1
00:00:02,360 --> 00:00:04,360
Speaker 1: Thank you so much for joining us for this special

2
00:00:04,519 --> 00:00:08,080
Speaker 1: edition of Bloomberg Daybreak. I'm Nathan Hager. US markets are

3
00:00:08,119 --> 00:00:11,119
Speaker 1: closed for the Independence Day holiday and it's become a

4
00:00:11,240 --> 00:00:13,840
Speaker 1: tradition for the Fourth of July. You got the fireworks,

5
00:00:13,880 --> 00:00:17,320
Speaker 1: the Nathan's Hot Dog eating contest, and Genemunster and Dan

6
00:00:17,360 --> 00:00:20,040
Speaker 1: Ives for the hour on Bloomberg Daybreak. That's right, we

7
00:00:20,120 --> 00:00:23,920
Speaker 1: have a special one hour high tech roundtable once again

8
00:00:24,040 --> 00:00:27,080
Speaker 1: with two of Wall Street's most influential analysts in the space.

9
00:00:27,200 --> 00:00:31,200
Speaker 1: Gene Munster, managing partner in deepwater Asset Management and Dan Ives,

10
00:00:31,240 --> 00:00:34,680
Speaker 1: the former head of Global Technology research at Webbush Securities.

11
00:00:34,840 --> 00:00:37,360
Speaker 1: We should note we did tape this conversation a few

12
00:00:37,400 --> 00:00:39,960
Speaker 1: days before the holiday, but it's great to have the

13
00:00:40,000 --> 00:00:43,040
Speaker 1: both of you back with us for this roundtable. And

14
00:00:43,120 --> 00:00:45,880
Speaker 1: I know you like to both talk about where things

15
00:00:45,920 --> 00:00:50,120
Speaker 1: stand in the AI investment cycle. Where we are, so, Dan,

16
00:00:50,960 --> 00:00:54,280
Speaker 1: here's what you told us last time we did this conversation.

17
00:00:54,440 --> 00:00:56,040
Speaker 1: At the beginning of the new year.

18
00:00:56,240 --> 00:00:59,480
Speaker 2: It's ten pm in his AI party that goes to

19
00:00:59,560 --> 00:01:03,120
Speaker 2: four A. This is just the first step in two

20
00:01:03,360 --> 00:01:05,240
Speaker 2: trillion of AI cat backs.

21
00:01:05,520 --> 00:01:08,000
Speaker 1: Well, since then, it's kind of gotten a little bumpy

22
00:01:08,040 --> 00:01:10,440
Speaker 1: as far as the clock goes for the AI party,

23
00:01:10,480 --> 00:01:10,840
Speaker 1: hasn't it?

24
00:01:10,920 --> 00:01:11,080
Speaker 3: Dan?

25
00:01:11,360 --> 00:01:14,040
Speaker 2: Yeah, Look, we've always said, I mean, in the party,

26
00:01:14,760 --> 00:01:17,720
Speaker 2: DJ could stop playing music, Glass could drop in the

27
00:01:17,800 --> 00:01:20,880
Speaker 2: dance for cops could come to try and breakout for

28
00:01:21,000 --> 00:01:24,240
Speaker 2: noise violation. But that's gonna happen. But the party is

29
00:01:24,240 --> 00:01:27,920
Speaker 2: gonna continue. And we think right now it's still eleven

30
00:01:28,000 --> 00:01:31,039
Speaker 2: eleven thirty pm in the party, third inning in the

31
00:01:31,120 --> 00:01:34,800
Speaker 2: in the baseball game, because you've only gone through fifteen

32
00:01:34,840 --> 00:01:38,440
Speaker 2: percent of the cat backs demonizations spreading and you see

33
00:01:38,480 --> 00:01:41,759
Speaker 2: it from memory to what we see on the infrastructure,

34
00:01:41,840 --> 00:01:45,479
Speaker 2: to energy, some of the neo clouds. So that's my view,

35
00:01:45,520 --> 00:01:48,640
Speaker 2: like you were gonna have bumps, you're gonna have turbulence.

36
00:01:48,960 --> 00:01:52,000
Speaker 2: But we continue to believe Nazak thirty thousand and this

37
00:01:52,120 --> 00:01:57,160
Speaker 2: is just sort of, you know, worth early stages in

38
00:01:57,280 --> 00:01:58,840
Speaker 2: terms of where this all heads.

39
00:01:59,040 --> 00:02:00,640
Speaker 1: I want to ask you a little bit more about

40
00:02:00,640 --> 00:02:04,840
Speaker 1: that fifteen percent in AI capex. I mean, we've been

41
00:02:04,880 --> 00:02:09,240
Speaker 1: talking about hundreds of billions of dollars that just the

42
00:02:09,360 --> 00:02:13,400
Speaker 1: four main hyperscalers are saying that they're going to spend

43
00:02:13,480 --> 00:02:16,760
Speaker 1: just in the last earning cycle. I mean where do

44
00:02:16,840 --> 00:02:20,280
Speaker 1: you see this trajectory as far as the spending, Isn't

45
00:02:20,280 --> 00:02:23,000
Speaker 1: that part of the reason why we're seeing so many

46
00:02:23,080 --> 00:02:24,120
Speaker 1: jitters in this market?

47
00:02:24,800 --> 00:02:29,040
Speaker 2: Uh? Hunt, Yeah, hundreds and Gene, we've talked about a lot.

48
00:02:29,080 --> 00:02:31,680
Speaker 2: But I view it as like it's Vegas in the

49
00:02:31,760 --> 00:02:35,800
Speaker 2: nineteen fifties building the strip. Are there going to be

50
00:02:35,919 --> 00:02:36,720
Speaker 2: speed bumps?

51
00:02:36,800 --> 00:02:37,160
Speaker 4: Yeah?

52
00:02:37,320 --> 00:02:38,960
Speaker 2: But if someone told you the strip where it is

53
00:02:39,000 --> 00:02:42,280
Speaker 2: today back in the fifties, you'd say, no, what. That's

54
00:02:42,320 --> 00:02:44,760
Speaker 2: my view. When it comes to physical AI, and when

55
00:02:44,800 --> 00:02:48,920
Speaker 2: it comes to enterprise and the consumer side, you're building

56
00:02:49,160 --> 00:02:54,079
Speaker 2: out the foundation. Sovereigns haven't even started building out, and

57
00:02:54,440 --> 00:02:58,160
Speaker 2: then you start to think about you're up nothing, Asia

58
00:02:58,280 --> 00:02:58,840
Speaker 2: just starting.

59
00:03:00,120 --> 00:03:02,560
Speaker 1: I want to bring you into the conversation Gene as well,

60
00:03:02,560 --> 00:03:04,519
Speaker 1: but before I do, I want to give you a

61
00:03:04,560 --> 00:03:06,880
Speaker 1: little bit of a memory of what you had to say.

62
00:03:06,919 --> 00:03:10,200
Speaker 1: As far as where things are in the AI game, I.

63
00:03:10,120 --> 00:03:13,959
Speaker 3: Think we're probably on the fourth inning. We're still early,

64
00:03:14,000 --> 00:03:17,600
Speaker 3: which seems out of touch with reality, but I think

65
00:03:17,639 --> 00:03:20,360
Speaker 3: that that is how significant this transformation is going to be,

66
00:03:20,400 --> 00:03:24,200
Speaker 3: and so we're definitely further along. But I still believe

67
00:03:24,560 --> 00:03:26,200
Speaker 3: I talked about three to five years. I think we've

68
00:03:26,200 --> 00:03:28,160
Speaker 3: still got another two good years left here.

69
00:03:28,400 --> 00:03:31,680
Speaker 1: Okay, so maybe the question following that is are we

70
00:03:31,720 --> 00:03:35,160
Speaker 1: in for some long innings in the AI build out?

71
00:03:35,440 --> 00:03:38,440
Speaker 3: Well, I would first mention that on the inning question

72
00:03:38,840 --> 00:03:40,800
Speaker 3: is the way I answer that, I'm answering it to

73
00:03:40,840 --> 00:03:43,840
Speaker 3: amount of wealth creation that's left, not how much the

74
00:03:43,880 --> 00:03:45,080
Speaker 3: technology is going to advance.

75
00:03:45,120 --> 00:03:46,640
Speaker 4: So it's specific to the markets.

76
00:03:47,200 --> 00:03:50,760
Speaker 3: And kind of funny enough, after those comments in January,

77
00:03:50,800 --> 00:03:54,480
Speaker 3: I shifted my commentary to warn the second inning kind

78
00:03:54,480 --> 00:03:57,440
Speaker 3: of in February actually better than what we thought, and

79
00:03:57,480 --> 00:03:59,680
Speaker 3: I'm inching more towards that third inning. Now this is

80
00:03:59,720 --> 00:04:02,000
Speaker 3: all getting kind of caught in the details here. The

81
00:04:02,040 --> 00:04:04,440
Speaker 3: point is we're still early, whether it's the second or

82
00:04:04,560 --> 00:04:08,480
Speaker 3: third inning. And I think that from like a rational perspective,

83
00:04:08,640 --> 00:04:12,600
Speaker 3: that seems irrational that just given this these parabolic moves

84
00:04:12,640 --> 00:04:14,520
Speaker 3: that a lot of these companies have had, that these

85
00:04:14,560 --> 00:04:18,160
Speaker 3: massive amounts of invest that Dan's talking about, how could

86
00:04:18,160 --> 00:04:21,440
Speaker 3: we be in the middle of the second the third inning.

