1 00:00:02,520 --> 00:00:13,760 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is the Bloomberg 2 00:00:13,840 --> 00:00:17,920 Speaker 1: Surveillance Podcast. Catch us live weekdays at seven am Eastern 3 00:00:18,200 --> 00:00:22,000 Speaker 1: on Apple CarPlay or Android Auto with the Bloomberg Business app. 4 00:00:22,360 --> 00:00:25,680 Speaker 1: Listen on demand wherever you get your podcasts, or watch 5 00:00:25,760 --> 00:00:27,040 Speaker 1: us live on YouTube. 6 00:00:27,320 --> 00:00:32,159 Speaker 2: Constance Hunter gives us wonderful perspective this morning. How is 7 00:00:32,200 --> 00:00:34,839 Speaker 2: your view on this change with the information of the 8 00:00:34,920 --> 00:00:36,320 Speaker 2: last seventy two hours. 9 00:00:37,080 --> 00:00:39,960 Speaker 3: Yeah, well, so just to recap, right, it was the 10 00:00:40,000 --> 00:00:43,239 Speaker 3: benchmark revisions, and it was PPI, and of course the 11 00:00:43,240 --> 00:00:46,640 Speaker 3: benchmark revisions we could anticipate in advance that those were 12 00:00:46,920 --> 00:00:49,479 Speaker 3: very well forecast and we knew that it was going 13 00:00:49,560 --> 00:00:52,600 Speaker 3: to be large, and obviously it's the large. It's even 14 00:00:52,720 --> 00:00:55,720 Speaker 3: larger than the two thousand and nine benchmark revisions. And 15 00:00:55,760 --> 00:00:59,200 Speaker 3: what it foreshadows is that the labor market is weaker, 16 00:00:59,240 --> 00:01:01,240 Speaker 3: which is the same thing the last two data prints 17 00:01:01,240 --> 00:01:04,520 Speaker 3: have been telling us. And then of course PPI was 18 00:01:04,640 --> 00:01:08,360 Speaker 3: quite an interesting report. Yes, we saw goods prices see 19 00:01:08,360 --> 00:01:12,720 Speaker 3: pressure and services prices soften. That's actually what the Fed 20 00:01:12,800 --> 00:01:15,160 Speaker 3: sort of wants to see. I think they can look 21 00:01:15,200 --> 00:01:17,760 Speaker 3: through higher goods prices. It is harder for them to 22 00:01:17,800 --> 00:01:22,080 Speaker 3: look through sticky services prices. So that's quite encouraging actually, 23 00:01:23,040 --> 00:01:24,480 Speaker 3: And of course the other thing that came out of 24 00:01:24,520 --> 00:01:28,320 Speaker 3: PPI was that margins are companies are taking this, margins 25 00:01:28,319 --> 00:01:32,000 Speaker 3: are shrinking and if that continues, that is not a 26 00:01:32,120 --> 00:01:34,360 Speaker 3: very good outlook for the equity markets. 27 00:01:34,400 --> 00:01:36,560 Speaker 4: I have the Eco Go screen up on the bloomer 28 00:01:36,640 --> 00:01:39,640 Speaker 4: here looking at these these headline numbers. Beneath that what 29 00:01:39,720 --> 00:01:40,960 Speaker 4: is most important to you? What are you going to 30 00:01:41,000 --> 00:01:43,280 Speaker 4: be looking for when you begin to support through that release. 31 00:01:43,440 --> 00:01:45,200 Speaker 3: Sure, we're going to be looking through all the details 32 00:01:45,240 --> 00:01:48,360 Speaker 3: of goods, and of course it's going to be lumpy 33 00:01:48,440 --> 00:01:51,600 Speaker 3: as these as these tariff effects get passed through. We 34 00:01:51,720 --> 00:01:55,000 Speaker 3: haven't seen it in autos, for example. We did see 35 00:01:55,000 --> 00:01:59,000 Speaker 3: some indication in the PPI that component parts are going up. 36 00:01:59,120 --> 00:02:04,000 Speaker 3: Engines are going up, component parts are going up, and 37 00:02:04,080 --> 00:02:06,720 Speaker 3: so we do expect that passed through to come eventually. 38 00:02:06,800 --> 00:02:08,760 Speaker 3: I think it's going to be lumpy, right, So we 39 00:02:08,800 --> 00:02:11,079 Speaker 3: have a forecast each month of some average that we 40 00:02:11,120 --> 00:02:12,920 Speaker 3: think is going to occur over the next six months, 41 00:02:12,960 --> 00:02:14,680 Speaker 3: but very likely it's going to come in one or 42 00:02:14,680 --> 00:02:17,600 Speaker 3: two month bursts and then it's going to subside. 43 00:02:17,720 --> 00:02:21,240 Speaker 2: Does Chinese deflation affect this report or is that just 44 00:02:21,320 --> 00:02:23,600 Speaker 2: a sidebar on the other side of the world. 45 00:02:23,720 --> 00:02:26,040 Speaker 3: So that's a great question, Tom, because in the past, 46 00:02:26,160 --> 00:02:29,400 Speaker 3: disinflation or deflation in China has been exported to the 47 00:02:29,440 --> 00:02:32,720 Speaker 3: rest of the world, and it would be still being 48 00:02:32,760 --> 00:02:34,520 Speaker 3: exported to the rest of the world except that we 49 00:02:34,600 --> 00:02:37,680 Speaker 3: have put tariffs on and so that passed. 50 00:02:37,320 --> 00:02:38,480 Speaker 5: Through is not occurring. 51 00:02:39,360 --> 00:02:41,320 Speaker 3: Interesting, and we're not the only ones, by the way, 52 00:02:41,400 --> 00:02:45,680 Speaker 3: if you look globally, deminimus taxes started in force in 53 00:02:45,720 --> 00:02:49,720 Speaker 3: twenty twenty four from countries around the world, pushing back 54 00:02:50,240 --> 00:02:53,400 Speaker 3: on the disinflation and deflation and excess supply. 55 00:02:53,720 --> 00:02:55,680 Speaker 4: Let me ask an unfair question here. There is so 56 00:02:55,760 --> 00:02:58,760 Speaker 4: much scrutiny on the Bureau of Labor Statistics, and I 57 00:02:58,760 --> 00:03:00,640 Speaker 4: think what that's done is and have gotten a lot 58 00:03:00,720 --> 00:03:03,799 Speaker 4: of us to re engage with the processes that lead 59 00:03:03,840 --> 00:03:06,520 Speaker 4: to the job numbers that we get. Indeed, these inflation 60 00:03:06,600 --> 00:03:10,720 Speaker 4: numbers as well, just stepping back, how good are these numbers? 61 00:03:11,480 --> 00:03:14,239 Speaker 4: How much are they telling us about the overall inflation picture. 62 00:03:14,880 --> 00:03:21,079 Speaker 3: So the robustness of the policies and procedures that all 63 00:03:21,120 --> 00:03:25,760 Speaker 3: of our statistical agencies follow, including the BLS, are extremely robust. 64 00:03:26,120 --> 00:03:29,440 Speaker 3: They have multiple failsafes and by the way, like all 65 00:03:29,480 --> 00:03:34,120 Speaker 3: of us, they're always looking to find improvements, and they're 66 00:03:34,160 --> 00:03:36,600 Speaker 3: always looking to say, ah, this isn't exactly right. We 67 00:03:36,640 --> 00:03:38,600 Speaker 3: need to improve this, we need to improve that. And 68 00:03:38,640 --> 00:03:40,000 Speaker 3: I just want to say, on the face of it, 69 00:03:40,360 --> 00:03:45,840 Speaker 3: revisions are a really critical part of how data is 70 00:03:45,920 --> 00:03:50,200 Speaker 3: collected and then processed over time. Right. So the problem 71 00:03:50,280 --> 00:03:53,600 Speaker 3: with the CPI is that it is an average basket 72 00:03:53,920 --> 00:03:58,360 Speaker 3: and what we know is that people attached to what 73 00:03:58,760 --> 00:04:00,400 Speaker 3: economists call salients. 74 00:04:00,480 --> 00:04:00,600 Speaker 6: Right. 75 00:04:00,680 --> 00:04:02,280 Speaker 5: So for me, it's that cup of coffee. 76 00:04:02,600 --> 00:04:06,240 Speaker 3: I thought I had a vertical demand curve for coffee, 77 00:04:06,400 --> 00:04:08,120 Speaker 3: that there was no price at which I would not 78 00:04:08,200 --> 00:04:09,840 Speaker 3: buy out, buy coffee out in the morning. 