1 00:00:02,720 --> 00:00:09,040 Speaker 1: Bloomberg Audio Studios, podcasts, radio news, and Android auto with 2 00:00:09,119 --> 00:00:12,240 Speaker 1: the Bloomberg Business App. Listen on demand wherever you get 3 00:00:12,240 --> 00:00:15,040 Speaker 1: your podcasts, or watch us live on YouTube. 4 00:00:15,280 --> 00:00:17,480 Speaker 2: Okay, market's the equity market not doing much, but it's 5 00:00:17,480 --> 00:00:19,240 Speaker 2: the long end of the bond market that's getting hit 6 00:00:19,280 --> 00:00:21,960 Speaker 2: pretty hard with yields moving higher. Carol Pepper, founder and 7 00:00:22,079 --> 00:00:24,520 Speaker 2: CEO at Pepper International, joins us. 8 00:00:24,520 --> 00:00:24,680 Speaker 3: Now. 9 00:00:25,040 --> 00:00:27,360 Speaker 2: Carol, if we take a look at what's happening in 10 00:00:27,400 --> 00:00:29,639 Speaker 2: the long end of the bond market, what point do 11 00:00:29,800 --> 00:00:32,360 Speaker 2: yield start to impact the equity market. 12 00:00:33,440 --> 00:00:35,720 Speaker 4: Well, I think we're not too far from it. But 13 00:00:35,800 --> 00:00:38,960 Speaker 4: I think again, people are sort of hoping that this 14 00:00:39,040 --> 00:00:40,640 Speaker 4: will be a temporary. 15 00:00:40,080 --> 00:00:41,920 Speaker 5: Spike everyone's talking about. 16 00:00:41,920 --> 00:00:44,760 Speaker 4: In twenty eleven, the spike didn't last, so I think 17 00:00:44,760 --> 00:00:48,520 Speaker 4: there's similarly people not wanting to be headfaked, not wanting 18 00:00:48,560 --> 00:00:50,960 Speaker 4: to think that it's going to get a lot worse 19 00:00:51,000 --> 00:00:53,560 Speaker 4: than it is. The news have been known for a 20 00:00:53,600 --> 00:00:56,960 Speaker 4: long time. It's not a huge surprise. It's disappointing, of course, 21 00:00:57,680 --> 00:00:59,760 Speaker 4: and signals that at some point the US has to 22 00:00:59,800 --> 00:01:02,920 Speaker 4: get its deficit under control. But I think people are 23 00:01:03,000 --> 00:01:04,680 Speaker 4: just kind of going to take it in stride. That's 24 00:01:04,680 --> 00:01:07,240 Speaker 4: why you don't see the markets moving much today. There 25 00:01:07,240 --> 00:01:10,960 Speaker 4: are other potential moves of foot. What's going to happen 26 00:01:11,000 --> 00:01:12,520 Speaker 4: with the tariffs, what's going. 27 00:01:12,440 --> 00:01:14,600 Speaker 5: To happen with the tax builders. Is it actually going 28 00:01:14,640 --> 00:01:16,160 Speaker 5: to get passed? And in what form? 29 00:01:16,240 --> 00:01:19,520 Speaker 4: There are other more driving factors I think for the 30 00:01:19,560 --> 00:01:23,040 Speaker 4: markets right now. This is just sort of a disappointing 31 00:01:23,440 --> 00:01:24,920 Speaker 4: acknowledgment of reality. 32 00:01:25,880 --> 00:01:26,160 Speaker 6: Carol. 33 00:01:26,319 --> 00:01:28,399 Speaker 3: I know that you and the family offices that you 34 00:01:28,480 --> 00:01:33,200 Speaker 3: work with have for a long time been a tech bulls. 35 00:01:33,520 --> 00:01:36,960 Speaker 3: Do you use trading down days as an opportunity to 36 00:01:37,000 --> 00:01:39,280 Speaker 3: add to those positions here? Do you still think tech 37 00:01:39,280 --> 00:01:40,160 Speaker 3: can leave this market? 38 00:01:41,400 --> 00:01:44,679 Speaker 5: Absolutely? I don't know when, so it may not be 39 00:01:44,760 --> 00:01:45,160 Speaker 5: this year. 40 00:01:45,319 --> 00:01:47,160 Speaker 4: By the way, it may not be this year because 41 00:01:47,200 --> 00:01:49,680 Speaker 4: there are other factors out of the hands of the 42 00:01:49,680 --> 00:01:53,160 Speaker 4: market that are driving things, namely policies out of Washington. 43 00:01:53,240 --> 00:01:55,800 Speaker 4: So as long as Washington's driving the bus right now, 44 00:01:56,240 --> 00:01:58,760 Speaker 4: it's very hard for the markets to do anything other 45 00:01:58,840 --> 00:02:01,080 Speaker 4: than react, as we you know of seeing the Fed 46 00:02:01,160 --> 00:02:04,640 Speaker 4: can only react, everybody can only react at this point. However, 47 00:02:04,680 --> 00:02:07,520 Speaker 4: that doesn't mean that Amazon isn't holding its value, that 48 00:02:07,640 --> 00:02:11,720 Speaker 4: Nvidia isn't holding its value that Microsoft isn't holding its value. 