years in terms of the build out to ripple effect. 257 00:14:10,600 --> 00:14:13,040 Speaker 2: Every dollar spent on videoship, there's an eight ten dollars 258 00:14:13,080 --> 00:14:16,480 Speaker 2: multiply across the rest of the tech. So investors like 259 00:14:16,920 --> 00:14:20,240 Speaker 2: they're looking non next one two years, they're looking beyond 260 00:14:20,320 --> 00:14:23,080 Speaker 2: that to understand who the core winners are and will 261 00:14:23,120 --> 00:14:26,040 Speaker 2: they grow into valuations. I mean it goes back to like, 262 00:14:26,640 --> 00:14:28,360 Speaker 2: you know, if you go back to some of the 263 00:14:28,400 --> 00:14:32,800 Speaker 2: Amazon days, some of Meta somewhere in video was twenty 264 00:14:32,880 --> 00:14:35,600 Speaker 2: twenty one two down twenty two, you know. I think 265 00:14:35,680 --> 00:14:38,160 Speaker 2: that sort of the view in terms of this transformation 266 00:14:39,120 --> 00:14:43,360 Speaker 2: that we continue to believe, like you only have three 267 00:14:43,400 --> 00:14:45,480 Speaker 2: percent of companies in the US that have fully gone 268 00:14:45,520 --> 00:14:48,920 Speaker 2: down the AI path, and for the first time globally 269 00:14:49,480 --> 00:14:51,840 Speaker 2: in thirty years, the US is headed China when it 270 00:14:51,880 --> 00:14:52,520 Speaker 2: comes to tech. 271 00:14:52,800 --> 00:14:55,360 Speaker 1: I think I heard Dan talk about the idea of 272 00:14:55,400 --> 00:14:59,600 Speaker 1: winners and losers here in the large language models. Gane, 273 00:14:59,640 --> 00:15:03,120 Speaker 1: how are you thinking about winners and losers right now 274 00:15:03,160 --> 00:15:03,840 Speaker 1: in that space? 275 00:15:04,320 --> 00:15:08,280 Speaker 3: Well, I think that there's basically four or five depending 276 00:15:08,320 --> 00:15:12,360 Speaker 3: how you count Meta as the large language models, and 277 00:15:12,440 --> 00:15:16,960 Speaker 3: I think that when there's this let me just take 278 00:15:17,000 --> 00:15:21,480 Speaker 3: a step back, is there is a view that ultimately 279 00:15:21,520 --> 00:15:24,800 Speaker 3: it's a race to the bottom, that these companies are 280 00:15:24,840 --> 00:15:29,680 Speaker 3: creating intelligence and therefore they will that the pricing is 281 00:15:29,720 --> 00:15:31,280 Speaker 3: going to go down to a level where we're going 282 00:15:31,320 --> 00:15:34,000 Speaker 3: to have five losers. Essentially, they're going to spend all 283 00:15:34,040 --> 00:15:38,400 Speaker 3: this money. And our belief is that actually what you'll 284 00:15:38,440 --> 00:15:41,640 Speaker 3: see is even though the pricing will come down, the 285 00:15:41,840 --> 00:15:46,040 Speaker 3: value will increase to a point where the pricing. This 286 00:15:46,240 --> 00:15:48,960 Speaker 3: gets back to this Gevins paradox that's been talked about 287 00:15:49,000 --> 00:15:52,560 Speaker 3: for the past year or so, that yes, pricing comes down, 288 00:15:52,560 --> 00:15:55,640 Speaker 3: but the value increases. Therefore, the usage increases that more 289 00:15:55,680 --> 00:15:59,640 Speaker 3: than offsets that decline in pricing. And so I think 290 00:15:59,680 --> 00:16:03,920 Speaker 3: that all these two different degrees are going to be winners. 291 00:16:04,520 --> 00:16:07,160 Speaker 3: One piece that is kind of like below the surface 292 00:16:07,200 --> 00:16:09,760 Speaker 3: that doesn't get talked about as much as the personalities 293 00:16:09,800 --> 00:16:12,080 Speaker 3: of the models, and the way we think about it 294 00:16:12,120 --> 00:16:16,080 Speaker 3: is the world isn't doesn't run on one personality, and 295 00:16:16,080 --> 00:16:18,720 Speaker 3: that's what these models are. They have personalities. You ask 296 00:16:18,880 --> 00:16:22,760 Speaker 3: one model, you ask five different models, five different questions, 297 00:16:22,760 --> 00:16:25,320 Speaker 3: and you get slightly different answers. And so I think 298 00:16:25,320 --> 00:16:28,240 Speaker 3: that there is something to be said about This isn't 299 00:16:28,280 --> 00:16:32,040 Speaker 3: a political statement, but some models lean right, some models 300 00:16:32,440 --> 00:16:35,560 Speaker 3: lean left. Organizations are going to want to build on 301 00:16:35,640 --> 00:16:39,880 Speaker 3: top of models that align more with their personality, and 302 00:16:39,920 --> 00:16:43,119 Speaker 3: so I think that that is going to create an opportunity. 303 00:16:43,160 --> 00:16:45,720 Speaker 3: It's probably you're probably going to see a couple on 304 00:16:45,760 --> 00:16:48,800 Speaker 3: the right and a couple on the left, and so 305 00:16:49,000 --> 00:16:51,040 Speaker 3: it's hard really at this point to say, you know 306 00:16:51,080 --> 00:16:53,520 Speaker 3: which one is the losers. I think I look at 307 00:16:53,560 --> 00:16:57,320 Speaker 3: it more of the conversation about them all being losers, 308 00:16:57,400 --> 00:17:00,120 Speaker 3: about this race to the bottom misses the fun a 309 00:17:00,120 --> 00:17:03,880 Speaker 3: mental point, which is, as value comes from the intelligence, 310 00:17:03,960 --> 00:17:06,520 Speaker 3: people will pay out for it. I realized that that 311 00:17:06,520 --> 00:17:09,719 Speaker 3: that is a bold statement, but I think that's the 312 00:17:09,760 --> 00:17:12,639 Speaker 3: piece that is missing in terms of how these companies 313 00:17:12,720 --> 00:17:16,480 Speaker 3: continue to how Opening Eye, for example, can be a 314 00:17:16,560 --> 00:17:17,800 Speaker 3: choin and a half dollar company. 