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 --> 00:00:26,800 Speaker 1: us live on YouTube. 6 00:00:26,920 --> 00:00:28,920 Speaker 2: Joining us out with our interview of the day without 7 00:00:29,040 --> 00:00:33,160 Speaker 2: question is liz Ane Sanders icondic at Charles Schwabs spend 8 00:00:33,200 --> 00:00:35,840 Speaker 2: there for at least I think it's five years, seven years, 9 00:00:35,840 --> 00:00:39,640 Speaker 2: something like that. Joining us in studio Lizzie Saunders today. Okay, 10 00:00:40,200 --> 00:00:44,000 Speaker 2: forget about all the equity discussion. I want to know 11 00:00:44,080 --> 00:00:47,400 Speaker 2: the act of your Twitter feed. Yesterday your Twitter feed 12 00:00:47,920 --> 00:00:52,479 Speaker 2: looked like the Federal Reserve analyzing economic data. It was 13 00:00:52,560 --> 00:00:57,800 Speaker 2: a rock star feed of like fifteen studies of GDP 14 00:00:57,920 --> 00:01:00,680 Speaker 2: and the dynamics into the equity mark good are you 15 00:01:00,760 --> 00:01:02,160 Speaker 2: doing that in your spare time? 16 00:01:02,360 --> 00:01:06,520 Speaker 3: Well, I'm not creating most of the charts, you know, 17 00:01:06,640 --> 00:01:09,479 Speaker 3: that's Kevin's domain. If I had to create, it would 18 00:01:09,480 --> 00:01:15,839 Speaker 3: be you know, from the terminals with crayon. So thankfully 19 00:01:15,959 --> 00:01:19,560 Speaker 3: I've got a great uh pair of folks with Kevin 20 00:01:19,560 --> 00:01:23,640 Speaker 3: and Adrian who do the charts. But you know, there 21 00:01:23,640 --> 00:01:27,760 Speaker 3: are there are days where weeks happen, and this week 22 00:01:27,840 --> 00:01:29,480 Speaker 3: is one of those unbelievable weeks. 23 00:01:29,800 --> 00:01:32,440 Speaker 2: When I get breakfast at Sarah Bass in Central Park 24 00:01:32,520 --> 00:01:35,000 Speaker 2: South today and do like a four hour conversation on 25 00:01:35,080 --> 00:01:38,200 Speaker 2: this moment at hand, I got brain crude under sixty 26 00:01:38,280 --> 00:01:42,840 Speaker 2: dollars a barrel global slow down, US slowdown? Is that 27 00:01:42,880 --> 00:01:44,160 Speaker 2: what you model in? Yeah? 28 00:01:44,400 --> 00:01:46,240 Speaker 3: I think what we're seeing now is there was a 29 00:01:46,240 --> 00:01:49,040 Speaker 3: lot of debate in the onset of the escalation of 30 00:01:49,080 --> 00:01:51,040 Speaker 3: the trade war as to whether the growth hit would 31 00:01:51,040 --> 00:01:54,000 Speaker 3: come first of the inflation pop would come first. And 32 00:01:54,040 --> 00:01:56,640 Speaker 3: it looks like the growth hit, YEP, maybe coming first. 33 00:01:57,080 --> 00:01:59,520 Speaker 4: So Liz, we've got the S and P five hundred. 34 00:01:59,520 --> 00:02:00,760 Speaker 4: I mean that good news. 35 00:02:00,280 --> 00:02:03,560 Speaker 5: Bad news is we're down ten percent from the high 36 00:02:03,600 --> 00:02:05,240 Speaker 5: early in the ear, but the good newses were ten 37 00:02:05,240 --> 00:02:06,160 Speaker 5: percent higher. 38 00:02:05,880 --> 00:02:09,400 Speaker 4: From the bottom. What do you make of this? What 39 00:02:09,440 --> 00:02:10,520 Speaker 4: do you think we should be doing here? 40 00:02:10,639 --> 00:02:13,240 Speaker 3: I think what we're seeing in the month of April, 41 00:02:13,320 --> 00:02:18,680 Speaker 3: particularly since the low, is a sign that the retail 42 00:02:18,760 --> 00:02:21,480 Speaker 3: trader is still very active. They're still in the by 43 00:02:21,520 --> 00:02:26,440 Speaker 3: the dip mentality. You've got tech BAC and the leaderboard 44 00:02:26,600 --> 00:02:28,720 Speaker 3: on a month to date basis even though it's toward 45 00:02:28,760 --> 00:02:32,000 Speaker 3: the bottom on a year to date basis. Vand Track 46 00:02:32,120 --> 00:02:35,600 Speaker 3: tracks what retail traders are doing. And that's in start 47 00:02:35,600 --> 00:02:40,920 Speaker 3: contrast to hedge funds and other institutions and CTAs that 48 00:02:41,000 --> 00:02:43,800 Speaker 3: have been going more risk off. And then when you 49 00:02:43,800 --> 00:02:46,600 Speaker 3: see something, you know, Goldman Sachs has those great indexes 50 00:02:46,600 --> 00:02:50,760 Speaker 3: and boxes of baskets, and their Meme stock basket has 51 00:02:50,800 --> 00:02:53,840 Speaker 3: been soaring in the last month too, another proxy for 52 00:02:54,360 --> 00:02:55,240 Speaker 3: retail traders. 53 00:02:56,040 --> 00:02:57,560 Speaker 4: What do you make here of earnings? 54 00:02:57,600 --> 00:02:57,680 Speaker 2: Right? 55 00:02:57,680 --> 00:03:00,240 Speaker 4: Guess we're almost halfway through the earning cycle. Ie, I 56 00:03:00,280 --> 00:03:00,560 Speaker 4: see a. 57 00:03:00,520 --> 00:03:02,320 Speaker 5: Lot of companies probably doing what I would do, which 58 00:03:02,360 --> 00:03:03,760 Speaker 5: is like, I don't know what's going on at there, 59 00:03:03,760 --> 00:03:05,720 Speaker 5: so I'm going to pull my guidance or give you 60 00:03:05,800 --> 00:03:07,480 Speaker 5: some ranges or some scenarios. 61 00:03:07,480 --> 00:03:08,720 Speaker 4: What are you taking away from earning shot? 62 00:03:08,720 --> 00:03:11,640 Speaker 3: I think companies have put themselves into time out, you know. 63 00:03:11,720 --> 00:03:14,079 Speaker 3: Earning so far for first quarter a little bit better 64 00:03:14,160 --> 00:03:16,960 Speaker 3: than expected, not quite the beat rate that we've seen 65 00:03:17,000 --> 00:03:21,000 Speaker 3: over the last year. So, but that's through March data. 66 00:03:21,120 --> 00:03:24,519 Speaker 3: So it's the guidance are lack thereof that I think 67 00:03:24,639 --> 00:03:27,240 Speaker 3: is really important. And it is starting to feel a 68 00:03:27,240 --> 00:03:29,720 Speaker 3: little bit like the early stages of the pandemic, when 69 00:03:29,760 --> 00:03:32,120 Speaker 3: at that time you've had a re percentage of companies 70 00:03:32,600 --> 00:03:33,560 Speaker 3: got and solved together. 71 00:03:33,840 --> 00:03:37,680 Speaker 2: Is institutional under owned in the MEGS seven that retail 72 00:03:37,760 --> 00:03:38,400 Speaker 2: owns up. 73 00:03:38,320 --> 00:03:43,240 Speaker 3: To their eyeballs in many cases yes, because of certain 74 00:03:43,320 --> 00:03:46,960 Speaker 3: funds requirements that they have a max on the amount 75 00:03:47,000 --> 00:03:50,000 Speaker 3: they can hold percentage wise in any individual stock. Even 76 00:03:50,000 --> 00:03:53,960 Speaker 3: some of the sector exchange traded funds are limited are limited, 77 00:03:54,120 --> 00:03:58,640 Speaker 3: so they they're by default can't get couldn't have developed 78 00:03:58,640 --> 00:04:02,600 Speaker 3: the same concentration problem is what was embedded in cap 79 00:04:02,640 --> 00:04:03,680 Speaker 3: weighted in Texas the. 80 00:04:03,760 --> 00:04:07,120 Speaker 2: Charon at the University of Delaware a few years ago, 81 00:04:07,880 --> 00:04:12,760 Speaker 2: Liz Anne Saunders read Securities Analysis. This is a Seth 82 00:04:12,840 --> 00:04:19,200 Speaker 2: Klarman version. I actually read the first edition, which starts 83 00:04:19,240 --> 00:04:22,640 Speaker 2: with railroad stocks and the Reason I bring us forward 84 00:04:22,640 --> 00:04:26,600 Speaker 2: by Warren Buffet, Graham Dodd and Coddalhealth two out of 85 00:04:26,640 --> 00:04:29,640 Speaker 2: colaun of this good work out of Columbia Lizzianne and 86 00:04:29,720 --> 00:04:31,640 Speaker 2: I read this cover to cover a few years ago, 87 00:04:31,960 --> 00:04:35,720 Speaker 2: and out there Lizzyanne is a terminal value. I am 88 00:04:35,880 --> 00:04:40,000 Speaker 2: appalled at the media's shortsightedness. What's Microsoft going to do 89 00:04:40,120 --> 00:04:43,360 Speaker 2: next quarter? What's Apple going to do next quarter? How 90 00:04:43,400 --> 00:04:45,920 Speaker 2: do we get back to actually looking at a five year, 91 00:04:46,040 --> 00:04:49,480 Speaker 2: a seven year analysis of what some of these juggernaut 92 00:04:49,520 --> 00:04:50,360 Speaker 2: stocks are doing. 93 00:04:50,839 --> 00:04:53,760 Speaker 3: Can I plug our version of May Day today? Yes, 94 00:04:54,400 --> 00:04:58,200 Speaker 3: so we are launching today the inaugural of be an 95 00:04:58,200 --> 00:05:02,320 Speaker 3: annual event called national in Day. May first is purposeful 96 00:05:02,440 --> 00:05:04,919 Speaker 3: because what it means in our world is that was 97 00:05:04,960 --> 00:05:07,200 Speaker 3: the year fifty years ago or the day fifty years 98 00:05:07,200 --> 00:05:11,000 Speaker 3: ago on May first, where the sec ended fixed Commission, 99 00:05:11,600 --> 00:05:17,400 Speaker 3: much of Wall Street decided to raise commissions and Juck 100 00:05:17,440 --> 00:05:19,920 Speaker 3: Schwab himself said, yeah, let's lower them. 101 00:05:20,600 --> 00:05:22,200 Speaker 2: It was revolutionary, that was. 102 00:05:22,400 --> 00:05:29,720 Speaker 3: But the day is about encouraging everyone to at least 103 00:05:29,720 --> 00:05:34,320 Speaker 3: take one day a year and educate themselves about investing 104 00:05:34,560 --> 00:05:38,280 Speaker 3: and learn a bit more, become engaged and you want 105 00:05:38,320 --> 00:05:39,159 Speaker 3: to empowered investor? 