79 00:04:09,960 --> 00:04:11,040 Speaker 5: Yes, but that it. 80 00:04:11,000 --> 00:04:13,120 Speaker 3: Turns out I do have a price, and that price 81 00:04:13,120 --> 00:04:17,960 Speaker 3: seems to be switching to Sanka. Well the eight coffee yeah, 82 00:04:17,960 --> 00:04:20,640 Speaker 3: and eight dollar latte is a really it's really tough 83 00:04:20,640 --> 00:04:21,200 Speaker 3: to swallow. 84 00:04:21,760 --> 00:04:24,680 Speaker 2: It's it's on our way in here, Lisa and your 85 00:04:24,680 --> 00:04:26,040 Speaker 2: pumpkin lot. It is. 86 00:04:26,160 --> 00:04:29,400 Speaker 5: I know it's very expensive. And are you cutting back? Yes, 87 00:04:29,880 --> 00:04:31,440 Speaker 5: I mean get home, let's. 88 00:04:31,240 --> 00:04:34,400 Speaker 2: Go down to you. There's something different this year at 89 00:04:34,440 --> 00:04:37,719 Speaker 2: our remembrances of September eleventh. Here we see the former 90 00:04:37,760 --> 00:04:43,839 Speaker 2: governor of New York, Andrew Como, in conversation with Michael Bloomberg, 91 00:04:44,760 --> 00:04:47,360 Speaker 2: as well as others. Mayor Adams is there. 92 00:04:47,640 --> 00:04:50,919 Speaker 4: I saw Jase Johnson, the former Homeland Security Secretary with mister. 93 00:04:50,800 --> 00:04:54,280 Speaker 2: Navarro I saw as well, and Secretary Lutnik is there. 94 00:04:54,400 --> 00:04:58,240 Speaker 2: I should say that Michael Bloomberg, who has endorsed Andrew Como, 95 00:04:58,360 --> 00:05:01,559 Speaker 2: is founder and majority owner of bloom briguelp the parent 96 00:05:01,640 --> 00:05:07,400 Speaker 2: company of Bloomberg Radio. To those conversations, it has become 97 00:05:08,360 --> 00:05:10,400 Speaker 2: a right of passage in New York. I think we 98 00:05:10,440 --> 00:05:13,760 Speaker 2: need to convey that across this nation is Paul Sweeney 99 00:05:13,839 --> 00:05:18,479 Speaker 2: says so eloquently, the light changes and you can barely 100 00:05:18,520 --> 00:05:21,440 Speaker 2: get through it, and it gets harder every year. Navarro's 101 00:05:21,440 --> 00:05:25,600 Speaker 2: standing with Cuomo the twenty David, your thoughts on these images. 102 00:05:25,440 --> 00:05:27,239 Speaker 4: Yeah, I mean, I we're going to see I believe 103 00:05:27,279 --> 00:05:29,160 Speaker 4: that the Vice President of the United States making his way 104 00:05:29,200 --> 00:05:31,520 Speaker 4: to Lower Manhattan as well. President Trump is going to 105 00:05:31,920 --> 00:05:34,520 Speaker 4: go to the Pentagon, and we see images of outside 106 00:05:34,560 --> 00:05:36,960 Speaker 4: the Pentagon as well as we kind of again mark 107 00:05:37,040 --> 00:05:39,200 Speaker 4: the way that all of this unfolded back in two 108 00:05:39,240 --> 00:05:42,680 Speaker 4: thousand and one. So these dueling memorials taking place here 109 00:05:42,720 --> 00:05:44,080 Speaker 4: on this on this Thursday morning in. 110 00:05:44,000 --> 00:05:46,680 Speaker 2: The USA today. I believe has now Vice President in 111 00:05:46,680 --> 00:05:49,960 Speaker 2: advanced with changed plans and we'll go directly to Utah. 112 00:05:50,160 --> 00:05:52,800 Speaker 2: Has it unsure on that? Yeah, we'll get out front 113 00:05:52,800 --> 00:05:54,920 Speaker 2: of that. We welcome all of you across the nation. 114 00:05:55,560 --> 00:05:58,279 Speaker 2: On this eleventh of September. We are on the constance 115 00:05:58,360 --> 00:06:02,280 Speaker 2: hunters with us you as we look at the inflation 116 00:06:02,400 --> 00:06:05,480 Speaker 2: and claims report. It completely unfair and I need to 117 00:06:05,480 --> 00:06:10,159 Speaker 2: get the Jason Furman annualized statistics three months. But Adam 118 00:06:10,200 --> 00:06:13,240 Speaker 2: Long had those numbers this morning, and I'm sorry they're 119 00:06:13,279 --> 00:06:15,680 Speaker 2: not two percent. This is the way it is. Do 120 00:06:15,800 --> 00:06:19,320 Speaker 2: you say we're in an elevated inflation regime right now 121 00:06:19,480 --> 00:06:21,520 Speaker 2: when you look at the annualized statistics? 122 00:06:21,760 --> 00:06:24,120 Speaker 3: Of course, I mean zero point four percent annualized is 123 00:06:24,160 --> 00:06:29,000 Speaker 3: a bit above four percent. If that number continues now, 124 00:06:29,000 --> 00:06:32,960 Speaker 3: we expect their content to be elevated inflation for the 125 00:06:33,040 --> 00:06:37,680 Speaker 3: next six seven months or so, especially in goods. But 126 00:06:37,800 --> 00:06:40,080 Speaker 3: over that time period we do expect to see some 127 00:06:40,160 --> 00:06:45,880 Speaker 3: moderation and services prices, especially housing services, and so by 128 00:06:45,920 --> 00:06:50,240 Speaker 3: this time next year, our forecast for three month annualized 129 00:06:50,279 --> 00:06:55,480 Speaker 3: core is around two point two percent, right, so very 130 00:06:55,520 --> 00:06:59,080 Speaker 3: close to the FEDS target. And let's not forget that 131 00:06:59,320 --> 00:07:01,720 Speaker 3: while we are seeing elevated prices and while people are 132 00:07:01,760 --> 00:07:05,960 Speaker 3: attaching to salient whatever their salient price is right, and 133 00:07:06,000 --> 00:07:09,320 Speaker 3: we saw feed inflation pretty significantly up in this book's report, 134 00:07:10,920 --> 00:07:14,720 Speaker 3: the overall picture is that this is really being influenced 135 00:07:15,080 --> 00:07:18,239 Speaker 3: by tariffs, which will feed through, that will pass through 136 00:07:18,560 --> 00:07:19,320 Speaker 3: a year from now. 137 00:07:19,400 --> 00:07:22,440 Speaker 2: Constance, thank you so much, Constance under eiu at stay 138 00:07:22,480 --> 00:07:26,360 Speaker 2: with us. More from Bloomberg Surveillance coming up after this. 139 00:07:33,600 --> 00:07:37,200 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us Live 140 00:07:37,240 --> 00:07:40,440 Speaker 1: weekday afternoons from seven to ten am Eastern Listen on 141 00:07:40,480 --> 00:07:44,160 Speaker 1: Applecarplay and Android Auto with the Bloomberg Business app, or 142 00:07:44,320 --> 00:07:45,960 Speaker 1: watch us Live on YouTube. 143 00:07:46,360 --> 00:07:49,640 Speaker 2: This should be a one hour conversation and along with 144 00:07:49,720 --> 00:07:53,880 Speaker 2: a blistering essay oh in the last seventy two hours saying, look, 145 00:07:54,320 --> 00:07:58,280 Speaker 2: the job character back eighteen months is a character of recession. 146 00:07:58,680 --> 00:08:00,520 Speaker 2: Even though she says we may be in a new 147 00:08:00,920 --> 00:08:03,880 Speaker 2: business cycle, We've got the inflation reports out as well, 148 00:08:04,080 --> 00:08:06,320 Speaker 2: and I've got to go to the crafting of your 149 00:08:06,360 --> 00:08:10,920 Speaker 2: paragraphs in the last seven hours or so. And you 150 00:08:11,040 --> 00:08:15,760 Speaker 2: do an annualized calculation like Jason Furman at Harvard on 151 00:08:15,840 --> 00:08:21,160 Speaker 2: a three month annualized inflation, et cetera. How bad is it? 152 00:08:21,160 --> 00:08:24,920 Speaker 6: It's the three month annualized core CPI is three point 153 00:08:24,960 --> 00:08:26,080 Speaker 6: six percent right now? 154 00:08:26,120 --> 00:08:30,640 Speaker 2: Wow, can you expand on that? Please? It's radio Anna, 155 00:08:30,720 --> 00:08:32,679 Speaker 2: you have to it's. 156 00:08:35,360 --> 00:08:40,760 Speaker 7: You're not really well, yes, yes, tom So three point 157 00:08:40,840 --> 00:08:45,280 Speaker 7: six percent is actually the one of the highests for 158 00:08:46,000 --> 00:08:49,560 Speaker 7: over six months now. So I think the contour of 159 00:08:49,640 --> 00:08:52,920 Speaker 7: three months annualized and this is a measure that Chris 160 00:08:52,960 --> 00:08:56,960 Speaker 7: Waller has said he looks at. It's basically it has 161 00:08:57,160 --> 00:09:01,080 Speaker 7: troughed a couple months ago and it's now on a rebound. 