315 00:17:18,080 --> 00:17:20,280 Speaker 1: Well that's a really interesting idea, And I wonder Dan 316 00:17:20,320 --> 00:17:22,480 Speaker 1: if that's something that you've thought about as well, whether 317 00:17:22,560 --> 00:17:26,240 Speaker 1: there could be a scenario where companies are using multiple 318 00:17:26,320 --> 00:17:30,280 Speaker 1: large language models as opposed to settling on just one look. 319 00:17:30,359 --> 00:17:34,679 Speaker 2: I think what Ginge just said there is gold, because that, 320 00:17:35,640 --> 00:17:40,280 Speaker 2: to me, that summarizes the whole the crux of everything 321 00:17:40,320 --> 00:17:44,520 Speaker 2: we're seeing in terms of this AI build out, Winners, losers. 322 00:17:45,000 --> 00:17:47,600 Speaker 2: You could pick your open A, I pick your Gemini. 323 00:17:48,080 --> 00:17:51,159 Speaker 2: Pick you know whether even in China some of the 324 00:17:51,160 --> 00:17:52,920 Speaker 2: models there. To me, it's all going to be about 325 00:17:53,000 --> 00:17:56,680 Speaker 2: hyperscalers and the data that it's built on. That continues 326 00:17:56,720 --> 00:18:00,240 Speaker 2: to be such a core piece of this AI, which 327 00:18:00,280 --> 00:18:03,800 Speaker 2: when you do about the hyperscoalurs and the infrastructure, it's 328 00:18:03,800 --> 00:18:06,040 Speaker 2: about the data the infrastructure to build out. 329 00:18:06,160 --> 00:18:08,680 Speaker 1: I want to talk about the theme that has really 330 00:18:08,800 --> 00:18:10,880 Speaker 1: driven this market for the last few years, of course, 331 00:18:10,920 --> 00:18:13,400 Speaker 1: that is the Magnificent seven, and take a look at 332 00:18:13,440 --> 00:18:17,960 Speaker 1: where those stocks in particular could go in the next year. Gene, 333 00:18:17,960 --> 00:18:21,520 Speaker 1: do you see the mag seven continuing to drive the 334 00:18:21,640 --> 00:18:25,400 Speaker 1: rally all boats lifted together in that space? 335 00:18:25,720 --> 00:18:28,600 Speaker 3: I do think simple answer is no. I think that 336 00:18:28,680 --> 00:18:31,119 Speaker 3: we're going to see some pockets. Some of them are 337 00:18:31,160 --> 00:18:34,399 Speaker 3: going to outperform really well, and some of them won't 338 00:18:34,440 --> 00:18:38,239 Speaker 3: perform as much. I mean, my sense is that the 339 00:18:38,280 --> 00:18:40,920 Speaker 3: small cap piece is going to continue to be an 340 00:18:40,960 --> 00:18:44,400 Speaker 3: important part. I want to be clear that I think 341 00:18:44,440 --> 00:18:47,280 Speaker 3: you should own many of the mag seven. I think 342 00:18:47,280 --> 00:18:50,560 Speaker 3: that they're going to continue to generate a better return 343 00:18:50,600 --> 00:18:53,600 Speaker 3: than just being in the queues, for example. But I 344 00:18:53,640 --> 00:18:56,119 Speaker 3: think that there is a little bit of a dynamic 345 00:18:57,280 --> 00:18:59,520 Speaker 3: when it comes to the mag seven, the two that 346 00:18:59,640 --> 00:19:02,680 Speaker 3: I'm focus most on. This wasn't your question, but I 347 00:19:02,760 --> 00:19:03,760 Speaker 3: do want to Highlight. 348 00:19:03,800 --> 00:19:04,440 Speaker 2: This is sure. 349 00:19:04,480 --> 00:19:06,480 Speaker 3: I'm kind of split in airs here in terms of 350 00:19:06,520 --> 00:19:08,720 Speaker 3: how to think about the winners in the MAGS seven 351 00:19:08,800 --> 00:19:12,000 Speaker 3: four for calendar twenty six. I think Apple I'm putting 352 00:19:12,000 --> 00:19:14,720 Speaker 3: that as the top performer for the front half of 353 00:19:14,720 --> 00:19:16,800 Speaker 3: the year just because I think there's going to be 354 00:19:16,880 --> 00:19:19,440 Speaker 3: multiple expansion going into the new series, which is code 355 00:19:19,520 --> 00:19:23,359 Speaker 3: named for the new Apple Intelligence, and they land that 356 00:19:23,560 --> 00:19:28,280 Speaker 3: after being i think more or less viscerated over what's 357 00:19:28,280 --> 00:19:31,320 Speaker 3: happened so far with AI, they land that the multiple 358 00:19:31,320 --> 00:19:32,840 Speaker 3: on Apple is likely going up. So I think that 359 00:19:32,920 --> 00:19:35,840 Speaker 3: Apple's going to have be the best performing MAG seven 360 00:19:36,840 --> 00:19:38,280 Speaker 3: through the first half of the year, and then if 361 00:19:38,280 --> 00:19:41,680 Speaker 3: you look at the full year, I think Google is 362 00:19:41,680 --> 00:19:44,360 Speaker 3: in a unique place just given you know, they're really 363 00:19:44,359 --> 00:19:49,560 Speaker 3: doing a great job of taking this the search traffic 364 00:19:49,600 --> 00:19:52,520 Speaker 3: and starting to find ways to get people to interact 365 00:19:52,560 --> 00:19:55,159 Speaker 3: with their products more, which obviously more shots on that. 366 00:19:55,280 --> 00:19:58,679 Speaker 3: It's good for the revenue growth within search, and of 367 00:19:58,680 --> 00:20:01,399 Speaker 3: course they've got their cloud, and so those are the 368 00:20:01,440 --> 00:20:05,320 Speaker 3: two that I would focus on most. Again, I'm not 369 00:20:05,720 --> 00:20:07,640 Speaker 3: it doesn't mean that the other ones won't do well, 370 00:20:07,680 --> 00:20:08,959 Speaker 3: but I think those are the ones that will do 371 00:20:09,000 --> 00:20:09,399 Speaker 3: the best. 372 00:20:09,680 --> 00:20:11,639 Speaker 1: Dan what are you looking at in the mag seven? 