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 --> 00:00:21,240 Speaker 1: on Apple car Play or Android Auto with the Bloomberg 4 00:00:21,320 --> 00:00:24,880 Speaker 1: Business App. Listen on demand wherever you get your podcasts, 5 00:00:25,280 --> 00:00:26,840 Speaker 1: or watch us live on YouTube. 6 00:00:26,960 --> 00:00:30,360 Speaker 2: Let's dive a little bit deeper into the Nvidia earnings. 7 00:00:30,520 --> 00:00:33,400 Speaker 2: Who do you want to dive deeper in than d. 8 00:00:33,920 --> 00:00:34,879 Speaker 3: No better person right now? 9 00:00:34,920 --> 00:00:36,800 Speaker 2: That's our guy. I mean, he's getting geared up for 10 00:00:36,880 --> 00:00:40,199 Speaker 2: Penn State, Nevada this weekend, but he's probably focusing a 11 00:00:40,240 --> 00:00:42,559 Speaker 2: little bit here on Nvidia. Hey, Dan, I thought these 12 00:00:42,680 --> 00:00:46,159 Speaker 2: numbers were darn good, but I know there's the law 13 00:00:46,200 --> 00:00:49,159 Speaker 2: of large numbers. I know there's a whole thing about expectations. 14 00:00:50,120 --> 00:00:54,120 Speaker 2: Give us your take on these Nvidia numbers, Dan, I. 15 00:00:54,200 --> 00:00:57,080 Speaker 4: Thought they were robot and I think the some extent 16 00:00:57,120 --> 00:01:01,760 Speaker 4: when you factored China and they actually beat expectations, especially 17 00:01:01,760 --> 00:01:03,880 Speaker 4: when you look at the outlook. I think there's a 18 00:01:03,880 --> 00:01:07,959 Speaker 4: stock that's up today and I think it further validates Well. 19 00:01:07,959 --> 00:01:09,959 Speaker 4: We've obviously been talking a lot, you know, with you 20 00:01:10,040 --> 00:01:13,440 Speaker 4: and the team about about the AI story now playing 21 00:01:13,440 --> 00:01:17,920 Speaker 4: out into the next stiege of growth. This is bullish 22 00:01:17,920 --> 00:01:19,119 Speaker 4: in my opinion. 23 00:01:19,959 --> 00:01:22,760 Speaker 5: Dan, what was your takeaway here as it relates to 24 00:01:23,480 --> 00:01:25,399 Speaker 5: a lot of the spending here Capax. 25 00:01:27,440 --> 00:01:29,800 Speaker 4: I think it just sures there's one ship in the world, 26 00:01:29,840 --> 00:01:33,040 Speaker 4: fewling the AI revolutions led by godfather of AI, Jensen, 27 00:01:33,080 --> 00:01:36,120 Speaker 4: the Vidning and you what's happened on Capex. It's just 28 00:01:36,200 --> 00:01:40,120 Speaker 4: continuing to accelerate, and then you factor in China that 29 00:01:40,160 --> 00:01:43,199 Speaker 4: could be fifty billion. I mean in just talking about 30 00:01:43,200 --> 00:01:46,680 Speaker 4: the fifty percent growth. I look, I think this is 31 00:01:47,000 --> 00:01:50,960 Speaker 4: just now it's showing the next feeds of the AI 32 00:01:51,040 --> 00:01:54,040 Speaker 4: revolutions now starting to play out, especially when you combine 33 00:01:54,080 --> 00:01:57,920 Speaker 4: it with hyper scalers and everything we've seen from Pallenteer 34 00:01:58,400 --> 00:02:02,280 Speaker 4: now Snowflake, Mango de Be, the use cases are expanded. 35 00:02:03,440 --> 00:02:07,320 Speaker 2: Dan, flush out for us the whole China situation. Where 36 00:02:07,400 --> 00:02:10,560 Speaker 2: is in Vidio today visa via China? And how do 37 00:02:10,560 --> 00:02:11,920 Speaker 2: you think this is going to play out over the 38 00:02:11,960 --> 00:02:13,800 Speaker 2: coming quarters with our age twenty. 39 00:02:13,720 --> 00:02:19,400 Speaker 4: Chip Yeah, Paul, Look, they're they're cognmental between US and China. 40 00:02:19,440 --> 00:02:22,720 Speaker 4: But the reality is Jensen's ten percent politician, ninety percent 41 00:02:22,880 --> 00:02:26,400 Speaker 4: CEO and Trump administration to do is big as Chip 42 00:02:26,440 --> 00:02:29,280 Speaker 4: on the broker table is in the video. So as 43 00:02:29,320 --> 00:02:32,239 Speaker 4: this all plays out there, it's to pay for play model. 44 00:02:32,280 --> 00:02:35,160 Speaker 4: They're going to have access to China, even if it's restricted, 45 00:02:35,600 --> 00:02:38,120 Speaker 4: and that's going to add and incremental what two five 46 00:02:38,400 --> 00:02:43,080 Speaker 4: six billion per quarter. And you know, even though Beijing's 47 00:02:43,120 --> 00:02:45,960 Speaker 4: saying telling you know, maybe these companies you don't want 48 00:02:46,000 --> 00:02:48,400 Speaker 4: to buy in video chips, that's like telling a kid 49 00:02:48,560 --> 00:02:54,079 Speaker 4: not eat candied. Big tech in China wants in video chips. 50 00:02:55,080 --> 00:02:57,560 Speaker 5: So, I mean, as we dig in here into the data, 51 00:02:57,600 --> 00:03:00,680 Speaker 5: what we saw from the earnings report, what is takeaway 52 00:03:00,680 --> 00:03:03,679 Speaker 5: in terms of what they were able to see specifically 53 00:03:03,680 --> 00:03:06,600 Speaker 5: in terms of data center AI demand. That's definitely something 54 00:03:06,600 --> 00:03:08,239 Speaker 5: that's been in focus here with this report. 55 00:03:09,840 --> 00:03:12,200 Speaker 4: Yeah, look, I think it's noise in terms of any 56 00:03:12,520 --> 00:03:15,919 Speaker 4: quote unquote like miss because when you factored China, it's 57 00:03:15,960 --> 00:03:19,919 Speaker 4: basically over a billion and a half feet. They're seeing 58 00:03:20,040 --> 00:03:24,200 Speaker 4: demand accelerate. I mean, no region is not showing acceleration. 59 00:03:24,919 --> 00:03:26,960 Speaker 4: And now you're starting to factor what's going to happen 60 00:03:26,919 --> 00:03:29,560 Speaker 4: in Middle East, what's going to happen in China. It's 61 00:03:29,560 --> 00:03:32,760 Speaker 4: got to rest the world and you're really talking about 62 00:03:32,840 --> 00:03:35,480 Speaker 4: one chip that's fueling it. So when I walk in 63 00:03:35,480 --> 00:03:37,720 Speaker 4: a video, I think there's a five trillion dollars mark 64 00:03:37,800 --> 00:03:40,800 Speaker 4: cap attention by a year under early twenty six, and 65 00:03:40,800 --> 00:03:44,600 Speaker 4: it's just further validation for the AI revolution. Biasis. 66 00:03:46,280 --> 00:03:48,680 Speaker 2: So talk to us DAN about their customer base and 67 00:03:48,720 --> 00:03:51,040 Speaker 2: the concentration of the customers, and I know they want 68 00:03:51,040 --> 00:03:53,920 Speaker 2: to broaden out their customer base maybe to sovereigns into 69 00:03:53,960 --> 00:03:57,720 Speaker 2: other net buyers out there. How do you think that's 70 00:03:57,720 --> 00:03:58,320 Speaker 2: going to evolve? 71 00:04:00,080 --> 00:04:02,280 Speaker 4: Big tech is going to continue domino as a quote 72 00:04:02,320 --> 00:04:06,080 Speaker 4: unquote customer base in terms of the concentration. But now 73 00:04:06,120 --> 00:04:09,520 Speaker 4: as sovereigns play out, as enterprises play out, and you're 74 00:04:09,520 --> 00:04:12,960 Speaker 4: going to see more and more people you know, obviously 75 00:04:13,000 --> 00:04:17,320 Speaker 4: start to understand that this revolution is not just big Tech. 76 00:04:18,040 --> 00:04:20,599 Speaker 4: It's about other sort of regions starting to play. And 77 00:04:20,600 --> 00:04:22,719 Speaker 4: there's only one ship in the world fuel in it, 78 00:04:23,200 --> 00:04:24,040 Speaker 4: and that's in video. 79 00:04:25,520 --> 00:04:28,159 Speaker 5: So taking a step back here in video wrapped up 80 00:04:28,360 --> 00:04:30,920 Speaker 5: all of the mag seven earnings here. What were your 81 00:04:30,960 --> 00:04:33,960 Speaker 5: thoughts more broadly overall this earning season. 82 00:04:36,000 --> 00:04:39,000 Speaker 4: I mean, I think this is the bullish Tech earning season. 83 00:04:39,080 --> 00:04:42,440 Speaker 4: We talked about it, the validation of the AI revolution, 84 00:04:42,680 --> 00:04:46,920 Speaker 4: his next stage of growth it's spreading, second, third, fourth derivatives. 85 00:04:47,080 --> 00:04:49,560 Speaker 4: Now grant look in video is a Scottie chauffeur of 86 00:04:49,680 --> 00:04:52,280 Speaker 4: tech okay, But what you're just starting to see now 87 00:04:52,400 --> 00:04:57,360 Speaker 4: play out is those derivatives, the spending, the multiplier, it's 88 00:04:57,360 --> 00:05:00,839 Speaker 4: all happening. And I think that's just bullish going into 89 00:05:00,920 --> 00:05:03,479 Speaker 4: year end in terms of tax stocks, and I think 90 00:05:03,480 --> 00:05:08,960 Speaker 4: this bull market has two to three year run still left. Dan. 91 00:05:09,080 --> 00:05:12,040 Speaker 2: So as you talk to institutional investors, how are they 92 00:05:12,120 --> 00:05:17,040 Speaker 2: viewing this fifteen percent? I don't know government fee that 93 00:05:17,360 --> 00:05:19,440 Speaker 2: the US government may impose on some of these chip 94 00:05:19,480 --> 00:05:23,800 Speaker 2: sales that China. How's that being viewed by investors? 