106 00:05:39,640 --> 00:05:40,040 Speaker 2: Why did that? 107 00:05:40,160 --> 00:05:40,800 Speaker 6: How long time? 108 00:05:40,920 --> 00:05:42,680 Speaker 2: This at the top of the interview. I'm running at 109 00:05:42,680 --> 00:05:45,719 Speaker 2: a time here and mister Schwab deserves some love here 110 00:05:46,240 --> 00:05:49,600 Speaker 2: for really what he courageously did there. I mentioned Arthur 111 00:05:49,680 --> 00:05:54,520 Speaker 2: Levitt is well, so today is your May Day. It's 112 00:05:54,560 --> 00:05:59,520 Speaker 2: a number one mistake the media makes in short termism right. 113 00:05:59,400 --> 00:06:03,479 Speaker 3: Now, asking people like me the question should investors get 114 00:06:03,480 --> 00:06:07,920 Speaker 3: in or get out. I mean, that's just shame on 115 00:06:08,000 --> 00:06:11,200 Speaker 3: anybody that that's not investing, that's gambling, not just on 116 00:06:11,279 --> 00:06:12,839 Speaker 3: a moment in time, but in two moments. 117 00:06:12,839 --> 00:06:16,760 Speaker 2: And is back to the humor, but the sadness folks 118 00:06:17,279 --> 00:06:22,600 Speaker 2: of America missing out on the Lizone Saunders great bull market, 119 00:06:22,880 --> 00:06:25,760 Speaker 2: the joke of the triple leverage all cash fun The 120 00:06:25,839 --> 00:06:29,160 Speaker 2: fact is it's not funny. It Can you come back 121 00:06:29,279 --> 00:06:29,799 Speaker 2: like soon? 122 00:06:30,360 --> 00:06:30,560 Speaker 7: Yeah? 123 00:06:30,680 --> 00:06:32,720 Speaker 3: You know, I mean I love being in here in person. 124 00:06:32,839 --> 00:06:35,080 Speaker 2: Have you seen Robert Plant this summer or you know, 125 00:06:35,440 --> 00:06:37,080 Speaker 2: we got any tour guy with the floods. 126 00:06:37,279 --> 00:06:40,800 Speaker 3: If he decides to pair back up with Page and 127 00:06:41,160 --> 00:06:46,120 Speaker 3: John so cool, Jason speaking, well, they are, they're on 128 00:06:46,240 --> 00:06:48,120 Speaker 3: speaking terms. Plant doesn't want to do it. 129 00:06:48,200 --> 00:06:50,120 Speaker 2: The only reason they go out is when somebody gets 130 00:06:50,160 --> 00:06:51,920 Speaker 2: divorced and they have to pay for it. I mean, 131 00:06:51,920 --> 00:06:52,360 Speaker 2: that's you know. 132 00:06:52,480 --> 00:06:55,159 Speaker 3: You know, there was rumor that Sir Richard Branson offered 133 00:06:55,160 --> 00:06:57,760 Speaker 3: them almost a billion dollars a number of years ago 134 00:06:58,120 --> 00:07:02,440 Speaker 3: to just do two concerts and wanted msg here. Wow, 135 00:07:02,720 --> 00:07:05,680 Speaker 3: And it was apparently Robert Plant that said, wow, I. 136 00:07:05,680 --> 00:07:12,000 Speaker 2: Know, there you go. Folks are surveying Bloeplin Sanaders. I 137 00:07:12,040 --> 00:07:16,080 Speaker 2: would look for her in Birmingham with Ira Jersey at 138 00:07:16,080 --> 00:07:19,600 Speaker 2: the Aston Villa. Was it pan Terror's playing? 139 00:07:19,800 --> 00:07:21,560 Speaker 4: I know that's a big show. 140 00:07:22,000 --> 00:07:24,760 Speaker 2: Lisa Mateo, Lizzie Sanders. They love Pantera. 141 00:07:25,680 --> 00:07:29,600 Speaker 1: This is the Bloomberg Surveillance Podcast. Listen live each weekday 142 00:07:29,640 --> 00:07:32,240 Speaker 1: starting at seven am Eastern on Apple cor Play and 143 00:07:32,240 --> 00:07:35,280 Speaker 1: Android Auto with the Bloomberg Business App. You can also 144 00:07:35,400 --> 00:07:39,040 Speaker 1: listen live on Amazon Alexa from our flagship New York station. 145 00:07:39,600 --> 00:07:42,960 Speaker 1: Just say Alexa play Bloomberg eleven thirty Right. 146 00:07:42,840 --> 00:07:46,560 Speaker 2: Now, Daniel Ives joins us, and he's the greatest thing 147 00:07:46,560 --> 00:07:49,080 Speaker 2: about Ives is when he's right, he doesn't do the 148 00:07:49,200 --> 00:07:51,720 Speaker 2: rhyme right and right and right thing. He just moves 149 00:07:51,760 --> 00:07:54,280 Speaker 2: on to the next analysis. So I'm going to go 150 00:07:54,360 --> 00:07:57,760 Speaker 2: CEFA on your Dan. I joining from Webb Bush. 151 00:07:58,200 --> 00:08:02,400 Speaker 6: The thing I don't get is the terminal value of 152 00:08:02,560 --> 00:08:07,760 Speaker 6: revenue growth for these juggernauts. The media is out one quarter, 153 00:08:08,000 --> 00:08:12,440 Speaker 6: if we're lucky, three quarters a year, The streets out 154 00:08:12,520 --> 00:08:15,920 Speaker 6: two years. I was trained to go out five or 155 00:08:15,960 --> 00:08:20,520 Speaker 6: even seven years. Do they have persistency of revenue growth 156 00:08:20,960 --> 00:08:22,760 Speaker 6: out to two thousand and thirty two? 157 00:08:24,680 --> 00:08:24,920 Speaker 4: Look? 158 00:08:25,000 --> 00:08:29,200 Speaker 8: I think, for really the first time, maybe ever big 159 00:08:29,280 --> 00:08:33,560 Speaker 8: tech because of this AI revolution, the visibility and the 160 00:08:33,679 --> 00:08:38,000 Speaker 8: demand that they're seeing gives them what I believe is 161 00:08:38,040 --> 00:08:42,880 Speaker 8: almost hypergrowth into the next call it five six, seven years. 162 00:08:42,880 --> 00:08:45,840 Speaker 8: And I think that's that's essentially what we're seeing play 163 00:08:45,840 --> 00:08:48,520 Speaker 8: out here, whether it's on digital media, whether it's on cloud, 164 00:08:49,120 --> 00:08:52,760 Speaker 8: across the board, even in the tariff uncertainty, Big tech 165 00:08:53,280 --> 00:08:56,640 Speaker 8: Rock of Gibraltar. I mean, it's playing through as we 166 00:08:56,720 --> 00:08:57,120 Speaker 8: see it. 167 00:08:58,120 --> 00:08:59,480 Speaker 4: Hey, Dan, I'm looking at a Microsoft. 168 00:08:59,480 --> 00:09:03,000 Speaker 5: I mean, here's a three trillion dollars market cap company, 169 00:09:03,360 --> 00:09:05,040 Speaker 5: stocks up t pre market. 170 00:09:05,080 --> 00:09:06,680 Speaker 4: I mean, it's just amazing here. 171 00:09:07,080 --> 00:09:10,680 Speaker 5: Talk to us about what's got the street enthused tier 172 00:09:10,679 --> 00:09:11,760 Speaker 5: about Microsoft this morning? 173 00:09:12,000 --> 00:09:14,080 Speaker 8: Well, first off, I mean think about all the rumors 174 00:09:14,080 --> 00:09:18,760 Speaker 8: abandoned data centers here and there that well, how about 175 00:09:18,800 --> 00:09:22,000 Speaker 8: them apples? Right? You don't see I don't think those 176 00:09:22,000 --> 00:09:25,160 Speaker 8: a banded datas. I think that story is gonna disappear, 177 00:09:25,200 --> 00:09:28,880 Speaker 8: right because the reality is like Azure two hundred bits 178 00:09:28,920 --> 00:09:32,400 Speaker 8: above street, accelerating into the next quarter or two. I 179 00:09:32,440 --> 00:09:34,720 Speaker 8: mean to put some numbers in, I basically think like 180 00:09:35,720 --> 00:09:39,600 Speaker 8: you could be looking at for a typical Microsoft customer, 181 00:09:40,280 --> 00:09:43,600 Speaker 8: you could be looking at thirty to forty dollars of 182 00:09:43,640 --> 00:09:47,000 Speaker 8: every hundred hours that they've already spent thirty to forty 183 00:09:47,040 --> 00:09:50,480 Speaker 8: incremental just on AI spent. You put that together and 184 00:09:50,559 --> 00:09:53,800 Speaker 8: you can essentially be looking at cloud numbers are essentially 185 00:09:53,880 --> 00:09:56,280 Speaker 8: double every two years. 186 00:09:56,880 --> 00:09:57,080 Speaker 4: Dan. 187 00:09:57,160 --> 00:09:59,200 Speaker 5: Prior to the beginning of this year, all we talked 188 00:09:59,200 --> 00:10:02,120 Speaker 5: about was AI for the past couple of years, and 189 00:10:02,200 --> 00:10:05,000 Speaker 5: for the last you know, four months, we've talked about 190 00:10:05,040 --> 00:10:06,000 Speaker 5: nothing but tariffs. 191 00:10:06,480 --> 00:10:09,040 Speaker 4: How is the AI story unfolding? Now? Can you give 192 00:10:09,080 --> 00:10:09,600 Speaker 4: us an update? 193 00:10:10,880 --> 00:10:13,200 Speaker 8: Yeah, look, i'd say, and we talk about it. You 194 00:10:13,240 --> 00:10:16,240 Speaker 8: know that that Tom reference. In the last few weeks, 195 00:10:16,280 --> 00:10:19,640 Speaker 8: like all of our checks, I mean, we've we've seen 196 00:10:19,800 --> 00:10:23,320 Speaker 8: some almost acceleration and a lot of the AI spend 197 00:10:23,640 --> 00:10:26,719 Speaker 8: because I think companies are basically saying like this is 198 00:10:27,600 --> 00:10:30,880 Speaker 8: you cannot touch this, because this is really what's driving 199 00:10:30,920 --> 00:10:33,880 Speaker 8: the strategic shitter view of a lot of these coms 200 00:10:33,920 --> 00:10:35,920 Speaker 8: over the coming years. And I think we're talking to 201 00:10:36,640 --> 00:10:38,800 Speaker 8: two and a half trillion that's going to be spent 202 00:10:38,880 --> 00:10:43,000 Speaker 8: with AI, with really a small amount of companies that 203 00:10:43,040 --> 00:10:45,720 Speaker 8: are going to benefit. And I think when it comes 204 00:10:45,720 --> 00:10:46,800 Speaker 8: to tariffs is not impound. 