373 00:20:12,280 --> 00:20:14,560 Speaker 1: Do you see winners and losers in there? 374 00:20:14,880 --> 00:20:18,320 Speaker 2: I mean Gene preaching to the quiet, like what did 375 00:20:18,359 --> 00:20:21,320 Speaker 2: he say about Apple? And Look, and it's been a 376 00:20:21,359 --> 00:20:24,639 Speaker 2: battle because they've essentially been invisible with the AI strategy. 377 00:20:24,680 --> 00:20:28,639 Speaker 2: But now with Google when the DOJ, that queers a 378 00:20:28,720 --> 00:20:31,879 Speaker 2: path for a bigger geminideal that comes out in the spring. 379 00:20:32,440 --> 00:20:37,399 Speaker 2: And I think there's no multiple for Apple given because 380 00:20:37,440 --> 00:20:39,760 Speaker 2: of AI with the biggest install based in the world, 381 00:20:39,760 --> 00:20:42,160 Speaker 2: I could already add seventy five hundred hours to share. 382 00:20:42,680 --> 00:20:45,679 Speaker 2: So I think I agree one hundred percent. And me 383 00:20:45,760 --> 00:20:48,879 Speaker 2: and Gene it's a very small Apple fan club. You 384 00:20:48,920 --> 00:20:52,280 Speaker 2: stick together there, okay, all right? And then and then 385 00:20:52,320 --> 00:20:55,760 Speaker 2: i'd also I agree with Google, but I think Microsoft, Look, 386 00:20:55,800 --> 00:21:00,639 Speaker 2: I think Microsoft here is so over sold. Just feel 387 00:21:00,640 --> 00:21:03,280 Speaker 2: like best is in the rear view mirror. It's now 388 00:21:03,359 --> 00:21:06,679 Speaker 2: about Google, Amazon, They're in the enterprise, the enterprise market 389 00:21:06,760 --> 00:21:09,280 Speaker 2: it's in that's Redmond's do me and I'm telling you, 390 00:21:09,359 --> 00:21:12,240 Speaker 2: like to me, that's the one that I focused on. 391 00:21:12,280 --> 00:21:13,720 Speaker 2: It just a table pounder here. 392 00:21:13,920 --> 00:21:16,800 Speaker 1: Interesting because it does seem like there is a pretty 393 00:21:16,840 --> 00:21:21,040 Speaker 1: more heated competition in the cloud space as well, Gene, 394 00:21:21,040 --> 00:21:22,879 Speaker 1: how are you looking at that? When it comes to 395 00:21:22,920 --> 00:21:28,320 Speaker 1: the competition between Microsoft, Azure, Google Cloud, and Amazon Web Services, 396 00:21:28,720 --> 00:21:29,560 Speaker 1: I think the bar. 397 00:21:29,520 --> 00:21:33,440 Speaker 3: Is lowest with AWS just because the growth has been lowest, 398 00:21:33,520 --> 00:21:36,000 Speaker 3: and you know, they just haven't seen that breath taking 399 00:21:36,080 --> 00:21:39,119 Speaker 3: into the thirty almost forty percent growth that Azure and 400 00:21:39,200 --> 00:21:43,080 Speaker 3: Google have experienced more recently off of a bigger number 401 00:21:43,160 --> 00:21:45,719 Speaker 3: because their market shares more so, it's it's harder to 402 00:21:45,880 --> 00:21:49,240 Speaker 3: grow at those rates. But I think that I mean, 403 00:21:49,400 --> 00:21:53,439 Speaker 3: this is, uh, you know, not the cleanest answer, but 404 00:21:53,440 --> 00:21:55,120 Speaker 3: I think all of them are going to do well. 405 00:21:55,200 --> 00:21:57,080 Speaker 3: I think if you go back to kind of where 406 00:21:57,160 --> 00:21:58,879 Speaker 3: Dan and I are at in terms of just the 407 00:21:58,920 --> 00:22:03,119 Speaker 3: broader build out that's going on, if if that in 408 00:22:03,160 --> 00:22:05,560 Speaker 3: fact does happen, all of them are going to benefit 409 00:22:05,600 --> 00:22:09,520 Speaker 3: the one. There's a contrarion piece in me that wants 410 00:22:09,640 --> 00:22:11,919 Speaker 3: I like what Dan saying about Microsoft. I agree that 411 00:22:11,920 --> 00:22:14,679 Speaker 3: that's definitely it's a contrarian on the top pick. Therefore 412 00:22:14,680 --> 00:22:19,159 Speaker 3: it probably happens. But the contri piece around AWS is 413 00:22:19,200 --> 00:22:22,320 Speaker 3: that that they end up being kind of the surprise 414 00:22:22,320 --> 00:22:25,359 Speaker 3: to go back to, uh, they had their AWS event. 415 00:22:25,400 --> 00:22:29,720 Speaker 3: The CEO of AWS said that they may even have 416 00:22:29,760 --> 00:22:32,320 Speaker 3: the exact his exact quota. I was just looking up 417 00:22:32,400 --> 00:22:36,040 Speaker 3: this morning on December fourth. This is Matt Garman. He said, 418 00:22:36,040 --> 00:22:41,080 Speaker 3: demand keeps skyrocketing or only speeding up that infrastructure build out, 419 00:22:41,680 --> 00:22:45,760 Speaker 3: so uh, you know, halfway through the quarter, three quarters, 420 00:22:45,760 --> 00:22:47,400 Speaker 3: two thirds of the way through the quarter. He says 421 00:22:47,400 --> 00:22:49,879 Speaker 3: that it's probably a good sign for ws D. 422 00:22:49,920 --> 00:22:53,239 Speaker 2: And your reaction to that, I mean, look, I agree, 423 00:22:54,520 --> 00:22:59,040 Speaker 2: and I'd almost further and say, I think one of 424 00:22:59,040 --> 00:23:03,119 Speaker 2: the biggest surprise as we go into twenty six, I 425 00:23:03,160 --> 00:23:06,879 Speaker 2: think it's going to start off with Jensen's keener at CEES, 426 00:23:08,040 --> 00:23:11,639 Speaker 2: you know, which will be at is just about the overall 427 00:23:11,800 --> 00:23:15,680 Speaker 2: demand that's accelerating across the whole universe. And I think 428 00:23:16,280 --> 00:23:20,919 Speaker 2: that's something where investors, I think are underestimating the scale 429 00:23:20,920 --> 00:23:22,879 Speaker 2: and scope of what this is going to look like 430 00:23:23,920 --> 00:23:26,159 Speaker 2: and also going to have a huge impact not just 431 00:23:26,200 --> 00:23:30,240 Speaker 2: on earnings, but I think even on increased capbacks and 432 00:23:30,320 --> 00:23:33,960 Speaker 2: on accelerate monization of the AI theme going in twenty 433 00:23:34,040 --> 00:23:35,560 Speaker 2: twenty six, Gene. 434 00:23:35,280 --> 00:23:38,600 Speaker 1: Are these hyperscalers going to have to continue to find 435 00:23:38,600 --> 00:23:42,800 Speaker 1: ways to cut costs to keep up the hundreds of 436 00:23:42,800 --> 00:23:45,879 Speaker 1: billions of dollars they're spending on AI. 437 00:23:46,640 --> 00:23:49,000 Speaker 3: Well, I think if I think they will try to 438 00:23:49,040 --> 00:23:51,520 Speaker 3: continue to cut costs, a lot of it is because 439 00:23:51,560 --> 00:23:56,360 Speaker 3: they're they're they're using, they're eating their own products, they're 440 00:23:56,760 --> 00:23:59,680 Speaker 3: implementing more. Think about how much they're using, whether it's 441 00:23:59,720 --> 00:24:02,400 Speaker 3: micro Soft to Meta and Google. In terms of code 442 00:24:02,400 --> 00:24:06,200 Speaker 3: creation today something like more than half is now generated 443 00:24:06,240 --> 00:24:09,879 Speaker 3: by machines. So but you know, do they have to 444 00:24:09,880 --> 00:24:13,040 Speaker 3: to grow this if you just some really high level 445 00:24:13,080 --> 00:24:16,400 Speaker 3: math here, but think about the average mag seven excluding 446 00:24:16,400 --> 00:24:19,920 Speaker 3: teslas generating about one hundred billion per year in free 447 00:24:19,920 --> 00:24:25,640 Speaker 3: cash flow, and so they're spending call it you know, 448 00:24:26,560 --> 00:24:30,200 Speaker 3: that's by the way, that one hundred billion includes them 449 00:24:30,240 --> 00:24:34,239 Speaker 3: spending fifty seventy five billion a year on infrastructure, and 450 00:24:34,280 --> 00:24:39,320 Speaker 3: so they can increase by twenty thirty percent and still 451 00:24:39,359 --> 00:24:43,840 Speaker 3: be bringing home fifty seventy five billion dollars. And so 452 00:24:43,880 --> 00:24:45,840 Speaker 3: they're a long way away. And that's I think one 453 00:24:45,880 --> 00:24:48,600 Speaker 3: of the big differences that we're experiencing today versus twenty 454 00:24:48,680 --> 00:24:53,119 Speaker 3: five years ago is the cash flow generation. They can 455 00:24:53,240 --> 00:24:58,159 Speaker 3: just keep feeding this machine and so inevitably investors do 456 00:24:58,320 --> 00:25:01,040 Speaker 3: care in the near term about earnings. Look what happened 457 00:25:01,040 --> 00:25:04,600 Speaker 3: with Meta. Meta just said after their September quarter that 458 00:25:05,240 --> 00:25:08,240 Speaker 3: next year the expenses were going to grow faster than revenue. 459 00:25:08,240 --> 00:25:11,199 Speaker 3: They have very upbeat commentary about revenue and the stock 460 00:25:11,840 --> 00:25:14,359 Speaker 3: I forget what it was down fifteen to twenty percent 461 00:25:14,480 --> 00:25:18,439 Speaker 3: over a short period, and so they do care in 462 00:25:18,480 --> 00:25:20,960 Speaker 3: the near term. But the reason why I stress that 463 00:25:21,000 --> 00:25:24,680 Speaker 3: near term, I think the long term investors will have 464 00:25:24,760 --> 00:25:28,760 Speaker 3: a sense like this money is going to good use. 465 00:25:29,080 --> 00:25:32,879 Speaker 3: And even if they're and they've got plenty of money, 466 00:25:32,920 --> 00:25:35,960 Speaker 3: to continue to invest in the business. And most importantly 467 00:25:35,960 --> 00:25:38,399 Speaker 3: that's the right thing for them to do, because if 468 00:25:38,440 --> 00:25:41,880 Speaker 3: they don't make those investments, obviously it poses them at 469 00:25:41,920 --> 00:25:44,600 Speaker 3: some bigger existential risk longer term. 470 00:25:44,720 --> 00:25:46,880 Speaker 1: We're going to keep this conversation going on the Mag 471 00:25:46,960 --> 00:25:50,040 Speaker 1: seven and more of the big tech sector as we 472 00:25:50,160 --> 00:25:54,920 Speaker 1: continue this special New Year's Day edition of Bloomberg Daybreak 473 00:25:54,920 --> 00:25:57,240 Speaker 1: with a look at another big piece of the Mag 474 00:25:57,359 --> 00:26:01,879 Speaker 1: seven that would be the Tesla coming up. I'm Nathan Hager, 475 00:26:02,040 --> 00:26:14,800 Speaker 1: and this is Bloomer. Thanks again for being with us 476 00:26:14,840 --> 00:26:17,880 Speaker 1: for this special edition of Bloomberg Daybreak. Markets are closed 477 00:26:17,880 --> 00:26:20,720 Speaker 1: for the New Year's Day holiday. I'm Nathan Hager. Wrapping 478 00:26:20,800 --> 00:26:23,600 Speaker 1: up our special high tech roundtable. We have been spending 479 00:26:23,600 --> 00:26:26,160 Speaker 1: the full hour with Dan Ives, global head of tech 480 00:26:26,200 --> 00:26:30,360 Speaker 1: research at Webbush Securities and Deepwater Asset Management's managing partner, 481 00:26:30,760 --> 00:26:34,000 Speaker 1: Gene Monster. We could keep this conversation going for the 482 00:26:34,200 --> 00:26:37,400 Speaker 