87
00:04:21,960 --> 00:04:26,080
Speaker 3: And the answer is that there's just the desire to

88
00:04:26,800 --> 00:04:30,320
Speaker 3: build out the brain the infrastructure side is increasing far

89
00:04:30,360 --> 00:04:33,000
Speaker 3: more than even the high expectations. I think Google's recent

90
00:04:33,720 --> 00:04:37,640
Speaker 3: equity sale that ultimately netted them about eighty five billion

91
00:04:37,680 --> 00:04:40,120
Speaker 3: dollars that they're going to spend majority of that on

92
00:04:40,480 --> 00:04:44,640
Speaker 3: basically building out their AI brain, I think is evidence

93
00:04:44,720 --> 00:04:48,480
Speaker 3: that we're still very early in this And ultimately, if

94
00:04:48,480 --> 00:04:50,360
Speaker 3: it comes down to a question, do you believe that

95
00:04:50,400 --> 00:04:53,000
Speaker 3: these companies that are spending the most are competent and

96
00:04:53,040 --> 00:04:54,880
Speaker 3: have a good view on what's going on in the future.

97
00:04:55,400 --> 00:04:57,240
Speaker 3: If you think the answer is yes to that, then

98
00:04:57,240 --> 00:04:59,839
Speaker 3: we're probably somewhere getting close to the third inning.

99
00:05:00,640 --> 00:05:03,480
Speaker 1: Well, that does get again to the question of how

100
00:05:03,600 --> 00:05:08,560
Speaker 1: much these companies are spending, not just in their own capital,

101
00:05:08,640 --> 00:05:13,720
Speaker 1: but you know, dipping into investment grade debt issuance as well.

102
00:05:14,400 --> 00:05:17,359
Speaker 1: At some point do we start to see a breaking

103
00:05:17,400 --> 00:05:17,880
Speaker 1: point here?

104
00:05:17,960 --> 00:05:21,560
Speaker 3: Gene, Well, this is you talked about the jitters with

105
00:05:21,600 --> 00:05:24,400
Speaker 3: Dan a minute ago and mentioned about kind of this

106
00:05:24,560 --> 00:05:28,240
Speaker 3: commentary around overspending, and at some point is there a

107
00:05:28,279 --> 00:05:31,760
Speaker 3: breaking point? And the simple answer is maybe, if in

108
00:05:31,839 --> 00:05:35,440
Speaker 3: fact that the revenue starts to accelerate, at least a

109
00:05:35,480 --> 00:05:39,000
Speaker 3: handful of companies can show meaningful revenue acceleration around AI,

110
00:05:39,520 --> 00:05:41,600
Speaker 3: then I think the market's going to largely be okay

111
00:05:41,640 --> 00:05:44,560
Speaker 3: with us. And if we don't really see that in

112
00:05:44,600 --> 00:05:46,880
Speaker 3: substance so far. Of course, we've seen Google with their

113
00:05:46,920 --> 00:05:50,160
Speaker 3: search business going from called eleven percent to nineteen percent,

114
00:05:50,880 --> 00:05:54,000
Speaker 3: their cloud business going from mid twenties growth to almost

115
00:05:54,080 --> 00:05:56,960
Speaker 3: sixty percent recently. That's over a three quarter period, just

116
00:05:57,040 --> 00:06:01,120
Speaker 3: these crazy growth numbers. Meta their advertising is going fifteen

117
00:06:01,240 --> 00:06:04,440
Speaker 3: to mid was it low thirty percent growth?

118
00:06:04,480 --> 00:06:06,040
Speaker 4: I mean, just crazy increases.

119
00:06:06,040 --> 00:06:09,200
Speaker 3: But it needs to expand out beyond what Google and

120
00:06:09,240 --> 00:06:11,960
Speaker 3: Meta have experience, to a lot of companies showing this

121
00:06:12,040 --> 00:06:15,479
Speaker 3: acceleration and revenue growth or margins. And so to ask

122
00:06:15,520 --> 00:06:18,400
Speaker 3: your question, Nata, is that the answer is maybe if

123
00:06:18,640 --> 00:06:21,960
Speaker 3: we probably start to need to see one or two

124
00:06:22,000 --> 00:06:25,599
Speaker 3: more really clear stories in the next year for the

125
00:06:25,640 --> 00:06:26,880
Speaker 3: market largely distill.

126
00:06:27,080 --> 00:06:28,520
Speaker 4: To go along with this trade.

127
00:06:28,520 --> 00:06:32,160
Speaker 1: We're speaking with Gene Munster, managing partner Deepwater Asset Management

128
00:06:32,279 --> 00:06:35,160
Speaker 1: and the former head of Global Technology at Webbush Securities,

129
00:06:35,200 --> 00:06:39,239
Speaker 1: Stan Ives, assessing where things stand in the AI race

130
00:06:39,360 --> 00:06:41,600
Speaker 1: right now. I want to get your view, Dan, picking

131
00:06:41,680 --> 00:06:43,279
Speaker 1: up on what Gene had to say in terms of

132
00:06:43,600 --> 00:06:46,719
Speaker 1: monetization around so much of the spending that we're seeing

133
00:06:46,760 --> 00:06:49,960
Speaker 1: among the hyperscalers. Where do you see things as far

134
00:06:50,120 --> 00:06:54,200
Speaker 1: as what these companies need to show to show that

135
00:06:54,240 --> 00:06:58,919
Speaker 1: they're really starting to turn a profit on this massive

136
00:06:58,920 --> 00:07:00,320
Speaker 1: spending that they're under way with.

137
00:07:01,560 --> 00:07:05,760
Speaker 2: Look, I think to that point we're almost in this

138
00:07:05,960 --> 00:07:11,360
Speaker 2: air pocket period between cap bacs and modernization for the

139
00:07:11,440 --> 00:07:14,560
Speaker 2: hyper scalers. When you look at ASURE growth, or you

140
00:07:14,600 --> 00:07:17,480
Speaker 2: look at you Cloud growth for Google, you look what

141
00:07:17,520 --> 00:07:20,400
Speaker 2: we see with AWS, it's really starting to see like

142
00:07:20,440 --> 00:07:23,360
Speaker 2: an acceleration. I think it's a very important earning season

143
00:07:23,560 --> 00:07:27,120
Speaker 2: coming up to really start to see that. And then

144
00:07:27,880 --> 00:07:32,520
Speaker 2: how does men monetize AI into its install base? It's

145
00:07:32,520 --> 00:07:33,640
Speaker 2: billions of users.

146
00:07:34,240 --> 00:07:35,560
Speaker 4: How does Microsoft take.

147
00:07:35,440 --> 00:07:37,640
Speaker 2: The next level in terms of making sure as the

148
00:07:37,720 --> 00:07:41,640
Speaker 2: enterprise is moved to AI that they're across and up

149
00:07:41,680 --> 00:07:45,480
Speaker 2: selling and you see the revenue growth and ultimately you're

150
00:07:45,520 --> 00:07:49,120
Speaker 2: really changing the model. That's why right now, like hyper

151
00:07:49,200 --> 00:07:53,720
Speaker 2: scalers outside alp BET have really been put in the

152
00:07:53,720 --> 00:07:57,200
Speaker 2: penalty box. Very important few quarters ahead.

153
00:07:58,640 --> 00:08:02,880
Speaker 1: And we haven't even to yet about the massive run

154
00:08:03,000 --> 00:08:06,840
Speaker 1: that we've seen in the memory chip stocks. They've gone

155
00:08:07,080 --> 00:08:09,920
Speaker 1: gangbusters over the last few months off the back of

156
00:08:10,440 --> 00:08:14,040
Speaker 1: this enormous pricing power that they have. It sent those

157
00:08:14,120 --> 00:08:17,640
Speaker 1: stocks up triple digits. Gene I want to put the

158
00:08:17,720 --> 00:08:22,520
Speaker 1: question to you as to what that means for these hyperscalers.

159
00:08:22,840 --> 00:08:26,960
Speaker 1: Does that start to have an impact on their profit trajectory.

160
00:08:28,960 --> 00:08:31,680
Speaker 3: Well, definitely can have an impact on that profit trajectory,

161
00:08:31,760 --> 00:08:34,120
Speaker 3: just because these cost of memory. If you just kind

162
00:08:34,160 --> 00:08:35,840
Speaker 3: of look at the first six months of the year,

163
00:08:36,520 --> 00:08:40,200
Speaker 3: somewhere between three and four hundred percent increase, This is

164
00:08:40,240 --> 00:08:42,920
Speaker 3: now accounting for fifteen percent of kind of the cost

165
00:08:42,960 --> 00:08:46,920
Speaker 3: of at least the core compute infrastructure outside of buildings

166
00:08:46,960 --> 00:08:49,520
Speaker 3: are on data centers. These are big numbers we're talking about.

167
00:08:50,360 --> 00:08:55,160
Speaker 3: The reality is is that these companies, I think this

168
00:08:55,240 --> 00:08:58,320
Speaker 3: is probably the biggest takeaway to Micron on where we

169
00:08:58,360 --> 00:09:02,040
Speaker 3: are on the AI trade, is that the biggest takeaway

170
00:09:02,080 --> 00:09:04,320
Speaker 3: is that they signed up the companies that are spending

171
00:09:04,360 --> 00:09:07,080
Speaker 3: the most, the big the hyper scalers, other companies that

172
00:09:07,840 --> 00:09:10,640
Speaker 3: are using a lot of this memory in there to

173
00:09:10,640 --> 00:09:13,480
Speaker 3: build consumer electronics. For example, Apple is a good example.

174
00:09:14,320 --> 00:09:17,720
Speaker 3: The number that have signed long term five year agreements

175
00:09:17,760 --> 00:09:19,800
Speaker 3: went from one in total, so they had their first

176
00:09:19,800 --> 00:09:23,000
Speaker 3: ever Micron did in the March quarter and they they

177
00:09:23,040 --> 00:09:26,680
Speaker 3: added fifteen in total, but call it six of those

178
00:09:27,320 --> 00:09:29,319
Speaker 3: were of five year.