205 00:10:47,080 --> 00:10:49,560 Speaker 2: I got a return on invested capital, Folks, that one 206 00:10:49,600 --> 00:10:52,640 Speaker 2: of the best screens in the Bloomberg terminal is w 207 00:10:52,840 --> 00:10:56,480 Speaker 2: acc Way did the average cost a capital study. It's 208 00:10:56,520 --> 00:11:00,000 Speaker 2: what's called a stern Stewart study from a million years ago, 209 00:11:00,520 --> 00:11:03,360 Speaker 2: and I got a persistent twenty five percent return on 210 00:11:03,559 --> 00:11:08,840 Speaker 2: invested capital for satchin company. Dan eives. I got revenue 211 00:11:08,880 --> 00:11:12,720 Speaker 2: pre pandemic of one hundred and twenty six gazillion. They've 212 00:11:12,720 --> 00:11:16,240 Speaker 2: done a double to where we are. Now do they 213 00:11:16,320 --> 00:11:19,440 Speaker 2: get out to I can't believe I've never said this number. 214 00:11:19,840 --> 00:11:22,960 Speaker 2: Are they going to get out to five hundred billion 215 00:11:23,559 --> 00:11:28,080 Speaker 2: in annual revenue two thousand and thirty one, two thousand 216 00:11:28,120 --> 00:11:30,200 Speaker 2: and thirty two? What's in the way of that? 217 00:11:31,800 --> 00:11:34,920 Speaker 8: I mean, I think four fifty to five hundred. I 218 00:11:34,960 --> 00:11:38,400 Speaker 8: mean it's it's hit able because just given I don't 219 00:11:38,440 --> 00:11:42,000 Speaker 8: see what's gonna stop it, just given where companies are 220 00:11:42,040 --> 00:11:44,679 Speaker 8: going and just to I mean, you put in perspective 221 00:11:44,760 --> 00:11:49,880 Speaker 8: today like you only have two percent of US enterprises 222 00:11:49,920 --> 00:11:52,720 Speaker 8: that have gone down the true aipath. It just should 223 00:11:53,080 --> 00:11:56,160 Speaker 8: that's just US. None in Europe none, really, I mean 224 00:11:56,200 --> 00:11:58,719 Speaker 8: outside of China it's minimum in termed agent. It just 225 00:11:58,760 --> 00:12:02,760 Speaker 8: shows where this is going on. Despite obviously tariff uncertainty. 226 00:12:03,400 --> 00:12:05,480 Speaker 5: Hey Dan, We're going to get our good friends from 227 00:12:05,800 --> 00:12:08,880 Speaker 5: Cooper Tino. Apples can report after the close here today. 228 00:12:09,200 --> 00:12:09,959 Speaker 4: What are you looking for? 229 00:12:11,160 --> 00:12:13,280 Speaker 8: I know like they're not going to give guidance, right, 230 00:12:13,360 --> 00:12:15,920 Speaker 8: I mean, I'd be shocked, and I think I think 231 00:12:15,920 --> 00:12:18,959 Speaker 8: the big question for them is the quarter itself actually 232 00:12:18,960 --> 00:12:21,920 Speaker 8: is pretty strong and even something that could be pulled forward. 233 00:12:22,360 --> 00:12:25,240 Speaker 8: The big question for them is like, how do you 234 00:12:25,440 --> 00:12:31,240 Speaker 8: navigate coming out with iPhone seventeen in a typical cycle 235 00:12:31,640 --> 00:12:34,520 Speaker 8: with these tariffs? What are you waiting for from the administration? 236 00:12:34,840 --> 00:12:35,120 Speaker 2: Is there? 237 00:12:35,559 --> 00:12:38,079 Speaker 8: And I think that's the question. Does the timing get 238 00:12:38,120 --> 00:12:41,760 Speaker 8: the way we've talked about for Apple obviously being bullsh 239 00:12:42,040 --> 00:12:45,000 Speaker 8: you know, for a ducade, this is you don't look 240 00:12:45,040 --> 00:12:47,200 Speaker 8: at over the next three months. You got to look 241 00:12:47,240 --> 00:12:49,040 Speaker 8: as you know, as tom Owi's reverence, you got to 242 00:12:49,040 --> 00:12:51,240 Speaker 8: look over the next twelve to eighteen months. I'll give 243 00:12:51,320 --> 00:12:54,160 Speaker 8: free cash flow, I'll get the install base, and even 244 00:12:54,200 --> 00:12:58,440 Speaker 8: if things move around and I didn't, negotiations ultimately come through, 245 00:12:58,480 --> 00:13:02,400 Speaker 8: and I think they will be much more unsteed relative 246 00:13:02,480 --> 00:13:04,480 Speaker 8: to you know, where we see things stay when it 247 00:13:04,520 --> 00:13:05,640 Speaker 8: comes to towers. 248 00:13:06,600 --> 00:13:09,120 Speaker 5: Tom Apple's gonna have over one hundred billion dollars a 249 00:13:09,200 --> 00:13:09,959 Speaker 5: free cash flow. 250 00:13:10,400 --> 00:13:10,600 Speaker 2: Yeah. 251 00:13:11,400 --> 00:13:14,360 Speaker 4: I mean, well, Dan, what do they do here with 252 00:13:14,400 --> 00:13:15,439 Speaker 4: this free cash flow here? 253 00:13:17,160 --> 00:13:19,880 Speaker 8: I mean, look, M and A has obviously been minimal 254 00:13:21,120 --> 00:13:23,640 Speaker 8: to that the way that they viewed in kuper Tina, 255 00:13:24,520 --> 00:13:27,800 Speaker 8: it's it's basically from an R O I C. It's 256 00:13:27,840 --> 00:13:30,800 Speaker 8: about to buy back and it's about ultimately how they 257 00:13:31,240 --> 00:13:33,920 Speaker 8: how they're going to continue return that to Cheryl right. 258 00:13:34,240 --> 00:13:36,800 Speaker 8: I mean, you. 259 00:13:36,880 --> 00:13:38,920 Speaker 2: Notice you don't see this on Bluebird Radio, but you 260 00:13:38,960 --> 00:13:41,920 Speaker 2: see it on YouTube. What I've does is he's at 261 00:13:41,960 --> 00:13:43,840 Speaker 2: some golf courses. He in Arizona. 262 00:13:43,840 --> 00:13:44,480 Speaker 4: I don't know where he is. 263 00:13:44,800 --> 00:13:46,320 Speaker 8: I'm in an area airport. 264 00:13:46,920 --> 00:13:50,920 Speaker 2: He drops in the wet bush backdrop of some class 265 00:13:51,520 --> 00:13:54,320 Speaker 2: hotel room. He's like in a motel five or a 266 00:13:54,360 --> 00:13:58,200 Speaker 2: Motel four somewhere instead of some two thousand dollars a 267 00:13:58,280 --> 00:14:01,000 Speaker 2: night golf course in Scott's you know, one of the 268 00:14:01,040 --> 00:14:05,960 Speaker 2: places sweeties been. Dan. I look at the belief here, 269 00:14:06,559 --> 00:14:10,120 Speaker 2: and what I see more than anything is mag seven 270 00:14:10,280 --> 00:14:16,920 Speaker 2: is under owned by disbelieving institution chefs. Retail America loves Apple. Okay, 271 00:14:17,000 --> 00:14:20,520 Speaker 2: that's a generalization of my part. But what happens when 272 00:14:20,560 --> 00:14:23,400 Speaker 2: we wake up this morning with thirty three percent as 273 00:14:23,480 --> 00:14:26,840 Speaker 2: your growth rate, what we get from Amazon tomorrow, whatever, 274 00:14:27,000 --> 00:14:29,760 Speaker 2: I just count the boxes at your bottom at discussion, 275 00:14:31,680 --> 00:14:35,600 Speaker 2: where is the institutional Wall Street these companies? 276 00:14:36,040 --> 00:14:40,640 Speaker 8: I think, well, I can nailed that retail, stuck with it, institutional. 277 00:14:41,080 --> 00:14:43,600 Speaker 8: They've hit the exit and I think they got and 278 00:14:44,240 --> 00:14:46,640 Speaker 8: they've got scared out a lot of the mags haven 279 00:14:46,680 --> 00:14:49,120 Speaker 8: a lot attack and now guess what's going to happen 280 00:14:49,160 --> 00:14:51,920 Speaker 8: over the coming weeks. They're they're going to have to 281 00:14:51,920 --> 00:14:54,040 Speaker 8: double down. And I think that's why I think the 282 00:14:54,200 --> 00:14:57,280 Speaker 8: run here that we can see intact over the next 283 00:14:57,320 --> 00:15:00,240 Speaker 8: three four weeks, especially as we go through I think 284 00:15:00,280 --> 00:15:04,600 Speaker 8: could be massive because it's under own institutionally. Because well 285 00:15:04,920 --> 00:15:07,360 Speaker 8: is Paul talked about Stock being on nine in terms 286 00:15:07,400 --> 00:15:09,240 Speaker 8: of mist there was a view that they were gonna 287 00:15:09,240 --> 00:15:13,120 Speaker 8: miss azure. They absolutely I mean, this is an Aaron 288 00:15:13,200 --> 00:15:14,360 Speaker 8: Judge like performance. 289 00:15:15,160 --> 00:15:17,800 Speaker 4: Hey, yes it is Aaron Judge. 290 00:15:18,080 --> 00:15:20,200 Speaker 5: Happened even a better year this year than last year 291 00:15:20,200 --> 00:15:23,120 Speaker 5: if that season impossible exactly? Hey, Dan talk to us 292 00:15:23,160 --> 00:15:26,080 Speaker 5: about Tesla and I think a lot of people are 293 00:15:26,120 --> 00:15:30,360 Speaker 5: probably most interested in Elon Musk. We haven't heard from 294 00:15:30,480 --> 00:15:32,760 Speaker 5: him much over the past month or two on the 295 00:15:32,880 --> 00:15:34,520 Speaker 5: Doge front. 