162 00:09:01,520 --> 00:09:04,560 Speaker 7: And I think that what it is that. 163 00:09:04,440 --> 00:09:07,800 Speaker 6: The I think the rate hikes in the last couple 164 00:09:07,880 --> 00:09:11,080 Speaker 6: of years in the level of that funds rate is 165 00:09:11,120 --> 00:09:14,840 Speaker 6: only sufficient to bring inflation back down to about two 166 00:09:14,880 --> 00:09:18,160 Speaker 6: point seven or two point eight percent, and thereafter it 167 00:09:18,240 --> 00:09:21,800 Speaker 6: is installed and it's now going And that's that's the bus. 168 00:09:22,000 --> 00:09:23,960 Speaker 2: Let me squeeze in this question, because David's got a 169 00:09:23,960 --> 00:09:26,640 Speaker 2: whole sequence of them that are smarter than mine. Is 170 00:09:26,679 --> 00:09:31,360 Speaker 2: two point seven percent inflation life changing for our listeners 171 00:09:31,400 --> 00:09:34,200 Speaker 2: and viewers. I would suggest analong it is. 172 00:09:36,120 --> 00:09:38,679 Speaker 6: Well, that is actually a very fair question. 173 00:09:39,000 --> 00:09:43,160 Speaker 8: So in many emerging markets, and I covered emerging markets 174 00:09:43,200 --> 00:09:47,319 Speaker 8: earlier in my career, at many emerging marketsy four percent, 175 00:09:47,440 --> 00:09:52,080 Speaker 8: five percent, six percent inflation with no problem with their economy, right. 176 00:09:52,280 --> 00:09:55,120 Speaker 6: And there are some many academic papers who has found 177 00:09:55,200 --> 00:10:01,400 Speaker 6: that inflation start cutting into activity and people inflation expectations 178 00:10:02,000 --> 00:10:05,400 Speaker 6: once the central bank decides to do something about it. 179 00:10:05,800 --> 00:10:10,120 Speaker 6: So if the FEDS inflation target is two percent, then 180 00:10:10,160 --> 00:10:13,240 Speaker 6: inflation stuck at two point seven percent would be life 181 00:10:13,320 --> 00:10:16,920 Speaker 6: changing in a sense that that distance that's zero point 182 00:10:16,960 --> 00:10:21,920 Speaker 6: seven percentage point distance to travel well problem means over 183 00:10:22,080 --> 00:10:25,560 Speaker 6: one hundred basis point of rate hike in order to 184 00:10:25,600 --> 00:10:28,640 Speaker 6: get rid of I mean that is the what the 185 00:10:28,760 --> 00:10:31,640 Speaker 6: kink in the flat part of the Phillips curve is about, 186 00:10:31,679 --> 00:10:34,280 Speaker 6: is that once you get through the easy part of 187 00:10:34,320 --> 00:10:36,719 Speaker 6: this inflation, which was the last three years, you're now 188 00:10:36,760 --> 00:10:39,280 Speaker 6: stuck at two point seven percent, and if you really 189 00:10:39,400 --> 00:10:41,760 Speaker 6: need it to bring it down to two point zero percent, 190 00:10:41,840 --> 00:10:46,920 Speaker 6: you are actually we probably need to increase unemployment substantially. 191 00:10:47,080 --> 00:10:49,400 Speaker 4: And I'm just confirming here the control room got you 192 00:10:49,480 --> 00:10:51,719 Speaker 4: saying that's actually a very fair question to Tom King. 193 00:10:51,800 --> 00:10:53,720 Speaker 4: That's a rare thing to hear from a gay from 194 00:10:53,720 --> 00:10:54,920 Speaker 4: a guest here on this show. 195 00:10:55,679 --> 00:10:58,000 Speaker 9: I'm not sure that you're aware, Anna of the Greenawation 196 00:10:58,120 --> 00:11:01,480 Speaker 9: doesn't give me this keydas it's been four days into 197 00:11:01,520 --> 00:11:03,319 Speaker 9: the week, and I don't know if you're aware of 198 00:11:03,400 --> 00:11:05,959 Speaker 9: how much the note that you wrote yesterday animated the show. 199 00:11:06,040 --> 00:11:09,440 Speaker 9: But Tom quoted early and often from your report on 200 00:11:09,520 --> 00:11:12,400 Speaker 9: your recession call that you made here, saying the revisions 201 00:11:12,559 --> 00:11:15,040 Speaker 9: in those jobs numbers confirmed the labor market began to 202 00:11:15,080 --> 00:11:17,560 Speaker 9: recover shortly after the FED started cutting rates in September 203 00:11:17,600 --> 00:11:20,040 Speaker 9: twenty fourth, then stalled out again. You said, it's possible 204 00:11:20,440 --> 00:11:22,560 Speaker 9: the economy is either still in recession or in the 205 00:11:22,600 --> 00:11:25,080 Speaker 9: early phase of a new business cycle. It was unfair 206 00:11:25,080 --> 00:11:27,000 Speaker 9: you weren't with us yesterday. But I asked a question 207 00:11:27,040 --> 00:11:30,000 Speaker 9: after reading that on air. So what so we marked 208 00:11:30,000 --> 00:11:33,520 Speaker 9: that this may have happened, may be continuing. What does 209 00:11:33,520 --> 00:11:36,440 Speaker 9: it tell us overall about the state of the US 210 00:11:36,440 --> 00:11:38,600 Speaker 9: economy that the call that you made yesterday. 211 00:11:39,280 --> 00:11:43,240 Speaker 6: Yes, it has tremendous implications. So suppose that we are 212 00:11:43,280 --> 00:11:46,040 Speaker 6: in the early phase of the business cycle. It means 213 00:11:46,080 --> 00:11:50,400 Speaker 6: that the moment the Fed cuts in late next week, 214 00:11:50,720 --> 00:11:54,760 Speaker 6: we are probably going to see a pretty sharp recovery. 215 00:11:54,800 --> 00:11:58,840 Speaker 6: But what's unique about this economy right now is there's 216 00:11:58,920 --> 00:12:02,440 Speaker 6: a bottle, there's bottling up a lot of inflationary pressure. 217 00:12:02,800 --> 00:12:06,960 Speaker 6: Firms are itching to pass through these tariff higher costs 218 00:12:07,200 --> 00:12:10,640 Speaker 6: to consumers, but they couldn't so far, so they're waiting 219 00:12:10,720 --> 00:12:13,880 Speaker 6: for the moment the economy is turning to pass it through. 220 00:12:14,200 --> 00:12:17,280 Speaker 6: And I think once the economy is well in the 221 00:12:17,360 --> 00:12:20,560 Speaker 6: recovery phase, that is when we are going to see 222 00:12:20,600 --> 00:12:22,959 Speaker 6: a lot of these tariff pass through. And I think 223 00:12:23,000 --> 00:12:26,360 Speaker 6: today's CPI report gives a little bit hints of that, 224 00:12:26,520 --> 00:12:30,479 Speaker 6: which is that we see hotel prices and airfare prices 225 00:12:30,880 --> 00:12:34,760 Speaker 6: go sharply up. And this is not something a recessionary 226 00:12:34,880 --> 00:12:37,679 Speaker 6: economy should look like. That we should be seeing airfares 227 00:12:37,720 --> 00:12:39,960 Speaker 6: and hotels plunging, not urging. 228 00:12:40,160 --> 00:12:43,679 Speaker 2: And Joe Wisenthal folks saw as well beef prices confirming 229 00:12:43,880 --> 00:12:46,640 Speaker 2: through the roof is doctor woe. Please stay with us. 230 00:12:46,640 --> 00:12:50,559 Speaker 2: We have an exceptional five six, seven minutes here with remembrance, 231 00:12:50,559 --> 00:12:53,120 Speaker 2: but anamog. Please stay with us, and we hope to 232 00:12:53,160 --> 00:12:56,480 Speaker 2: pick up this conversation depending on the comments of the 233 00:12:56,520 --> 00:13:00,000 Speaker 2: President of the United States in the last eighteen months, 234 00:13:00,440 --> 00:13:04,400 Speaker 2: you know, somewhat argue the most influential rbider of our 235 00:13:04,440 --> 00:13:07,760 Speaker 2: market economics in America. And I want to pick up 236 00:13:07,800 --> 00:13:11,560 Speaker 2: on the essay David Gerra mentioned where you talked about recession. 