179
00:09:30,760 --> 00:09:31,040
Speaker 4: Term.

180
00:09:31,600 --> 00:09:35,000
Speaker 3: So going from zero six months ago to seven. And

181
00:09:35,040 --> 00:09:38,240
Speaker 3: the only reason why these big companies would sign a

182
00:09:38,280 --> 00:09:41,240
Speaker 3: five year deal with Micron is if they knew how

183
00:09:41,320 --> 00:09:45,040
Speaker 3: much that they expected to spend far out well beyond

184
00:09:45,120 --> 00:09:47,120
Speaker 3: what they've communicated to the street. I think that's a

185
00:09:47,160 --> 00:09:51,080
Speaker 3: big tell. And so when you think about what's really

186
00:09:51,120 --> 00:09:54,520
Speaker 3: driving this, the insatiable demand to continue to build. Yes,

187
00:09:54,559 --> 00:09:58,280
Speaker 3: the high memory prices are having an impact on this,

188
00:09:58,720 --> 00:10:01,719
Speaker 3: but these companies are finding ways to navigate around it.

189
00:10:01,760 --> 00:10:05,240
Speaker 3: And I think that you know, this was a resounding

190
00:10:05,280 --> 00:10:09,960
Speaker 3: the Micron commentary around their strategic customer announcements agreements. I

191
00:10:09,960 --> 00:10:12,920
Speaker 3: think that is a resounding endorsement that we're still early

192
00:10:13,000 --> 00:10:16,080
Speaker 3: despite the negative impact that it's going to have on margins.

193
00:10:16,320 --> 00:10:19,280
Speaker 1: What does it mean for the overall market though, Gene,

194
00:10:20,000 --> 00:10:24,400
Speaker 1: When we have the chip companies as expensive as they are,

195
00:10:24,440 --> 00:10:26,640
Speaker 1: and you mentioned so much of the spending happening by

196
00:10:26,640 --> 00:10:31,120
Speaker 1: the hyperscalers, does that potentially leave other names, other sovereigns

197
00:10:31,160 --> 00:10:34,520
Speaker 1: potentially that want to get in on this in the cold.

198
00:10:34,679 --> 00:10:36,800
Speaker 3: Well, they're probably in the cold the near term, but

199
00:10:36,880 --> 00:10:40,240
Speaker 3: long term they will eventually get into on board and

200
00:10:40,280 --> 00:10:43,080
Speaker 3: start to buy and build these data centers and so

201
00:10:43,760 --> 00:10:48,080
Speaker 3: that's why there's commentary that Micron could be outside of

202
00:10:48,120 --> 00:10:51,840
Speaker 3: supply demand equilibrium. They said they didn't have line of

203
00:10:51,960 --> 00:10:54,959
Speaker 3: site at the end of twenty seven calendar twenty seven,

204
00:10:55,400 --> 00:10:57,560
Speaker 3: I mean it could be twenty twenty nine, and that

205
00:10:57,600 --> 00:10:59,880
Speaker 3: could be in part because the sovereigns start to enter

206
00:10:59,880 --> 00:11:02,920
Speaker 3: the equation. And kind of just for those listeners who

207
00:11:02,920 --> 00:11:05,160
Speaker 3: aren't as familiar with what we're talking about here, is

208
00:11:05,160 --> 00:11:07,360
Speaker 3: that basically the big tech companies have been driving this,

209
00:11:07,760 --> 00:11:12,080
Speaker 3: but eventually, like countries will be building their own AI

210
00:11:12,160 --> 00:11:14,720
Speaker 3: infrastructure and that is likely going to be this kind

211
00:11:14,720 --> 00:11:15,720
Speaker 3: of second.

212
00:11:15,440 --> 00:11:16,560
Speaker 4: Wave of spending.

213
00:11:17,200 --> 00:11:19,280
Speaker 3: So I think that when I line up all the

214
00:11:20,360 --> 00:11:23,959
Speaker 3: potential drivers, it gets us to that maybe entering the

215
00:11:24,000 --> 00:11:27,240
Speaker 3: third inning, middle of the second inning. Kind of a takeaway,

216
00:11:27,240 --> 00:11:30,200
Speaker 3: I think there's another part of that conversation we know

217
00:11:30,240 --> 00:11:32,440
Speaker 3: and Dan and I talk about, like this massive wave

218
00:11:32,520 --> 00:11:35,360
Speaker 3: of spending and all this transformation that's going on. Why

219
00:11:35,400 --> 00:11:39,080
Speaker 3: do we have situations like in Vidia recently over the

220
00:11:39,200 --> 00:11:41,240
Speaker 3: since year to date, I think the stock's down something

221
00:11:41,320 --> 00:11:44,480
Speaker 3: like eight percent, The Nasdaq is down like one percent.

222
00:11:45,120 --> 00:11:49,240
Speaker 3: The numbers the revenue estimates for next year for in

223
00:11:49,360 --> 00:11:53,040
Speaker 3: Vidia have gone up three percent over the last six months,

224
00:11:53,120 --> 00:11:56,360
Speaker 3: and so you're basically seeing multiple compression and other good

225
00:11:56,360 --> 00:11:59,800
Speaker 3: example is Micron, I mean they're multiple despite the stock

226
00:12:00,040 --> 00:12:02,480
Speaker 3: of twelve percent over the past year, it's still trades

227
00:12:02,480 --> 00:12:03,760
Speaker 3: at like a nine multiple.

228
00:12:04,000 --> 00:12:05,079
Speaker 4: How's that possible?

229
00:12:05,480 --> 00:12:07,360
Speaker 3: And the reason is that this is the part that

230
00:12:07,600 --> 00:12:09,760
Speaker 3: is a concern to me when I think about sovereign

231
00:12:09,800 --> 00:12:13,560
Speaker 3: I think about how this trade can continue. Is the

232
00:12:13,600 --> 00:12:17,920
Speaker 3: market just progressively believing that eventually we're going to hit

233
00:12:17,920 --> 00:12:20,320
Speaker 3: the wall and really don't put too much weight into

234
00:12:20,360 --> 00:12:21,800
Speaker 3: all this goodness that's happening.

235
00:12:21,880 --> 00:12:25,080
Speaker 1: Now we're going to continue this conversation with Gene Munster

236
00:12:25,400 --> 00:12:30,000
Speaker 1: of Deepwater Asset Management and Dan Ives, formerly of Webbush Securities,

237
00:12:30,200 --> 00:12:33,680
Speaker 1: as this special high tech edition of Bloomberg Daybreak for

238
00:12:33,720 --> 00:12:37,960
Speaker 1: the Independence Day holiday continues. It's now twenty minutes past

239
00:12:38,000 --> 00:12:53,240
Speaker 1: the hour. I'm Nathan Hager, and this this boomer Welcome

240
00:12:53,240 --> 00:12:56,240
Speaker 1: back to the special edition of Bloomberg Daybreak. US markets

241
00:12:56,280 --> 00:12:59,600
Speaker 1: are closed for the long Independence holiday weekend. I'm Nathan

242
00:12:59,600 --> 00:13:02,800
Speaker 1: Hager bringing you a high tech power hour. We're speaking

243
00:13:02,800 --> 00:13:07,160
Speaker 1: with Dan Ives, former global technology headed Webbush Securities and

244
00:13:07,240 --> 00:13:11,040
Speaker 1: Deepwater Asset Management managing partner Gene Monster. We should know

245
00:13:11,160 --> 00:13:14,360
Speaker 1: we taped this conversation a few days before the holiday. Dan,

246
00:13:14,440 --> 00:13:17,640
Speaker 1: let's pick up where Gene left off in terms of

247
00:13:18,040 --> 00:13:21,160
Speaker 1: sort of the split that we're starting to see in

248
00:13:21,200 --> 00:13:23,680
Speaker 1: some of these memory chip makers, the ones that have

249
00:13:23,720 --> 00:13:26,800
Speaker 1: been so much involved in the AI race. We've seen

250
00:13:26,920 --> 00:13:30,080
Speaker 1: Nvidia down a bit, Micron, as we mentioned, has been

251
00:13:30,320 --> 00:13:33,720
Speaker 1: surging over the last few months. Where do you see

252
00:13:33,760 --> 00:13:34,360
Speaker 1: this going.

253
00:13:34,800 --> 00:13:38,960
Speaker 2: There will be a normalization as this starts to play

254
00:13:39,040 --> 00:13:43,479
Speaker 2: on the Modernizesian side, which will be bullish for hyperscours,

255
00:13:43,480 --> 00:13:47,120
Speaker 2: bullsh for Nvidia, bullsh for a MD But right now,

256
00:13:47,400 --> 00:13:50,920
Speaker 2: because of memory prices and because there's only women. I

257
00:13:50,960 --> 00:13:54,480
Speaker 2: mean when you go sk and Micron, and you know

258
00:13:54,600 --> 00:13:57,240
Speaker 2: Samsung and sand Disk, and we're talking about a very

259
00:13:57,320 --> 00:13:59,520
Speaker 2: selective group of companies.

260
00:14:00,040 --> 00:14:01,800
Speaker 4: This will normalize.