49 00:02:11,760 --> 00:02:14,720 Speaker 4: So if you're underweight in your tech positions because you 50 00:02:14,840 --> 00:02:18,200 Speaker 4: felt it was too expensive before this period, might be 51 00:02:18,280 --> 00:02:20,160 Speaker 4: a good time to get in on a fair day 52 00:02:20,200 --> 00:02:23,359 Speaker 4: and up your positions of it, because those are leaders 53 00:02:23,400 --> 00:02:25,040 Speaker 4: and they will continue to lead. 54 00:02:25,560 --> 00:02:27,959 Speaker 2: We have a breaking headline here from Reuters saying that 55 00:02:28,040 --> 00:02:30,359 Speaker 2: nip On Steel is going to invest fourteen billion dollars 56 00:02:30,400 --> 00:02:35,000 Speaker 2: in US steel If Trump okays that takeover deal. According 57 00:02:35,040 --> 00:02:37,480 Speaker 2: to reports, it will be about four billion dollars for 58 00:02:37,600 --> 00:02:40,520 Speaker 2: a new mill, a new steel mill. Just take that 59 00:02:40,600 --> 00:02:44,480 Speaker 2: in for a second. That'd be huge. Carol, you mentioned 60 00:02:44,480 --> 00:02:47,360 Speaker 2: tech like buy on the dip, right, the valuations make sense. 61 00:02:47,600 --> 00:02:50,440 Speaker 2: Do you feel like there is FOMO right now on tech? 62 00:02:52,080 --> 00:02:55,040 Speaker 4: Not yet, but I do think that there are people 63 00:02:55,040 --> 00:02:58,560 Speaker 4: that missed it completely before, people that were extremely skeptical 64 00:02:58,560 --> 00:02:59,840 Speaker 4: and are very underweight. 65 00:03:00,680 --> 00:03:02,240 Speaker 5: So I don't know if it's FOMA, but I. 66 00:03:02,160 --> 00:03:04,079 Speaker 4: Do think it's not a bad time to get in 67 00:03:04,520 --> 00:03:07,959 Speaker 4: and remember things like AI and the IoT technology that 68 00:03:08,000 --> 00:03:10,000 Speaker 4: it's going to allow you to have data on every 69 00:03:10,200 --> 00:03:13,240 Speaker 4: type of manufacturing that we do in the United States 70 00:03:13,960 --> 00:03:18,280 Speaker 4: thanks to these new manufacturing policies, will need AI, will 71 00:03:18,280 --> 00:03:20,960 Speaker 4: need IoT sensors will need all of the things that 72 00:03:21,040 --> 00:03:23,680 Speaker 4: tech is building for us. And I can tell you 73 00:03:23,760 --> 00:03:26,680 Speaker 4: that many family offices right now are actively investing in 74 00:03:26,800 --> 00:03:27,560 Speaker 4: data centers. 75 00:03:28,160 --> 00:03:30,600 Speaker 5: Data centers are being built all over the country. 76 00:03:31,120 --> 00:03:34,840 Speaker 4: The municipal governments, for example, in the state of Oklahoma, 77 00:03:35,440 --> 00:03:39,640 Speaker 4: the state governments are actively partnering with private sector to 78 00:03:39,760 --> 00:03:43,160 Speaker 4: build more capacity for AI and technology in this country 79 00:03:43,200 --> 00:03:47,000 Speaker 4: over the next ten twenty four months. So don't count 80 00:03:47,080 --> 00:03:49,120 Speaker 4: tech out. It's not out at all. It's just a 81 00:03:49,200 --> 00:03:52,960 Speaker 4: question of when the market starts driving, rather than the policy. 82 00:03:53,640 --> 00:03:56,000 Speaker 3: Hey, Carol, there was a time earlier this year when 83 00:03:56,040 --> 00:04:00,120 Speaker 3: the markets are really trying to digest all these new tariffs, 84 00:04:00,680 --> 00:04:02,560 Speaker 3: people said, hey, how about the rest of the world. 85 00:04:02,600 --> 00:04:05,600 Speaker 3: We saw a lot of capital flow from US equity markets, 86 00:04:05,640 --> 00:04:10,120 Speaker 3: bond markets overseas, particularly to Europe. Is that something you 87 00:04:10,160 --> 00:04:11,040 Speaker 3: think is still viable? 88 00:04:12,120 --> 00:04:14,640 Speaker 5: Yes, I do think that finally we'll see some movement 89 00:04:14,640 --> 00:04:15,040 Speaker 5: in Europe. 90 00:04:15,040 --> 00:04:18,839 Speaker 4: We've had ten to fifteen twenty years of US exceptionalism 91 00:04:19,200 --> 00:04:20,760 Speaker 4: when it really didn't make a lot of sense to 92 00:04:20,800 --> 00:04:22,560 Speaker 4: diversify that much outside. 93 00:04:22,200 --> 00:04:25,599 Speaker 5: Of the US. But now Europe is looking more interesting again. 94 00:04:25,640 --> 00:04:30,320 Speaker 4: They're uniting, they're actively rebuilding defense stocks and they're trying 95 00:04:30,360 --> 00:04:33,920 Speaker 4: to kind of take a bigger role in their own defense, 96 00:04:34,000 --> 00:04:35,920 Speaker 4: and I think that's an area where we can really 97 00:04:36,279 --> 00:04:37,880 Speaker 4: potentially make some money this year. 98 00:04:37,920 --> 00:04:39,520 Speaker 5: I don't think it's a bad thing that Europe is 99 00:04:39,560 --> 00:04:40,719 Speaker 5: going to step up to the plate. 