237 00:13:12,120 --> 00:13:16,400 Speaker 2: Why can anawong study a recession so acutely and with 238 00:13:16,520 --> 00:13:19,719 Speaker 2: your optimism say it's a new business cycle. And I've 239 00:13:19,760 --> 00:13:21,840 Speaker 2: got to wait till the Red Sox win a world 240 00:13:21,960 --> 00:13:26,520 Speaker 2: series for the NBER to formally say there's a recession. 241 00:13:27,040 --> 00:13:30,679 Speaker 5: Why the delay, Well, because. 242 00:13:32,360 --> 00:13:35,720 Speaker 6: Usually in the late part of a business cycle, you 243 00:13:35,800 --> 00:13:41,079 Speaker 6: see that firms, small firms tend to go bust, and 244 00:13:41,400 --> 00:13:45,000 Speaker 6: those small firms are very hard to capture in national statistics, 245 00:13:45,120 --> 00:13:48,800 Speaker 6: so bls use a model to forecast this. Now, we 246 00:13:48,880 --> 00:13:52,440 Speaker 6: have a lot of private sector alternative data nowadays, and 247 00:13:52,920 --> 00:13:56,560 Speaker 6: the data we look at is a payroll provider focus 248 00:13:56,640 --> 00:14:01,720 Speaker 6: a small to medium businesses, and these businesses were showing 249 00:14:01,720 --> 00:14:04,200 Speaker 6: that the last two years had been terrible for them. 250 00:14:04,600 --> 00:14:07,400 Speaker 6: But what I've been seeing in the last three months, 251 00:14:07,760 --> 00:14:10,600 Speaker 6: maybe two or three months, is that these there is 252 00:14:10,640 --> 00:14:15,360 Speaker 6: an upswing in these small to small medium businesses and 253 00:14:16,080 --> 00:14:20,400 Speaker 6: in fact our own forecast error. Everyone makes errors, forecast errors, 254 00:14:20,400 --> 00:14:23,920 Speaker 6: including us, And I've noticed that, based on these small 255 00:14:24,160 --> 00:14:27,040 Speaker 6: medium businesses, our forecast error in the last two months 256 00:14:27,080 --> 00:14:30,680 Speaker 6: have been consistently on the upside, which suggests to me 257 00:14:31,000 --> 00:14:36,240 Speaker 6: that maybe that there is this early phace dynamics that's 258 00:14:36,280 --> 00:14:38,400 Speaker 6: going on where you know, you see small caps and 259 00:14:38,480 --> 00:14:43,320 Speaker 6: smaller business rebounding first before everything else are lifted. 260 00:14:44,000 --> 00:14:46,200 Speaker 4: And I look at the note and look at what 261 00:14:46,200 --> 00:14:48,360 Speaker 4: you wrote about those preliminary revisions. You say they flag 262 00:14:48,400 --> 00:14:50,960 Speaker 4: a strong possibility that the economy entered a recession last 263 00:14:51,040 --> 00:14:53,840 Speaker 4: year and recovered after the FED cut rates in late 264 00:14:53,920 --> 00:14:57,040 Speaker 4: twenty twenty four. So say Chair Powell wanders into the 265 00:14:57,040 --> 00:14:59,560 Speaker 4: anti chamber outside his office, there's the Bloomberg terminal. He 266 00:14:59,600 --> 00:15:02,440 Speaker 4: pulls up your report. What does it say to him 267 00:15:02,480 --> 00:15:06,120 Speaker 4: about perhaps mistakes made, but the path forward here if 268 00:15:06,160 --> 00:15:09,320 Speaker 4: in fact that happened, how it might have colored if 269 00:15:09,320 --> 00:15:11,600 Speaker 4: we do the counterfactual here, that the decisions that the 270 00:15:11,600 --> 00:15:13,120 Speaker 4: Fed's made in the months between. 271 00:15:14,880 --> 00:15:19,240 Speaker 6: I think Powell actually felt vindicated because he was the 272 00:15:19,280 --> 00:15:21,640 Speaker 6: one who pushed for the fifty BIPs right it cut 273 00:15:21,800 --> 00:15:25,280 Speaker 6: last September on the basis of the Beige Book. The 274 00:15:25,320 --> 00:15:29,080 Speaker 6: Beige Book is a bunch of anecdotes and soft data, 275 00:15:29,160 --> 00:15:32,360 Speaker 6: and many people in the market discounted these soft data, 276 00:15:32,520 --> 00:15:35,600 Speaker 6: saying that hard data does not is showing that things 277 00:15:35,640 --> 00:15:39,280 Speaker 6: are great well. But the soft data in the Beige 278 00:15:39,280 --> 00:15:42,520 Speaker 6: Book is saying that employment was flat and declining. Now 279 00:15:42,560 --> 00:15:47,960 Speaker 6: today the Beige Book is saying that employment is rising 280 00:15:48,800 --> 00:15:52,080 Speaker 6: just slightly, so things are not as bad as last summer. 281 00:15:52,680 --> 00:15:57,160 Speaker 6: Things are arising, you know, just barely, which is consistent 282 00:15:57,240 --> 00:16:01,960 Speaker 6: with payrolls around twenty thousand or ten thousand per month. 283 00:16:02,480 --> 00:16:06,040 Speaker 6: So I think Powell will look to this as saying 284 00:16:06,080 --> 00:16:09,239 Speaker 6: that while he's going to take more signals from anecdotes 285 00:16:09,280 --> 00:16:11,280 Speaker 6: and talking to businesses and firms. 286 00:16:11,560 --> 00:16:13,840 Speaker 2: And I'm brilliant, and thank you so much for all 287 00:16:13,920 --> 00:16:16,640 Speaker 2: of us the team's surveillance, for your work here. She's 288 00:16:16,680 --> 00:16:20,880 Speaker 2: been just extraordinary over the last seventy two hours. Stay 289 00:16:20,920 --> 00:16:24,800 Speaker 2: with us. More from Bloomberg Surveillance coming up after this. 290 00:16:32,040 --> 00:16:35,640 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch US Live 291 00:16:35,680 --> 00:16:38,840 Speaker 1: weekday afternoons from seven to ten am Eastern Listen on 292 00:16:38,920 --> 00:16:42,600 Speaker 1: Applecarplay and Android Otto with the Bloomberg Business app, or 293 00:16:42,760 --> 00:16:43,840 Speaker 1: watch US Live on. 294 00:16:43,800 --> 00:16:46,400 Speaker 2: YouTube right now, we would digress and we've heard from 295 00:16:46,400 --> 00:16:50,480 Speaker 2: a number of economists that the airlines are sprightly. I 296 00:16:50,480 --> 00:16:54,320 Speaker 2: guess the defense business is sprightly. Germany's back in business. 297 00:16:54,920 --> 00:16:57,960 Speaker 2: We have truly an expert this morning. This is someone 298 00:16:58,360 --> 00:17:01,040 Speaker 2: that isn't just like, you know, what's Boeing going to do, 299 00:17:01,120 --> 00:17:04,440 Speaker 2: what's Airbus going to do, but as a really encyclopedic 300 00:17:05,200 --> 00:17:10,280 Speaker 2: handle on the defense business. Shia Luju joins US Aerospace 301 00:17:10,280 --> 00:17:13,440 Speaker 2: and Defense equity research at Jeffreys as well. I got 302 00:17:13,440 --> 00:17:16,000 Speaker 2: to ask the first question, whither Boeing? Is it finally 303 00:17:16,160 --> 00:17:17,000 Speaker 2: up for Boeing? 304 00:17:17,560 --> 00:17:21,880 Speaker 10: Yeah, the orders in August we're great. The deliveries were 305 00:17:22,320 --> 00:17:24,960 Speaker 10: even better, So they finally seem to have a run 306 00:17:25,040 --> 00:17:28,920 Speaker 10: rate of deliveries hitting their target and goal of thirty 307 00:17:28,960 --> 00:17:30,800 Speaker 10: eight for our month. By the end of this year, 308 00:17:30,840 --> 00:17:32,240 Speaker 10: we're going to forty two on the max. 309 00:17:32,359 --> 00:17:34,520 Speaker 2: I mean, it was at one forty when Shila said 310 00:17:34,520 --> 00:17:37,520 Speaker 2: by it and we're now popping to twenty seven. So 311 00:17:37,560 --> 00:17:40,639 Speaker 2: it's back to being a blue chip security. 