296 00:15:34,440 --> 00:15:37,320 Speaker 7: Where do you and I know you've been very very. 297 00:15:37,120 --> 00:15:40,800 Speaker 5: Public and very outspoken about suggesting that he really needs 298 00:15:40,840 --> 00:15:43,520 Speaker 5: to get back to his day job at Tesla. What 299 00:15:43,560 --> 00:15:45,600 Speaker 5: do we know about Elon Musk and Tesla these days? 300 00:15:45,840 --> 00:15:48,520 Speaker 8: Yeah, and then obviously you know the Journal article of 301 00:15:48,560 --> 00:15:51,880 Speaker 8: j obviously a board denied. Then that came out last 302 00:15:51,960 --> 00:15:55,120 Speaker 8: night about you know, looking for a CEO potentially, Look, 303 00:15:55,200 --> 00:15:57,840 Speaker 8: the reality is a must. That was a code red 304 00:15:57,920 --> 00:16:00,920 Speaker 8: situation and it was the most important comments call he 305 00:16:01,000 --> 00:16:03,200 Speaker 8: ever had to do, and he handled it. I think 306 00:16:03,320 --> 00:16:06,400 Speaker 8: the best I've ever seen him. Pick Tesla. He's going 307 00:16:06,480 --> 00:16:08,840 Speaker 8: to lead them into this next chapter when it comes 308 00:16:08,880 --> 00:16:11,840 Speaker 8: to autonomous robotics and ultimately I think that more and 309 00:16:11,840 --> 00:16:15,400 Speaker 8: more a growth reband that we see in China and 310 00:16:15,720 --> 00:16:19,040 Speaker 8: his days the White House are done. However you want 311 00:16:19,080 --> 00:16:20,680 Speaker 8: to call it one to two days that we I mean, 312 00:16:20,720 --> 00:16:22,680 Speaker 8: I think this is the be and the end. The 313 00:16:22,720 --> 00:16:25,640 Speaker 8: board was not gonna take it, CHERYLD is not going 314 00:16:25,720 --> 00:16:28,040 Speaker 8: to take it. But that's you're talking about one of 315 00:16:28,080 --> 00:16:32,440 Speaker 8: the biggestess up the technology companies or a Muscus, Tesla's Musk. 316 00:16:32,280 --> 00:16:34,480 Speaker 2: And your community across the nation. This morning, and of 317 00:16:34,480 --> 00:16:37,600 Speaker 2: course on YouTube, Dan, I's with us with Webbush looking 318 00:16:37,640 --> 00:16:40,400 Speaker 2: over here to see the Secretary of Treasury and conversation. 319 00:16:40,840 --> 00:16:44,040 Speaker 2: I believe with Maria over at Fox Furs will monitor 320 00:16:44,080 --> 00:16:47,560 Speaker 2: those headlines from the Secretary of Treasury. It seems Paul 321 00:16:47,840 --> 00:16:50,600 Speaker 2: every time he speaks is that press conference the other day, 322 00:16:51,120 --> 00:16:52,080 Speaker 2: he moves the markets. 323 00:16:52,120 --> 00:16:54,920 Speaker 5: Guys, Hey, Dan, just on the EV front here, I 324 00:16:54,920 --> 00:16:57,800 Speaker 5: mean there's a lot of I guess, fundamental concerns here. 325 00:16:57,840 --> 00:17:00,920 Speaker 4: If you're a Tesla investor, I guess just from the 326 00:17:01,080 --> 00:17:01,640 Speaker 4: car business. 327 00:17:01,680 --> 00:17:04,920 Speaker 5: I know Elon's trying to have your focus on other areas, 328 00:17:04,920 --> 00:17:08,359 Speaker 5: but boy, by D and the Chinese operators are just 329 00:17:09,320 --> 00:17:10,400 Speaker 5: really tough, aren't they. 330 00:17:11,040 --> 00:17:12,560 Speaker 8: Yeah, it look b what I mean we've seen in 331 00:17:12,640 --> 00:17:15,720 Speaker 8: firsthand in China. You know many times BYD has done 332 00:17:16,240 --> 00:17:19,960 Speaker 8: phenomenal and but I think it's not a mutually exclusive 333 00:17:19,960 --> 00:17:21,960 Speaker 8: in other words, like Tessa is going to be also 334 00:17:22,080 --> 00:17:26,200 Speaker 8: successful in China like they have been when it comes 335 00:17:26,240 --> 00:17:30,040 Speaker 8: to the EV market. I mean, Paul, I think ninety 336 00:17:30,520 --> 00:17:33,760 Speaker 8: the future value of Tessa is going to be autonomous 337 00:17:33,880 --> 00:17:36,159 Speaker 8: about it. I mean that's my. 338 00:17:38,480 --> 00:17:40,480 Speaker 5: And and Dan just just to be clear here, the 339 00:17:40,520 --> 00:17:42,960 Speaker 5: board at Tesla thinking about a replacement. 340 00:17:43,000 --> 00:17:45,840 Speaker 4: That's not even that's not even thought of. Is it really? 341 00:17:46,800 --> 00:17:47,080 Speaker 2: Again? 342 00:17:47,240 --> 00:17:50,200 Speaker 8: Keene came, he didn't want to do it, so after 343 00:17:50,280 --> 00:17:52,360 Speaker 8: he was after he took his hat out of the ring, 344 00:17:52,560 --> 00:17:55,520 Speaker 8: there was there was no one left. Look, I think, 345 00:17:56,520 --> 00:17:59,320 Speaker 8: but Paul, they had to do something, whether it Tesla 346 00:17:59,359 --> 00:18:02,280 Speaker 8: denies or they had to do a warning shot. It 347 00:18:02,359 --> 00:18:04,080 Speaker 8: got to and we talked about with you guys while 348 00:18:04,119 --> 00:18:07,800 Speaker 8: on the ship. They it hit. It hit that moment, true. 349 00:18:07,960 --> 00:18:11,439 Speaker 2: Dan, I got a minute left on Tesla. Have you 350 00:18:11,560 --> 00:18:14,239 Speaker 2: been in one of the Chinese EV's have you you know, 351 00:18:14,240 --> 00:18:16,359 Speaker 2: you're such a hitter. Have you been like in a 352 00:18:16,440 --> 00:18:19,840 Speaker 2: B Y D yep? Are they are they nice? Are 353 00:18:19,840 --> 00:18:20,199 Speaker 2: they like? 354 00:18:20,400 --> 00:18:20,440 Speaker 7: No? 355 00:18:20,600 --> 00:18:23,120 Speaker 4: They're they're there so that you go, what are. 356 00:18:23,000 --> 00:18:26,359 Speaker 2: They like you? He doesn't. Michael bar Ives doesn't even 357 00:18:26,400 --> 00:18:29,840 Speaker 2: know what a ugo is. It's sort of like a pinto. 358 00:18:30,119 --> 00:18:32,440 Speaker 2: I wish I didn't know what you go, Jives, what's 359 00:18:32,480 --> 00:18:35,320 Speaker 2: the quality of a Chinese EV? Look? 360 00:18:35,440 --> 00:18:37,920 Speaker 8: I mean by d high quality, I mean I think 361 00:18:37,960 --> 00:18:40,240 Speaker 8: even someone like Sweeney would take that to the golf. 362 00:18:40,080 --> 00:18:43,280 Speaker 2: Course where I go, Dan, I thank you so much, 363 00:18:43,320 --> 00:18:46,200 Speaker 2: your trooper. I can't say enough about the hours Paul, 364 00:18:46,240 --> 00:18:47,720 Speaker 2: you mentioned the hours he works. 365 00:18:53,359 --> 00:18:56,960 Speaker 1: You're listening to the Bloomberg Surveillance Podcast. Catch us live 366 00:18:57,040 --> 00:19:00,000 Speaker 1: weekday afternoons from seven to ten a m Eastern. Listen 367 00:19:00,119 --> 00:19:03,720 Speaker 1: on Apple, Karplay and Android Otto with the Bloomberg Business app, 368 00:19:03,840 --> 00:19:05,600 Speaker 1: or watch us live on YouTube. 369 00:19:05,920 --> 00:19:09,280 Speaker 2: Leland Miller is a China basebook. Where's thrilled he could 370 00:19:09,359 --> 00:19:13,320 Speaker 2: join us this morning? What's the thing in the zeitgeist 371 00:19:13,480 --> 00:19:17,760 Speaker 2: on the China US US China trade war that's not 372 00:19:17,920 --> 00:19:18,920 Speaker 2: talked about enough? 373 00:19:19,440 --> 00:19:22,000 Speaker 7: Well, I think too much is being made of the 374 00:19:22,119 --> 00:19:24,320 Speaker 7: idea that she can't come to the table and Trump 375 00:19:24,400 --> 00:19:26,440 Speaker 7: can't come to the table because each of them has 376 00:19:26,480 --> 00:19:28,200 Speaker 7: to have the other one go to the table first. 377 00:19:28,560 --> 00:19:30,840 Speaker 7: It's in the boat interest of both these countries to 378 00:19:30,920 --> 00:19:33,600 Speaker 7: eventually move towards some sort of negotiation. That doesn't mean 379 00:19:33,600 --> 00:19:35,320 Speaker 7: that the negotiation is going to move to anything, but 380 00:19:35,560 --> 00:19:38,439 Speaker 7: the terriffs are in a very very high level of 381 00:19:38,480 --> 00:19:41,640 Speaker 7: both directions. They don't even serve an economic purpose past 382 00:19:41,680 --> 00:19:43,199 Speaker 7: a certain point. And if you have tariffs at one 383 00:19:43,240 --> 00:19:46,440 Speaker 7: hundred and forty five percent, even at half that, you're 384 00:19:46,480 --> 00:19:49,520 Speaker 7: not making an economic difference because no Chinese goods are 385 00:19:49,600 --> 00:19:51,680 Speaker 7: cost competitive at even half of one hundred and forty 386 00:19:51,720 --> 00:19:52,159 Speaker 7: five percent. 387 00:19:52,560 --> 00:19:55,040 Speaker 2: So the tariffs are sort of arbitrary at a certain point. 388 00:19:55,200 --> 00:19:58,160 Speaker 7: If the President wants to come to the table say look, 389 00:19:58,160 --> 00:20:00,400 Speaker 7: we'll bring things down in return you do some things 390 00:20:00,440 --> 00:20:03,960 Speaker 7: for us, that certainly is a possibility if he's feeling 391 00:20:03,960 --> 00:20:07,000 Speaker 7: economic pressure, if he's feeling pressure to sort of coalesce 392 00:20:07,240 --> 00:20:10,960 Speaker 7: the Republican Party in one direction towards towards the tax 393 00:20:10,960 --> 00:20:12,840 Speaker 7: bill as well. So there's a lot of pressures that 394 00:20:12,840 --> 00:20:14,919 Speaker 7: are building up as we get towards summertime, they're going 395 00:20:14,920 --> 00:20:17,560 Speaker 7: to sort of change the dynamics around the tariff discussion. 396 00:20:18,280 --> 00:20:20,639 Speaker 5: Lee, then, can you give us a sense of where 397 00:20:21,040 --> 00:20:23,880 Speaker 5: you think China is in terms of its relative strength 398 00:20:24,440 --> 00:20:26,760 Speaker 5: in negotiating with the United States. 399 00:20:27,240 --> 00:20:28,160 Speaker 4: Give us a sense. 