100 00:04:41,320 --> 00:04:43,520 Speaker 4: And there are some people rotating out of the United 101 00:04:43,560 --> 00:04:45,880 Speaker 4: States for other reasons, and the first place they're going 102 00:04:45,920 --> 00:04:49,440 Speaker 4: to go is Europe. It's perceived as less risky then 103 00:04:49,480 --> 00:04:51,359 Speaker 4: let's say emerging markets or Asia. 104 00:04:52,000 --> 00:04:53,920 Speaker 5: So yes, Europe. 105 00:04:53,720 --> 00:04:55,680 Speaker 4: Is a good place if you're thinking of sticking your 106 00:04:55,680 --> 00:04:58,039 Speaker 4: toe in the water and going outside the US right now. 107 00:04:58,720 --> 00:05:00,360 Speaker 3: Very good, Carol, Thank you so much for We really 108 00:05:00,400 --> 00:05:04,400 Speaker 3: appreciate it. Carol Pepper, founder and CEO of Pepper International. 109 00:05:06,120 --> 00:05:09,800 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 110 00:05:09,880 --> 00:05:13,279 Speaker 1: weekdays at ten am Eastern on Applecarclay and Android Auto 111 00:05:13,400 --> 00:05:16,440 Speaker 1: with the Bloomberg Business App. Listen on demand wherever you 112 00:05:16,480 --> 00:05:19,480 Speaker 1: get your podcasts, or watch us live on YouTube. 113 00:05:19,960 --> 00:05:22,440 Speaker 3: The Alextel Paul Swooney live here in our Bloomberg Interactive 114 00:05:22,440 --> 00:05:26,000 Speaker 3: Broker Studio streaming live on YouTube as well, and starting today, 115 00:05:26,040 --> 00:05:30,080 Speaker 3: the video presentations of Bloomberg Intelligence and Balance of power. 116 00:05:30,440 --> 00:05:33,360 Speaker 3: We'll be running live on Bloomberg Originals. That's on your 117 00:05:33,360 --> 00:05:36,880 Speaker 3: smart TV, Roku TV, Samsung TV, all that kind of 118 00:05:36,920 --> 00:05:38,800 Speaker 3: good smart TV stuff. So we're there as well. So 119 00:05:38,839 --> 00:05:42,880 Speaker 3: we welcome that audience to Bloomberg Intelligence. Philolando Joins is here, 120 00:05:42,960 --> 00:05:46,160 Speaker 3: chief equity market strategist and head of Client portfolio Management 121 00:05:46,240 --> 00:05:49,440 Speaker 3: at Federated at Hermes. Phil, it seems like, you know, 122 00:05:49,760 --> 00:05:53,119 Speaker 3: this market has retraced much of its peak to trough 123 00:05:53,200 --> 00:05:56,039 Speaker 3: fall here just over the last several weeks as we 124 00:05:56,080 --> 00:05:58,760 Speaker 3: get maybe a little bit more clarity on the tariffs, 125 00:05:58,960 --> 00:06:02,279 Speaker 3: but a tremendous amount of volatility down then up. Where 126 00:06:02,279 --> 00:06:02,960 Speaker 3: do we go from here? 127 00:06:05,240 --> 00:06:08,159 Speaker 6: Good morning, Paul, Thank you very much for having me back. 128 00:06:08,880 --> 00:06:10,800 Speaker 6: I think you've hit the nail on the head that 129 00:06:11,240 --> 00:06:15,040 Speaker 6: the volatility over the last six weeks, looking at something 130 00:06:15,080 --> 00:06:19,239 Speaker 6: like the vixendix as an example, you know, went from 131 00:06:19,279 --> 00:06:22,440 Speaker 6: like fifteen to sixty and is now back in the 132 00:06:22,480 --> 00:06:26,360 Speaker 6: mid teen so the volatility is completely round tripped. Same 133 00:06:26,400 --> 00:06:31,040 Speaker 6: story with the equity market. You know, from the Liberation 134 00:06:31,320 --> 00:06:38,599 Speaker 6: Day announcement on April second, market dropped like fifteen percent 135 00:06:39,320 --> 00:06:41,080 Speaker 6: and then over the course of the last six weeks 136 00:06:41,160 --> 00:06:43,520 Speaker 6: or so, we've rallied, like I don't know, twenty one 137 00:06:43,520 --> 00:06:45,680 Speaker 6: to twenty two percent. We've gotten all the money back. 138 00:06:45,800 --> 00:06:50,000 Speaker 6: So we're now, you know, back ahead of where we were. 139 00:06:50,400 --> 00:06:52,880 Speaker 6: And so now, you know, I guess investors are asking 140 00:06:52,920 --> 00:06:56,120 Speaker 6: the question, well, what's next. You know, we're heading into 141 00:06:56,720 --> 00:07:00,000 Speaker 6: what typically is a seasonally sluggish time of the year, 142 00:07:00,000 --> 00:07:03,400 Speaker 6: you know, the sell and may go away period, you know. 143 00:07:03,440 --> 00:07:05,800 Speaker 6: But the underlying fundamentals of the market I think are 144 00:07:05,839 --> 00:07:10,280 Speaker 6: going to be driving the bus here, and what has 145 00:07:10,400 --> 00:07:16,320 Speaker 6: lately improved the prospects of the market are two things. 