312 00:17:41,440 --> 00:17:44,160 Speaker 10: Boeing is a tough name. It's not one of these 313 00:17:44,200 --> 00:17:46,800 Speaker 10: momentum names that you could continue to say, you know, 314 00:17:46,800 --> 00:17:49,880 Speaker 10: we're going to go from twenty four Max's last year 315 00:17:49,960 --> 00:17:51,800 Speaker 10: a month to thirty eight this year. 316 00:17:51,960 --> 00:17:53,000 Speaker 5: Those are big. 317 00:17:52,760 --> 00:17:55,440 Speaker 10: Growth rates for any if you're building a widget, let 318 00:17:55,480 --> 00:17:57,960 Speaker 10: alone an aircraft. So I think you have to take 319 00:17:58,000 --> 00:18:01,960 Speaker 10: that into account when you look at Boeing's momentum. But 320 00:18:02,040 --> 00:18:04,680 Speaker 10: they are doing the right things. They're producing aircraft better, 321 00:18:04,800 --> 00:18:07,840 Speaker 10: they're finally starting to turn the corner on free cash low. 322 00:18:08,520 --> 00:18:11,080 Speaker 10: Their defense business is also turning the corner. This is 323 00:18:11,080 --> 00:18:13,840 Speaker 10: a business that was losing about three billion dollars last year, 324 00:18:13,920 --> 00:18:15,520 Speaker 10: so we're doing better there as well. 325 00:18:15,640 --> 00:18:18,800 Speaker 4: Okay, she will be focused so much on these trade deals, 326 00:18:18,840 --> 00:18:20,800 Speaker 4: but really, of course they're more than that, and you 327 00:18:20,840 --> 00:18:22,639 Speaker 4: look at sort of what's been announced, and there are 328 00:18:22,640 --> 00:18:24,359 Speaker 4: many where we don't have a lot of granular detail, 329 00:18:24,359 --> 00:18:28,000 Speaker 4: but they're often kind of complimented by corporate deals and 330 00:18:28,080 --> 00:18:30,720 Speaker 4: purchasing deals as well. And we were talking about yesterday 331 00:18:30,720 --> 00:18:33,360 Speaker 4: the involvement of the US government and Intel these other companies. 332 00:18:34,119 --> 00:18:36,679 Speaker 4: What's the effect that that's had that as the president 333 00:18:36,760 --> 00:18:38,879 Speaker 4: and his team negotiate these deals, often there is a 334 00:18:38,880 --> 00:18:42,280 Speaker 4: component part that involves purchasing X amount of aircraft or 335 00:18:42,320 --> 00:18:44,919 Speaker 4: why amount of aircraft from Boeing or another company. 336 00:18:45,280 --> 00:18:48,000 Speaker 10: It was one of my favorite pieces we published this 337 00:18:48,119 --> 00:18:51,480 Speaker 10: year on April eighth, and it was really looking at 338 00:18:51,720 --> 00:18:53,879 Speaker 10: how many airplanes does it take to get to the 339 00:18:53,920 --> 00:18:56,200 Speaker 10: bottom of a trade deficit? So we looked at the 340 00:18:56,200 --> 00:18:59,719 Speaker 10: biggest trade deficits that the US has among countries and 341 00:18:59,720 --> 00:19:03,120 Speaker 10: how any airplanes they could buy per annum to offset 342 00:19:03,160 --> 00:19:06,040 Speaker 10: that deficit. And sure enough, you know what's easier to 343 00:19:06,080 --> 00:19:09,080 Speaker 10: offset a deficit than an aircraft that costs one hundred 344 00:19:09,080 --> 00:19:11,560 Speaker 10: million to two hundred and fifty million. They add up 345 00:19:11,640 --> 00:19:14,000 Speaker 10: kind of quickly, and we've seen that happen with multiple 346 00:19:14,000 --> 00:19:17,080 Speaker 10: countries and some of Boeing's largest orders this year. 347 00:19:17,520 --> 00:19:20,159 Speaker 2: Can I ask a dumb question that was brilliant what 348 00:19:20,240 --> 00:19:24,320 Speaker 2: you just said? Apple iPhones are fifteen hundred two thousand bucks, 349 00:19:24,480 --> 00:19:27,439 Speaker 2: but nobody spends that. We go to our phone carrier 350 00:19:27,440 --> 00:19:30,199 Speaker 2: and we do a monthly plan. When you buy a 351 00:19:30,240 --> 00:19:33,639 Speaker 2: Boeing seven seventy seven, do you buy it with a 352 00:19:33,720 --> 00:19:36,239 Speaker 2: lump of one hundred million or they do it a 353 00:19:36,240 --> 00:19:38,600 Speaker 2: monthly plan. No, it's just like my iPhone. 354 00:19:38,640 --> 00:19:41,200 Speaker 10: When you put in an order, usually it's five percent down. 355 00:19:41,320 --> 00:19:45,040 Speaker 10: But you know, you buy an aircraft upround when you 356 00:19:45,600 --> 00:19:48,680 Speaker 10: when you receive the air cash. Yes, so you have delivery. 357 00:19:48,720 --> 00:19:52,160 Speaker 10: Whether you finance it or release it, you are paying 358 00:19:52,160 --> 00:19:55,320 Speaker 10: for the aircraft upfront. I'm curious, I'm delivery. 359 00:19:55,359 --> 00:20:00,560 Speaker 4: Sorry, I'm curious of how the administration's approached defense has 360 00:20:00,680 --> 00:20:04,359 Speaker 4: changed it on the industry side. So hexith running the 361 00:20:04,520 --> 00:20:07,000 Speaker 4: Department of War as it's being called at least five 362 00:20:07,040 --> 00:20:09,520 Speaker 4: by the administration itself. We've heard so much talk about 363 00:20:09,520 --> 00:20:14,360 Speaker 4: new missile defense systems and the like. Famously, it's hard 364 00:20:14,359 --> 00:20:16,280 Speaker 4: for the government to pivot. It's hard for the Pentagon 365 00:20:16,400 --> 00:20:19,199 Speaker 4: to pivot. Is that happening now? Is it underway or 366 00:20:19,200 --> 00:20:21,440 Speaker 4: we had a point where in terms of the weapons 367 00:20:21,600 --> 00:20:24,320 Speaker 4: and programs that they're focused on, they're going to be different. 368 00:20:24,480 --> 00:20:25,680 Speaker 5: Where are we in that process? 369 00:20:27,000 --> 00:20:28,840 Speaker 10: I think that's where I've been a little bit surprised. 370 00:20:28,880 --> 00:20:31,480 Speaker 10: So well, Golden Dome was first announced in January. It 371 00:20:31,560 --> 00:20:33,439 Speaker 10: was sort of this concept. No one knew what it was. 372 00:20:33,480 --> 00:20:35,080 Speaker 10: No one still knows what it is, but it's going 373 00:20:35,119 --> 00:20:37,080 Speaker 10: to be one hundred and seventy five billion dollar missile 374 00:20:37,119 --> 00:20:42,160 Speaker 10: defense shield system encompassing all sorts of threats. And fast 375 00:20:42,160 --> 00:20:44,280 Speaker 10: forward eight to nine months, we're now at the stage 376 00:20:44,320 --> 00:20:46,280 Speaker 10: where we have to spend twenty five billion. It's in 377 00:20:46,280 --> 00:20:50,119 Speaker 10: the reconciliation bill by twenty twenty six. So the government 378 00:20:50,240 --> 00:20:53,760 Speaker 10: has to essentially allocate the five large defense contractors and 379 00:20:53,800 --> 00:20:56,280 Speaker 10: a bunch of small ones twenty five billion. And if 380 00:20:56,320 --> 00:20:59,280 Speaker 10: you think about the defense budget, yes it's a trillion dollars, 381 00:20:59,320 --> 00:21:03,080 Speaker 10: but really the allocation to R and D and procurement 382 00:21:03,119 --> 00:21:06,480 Speaker 10: dollars is around four hundred billion, so twenty five billion 383 00:21:06,560 --> 00:21:10,920 Speaker 10: actually increases their spending and potential. So Golden Dome is 384 00:21:10,960 --> 00:21:14,080 Speaker 10: the contract. Our favorite name in defense is LHX. Another 385 00:21:14,160 --> 00:21:17,480 Speaker 10: name we like is Letos. It's ID Services. We hosted 386 00:21:17,600 --> 00:21:22,280 Speaker 10: lhx's CEO last week at our Jeffrey's Industrials conference, and 387 00:21:22,359 --> 00:21:25,520 Speaker 10: they're putting in RFP. It's not even an RFP process. 