400 00:20:27,920 --> 00:20:31,240 Speaker 5: Of how things are in China and how they might 401 00:20:31,359 --> 00:20:33,240 Speaker 5: impact its ability to negotiate. 402 00:20:32,800 --> 00:20:35,400 Speaker 9: With us well in a vacuum. 403 00:20:35,400 --> 00:20:38,200 Speaker 7: The United States has much much more leverage over China 404 00:20:38,200 --> 00:20:40,200 Speaker 7: than China has of the United States because the size 405 00:20:40,240 --> 00:20:43,600 Speaker 7: of the of the of the trade surplus that that 406 00:20:43,600 --> 00:20:46,679 Speaker 7: that China has the United States. And I think that 407 00:20:46,720 --> 00:20:49,760 Speaker 7: the idea here is if that were all we were 408 00:20:49,800 --> 00:20:52,000 Speaker 7: talking about, there is there's a very good chance that 409 00:20:52,000 --> 00:20:54,560 Speaker 7: the United States could just weigh this out. The problem 410 00:20:54,600 --> 00:20:55,879 Speaker 7: is there's a lot of other things going on in 411 00:20:55,880 --> 00:20:59,720 Speaker 7: the world. You've got You've got tariff battles with with 412 00:20:59,720 --> 00:21:03,160 Speaker 7: with about everybody right now, and so it's a question 413 00:21:03,240 --> 00:21:05,679 Speaker 7: of who has a higher pain tolerance. And the Chinese 414 00:21:05,760 --> 00:21:08,240 Speaker 7: have a higher pain tolerance in the US than the 415 00:21:08,280 --> 00:21:10,840 Speaker 7: Americans do because of the fact that the American system 416 00:21:11,119 --> 00:21:13,919 Speaker 7: doesn't quite allow for what the Chinese system does. So 417 00:21:13,960 --> 00:21:16,359 Speaker 7: I think right now it's a question of who wants 418 00:21:16,400 --> 00:21:19,520 Speaker 7: to take the most pain. The Chinese economy is under 419 00:21:19,680 --> 00:21:23,119 Speaker 7: some duress right now, but the United States economy is 420 00:21:23,119 --> 00:21:24,600 Speaker 7: going to be under more dress as we get into 421 00:21:24,640 --> 00:21:28,840 Speaker 7: mid Bay and retail shelves are aren't restocked and freight 422 00:21:28,920 --> 00:21:31,119 Speaker 7: starts breaking down. So there's a lot of pressure right 423 00:21:31,160 --> 00:21:34,520 Speaker 7: now to come to some sort of you know, short 424 00:21:34,600 --> 00:21:36,639 Speaker 7: term solution as we think through how this is going 425 00:21:36,680 --> 00:21:37,240 Speaker 7: to end out. 426 00:21:37,920 --> 00:21:39,959 Speaker 4: So how do you expect this to play out? Leland? 427 00:21:40,040 --> 00:21:43,879 Speaker 5: I mean, do you expect a meeting between President Trump 428 00:21:43,880 --> 00:21:47,040 Speaker 5: and President She? Do you think maybe it'll just be 429 00:21:47,440 --> 00:21:50,680 Speaker 5: trade representatives hammering out something, just the meat and potatoes 430 00:21:50,720 --> 00:21:51,919 Speaker 5: kind of stuff that always happens. 431 00:21:52,160 --> 00:21:53,479 Speaker 4: How do you think this might play out? 432 00:21:54,000 --> 00:21:56,360 Speaker 7: Well, Trump clearly wants to get in the room with she, 433 00:21:56,960 --> 00:21:58,320 Speaker 7: and she doesn't want to get in the room with 434 00:21:58,359 --> 00:22:01,880 Speaker 7: Trump because he's worried that will do something to embarrass him, 435 00:22:01,920 --> 00:22:04,840 Speaker 7: that he'll say that something's happening, or and then he'll 436 00:22:04,840 --> 00:22:07,680 Speaker 7: go back after she agrees. So there's there's a cadence 437 00:22:07,720 --> 00:22:09,800 Speaker 7: to this that has to happen. I think in order 438 00:22:09,840 --> 00:22:13,960 Speaker 7: for anything enduring to to move forward, somebody that will 439 00:22:14,000 --> 00:22:16,479 Speaker 7: stay for longer than a few weeks or a few months, 440 00:22:16,720 --> 00:22:18,240 Speaker 7: you have to get the two leaders in a room 441 00:22:18,240 --> 00:22:19,639 Speaker 7: and you have to have them agree in front of 442 00:22:19,640 --> 00:22:21,840 Speaker 7: a camera that this is the deal going forward. But 443 00:22:21,880 --> 00:22:24,760 Speaker 7: that's not necessarily any you know, any going to happen 444 00:22:24,760 --> 00:22:26,480 Speaker 7: in the near term because the Chinese side is very 445 00:22:26,480 --> 00:22:29,520 Speaker 7: worried that the Americans are going to change the nature 446 00:22:29,520 --> 00:22:30,400 Speaker 7: of the games. 447 00:22:30,680 --> 00:22:33,600 Speaker 2: Involved Leland Miller to China, Beijing, where it's just thrilled 448 00:22:33,640 --> 00:22:36,480 Speaker 2: that he's with us. Okay, here's the reality, folks, And 449 00:22:36,560 --> 00:22:40,359 Speaker 2: Paul knows this. When I say I went to China, 450 00:22:40,480 --> 00:22:44,879 Speaker 2: it's the airport a Mercedes. Maybe you go two miles, 451 00:22:44,920 --> 00:22:49,199 Speaker 2: three miles Shanghai, a little longer some fancy hotel, a 452 00:22:49,240 --> 00:22:51,360 Speaker 2: fancy office. Yep. Then I get in the. 453 00:22:51,320 --> 00:22:55,720 Speaker 6: Cargo back to the airport and I've been deep into China. 454 00:22:55,320 --> 00:22:58,040 Speaker 2: Leland Miller. I want to go deep into China right now? 455 00:22:58,160 --> 00:23:02,080 Speaker 2: Southwest of Beijing. I guess north, a little bit west 456 00:23:02,160 --> 00:23:06,399 Speaker 2: rather of Shanghai, and I'm gonna I think I'm mispronouncing it. 457 00:23:06,480 --> 00:23:15,560 Speaker 2: Shang She's Sha n Xi, huge manufacturing appliance place. What 458 00:23:15,680 --> 00:23:18,000 Speaker 2: do they do, I mean, when they're out of a job, 459 00:23:18,600 --> 00:23:22,080 Speaker 2: are they like starving? Or is there a social net 460 00:23:22,200 --> 00:23:26,000 Speaker 2: in this trade war for people deep into China and 461 00:23:26,080 --> 00:23:27,760 Speaker 2: all those manufacturing jobs. 462 00:23:28,240 --> 00:23:30,760 Speaker 7: Well, there is a social safety net, but there's also 463 00:23:30,800 --> 00:23:33,720 Speaker 7: a lot of pain. So we're seeing right now manufacturing 464 00:23:33,720 --> 00:23:36,399 Speaker 7: in China is actually under a lot of duress. The 465 00:23:36,960 --> 00:23:41,320 Speaker 7: economy outside of manufacturing is actually looking more resilient than 466 00:23:41,359 --> 00:23:43,359 Speaker 7: it did earlier this year. You know that if you 467 00:23:43,359 --> 00:23:45,199 Speaker 7: look at the PMI has just reported all these things 468 00:23:45,240 --> 00:23:48,080 Speaker 7: happening in manufacturing. We had that data last month and 469 00:23:48,119 --> 00:23:50,199 Speaker 7: so we saw a huge fall off last month. We 470 00:23:50,200 --> 00:23:53,000 Speaker 7: saw the end of most of the front loading happened 471 00:23:53,000 --> 00:23:54,920 Speaker 7: at the end of last year. So what we're seeing 472 00:23:55,000 --> 00:23:57,520 Speaker 7: right now is a is some resilience in the economy 473 00:23:57,520 --> 00:24:00,000 Speaker 7: outside of manufacturing, but a lot of pain within manufacturing. 474 00:24:00,280 --> 00:24:02,679 Speaker 7: So what do they do with manufacturing? The cost of 475 00:24:02,680 --> 00:24:05,399 Speaker 7: credits going down, there's they're they're they're boosting it any 476 00:24:05,440 --> 00:24:08,480 Speaker 7: way they can. They're gonna have to. Fiscal support is 477 00:24:08,520 --> 00:24:10,879 Speaker 7: going up, so they're gonna have to continue to support 478 00:24:10,880 --> 00:24:13,320 Speaker 7: manufacturing more and more and more because if this trade 479 00:24:13,359 --> 00:24:17,080 Speaker 7: war does continue, then they're gonna be under significant page. 480 00:24:16,880 --> 00:24:20,040 Speaker 2: Okay, so classic economy and a command control economy, I 481 00:24:20,040 --> 00:24:23,760 Speaker 2: get that. The classic economics. Here, they're gonna give a 482 00:24:23,800 --> 00:24:27,840 Speaker 2: surplus spur to the people of China, and the only 483 00:24:27,920 --> 00:24:31,080 Speaker 2: outro there is a depreciation of the Chinese. You want? 484 00:24:31,560 --> 00:24:34,840 Speaker 2: Is that just? Is that a Leland Miller certain to happen? 485 00:24:35,480 --> 00:24:36,639 Speaker 6: Now, I don't think it's certain at all. 486 00:24:36,640 --> 00:24:37,960 Speaker 7: As a matter of fact, I don't think they want 487 00:24:38,000 --> 00:24:40,440 Speaker 7: it to happen unless there's a break the glass emergency. 488 00:24:40,720 --> 00:24:42,880 Speaker 7: So one of the problems with just appreciating your way 489 00:24:42,880 --> 00:24:45,080 Speaker 7: out of this. Yes, it would help manufacturing, it would 490 00:24:45,160 --> 00:24:47,800 Speaker 7: it would badly hurt consumption. It would be a political 491 00:24:47,840 --> 00:24:51,280 Speaker 7: disaster for China around the world because there'd be countere valuations, 492 00:24:51,320 --> 00:24:54,080 Speaker 7: there'd be a enormous amount of political friction from that, 493 00:24:54,440 --> 00:24:57,240 Speaker 7: especially for the United States, but but also for everywhere else. 494 00:24:57,520 --> 00:24:59,920 Speaker 7: So the the you know, the you want is talk 495 00:25:00,119 --> 00:25:03,720 Speaker 7: about as if it's a tool in China's economic weaponry. 