95 00:05:23,839 --> 00:05:28,800 Speaker 4: Look, it's obviously it's unusual. It's a pay for play model, 96 00:05:28,920 --> 00:05:31,600 Speaker 4: but guess what, investors, it's new rules of the road, right, 97 00:05:31,880 --> 00:05:35,040 Speaker 4: big text, start and understand how that works. But when 98 00:05:35,080 --> 00:05:39,200 Speaker 4: it comes in video, okay, pay fifteen percent, that's breadcrumbs. 99 00:05:39,240 --> 00:05:42,360 Speaker 4: You can raise prices fifteen percent. You need access to China. 100 00:05:42,720 --> 00:05:45,840 Speaker 4: You can't give Huawei on a silver platter that market. 101 00:05:46,200 --> 00:05:48,640 Speaker 4: So as it continues to play out, I think investors 102 00:05:48,640 --> 00:05:52,040 Speaker 4: have accepted they want to video open access to China 103 00:05:52,120 --> 00:05:55,640 Speaker 4: because that continues to be the golden goose that Jensen's 104 00:05:55,680 --> 00:05:56,560 Speaker 4: going after. 105 00:05:58,000 --> 00:05:58,160 Speaker 2: Dan. 106 00:05:58,240 --> 00:06:00,200 Speaker 5: I want to quickly go right back to what we 107 00:06:00,200 --> 00:06:02,799 Speaker 5: were talking about here when it relates to data centers. 108 00:06:02,839 --> 00:06:05,919 Speaker 5: How concentrated is in Video's revenue right now or like 109 00:06:05,960 --> 00:06:08,720 Speaker 5: you know, the top five hyper scalers still the overwhelming 110 00:06:08,760 --> 00:06:10,239 Speaker 5: majority of data center sales. 111 00:06:11,560 --> 00:06:14,560 Speaker 4: You know, it's concentrated. But that's just the nature right 112 00:06:14,600 --> 00:06:18,120 Speaker 4: now big text three hundred, what fifty during sixty billion? 113 00:06:18,680 --> 00:06:22,080 Speaker 4: But it's going to spread sovereigns enterprises the rest of 114 00:06:22,120 --> 00:06:24,240 Speaker 4: the world, and Vidia is going to continue to own 115 00:06:24,320 --> 00:06:27,440 Speaker 4: that so contrade today when you look out three four, 116 00:06:27,560 --> 00:06:31,320 Speaker 4: five years ago, that concentration will continue, I think to 117 00:06:31,400 --> 00:06:36,960 Speaker 4: diminish as more players get into AI. But there's one 118 00:06:37,040 --> 00:06:38,560 Speaker 4: chip fuel in it. It's in video. 119 00:06:39,560 --> 00:06:42,400 Speaker 2: Dam How do you think about the competitive environment for 120 00:06:42,760 --> 00:06:43,240 Speaker 2: in Nvidia? 121 00:06:43,360 --> 00:06:43,600 Speaker 4: Here? 122 00:06:44,080 --> 00:06:46,839 Speaker 2: Is it AMD? Is it Huawei? Is it others? We 123 00:06:46,880 --> 00:06:48,440 Speaker 2: don't know about at the moment. 124 00:06:48,920 --> 00:06:52,880 Speaker 4: Here, well, glease issue in AMD clearly competition. I think 125 00:06:52,960 --> 00:06:55,559 Speaker 4: that we continue to be bullsh in that in terms 126 00:06:55,560 --> 00:06:59,200 Speaker 4: of getting more and more pieces of pie. Huawei is 127 00:06:59,240 --> 00:07:01,640 Speaker 4: a competitor, but that's the whole reason that you don't 128 00:07:01,640 --> 00:07:04,000 Speaker 4: want to just give them full access to China because 129 00:07:04,000 --> 00:07:07,080 Speaker 4: that will help them narrow the gap for bulls obviously 130 00:07:07,080 --> 00:07:09,960 Speaker 4: on Broad common others. And I think, look as this 131 00:07:10,120 --> 00:07:12,720 Speaker 4: plays out, in Vidia is years ahead of any of 132 00:07:12,800 --> 00:07:15,440 Speaker 4: their competition. And even when you hear talked about you know, 133 00:07:15,640 --> 00:07:19,480 Speaker 4: US government and obviously you know SoftBank investing in Intel. 134 00:07:19,840 --> 00:07:23,920 Speaker 4: I mean, Intel is you know, so many years behind. 135 00:07:24,920 --> 00:07:27,280 Speaker 4: You know, they continue to really have just a massive 136 00:07:27,360 --> 00:07:29,680 Speaker 4: uptil battle. And that's why video is top of the mountain. 137 00:07:30,320 --> 00:07:32,520 Speaker 2: All right, Dan, your Penn State Nitley Ions open the 138 00:07:32,520 --> 00:07:36,720 Speaker 2: season Saturday, three thirty pm on the CBS Television network, 139 00:07:36,720 --> 00:07:40,760 Speaker 2: Compariment plus against Nevada forty three and a half point favorites. 140 00:07:40,760 --> 00:07:42,440 Speaker 2: How do you feel about you Nitley Lions this year? 141 00:07:43,120 --> 00:07:45,960 Speaker 4: I mean, look, I was at practice last week State College. 142 00:07:46,120 --> 00:07:47,960 Speaker 4: I told you, I think this is the year. I 143 00:07:47,960 --> 00:07:50,520 Speaker 4: think we win the nanty. We have some tough games 144 00:07:50,560 --> 00:07:53,960 Speaker 4: of Oregon Ohio State, but I think Big ten continues 145 00:07:54,000 --> 00:07:56,680 Speaker 4: to hold the mantle. I like al our Singleton and 146 00:07:56,720 --> 00:07:58,640 Speaker 4: Penn State. I think I think we'll be holding the 147 00:07:58,680 --> 00:08:00,000 Speaker 4: trophy in January. 148 00:08:00,360 --> 00:08:03,280 Speaker 2: I like the call LEAs and clear and confident. Dan 149 00:08:03,360 --> 00:08:06,720 Speaker 2: ives Global ahead of technology Webush Securities appreciate getting a 150 00:08:06,760 --> 00:08:10,000 Speaker 2: few minutes of Dan's time here today on Nvidia and 151 00:08:10,040 --> 00:08:12,800 Speaker 2: big tech. Stay with us. More from Bloomberg Surveillance coming 152 00:08:12,880 --> 00:08:13,760 Speaker 2: up after this. 153 00:08:19,840 --> 00:08:23,400 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us Live 154 00:08:23,480 --> 00:08:26,640 Speaker 1: weekday afternoons from seven to ten am Eastern Listen on 155 00:08:26,720 --> 00:08:30,400 Speaker 1: Applecarplay and Android Auto with the Bloomberg Business app, or 156 00:08:30,560 --> 00:08:31,920 Speaker 1: watch us live on YouTube. 157 00:08:31,960 --> 00:08:35,640 Speaker 2: Anastasia Amoroso joints as chief investment strategist at Private Wealth 158 00:08:35,679 --> 00:08:40,360 Speaker 2: at Firms Partners Group. Anastasia, the market's been so fixated 159 00:08:40,400 --> 00:08:43,839 Speaker 2: on AI and then I guess Nvidia is probably the 160 00:08:43,840 --> 00:08:47,280 Speaker 2: poster child for AI. How do you think about that 161 00:08:47,360 --> 00:08:49,720 Speaker 2: as a theme for the market. How important is that 162 00:08:50,000 --> 00:08:52,280 Speaker 2: to you? The NVIDIAs of the world in this AI? 163 00:08:52,400 --> 00:08:55,280 Speaker 6: Sure well, obviously very important, and Paul, I'm with you. 164 00:08:55,320 --> 00:08:57,880 Speaker 6: I thought the Nvidia numbers were just fine. It's really 165 00:08:57,880 --> 00:09:02,160 Speaker 6: interesting that on the surface, investors were disappointed because in Vidia, 166 00:09:02,400 --> 00:09:04,760 Speaker 6: despite the fact that they beat and raised, they didn't 167 00:09:04,760 --> 00:09:07,960 Speaker 6: meet the loftiest of expectations. Of course, that probably makes 168 00:09:08,000 --> 00:09:09,760 Speaker 6: sense because the stock has rallied as. 169 00:09:09,720 --> 00:09:11,840 Speaker 3: Much as it has, I think over one hundred percent. 170 00:09:11,760 --> 00:09:14,080 Speaker 6: Since since the bottom in April, so I thought the 171 00:09:14,120 --> 00:09:18,800 Speaker 6: numbers were fine, and the AI theme is obviously hugely important, 172 00:09:18,880 --> 00:09:21,160 Speaker 6: and I think in Vidia highlights that it's still top 173 00:09:21,200 --> 00:09:23,239 Speaker 6: of mind in front and center for investors. 174 00:09:23,600 --> 00:09:25,480 Speaker 3: And I say that because, you know. 175 00:09:25,600 --> 00:09:28,400 Speaker 6: Analysts focus on the growth rates that are tapering off, 176 00:09:28,440 --> 00:09:29,720 Speaker 6: but consider the base. 177 00:09:30,120 --> 00:09:31,240 Speaker 3: You know, consider the. 178 00:09:31,240 --> 00:09:35,440 Speaker 6: Fact that AI hyperscalers are going to spend four hundred 179 00:09:35,480 --> 00:09:39,240 Speaker 6: billion dollars in AI cap x in twenty twenty six. 180 00:09:39,480 --> 00:09:41,920 Speaker 6: This would be a number that was unthinkable about just 181 00:09:41,920 --> 00:09:45,240 Speaker 6: a couple of years ago. So we're at a significantly 182 00:09:45,360 --> 00:09:48,280 Speaker 6: higher scale. But what happens at that point? It's natural 183 00:09:48,320 --> 00:09:51,320 Speaker 6: that some of those growth rates taper off, But for us, Paul, 184 00:09:51,480 --> 00:09:55,160 Speaker 6: it's still AI is such an important theme, and I 185 00:09:55,160 --> 00:09:58,480 Speaker 6: think in Vidia results also highlight that there's so many 186 00:09:58,520 --> 00:10:02,679 Speaker 6: other ways to access that, including in private markets, including 187 00:10:02,679 --> 00:10:03,560 Speaker 6: in infrastructure. 