261
00:14:02,440 --> 00:14:04,920
Speaker 2: I believe as we get to the next six nine

262
00:14:05,000 --> 00:14:08,920
Speaker 2: twelve months, market will look ahead of that equilibrium. We

263
00:14:09,000 --> 00:14:12,280
Speaker 2: don't probably hit for eighteen twenty four months when it

264
00:14:12,320 --> 00:14:15,520
Speaker 2: comes to demand, spy for memberships. But to me, it

265
00:14:15,559 --> 00:14:18,439
Speaker 2: all comes down to like market will start to look

266
00:14:18,520 --> 00:14:27,760
Speaker 2: for on software, cybersecurity, infrastructure, energy on the data center side,

267
00:14:27,920 --> 00:14:31,560
Speaker 2: who are going to be the need who's the next Micron,

268
00:14:32,040 --> 00:14:36,400
Speaker 2: Who's the next sand disk? And I think that's it's

269
00:14:36,440 --> 00:14:38,800
Speaker 2: our viewing. We're in a multi year tech bal market.

270
00:14:38,920 --> 00:14:40,760
Speaker 2: It's a year three of a ten year build out.

271
00:14:41,360 --> 00:14:44,400
Speaker 2: We're just going through a major gut check period for

272
00:14:44,480 --> 00:14:47,800
Speaker 2: a while. The quote unquote traditional winners in max seventy.

273
00:14:47,840 --> 00:14:51,160
Speaker 1: Jane, let's bring you back in. Do you see normalization coming?

274
00:14:51,200 --> 00:14:54,040
Speaker 1: And that kind of timeline six to twelve months, and

275
00:14:54,200 --> 00:14:58,120
Speaker 1: I mean Dan mentioned all the different sectors that are

276
00:14:58,160 --> 00:15:02,920
Speaker 1: affected by this. Seems like there's a pretty significant split

277
00:15:03,400 --> 00:15:05,560
Speaker 1: on where the winners and losers are right now.

278
00:15:06,320 --> 00:15:08,920
Speaker 3: That kind of I had a question for Dan on

279
00:15:08,960 --> 00:15:12,480
Speaker 3: that is when we talk about like normalization, can you

280
00:15:12,520 --> 00:15:14,080
Speaker 3: tell me a little bit more about what are your

281
00:15:14,080 --> 00:15:15,960
Speaker 3: front of just normalization of growth rates?

282
00:15:16,240 --> 00:15:19,880
Speaker 2: Yeah, I'm really looking at normalization of price increases because

283
00:15:19,920 --> 00:15:24,400
Speaker 2: I think the big issue now as Gene and I've

284
00:15:24,440 --> 00:15:28,480
Speaker 2: seen some closely from app O to Microsoft that it's

285
00:15:28,520 --> 00:15:31,720
Speaker 2: the fear of the unknown. What happens if this just continues?

286
00:15:32,040 --> 00:15:33,840
Speaker 2: When has the price go up more? I think the

287
00:15:33,880 --> 00:15:38,040
Speaker 2: normalization will start to happen on a price perspective over

288
00:15:38,080 --> 00:15:38,640
Speaker 2: that period.

289
00:15:39,480 --> 00:15:42,560
Speaker 3: So, Nathan, my response to that is I agree. I

290
00:15:42,600 --> 00:15:45,520
Speaker 3: think that there will be normalization on the price, and

291
00:15:45,520 --> 00:15:47,680
Speaker 3: I think some I mean, just using micron as just

292
00:15:47,720 --> 00:15:49,800
Speaker 3: like a microcosm.

293
00:15:49,120 --> 00:15:50,440
Speaker 4: Of that topic.

294
00:15:51,080 --> 00:15:55,000
Speaker 3: Is that the the fact that we're seeing these fifteen

295
00:15:55,320 --> 00:16:01,240
Speaker 3: now SCA sixteen scas, these strategic customerments that are long term,

296
00:16:01,280 --> 00:16:06,000
Speaker 3: I mean that helps build some normalization within pricing. I

297
00:16:06,000 --> 00:16:08,760
Speaker 3: mean there may be an opportunity. It's recently rumored that

298
00:16:08,800 --> 00:16:12,800
Speaker 3: Apple is working with a Chinese memory supplier that's currently

299
00:16:12,840 --> 00:16:17,840
Speaker 3: blacklisted by the US to get that company unblacklisted, which

300
00:16:17,920 --> 00:16:20,040
Speaker 3: can open up some lower priced.

301
00:16:21,160 --> 00:16:21,560
Speaker 4: Memory.

302
00:16:21,600 --> 00:16:23,720
Speaker 3: And so I think that I would generally agree with that.

303
00:16:23,880 --> 00:16:25,000
Speaker 4: I would say the part that.

304
00:16:25,600 --> 00:16:28,600
Speaker 3: Is not going to normalize is that I think the

305
00:16:28,680 --> 00:16:31,680
Speaker 3: pace of what we're seeing with the broader hyper scaler

306
00:16:31,720 --> 00:16:35,440
Speaker 3: build out and just kind of the cheat sheet here

307
00:16:35,520 --> 00:16:40,320
Speaker 3: is that the AI trade focuses. If you're going to

308
00:16:40,360 --> 00:16:43,800
Speaker 3: pick one data point, it's probably like hyperscaler cap BAX

309
00:16:43,840 --> 00:16:46,640
Speaker 3: growth is kind of like the key indicator about what

310
00:16:46,680 --> 00:16:48,560
Speaker 3: that's going to be next year for how the AI

311
00:16:48,680 --> 00:16:51,000
Speaker 3: build out and the AI trade is going to perform.

312
00:16:51,280 --> 00:16:54,400
Speaker 3: And a year ago, so a year ago in twenty

313
00:16:54,440 --> 00:16:56,960
Speaker 3: twenty six, the street is looking for about twenty percent growth.

314
00:16:57,000 --> 00:17:00,720
Speaker 3: It's going to be eighty percent next year. The streets

315
00:17:00,800 --> 00:17:04,280
Speaker 3: currently looking for twenty four percent growth. It was fifteen

316
00:17:04,359 --> 00:17:06,960
Speaker 3: percent growth about a month ago. But because of Micron

317
00:17:07,040 --> 00:17:09,680
Speaker 3: and it's going up. I think that a year from now,

318
00:17:10,119 --> 00:17:12,560
Speaker 3: i'd say this, in six months from now, I think

319
00:17:12,600 --> 00:17:14,359
Speaker 3: that that number, that average number is going to be

320
00:17:14,359 --> 00:17:17,560
Speaker 3: close to forty percent and ultimately end up above fifty.

321
00:17:18,040 --> 00:17:20,439
Speaker 3: And so maybe you could say that, like the second

322
00:17:20,480 --> 00:17:23,600
Speaker 3: derivative isn't getting this strong. So that's a form of normalization.

323
00:17:24,160 --> 00:17:27,439
Speaker 3: But the upside surprises that these companies can print, I

324
00:17:27,440 --> 00:17:30,840
Speaker 3: think over the next year will still be meaningful and surprising.

325
00:17:31,160 --> 00:17:33,879
Speaker 1: I got to ask you both about the bubble question.

326
00:17:34,040 --> 00:17:36,280
Speaker 1: I'm anticipating that you're going to tell me that we're

327
00:17:36,280 --> 00:17:38,399
Speaker 1: not in an AI bubble. But when you think about

328
00:17:38,480 --> 00:17:41,320
Speaker 1: the kind of numbers that you're mentioning their eighty plus

329
00:17:41,359 --> 00:17:44,600
Speaker 1: growth in terms of the trajectory of the AI build out,

330
00:17:44,600 --> 00:17:47,879
Speaker 1: and as I've been mentioning the triple digit growth in

331
00:17:47,960 --> 00:17:51,200
Speaker 1: terms of price of the chip stocks, the bubble question

332
00:17:51,440 --> 00:17:53,240
Speaker 1: has to be something you're considering, isn't it.

333
00:17:53,320 --> 00:17:57,399
Speaker 2: Dan. When it comes to the bubble, it's obviously a

334
00:17:57,600 --> 00:18:02,479
Speaker 2: huge talking point bulls bears go back to niney nine

335
00:18:02,520 --> 00:18:07,600
Speaker 2: and two thousands is another Bubble moment. I think it's

336
00:18:07,640 --> 00:18:10,960
Speaker 2: an apples to oranges because in my view, textocs call

337
00:18:11,000 --> 00:18:14,960
Speaker 2: it whatever you know mid twenty times in terms of earnings,

338
00:18:15,040 --> 00:18:17,720
Speaker 2: I go back to bubble the average techom ministrant thirty

339
00:18:17,760 --> 00:18:21,240
Speaker 2: times revenues. You have basically big tech with a trillion

340
00:18:21,280 --> 00:18:24,280
Speaker 2: dollars in the balance sheet. Find this versus you go

341
00:18:24,359 --> 00:18:26,199
Speaker 2: back to Bubble that was a lot of lever it

342
00:18:26,280 --> 00:18:30,040
Speaker 2: up balance sheets which basically no business models. I think

343
00:18:30,119 --> 00:18:32,800
Speaker 2: part of the problem is that I must say history

344
00:18:32,880 --> 00:18:35,159
Speaker 2: pizza self and always the worry, but there's always worris

345
00:18:35,160 --> 00:18:38,880
Speaker 2: that oh here we go again. But this is truly

346
00:18:39,440 --> 00:18:42,600
Speaker 2: a fourth and dush revolution. And I could argue the

347
00:18:42,640 --> 00:18:45,520
Speaker 2: Bubble period nine nine, two thousand we had the groundwork

348
00:18:45,560 --> 00:18:47,359
Speaker 2: from a fiver and really from the star of the

349
00:18:47,440 --> 00:18:50,240
Speaker 2: Internet to where we are today, and you could argue

350
00:18:50,280 --> 00:18:52,679
Speaker 2: it's really actually like a forty year cycle when you

351
00:18:52,680 --> 00:18:55,280
Speaker 2: actually put it together. That's why I'm just a believer.