388 00:21:25,600 --> 00:21:28,160 Speaker 10: The government saying what can you demo for me? When 389 00:21:28,480 --> 00:21:30,680 Speaker 10: come in and let's see what you got. 390 00:21:30,960 --> 00:21:32,600 Speaker 2: We would have to go in a moment here with 391 00:21:32,680 --> 00:21:36,200 Speaker 2: a huge news flow. Today, as we speak, the ECP 392 00:21:36,359 --> 00:21:38,520 Speaker 2: comes out with their headlines there's no rate change. You'll 393 00:21:38,520 --> 00:21:42,160 Speaker 2: have Leguard's press conference. But I'm looking at nominal GDP, 394 00:21:42,359 --> 00:21:45,800 Speaker 2: the inflation plus growth espers out there that are tepping 395 00:21:45,880 --> 00:21:49,280 Speaker 2: as well. With all your expertise, Shila, do you believe 396 00:21:49,680 --> 00:21:55,359 Speaker 2: that Germany will actually spur defense spending and a nominal 397 00:21:55,359 --> 00:21:57,679 Speaker 2: GDP oomph in Europe? 398 00:21:57,880 --> 00:22:00,760 Speaker 10: I was in Europe three weeks ago. I met with 399 00:22:00,840 --> 00:22:04,200 Speaker 10: sixteen clients the equivalent of their labor day weekend. That 400 00:22:04,240 --> 00:22:06,560 Speaker 10: does not happen in Europe. A defense analysts going to 401 00:22:06,600 --> 00:22:10,040 Speaker 10: meet with sixteen investors, they've usually been hands off defense. 402 00:22:10,119 --> 00:22:13,240 Speaker 10: But all I heard about was defense. So yes, I 403 00:22:13,320 --> 00:22:16,399 Speaker 10: do think that the NATO countries are going to actually 404 00:22:16,400 --> 00:22:19,520 Speaker 10: increase their spending. Historically, fifty percent of that has come 405 00:22:19,600 --> 00:22:22,639 Speaker 10: back to US contractors. Let's say if it's even twenty 406 00:22:22,640 --> 00:22:26,240 Speaker 10: five percent, that's two hundred and eighty billion additional dollars 407 00:22:26,240 --> 00:22:28,560 Speaker 10: to the US contract I believe in the story. Wow, 408 00:22:29,119 --> 00:22:31,720 Speaker 10: it's happening. I mean we're seeing orders from countries like 409 00:22:31,800 --> 00:22:34,280 Speaker 10: Serbia to albert that Serbia has never been a country 410 00:22:34,320 --> 00:22:36,840 Speaker 10: to order two billion dollars of equipment. 411 00:22:37,119 --> 00:22:39,520 Speaker 2: Don't be a stranger, sheilacter her. Thank you so much. 412 00:22:40,600 --> 00:22:44,800 Speaker 2: Stay with us. More from Bloomberg Surveillance coming up after this. 413 00:22:52,040 --> 00:22:55,639 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us Live 414 00:22:55,680 --> 00:22:58,840 Speaker 1: weekday afternoons from seven to ten am Eastern Listen on 415 00:22:58,920 --> 00:23:02,320 Speaker 1: alval karplay and droid auto with the Bloomberg Business app, 416 00:23:02,520 --> 00:23:05,920 Speaker 1: or watch us live on YouTube's. 417 00:23:05,000 --> 00:23:08,679 Speaker 2: Terry's got the most important job in tech. He's a 418 00:23:08,800 --> 00:23:13,080 Speaker 2: legend on Wall Street and it manages the technology analysis 419 00:23:13,560 --> 00:23:17,359 Speaker 2: of City Group Right now. You had your soiree a 420 00:23:17,359 --> 00:23:20,800 Speaker 2: few days ago. What was the biggest surprise for you 421 00:23:21,400 --> 00:23:22,080 Speaker 2: at that event? 422 00:23:22,840 --> 00:23:25,320 Speaker 11: I think the biggest takeaway We had two thousand people 423 00:23:25,400 --> 00:23:28,080 Speaker 11: here in midtown, two hundred and fifty over two hundred 424 00:23:28,080 --> 00:23:32,560 Speaker 11: and fifty company management teams, forty private AI companies that 425 00:23:32,920 --> 00:23:35,639 Speaker 11: we hosted across a number of sessions and tracks, and 426 00:23:35,680 --> 00:23:38,199 Speaker 11: I think the thing that everybody walked away from was 427 00:23:39,160 --> 00:23:44,120 Speaker 11: with was this sense of urgency around artificial intelligence and 428 00:23:44,280 --> 00:23:45,680 Speaker 11: just the pace of things. 429 00:23:45,720 --> 00:23:47,040 Speaker 2: The pace of it it is. 430 00:23:47,440 --> 00:23:50,120 Speaker 11: You know, their comparisons and Gershen and I were talking 431 00:23:50,160 --> 00:23:52,760 Speaker 11: in the green room before this, there are comparisons being 432 00:23:52,800 --> 00:23:55,640 Speaker 11: made to sort of prior cycles and technologies that we've 433 00:23:55,640 --> 00:23:58,920 Speaker 11: been through, and where all of those comparisons fall flat 434 00:23:59,000 --> 00:24:01,880 Speaker 11: is just the speed that is that this is moving at. 435 00:24:01,920 --> 00:24:04,240 Speaker 11: And I don't think anybody walked out of that conference. 436 00:24:04,240 --> 00:24:07,560 Speaker 2: Fire Tyler Radkey two days ago when he got Oracle wrong, 437 00:24:08,200 --> 00:24:11,560 Speaker 2: Tyler Keith, I've never seen this. Look, I've never seen 438 00:24:11,600 --> 00:24:14,400 Speaker 2: a jump in a blue chip stock like Oracle. 439 00:24:14,480 --> 00:24:17,240 Speaker 11: Yeah, I'm right there with you. I've never seen anything 440 00:24:17,280 --> 00:24:20,600 Speaker 11: like that. Tyler's a fantastic I'm medicated. I know as 441 00:24:20,640 --> 00:24:22,800 Speaker 11: an analyst who's been doing this for like twenty five years, 442 00:24:22,840 --> 00:24:26,800 Speaker 11: you've gone wrong. I've certainly gotten wrong right now. 443 00:24:26,840 --> 00:24:28,920 Speaker 2: I mean, I know it's a brutal day for the nation. 444 00:24:29,040 --> 00:24:31,199 Speaker 2: But the FBI is speaking right now, but they have 445 00:24:31,280 --> 00:24:34,199 Speaker 2: Gersten Distant Felt and Heath, Terry and David when we 446 00:24:34,240 --> 00:24:36,560 Speaker 2: invented this. This is what it's about. You. 447 00:24:36,720 --> 00:24:38,320 Speaker 5: You're jealous that you were in the green room. 448 00:24:38,400 --> 00:24:41,120 Speaker 2: They were talking out of Alabama with a slide roll 449 00:24:41,160 --> 00:24:44,199 Speaker 2: he got from Werner von Braun and it was before 450 00:24:44,200 --> 00:24:47,200 Speaker 2: Excel spreadsheets when Heath was doing this continued today. 451 00:24:47,320 --> 00:24:49,359 Speaker 4: Let me pick up on the surprise that Tom's talking 452 00:24:49,359 --> 00:24:52,040 Speaker 4: about and you're picking up on with those Oracle results. 453 00:24:52,560 --> 00:24:56,000 Speaker 4: Put them into the broader picture here. What does it 454 00:24:56,040 --> 00:24:59,520 Speaker 4: indicate about the speed the trajectory that we're on that 455 00:24:59,560 --> 00:25:03,159 Speaker 4: we saw really such an exuberant growth there in Oracle 456 00:25:03,200 --> 00:25:04,480 Speaker 4: as it's changed kind of its tack. 457 00:25:04,520 --> 00:25:08,080 Speaker 11: More broadly, well, look, I think in that bigger picture, 458 00:25:08,400 --> 00:25:10,879 Speaker 11: it is the combination of what we saw from Oracle, 459 00:25:10,920 --> 00:25:13,400 Speaker 11: what we saw from Mango dB, what we saw from Snowflake. 460 00:25:13,920 --> 00:25:17,480 Speaker 11: This AI moment that we're in is moving up the stack, right. 461 00:25:17,560 --> 00:25:22,560 Speaker 11: This was an Nvidia Amphenol Arista Networks sort of thing 462 00:25:22,600 --> 00:25:25,040 Speaker 11: as we did the picks and shovels part of this, 463 00:25:25,440 --> 00:25:27,520 Speaker 11: and now we're moving up the stack to the data layer, 464 00:25:27,600 --> 00:25:30,000 Speaker 11: the consumption layer, and so anything that sort of leveraged 465 00:25:30,000 --> 00:25:33,200 Speaker 11: a consumption. We saw this in Microsoft's numbers back when 466 00:25:33,200 --> 00:25:36,560 Speaker 11: they reported their June numbers. Anything leverage to consumption is 467 00:25:36,600 --> 00:25:39,479 Speaker 11: seeing the kind of benefit that you saw out of Oracle. 