188 00:10:03,640 --> 00:10:05,080 Speaker 3: So that's what we're really focused on. 189 00:10:05,440 --> 00:10:07,280 Speaker 5: I mean, when we look at any sort of earnings 190 00:10:07,280 --> 00:10:10,000 Speaker 5: report from Nvidia, there's a lot of anticipation heading up 191 00:10:10,040 --> 00:10:11,320 Speaker 5: to it, and we do see a lot of these 192 00:10:11,400 --> 00:10:15,040 Speaker 5: lofty expectations. As you noted, is there any concern that maybe, 193 00:10:15,080 --> 00:10:18,400 Speaker 5: you know, expectations are too high for some of these companies. 194 00:10:19,120 --> 00:10:21,640 Speaker 3: I mean, they've certainly been ratcheted up. But I will 195 00:10:21,679 --> 00:10:22,200 Speaker 3: say that if. 196 00:10:22,120 --> 00:10:24,400 Speaker 6: You look at the history of Nvidia, for example, it 197 00:10:24,520 --> 00:10:27,760 Speaker 6: has a history of delivering on those expectations, and maybe 198 00:10:27,760 --> 00:10:30,760 Speaker 6: on the exact earnings day, they don't always deliver on 199 00:10:30,800 --> 00:10:33,679 Speaker 6: the loftiest of expectations. But what you see over time 200 00:10:33,800 --> 00:10:37,360 Speaker 6: is the price continued to march higher because the expectations 201 00:10:37,360 --> 00:10:40,600 Speaker 6: have continued to march higher. So I think that's something 202 00:10:40,640 --> 00:10:43,760 Speaker 6: that supported the stock and probably will continue. And look, 203 00:10:43,840 --> 00:10:47,000 Speaker 6: you know, broadly speaking, if I think about is AI 204 00:10:47,280 --> 00:10:51,240 Speaker 6: meeting expectations, I think it is for what it is today. 205 00:10:51,600 --> 00:10:54,199 Speaker 6: We are starting to see some early signs of monetization, 206 00:10:54,480 --> 00:10:56,280 Speaker 6: and you can think about it in terms of a 207 00:10:56,320 --> 00:10:57,359 Speaker 6: couple of pockets. 208 00:10:57,520 --> 00:10:58,360 Speaker 3: You can think about it. 209 00:10:58,360 --> 00:11:02,080 Speaker 6: In terms of cost reduction, in terms of productivity improvements, 210 00:11:02,160 --> 00:11:05,400 Speaker 6: and also in terms of actual new revenue streams. And 211 00:11:05,480 --> 00:11:07,800 Speaker 6: I think the actual new revenue streams maybe are a 212 00:11:07,840 --> 00:11:10,520 Speaker 6: little bit further off for some companies. Although I think 213 00:11:10,559 --> 00:11:12,720 Speaker 6: we are starting to see more cloud, we're starting to 214 00:11:12,760 --> 00:11:17,240 Speaker 6: see utilization, We're starting to see more social media success, for. 215 00:11:17,120 --> 00:11:18,760 Speaker 3: Example with our targeted ads. 216 00:11:18,960 --> 00:11:21,480 Speaker 6: So I think you start to you do have some 217 00:11:21,720 --> 00:11:24,800 Speaker 6: positives in that revenue generation pocket, but you have more 218 00:11:24,800 --> 00:11:27,600 Speaker 6: and more positives that companies are citing in terms of 219 00:11:27,960 --> 00:11:30,800 Speaker 6: efficiency gains and in terms of cost reductions. 220 00:11:31,040 --> 00:11:32,120 Speaker 3: And so that's. 221 00:11:31,880 --> 00:11:35,679 Speaker 6: Why the momentum for US for AI is likely to continue, 222 00:11:36,000 --> 00:11:39,040 Speaker 6: because there are tangible benefits that more and more companies 223 00:11:39,080 --> 00:11:39,600 Speaker 6: can point to. 224 00:11:40,440 --> 00:11:44,280 Speaker 2: So what are the ways are you suggesting that investors 225 00:11:44,280 --> 00:11:46,760 Speaker 2: get exposure to AI? A lot of folks saying maybe 226 00:11:46,800 --> 00:11:49,080 Speaker 2: like power generation or something like that. How do you 227 00:11:49,120 --> 00:11:51,600 Speaker 2: think about that? Because not everybody is comfortable paying some 228 00:11:51,600 --> 00:11:54,480 Speaker 2: of these technology multiples, and maybe a lot of folks 229 00:11:54,520 --> 00:11:56,840 Speaker 2: think that some of these tech names, like the software 230 00:11:56,880 --> 00:12:00,760 Speaker 2: names or maybe the hyperscalars, have kind of outrun comfort level, 231 00:12:00,800 --> 00:12:02,160 Speaker 2: so they're looking for other ways. 232 00:12:02,080 --> 00:12:04,160 Speaker 6: Right, Well, I think the first thing investors have to 233 00:12:04,160 --> 00:12:06,520 Speaker 6: do is take a giant step back and just size 234 00:12:06,600 --> 00:12:09,160 Speaker 6: the opportunity set. Right, a couple of years ago, the 235 00:12:09,320 --> 00:12:13,280 Speaker 6: GENAI total addressable market was somewhere around two hundred billion dollars. 236 00:12:13,520 --> 00:12:16,920 Speaker 6: You fast forward to twenty twenty seven, twenty thirty, you're 237 00:12:16,920 --> 00:12:21,359 Speaker 6: now looking close to a trillion dollar TAM for artificial intelligence. 238 00:12:21,600 --> 00:12:24,840 Speaker 6: So that means that it's not just nvidiaan semiconductors. But 239 00:12:24,880 --> 00:12:28,080 Speaker 6: it's a whole host of beneficiaries, and I would put 240 00:12:28,120 --> 00:12:31,319 Speaker 6: them in two sorts of opportunities bucket. The first one, 241 00:12:31,320 --> 00:12:33,760 Speaker 6: I would say, is an infrastructure. We have to build 242 00:12:33,840 --> 00:12:36,560 Speaker 6: up the infrastructure to ensure that AI is possible. 243 00:12:36,800 --> 00:12:37,600 Speaker 3: So what does that mean. 244 00:12:37,720 --> 00:12:40,960 Speaker 6: That certainly means data centers, and not just any data center, 245 00:12:41,000 --> 00:12:43,760 Speaker 6: but an AI specific data center, which. 246 00:12:43,559 --> 00:12:45,840 Speaker 3: Requires more power density. 247 00:12:45,440 --> 00:12:48,400 Speaker 6: Which requires greater connectivity, which requires more cooling. 248 00:12:48,679 --> 00:12:50,640 Speaker 3: So that's a big topic for us. 249 00:12:50,880 --> 00:12:54,200 Speaker 6: The second one, as you mentioned, it's actually power generation. 250 00:12:54,400 --> 00:12:57,560 Speaker 6: You can't really run that data center without the power. 251 00:12:57,920 --> 00:12:59,719 Speaker 3: And if you think about the power. 252 00:12:59,480 --> 00:13:02,199 Speaker 6: Consumption, and it's for some of these things, it's approaching 253 00:13:02,360 --> 00:13:05,720 Speaker 6: one gigawot, you know. That's what we're talking about here. 254 00:13:06,200 --> 00:13:09,560 Speaker 6: The third component, which is not as well talked about, 255 00:13:09,600 --> 00:13:12,320 Speaker 6: I would say, is actually fiber and all sorts of 256 00:13:12,320 --> 00:13:15,760 Speaker 6: wireless connectivity. You know, it's one thing to train AI 257 00:13:15,920 --> 00:13:17,599 Speaker 6: in a data center, let's say, in the middle of 258 00:13:17,679 --> 00:13:20,320 Speaker 6: the country without a proximity to the end user. But 259 00:13:20,400 --> 00:13:22,320 Speaker 6: it's a whole different thing if you start to do 260 00:13:22,679 --> 00:13:26,880 Speaker 6: inference and you need that instant feedback loop and reaction, 261 00:13:27,040 --> 00:13:31,080 Speaker 6: so you need fiber. You need you know, dense network, 262 00:13:31,120 --> 00:13:33,679 Speaker 6: you need towers, you need small cells. So there's so 263 00:13:33,800 --> 00:13:37,400 Speaker 6: many opportunities within infrastructure. And then Paul the other thing, 264 00:13:37,440 --> 00:13:40,760 Speaker 6: I would say in software, there's going to be winners 265 00:13:40,760 --> 00:13:44,640 Speaker 6: and losers in software. But companies that we're emphasizing are 266 00:13:44,679 --> 00:13:47,560 Speaker 6: those that maybe have a proprietary data set. 267 00:13:47,640 --> 00:13:48,920 Speaker 3: I think that's really important. 268 00:13:49,440 --> 00:13:53,280 Speaker 6: They are developing AI tools, like large language models that 269 00:13:53,360 --> 00:13:56,640 Speaker 6: are able to use some of that proprietary data. They 270 00:13:56,720 --> 00:14:00,960 Speaker 6: automate certain workflows and in some cases completely sort of 271 00:14:00,960 --> 00:14:04,440 Speaker 6: substitute what a human may do in that situation. So 272 00:14:05,200 --> 00:14:08,800 Speaker 6: you know, it's definitely a careful selection approach. But I 273 00:14:08,840 --> 00:14:12,520 Speaker 6: would say so many of those companies AI software companies 274 00:14:12,559 --> 00:14:16,120 Speaker 6: are actually available in private markets, much more so than 275 00:14:16,160 --> 00:14:17,480 Speaker 6: what's publicly traded today. 276 00:14:18,240 --> 00:14:21,320 Speaker 5: So you know, we heard that Nvidia expects to spend 277 00:14:21,400 --> 00:14:25,480 Speaker 5: three to four trillion dollars on AI infrastructure through between 278 00:14:25,480 --> 00:14:28,480 Speaker 5: now and the end of the decade. Here, do you 279 00:14:28,520 --> 00:14:31,920 Speaker 5: have any sort of thoughts about what CAPEX looks like 280 00:14:32,000 --> 00:14:34,280 Speaker 5: right now, what is spending right now in the space 281 00:14:34,640 --> 00:14:37,880 Speaker 5: technology more broadly when it pertains to AI spend. 