1: entire day, but we got to wrap this up. Starting off, 483 00:26:37,480 --> 00:26:40,119 Speaker 1: guys with a stock that I know both of you 484 00:26:40,280 --> 00:26:44,280 Speaker 1: follow very closely. That would be Tesla. Both of you 485 00:26:44,280 --> 00:26:47,639 Speaker 1: have made some pretty bold calls on the electric vehicle maker, 486 00:26:47,880 --> 00:26:52,439 Speaker 1: but does it continue to be driven by the evs 487 00:26:52,800 --> 00:26:54,840 Speaker 1: headed into twenty twenty six, Dan. 488 00:26:55,200 --> 00:26:57,080 Speaker 2: I first off just want to say, I mean I 489 00:26:57,080 --> 00:27:00,120 Speaker 2: could listen to Gene I've had some sour pats, kids 490 00:27:00,119 --> 00:27:05,200 Speaker 2: and media tabernet, I costendim talk tech the whole day. Yes. 491 00:27:05,359 --> 00:27:09,960 Speaker 2: Now then now with that said, look Tesla, they're entering 492 00:27:10,040 --> 00:27:15,679 Speaker 2: the most important year ever autonomous and robotics, weave thirty cities, 493 00:27:15,760 --> 00:27:20,440 Speaker 2: web robotaxis, you know, in twenty twenty six, and this 494 00:27:20,880 --> 00:27:23,800 Speaker 2: is the year AI revolution comes to Tesla. And I 495 00:27:23,880 --> 00:27:26,520 Speaker 2: think when it comes to physical AI, the two best 496 00:27:26,560 --> 00:27:30,840 Speaker 2: physical AI please in the world on Nvidia and Tessa, 497 00:27:31,359 --> 00:27:36,040 Speaker 2: And I think now musk Wartime CEO and really is 498 00:27:36,240 --> 00:27:40,480 Speaker 2: going into the next such an important chapter in the 499 00:27:40,560 --> 00:27:41,320 Speaker 2: Tesla story. 500 00:27:41,960 --> 00:27:45,280 Speaker 1: A great way to describe him as a wartime CEO, 501 00:27:45,400 --> 00:27:49,240 Speaker 1: I think gene because Elon Musk has been through a 502 00:27:49,400 --> 00:27:55,480 Speaker 1: lot just throughout twenty twenty five, between the political moves 503 00:27:55,640 --> 00:27:59,280 Speaker 1: and coming back to Tesla with the renewed focus. Where 504 00:27:59,320 --> 00:28:01,520 Speaker 1: do you see tech going in twenty twenty six? 505 00:28:01,920 --> 00:28:04,800 Speaker 3: I think you know, Dan summed it up. It's about 506 00:28:04,880 --> 00:28:07,800 Speaker 3: the robo taxi, It's about autonomy. I mean, that's those 507 00:28:07,840 --> 00:28:10,639 Speaker 3: are the headlines that are going to be of most focus. 508 00:28:11,520 --> 00:28:14,240 Speaker 3: There is the question like I think that's what matters most. 509 00:28:14,280 --> 00:28:16,879 Speaker 3: There is a question like what happens with deliveries. I 510 00:28:17,000 --> 00:28:19,320 Speaker 3: don't think i'd be curious Dan your take on this. 511 00:28:19,359 --> 00:28:21,840 Speaker 3: I don't know if investors really care if they beat 512 00:28:21,880 --> 00:28:24,720 Speaker 3: the numbers a little bit. But just for some context, 513 00:28:25,400 --> 00:28:27,240 Speaker 3: this is as of a week ago, the shoot was 514 00:28:27,280 --> 00:28:30,840 Speaker 3: looking for sixteen percent delivery growth for calendar twenty six. 515 00:28:30,920 --> 00:28:33,520 Speaker 3: I think it's probably going to be more like flat 516 00:28:33,600 --> 00:28:35,640 Speaker 3: to up five percent. A little bit of a miss there, 517 00:28:35,760 --> 00:28:39,760 Speaker 3: and again when you start talking about some of these 518 00:28:39,840 --> 00:28:43,840 Speaker 3: negative things misses the point. I agree with Dan's highest level, 519 00:28:43,880 --> 00:28:47,240 Speaker 3: which is one of the best positioned physical AI companies 520 00:28:47,320 --> 00:28:50,840 Speaker 3: full stop. But I do wonder. I'll stand, like, do 521 00:28:51,440 --> 00:28:55,120 Speaker 3: people care let's say deliveries. Let's say they missed deliveries 522 00:28:55,200 --> 00:28:56,760 Speaker 3: for twenty twenty six. Does it matter? 523 00:28:57,240 --> 00:29:00,240 Speaker 2: I mean, this should be like going to carb going 524 00:29:00,280 --> 00:29:05,440 Speaker 2: to Miami for the water. The point is you're you're 525 00:29:05,600 --> 00:29:12,000 Speaker 2: focused on autonomous and robotics. That is the focus of deliveries. Look, Gene, 526 00:29:12,040 --> 00:29:15,520 Speaker 2: there's a stabilization, and nasal investors want to see your bobs. 527 00:29:15,560 --> 00:29:19,040 Speaker 2: It continues to still be very depressed. But I think 528 00:29:19,040 --> 00:29:22,080 Speaker 2: as long as you see a steabilization and you're seeing that, 529 00:29:22,560 --> 00:29:26,160 Speaker 2: that's fine enough. But you own the stock beers about 530 00:29:26,200 --> 00:29:27,360 Speaker 2: Thomas and robotics. 