146 00:07:16,400 --> 00:07:21,000 Speaker 6: Number One, we're making some positive progress with the tariff negotiations, 147 00:07:21,880 --> 00:07:25,000 Speaker 6: you know, with the UK and China, and the hope 148 00:07:25,080 --> 00:07:28,280 Speaker 6: is that there's another you know, a dozen or eighteen 149 00:07:28,400 --> 00:07:32,920 Speaker 6: or so countries that are sort of in the mix 150 00:07:33,040 --> 00:07:36,200 Speaker 6: now and we'll get some positive announcements in coming days 151 00:07:36,280 --> 00:07:40,640 Speaker 6: or weeks. And then second is that when you actually 152 00:07:40,680 --> 00:07:43,520 Speaker 6: look at the data that that you know drives the market, 153 00:07:44,240 --> 00:07:48,320 Speaker 6: we've got this ongoing tug of war, you know, between 154 00:07:48,440 --> 00:07:51,120 Speaker 6: the hard data which has been which has been fine, 155 00:07:51,800 --> 00:07:54,600 Speaker 6: and the soft data, the sentiment data, which has been terrible. 156 00:07:56,560 --> 00:08:00,760 Speaker 6: So what yeah, yeah, go ahead, Alex, I'm sorry well doesn't. 157 00:08:00,560 --> 00:08:02,720 Speaker 2: Say something, Where does that? Where does that leave us? 158 00:08:03,920 --> 00:08:06,920 Speaker 6: Well, we're we're we're we're looking for more, you know, 159 00:08:07,200 --> 00:08:10,440 Speaker 6: Where's like again, the hard data that we saw last week, 160 00:08:10,600 --> 00:08:14,360 Speaker 6: you know, CPI and PPI data was fine. The retail 161 00:08:14,440 --> 00:08:17,560 Speaker 6: sales for the Marparol season up five point two percent 162 00:08:17,680 --> 00:08:20,640 Speaker 6: year on year versus three percent a year ago. So 163 00:08:20,720 --> 00:08:24,960 Speaker 6: the the consumer data is fine. But then additional sentiment data, 164 00:08:25,040 --> 00:08:28,640 Speaker 6: the HMI, the housing data is terrible. The the Michigan 165 00:08:28,720 --> 00:08:31,960 Speaker 6: data was terrible. And so now the next big data 166 00:08:31,960 --> 00:08:34,280 Speaker 6: point we're going to get this week is you know, 167 00:08:34,320 --> 00:08:37,560 Speaker 6: the claims data. Uh, this is the survey week for 168 00:08:37,600 --> 00:08:41,640 Speaker 6: the main jobs report, so incrementally what investors are looking for. 169 00:08:41,679 --> 00:08:43,880 Speaker 6: It's okay, well, what's the next data point? You know, 170 00:08:43,920 --> 00:08:45,640 Speaker 6: how do we how do we sort of complete this 171 00:08:45,760 --> 00:08:49,800 Speaker 6: giant jigsaw puzzle. There are some folks like us who 172 00:08:49,880 --> 00:08:53,319 Speaker 6: think that this situation is going to continue to improve, 173 00:08:53,840 --> 00:08:56,920 Speaker 6: that we'll get more countries that will sort of fall 174 00:08:56,960 --> 00:09:00,480 Speaker 6: into place with the tariff negotiations, and the heart data 175 00:09:00,520 --> 00:09:03,320 Speaker 6: is ultimately going to prevail. The soft data will sort 176 00:09:03,360 --> 00:09:06,040 Speaker 6: of fade. But there are other folks that you know, 177 00:09:06,280 --> 00:09:08,400 Speaker 6: are looking at the other side. Of the coin are 178 00:09:08,440 --> 00:09:11,439 Speaker 6: saying that the good hard data is going to dissipate, 179 00:09:11,720 --> 00:09:13,520 Speaker 6: and then it's the soft data that's pointing in the 180 00:09:13,559 --> 00:09:16,280 Speaker 6: right direction. So the short answer is alex right now, 181 00:09:16,320 --> 00:09:19,200 Speaker 6: no one knows and they're just waiting for more incremental 182 00:09:19,240 --> 00:09:21,480 Speaker 6: information to sort of form that picture. 