352
00:18:55,480 --> 00:18:57,640
Speaker 2: We're in year three of eight ten year build out

353
00:18:58,359 --> 00:19:02,760
Speaker 2: Nazak thirty thousand from the rude to that for starters

354
00:19:03,280 --> 00:19:05,760
Speaker 2: and I just I'm not a believer in the bubble

355
00:19:05,800 --> 00:19:08,359
Speaker 2: given everything we see in Asia and overall demand.

356
00:19:08,560 --> 00:19:11,680
Speaker 1: We're speaking with Dan Ives, former global technology headed White

357
00:19:11,680 --> 00:19:15,480
Speaker 1: Bush Securities, along with Gene Munster, managing partner at deep

358
00:19:15,520 --> 00:19:19,720
Speaker 1: Water Asset Management. In terms of that question, Gene, how

359
00:19:19,720 --> 00:19:23,960
Speaker 1: do you answer some of those bearish names who might

360
00:19:24,040 --> 00:19:28,200
Speaker 1: be drawing comparison still to what we saw in the

361
00:19:28,680 --> 00:19:29,440
Speaker 1: dot com era.

362
00:19:29,880 --> 00:19:32,760
Speaker 3: I'm always I have to like check my answer based

363
00:19:32,800 --> 00:19:34,879
Speaker 3: on this idea of it's going to be different now,

364
00:19:34,920 --> 00:19:38,639
Speaker 3: like that like famous words that blow investors up. They

365
00:19:38,640 --> 00:19:40,280
Speaker 3: think it's going to be different this time, and then

366
00:19:40,400 --> 00:19:43,320
Speaker 3: history reverts back to the mean. And so I think

367
00:19:43,320 --> 00:19:47,000
Speaker 3: what Danced is is really sums up how I feel

368
00:19:47,040 --> 00:19:50,360
Speaker 3: about this is this is much bigger than any sort

369
00:19:50,400 --> 00:19:53,440
Speaker 3: of like little infrastructure build out. It's it's a it's

370
00:19:53,440 --> 00:19:56,480
Speaker 3: a tech revolution, it's it's it's a fundamental change in

371
00:19:56,520 --> 00:19:59,800
Speaker 3: how humanity happens. And I think that the trap is

372
00:20:00,040 --> 00:20:03,880
Speaker 3: to overweight to what happened in dot Com. That doesn't

373
00:20:03,920 --> 00:20:07,960
Speaker 3: mean you shouldn't be have some way of risk management,

374
00:20:08,000 --> 00:20:11,440
Speaker 3: but I think the trap is to overweight on that.

375
00:20:11,560 --> 00:20:13,399
Speaker 3: And specifically, I mean, if you're going to boil the

376
00:20:13,440 --> 00:20:16,959
Speaker 3: Internet down to its most basic level. What it was

377
00:20:17,119 --> 00:20:20,000
Speaker 3: is essentially what it ultimately was and all of its

378
00:20:20,040 --> 00:20:23,560
Speaker 3: forms that it took mobile to laying the groundwork for AI.

379
00:20:23,640 --> 00:20:28,560
Speaker 3: What it ultimately is is just a new distribution mechanism

380
00:20:28,840 --> 00:20:32,959
Speaker 3: for data. I mean, that's effectively what this all is.

381
00:20:33,480 --> 00:20:36,800
Speaker 3: So that's really important. And when I think about that's

382
00:20:36,880 --> 00:20:40,320
Speaker 3: kind of the the one oh one of what the

383
00:20:40,359 --> 00:20:44,520
Speaker 3: Internet bubble was all about different ways to use that

384
00:20:44,640 --> 00:20:49,959
Speaker 3: data create e commerce. AI to me feels different in

385
00:20:50,000 --> 00:20:54,840
Speaker 3: that it is what is the value of scale intelligence

386
00:20:54,920 --> 00:20:58,520
Speaker 3: at scale at very low cost? And I mean this

387
00:20:58,680 --> 00:21:01,520
Speaker 3: is just how very simplistically I think about it is.

388
00:21:01,560 --> 00:21:04,760
Speaker 3: To me, that's a bigger deal. That's a bigger opportunity

389
00:21:04,880 --> 00:21:09,199
Speaker 3: thinking is bigger than data distribution and well it seems

390
00:21:09,240 --> 00:21:14,040
Speaker 3: like pretty elementary. I think that ultimately that means that

391
00:21:14,080 --> 00:21:17,120
Speaker 3: we should not overweight on what happened.

392
00:21:17,320 --> 00:21:19,560
Speaker 1: One thing we haven't talked about is some of the

393
00:21:19,600 --> 00:21:24,960
Speaker 1: blowback that we've seen, not just from investors but from

394
00:21:25,760 --> 00:21:31,080
Speaker 1: regular people about artificial intelligence. We've seen you know, graduates

395
00:21:31,119 --> 00:21:35,760
Speaker 1: at college commencements booing speakers when they talk about the

396
00:21:35,760 --> 00:21:40,200
Speaker 1: AI development. That sort of thing. I think I've heard

397
00:21:40,200 --> 00:21:43,119
Speaker 1: you Dan talk about this as a PR problem for

398
00:21:44,119 --> 00:21:47,159
Speaker 1: these AI companies, But I mean, that's a pretty big

399
00:21:47,520 --> 00:21:48,880
Speaker 1: PR problem, isn't.

400
00:21:48,720 --> 00:21:53,240
Speaker 2: It look a lot of itself created. I mean, if

401
00:21:53,280 --> 00:21:56,280
Speaker 2: you go out there and tell people that they're going

402
00:21:56,359 --> 00:21:59,959
Speaker 2: to lose their jobs and then there are trisy bills

403
00:22:00,080 --> 00:22:02,720
Speaker 2: going to go up higher because the data center's being

404
00:22:02,720 --> 00:22:06,719
Speaker 2: built in their backyard, what's in it for them? It

405
00:22:06,800 --> 00:22:09,200
Speaker 2: just goes back to why you know, a while surveys

406
00:22:09,280 --> 00:22:12,680
Speaker 2: AI is like under long TSA lines, you know, when

407
00:22:12,720 --> 00:22:17,000
Speaker 2: it comes to survey data. The reality is is much

408
00:22:17,080 --> 00:22:21,240
Speaker 2: different than that dystopian view because, in my opinion, like

409
00:22:21,320 --> 00:22:23,280
Speaker 2: for the first time in thirty years, the US is

410
00:22:23,320 --> 00:22:26,919
Speaker 2: headed China when it comes to tech. Are there gonna

411
00:22:26,960 --> 00:22:30,800
Speaker 2: be changes in the job market, no doubt, But also

412
00:22:30,880 --> 00:22:32,280
Speaker 2: remember when it comes to like a lot of big

413
00:22:32,359 --> 00:22:38,560
Speaker 2: tech companies, like these companies basically hired city's worth of

414
00:22:38,720 --> 00:22:41,879
Speaker 2: people from COVID to now. So I'm just saying some

415
00:22:41,920 --> 00:22:44,560
Speaker 2: of those cuts sometimes get, you know, in terms of

416
00:22:44,600 --> 00:22:47,920
Speaker 2: the numbers, and I just think where we're just starting

417
00:22:47,960 --> 00:22:51,000
Speaker 2: to rip effect, more jobs will be created from AI

418
00:22:51,600 --> 00:22:54,160
Speaker 2: than taken away over the next five to ten years.

419
00:22:54,200 --> 00:22:57,159
Speaker 2: That's my view, but the PR pump. If you go

420
00:22:57,280 --> 00:23:00,919
Speaker 2: out there and you scare people saying, don't jump in

421
00:23:00,920 --> 00:23:04,600
Speaker 2: the pool because there's alligators, Yeah, you could understand why

422
00:23:04,600 --> 00:23:06,120
Speaker 2: people are afraid to go in the pool and while

423
00:23:06,160 --> 00:23:08,640
Speaker 2: they're against it. And I think that is a PR problem.

424
00:23:09,000 --> 00:23:12,400
Speaker 2: You've seen, you know, Altman change a bit, but obviously

425
00:23:12,440 --> 00:23:16,040
Speaker 2: in anthropic and others that continues to be I think

426
00:23:16,080 --> 00:23:19,080
Speaker 2: part of this sort of you know, tug of war

427
00:23:19,520 --> 00:23:23,160
Speaker 2: that you're seeing in terms of you know, the PR perspective.

428
00:23:22,880 --> 00:23:24,760
Speaker 1: And how do you see that tug of war playing

429
00:23:24,800 --> 00:23:27,160
Speaker 1: out over the next not just a few months, but

430
00:23:27,160 --> 00:23:30,240
Speaker 1: potentially a few years, Jane, I.

431
00:23:30,160 --> 00:23:34,320
Speaker 3: Mean, this may be one of those rare examples that

432
00:23:34,359 --> 00:23:36,399
Speaker 3: maybe we're Dan and I on a slightly different page.

433
00:23:36,560 --> 00:23:40,080
Speaker 3: I do think that ultimately we will see more job

434
00:23:40,160 --> 00:23:43,320
Speaker 3: creation with around AI, but I think there's a gap,

435
00:23:43,960 --> 00:23:47,800
Speaker 3: probably somewhere between a five and eight year gap, or

436
00:23:48,000 --> 00:23:50,480
Speaker 3: it takes kind of the world to kind of reassess.

437
00:23:50,680 --> 00:23:54,280
Speaker 3: I believe the biggest reason why we haven't seen more

438
00:23:54,400 --> 00:23:59,240
Speaker 3: headcount reductions is because it's just politically not acceptable within country.