468 00:25:39,680 --> 00:25:42,439 Speaker 11: The reason Oracle had such a big reaction to it 469 00:25:42,480 --> 00:25:44,200 Speaker 11: is because it is more of a surprise when you 470 00:25:44,240 --> 00:25:45,600 Speaker 11: see it out of Oracle than it is when you 471 00:25:45,640 --> 00:25:46,320 Speaker 11: see it out of micros. 472 00:25:46,440 --> 00:25:48,600 Speaker 4: All some Microsoft doing this big deal with a Dutch 473 00:25:48,920 --> 00:25:51,520 Speaker 4: company this week and other I just okay. 474 00:25:51,359 --> 00:25:53,639 Speaker 2: Keep up with Mistral. They're doing an ASLM did a 475 00:25:53,720 --> 00:25:56,040 Speaker 2: thing with Mysterill of France to keep them away from 476 00:25:56,080 --> 00:26:00,200 Speaker 2: the Americans. What is the behavior of the executives? Are 477 00:26:00,200 --> 00:26:05,680 Speaker 2: they like frenzy exuberants? Are they measured what's the actual demeanor. 478 00:26:05,920 --> 00:26:09,240 Speaker 11: Yeah, I think frenzied is probably a lot closer than 479 00:26:09,320 --> 00:26:09,919 Speaker 11: sort of measured. 480 00:26:10,000 --> 00:26:10,160 Speaker 2: Right. 481 00:26:10,200 --> 00:26:13,399 Speaker 11: No company wants to be left behind in this. This 482 00:26:13,520 --> 00:26:16,119 Speaker 11: is a technology that is going to reorder the competitive 483 00:26:16,160 --> 00:26:20,360 Speaker 11: stack across every industry. And so no board, no CEO 484 00:26:20,680 --> 00:26:23,320 Speaker 11: is sitting there saying, you know what, let's play wait 485 00:26:23,400 --> 00:26:25,440 Speaker 11: and see on this and the ones that are probably 486 00:26:25,920 --> 00:26:29,080 Speaker 11: to regret it. We have a generation of leaders in 487 00:26:29,440 --> 00:26:32,400 Speaker 11: office now that have been trained on the innovator's dilemma, 488 00:26:32,720 --> 00:26:34,800 Speaker 11: and no one wants to be the next one of 489 00:26:34,800 --> 00:26:35,600 Speaker 11: those companies left. 490 00:26:35,720 --> 00:26:38,040 Speaker 2: We are honored that Heath Terry of City Group is 491 00:26:38,080 --> 00:26:41,240 Speaker 2: with us. I made note of actually I think it 492 00:26:41,240 --> 00:26:44,520 Speaker 2: was Tyler red that sent me some research on this, 493 00:26:44,600 --> 00:26:48,919 Speaker 2: but in a very important visceral City Group meeting on 494 00:26:49,040 --> 00:26:53,719 Speaker 2: all this technology. And when you look at the companies 495 00:26:53,840 --> 00:26:58,480 Speaker 2: and the executives as well, they're all generally younger. They've 496 00:26:58,480 --> 00:27:02,639 Speaker 2: seen cycles of that, your Steve Jobs and others Terodyne, 497 00:27:02,640 --> 00:27:05,919 Speaker 2: Teledyne names that are ancient history, but this is the 498 00:27:06,119 --> 00:27:09,919 Speaker 2: new new Which company has the best model? When you 499 00:27:09,960 --> 00:27:12,399 Speaker 2: talk to the I don't know eighty seven analysts that 500 00:27:12,480 --> 00:27:15,879 Speaker 2: report to you which company right, now is doing it 501 00:27:16,000 --> 00:27:18,160 Speaker 2: best for Heath Terry, Well, look, I. 502 00:27:18,080 --> 00:27:20,919 Speaker 11: Think if you look at the public companies that are 503 00:27:20,920 --> 00:27:22,920 Speaker 11: out there, I'm assuming that's what you're what you're talking about. 504 00:27:23,400 --> 00:27:26,480 Speaker 11: The companies that have the most leverage to this are 505 00:27:26,480 --> 00:27:28,399 Speaker 11: the companies that are providing the models and the tools 506 00:27:28,440 --> 00:27:31,119 Speaker 11: and the infrastructure for this. So Microsoft's obviously at the 507 00:27:31,240 --> 00:27:35,080 Speaker 11: at the top of that list, alphabet Google is very 508 00:27:35,080 --> 00:27:37,600 Speaker 11: close to the top of that list as well. And 509 00:27:37,600 --> 00:27:39,800 Speaker 11: then you start to see some of these neo clouds 510 00:27:39,840 --> 00:27:43,199 Speaker 11: that are emerging companies like core Weave that are that 511 00:27:43,280 --> 00:27:46,680 Speaker 11: are really providing a lot of the capacity and benefiting 512 00:27:46,720 --> 00:27:50,639 Speaker 11: from Nvidia's willingness to supply these clouds with the chips 513 00:27:50,640 --> 00:27:51,959 Speaker 11: that are in such a short supply. 514 00:27:52,440 --> 00:27:55,040 Speaker 2: David asked a question because I got a rude follow up, 515 00:27:55,320 --> 00:27:56,800 Speaker 2: But you want Heath to stay around. 516 00:27:57,800 --> 00:28:01,320 Speaker 4: Where are we in terms of domestic production for those chips. 517 00:28:01,320 --> 00:28:04,040 Speaker 4: Of course, the swirling story here in the conversation about 518 00:28:04,040 --> 00:28:07,520 Speaker 4: trade policy has been about in Nvidia about the export 519 00:28:07,560 --> 00:28:09,560 Speaker 4: of those chips, but also just about the need to 520 00:28:10,119 --> 00:28:12,880 Speaker 4: manufacture these high end chips here in the United States. 521 00:28:13,560 --> 00:28:15,639 Speaker 4: How do you assess the progress the country's making and 522 00:28:15,640 --> 00:28:17,639 Speaker 4: pushing ahead to that, which I know will take an 523 00:28:17,680 --> 00:28:19,879 Speaker 4: ample amount of time, shall we say, to get up 524 00:28:19,880 --> 00:28:20,280 Speaker 4: and running. 525 00:28:20,400 --> 00:28:24,640 Speaker 11: Look, we have capacity in the US from TSMC's investments 526 00:28:24,640 --> 00:28:28,160 Speaker 11: in Arizona, so you're starting to see that happening. We're 527 00:28:28,200 --> 00:28:31,680 Speaker 11: still a very long way away. And what's perhaps even 528 00:28:31,760 --> 00:28:34,920 Speaker 11: more important than the production capacity is the talent that's 529 00:28:35,040 --> 00:28:38,240 Speaker 11: needed to produce those chefs. Most of that cutting edge salent, 530 00:28:38,560 --> 00:28:42,720 Speaker 11: my question, is still sitting in Taiwan, and that's something 531 00:28:42,720 --> 00:28:44,600 Speaker 11: that we clearly have to invest in. 532 00:28:44,720 --> 00:28:47,320 Speaker 2: I got two questions here, and let's pretend you're in 533 00:28:47,320 --> 00:28:50,840 Speaker 2: the office with Missus Frasier and she's just grilling you. 534 00:28:51,760 --> 00:28:55,760 Speaker 2: Why in God's name is Lisa Matteo electric bill going 535 00:28:55,840 --> 00:29:00,920 Speaker 2: up to pay for fancy tech people's AI development discuss? 