282 00:14:38,120 --> 00:14:40,480 Speaker 6: Yeah, well, let's look at the hyperscalers for example, you know, 283 00:14:40,520 --> 00:14:42,800 Speaker 6: I mentioned that in twenty twenty six they're likely to 284 00:14:42,840 --> 00:14:45,960 Speaker 6: spend four hundred billion dollars. That's up from three hundred 285 00:14:46,000 --> 00:14:49,560 Speaker 6: and fifty billion that we're forecasting for twenty twenty five. 286 00:14:49,640 --> 00:14:51,080 Speaker 3: And that's up a lot. 287 00:14:50,800 --> 00:14:53,240 Speaker 6: From you know, one hundred billion dollars so run rate 288 00:14:53,560 --> 00:14:56,520 Speaker 6: just a couple of years ago. Now, the interesting thing 289 00:14:56,560 --> 00:15:00,520 Speaker 6: about that is those estimates have been consistently moved higher, 290 00:15:00,800 --> 00:15:03,040 Speaker 6: and that I think goes back to the point is 291 00:15:03,080 --> 00:15:06,160 Speaker 6: a demand for AI at this point is really insatiable, 292 00:15:06,440 --> 00:15:09,840 Speaker 6: and it's because we're starting to see those early signs 293 00:15:09,880 --> 00:15:13,000 Speaker 6: of payoff. And so you know, if the question is 294 00:15:13,000 --> 00:15:15,480 Speaker 6: do we have a concern about the sort of massive 295 00:15:15,880 --> 00:15:20,200 Speaker 6: spend on AI, I wouldn't say so because the demand 296 00:15:20,360 --> 00:15:21,640 Speaker 6: is just so robust. 297 00:15:21,840 --> 00:15:23,480 Speaker 2: All right, let's back away from the air. I talked 298 00:15:23,480 --> 00:15:25,600 Speaker 2: a little bit last week to talk was about the 299 00:15:25,600 --> 00:15:27,400 Speaker 2: Federal Reserve and what are they going to do with 300 00:15:27,480 --> 00:15:29,560 Speaker 2: interest rates? What did you take away from Jackson Hole 301 00:15:30,120 --> 00:15:31,800 Speaker 2: and moving forward here through major. 302 00:15:31,880 --> 00:15:35,760 Speaker 6: Right, Well, it was probably a strong Evan nod to September, 303 00:15:35,960 --> 00:15:39,160 Speaker 6: as we could have expected from Fetchair Powell. And you 304 00:15:39,160 --> 00:15:41,680 Speaker 6: know what's interesting is he clearly pivoted to focus on 305 00:15:41,720 --> 00:15:44,440 Speaker 6: the labor market weakness, and we saw that once again 306 00:15:44,480 --> 00:15:46,840 Speaker 6: in the conference board. For example, we saw that the 307 00:15:46,920 --> 00:15:50,640 Speaker 6: labor market differential meaning the jobs that are plentiful versus 308 00:15:50,680 --> 00:15:53,880 Speaker 6: hard to get, that continues to narrow. So that suggests 309 00:15:53,920 --> 00:15:57,480 Speaker 6: that labor market weakness. The other thought that I thought 310 00:15:57,600 --> 00:16:01,880 Speaker 6: was interesting from Jackson Hole is that while inflation is 311 00:16:01,960 --> 00:16:05,760 Speaker 6: surely likely to spike in the coming months, they're willing 312 00:16:05,800 --> 00:16:08,440 Speaker 6: to look through that. And part of the reason for 313 00:16:08,520 --> 00:16:10,720 Speaker 6: that is because they don't expect it to be sticky. 314 00:16:11,000 --> 00:16:13,000 Speaker 6: They don't think this is going to be systemic, they 315 00:16:13,000 --> 00:16:15,480 Speaker 6: don't think is going to be structural. The reason for 316 00:16:15,520 --> 00:16:19,240 Speaker 6: that is actually that weakening labor market. And you know, 317 00:16:19,400 --> 00:16:22,760 Speaker 6: if you're trying to raise prices into a weakening consumer 318 00:16:23,240 --> 00:16:25,680 Speaker 6: or into a weaker jobs market, you're likely not going 319 00:16:25,720 --> 00:16:28,520 Speaker 6: to be successful. And so that's becoming part of the 320 00:16:28,520 --> 00:16:31,640 Speaker 6: FED narrative as well. So I think it is a 321 00:16:31,760 --> 00:16:35,440 Speaker 6: layout for September. I mean, barring just a huge upside 322 00:16:35,480 --> 00:16:38,600 Speaker 6: surprise on payrolls, which I don't expect, or you know, 323 00:16:38,680 --> 00:16:41,400 Speaker 6: barring I would say not only a spike in inflation, 324 00:16:41,480 --> 00:16:42,760 Speaker 6: but a spike in inflation. 325 00:16:42,480 --> 00:16:45,280 Speaker 5: Expectations, and I don't think we're seeing that. Do you 326 00:16:45,280 --> 00:16:48,080 Speaker 5: agree with that view from the Fed right now? I mean, 327 00:16:48,200 --> 00:16:50,560 Speaker 5: of course we know about this dual mandate. It's about 328 00:16:50,600 --> 00:16:55,120 Speaker 5: stabilizing prices, bringing down inflation, and of course maximum unemployment 329 00:16:55,400 --> 00:16:56,640 Speaker 5: or maximum employment excuse. 330 00:16:56,440 --> 00:16:58,280 Speaker 3: Me, Yeah, I do actually very much agree. 331 00:16:58,360 --> 00:17:01,880 Speaker 6: You know, I do think the FLA story, the teriff 332 00:17:01,880 --> 00:17:05,359 Speaker 6: for re lated induced inflation is a one time step 333 00:17:05,440 --> 00:17:07,840 Speaker 6: up higher in the price levels, and I very much 334 00:17:07,880 --> 00:17:10,679 Speaker 6: agree with the argument that you don't have the labor 335 00:17:10,800 --> 00:17:13,200 Speaker 6: market strength in order to be able to fully pass 336 00:17:13,240 --> 00:17:14,359 Speaker 6: through those increases. 337 00:17:14,560 --> 00:17:14,760 Speaker 2: You know. 338 00:17:14,840 --> 00:17:17,359 Speaker 6: The other thing I would say, if you look at companies, 339 00:17:17,400 --> 00:17:20,720 Speaker 6: including our portfolio companies, they're using a mix of tactics 340 00:17:20,760 --> 00:17:23,040 Speaker 6: in order to deal with tariffs. Some of them are 341 00:17:23,080 --> 00:17:25,399 Speaker 6: passing through all of the cost increases, for example in 342 00:17:25,440 --> 00:17:28,520 Speaker 6: the data center space, because they can. Some of them 343 00:17:28,560 --> 00:17:32,760 Speaker 6: are passing through partial cost increases. They're working with suppliers 344 00:17:33,080 --> 00:17:36,679 Speaker 6: to absorb some of those TERRAF related increases as well, 345 00:17:36,920 --> 00:17:38,760 Speaker 6: and some of them are shifting supply chains. 346 00:17:38,880 --> 00:17:40,160 Speaker 3: So for that reason, I. 347 00:17:40,040 --> 00:17:42,680 Speaker 6: Don't think we're seeing a huge we're going to see 348 00:17:42,720 --> 00:17:46,000 Speaker 6: a huge spike in inflation as it could have been 349 00:17:46,200 --> 00:17:47,040 Speaker 6: in the coming months. 350 00:17:47,160 --> 00:17:48,840 Speaker 3: So that's the first part that I agree with. 351 00:17:49,040 --> 00:17:51,600 Speaker 6: The second part I agree with is the labor market 352 00:17:51,680 --> 00:17:52,840 Speaker 6: is clearly. 353 00:17:52,480 --> 00:17:54,480 Speaker 3: Weakening, and I would say it's sort of I don't 354 00:17:54,480 --> 00:17:56,360 Speaker 3: want to say the precipice, but I'll call it. It's 355 00:17:56,359 --> 00:17:57,320 Speaker 3: sort of on edge. 356 00:17:57,359 --> 00:17:59,840 Speaker 6: It's sort of on this edge, and if you tip 357 00:18:00,040 --> 00:18:02,800 Speaker 6: it over, you're going to tip it over into weakness. 358 00:18:03,040 --> 00:18:04,960 Speaker 6: You know, if you look at the unemployment rate of 359 00:18:05,000 --> 00:18:07,879 Speaker 6: four point two likely go into four point three percent. 360 00:18:08,240 --> 00:18:11,600 Speaker 6: If you look at the layoffs, you know, we're just 361 00:18:11,800 --> 00:18:17,760 Speaker 6: this close to actually slipping into outright potential negative job growth. 362 00:18:17,800 --> 00:18:20,200 Speaker 6: And by the way, you know, I mentioned that if 363 00:18:20,200 --> 00:18:22,639 Speaker 6: companies are not passing through the cost increases, what are 364 00:18:22,640 --> 00:18:26,000 Speaker 6: they doing. They're absorbing that in their margins. So that's 365 00:18:26,000 --> 00:18:29,040 Speaker 6: why the labor market in turn is again on this edge. 366 00:18:29,160 --> 00:18:31,119 Speaker 6: So I do very much agree, and I hope we 367 00:18:31,160 --> 00:18:33,920 Speaker 6: see a rate cut in September. I do associate scope 368 00:18:33,960 --> 00:18:35,280 Speaker 6: for a couple more this year. 369 00:18:36,600 --> 00:18:39,280 Speaker 2: Other than technology. What screens well for you guys these days? 370 00:18:39,280 --> 00:18:41,880 Speaker 2: I don't know if you'd do it by industry, sector, 371 00:18:41,960 --> 00:18:44,720 Speaker 2: by factor, how do you guys try to find some opportunities? 