439
00:23:59,280 --> 00:24:03,520
Speaker 3: Inside company needs to do this is I've talked to

440
00:24:03,840 --> 00:24:07,920
Speaker 3: leadership who've made aggressive changes related to AI, and it

441
00:24:07,960 --> 00:24:10,760
Speaker 3: can have a massive demoralizing effect on the ones that

442
00:24:10,840 --> 00:24:13,800
Speaker 3: are remaining, thinking they have to look over their shoulder,

443
00:24:13,840 --> 00:24:16,199
Speaker 3: maybe it's time for them to find something new. And

444
00:24:16,280 --> 00:24:19,760
Speaker 3: so I think there's kind of this natural like break

445
00:24:19,880 --> 00:24:24,520
Speaker 3: that's in place for companies really to fully embrace what

446
00:24:24,600 --> 00:24:28,080
Speaker 3: can be done with some of these agents. Eventually those

447
00:24:28,119 --> 00:24:31,560
Speaker 3: breaks come off. I don't think it's a wholesale come off,

448
00:24:31,600 --> 00:24:33,320
Speaker 3: but I think they do come off, and I think

449
00:24:33,320 --> 00:24:37,280
Speaker 3: we will see some elevated unemployment with knowledge workers. But

450
00:24:37,800 --> 00:24:40,960
Speaker 3: if in fact this is such a big opportunity around

451
00:24:41,200 --> 00:24:46,400
Speaker 3: intelligence at scale, humans will figure out ways to become valuable,

452
00:24:46,440 --> 00:24:49,639
Speaker 3: to leverage the tools themselves, to leverage their people skills,

453
00:24:49,640 --> 00:24:53,720
Speaker 3: whatever it may be, and ultimately I think that it

454
00:24:53,760 --> 00:24:56,399
Speaker 3: will create new opportunities, just like we saw with the

455
00:24:56,400 --> 00:24:59,680
Speaker 3: Internet and all the different industrial revolutions. But I'm a

456
00:24:59,720 --> 00:25:01,840
Speaker 3: little bit more and by the way, I debate this

457
00:25:01,960 --> 00:25:04,959
Speaker 3: topic internally at deep Water, and I'm the only one

458
00:25:05,240 --> 00:25:08,800
Speaker 3: who thinks that were headed over the next few years to.

459
00:25:08,760 --> 00:25:11,840
Speaker 4: Some elevated knowledge worker unemployment.

460
00:25:12,080 --> 00:25:14,800
Speaker 1: We'll continue this conversation with Gene Munster of deep Water

461
00:25:14,840 --> 00:25:18,720
Speaker 1: Asset Management and Dan Ives, formerly of Webbush Securities. As

462
00:25:18,800 --> 00:25:22,560
Speaker 1: this special holiday edition of Bloomberg Daybreak continues, It's thirty

463
00:25:22,560 --> 00:25:25,600
Speaker 1: seven minutes past the hour. I'm Nathan Hager, and this

464
00:25:26,080 --> 00:25:39,840
Speaker 1: is Bloomberg. Thanks again for being here on this special

465
00:25:39,960 --> 00:25:43,640
Speaker 1: edition of Bloomberg Daybreak. US markets are closed for America's

466
00:25:43,640 --> 00:25:46,640
Speaker 1: two hundred and fiftieth birthday. I'm Nathan Hager, and it's

467
00:25:46,640 --> 00:25:48,480
Speaker 1: time to close out this hour speaking with two of

468
00:25:48,480 --> 00:25:51,399
Speaker 1: the biggest names in tech on Wall Street. Dan Ives,

469
00:25:51,440 --> 00:25:55,520
Speaker 1: the former global technology head had Webbush Securities, and Gene Monster,

470
00:25:55,680 --> 00:25:59,000
Speaker 1: managing partner at Deepwater Asset Management. Again, we recorded this

471
00:25:59,040 --> 00:26:01,800
Speaker 1: conversation a few day before the holiday, but before we

472
00:26:01,840 --> 00:26:04,160
Speaker 1: get to some of the individual names that the two

473
00:26:04,240 --> 00:26:07,040
Speaker 1: of you cover, Gene, I know you have a few

474
00:26:07,080 --> 00:26:11,280
Speaker 1: thoughts here about what it means for America to hit

475
00:26:11,480 --> 00:26:12,760
Speaker 1: the big two five zero.

476
00:26:12,960 --> 00:26:16,439
Speaker 3: You know, we got to mark these big milestones. And

477
00:26:16,440 --> 00:26:18,720
Speaker 3: one of the things that I think about every Fourth

478
00:26:18,760 --> 00:26:21,800
Speaker 3: of July and make a special note today, is when

479
00:26:21,840 --> 00:26:25,000
Speaker 3: I think about probably the most like holy part of

480
00:26:25,040 --> 00:26:27,720
Speaker 3: American history, which is the Gettysburg Address. Kind of seems

481
00:26:27,760 --> 00:26:30,520
Speaker 3: like an off topic is this, of course, was in

482
00:26:30,560 --> 00:26:33,600
Speaker 3: the eighteen hundreds, not the seventeen seventy six. But I

483
00:26:33,680 --> 00:26:36,200
Speaker 3: just want people to get on the same page about

484
00:26:36,240 --> 00:26:38,399
Speaker 3: the Gettysburg Address for just a quick minute, Nathan. I

485
00:26:38,400 --> 00:26:42,760
Speaker 3: appreciate the time sure the Gettysburg Address. Many think most

486
00:26:42,800 --> 00:26:45,040
Speaker 3: people memorize it and they remember the first one or

487
00:26:45,080 --> 00:26:49,040
Speaker 3: two sentences of it, but most think it's about Lincoln's

488
00:26:49,040 --> 00:26:52,720
Speaker 3: commentary about slavery and a critical part about this division

489
00:26:52,800 --> 00:26:55,560
Speaker 3: of the states that was a big topic related to it.

490
00:26:56,000 --> 00:26:58,399
Speaker 3: But I just want to sum up what Lincoln says

491
00:26:58,440 --> 00:27:01,359
Speaker 3: in this He has asked to go to Gettysburg to

492
00:27:01,440 --> 00:27:06,679
Speaker 3: commemorate the fallen soldiers that had fought so bravely previously,

493
00:27:07,000 --> 00:27:09,840
Speaker 3: and he says in the address that he actually has

494
00:27:09,880 --> 00:27:12,200
Speaker 3: no power to do that, nothing to add or detract.

495
00:27:12,280 --> 00:27:15,800
Speaker 3: Only the men who bravely gave the full measure can

496
00:27:15,840 --> 00:27:17,760
Speaker 3: do that. And I thought, that's just amazing that the

497
00:27:17,760 --> 00:27:20,200
Speaker 3: President says, You've asked me to come here and do

498
00:27:20,240 --> 00:27:23,200
Speaker 3: something that I have no power to do. But then

499
00:27:23,240 --> 00:27:26,560
Speaker 3: he adds that there is something that we all can do,

500
00:27:26,720 --> 00:27:30,960
Speaker 3: which is take full this dedication that these soldiers have

501
00:27:31,080 --> 00:27:34,439
Speaker 3: given and finish the work that they started. And that

502
00:27:34,560 --> 00:27:38,480
Speaker 3: work that they started was to maintain essentially the greatest

503
00:27:38,760 --> 00:27:41,760
Speaker 3: thing on earth, which is a government for the people,

504
00:27:41,800 --> 00:27:45,680
Speaker 3: by the people, and that if we continue that, if

505
00:27:45,680 --> 00:27:47,879
Speaker 3: we continue the work of those people and get that

506
00:27:48,000 --> 00:27:51,119
Speaker 3: job done of maintaining that by the people, for the people,

507
00:27:51,560 --> 00:27:54,720
Speaker 3: that it shall never perish. And I think about all

508
00:27:54,760 --> 00:27:57,280
Speaker 3: the amazing things that we have around us. I think

509
00:27:57,280 --> 00:28:01,960
Speaker 3: about our lifestyle here, I think about all the technology innovation.

510
00:28:02,720 --> 00:28:05,480
Speaker 3: You know, at the very very baseline I think of

511
00:28:05,480 --> 00:28:08,960
Speaker 3: that is this incredible structure that we have here. And

512
00:28:09,040 --> 00:28:12,520
Speaker 3: so I just encourage people. It's short, it's a short,

513
00:28:13,119 --> 00:28:15,879
Speaker 3: a short read. Just to take a minute. It's two

514
00:28:15,960 --> 00:28:17,320
Speaker 3: hundred and fifty You won't have to do it again

515
00:28:17,359 --> 00:28:18,720
Speaker 3: for another two hundred and fifty years.

516
00:28:18,720 --> 00:28:21,320
Speaker 4: Just do it this time. Read the Gettysburg Address and

517
00:28:21,440 --> 00:28:22,119
Speaker 4: just savor it.

518
00:28:22,480 --> 00:28:26,560
Speaker 1: Yeah, Nation conceived in liberty one of the lines from

519
00:28:27,080 --> 00:28:30,480
Speaker 1: President Lincoln's Gettysburg Address. We're coming up on that anniversary

520
00:28:30,520 --> 00:28:35,560
Speaker 1: as well, that very important moment in the Civil War.

521
00:28:36,080 --> 00:28:39,480
Speaker 1: Thanks for bringing that to us, gee, I appreciate that.

522
00:28:40,040 --> 00:28:43,760
Speaker 1: As we close out this conversation though, on the tech space,

523
00:28:43,880 --> 00:28:46,800
Speaker 1: let's talk about some of those individual names that you

524
00:28:46,920 --> 00:28:49,960
Speaker 1: all focus on so closely. I'll start with you, Dan.