496 00:25:03,920 --> 00:25:06,240 Speaker 7: It's really not. It's at the end of the lion 497 00:25:06,400 --> 00:25:09,159 Speaker 7: to break the glass eburgency. If they do anything other 498 00:25:09,200 --> 00:25:12,720 Speaker 7: than just sort of ease, you know, ease pressure off 499 00:25:12,720 --> 00:25:15,760 Speaker 7: the currency and very gradual movements, they're going to get 500 00:25:15,800 --> 00:25:17,360 Speaker 7: a lot of political friction for the rest of the world, 501 00:25:17,400 --> 00:25:19,239 Speaker 7: particularly United States. I don't think they want that, and 502 00:25:19,320 --> 00:25:21,200 Speaker 7: they don't want the domestic repercussions either. 503 00:25:21,400 --> 00:25:23,920 Speaker 2: Don't be a stranger, Leila Miller. Thank you so much, 504 00:25:24,119 --> 00:25:24,760 Speaker 2: China BASEBA. 505 00:25:25,040 --> 00:25:28,920 Speaker 1: This is the Bloomberg Surveillance Podcast. Listen live each weekday 506 00:25:28,960 --> 00:25:32,240 Speaker 1: starting at seven am Eastern on Applecarplay and Android Auto 507 00:25:32,359 --> 00:25:35,359 Speaker 1: with the Bloomberg Business app. You can also listen live 508 00:25:35,400 --> 00:25:39,000 Speaker 1: on Amazon Alexa from our flagship New York station, Just 509 00:25:39,040 --> 00:25:41,520 Speaker 1: say Alexa play Bloomberg eleven thirty. 510 00:25:41,640 --> 00:25:44,199 Speaker 2: He's joined us before and for all of you across 511 00:25:44,240 --> 00:25:47,440 Speaker 2: the nation and your commute on YouTube across this nation, 512 00:25:47,680 --> 00:25:51,560 Speaker 2: Canada and Mexico, around the world. The New York City 513 00:25:52,000 --> 00:25:55,720 Speaker 2: mayoral primary, the Democratic Party primary, because there's like twelve 514 00:25:55,760 --> 00:26:00,639 Speaker 2: Republicans within the tri state area. I'm kidding. The answer is, 515 00:26:00,720 --> 00:26:04,879 Speaker 2: it's a really interesting study on a budget standpoint of 516 00:26:04,920 --> 00:26:06,600 Speaker 2: what to come. We've had in a number of the 517 00:26:06,640 --> 00:26:10,159 Speaker 2: candidates joining us again. Brad Lander joins us. He's a 518 00:26:10,240 --> 00:26:14,639 Speaker 2: forty fifth New York City controller, understands budgets. He's to 519 00:26:14,760 --> 00:26:16,600 Speaker 2: the left of left. But hey, you know what, it's 520 00:26:16,640 --> 00:26:20,879 Speaker 2: a big city. We had a budget yesterday, and I 521 00:26:20,920 --> 00:26:23,400 Speaker 2: get it. It's an election year. Mayor Adams put out 522 00:26:23,400 --> 00:26:26,840 Speaker 2: a budget that is, if I'm elected, free beer. But 523 00:26:27,040 --> 00:26:30,920 Speaker 2: how close are we to the headlines from another time 524 00:26:31,000 --> 00:26:35,040 Speaker 2: in place? There's a movie out now on this four 525 00:26:35,119 --> 00:26:38,840 Speaker 2: to city Drop Dead? Are we going to screw this 526 00:26:38,960 --> 00:26:41,760 Speaker 2: up so bad? Whoever is a new mayor that we're 527 00:26:41,760 --> 00:26:46,520 Speaker 2: going to see Trump to city full colon drop dead? 528 00:26:46,720 --> 00:26:49,280 Speaker 9: The mayor that Eric Adams. The budget that Mayor Eric 529 00:26:49,280 --> 00:26:52,879 Speaker 9: Adams put out yesterday is preposterous. It makes no allowances 530 00:26:52,880 --> 00:26:55,680 Speaker 9: for the likelihood of an economic downturn, no allowances for 531 00:26:55,760 --> 00:26:58,920 Speaker 9: the likelihood of federal budget cuts. He doesn't put one 532 00:26:59,160 --> 00:27:02,480 Speaker 9: penny in reserves, and it's got a one point four 533 00:27:02,480 --> 00:27:06,480 Speaker 9: billion dollar deficit in the current fiscal year. So yes, 534 00:27:06,520 --> 00:27:09,440 Speaker 9: this is him trying to campaign even though he long 535 00:27:09,560 --> 00:27:13,359 Speaker 9: destroyed his chances of people voting for him again. But yes, 536 00:27:13,400 --> 00:27:16,240 Speaker 9: he is going to hand the next mayor or real problem, 537 00:27:16,280 --> 00:27:18,600 Speaker 9: which is why New Yorkers need someone who knows how 538 00:27:18,600 --> 00:27:19,320 Speaker 9: the budget works. 539 00:27:19,520 --> 00:27:21,520 Speaker 4: Give us it. Just a sense of the state of 540 00:27:21,560 --> 00:27:24,720 Speaker 4: the city right now from a financial perspective, where are we? 541 00:27:25,040 --> 00:27:28,800 Speaker 9: Yeah, so before the tariff threats, we were actually in 542 00:27:28,840 --> 00:27:32,199 Speaker 9: pretty good shape. Private sector jobs back up above the 543 00:27:32,240 --> 00:27:38,159 Speaker 9: pandemic for the first time, commercial vacancies starting to decline. 544 00:27:38,359 --> 00:27:40,960 Speaker 9: Now too much growth in low wage sectors healthcare and 545 00:27:41,000 --> 00:27:44,800 Speaker 9: social services, but some promising signs. But if the tariffs 546 00:27:45,200 --> 00:27:48,000 Speaker 9: tip us into an economic downturn or a recession, that'll 547 00:27:48,000 --> 00:27:50,199 Speaker 9: blow a big hole in our budget. If there are 548 00:27:50,200 --> 00:27:54,000 Speaker 9: a big federal budget cuts to course services, that'll blow 549 00:27:54,000 --> 00:27:55,120 Speaker 9: a big hole in our budget. 550 00:27:55,200 --> 00:27:58,720 Speaker 5: Do you at this point anticipate the federal government cutting 551 00:27:58,760 --> 00:28:02,159 Speaker 5: back support of New York City for example? 552 00:28:02,240 --> 00:28:04,440 Speaker 9: Yeah, going two different ways. Look, the budget that they've 553 00:28:04,480 --> 00:28:06,680 Speaker 9: set the framework up for is going to cut money 554 00:28:06,680 --> 00:28:10,200 Speaker 9: to all cities and states, leave politics aside, and that's 555 00:28:10,280 --> 00:28:12,520 Speaker 9: you know, money for school lunches and money for healthcare 556 00:28:12,520 --> 00:28:15,200 Speaker 9: in our public hospitals. And then yes, I mean Trump 557 00:28:15,240 --> 00:28:18,760 Speaker 9: is clearly aiming at cities like New York, and that's 558 00:28:18,800 --> 00:28:21,560 Speaker 9: a real risk. So I've recommended putting a billion dollars 559 00:28:21,600 --> 00:28:23,920 Speaker 9: more in our Rainy Day Fund, a billion dollars more 560 00:28:23,960 --> 00:28:27,359 Speaker 9: in our general reserve, just so we could be prepared 561 00:28:27,400 --> 00:28:28,320 Speaker 9: for what's coming. 562 00:28:28,280 --> 00:28:31,800 Speaker 2: The land or distinction, like a lot of most people 563 00:28:31,880 --> 00:28:34,480 Speaker 2: grew up in one zip code, you know, on this 564 00:28:34,600 --> 00:28:36,560 Speaker 2: side of that side of Central Park or one of 565 00:28:36,560 --> 00:28:40,560 Speaker 2: the boroughs. You grew up in the shadow of kmox 566 00:28:40,600 --> 00:28:44,400 Speaker 2: out in Saint Louis, you are different because you actually 567 00:28:44,520 --> 00:28:48,120 Speaker 2: understand there's other cities out there, just like New York. 568 00:28:48,360 --> 00:28:50,560 Speaker 2: How bad is this going to be for Saint Louis 569 00:28:51,160 --> 00:28:54,680 Speaker 2: or for Dallas or for a very beleagued crime ridden 570 00:28:54,680 --> 00:28:55,320 Speaker 2: in Chicago. 571 00:28:55,800 --> 00:28:58,160 Speaker 9: Look, this is going to be a challenge for every city. 572 00:28:58,200 --> 00:29:01,000 Speaker 9: If you lose the federal funding that pays your school lunches, 573 00:29:01,120 --> 00:29:03,479 Speaker 9: or the money and your public hospitals, or your housing 574 00:29:03,600 --> 00:29:05,560 Speaker 9: vouchers there were you know, New York stands to lose 575 00:29:05,600 --> 00:29:08,360 Speaker 9: eight thousand housing vouchers. I don't know how many Saint. 576 00:29:08,200 --> 00:29:11,360 Speaker 2: Louis President Trump have the power to do that. Does 577 00:29:11,360 --> 00:29:14,280 Speaker 2: he have the power in two thousand and seventy five 578 00:29:14,680 --> 00:29:17,120 Speaker 2: to say, Trump to city drop dead? 579 00:29:17,440 --> 00:29:20,280 Speaker 9: Look, you know these eight thousand housing vouchers he's already 580 00:29:20,280 --> 00:29:22,360 Speaker 9: said he's going to cut. He absolutely has that power. 581 00:29:22,360 --> 00:29:24,880 Speaker 9: That'd be eight thousand more homeless families if we don't 582 00:29:24,920 --> 00:29:25,760 Speaker 9: do something about it. 583 00:29:26,640 --> 00:29:28,959 Speaker 5: Right outside our front doors here on Lexington Avenue, we've 584 00:29:28,960 --> 00:29:32,120 Speaker 5: got these big cameras on Lexington Avenue for the congestion pricing. 