372 00:18:44,920 --> 00:18:48,920 Speaker 6: We do it by theme and also of course by 373 00:18:48,960 --> 00:18:51,879 Speaker 6: industry sector as well. But when I think about some 374 00:18:51,960 --> 00:18:54,159 Speaker 6: of the themes that we're excited about, it's clearly the 375 00:18:54,200 --> 00:18:57,880 Speaker 6: digital transformation and the many sectors that it touches. We're 376 00:18:57,920 --> 00:19:03,320 Speaker 6: also investing along the sustained nobility theme as well. And finally, 377 00:19:03,480 --> 00:19:06,439 Speaker 6: this notion of new living. The way we consume, the 378 00:19:06,440 --> 00:19:08,720 Speaker 6: way we take care of ourselves, the way we exercise, 379 00:19:08,800 --> 00:19:11,719 Speaker 6: the way we live is all very different today, and 380 00:19:11,720 --> 00:19:13,160 Speaker 6: in many ways it's tech enabled. 381 00:19:13,440 --> 00:19:13,600 Speaker 4: You know. 382 00:19:13,720 --> 00:19:16,080 Speaker 6: Further, I would think of it in terms of different 383 00:19:16,320 --> 00:19:21,040 Speaker 6: sectors within sort of the private market space, and it's 384 00:19:21,320 --> 00:19:26,120 Speaker 6: it's goods and its services, it's goods and products, it's technology, 385 00:19:26,520 --> 00:19:30,320 Speaker 6: and it's also healthcare, health and healthcare sciences. And so 386 00:19:30,400 --> 00:19:34,200 Speaker 6: we're we're finding a multid of opportunities along all those, 387 00:19:34,320 --> 00:19:34,880 Speaker 6: all four of. 388 00:19:34,800 --> 00:19:37,640 Speaker 5: Those, digging into healthcare because I mean, it's the worst 389 00:19:37,680 --> 00:19:39,480 Speaker 5: performing sector so far this year in the S and 390 00:19:39,480 --> 00:19:42,040 Speaker 5: P five hundred. Where are you seeing opportunities there? 391 00:19:42,840 --> 00:19:43,080 Speaker 7: Right? 392 00:19:43,680 --> 00:19:47,119 Speaker 6: So clearly healthcare in the public markets has been the 393 00:19:47,200 --> 00:19:49,639 Speaker 6: mercy of what's happening in Washington, d C. And the 394 00:19:49,680 --> 00:19:53,359 Speaker 6: policy there. You know, one secular growth in healthcare, I 395 00:19:53,359 --> 00:19:56,159 Speaker 6: would say, is within pharmaceuticals and the fact that so 396 00:19:56,400 --> 00:20:00,119 Speaker 6: many R and D dollars have gone into new clinical 397 00:20:00,200 --> 00:20:04,280 Speaker 6: trials and new discoveries and eventually for some companies those payoff. 398 00:20:04,560 --> 00:20:08,760 Speaker 6: That's not actually where we're taking our risks, but rather 399 00:20:09,040 --> 00:20:13,480 Speaker 6: we're looking at pharmaceutical services that cater to the large 400 00:20:13,640 --> 00:20:16,919 Speaker 6: or small farmer companies in helping them develop some of 401 00:20:16,920 --> 00:20:20,080 Speaker 6: those new biologics. So we think the services side of 402 00:20:20,119 --> 00:20:24,000 Speaker 6: pharmaceuticals is a better risk adjusted return in order to 403 00:20:24,040 --> 00:20:27,320 Speaker 6: capitalize for what is a trend in healthcare, which is 404 00:20:27,359 --> 00:20:30,000 Speaker 6: the growth in the number of molecules that are being created. 405 00:20:30,920 --> 00:20:33,280 Speaker 2: Where do you see the just private capital going. It 406 00:20:33,280 --> 00:20:35,400 Speaker 2: seems like the deal market's kind of picking up, seeing 407 00:20:35,440 --> 00:20:39,320 Speaker 2: some more from MNA IPOs becase it's some really successful 408 00:20:39,400 --> 00:20:42,479 Speaker 2: tech enabled IPOs this year. Is that suggests to you 409 00:20:42,520 --> 00:20:44,480 Speaker 2: that maybe the capital markets are picking up and that 410 00:20:44,520 --> 00:20:45,000 Speaker 2: could be a. 411 00:20:45,000 --> 00:20:47,879 Speaker 3: Driver they are actually picking up. And I feel like 412 00:20:48,119 --> 00:20:49,280 Speaker 3: this maybe. 413 00:20:49,040 --> 00:20:51,639 Speaker 6: Is catching people by surprise, because when you look at 414 00:20:51,680 --> 00:20:54,640 Speaker 6: the numbers year today, the first half of the year, 415 00:20:54,760 --> 00:20:57,399 Speaker 6: the M and A activity is up about thirty percent. 416 00:20:57,640 --> 00:21:01,000 Speaker 6: If you look at the IPO market up about twenty 417 00:21:01,080 --> 00:21:03,879 Speaker 6: one percent, and Paul, You're right that it's not just 418 00:21:03,960 --> 00:21:06,600 Speaker 6: the volume and the number of companies that are, you know, 419 00:21:07,320 --> 00:21:10,440 Speaker 6: seeking that public listing, but it's also the performance. If 420 00:21:10,480 --> 00:21:13,960 Speaker 6: you look at the average IPO of a company year 421 00:21:14,000 --> 00:21:16,520 Speaker 6: to date, it's it's up fifty or sixty percent, so 422 00:21:16,560 --> 00:21:17,520 Speaker 6: it's been successful. 423 00:21:18,160 --> 00:21:18,360 Speaker 7: Now. 424 00:21:18,520 --> 00:21:21,159 Speaker 6: I don't think it's an accident that this level of 425 00:21:21,160 --> 00:21:25,959 Speaker 6: activity is happening. I think public market valuations are interesting 426 00:21:26,160 --> 00:21:29,560 Speaker 6: to some of those private market companies becoming listed. I 427 00:21:29,600 --> 00:21:33,920 Speaker 6: think it's increasing consumer confidence and also business confidence, which 428 00:21:33,960 --> 00:21:38,320 Speaker 6: we've seen quite a turnaround actually since April. And finally 429 00:21:38,480 --> 00:21:40,640 Speaker 6: it's you know, the market is sniffing out a RAID 430 00:21:40,680 --> 00:21:44,280 Speaker 6: cut and so all of those things are supportive for 431 00:21:44,440 --> 00:21:47,480 Speaker 6: capital markets activity. So we've seen a very robust first 432 00:21:47,480 --> 00:21:50,480 Speaker 6: half of the year already. We've actually seen an acceleration 433 00:21:50,880 --> 00:21:54,080 Speaker 6: in the third quarter as well. So I suspect, especially 434 00:21:54,080 --> 00:21:56,400 Speaker 6: with a RAID cut in September, this should continue. 435 00:21:56,520 --> 00:21:58,240 Speaker 2: And have to labor to everybody else get back to work. 436 00:21:58,240 --> 00:22:01,880 Speaker 2: Anastasia Almarroso, she's at work, chief investment strategist Private Wealth 437 00:22:02,119 --> 00:22:04,040 Speaker 2: at Partners Group, joining us live here on our Bloomberg 438 00:22:04,040 --> 00:22:06,800 Speaker 2: and Act report shooting. We appreciate that stay with us. 439 00:22:06,880 --> 00:22:09,360 Speaker 2: More from Bloomberg Surveillance coming up after this. 440 00:22:15,400 --> 00:22:19,000 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us Live 441 00:22:19,040 --> 00:22:22,239 Speaker 1: weekday afternoons from seven to ten am Eastern. Listen on 442 00:22:22,280 --> 00:22:25,960 Speaker 1: Applecarplay and Android Auto with the Bloomberg Business app, or 443 00:22:26,119 --> 00:22:27,560 Speaker 1: watch US Live on YouTube. 444 00:22:27,640 --> 00:22:31,480 Speaker 2: John Murray, he's the CIO of NFJ. They're based down 445 00:22:31,680 --> 00:22:35,879 Speaker 2: in Dallas, Texas. John, how do you think about inflation, 446 00:22:36,880 --> 00:22:39,720 Speaker 2: the labor market and maybe how the FED should be 447 00:22:39,800 --> 00:22:40,560 Speaker 2: proceding here? 448 00:22:41,480 --> 00:22:44,240 Speaker 8: So a couple of things I would say, Paul, the 449 00:22:44,280 --> 00:22:47,399 Speaker 8: first on inflation, I think inflation is going to cool, 450 00:22:47,600 --> 00:22:50,399 Speaker 8: and I'll say that for two reasons. The first is 451 00:22:50,440 --> 00:22:53,480 Speaker 8: that housing, which is the biggest component R one third 452 00:22:53,520 --> 00:22:57,119 Speaker 8: of CPI, that should continue too slow. And the reason 453 00:22:57,240 --> 00:23:00,440 Speaker 8: for that is real time rents tracked by Zillo are 454 00:23:00,480 --> 00:23:03,360 Speaker 8: flat to negative. On top of that, as a fundamental 455 00:23:03,400 --> 00:23:05,680 Speaker 8: bottom up stock picker, I can see that in the 456 00:23:05,720 --> 00:23:09,600 Speaker 8: FFO reports coming out of Mid America apartments funds flow 457 00:23:09,680 --> 00:23:10,800 Speaker 8: from operation funds. 458 00:23:10,840 --> 00:23:14,000 Speaker 5: Oh yeah, cover reads. 459 00:23:14,000 --> 00:23:14,960 Speaker 7: So we always dook about. 460 00:23:14,960 --> 00:23:17,679 Speaker 8: Okay, okay, I like that, so you can see it. 461 00:23:17,720 --> 00:23:20,440 Speaker 8: You can see it in the numbers. So for those reasons. 