525
00:28:50,440 --> 00:28:53,080
Speaker 1: We were talking a bit about the dot com era,

526
00:28:53,440 --> 00:28:56,560
Speaker 1: and it just so happens that Microsoft is coming off

527
00:28:56,600 --> 00:29:00,640
Speaker 1: its worst month since y two K, losing more than

528
00:29:00,680 --> 00:29:04,120
Speaker 1: five hundred and seventy billion dollars in market value. There's

529
00:29:04,200 --> 00:29:08,560
Speaker 1: this question about where Microsoft is going to stand when

530
00:29:08,600 --> 00:29:10,960
Speaker 1: it comes to the AI race. Is there going to

531
00:29:10,960 --> 00:29:13,120
Speaker 1: be the focus on the cloud? Is there going to

532
00:29:13,160 --> 00:29:15,720
Speaker 1: be the focus on some of the software names that

533
00:29:15,760 --> 00:29:19,480
Speaker 1: Microsoft puts out that could be potentially disrupted by AI?

534
00:29:19,560 --> 00:29:21,560
Speaker 1: Where do you see things now when it comes to Microsoft.

535
00:29:22,520 --> 00:29:26,800
Speaker 2: I think Microsoft's the most over sold tech stoc, especially

536
00:29:26,800 --> 00:29:31,080
Speaker 2: when it comes to large cap. I think investors are

537
00:29:31,200 --> 00:29:37,760
Speaker 2: misreading or heavily discounting the success that they're going to

538
00:29:37,880 --> 00:29:43,200
Speaker 2: have in monetizing their core enterprise and install base around Azure,

539
00:29:43,960 --> 00:29:48,400
Speaker 2: as well as what I believe is probably an incremental

540
00:29:48,600 --> 00:29:54,560
Speaker 2: forty to fifty billion of crossow opportunities nolok Is Are

541
00:29:54,640 --> 00:30:01,720
Speaker 2: there competitive forces that could eat at some market chair? Yeah,

542
00:30:02,200 --> 00:30:05,520
Speaker 2: but when I look at the stock, I mean, I

543
00:30:05,600 --> 00:30:08,280
Speaker 2: believe this is five and fifty six und drawer stock,

544
00:30:08,720 --> 00:30:11,000
Speaker 2: and I think, just like off but a year ago,

545
00:30:11,160 --> 00:30:14,360
Speaker 2: with that narrative, they got way overdone we saw the rebound.

546
00:30:15,040 --> 00:30:18,560
Speaker 2: That's my view of Microsoft. I just think enterprise they

547
00:30:18,600 --> 00:30:21,320
Speaker 2: will own and they're going to be a core winner

548
00:30:21,320 --> 00:30:22,240
Speaker 2: when it comes to AI.

549
00:30:22,720 --> 00:30:24,239
Speaker 1: I did want to ask you a little bit more

550
00:30:24,280 --> 00:30:27,240
Speaker 1: about Apple Gene, because I know you follow that stock

551
00:30:27,400 --> 00:30:32,040
Speaker 1: very closely. They recently announced their increasing prices across much

552
00:30:32,080 --> 00:30:34,800
Speaker 1: of their product line because of the what we talked

553
00:30:34,800 --> 00:30:38,000
Speaker 1: about for so much of this hour, memory chip prices.

554
00:30:39,440 --> 00:30:42,760
Speaker 1: Where do you see things going for Apple? Are these

555
00:30:42,800 --> 00:30:46,479
Speaker 1: price increases going to be an issue for Apple fans?

556
00:30:46,840 --> 00:30:50,560
Speaker 3: I mean, I'd kind of revisit my price elasticty curs

557
00:30:50,560 --> 00:30:54,360
Speaker 3: from back in school, and in this case, I generally

558
00:30:54,400 --> 00:30:57,760
Speaker 3: see Apple's products as being inelastic demand. That means a

559
00:30:57,880 --> 00:31:03,400
Speaker 3: large increase in price has a less big, less negative

560
00:31:03,440 --> 00:31:07,440
Speaker 3: impact on demand, and so these tend to be when

561
00:31:07,520 --> 00:31:10,880
Speaker 3: consumers are relatively priced takers. Now, if we look at

562
00:31:10,880 --> 00:31:12,880
Speaker 3: the average price increase, if it ends up being twenty

563
00:31:12,880 --> 00:31:15,800
Speaker 3: percent across all their products, that could be around two

564
00:31:15,840 --> 00:31:17,960
Speaker 3: hundred dollars. If you look at a Mac for example,

565
00:31:18,120 --> 00:31:20,880
Speaker 3: average life of the initial Mac four and a half years,

566
00:31:21,280 --> 00:31:23,960
Speaker 3: that adds right around three to four dollars per month.

567
00:31:24,000 --> 00:31:26,760
Speaker 3: Now people per month over the lifetime, so it's relatively small.

568
00:31:27,080 --> 00:31:29,280
Speaker 3: Consumers don't think about it generally like that. They think

569
00:31:29,320 --> 00:31:31,480
Speaker 3: about cost an extra two hundred bucks. So there is

570
00:31:31,520 --> 00:31:36,600
Speaker 3: going to be some demand destruction, but I think in

571
00:31:36,760 --> 00:31:40,480
Speaker 3: large part, the vast majority of this kind of comes together.

572
00:31:40,520 --> 00:31:41,880
Speaker 3: And now, if I was going to put it together

573
00:31:42,520 --> 00:31:44,640
Speaker 3: really rough numbers, here is kind of for next year.

574
00:31:44,680 --> 00:31:48,120
Speaker 3: The Street's high four hundred billions in revenue for Apple.

575
00:31:48,240 --> 00:31:51,440
Speaker 3: I think the price increase, factoring in they're going to

576
00:31:51,480 --> 00:31:54,240
Speaker 3: lose some customers, is going to add about thirty five

577
00:31:54,240 --> 00:31:57,720
Speaker 3: billion to revenue, which is pretty similar to probably what

578
00:31:57,760 --> 00:32:00,480
Speaker 3: their incremental costs around memory are. We'll see it happens

579
00:32:00,480 --> 00:32:03,440
Speaker 3: with this China opportunity. So I think kind of the

580
00:32:03,480 --> 00:32:05,320
Speaker 3: net of this is you're gonna see growth rates next

581
00:32:05,400 --> 00:32:08,880
Speaker 3: year probably eleven to twelve percent versus the Street at

582
00:32:08,920 --> 00:32:13,200
Speaker 3: six percent, so meaningfully higher, and margins probably similar. I'd

583
00:32:13,200 --> 00:32:15,440
Speaker 3: be very curious Dan, how you think about the margin question.

584
00:32:15,440 --> 00:32:16,800
Speaker 3: I'm sure you've given a lot of thought over the

585
00:32:16,840 --> 00:32:19,960
Speaker 3: past few days that, yeh, the speet's at forty nine percent.

586
00:32:20,000 --> 00:32:21,960
Speaker 3: I kind of think that's probably a good number for

587
00:32:22,040 --> 00:32:24,000
Speaker 3: next year as well as similar margins.

588
00:32:24,080 --> 00:32:25,719
Speaker 4: Is this year Nathan.

589
00:32:25,800 --> 00:32:29,880
Speaker 2: That's why they call gene Tex north Star. It's like

590
00:32:31,240 --> 00:32:36,760
Speaker 2: because he what he said poetic, I mean not Gaysberger

591
00:32:36,840 --> 00:32:42,360
Speaker 2: dress like, but poetics because because it look that's far

592
00:32:42,400 --> 00:32:45,320
Speaker 2: as the trees like. In terms of what Apple's doing.

593
00:32:45,520 --> 00:32:49,440
Speaker 2: We know the price increases, Yeah, they they're going to

594
00:32:49,560 --> 00:32:53,080
Speaker 2: navigate into the takeoff called one hundred bits off gross

595
00:32:53,080 --> 00:32:58,240
Speaker 2: margin max possible, but the churn rate's going to be small.

596
00:32:58,520 --> 00:33:01,520
Speaker 2: The reaction has been dramatic in terms of what we

597
00:33:01,560 --> 00:33:04,479
Speaker 2: see with the stock. And this is also Apple going

598
00:33:04,560 --> 00:33:08,600
Speaker 2: into probably what's gonna be their strongest three year product

599
00:33:08,680 --> 00:33:11,479
Speaker 2: cycle ever. You know, when you start to think about

600
00:33:11,760 --> 00:33:14,800
Speaker 2: how they've laid out for AI and ultimately AI power

601
00:33:14,880 --> 00:33:18,440
Speaker 2: devices across the hole sort of spectrum that's turners what

602
00:33:18,440 --> 00:33:22,000
Speaker 2: what he'll ultimately build. So I just think it's right time,

603
00:33:22,080 --> 00:33:23,120
Speaker 2: right place to do this.

604
00:33:23,480 --> 00:33:26,600
Speaker 1: We're speaking with Dan Ives, former global technology headed White

605
00:33:26,640 --> 00:33:32,160
Speaker 1: Bush Securities, and Gene Munster, managing partner at Deepwater Asset Management. Dan,

606
00:33:32,240 --> 00:33:35,000
Speaker 1: I want to ask you about meta platforms as well.

607
00:33:35,640 --> 00:33:38,240
Speaker 1: This one's been through quite a few ups and downs

608
00:33:38,280 --> 00:33:40,680
Speaker 1: over the last few months. You still bullish on Meta.

609
00:33:41,880 --> 00:33:45,000
Speaker 2: Look, it's being treated like the mets of tech rights.

610
00:33:45,320 --> 00:33:48,640
Speaker 2: I mean, obviously you know, no, no, allot that's self

611
00:33:48,680 --> 00:33:52,680
Speaker 2: inflicted may bike mets as well. But when you look

612
00:33:52,720 --> 00:33:57,440
Speaker 2: at meta, the cap acts will result monization of your

613
00:33:57,480 --> 00:34:02,960
Speaker 2: talking three billion plus users on the advertising side on

614
00:34:03,160 --> 00:34:06,640
Speaker 2: Instagram on what you see when it comes to advertising

615
00:34:07,000 --> 00:34:10,760
Speaker 2: really across the whole platform. They're in a media rare pocket.