183 00:09:22,440 --> 00:09:26,600 Speaker 3: Now nobody knows. That probably includes the Federal Reserve. Don't 184 00:09:26,600 --> 00:09:29,040 Speaker 3: you think, Phil, how do you think they're preceding these days? 185 00:09:29,760 --> 00:09:32,080 Speaker 6: Well, exactly right. I mean you look at the last 186 00:09:32,160 --> 00:09:36,199 Speaker 6: FOMC meeting where Powell basically said we're going to take 187 00:09:36,200 --> 00:09:40,160 Speaker 6: a wait and see approach like two dozen times because 188 00:09:40,200 --> 00:09:43,840 Speaker 6: they're waiting for more data. They're waiting for clarity of 189 00:09:43,840 --> 00:09:48,040 Speaker 6: the picture. And the bond market, which you know, a 190 00:09:48,080 --> 00:09:50,599 Speaker 6: couple of weeks ago, was thinking that we're going to 191 00:09:50,679 --> 00:09:52,520 Speaker 6: have three or four cuts in the back half of 192 00:09:52,520 --> 00:09:54,719 Speaker 6: the year. They now think we're we're only going to 193 00:09:54,760 --> 00:09:57,400 Speaker 6: have two, with the first cut maybe not coming until 194 00:09:57,520 --> 00:10:00,640 Speaker 6: the September FOMC meeting. Because the thing thinking is that 195 00:10:00,679 --> 00:10:03,679 Speaker 6: the FED needs more data to be able to figure 196 00:10:03,679 --> 00:10:07,199 Speaker 6: out what their next policy move is. Our position here 197 00:10:07,200 --> 00:10:12,040 Speaker 6: at Federated Hermes is that the FED will cut, give 198 00:10:12,120 --> 00:10:14,240 Speaker 6: us two or three cuts in the back half of 199 00:10:14,280 --> 00:10:16,720 Speaker 6: the year. Maybe that first cut comes to the July meeting, 200 00:10:17,360 --> 00:10:21,160 Speaker 6: because the economy is slowing down, but the labor market's 201 00:10:21,200 --> 00:10:24,800 Speaker 6: not collapsing. And as we saw with the CPI, the 202 00:10:24,840 --> 00:10:28,120 Speaker 6: retail and the wholesale inflation data last week that the 203 00:10:28,120 --> 00:10:31,080 Speaker 6: inflation data is pretty good. All of that suggests that 204 00:10:31,120 --> 00:10:34,679 Speaker 6: the federal reserves should be reducing interest rates in the 205 00:10:34,679 --> 00:10:37,120 Speaker 6: back half of the year, and we're pretty comfortable with 206 00:10:37,160 --> 00:10:37,640 Speaker 6: that position. 207 00:10:38,080 --> 00:10:40,600 Speaker 2: Before I let you go, are you surprised about the 208 00:10:40,640 --> 00:10:43,160 Speaker 2: non market reaction to the Moody's downgrade. 209 00:10:46,600 --> 00:10:49,000 Speaker 6: I'm sort of surprised that Moody's was as late to 210 00:10:49,040 --> 00:10:53,280 Speaker 6: the party as they were in terms of when, you know, 211 00:10:53,440 --> 00:10:56,440 Speaker 6: Fitch and s and P made their downgrades years ago, 212 00:10:56,880 --> 00:10:59,680 Speaker 6: And in my mind, I'm asking the question, if Moody's 213 00:10:59,720 --> 00:11:02,960 Speaker 6: is down grading now, where were they, you know, over 214 00:11:03,000 --> 00:11:05,600 Speaker 6: the last three or four years when inflation spiked up 215 00:11:05,640 --> 00:11:08,640 Speaker 6: to the highest levels in forty years. Why are they 216 00:11:08,679 --> 00:11:12,960 Speaker 6: picking this moment as opposed to, you know, perhaps a 217 00:11:13,040 --> 00:11:16,640 Speaker 6: more reasonable moment a couple of years ago. So I 218 00:11:16,679 --> 00:11:18,199 Speaker 6: don't know what to read into that. 219 00:11:19,000 --> 00:11:20,760 Speaker 3: All right, Phil, thanks so much for joining us. Always 220 00:11:20,760 --> 00:11:24,520 Speaker 3: appreciate getting your thoughts. Fill Orlando, chief equity market strategist 221 00:11:24,520 --> 00:11:28,720 Speaker 3: and head Client Portfolio Management, and Federated Hermes joining us there. 222 00:11:30,679 --> 00:11:34,360 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 223 00:11:34,440 --> 00:11:37,520 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 224 00:11:37,559 --> 00:11:40,840 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 225 00:11:40,920 --> 00:11:44,040 Speaker 1: you get your podcasts, or watch us live on YouTube. 226 00:11:44,440 --> 00:11:46,360 Speaker 3: All right, Alex Steel, Paul Sweeney live here on Bloomberg 227 00:11:46,400 --> 00:11:49,600 Speaker 3: and Arctia Broker Studio streaming live on YouTube as well. 228 00:11:49,600 --> 00:11:53,280 Speaker 3: We're also on Bloomberg Originals. To check us out there 229 00:11:53,320 --> 00:11:56,760 Speaker 3: on your smart TV. Let's talk Apple, Let's talk AI. 230 00:11:57,120 --> 00:12:00,680 Speaker 3: I mean, we've all followed Apple for twenty thirty four years. 