462 00:23:20,520 --> 00:23:23,400 Speaker 8: I think that people are underestimating and that's a twelve 463 00:23:23,440 --> 00:23:26,600 Speaker 8: month lag, and so that data should be coming out 464 00:23:26,640 --> 00:23:29,280 Speaker 8: and you have inventory building and vacancy rates rising. And 465 00:23:29,280 --> 00:23:31,720 Speaker 8: that's because when rates were low, people built a lot 466 00:23:31,960 --> 00:23:33,840 Speaker 8: that all came on the market, and now you have 467 00:23:34,280 --> 00:23:38,320 Speaker 8: restricted that because rates are high. So there's an imbalanced brewing, 468 00:23:38,400 --> 00:23:41,040 Speaker 8: I think. So I expect that to roll over. And 469 00:23:41,040 --> 00:23:44,520 Speaker 8: then the second piece is around services, which is a 470 00:23:44,600 --> 00:23:47,359 Speaker 8: quarter of the CPI. Healthcare is a big chunk of that. 471 00:23:47,760 --> 00:23:49,840 Speaker 8: And again bottom up basis. So you guys have seen 472 00:23:50,200 --> 00:23:52,760 Speaker 8: U and H, you've seen Humana. Well, a lot of 473 00:23:52,760 --> 00:23:56,680 Speaker 8: folks don't realize that the insurer portion of that basket, okay, 474 00:23:56,960 --> 00:23:59,439 Speaker 8: is calculated based on margins, not what you pay at 475 00:23:59,440 --> 00:24:01,920 Speaker 8: the doctor. Everyone says, well, why healthcare inflation keeps going 476 00:24:02,000 --> 00:24:04,080 Speaker 8: up up, up, up up, But it's not based on that. 477 00:24:04,520 --> 00:24:07,280 Speaker 8: The insurers is based on the margins. Margins have been crushed. 478 00:24:07,720 --> 00:24:09,600 Speaker 8: So I think that's going to come down and that's 479 00:24:09,600 --> 00:24:12,080 Speaker 8: going to give the room a lot more ammo to cut. 480 00:24:13,040 --> 00:24:16,320 Speaker 5: So speaking of cuts, I mean market is essentially pricing 481 00:24:16,359 --> 00:24:19,000 Speaker 5: in a cut in the coming weeks here in September. 482 00:24:19,880 --> 00:24:22,240 Speaker 5: Is that also in line with what your expectations are. 483 00:24:22,359 --> 00:24:24,639 Speaker 5: And if so, what's the cadence afterward for cuts? 484 00:24:24,920 --> 00:24:27,000 Speaker 8: Well, the two year bond yield has been screaming at 485 00:24:27,000 --> 00:24:30,000 Speaker 8: the FETI cut for a long time now. So you've 486 00:24:30,000 --> 00:24:32,440 Speaker 8: got that down there at three point six versus four 487 00:24:32,480 --> 00:24:34,760 Speaker 8: and a half. You know, let's give a little bit 488 00:24:34,760 --> 00:24:37,040 Speaker 8: of a sneak preed for what could happen when they 489 00:24:37,040 --> 00:24:38,359 Speaker 8: start to move rates lower. 490 00:24:38,840 --> 00:24:40,880 Speaker 7: The Russell two thousand. 491 00:24:40,520 --> 00:24:44,840 Speaker 8: Value okay, on Friday was up just over four percent. 492 00:24:45,520 --> 00:24:49,000 Speaker 8: You got one third of the entire the entire year's 493 00:24:49,000 --> 00:24:50,880 Speaker 8: gain of the S and P five hundred a day. 494 00:24:51,440 --> 00:24:53,760 Speaker 8: So like you, I think, think about that for a second. 495 00:24:53,760 --> 00:24:56,200 Speaker 8: It's like all year the SMP, Grind, Grind Grind and 496 00:24:56,280 --> 00:24:59,800 Speaker 8: vida Ai, all these amazing companies. You get one third 497 00:24:59,840 --> 00:25:02,400 Speaker 8: of that return in a single day, just because Jpowell 498 00:25:02,440 --> 00:25:05,879 Speaker 8: opens his mouth and says we may need to lower rates. 499 00:25:06,200 --> 00:25:08,160 Speaker 7: So this is a coiled spring. 500 00:25:08,720 --> 00:25:12,280 Speaker 8: And to get on another topic just briefly, with regard 501 00:25:12,320 --> 00:25:15,560 Speaker 8: to unemployment, I actually think it's a moral issue that 502 00:25:15,600 --> 00:25:20,000 Speaker 8: we're waiting to lower rates to see unemployment go up, 503 00:25:20,440 --> 00:25:23,080 Speaker 8: because why are we doing this? We have a system 504 00:25:23,160 --> 00:25:27,520 Speaker 8: that encourages debt. That is the incentive structure that is 505 00:25:27,560 --> 00:25:29,680 Speaker 8: embedded with how interest is deducted. 506 00:25:30,240 --> 00:25:32,399 Speaker 7: And yet we're waiting to see unemployment tick up. 507 00:25:32,480 --> 00:25:34,320 Speaker 8: We're waiting to see people lose jobs before we make 508 00:25:34,359 --> 00:25:36,719 Speaker 8: we make barring costs lower. And I know that the 509 00:25:36,720 --> 00:25:39,320 Speaker 8: inflation goes of the seventies are haunting the FED. But 510 00:25:39,359 --> 00:25:41,520 Speaker 8: I'll be honest, I think it's totally different with the 511 00:25:41,880 --> 00:25:46,480 Speaker 8: economies more globalized, unionization's way down, It's a totally different landscape. 512 00:25:46,480 --> 00:25:49,800 Speaker 8: So I think we should rethink this entire discussion around 513 00:25:50,119 --> 00:25:52,240 Speaker 8: waiting for unemployment to go up before we cut. 514 00:25:52,640 --> 00:25:54,760 Speaker 5: So what do you think the FED should be squarely 515 00:25:54,800 --> 00:25:58,800 Speaker 5: focused on right now? Is the priority here stabilizing prices, 516 00:25:58,880 --> 00:26:02,200 Speaker 5: bringing down inflation, or maximizing unemployment? Where do you think 517 00:26:02,200 --> 00:26:03,040 Speaker 5: their eyes are fixed? 518 00:26:03,160 --> 00:26:06,760 Speaker 8: I think well, I think they're pivoting to the unemployment picture, 519 00:26:06,880 --> 00:26:08,480 Speaker 8: and they should be, and they should be and that 520 00:26:08,520 --> 00:26:11,360 Speaker 8: should be the primary focus. To be honest, the inflation 521 00:26:11,440 --> 00:26:15,160 Speaker 8: pictures already tackled. We're down at the long term range. 522 00:26:15,200 --> 00:26:16,560 Speaker 8: The long term range for inflation is two and a 523 00:26:16,560 --> 00:26:18,480 Speaker 8: half to three percent, going back all the way to 524 00:26:18,480 --> 00:26:19,320 Speaker 8: the nineteen seventies. 525 00:26:19,359 --> 00:26:20,160 Speaker 7: That's where it's been. 526 00:26:21,000 --> 00:26:22,800 Speaker 8: The reality is I have a bit of an issue 527 00:26:22,800 --> 00:26:25,440 Speaker 8: with this whole discussion because we're talking about the rate 528 00:26:25,440 --> 00:26:28,080 Speaker 8: of change. Things aren't cheaper. Hamburgers are more expensive and 529 00:26:28,080 --> 00:26:29,320 Speaker 8: they're going to stay more expensive. 530 00:26:29,359 --> 00:26:31,040 Speaker 7: We all know this. Cars are more expensive, houses and 531 00:26:31,040 --> 00:26:31,560 Speaker 7: more expensive. 532 00:26:31,960 --> 00:26:35,280 Speaker 8: The rate of change calculation is what they target, and 533 00:26:35,320 --> 00:26:38,040 Speaker 8: to be honest, the cumulative graph or inflation does this 534 00:26:38,160 --> 00:26:41,720 Speaker 8: over time. So the idea that we've tamed inflation is 535 00:26:41,720 --> 00:26:44,960 Speaker 8: a bit of a misnomer. It's just how the calculation's done. 536 00:26:45,080 --> 00:26:48,720 Speaker 8: But unemployment is the real issue because if you have 537 00:26:48,800 --> 00:26:50,680 Speaker 8: people that lose their jobs, that is a real toll 538 00:26:50,720 --> 00:26:54,080 Speaker 8: in the psyche of Americans, and that's an acute problem 539 00:26:54,119 --> 00:26:56,600 Speaker 8: that is harder to solve. So I think, based on 540 00:26:56,600 --> 00:26:59,200 Speaker 8: where the two year bond yield sits, they should lower rates, 541 00:26:59,200 --> 00:27:00,800 Speaker 8: and they should be quick about it, and they should 542 00:27:00,840 --> 00:27:03,240 Speaker 8: be more dynamic about it. And I think waiting too 543 00:27:03,280 --> 00:27:07,880 Speaker 8: long presents serious risks to the US economy. 544 00:27:08,000 --> 00:27:10,680 Speaker 2: If the FED is going to be in a rate 545 00:27:10,760 --> 00:27:14,600 Speaker 2: cutting mode for the next twelve eighteen months, what do 546 00:27:14,600 --> 00:27:15,960 Speaker 2: you own? What do you want to own? 547 00:27:16,920 --> 00:27:19,560 Speaker 7: So I mentioned small caps. 548 00:27:19,760 --> 00:27:23,120 Speaker 8: I think an area that is just primed to outperform 549 00:27:23,240 --> 00:27:26,200 Speaker 8: are the regional banks. Let me give a couple comments 550 00:27:26,240 --> 00:27:29,760 Speaker 8: on this. The price to books for regional banks. Some 551 00:27:29,800 --> 00:27:32,640 Speaker 8: of these are trading back to where they were in 552 00:27:32,680 --> 00:27:35,640 Speaker 8: March of twenty three during the banking crisis. No one's 553 00:27:35,680 --> 00:27:38,399 Speaker 8: looking at this. Price to books are very attractive. But 554 00:27:38,480 --> 00:27:41,199 Speaker 8: on top of that, you've got earnings growth in the 555 00:27:41,200 --> 00:27:44,200 Speaker 8: mid teens fifteen sixteen percent. Some of these are growing 556 00:27:44,200 --> 00:27:47,119 Speaker 8: faster than growth stock. So I'm getting price to books 557 00:27:47,119 --> 00:27:50,200 Speaker 8: at a discount earnings growth. And if that yield curve steepens, 558 00:27:50,240 --> 00:27:53,359 Speaker 8: and it should and it should, they're going to print money. 