585 00:29:32,680 --> 00:29:35,120 Speaker 4: What's your view on that? Where are we on that? 586 00:29:35,320 --> 00:29:37,440 Speaker 9: It's a great step forward. You know, I was one 587 00:29:37,440 --> 00:29:39,440 Speaker 9: of the people. I've been fighting for it alongside Mike 588 00:29:39,440 --> 00:29:42,160 Speaker 9: Bloomberg since two thousand and seven when the governor put 589 00:29:42,160 --> 00:29:45,920 Speaker 9: it on pause. I convened the litigation coalition that got 590 00:29:45,920 --> 00:29:48,520 Speaker 9: it off pause by bringing two lawsuits. And now we've 591 00:29:48,560 --> 00:29:51,160 Speaker 9: got one hundred and sixty million dollars more headed toward 592 00:29:51,240 --> 00:29:55,120 Speaker 9: fifteen billion to invest in modern signals, in subway elevators, 593 00:29:55,120 --> 00:29:57,680 Speaker 9: in platform barriers and station gates. Is it better faster 594 00:29:57,800 --> 00:30:01,520 Speaker 9: subway service? Travel Time across the bridges are up ten 595 00:30:01,560 --> 00:30:05,560 Speaker 9: to thirty percent, Traffic is down twelve percent. More people 596 00:30:05,600 --> 00:30:07,760 Speaker 9: are on the subways more people are on the buses, 597 00:30:07,920 --> 00:30:10,280 Speaker 9: more people are taking a city bike. It is working 598 00:30:10,440 --> 00:30:11,840 Speaker 9: better than anybody predicting. 599 00:30:11,920 --> 00:30:15,280 Speaker 2: North to sixtieth Street, Park Avenue looks like downtown in 600 00:30:15,360 --> 00:30:19,080 Speaker 2: nineteen ten. It's like jammed up outside the congestion or 601 00:30:19,440 --> 00:30:20,240 Speaker 2: am I right on that? 602 00:30:20,760 --> 00:30:23,200 Speaker 9: There have not been big traffic backups, even on the 603 00:30:23,280 --> 00:30:25,640 Speaker 9: edges of the zone. Honestly, it is working better than 604 00:30:25,680 --> 00:30:29,160 Speaker 9: anyone expected. Foot traffic is up, business is going well. 605 00:30:29,200 --> 00:30:31,400 Speaker 9: This is one that I thought would be good. It's 606 00:30:31,440 --> 00:30:32,000 Speaker 9: even better. 607 00:30:32,120 --> 00:30:35,320 Speaker 2: Redlander, with this New York City controller and may oral 608 00:30:35,440 --> 00:30:38,680 Speaker 2: candidate here, what do you do up to the June primary? 609 00:30:38,720 --> 00:30:42,360 Speaker 2: I mean, well, what's the do you in this fractured 610 00:30:42,560 --> 00:30:45,800 Speaker 2: cultural New York City? I mean, I don't think it's 611 00:30:45,840 --> 00:30:49,240 Speaker 2: a city of a Beam or David Dinkins or others. Now, 612 00:30:49,600 --> 00:30:52,320 Speaker 2: how do you campaign in this modern age? 613 00:30:52,400 --> 00:30:55,080 Speaker 9: Well, first, you go everywhere, and it's an amazing city. 614 00:30:55,120 --> 00:30:58,400 Speaker 9: Yesterday I was out in Brownsville, I'm up in the Bronx, 615 00:30:58,480 --> 00:31:01,080 Speaker 9: I'm in all the as many neighborhood as I can 616 00:31:01,120 --> 00:31:02,840 Speaker 9: be personally. Of course, I'm up on the air with 617 00:31:02,880 --> 00:31:06,520 Speaker 9: TV ads next week. You're doing radio digital, You're getting 618 00:31:06,520 --> 00:31:08,680 Speaker 9: out on every single place. I love being here. 619 00:31:09,360 --> 00:31:09,760 Speaker 2: It's fun. 620 00:31:09,840 --> 00:31:12,880 Speaker 9: New Yorkers are amazing. They're very diverse. They tell you 621 00:31:12,920 --> 00:31:15,520 Speaker 9: how they feel. They're pissed off about how much how 622 00:31:15,520 --> 00:31:18,440 Speaker 9: expensive it is, and how expensive housing and childcare are. 623 00:31:18,720 --> 00:31:20,760 Speaker 9: They want to feel safer on the subways. So they 624 00:31:20,800 --> 00:31:23,600 Speaker 9: love hearing my plan to end street homelessness for folks 625 00:31:23,600 --> 00:31:24,840 Speaker 9: with serious mental illness. 626 00:31:24,960 --> 00:31:26,560 Speaker 4: What they want solution? 627 00:31:27,000 --> 00:31:28,880 Speaker 5: I mean, Tom and I we've been in this city 628 00:31:28,880 --> 00:31:29,920 Speaker 5: for a long long time. 629 00:31:29,960 --> 00:31:30,680 Speaker 4: Lisa as well. 630 00:31:31,960 --> 00:31:35,040 Speaker 9: What does the city like New York do on that. Look, 631 00:31:35,080 --> 00:31:38,080 Speaker 9: it's only about two thousand people who have serious mental 632 00:31:38,120 --> 00:31:40,840 Speaker 9: illness and are sleeping on subways and streets. We can 633 00:31:40,880 --> 00:31:44,400 Speaker 9: connect them to housing and services with a better continuum 634 00:31:44,400 --> 00:31:46,480 Speaker 9: of care and a model called Housing First. I put 635 00:31:46,480 --> 00:31:47,520 Speaker 9: out a plan to do it. 636 00:31:47,840 --> 00:31:48,400 Speaker 6: One of the. 637 00:31:48,240 --> 00:31:51,000 Speaker 2: Themes we're hearing from all the candidates, including your bread, 638 00:31:51,600 --> 00:31:55,120 Speaker 2: is the basic idea we need more police officers. You're 639 00:31:55,200 --> 00:31:59,760 Speaker 2: a liberal, how do you meet the Staten Island block 640 00:32:00,040 --> 00:32:03,720 Speaker 2: It says we're three thousand short now NYPD? How do 641 00:32:03,760 --> 00:32:04,800 Speaker 2: we affect that change? 642 00:32:04,840 --> 00:32:06,760 Speaker 9: Yeah, I mean I'm honest about it. I do think 643 00:32:06,800 --> 00:32:10,400 Speaker 9: progresses myself included. We're slow to reckon with rising disorder 644 00:32:10,480 --> 00:32:14,360 Speaker 9: coming out of the pandemic mental health crime, crime crime, 645 00:32:14,680 --> 00:32:18,080 Speaker 9: mental health disorder. But look, we're now, you know, fifteen 646 00:32:18,120 --> 00:32:20,840 Speaker 9: hundred officers down and by January first, it'll probably be 647 00:32:20,880 --> 00:32:22,880 Speaker 9: two or three thousand. So I have a plan to 648 00:32:22,920 --> 00:32:27,400 Speaker 9: recruit and retain officers underpaid. Growing the NYPD Cadet program. Well, 649 00:32:27,960 --> 00:32:30,440 Speaker 9: my big idea is, let's grow the NYPD Cadet program, 650 00:32:30,440 --> 00:32:33,160 Speaker 9: which brings people in and pays their college tuition. But 651 00:32:33,200 --> 00:32:35,600 Speaker 9: you have to be halfway through college first. Let's open 652 00:32:35,600 --> 00:32:37,640 Speaker 9: that up to kids out of high school. They could 653 00:32:37,640 --> 00:32:41,120 Speaker 9: become cadets. They start getting paid, they get their tuition covered, 654 00:32:41,120 --> 00:32:42,960 Speaker 9: they become better officers, keep our cities. 655 00:32:42,960 --> 00:32:46,520 Speaker 2: Say a two year old NYPD officer can go out 656 00:32:46,560 --> 00:32:49,880 Speaker 2: to the suburbs for more money, right are they? Frankly, 657 00:32:49,920 --> 00:32:54,000 Speaker 2: the nurses, the teachers, everybody else. It is the pay 658 00:32:54,040 --> 00:32:58,520 Speaker 2: grid of New York City. Underpaid is a general statement. 659 00:32:58,760 --> 00:33:00,520 Speaker 2: After X years, it's. 660 00:33:00,520 --> 00:33:03,200 Speaker 9: Very expensive to live in New York City. That is 661 00:33:03,240 --> 00:33:05,720 Speaker 9: a huge part of the challenge. That's why I'm focused 662 00:33:05,720 --> 00:33:08,480 Speaker 9: on housing affordability. I've got a program called Homes for 663 00:33:08,640 --> 00:33:12,600 Speaker 9: City Workers that'll invest pension funds alongside teachers and cops 664 00:33:12,760 --> 00:33:14,800 Speaker 9: and double the home they could afford. So if they 665 00:33:14,800 --> 00:33:17,720 Speaker 9: could afford a four hundred thousand dollars mortgage pension fund 666 00:33:17,800 --> 00:33:21,000 Speaker 9: invest alongside, they can buy an eight hundred thousand dollars home, 667 00:33:21,320 --> 00:33:23,800 Speaker 9: split the proceeds when they sell it. The pension funds 668 00:33:23,800 --> 00:33:25,960 Speaker 9: will keep doing well and we could have the next 669 00:33:26,000 --> 00:33:31,480 Speaker 9: generation of homeowners who are teachers, firefighters, cops, public hospital nurses. 670 00:33:31,560 --> 00:33:36,760 Speaker 9: That's what we need in New York, Saint Louis Cardinals. 671 00:33:37,200 --> 00:33:40,600 Speaker 9: But to this week, New York Knicks, I'm excited. You're 672 00:33:40,680 --> 00:33:44,880 Speaker 9: doing great. Let's you know, prostitutle for that game. Controller 673 00:33:46,040 --> 00:33:49,560 Speaker 9: comptroller buys his own seats in the noise greed section. 674 00:33:50,200 --> 00:33:53,000 Speaker 2: Brad Lander, thank you so much, New York City Controller. 675 00:33:58,560 --> 00:34:02,040 Speaker 1: This is the Bloomberg Survey Lengths podcast. Listen live each 676 00:34:02,080 --> 00:34:05,520 Speaker 1: weekday starting at seven am Eastern on Applecarplay and Android 677 00:34:05,560 --> 00:34:08,520 Speaker 1: Auto with the Bloomberg Business app. You can also watch 678 00:34:08,640 --> 00:34:11,560 Speaker 1: us live every weekday on YouTube and always on the 679 00:34:11,600 --> 00:34:12,680 Speaker 1: Bloomberg terminal. 680 00:34:12,960 --> 00:34:14,759 Speaker 2: Now the newspapers, here's Lisa to two. 681 00:34:14,920 --> 00:34:16,759 Speaker 10: Okay, so we all know how AI is being used 682 00:34:16,760 --> 00:34:19,359 Speaker 10: for so many things, right, so here is another. 