531 00:29:28,320 --> 00:29:31,160 Speaker 3: Indeed, I do own it. Yeah, and that's well said. 532 00:29:31,160 --> 00:29:34,840 Speaker 3: I think the stabilization piece is really important. One other 533 00:29:34,920 --> 00:29:37,360 Speaker 3: thing just to kind of play for it. So who 534 00:29:37,400 --> 00:29:39,760 Speaker 3: knows my senses, they're probably going to be a little 535 00:29:39,760 --> 00:29:42,680 Speaker 3: bit too high for the you know, for the for 536 00:29:43,080 --> 00:29:45,320 Speaker 3: calendar twenty six, But I don't think it really changes 537 00:29:45,360 --> 00:29:47,880 Speaker 3: the big picture. Like when I see what Ford did 538 00:29:48,480 --> 00:29:53,160 Speaker 3: at the end of twenty twenty five, basically, what was 539 00:29:53,200 --> 00:29:55,880 Speaker 3: it a two and a half billion charge five and 540 00:29:55,920 --> 00:30:00,400 Speaker 3: a half billion charge, these these bees and the becoming 541 00:30:00,920 --> 00:30:04,600 Speaker 3: all noise at some point. But the reality that they're 542 00:30:04,680 --> 00:30:07,280 Speaker 3: taking this big step back. I ask a question like, 543 00:30:07,720 --> 00:30:11,840 Speaker 3: if they want to participate in autonomy is and they're 544 00:30:11,960 --> 00:30:15,840 Speaker 3: not investing in the EV piece. Are they envisioning I 545 00:30:15,880 --> 00:30:17,720 Speaker 3: don't know the answer to this, but are they envisioning 546 00:30:17,760 --> 00:30:20,560 Speaker 3: a world where it's like hybrids are going to be autonomous? 547 00:30:21,480 --> 00:30:24,040 Speaker 3: I think that is not the world. I think it's 548 00:30:24,080 --> 00:30:26,320 Speaker 3: going to be all electric. But I think when you 549 00:30:26,560 --> 00:30:28,520 Speaker 3: look at what's going to happen with the delivery numbers 550 00:30:28,600 --> 00:30:30,960 Speaker 3: this year, beat them or miss some, the stabilization is 551 00:30:31,000 --> 00:30:34,080 Speaker 3: really important. I love that perspective, Dan. And then the 552 00:30:34,160 --> 00:30:36,880 Speaker 3: second piece is like just look at the big picture, 553 00:30:37,040 --> 00:30:40,240 Speaker 3: is that these other carmakers they're not only nowhere to 554 00:30:40,320 --> 00:30:43,600 Speaker 3: be found when it comes to autonomy, but they're they're 555 00:30:43,760 --> 00:30:47,760 Speaker 3: running towards profitability at giving back for the cost of 556 00:30:47,840 --> 00:30:48,320 Speaker 3: the future. 557 00:30:48,640 --> 00:30:50,160 Speaker 1: Yeah, I look, I agree. 558 00:30:50,200 --> 00:30:52,720 Speaker 2: I The one thing I'd say is like, you look 559 00:30:52,800 --> 00:30:55,200 Speaker 2: what's happening. I mean, like, GM's handler a lot better 560 00:30:55,360 --> 00:30:57,720 Speaker 2: than Ford, but if you look what Ford's done, they're 561 00:30:57,760 --> 00:31:01,640 Speaker 2: basically thrown in the white towel. In the extent to 562 00:31:01,800 --> 00:31:05,480 Speaker 2: Jean's point you're gonna have to eventually see when it 563 00:31:05,520 --> 00:31:10,400 Speaker 2: comes to autonomous they're gonna ultimately I could see Tesla 564 00:31:10,480 --> 00:31:13,680 Speaker 2: at a point partnering with some of the big US 565 00:31:13,760 --> 00:31:16,160 Speaker 2: auto makers as they ultimately go down this past. 566 00:31:16,400 --> 00:31:19,000 Speaker 1: That would be an interesting idea. But I'm curious, Gene 567 00:31:19,680 --> 00:31:22,320 Speaker 1: just to go back to a called Dan made earlier 568 00:31:22,400 --> 00:31:26,560 Speaker 1: about robotaxi in thirty cities. I mean, we've seen Elon 569 00:31:26,720 --> 00:31:31,880 Speaker 1: Musk set deadlines and let deadlines go quite a few 570 00:31:31,960 --> 00:31:37,120 Speaker 1: times over the years. Does Tesla need to expand robotaxi 571 00:31:37,600 --> 00:31:40,840 Speaker 1: to that extent to keep investors satisfied? 572 00:31:41,400 --> 00:31:42,680 Speaker 2: I just love that Bowld call. 573 00:31:43,480 --> 00:31:45,360 Speaker 3: They don't need to get there, and I guess is 574 00:31:45,440 --> 00:31:47,400 Speaker 3: Dan's sense is the same. They don't need to get 575 00:31:47,400 --> 00:31:51,800 Speaker 3: to that level to satisfy expectations in the movie the 576 00:31:51,840 --> 00:31:53,960 Speaker 3: stock higher. So at a point of reference there in 577 00:31:54,000 --> 00:31:58,360 Speaker 3: two cities today. They recently in Austin went to no 578 00:31:58,560 --> 00:32:02,080 Speaker 3: safety driver, but there's also no customers in there either, 579 00:32:02,800 --> 00:32:05,400 Speaker 3: and it usually takes three to six months. I've recently 580 00:32:05,480 --> 00:32:08,400 Speaker 3: done some deeper work in terms of how the approval 581 00:32:08,480 --> 00:32:11,760 Speaker 3: process works in terms of local municipalities up to the 582 00:32:11,840 --> 00:32:16,080 Speaker 3: state level, and it is the state's playoff of each other. 583 00:32:16,280 --> 00:32:19,680 Speaker 3: And so to Dan's point is that they, let's say 584 00:32:19,720 --> 00:32:22,880 Speaker 3: three six months from now, they start to get some 585 00:32:23,080 --> 00:32:25,440 Speaker 3: good feedback in terms of how they're doing without a 586 00:32:25,480 --> 00:32:28,480 Speaker 3: safety driver in the car. Other cities will use that 587 00:32:28,760 --> 00:32:31,720 Speaker 3: to quickly turn it on. And the beautiful thing about 588 00:32:31,800 --> 00:32:34,320 Speaker 3: Tessa's model of courtse is they can turn it on 589 00:32:34,480 --> 00:32:36,360 Speaker 3: in a heartbeat. I mean they can build these cars 590 00:32:36,400 --> 00:32:39,440 Speaker 3: at thirty thousand a piece. That's for like a Model 591 00:32:39,600 --> 00:32:43,800 Speaker 3: Y autonomous and eventually the cybercab and Waymo just can't 592 00:32:43,840 --> 00:32:47,560 Speaker 3: do that. I mean they're at one hundred thousand plus. 593 00:32:47,720 --> 00:32:50,360 Speaker 1: In the time we have left with Dan Ives, global 594 00:32:50,400 --> 00:32:52,760 Speaker 1: head of Tech Research at web Bush Securities and Deep 595 00:32:52,840 --> 00:32:56,160 Speaker 1: Water Asset Management spnaging partner gene Monster. I want to 