231 00:12:01,280 --> 00:12:05,120 Speaker 3: They don't miss very often. They kind of get the PC, 232 00:12:05,360 --> 00:12:09,079 Speaker 3: they get the phone, they get the gadgets. But boy, 233 00:12:09,760 --> 00:12:12,360 Speaker 3: even to this person who doesn't really follow that closely, 234 00:12:12,559 --> 00:12:14,600 Speaker 3: they're not getting AI. And I think I wonder if 235 00:12:14,600 --> 00:12:16,719 Speaker 3: just what extent that's the problem. Our next guests will 236 00:12:16,760 --> 00:12:19,320 Speaker 3: help us out there. Mark Herman, Managing editor for Global 237 00:12:19,480 --> 00:12:22,800 Speaker 3: Consumer Tech for Bloomberg News. He's based in LA but 238 00:12:22,840 --> 00:12:25,120 Speaker 3: he's here in New York's. We got him in studio. 239 00:12:25,440 --> 00:12:28,120 Speaker 3: You've got a Bloomberg BusinessWeek big take story out today 240 00:12:28,200 --> 00:12:31,800 Speaker 3: on Apple, and they're just kind of missing AI. What's 241 00:12:31,840 --> 00:12:34,080 Speaker 3: going on in Coopertino as it relates to AI. 242 00:12:34,840 --> 00:12:40,160 Speaker 7: Well, philosophical differences, mismanagement, and the biggest thing is they 243 00:12:40,160 --> 00:12:43,640 Speaker 7: were blindsided when generative AI with chat, GPT and GitHub 244 00:12:43,760 --> 00:12:47,200 Speaker 7: launched back in twenty twenty two. November twenty twenty two, 245 00:12:47,360 --> 00:12:52,120 Speaker 7: I'm told Apple Intelligence wasn't even an idea back then. Why, well, 246 00:12:52,160 --> 00:12:52,959 Speaker 7: they missed the boat. 247 00:12:53,080 --> 00:12:55,400 Speaker 2: But how I mean, I mean, I don't understand. 248 00:12:55,720 --> 00:12:59,920 Speaker 7: Yeah, well, clearly there was philosophical disagreement, in philosophical dis 249 00:13:00,120 --> 00:13:03,160 Speaker 7: interest in the topic of artificial intelligence. I write about 250 00:13:03,160 --> 00:13:07,000 Speaker 7: how Craig Federighi, Apple's senior VP of software engineering, doesn't 251 00:13:07,040 --> 00:13:11,600 Speaker 7: really believe in these multi billion dollar projects. He tends 252 00:13:11,640 --> 00:13:14,240 Speaker 7: to try to shut down or steer away from projects 253 00:13:14,280 --> 00:13:16,920 Speaker 7: of that sort, and AI is something of that nature. 254 00:13:17,000 --> 00:13:19,319 Speaker 7: AI is quite a bit messy. They're known for the 255 00:13:19,480 --> 00:13:24,360 Speaker 7: very intricate and well designed user experiences. AI sometimes with hallucidations, 256 00:13:24,360 --> 00:13:26,640 Speaker 7: can take away from that. But I think they didn't 257 00:13:26,679 --> 00:13:28,120 Speaker 7: think it was going to be as big of a 258 00:13:28,160 --> 00:13:30,240 Speaker 7: thing as it became today. A lot of it fell 259 00:13:30,280 --> 00:13:33,720 Speaker 7: on deaf years years ago, I'm told. But really, this 260 00:13:33,760 --> 00:13:36,439 Speaker 7: is a company that's known for updating their operating systems 261 00:13:36,480 --> 00:13:40,079 Speaker 7: once a year. It's known as a company that focuses 262 00:13:40,280 --> 00:13:43,360 Speaker 7: on the minutia, and they missed the big picture here 263 00:13:43,640 --> 00:13:47,360 Speaker 7: with artificial intelligence, and it really is a shame. You know, 264 00:13:47,400 --> 00:13:50,520 Speaker 7: the big picture here isn't the AI capabilities of its 265 00:13:50,520 --> 00:13:54,400 Speaker 7: devices today. The big picture today is the AI capability 266 00:13:54,760 --> 00:13:57,760 Speaker 7: of future hardware. If you don't have the core technology, 267 00:13:57,800 --> 00:14:00,080 Speaker 7: the AI ready to go at a deep level, how 268 00:14:00,080 --> 00:14:04,160 Speaker 7: are you going to develop products like humanoid robots, smart glasses, 269 00:14:04,800 --> 00:14:08,479 Speaker 7: watches in AirPods with depth sens and cameras for AI purposes. 270 00:14:08,920 --> 00:14:11,280 Speaker 7: Can't do any of that if you don't have that technology. 271 00:14:11,600 --> 00:14:14,439 Speaker 7: So they need to seriously turn this thing around quickly 272 00:14:14,559 --> 00:14:17,120 Speaker 7: or are they're going to be in big trouble. This 273 00:14:17,360 --> 00:14:20,440 Speaker 7: is as core technology as the touchscreen. 274 00:14:21,440 --> 00:14:23,920 Speaker 3: Wow. I mean, first of all, how many words is 275 00:14:23,960 --> 00:14:24,720 Speaker 3: this story, dude? 276 00:14:24,920 --> 00:14:25,520 Speaker 7: Six thousand? 