559 00:27:53,800 --> 00:27:57,040 Speaker 8: So those look very attractive. They're twenty percent of the 560 00:27:57,119 --> 00:28:00,560 Speaker 8: Russell two thousand value. You can't get a small rally 561 00:28:00,560 --> 00:28:03,480 Speaker 8: without the banks. You can't get a value rally without 562 00:28:03,480 --> 00:28:06,119 Speaker 8: the banks. We've been in a decade growth market. I 563 00:28:06,280 --> 00:28:09,000 Speaker 8: like regional banks here. I think they're prime. No one's looking. 564 00:28:09,040 --> 00:28:12,119 Speaker 8: They're growing big dividends, and the regulation going on with 565 00:28:12,119 --> 00:28:14,199 Speaker 8: the Basle three requirements for big banks is going to 566 00:28:14,240 --> 00:28:17,199 Speaker 8: level the playing field more for the smaller and mid banks. 567 00:28:18,440 --> 00:28:21,640 Speaker 5: Well, let's stick with another sector that is very rate 568 00:28:21,760 --> 00:28:23,600 Speaker 5: sensitive as well, real estate. 569 00:28:23,720 --> 00:28:24,879 Speaker 3: What are you seeing there? 570 00:28:25,680 --> 00:28:27,680 Speaker 7: I like real estate, but not all of it. 571 00:28:28,560 --> 00:28:34,920 Speaker 8: Industrial routs look really attractive names like Proligious, Rexford, First Industrial, 572 00:28:35,440 --> 00:28:38,400 Speaker 8: a couple of things on these They have massive structural tailwinds. 573 00:28:38,400 --> 00:28:40,280 Speaker 8: I don't know about you guys, but Amazon keeps coming 574 00:28:40,320 --> 00:28:42,080 Speaker 8: to my house pretty regularly. 575 00:28:42,480 --> 00:28:44,960 Speaker 7: So those boxes are around the clock. 576 00:28:45,040 --> 00:28:48,040 Speaker 8: So those, uh, those need to go through those logistical 577 00:28:48,040 --> 00:28:51,680 Speaker 8: warehouses and ports. Those are strategic assets. These are some 578 00:28:51,680 --> 00:28:54,200 Speaker 8: of these are trading at the biggest valuation discounts in 579 00:28:54,240 --> 00:28:57,520 Speaker 8: a decade, namely Proligious as kind of a Hallmark company. 580 00:28:58,280 --> 00:29:01,080 Speaker 8: Very juicy diviting yields. They're not at risk of being caught. 581 00:29:01,320 --> 00:29:04,080 Speaker 8: Evaluations are attractive. Again, no one wants to really own 582 00:29:04,160 --> 00:29:07,920 Speaker 8: real estate. They're non existent in the growth indexes. 583 00:29:08,240 --> 00:29:10,040 Speaker 7: So I like that space a lot. I think there's 584 00:29:10,240 --> 00:29:11,680 Speaker 7: major upside of these names. 585 00:29:12,000 --> 00:29:14,960 Speaker 8: And you saw them move big on Friday, and they 586 00:29:14,960 --> 00:29:16,880 Speaker 8: are a coiled spring. So when do you want to 587 00:29:16,880 --> 00:29:19,840 Speaker 8: own real state? Ironically when capital gets turned off? So 588 00:29:19,840 --> 00:29:20,600 Speaker 8: where are you avoiding? 589 00:29:20,680 --> 00:29:22,640 Speaker 5: I mean you mentioned that there are opportunities you're looking 590 00:29:22,680 --> 00:29:25,200 Speaker 5: at industrial, What about what areas? 591 00:29:25,200 --> 00:29:26,400 Speaker 2: Are you a little. 592 00:29:26,200 --> 00:29:28,400 Speaker 8: Bit so there are I would say that you know, 593 00:29:28,440 --> 00:29:30,240 Speaker 8: if you look up and down the cap scale, and 594 00:29:30,240 --> 00:29:31,880 Speaker 8: you look to where the opportunities. I would say that 595 00:29:31,920 --> 00:29:33,920 Speaker 8: some of the growth areas are priced to perfection. You've 596 00:29:33,920 --> 00:29:36,840 Speaker 8: got really high multiples, particularly in some of the semi names. 597 00:29:36,840 --> 00:29:38,640 Speaker 8: I know those names are firing and all cylinders, and 598 00:29:38,640 --> 00:29:41,160 Speaker 8: they look great. Broadcom is an example of that. It's 599 00:29:41,200 --> 00:29:43,600 Speaker 8: a great company, but you're paying a lot. And so 600 00:29:43,800 --> 00:29:46,160 Speaker 8: I think that if you look at the market as 601 00:29:46,160 --> 00:29:48,920 Speaker 8: a whole, some of the technology names are more expensive 602 00:29:49,000 --> 00:29:52,960 Speaker 8: than I would argue people should pay for those multiples, 603 00:29:52,960 --> 00:29:55,200 Speaker 8: and it makes sense the markets at all time high multiples. 604 00:29:55,440 --> 00:29:58,440 Speaker 8: But that being said, there are plenty of technology names 605 00:29:58,480 --> 00:30:01,280 Speaker 8: that still look good. Some of the software names look 606 00:30:01,400 --> 00:30:03,760 Speaker 8: very interesting to us. Google is a name that we 607 00:30:03,800 --> 00:30:06,080 Speaker 8: really like here. You know, that's now one of the 608 00:30:06,160 --> 00:30:08,960 Speaker 8: largest weights in the Russell one thousand values, So that's 609 00:30:09,000 --> 00:30:11,320 Speaker 8: a value stock. I love how Frank Russell gets to 610 00:30:11,320 --> 00:30:15,120 Speaker 8: decide what's in and out. But that's fine. But I 611 00:30:15,120 --> 00:30:17,320 Speaker 8: think there's a lot of opportunity in that name as well. 612 00:30:17,400 --> 00:30:21,120 Speaker 8: And they've got one of the best teams around Quantum 613 00:30:21,200 --> 00:30:24,120 Speaker 8: ai Talent, and they're trading one of the lower multiples. 614 00:30:24,120 --> 00:30:26,120 Speaker 8: Tons of cash, buybacks, dividends. 615 00:30:25,720 --> 00:30:26,080 Speaker 7: Et cetera. 616 00:30:26,280 --> 00:30:27,840 Speaker 2: For being like, yo, what you call in the bond 617 00:30:27,840 --> 00:30:29,560 Speaker 2: market here? Where do you see opportunities if at all 618 00:30:29,600 --> 00:30:30,320 Speaker 2: in the bond market. 619 00:30:30,440 --> 00:30:32,640 Speaker 8: Well, I'm an equity guy. Guy, I'm an equity guy, 620 00:30:32,640 --> 00:30:35,120 Speaker 8: so I won't motificate there. But what I'll say is 621 00:30:35,160 --> 00:30:38,959 Speaker 8: I think that the equity income area of the market, 622 00:30:39,080 --> 00:30:41,000 Speaker 8: namely those reachs we talked about those banks. 623 00:30:41,200 --> 00:30:42,800 Speaker 7: If you think that rates are going to. 624 00:30:42,840 --> 00:30:45,840 Speaker 8: Come down and you like bonds, and you should really 625 00:30:45,960 --> 00:30:48,240 Speaker 8: like some of the equity income areas of the market. 626 00:30:47,960 --> 00:30:49,920 Speaker 2: Great stuff is always John, Thanks so much for joining us, 627 00:30:49,960 --> 00:30:53,320 Speaker 2: John Murray, cio at n FJ, giving you some good 628 00:30:53,400 --> 00:30:56,320 Speaker 2: names there, some good thoughts on some themes there in 629 00:30:56,360 --> 00:30:58,240 Speaker 2: the marketplace for a feed a reserve that looks like 630 00:30:58,320 --> 00:31:00,800 Speaker 2: it's getting ready to cut us with us. More from 631 00:31:00,840 --> 00:31:03,000 Speaker 2: Bloomberg Surveillance coming up after this. 632 00:31:09,040 --> 00:31:12,640 Speaker 1: You're listening to the Bloomberg Surveillance podcast. Catch us live 633 00:31:12,680 --> 00:31:15,880 Speaker 1: weekday afternoons from seven to ten am Eastern Listen on 634 00:31:15,920 --> 00:31:19,600 Speaker 1: Applecarplay and Android Auto with the Bloomberg Business app, or 635 00:31:19,760 --> 00:31:21,240 Speaker 1: watch us live on YouTube. 636 00:31:21,440 --> 00:31:26,680 Speaker 2: It's time for the famous Lisa Matteo newspaper segment, Lisa, what. 637 00:31:26,680 --> 00:31:27,120 Speaker 7: Do you got first? 638 00:31:27,120 --> 00:31:27,360 Speaker 2: Today? 639 00:31:27,360 --> 00:31:28,320 Speaker 7: Famous I'm excited. 640 00:31:28,760 --> 00:31:32,959 Speaker 9: Okay, yes, Nora, welcome to newspapers. Okay, So the job market, right, 641 00:31:33,000 --> 00:31:35,000 Speaker 9: we know for entry level workers, it's a little bit 642 00:31:35,000 --> 00:31:36,720 Speaker 9: of a slump, right, But the Wall Street Journal actually 643 00:31:36,760 --> 00:31:39,360 Speaker 9: has a story it says, not if you're in AI 644 00:31:39,440 --> 00:31:42,160 Speaker 9: and you've experienced in machine learning. They're saying some of 645 00:31:42,160 --> 00:31:44,080 Speaker 9: these kids in their twenty I call them kids, sorry, 646 00:31:44,120 --> 00:31:46,840 Speaker 9: in their twenties, that many of them are making a 647 00:31:47,000 --> 00:31:51,000 Speaker 9: million dollars a year. Okay, this is a new report. 