596 00:32:56,200 --> 00:32:59,360 Speaker 1: look outside the mag seven to some of the other 597 00:32:59,400 --> 00:33:02,440 Speaker 1: big techs that you guys follow, what we should be 598 00:33:02,520 --> 00:33:06,240 Speaker 1: looking at in twenty twenty six as we think about 599 00:33:06,320 --> 00:33:10,280 Speaker 1: this sector. Dan, I'll start with you, which companies are 600 00:33:10,360 --> 00:33:14,400 Speaker 1: you really focused on in the new year to outperform BOK. 601 00:33:14,440 --> 00:33:17,600 Speaker 2: It continues to be you know, MESSI AI pallunteer in 602 00:33:17,720 --> 00:33:21,040 Speaker 2: terms of front and center on the use cases. But 603 00:33:21,120 --> 00:33:23,720 Speaker 2: I think you're going to see Snowflake, Mango, dB, those 604 00:33:23,760 --> 00:33:27,240 Speaker 2: are going to be some significant performers. I like when 605 00:33:27,280 --> 00:33:30,440 Speaker 2: I look at the infrastructure and NEBIS that continues to 606 00:33:30,480 --> 00:33:33,520 Speaker 2: be a name that Richud bullsh on, Iron Iri e 607 00:33:33,720 --> 00:33:36,920 Speaker 2: n That's one where it's also a power play along 608 00:33:37,000 --> 00:33:40,280 Speaker 2: with ge Veranova, It's one of our favorites. I think 609 00:33:40,320 --> 00:33:44,520 Speaker 2: you have to focus on the second third fourth derivatives cybersecurity, 610 00:33:44,600 --> 00:33:47,760 Speaker 2: crowdstrikes another one front and center along with Powell out there. 611 00:33:48,360 --> 00:33:52,160 Speaker 1: Interesting because a lot of those running into the same 612 00:33:52,440 --> 00:33:57,640 Speaker 1: kind of potential criticisms in terms of valuations. I'm thinking 613 00:33:57,720 --> 00:34:01,640 Speaker 1: of Pallenteer in particular. Ge what do you think of 614 00:34:01,720 --> 00:34:04,440 Speaker 1: some of what Dan's talking about there and what companies 615 00:34:04,480 --> 00:34:06,600 Speaker 1: are you keeping an eye on that could outperform? 616 00:34:07,240 --> 00:34:12,120 Speaker 3: It all makes sense, and you know his he'll forget 617 00:34:13,120 --> 00:34:16,080 Speaker 3: a day or he just knows infinitely more on some 618 00:34:16,120 --> 00:34:17,880 Speaker 3: of those companies than I know. And when I think 619 00:34:17,920 --> 00:34:21,360 Speaker 3: about kind of the expectations around some of these, and 620 00:34:21,520 --> 00:34:24,840 Speaker 3: I mentioned Apple and Google on the mega cap and 621 00:34:24,920 --> 00:34:26,400 Speaker 3: then it'll be kind of fun we maybe we can 622 00:34:26,440 --> 00:34:27,240 Speaker 3: play this sound. 623 00:34:27,120 --> 00:34:29,520 Speaker 2: By when we joined in the middle of the year, 624 00:34:29,600 --> 00:34:30,200 Speaker 2: how this is going. 625 00:34:30,280 --> 00:34:34,360 Speaker 3: But I think that the small cap index, which we'll 626 00:34:34,440 --> 00:34:37,480 Speaker 3: just use the PSCT as that it is going to 627 00:34:37,520 --> 00:34:40,759 Speaker 3: outperform the cues. And so that's kind of the sub 628 00:34:40,840 --> 00:34:43,480 Speaker 3: five hundred billion dollars. Still believe you should own the 629 00:34:43,560 --> 00:34:46,160 Speaker 3: mega caps, but I think you're going to see better 630 00:34:46,239 --> 00:34:49,839 Speaker 3: performance from some of these small caps in twenty twenty six. 631 00:34:50,600 --> 00:34:54,000 Speaker 1: You keeping an eye on some small caps, Dan, okay. 632 00:34:54,080 --> 00:34:57,400 Speaker 2: I mean there's a handful of small caps, you know, 633 00:34:57,640 --> 00:35:01,920 Speaker 2: specifical on like cybersecurity. I think there's number names like 634 00:35:02,040 --> 00:35:05,400 Speaker 2: Tenable Qualis. I think there's a number of names that 635 00:35:05,560 --> 00:35:09,480 Speaker 2: on the power side that could be super interesting. Names 636 00:35:09,520 --> 00:35:13,359 Speaker 2: on the software side like PEGAS Systems. Look, I think 637 00:35:13,800 --> 00:35:18,359 Speaker 2: you look at like as Gene said, second, third, fourth 638 00:35:18,480 --> 00:35:22,279 Speaker 2: derivatives across AI. That's where I think some of these, 639 00:35:22,960 --> 00:35:25,280 Speaker 2: you know, gold maybe at the end of the rainbow 640 00:35:25,360 --> 00:35:26,759 Speaker 2: could be interesting. 641 00:35:26,920 --> 00:35:29,520 Speaker 1: So does that point to the idea that we could 642 00:35:29,640 --> 00:35:33,480 Speaker 1: see something of a rotation, like there's been a debate 643 00:35:33,600 --> 00:35:36,680 Speaker 1: on in the broader market within big tech, maybe a 644 00:35:36,800 --> 00:35:41,160 Speaker 1: rotation or a broad dig away from the magnificent seven 645 00:35:41,280 --> 00:35:44,640 Speaker 1: names into more of the tech space, Dan, Or is 646 00:35:44,680 --> 00:35:45,840 Speaker 1: that something you're thinking about. 647 00:35:46,600 --> 00:35:50,120 Speaker 2: I think it's a broadening out. But it's still going 648 00:35:50,200 --> 00:35:54,440 Speaker 2: to be led by big tech and led by the 649 00:35:54,520 --> 00:35:58,279 Speaker 2: core AI revolution names, but it's it spread to second, third, 650 00:35:58,360 --> 00:36:01,040 Speaker 2: fourth derivative, and you're gonna see that spreading out. And 651 00:36:01,160 --> 00:36:03,760 Speaker 2: I could argue even you're gonna have an AI ripple 652 00:36:03,840 --> 00:36:08,080 Speaker 2: effect to financials or healthcare, a broadening of the market. 