277 00:14:25,600 --> 00:14:25,800 Speaker 2: Yeah? 278 00:14:25,800 --> 00:14:29,240 Speaker 3: This is a long, well story, folks. So if you 279 00:14:29,240 --> 00:14:31,920 Speaker 3: wantn't get smart on AI and Apple, you got to 280 00:14:31,960 --> 00:14:33,760 Speaker 3: read the story. It's in the Bloomberg Business Week, It's 281 00:14:33,800 --> 00:14:35,680 Speaker 3: on the Terminal up shirts everywhere else as well. 282 00:14:36,480 --> 00:14:36,760 Speaker 6: Mark. 283 00:14:37,000 --> 00:14:40,120 Speaker 3: What can they do if I'm an investor, That's the 284 00:14:40,160 --> 00:14:42,960 Speaker 3: only question I have for Tim Cook. Can you guys 285 00:14:43,240 --> 00:14:45,560 Speaker 3: catch up and get some of that AI pixie dusk 286 00:14:45,640 --> 00:14:46,280 Speaker 3: in your stock? 287 00:14:46,440 --> 00:14:49,240 Speaker 7: Yes, they need to make acquisitions, and they need to 288 00:14:49,680 --> 00:14:53,520 Speaker 7: up the percentage of that R and D budget tied 289 00:14:53,560 --> 00:14:55,560 Speaker 7: to AI. They need to up that percentage. They need 290 00:14:55,600 --> 00:14:58,200 Speaker 7: to allocate more of their hires to AI as well. 291 00:14:58,280 --> 00:15:00,480 Speaker 7: So they need to go bigger, go home on this. 292 00:15:00,800 --> 00:15:02,520 Speaker 6: And I think did they know that? 293 00:15:02,560 --> 00:15:02,920 Speaker 5: Do you think? 294 00:15:03,000 --> 00:15:03,200 Speaker 4: Yeah? 295 00:15:03,200 --> 00:15:03,920 Speaker 7: Of course they know that. 296 00:15:03,960 --> 00:15:05,760 Speaker 2: Okay, how do they go big? 297 00:15:06,480 --> 00:15:09,280 Speaker 7: You got to spend more money. AI is really one 298 00:15:09,320 --> 00:15:12,120 Speaker 7: of the only things that you can buy your way 299 00:15:12,160 --> 00:15:15,080 Speaker 7: into when it comes to this technology, right, you can 300 00:15:15,120 --> 00:15:17,040 Speaker 7: buy your way into it. You just need to throw 301 00:15:17,120 --> 00:15:20,080 Speaker 7: billions and billions at AI training. They need to make 302 00:15:20,080 --> 00:15:22,800 Speaker 7: probably some tweaks to their privacy policy. Right, they have 303 00:15:22,960 --> 00:15:25,160 Speaker 7: so many devices, They have more devices than anyone else 304 00:15:25,200 --> 00:15:27,800 Speaker 7: as a single brand of a hardware company, of any 305 00:15:27,840 --> 00:15:29,800 Speaker 7: company in the entire world in the history of the world. 306 00:15:30,000 --> 00:15:32,520 Speaker 7: But they don't leverage that because of their privacy stand 307 00:15:32,600 --> 00:15:34,320 Speaker 7: So maybe make some tweaks there to be able to 308 00:15:34,320 --> 00:15:37,160 Speaker 7: collect some more data. Maybe figure out a way to 309 00:15:37,160 --> 00:15:39,000 Speaker 7: convince people to give up some of their data for 310 00:15:39,040 --> 00:15:42,040 Speaker 7: this purpose, and I think that could go a long 311 00:15:42,080 --> 00:15:44,560 Speaker 7: way for them. So spending money collecting more data. 312 00:15:45,680 --> 00:15:48,040 Speaker 3: Is there somebody out there that they could buy, should buy, 313 00:15:48,120 --> 00:15:50,480 Speaker 3: that would leapfrog them? Do you think I hate doing 314 00:15:50,480 --> 00:15:50,760 Speaker 3: that though? 315 00:15:50,840 --> 00:15:51,120 Speaker 4: Right? 316 00:15:51,280 --> 00:15:54,840 Speaker 7: Well, the problem is this philosophical disgust. I would say 317 00:15:54,920 --> 00:15:58,600 Speaker 7: to making these large acquisitions. If I told you, I mean, 318 00:15:58,640 --> 00:16:00,640 Speaker 7: you know this is true, so maybe you're not good. Example, 319 00:16:00,640 --> 00:16:03,200 Speaker 7: But if I said to someone who didn't know the 320 00:16:03,200 --> 00:16:05,000 Speaker 7: company as well as you too, would you believe me 321 00:16:05,040 --> 00:16:07,240 Speaker 7: if I told you that Apple's biggest acquisition in the 322 00:16:07,280 --> 00:16:09,400 Speaker 7: history of the company was three billion dollars. 