683 00:34:19,320 --> 00:34:20,200 Speaker 9: Use for it. 684 00:34:20,200 --> 00:34:23,600 Speaker 10: It's helping job seekers find new careers, not just a 685 00:34:23,600 --> 00:34:26,200 Speaker 10: new job, but an entirely new career. So you have 686 00:34:26,239 --> 00:34:29,760 Speaker 10: AI tools from companies like Salesforce, Google, LinkedIn. They're helping 687 00:34:29,800 --> 00:34:34,560 Speaker 10: workers basically sell their skills, tailor their resumes to new areas, 688 00:34:34,680 --> 00:34:36,880 Speaker 10: identify roles that are kind of under the radar that 689 00:34:36,880 --> 00:34:37,400 Speaker 10: they wouldn't have. 690 00:34:37,400 --> 00:34:38,240 Speaker 7: Thought about before. 691 00:34:39,000 --> 00:34:42,399 Speaker 10: It's already in positions, and people in positions are already using 692 00:34:42,440 --> 00:34:45,720 Speaker 10: it within the company. For example, Salesforce has this AI 693 00:34:45,760 --> 00:34:49,920 Speaker 10: tool called Career Connect, so it analyzes their skills, right, 694 00:34:49,960 --> 00:34:53,279 Speaker 10: it recommends roles internally that they might not have thought of. 695 00:34:53,360 --> 00:34:56,279 Speaker 10: And then you have LinkedIn has one too, Google has 696 00:34:56,440 --> 00:34:57,360 Speaker 10: career Dreamer. 697 00:34:57,600 --> 00:35:01,120 Speaker 2: Is Salesforce just to pick on that wonderful shop? Do 698 00:35:01,160 --> 00:35:04,040 Speaker 2: they also use AI for career exit? Are they using 699 00:35:04,080 --> 00:35:05,080 Speaker 2: it to get rid of people? 700 00:35:05,160 --> 00:35:09,200 Speaker 10: Oh, that's a good question. That's usually yeah, it's usually 701 00:35:09,239 --> 00:35:10,439 Speaker 10: the word to get them in, but not. 702 00:35:10,360 --> 00:35:12,840 Speaker 4: To get them out. That's interesting. I mean, it's amazing. 703 00:35:12,960 --> 00:35:16,320 Speaker 2: What a I couldn't use stock movers exactly? 704 00:35:16,320 --> 00:35:17,200 Speaker 4: Well, I don't know. 705 00:35:17,760 --> 00:35:20,120 Speaker 5: Maybe I do give those emails from like your LinkedIn 706 00:35:20,160 --> 00:35:20,520 Speaker 5: and stuff. 707 00:35:20,520 --> 00:35:22,040 Speaker 4: Hey this job might be good for you, you know, 708 00:35:22,040 --> 00:35:25,320 Speaker 4: But suggests yeah, but I'm like I don't think so. Yeah, 709 00:35:25,360 --> 00:35:25,640 Speaker 4: but it. 710 00:35:25,640 --> 00:35:27,480 Speaker 10: Kind of like opens up their eyes, like you know, 711 00:35:27,520 --> 00:35:29,040 Speaker 10: you're like, wow, I never would have thought of that. 712 00:35:29,239 --> 00:35:31,960 Speaker 2: I got a LinkedIn email. This job would be good 713 00:35:31,960 --> 00:35:35,759 Speaker 2: for you. It was a lifeguard in Philadelphia. 714 00:35:39,360 --> 00:35:43,880 Speaker 10: Next, okay, we'll stick with tech, will go to eyeball 715 00:35:44,000 --> 00:35:47,080 Speaker 10: scanning technology. Okay, I don't know if either of you 716 00:35:47,120 --> 00:35:48,960 Speaker 10: would be up for it, but it's from the company 717 00:35:49,000 --> 00:35:53,719 Speaker 10: Tools for Humanity start up for COVID or no, why 718 00:35:53,760 --> 00:35:54,080 Speaker 10: would that? 719 00:35:54,120 --> 00:35:56,200 Speaker 2: Part of it is like Star Wars. 720 00:35:56,040 --> 00:35:59,640 Speaker 10: Straight out of Star Wars. So it's starting this week 721 00:35:59,719 --> 00:36:03,000 Speaker 10: people in like six cities San Francisco, La Atlanta or 722 00:36:03,000 --> 00:36:05,480 Speaker 10: some of them, and you can scan your eyes using 723 00:36:05,520 --> 00:36:09,320 Speaker 10: this spherical orb device at certain locations. So it's basically 724 00:36:09,400 --> 00:36:12,560 Speaker 10: to verify your identity, prove someone is human because there's 725 00:36:12,560 --> 00:36:16,000 Speaker 10: so many aid fakes out there. Okay, so that's why 726 00:36:16,000 --> 00:36:18,879 Speaker 10: they're doing this. And what's really interesting is that they're 727 00:36:19,000 --> 00:36:22,439 Speaker 10: using it also for dating apps because there's so many 728 00:36:22,440 --> 00:36:25,480 Speaker 10: people putting out of fake profiles. So this is going 729 00:36:25,520 --> 00:36:27,880 Speaker 10: to kind of make sure that people are not lying 730 00:36:28,000 --> 00:36:31,759 Speaker 10: and setting up these profiles that you know, people want 731 00:36:31,760 --> 00:36:33,120 Speaker 10: to date and they want to make sure they're getting 732 00:36:33,120 --> 00:36:36,319 Speaker 10: a real person. So like match Group is piloting with 733 00:36:36,320 --> 00:36:38,880 Speaker 10: this company Tools for Humanity and starting to use it 734 00:36:38,920 --> 00:36:39,520 Speaker 10: for that too. 735 00:36:39,440 --> 00:36:42,719 Speaker 4: Age verification on Tinder in Japan, they're using it for 736 00:36:42,960 --> 00:36:46,160 Speaker 4: oh my god people. So honest, I know, I guess 737 00:36:46,160 --> 00:36:47,000 Speaker 4: on these apps. 738 00:36:47,040 --> 00:36:49,520 Speaker 5: I mean, you know, I'm twenty six, No you're not, 739 00:36:49,560 --> 00:36:51,719 Speaker 5: you're sixty college. 740 00:36:52,120 --> 00:36:52,960 Speaker 2: What's your major? 741 00:36:53,120 --> 00:36:54,680 Speaker 4: Yeah, that's exactly. 742 00:36:54,960 --> 00:36:57,480 Speaker 10: So it was okay, So we've heard a lot of 743 00:36:57,480 --> 00:36:59,759 Speaker 10: stories about, you know, the big money that CEOs make, 744 00:36:59,840 --> 00:37:01,600 Speaker 10: right media and CEO paying the s and P five 745 00:37:01,680 --> 00:37:04,080 Speaker 10: hundred hit a high of sixteen point four million last year. 746 00:37:04,480 --> 00:37:06,480 Speaker 10: But the Wall Street Journal is saying a lot of 747 00:37:06,520 --> 00:37:09,400 Speaker 10: these heads of the companies they'd rather just pass on 748 00:37:09,480 --> 00:37:12,360 Speaker 10: the position than deal with what's going on in the 749 00:37:12,400 --> 00:37:15,399 Speaker 10: climate today. So a new study said that last year, 750 00:37:15,480 --> 00:37:18,200 Speaker 10: three hundred and seventy three public company chiefs left and 751 00:37:18,239 --> 00:37:21,719 Speaker 10: that was twenty four percent more than twenty twenty three. 752 00:37:21,800 --> 00:37:24,120 Speaker 10: So you see the number. But you know, they thought, 753 00:37:24,120 --> 00:37:26,120 Speaker 10: they're saying, they thought that, you know, the worst was 754 00:37:26,160 --> 00:37:28,719 Speaker 10: over when the pandemic was gone, and okay, we're back 755 00:37:28,760 --> 00:37:31,520 Speaker 10: to normal, But then came AI. Then came tariffs, then 756 00:37:31,560 --> 00:37:35,240 Speaker 10: came the positivety recession, then came scrutiny of DEI efforts, 757 00:37:35,239 --> 00:37:37,880 Speaker 10: and they're all thrown into this tizzy. So the problem 758 00:37:37,920 --> 00:37:40,719 Speaker 10: is that they're saying is that the turnover affects not 759 00:37:40,760 --> 00:37:44,680 Speaker 10: only them but everybody around them because new bosses come 760 00:37:44,680 --> 00:37:50,040 Speaker 10: in and they bosses sorry Brooklyn Accent bosses coming reorganize them. 761 00:37:50,360 --> 00:37:52,600 Speaker 10: Even if a business is healthy, people get laid off. 762 00:37:52,640 --> 00:37:54,120 Speaker 10: So there's starting to see. 763 00:37:53,920 --> 00:37:54,960 Speaker 9: That trickle down effect. 764 00:37:55,000 --> 00:37:56,520 Speaker 10: And that's that's basically. 765 00:37:56,719 --> 00:37:58,800 Speaker 5: I think a lot of these CEOs that made so 766 00:37:58,920 --> 00:38:01,480 Speaker 5: much money on their style over the past five ten 767 00:38:01,600 --> 00:38:04,000 Speaker 5: years that they're like, I'm done, you know, and particularly 768 00:38:04,040 --> 00:38:06,120 Speaker 5: in a time the economic times, we have the uncertain 769 00:38:06,200 --> 00:38:07,680 Speaker 5: to hear, what's a managed through. 770 00:38:08,280 --> 00:38:09,319 Speaker 10: It'll deal with it. 771 00:38:09,440 --> 00:38:10,400 Speaker 4: They don't want to deal with it. 772 00:38:10,440 --> 00:38:12,160 Speaker 10: A lot of them are saying they're empty nesters. Some 773 00:38:12,280 --> 00:38:14,120 Speaker 10: are saying, you know what, I'd rather be a consultant 774 00:38:14,239 --> 00:38:15,799 Speaker 10: and just we've done with this. 775 00:38:16,719 --> 00:38:18,359 Speaker 4: So it's got to get up every morning, go on. 776 00:38:18,440 --> 00:38:19,440 Speaker 4: The landscape is changing. 777 00:38:19,600 --> 00:38:23,120 Speaker 2: Lisa Mateo with our tech newspapers this morning. Thank you 778 00:38:23,160 --> 00:38:25,080 Speaker 2: so much, greatly appreciate it. 779 00:38:25,239 --> 00:38:30,080 Speaker 1: This is the Bloomberg Surveillance podcast, available on Apple, Spotify, 780 00:38:30,200 --> 00:38:34,480 Speaker 1: and anywhere else you get your podcasts. Listen live each weekday, 781 00:38:34,600 --> 00:38:37,840 Speaker 1: seven to ten am Easter and on Bloomberg dot Com, 782 00:38:38,000 --> 00:38:41,800 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app. 783 00:38:42,080 --> 00:38:45,200 Speaker 1: You can also watch us live every weekday on YouTube 784 00:38:45,520 --> 00:38:47,520 Speaker 1: and always on the Bloomberg terminal