653 00:36:08,160 --> 00:36:10,719 Speaker 2: But do remember text no lef Lean one hundred miles 654 00:36:10,760 --> 00:36:14,399 Speaker 2: an hour in a Ferrari. I'd rather have that, Yeah, 655 00:36:14,560 --> 00:36:18,000 Speaker 2: you'll get some speeding tickets rather than being in value. 656 00:36:18,200 --> 00:36:20,279 Speaker 2: You in the right lane forty five miles an hour 657 00:36:20,640 --> 00:36:23,520 Speaker 2: with a bumper sticker saying Mike kez nanotuonent in third grade. 658 00:36:23,680 --> 00:36:28,360 Speaker 1: So still with a very polish call on the tech sector, Gene, 659 00:36:28,440 --> 00:36:30,840 Speaker 1: where are you when it comes to that kind of 660 00:36:30,880 --> 00:36:33,680 Speaker 1: thinking about big tech in twenty twenty six. 661 00:36:34,480 --> 00:36:37,960 Speaker 3: I'm still just thinking about that bumper sticker, big deck 662 00:36:38,040 --> 00:36:42,880 Speaker 3: in twenty twenty six. I think that it's I think 663 00:36:42,920 --> 00:36:45,560 Speaker 3: you should own some big tech, And I mean, this 664 00:36:45,800 --> 00:36:48,359 Speaker 3: is what kind of makes some fun. I mean, Dan 665 00:36:48,400 --> 00:36:50,200 Speaker 3: and I on the exact same page at the bigger 666 00:36:50,239 --> 00:36:52,840 Speaker 3: picture here, there's a little nuance that I have related 667 00:36:52,880 --> 00:36:55,560 Speaker 3: to some of the small cap and we'll see how 668 00:36:56,040 --> 00:37:00,880 Speaker 3: ps CT does relative to the cues and companies, you know, 669 00:37:01,000 --> 00:37:03,560 Speaker 3: smaller ones, smaller and cool one hundred and fifty billion 670 00:37:03,600 --> 00:37:07,720 Speaker 3: dollars a risk of networks or very on the power 671 00:37:07,880 --> 00:37:12,360 Speaker 3: cooling side. I mean, these companies have had just breathtaking moves. 672 00:37:12,480 --> 00:37:15,160 Speaker 3: But if we're right on the bigger picture here of 673 00:37:15,239 --> 00:37:17,240 Speaker 3: how much infrastructure is going to be put into place, 674 00:37:18,120 --> 00:37:20,120 Speaker 3: those companies like that should do well. And I think 675 00:37:20,160 --> 00:37:22,319 Speaker 3: that's going to be a positive for the small cat trade. 676 00:37:22,920 --> 00:37:25,320 Speaker 2: And Nathan, I would also just say, I, you know, 677 00:37:25,480 --> 00:37:30,560 Speaker 2: and I just keep trying to figure out, besides the 678 00:37:30,600 --> 00:37:33,279 Speaker 2: AI revolution, how do we get Gene to wear a 679 00:37:33,400 --> 00:37:37,160 Speaker 2: pink sports shock. That's something that we have to we 680 00:37:37,239 --> 00:37:38,880 Speaker 2: have to just we have to figure that out. We 681 00:37:39,000 --> 00:37:39,600 Speaker 2: only should. 682 00:37:39,800 --> 00:37:43,359 Speaker 3: Let's we need to come up with some like market number. 683 00:37:43,400 --> 00:37:44,800 Speaker 3: Then people will say, well, that's going to be the 684 00:37:44,880 --> 00:37:48,880 Speaker 3: peak of the market, but I'll purchase a pink sport 685 00:37:49,040 --> 00:37:52,320 Speaker 3: code at We'll figure out that number, Dan and be 686 00:37:52,480 --> 00:37:53,320 Speaker 3: back to Nathan. 687 00:37:53,680 --> 00:37:57,560 Speaker 1: If Dan ives and Gene Munster switch wardrobes, we will 688 00:37:57,680 --> 00:38:00,239 Speaker 1: know that we have gotten somewhere in the. 689 00:38:00,360 --> 00:38:03,440 Speaker 3: Text, right, I think you'd recognize either of us. 690 00:38:03,600 --> 00:38:06,759 Speaker 1: But seriously, not to end this on a downer, but 691 00:38:07,080 --> 00:38:10,360 Speaker 1: just quickly before we let you guys go, what should 692 00:38:10,600 --> 00:38:14,279 Speaker 1: investors avoid like the plague in the tech space in 693 00:38:14,360 --> 00:38:17,000 Speaker 1: twenty twenty six, gene Monster Just quickly. 694 00:38:16,960 --> 00:38:20,680 Speaker 3: Well, I guess I'm just so optimistic about how early 695 00:38:20,760 --> 00:38:23,960 Speaker 3: we are. I'm reluctant to pick kind of a avoid 696 00:38:24,200 --> 00:38:28,200 Speaker 3: like avoid like the plague. I think we'll see how 697 00:38:28,280 --> 00:38:33,320 Speaker 3: this plays out when the companies go vertical and in 698 00:38:33,520 --> 00:38:36,640 Speaker 3: short amounts of time, then we could maybe have evaluation. 699 00:38:36,800 --> 00:38:37,160 Speaker 2: But I'm not. 700 00:38:37,840 --> 00:38:39,319 Speaker 3: I just don't have anything on my list. 701 00:38:39,600 --> 00:38:42,640 Speaker 1: All right, Well, we'll end it there now, but again, 702 00:38:42,880 --> 00:38:46,480 Speaker 1: always a pleasure getting you guys together this time of 703 00:38:46,520 --> 00:38:50,520 Speaker 1: the year. That's Gene Monster managing partner Deepwater Asset Management 704 00:38:51,000 --> 00:38:53,520 Speaker 1: and dan Ives Global Ahead of Tech Research at web 705 00:38:53,560 --> 00:38:55,560 Speaker 1: Bush Securities. Thanks to both of you for spending the 706 00:38:55,800 --> 00:38:58,399 Speaker 1: entire hour with us, and thanks to you as well 707 00:38:59,040 --> 00:39:01,200 Speaker 1: for bringing in part of your new year with us. 708 00:39:01,320 --> 00:39:04,560 Speaker 1: I'm Nathan Hager, wishing you many happy returns tech or 709 00:39:04,640 --> 00:39:08,160 Speaker 1: otherwise in twenty twenty six. Stay with us Top stories 710 00:39:08,200 --> 00:39:10,440 Speaker 1: global business headlines coming up right now.