648 00:31:51,040 --> 00:31:55,040 Speaker 9: It says base salaries for even non managerial AI workers 649 00:31:55,280 --> 00:31:58,640 Speaker 9: zero to three years experience increase by abound twelve percent 650 00:31:58,640 --> 00:32:01,160 Speaker 9: from twenty twenty four to twenty twenty. And they're also 651 00:32:01,240 --> 00:32:04,560 Speaker 9: moving to management roles twice as fast as some of 652 00:32:04,560 --> 00:32:06,560 Speaker 9: the other folks who are just doing regular you know, 653 00:32:06,600 --> 00:32:10,760 Speaker 9: software engineers. So there's a company called Data Bricks and 654 00:32:10,800 --> 00:32:14,000 Speaker 9: they said, if you have a generative AI research scientists 655 00:32:14,040 --> 00:32:16,719 Speaker 9: as little as two years experience, they can make a 656 00:32:16,760 --> 00:32:19,480 Speaker 9: base salary between one hundred and ninety and two hundred 657 00:32:19,480 --> 00:32:21,920 Speaker 9: and sixty thousand dollars there, and if you include the 658 00:32:21,920 --> 00:32:23,080 Speaker 9: stock grants, it's even more. 659 00:32:23,400 --> 00:32:23,480 Speaker 4: So. 660 00:32:23,520 --> 00:32:26,080 Speaker 9: It just goes to show you, you know, exactly how 661 00:32:26,160 --> 00:32:29,120 Speaker 9: much these students can make when they come out of 662 00:32:29,120 --> 00:32:31,000 Speaker 9: college having these AI. 663 00:32:30,880 --> 00:32:32,280 Speaker 3: Skills and what companies are looking for. 664 00:32:32,360 --> 00:32:35,720 Speaker 2: It's crazy. So I mean, is there an AI degree 665 00:32:35,920 --> 00:32:39,080 Speaker 2: or is it just I mean it's so new, I 666 00:32:39,080 --> 00:32:41,560 Speaker 2: mean it's very nice. I guess it's machine learning versus 667 00:32:41,680 --> 00:32:45,040 Speaker 2: software engineer. Correct? Correct, because a software engineer that's been this. 668 00:32:45,240 --> 00:32:48,320 Speaker 5: It's like the next generation y software engineers and the 669 00:32:48,400 --> 00:32:49,480 Speaker 5: next iteration here. 670 00:32:50,080 --> 00:32:52,920 Speaker 9: Yeah, so that's the way to go, I know. Okay, 671 00:32:52,960 --> 00:32:55,880 Speaker 9: So this one, I just want to say, I'm sorry 672 00:32:55,960 --> 00:32:59,800 Speaker 9: kids before we get to the story. A school cafeteria staple. 673 00:33:00,080 --> 00:33:02,400 Speaker 9: New York City public schools could be disappearing. We're talking 674 00:33:02,440 --> 00:33:03,360 Speaker 9: about the chicken nugget. 675 00:33:03,600 --> 00:33:04,000 Speaker 4: Guys. 676 00:33:04,160 --> 00:33:05,680 Speaker 3: This is serious, Okay. 677 00:33:05,600 --> 00:33:07,480 Speaker 9: No, but the reason why Okay, So there's these new 678 00:33:07,520 --> 00:33:09,920 Speaker 9: food standards, right, they were announced this week. They go 679 00:33:09,960 --> 00:33:12,720 Speaker 9: into effect July twenty twenty six. It's for like a 680 00:33:12,760 --> 00:33:16,080 Speaker 9: dozen city agencies and that includes the Department of Education. 681 00:33:16,680 --> 00:33:19,640 Speaker 9: So they want to do things like ban process meats 682 00:33:19,720 --> 00:33:23,960 Speaker 9: like chicken nuggets, create new restrictions on artificial colors, preservatives, 683 00:33:24,320 --> 00:33:28,720 Speaker 9: further limit those low calorie sweeteners, increase offerings of plant protein. 684 00:33:29,240 --> 00:33:30,240 Speaker 2: So mayor Eric. 685 00:33:30,080 --> 00:33:31,640 Speaker 9: Addams is saying, you know what, we're going to make 686 00:33:31,760 --> 00:33:36,040 Speaker 9: New Yorkers healthier. You remember he tried that vegan Friday 687 00:33:36,120 --> 00:33:37,479 Speaker 9: thing back in twenty twenty two. 688 00:33:37,600 --> 00:33:38,719 Speaker 7: Didn't didn't kind of work out. 689 00:33:38,840 --> 00:33:39,360 Speaker 3: He tried it. 690 00:33:40,160 --> 00:33:41,840 Speaker 9: But a lot of educators are saying, you know what, 691 00:33:42,160 --> 00:33:44,200 Speaker 9: the kids might not like this, and what if you 692 00:33:44,240 --> 00:33:45,200 Speaker 9: have those picky. 693 00:33:44,920 --> 00:33:47,120 Speaker 7: Eaters, what are they going to eat instead? 694 00:33:47,240 --> 00:33:50,040 Speaker 9: Because now they're going to be hungry. So it's a 695 00:33:50,120 --> 00:33:52,280 Speaker 9: it's a battle in the New York City public schools 696 00:33:52,280 --> 00:33:52,840 Speaker 9: for the nugget. 697 00:33:52,960 --> 00:33:54,560 Speaker 3: So they'll just you know, skip out on lunch. You're like, 698 00:33:54,600 --> 00:33:56,320 Speaker 3: this is this is too healthy for me. 699 00:33:56,520 --> 00:33:57,440 Speaker 5: I'm not gonna eat it, you. 700 00:33:57,480 --> 00:33:59,400 Speaker 2: Know, because you do have the picky eaters. I know, 701 00:33:59,480 --> 00:34:00,120 Speaker 2: I had one. 702 00:34:00,200 --> 00:34:02,960 Speaker 9: I had one. He grew out of it, thank goodness. Okay, 703 00:34:03,320 --> 00:34:06,080 Speaker 9: I gotta go to cracker Barrel Paul for you. Okay, 704 00:34:06,440 --> 00:34:08,960 Speaker 9: all right, you know they went back to the original logo, right, 705 00:34:09,000 --> 00:34:10,880 Speaker 9: but the New York Post is saying, now you have 706 00:34:11,000 --> 00:34:15,160 Speaker 9: the workers. They're going on social media complaining about the company. Right, 707 00:34:15,160 --> 00:34:17,720 Speaker 9: They're complaining about how much money they're making, their hours 708 00:34:17,760 --> 00:34:21,480 Speaker 9: are cut back, and they're also complaining about fake homestyle cooking. 709 00:34:21,560 --> 00:34:22,400 Speaker 2: So I'm not sure. 710 00:34:23,120 --> 00:34:24,480 Speaker 9: Did you ever have the meat. 711 00:34:24,239 --> 00:34:26,440 Speaker 3: Loaf when you were there? No, you never did the 712 00:34:26,520 --> 00:34:29,840 Speaker 3: meat I did. I always get the pancakes. 713 00:34:29,880 --> 00:34:32,359 Speaker 9: Well, you're traveling on the road, right, you're a crackerbll yay, 714 00:34:32,440 --> 00:34:33,279 Speaker 9: let me try the meat loaf. 715 00:34:33,320 --> 00:34:34,160 Speaker 7: Okay, So I did. 716 00:34:34,880 --> 00:34:35,600 Speaker 3: It was okay. 717 00:34:36,080 --> 00:34:38,520 Speaker 9: But what they're saying now is because they've been cutting 718 00:34:38,560 --> 00:34:42,040 Speaker 9: back on kitchen staff. What the meat loaf actually is, 719 00:34:42,440 --> 00:34:45,279 Speaker 9: it's off a truck, it's frozen, it's prepackaged and these 720 00:34:45,320 --> 00:34:47,719 Speaker 9: sealed things. So all the basically workers do is they 721 00:34:47,719 --> 00:34:49,239 Speaker 9: take it out of the steel package, pop it in 722 00:34:49,239 --> 00:34:53,960 Speaker 9: the microwave, and there's your homestyle. So people are just 723 00:34:54,040 --> 00:34:56,440 Speaker 9: like going off about it. They're saying they're cutting back 724 00:34:56,480 --> 00:34:59,440 Speaker 9: on their hours because they don't have to give him 725 00:34:59,440 --> 00:35:01,640 Speaker 9: the health insurance benefits if they cut back their hours. 726 00:35:02,040 --> 00:35:04,359 Speaker 9: But it's this whole back and forth now on social media. 727 00:35:04,560 --> 00:35:07,160 Speaker 9: The company hasn't said anything about it, but it's this 728 00:35:07,320 --> 00:35:10,720 Speaker 9: like continuing thing with with the restaurant. 729 00:35:10,760 --> 00:35:13,720 Speaker 2: It's been in the headline, Yeah, it's been in the headlines. Crazy. 730 00:35:13,760 --> 00:35:16,080 Speaker 2: The stock is up eighteen percent year to date, a 731 00:35:16,120 --> 00:35:18,719 Speaker 2: lot of molatility. It's up fifty percent. You spoke to 732 00:35:18,760 --> 00:35:21,600 Speaker 2: Mike Mike Helen yesterday and BlueBag Intelligence. He covers the 733 00:35:21,600 --> 00:35:24,279 Speaker 2: restaurants for BI. He says, this management team is doing 734 00:35:24,320 --> 00:35:25,880 Speaker 2: a great job. Wall Street loves. 735 00:35:25,680 --> 00:35:29,040 Speaker 7: Them, yes, and even this whole absolutely. 736 00:35:29,080 --> 00:35:30,759 Speaker 2: You can see it in the stock prices. He said, 737 00:35:30,800 --> 00:35:35,360 Speaker 2: they weren't getting younger people. The older people that were complaining, 738 00:35:35,360 --> 00:35:36,919 Speaker 2: and maybe or the people that are complaining on social 739 00:35:36,920 --> 00:35:39,960 Speaker 2: media weren't the ones coming into the store. Interesting, So anyway, 740 00:35:40,040 --> 00:35:42,239 Speaker 2: it's just a different take on what's going on there. 741 00:35:42,239 --> 00:35:45,120 Speaker 2: All right, LEAs man tell you with the newspapers. Thank 742 00:35:45,120 --> 00:35:45,600 Speaker 2: you so much. 743 00:35:45,920 --> 00:35:50,759 Speaker 1: This is the Bloomberg Surveillance podcast, available on Apple, Spotify, 744 00:35:50,880 --> 00:35:53,120 Speaker 1: and anywhere else you get your podcasts. 745 00:35:53,640 --> 00:35:54,920 Speaker 7: Listen live each. 746 00:35:54,680 --> 00:35:58,520 Speaker 1: Weekday, seven to ten am Eastern on Bloomberg dot com, 747 00:35:58,680 --> 00:36:02,480 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app. 748 00:36:02,760 --> 00:36:05,880 Speaker 1: You can also watch us live every weekday on YouTube 749 00:36:06,160 --> 00:36:08,200 Speaker 1: and always on the Bloomberg terminal.