536 00:29:01,240 --> 00:29:01,280 Speaker 9: No. 537 00:29:01,480 --> 00:29:03,720 Speaker 11: Look, that is going to be a huge challenge for 538 00:29:03,760 --> 00:29:08,320 Speaker 11: the development of this. The utilities, the regulated utilities, are 539 00:29:08,320 --> 00:29:09,720 Speaker 11: going to have to figure out how to divide this 540 00:29:09,880 --> 00:29:13,320 Speaker 11: because there's a big difference between the electrical demand that 541 00:29:13,360 --> 00:29:16,840 Speaker 11: you're seeing for AI and the trends that we were 542 00:29:16,840 --> 00:29:19,840 Speaker 11: seeing in overall efficiency and power demand. And if this 543 00:29:19,960 --> 00:29:23,360 Speaker 11: is going to be a cost that is driven by AI, 544 00:29:23,520 --> 00:29:25,120 Speaker 11: driven by data centers. Then it's going to be a 545 00:29:25,120 --> 00:29:27,160 Speaker 11: cost that needs to be borne by those data centers, 546 00:29:27,440 --> 00:29:29,560 Speaker 11: and by the way, they've got the capacity to be 547 00:29:29,600 --> 00:29:30,200 Speaker 11: able to do it. 548 00:29:30,480 --> 00:29:34,960 Speaker 2: Back to John Reid and Walter Risten, you people Owned International, 549 00:29:35,600 --> 00:29:38,520 Speaker 2: Do you have any studies the show that we can 550 00:29:38,600 --> 00:29:45,600 Speaker 2: develop many thousands American manufacturing forces to do what they 551 00:29:45,680 --> 00:29:49,160 Speaker 2: do in Asia? Or does City Groups City Bank? Did 552 00:29:49,160 --> 00:29:55,240 Speaker 2: you just assume that we're going to import Asia manufacturing 553 00:29:55,320 --> 00:29:56,840 Speaker 2: skill sets? How are we going to do this? 554 00:29:57,600 --> 00:29:58,880 Speaker 11: I think it has to be both. I think you 555 00:29:58,960 --> 00:30:00,520 Speaker 11: have to train people here at home. I think you 556 00:30:00,560 --> 00:30:03,600 Speaker 11: have to import the talent from abroad. There is no 557 00:30:03,720 --> 00:30:06,640 Speaker 11: way that you can get people up to speed as 558 00:30:06,720 --> 00:30:09,200 Speaker 11: fast as they need to be to meet the moment 559 00:30:09,240 --> 00:30:11,800 Speaker 11: that we're in right now. So that means having the 560 00:30:11,920 --> 00:30:16,440 Speaker 11: kind of immigration policy, having the kind of active effort 561 00:30:16,560 --> 00:30:18,960 Speaker 11: at bringing that kind of talent into the US. But 562 00:30:19,000 --> 00:30:20,520 Speaker 11: then you also have to make the investment in the 563 00:30:20,520 --> 00:30:21,280 Speaker 11: people here as well. 564 00:30:21,400 --> 00:30:23,360 Speaker 4: Talking with Heath Terry had a tech and research at 565 00:30:23,400 --> 00:30:25,640 Speaker 4: City As we watched that press conference in Utah rap 566 00:30:25,760 --> 00:30:27,680 Speaker 4: up again with the head of Public Safety in Utah, 567 00:30:27,720 --> 00:30:30,680 Speaker 4: the FBI Special Agent in charge, and the headlines from 568 00:30:30,720 --> 00:30:33,280 Speaker 4: that update on the assassination of Charlie kirk Or. The 569 00:30:33,280 --> 00:30:35,440 Speaker 4: police have been able to track the movements of the 570 00:30:35,440 --> 00:30:38,240 Speaker 4: shooter involved. They have video that they're going through. There's 571 00:30:38,240 --> 00:30:42,400 Speaker 4: also solicitation there at that news conference of video and 572 00:30:42,480 --> 00:30:45,400 Speaker 4: footage photos from the event. They're trying to piece together 573 00:30:45,440 --> 00:30:47,080 Speaker 4: what's happened here. Of course, we'll keep tabs on that 574 00:30:47,120 --> 00:30:49,400 Speaker 4: over the course of the day as we follow that story, 575 00:30:49,440 --> 00:30:52,000 Speaker 4: and keep your prize to memorials that are ongoing in 576 00:30:52,160 --> 00:30:55,520 Speaker 4: Northern Virginia and Lower Manhattan Heath Terry, let me go 577 00:30:55,560 --> 00:30:57,120 Speaker 4: back to that conference you mentioned at the top, because 578 00:30:57,160 --> 00:30:58,320 Speaker 4: I want to get a sense from you how the 579 00:30:58,360 --> 00:31:01,680 Speaker 4: conversation has changed or is changing. There is a moment 580 00:31:01,720 --> 00:31:04,400 Speaker 4: when I think a lot of executives knew they had 581 00:31:04,400 --> 00:31:06,240 Speaker 4: to do something with AI. They poured a lot of 582 00:31:06,280 --> 00:31:11,000 Speaker 4: money into that effort, building up their capacity to do it. 583 00:31:11,040 --> 00:31:13,560 Speaker 4: Is that still where we're at, or are you finding 584 00:31:13,560 --> 00:31:15,720 Speaker 4: that more and more executives have a feeling about how 585 00:31:15,760 --> 00:31:18,920 Speaker 4: to more narrowly tailor AI to the work that they're 586 00:31:18,960 --> 00:31:20,600 Speaker 4: doing day in and day out, such that it's actually 587 00:31:20,640 --> 00:31:22,600 Speaker 4: making a difference in terms of their productivity and what 588 00:31:22,600 --> 00:31:23,680 Speaker 4: these companies are able to do. 589 00:31:24,120 --> 00:31:26,200 Speaker 11: Yeah, I think we're somewhere in the middle of those two. 590 00:31:26,280 --> 00:31:28,960 Speaker 11: You're still seeing this effort to really put a lot 591 00:31:28,960 --> 00:31:31,560 Speaker 11: into proof of concept to try and bring these things on. 592 00:31:31,920 --> 00:31:34,000 Speaker 11: At the same time, we are beginning to see sort 593 00:31:34,040 --> 00:31:37,560 Speaker 11: of the proof of concepts go into production and it 594 00:31:37,600 --> 00:31:39,280 Speaker 11: is having an impact. You look at some of the 595 00:31:39,520 --> 00:31:43,440 Speaker 11: efficiency announcements that you've seen, Hiring starting to slow down 596 00:31:43,760 --> 00:31:46,320 Speaker 11: as companies sort of take a break, particularly in areas 597 00:31:46,320 --> 00:31:49,200 Speaker 11: like code development and customer service, take a break to 598 00:31:49,200 --> 00:31:51,480 Speaker 11: figure out what they really have and what they need. 599 00:31:52,960 --> 00:31:55,960 Speaker 11: As we get through this, our view on this is 600 00:31:56,000 --> 00:31:59,080 Speaker 11: that if you make people more productive, particularly code developers, 601 00:31:59,200 --> 00:32:00,960 Speaker 11: you're going to want more of them, not less. 602 00:32:01,440 --> 00:32:04,080 Speaker 2: I got one final question, Tyler, Ricky, how did he 603 00:32:04,120 --> 00:32:06,960 Speaker 2: get this across your desk? He has a four to 604 00:32:06,960 --> 00:32:11,000 Speaker 2: ten target on Oracle, which I believe is top of 605 00:32:11,040 --> 00:32:16,440 Speaker 2: the reset here, you know, September nine, September tenth. How 606 00:32:16,440 --> 00:32:19,840 Speaker 2: does that work? Does the securities analysts have to get 607 00:32:19,880 --> 00:32:21,800 Speaker 2: approval from you on a price target? 608 00:32:21,960 --> 00:32:24,480 Speaker 11: No, they don't. Tyler's independent. 609 00:32:25,240 --> 00:32:26,800 Speaker 2: He makes it up in a bar downtown. 610 00:32:26,840 --> 00:32:28,640 Speaker 5: So again, Tyler, we're going to get Tyler in here 611 00:32:29,040 --> 00:32:31,000 Speaker 5: talk so much about him. I feel like he's gotta 612 00:32:31,080 --> 00:32:32,240 Speaker 5: you know, Tyler's just downtown. 613 00:32:32,280 --> 00:32:36,160 Speaker 2: I'm just does Alabama football team this year. I'm not 614 00:32:36,200 --> 00:32:37,280 Speaker 2: sure I will. 615 00:32:37,320 --> 00:32:39,400 Speaker 11: We'll see this weekend, so I will. I will be 616 00:32:39,440 --> 00:32:40,400 Speaker 11: in Tuscalos, all. 617 00:32:40,320 --> 00:32:45,960 Speaker 2: Right, report he Jerry will be in tuscles to thank 618 00:32:46,000 --> 00:32:47,880 Speaker 2: you so much. He's just sitting group driving all of 619 00:32:47,920 --> 00:32:49,640 Speaker 2: their technology coverage. 620 00:32:49,920 --> 00:32:54,719 Speaker 1: This is the Bloomberg Surveillance podcast, available on Apple, Spotify, 621 00:32:54,840 --> 00:32:58,640 Speaker 1: and anywhere else you get your podcasts. Listen live each 622 00:32:58,640 --> 00:33:02,600 Speaker 1: week day, seven to ten Eastern on Bloomberg dot com, 623 00:33:02,640 --> 00:33:06,440 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app. 624 00:33:06,720 --> 00:33:09,840 Speaker 1: You can also watch us live every weekday on YouTube 625 00:33:10,160 --> 00:33:12,160 Speaker 1: and always on the Bloomberg terminal