323 00:16:09,360 --> 00:16:10,560 Speaker 2: I actually believe that much. 324 00:16:10,640 --> 00:16:12,480 Speaker 7: Well, you believe that because you know that, But I 325 00:16:12,520 --> 00:16:14,440 Speaker 7: think if you ask people who didn't know that, that 326 00:16:14,480 --> 00:16:18,280 Speaker 7: would be completely unbelievable. Yeah, they make these small acquisitions, 327 00:16:18,520 --> 00:16:20,720 Speaker 7: and in addition to not wanting to spend big bucks 328 00:16:21,120 --> 00:16:25,560 Speaker 7: on a company, they're really poor at integrating companies. The 329 00:16:25,600 --> 00:16:30,240 Speaker 7: Beats integration, integrating all those engineers into the company, Disaster Intel, 330 00:16:30,280 --> 00:16:32,280 Speaker 7: they bought the motim unit for a billion dollars back 331 00:16:32,280 --> 00:16:36,080 Speaker 7: in nineteen Disaster, what is it going to feel as 332 00:16:36,120 --> 00:16:39,600 Speaker 7: an AI person at Apple today. If you're bringing if 333 00:16:39,640 --> 00:16:42,680 Speaker 7: the company buys your replacement to bring them in, it's 334 00:16:42,680 --> 00:16:44,840 Speaker 7: not going to be fun. There's enough turf wars as 335 00:16:44,840 --> 00:16:45,600 Speaker 7: it is at Apple. 336 00:16:46,080 --> 00:16:49,480 Speaker 2: So they do then have to do it internally. They've 337 00:16:49,520 --> 00:16:50,960 Speaker 2: still not done well at that. 338 00:16:51,400 --> 00:16:53,320 Speaker 7: They've got to do both. They got to make the acquisition. 339 00:16:53,320 --> 00:16:54,880 Speaker 7: They got to just deal with that. They got to 340 00:16:54,880 --> 00:16:57,320 Speaker 7: make their biggest acquisition ever, and it has to be 341 00:16:57,360 --> 00:17:01,400 Speaker 7: for AI, maybe multiple acquisitions. They have to turn things 342 00:17:01,440 --> 00:17:03,920 Speaker 7: up a notch internally as well. They're going to be 343 00:17:04,000 --> 00:17:07,399 Speaker 7: making changes. I mean, there's so many philosophical disagreements. The 344 00:17:07,400 --> 00:17:10,600 Speaker 7: biggest is about chatbots. When it comes to AI. They 345 00:17:10,680 --> 00:17:13,520 Speaker 7: are allergic to AI chatbots. They don't like the technology. 346 00:17:13,520 --> 00:17:16,880 Speaker 7: They don't think open AI has staying power. So you're yes, 347 00:17:17,320 --> 00:17:17,840 Speaker 7: I know, I. 348 00:17:17,800 --> 00:17:18,840 Speaker 2: Made a face when he said that. 349 00:17:19,400 --> 00:17:22,280 Speaker 7: Okay, you're going to see deeper integrations with other companies. 350 00:17:22,280 --> 00:17:24,640 Speaker 7: They're going to see Google Gemini integration. I think next 351 00:17:24,680 --> 00:17:29,200 Speaker 7: year you'll see Perplexity integration, maybe some Anthropic integration, maybe 352 00:17:29,200 --> 00:17:32,680 Speaker 7: some Microsoft integration. But they're going to keep pushing and 353 00:17:32,760 --> 00:17:34,399 Speaker 7: this is going to be a multi year thing. The 354 00:17:34,400 --> 00:17:36,920 Speaker 7: biggest problems they were caught off. Guvernment's happened, so they 355 00:17:37,000 --> 00:17:40,399 Speaker 7: had no head start on this. They're coming way from behind. 356 00:17:41,000 --> 00:17:45,000 Speaker 3: Oh yeah, it's amazing. It's amazing. Now some people would say, hey, 357 00:17:45,000 --> 00:17:48,359 Speaker 3: they're rarely first phones. Oh boy, when they decide to 358 00:17:48,400 --> 00:17:49,760 Speaker 3: get into phones, they do it. 359 00:17:49,920 --> 00:17:52,720 Speaker 7: That's the big difference. They were not first, and they're 360 00:17:52,720 --> 00:17:53,119 Speaker 7: the worst. 361 00:17:53,400 --> 00:17:55,280 Speaker 3: Okay companies. 362 00:17:55,359 --> 00:17:57,600 Speaker 2: Yeah, yea is the reason why I need to read 363 00:17:57,600 --> 00:17:59,720 Speaker 2: the six thousand page word article. 364 00:17:59,760 --> 00:18:00,520 Speaker 3: Thank you, Thank you so much. 365 00:18:00,560 --> 00:18:03,280 Speaker 2: Mark, really a pleasure. Mark German, Bloomberg News Managing editor 366 00:18:03,320 --> 00:18:04,480 Speaker 2: for Global Consumer Tech. 367 00:18:04,760 --> 00:18:09,480 Speaker 1: This is the Bloomberg Intelligence Podcast, available on Apple, Spotify, 368 00:18:09,680 --> 00:18:13,160 Speaker 1: and anywhere else you get your podcasts. Listen live each 369 00:18:13,160 --> 00:18:16,920 Speaker 1: weekday ten am to noon Eastern on Bloomberg dot com, 370 00:18:17,040 --> 00:18:20,560 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app. 371 00:18:21,000 --> 00:18:23,920 Speaker 1: You can also watch us live every weekday on YouTube 372 00:18:24,320 --> 00:18:26,560 Speaker 1: and always on the Bloomberg terminal.