616
00:34:11,280 --> 00:34:13,799
Speaker 2: You can't have dog eate the homework type quarters like

617
00:34:13,840 --> 00:34:16,600
Speaker 2: they had last quarter. But I just think this is

618
00:34:16,719 --> 00:34:18,880
Speaker 2: way way over there. And unless you think this is

619
00:34:19,320 --> 00:34:22,920
Speaker 2: a business model that's going to be destructed, this stock

620
00:34:23,120 --> 00:34:24,319
Speaker 2: is a queer buy.

621
00:34:25,239 --> 00:34:28,280
Speaker 1: I can't let either of you guys go without asking

622
00:34:28,320 --> 00:34:33,040
Speaker 1: you about SpaceX. The stock has almost acted like one

623
00:34:33,040 --> 00:34:36,239
Speaker 1: of Elon Musk's own rockets since the IPO, shooting up

624
00:34:36,320 --> 00:34:40,000
Speaker 1: past the stratosphere and now basically kind of landing like

625
00:34:40,080 --> 00:34:43,400
Speaker 1: it's on a barge where it was close to the

626
00:34:43,400 --> 00:34:47,920
Speaker 1: IPO price gene. Where do you see SpaceX going in

627
00:34:47,960 --> 00:34:49,160
Speaker 1: the next few months or years?

628
00:34:49,600 --> 00:34:54,480
Speaker 3: Two answers. The next few months. I think that you know,

629
00:34:54,520 --> 00:34:56,520
Speaker 3: it's going to be pretty choppier on the stock, and

630
00:34:56,600 --> 00:34:59,359
Speaker 3: I think there's so much noise around these lockups coming

631
00:34:59,440 --> 00:35:02,520
Speaker 3: off and and not just the noise around the lockups,

632
00:35:02,560 --> 00:35:05,160
Speaker 3: but concern around investors about what the impact of the

633
00:35:05,200 --> 00:35:07,640
Speaker 3: lockups is going to be is probably more the substance,

634
00:35:08,239 --> 00:35:10,080
Speaker 3: and that's going to probably be kind of a six

635
00:35:10,160 --> 00:35:13,919
Speaker 3: month period when really it's not trading on the true opportunity.

636
00:35:14,600 --> 00:35:17,040
Speaker 3: I think it's more of that kind of psychological piece.

637
00:35:17,080 --> 00:35:21,040
Speaker 3: If you think about beyond this near term trading, this

638
00:35:21,120 --> 00:35:24,200
Speaker 3: company right now called a two trillion dollar market cap,

639
00:35:24,320 --> 00:35:26,799
Speaker 3: this is a potential to be a much bigger and

640
00:35:26,960 --> 00:35:30,360
Speaker 3: should by all measures, be the largest company in the world.

641
00:35:30,400 --> 00:35:33,359
Speaker 3: I think that what they have, the assets they have

642
00:35:33,719 --> 00:35:37,640
Speaker 3: are unique, and separately, I think what they're doing around AI,

643
00:35:37,760 --> 00:35:41,200
Speaker 3: and this we refer to as sovereign AI is basically

644
00:35:41,280 --> 00:35:43,680
Speaker 3: and then everything from energy to chips all the way

645
00:35:43,719 --> 00:35:47,920
Speaker 3: to distribution is something that really no other company can touch.

646
00:35:48,000 --> 00:35:51,000
Speaker 3: And So, going back to the start of our conversation

647
00:35:51,120 --> 00:35:55,880
Speaker 3: today about what this chapter, this industrial tech revolution that's

648
00:35:55,960 --> 00:35:59,600
Speaker 3: going on, if you believe that, then it would make

649
00:35:59,680 --> 00:36:03,000
Speaker 3: sense to believe that SpaceX is probably the best position

650
00:36:03,120 --> 00:36:05,160
Speaker 3: company within that opportunity.

651
00:36:05,239 --> 00:36:06,959
Speaker 4: So long term, I'm very bullish.

652
00:36:06,880 --> 00:36:10,719
Speaker 1: Dan, do you see SpaceX paying off on you know,

653
00:36:10,800 --> 00:36:13,000
Speaker 1: so many of the ambitions that Elon Musk has put

654
00:36:13,040 --> 00:36:17,280
Speaker 1: out there, from orbital data centers to getting people on Mars.

655
00:36:17,320 --> 00:36:19,879
Speaker 1: I mean we've seen the likes of you know, Softbanks,

656
00:36:20,120 --> 00:36:23,200
Speaker 1: Masioshi San throwing cold water on the whole orbital data

657
00:36:23,280 --> 00:36:23,840
Speaker 1: center idea.

658
00:36:24,760 --> 00:36:26,800
Speaker 2: Yeah. Look, I just view first of all, those that

659
00:36:26,920 --> 00:36:29,839
Speaker 2: bet against Musk have been proved wrong and again again

660
00:36:29,920 --> 00:36:32,000
Speaker 2: you know when it comes to tests and obviously you

661
00:36:32,040 --> 00:36:35,120
Speaker 2: know SpaceX and so many others. Look, my view is

662
00:36:35,920 --> 00:36:41,160
Speaker 2: it's really more around AI and data as much as

663
00:36:41,239 --> 00:36:44,680
Speaker 2: it is space because when you start to put all

664
00:36:44,680 --> 00:36:47,480
Speaker 2: together with the XII and ultimately my view, you know,

665
00:36:47,600 --> 00:36:51,000
Speaker 2: eighty percent chance that they acquire Tesla. I mean it

666
00:36:51,080 --> 00:36:55,000
Speaker 2: will be from a data perspective, basically probably the most

667
00:36:55,080 --> 00:36:59,960
Speaker 2: valuable company in the world from from a data capacity perspective.

668
00:37:00,560 --> 00:37:02,839
Speaker 2: I think that's so important when you talk about data

669
00:37:02,840 --> 00:37:05,200
Speaker 2: senters in space and when's it happened. Some of the

670
00:37:05,280 --> 00:37:08,440
Speaker 2: SpaceX launches. Obviously those are all going to be devils

671
00:37:08,440 --> 00:37:11,800
Speaker 2: in the details, but you know that's really the vision

672
00:37:12,000 --> 00:37:13,080
Speaker 2: what Musk is building.

673
00:37:13,719 --> 00:37:16,320
Speaker 1: Before I let both of you go just rapid fire

674
00:37:17,360 --> 00:37:19,640
Speaker 1: stock to avoid gene monster.

675
00:37:20,600 --> 00:37:25,319
Speaker 3: Does it have to be in tech, Nathan, does? I'm

676
00:37:25,400 --> 00:37:28,160
Speaker 3: still just so optimistic. I mean, I can say this

677
00:37:28,480 --> 00:37:32,319
Speaker 3: is that we're big, this isn't avoid but I think

678
00:37:32,440 --> 00:37:35,520
Speaker 3: just to some general commentary is a few months ago

679
00:37:35,600 --> 00:37:37,120
Speaker 3: we sold our in video position.

680
00:37:38,080 --> 00:37:38,920
Speaker 4: Numbers have gone up.

681
00:37:39,000 --> 00:37:41,839
Speaker 3: Stock really hasn't done much, but I think that's one

682
00:37:41,920 --> 00:37:45,759
Speaker 3: where you probably have your money is better spent in

683
00:37:45,880 --> 00:37:48,280
Speaker 3: like an Apple or Microsoft than in video.

684
00:37:48,640 --> 00:37:50,400
Speaker 1: How about you, Dan, are there any stocks in your

685
00:37:50,560 --> 00:37:52,280
Speaker 1: portfolio that you're ditching?

686
00:37:53,400 --> 00:37:55,920
Speaker 2: I mean, look to me, it's it's ones on the

687
00:37:56,040 --> 00:37:59,080
Speaker 2: software side. They're heavily exposed to some of the AI

688
00:37:59,200 --> 00:38:03,239
Speaker 2: turns in the naked so whether that's Nice Systems, UiPath

689
00:38:03,360 --> 00:38:04,920
Speaker 2: and others. I think those are the ones that you

690
00:38:05,040 --> 00:38:08,680
Speaker 2: tend to be more weary of. Adobe clearly has a

691
00:38:08,920 --> 00:38:11,600
Speaker 2: huge hurdle that they need to get through. Those are

692
00:38:11,600 --> 00:38:13,880
Speaker 2: the ones I would focus on to avoid.

693
00:38:14,280 --> 00:38:17,799
Speaker 1: Really appreciate the time as always, and thanks for making

694
00:38:17,880 --> 00:38:21,240
Speaker 1: this a holiday tradition for us. Dan Ives, former global

695
00:38:21,320 --> 00:38:25,000
Speaker 1: tech head at Webbush Securities and Gene Monster, managing partner

696
00:38:25,400 --> 00:38:28,399
Speaker 1: at Deepwater Asset Management, here with us for the full

697
00:38:28,480 --> 00:38:31,040
Speaker 1: hour on this fourth of July holiday, And thanks to

698
00:38:31,120 --> 00:38:32,759
Speaker 1: you as well for taking the time out of your

699
00:38:32,840 --> 00:38:34,960
Speaker 1: long holiday weekend to join us, and we hope everyone

700
00:38:35,080 --> 00:38:37,920
Speaker 1: has a safe and happy two hundred and fiftieth birthday

701
00:38:38,000 --> 00:38:41,960
Speaker 1: celebration for the USA, I'm Nathan Hager. Stay with US

702
00:38:42,200 --> 00:38:45,279
Speaker 1: top stories and global business headlines are coming up right

703
00:38:45,360 --> 00:38:45,480
Speaker 1: now