1 00:00:02,759 --> 00:00:10,600 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the 2 00:00:10,640 --> 00:00:14,600 Speaker 1: Bloomberg Intelligence Podcast. Catch us live weekdays at ten am 3 00:00:14,640 --> 00:00:17,880 Speaker 1: Eastern on Apple, Cocklay and Android Auto with the Bloomberg 4 00:00:17,960 --> 00:00:21,080 Speaker 1: Business App. Listen on demand wherever you get your podcasts, 5 00:00:21,400 --> 00:00:23,120 Speaker 1: or watch us live on YouTube. 6 00:00:24,200 --> 00:00:27,520 Speaker 2: Dell reported fewer sales of AI servers, lower profit margins 7 00:00:27,560 --> 00:00:30,360 Speaker 2: and expected that's really taking a toll on shares. They're 8 00:00:30,360 --> 00:00:32,959 Speaker 2: down about nine percent. So you want someone who could 9 00:00:32,960 --> 00:00:35,320 Speaker 2: break it all down for us. Let's bring in Woojin Ho, 10 00:00:35,440 --> 00:00:39,839 Speaker 2: Bloomberg Intelligence senior technology analysts joining us from Princeton. Woojin, 11 00:00:39,960 --> 00:00:42,960 Speaker 2: welcome back to the show. I want to start broader. 12 00:00:43,040 --> 00:00:46,239 Speaker 2: So taking these results into consideration, I mean, is it 13 00:00:46,360 --> 00:00:49,239 Speaker 2: showing that the AI rally has has more room to 14 00:00:49,360 --> 00:00:51,400 Speaker 2: run or not? I mean, what are you hearing? 15 00:00:52,600 --> 00:00:56,440 Speaker 3: And in terms of the AI rally in general, I 16 00:00:56,480 --> 00:00:59,200 Speaker 3: mean we saw in videos numbers and video is actually 17 00:00:59,280 --> 00:01:01,240 Speaker 3: doing quiet well. I mean if you ex out to 18 00:01:01,320 --> 00:01:07,720 Speaker 3: China outlook right, the demand is still robust and this 19 00:01:07,760 --> 00:01:13,080 Speaker 3: actually flows through to Dell. If anything, the AI numbers 20 00:01:13,120 --> 00:01:15,600 Speaker 3: for a server numbers were better than expected in the quarter, 21 00:01:15,880 --> 00:01:18,360 Speaker 3: and they also raised their guidance by another full year 22 00:01:18,360 --> 00:01:20,640 Speaker 3: guidance by another five billion, So instead of fifteen billion 23 00:01:20,640 --> 00:01:23,479 Speaker 3: for the year, they're expecting twenty billion for the year, 24 00:01:23,760 --> 00:01:26,880 Speaker 3: and add more of these sovereign and neocloud deployment start 25 00:01:26,959 --> 00:01:29,920 Speaker 3: ramping up. You know, twenty twenty six AI server revenue 26 00:01:29,959 --> 00:01:33,040 Speaker 3: should be better for Dell given how they're positioned. 27 00:01:33,680 --> 00:01:36,119 Speaker 4: So then can you try to explain why this stock 28 00:01:36,160 --> 00:01:38,680 Speaker 4: is down nine percent? I mean, Dell just said it 29 00:01:38,680 --> 00:01:42,319 Speaker 4: now plans to ship twenty billion dollars of artificial intelligence 30 00:01:42,319 --> 00:01:46,319 Speaker 4: servers in fiscal twenty twenty six, double what it sold 31 00:01:46,400 --> 00:01:48,800 Speaker 4: last year. What is upsetting investors? 32 00:01:49,560 --> 00:01:52,280 Speaker 3: Yeah, So, so there's a couple of things. Let's start 33 00:01:52,360 --> 00:01:55,640 Speaker 3: on the AI server piece first. I've always said and 34 00:01:56,360 --> 00:02:00,320 Speaker 3: Dell is we'll contend to it. Having Aisells is double 35 00:02:00,400 --> 00:02:03,760 Speaker 3: edged sword. What you're getting in sales, you kind of 36 00:02:03,800 --> 00:02:06,040 Speaker 3: lose out on gross margin. So let me give you 37 00:02:06,040 --> 00:02:10,239 Speaker 3: an example. From a gross margin standpoint, traditional servers as 38 00:02:10,280 --> 00:02:14,360 Speaker 3: well as storage combined are roughly in the you know, 39 00:02:14,400 --> 00:02:19,359 Speaker 3: the twenties to thirties range, right. AI servers they're they're 40 00:02:19,639 --> 00:02:23,480 Speaker 3: closer to the mid teens range, right, So from an 41 00:02:23,480 --> 00:02:28,200 Speaker 3: operating margin standpoint, it actually is somewhat earnings deluded to 42 00:02:28,240 --> 00:02:32,040 Speaker 3: some degree if you sell way too much AI servers. 43 00:02:32,240 --> 00:02:35,600 Speaker 3: So you know, the one point two billion AI server 44 00:02:35,760 --> 00:02:39,800 Speaker 3: beat that only equated to two cents in an EPs. 45 00:02:39,840 --> 00:02:42,280 Speaker 3: So what Della has been saying for quite some time now, 46 00:02:42,560 --> 00:02:45,880 Speaker 3: don't focus on operating margin because that's that's what they missed. 47 00:02:46,320 --> 00:02:51,359 Speaker 3: Focus on the operating margin dollars. That's fantastic, But you know, 48 00:02:51,800 --> 00:02:55,000 Speaker 3: the you know, the the incremental five billion for the 49 00:02:55,080 --> 00:02:57,640 Speaker 3: year isn't going to be the big boost the EPs 50 00:02:57,639 --> 00:02:58,880 Speaker 3: that people are hoping for. 51 00:03:00,080 --> 00:03:02,960 Speaker 2: A big concern for investors is at the profitability of 52 00:03:03,000 --> 00:03:05,680 Speaker 2: AI servers. I mean they run on processors from companies 53 00:03:05,680 --> 00:03:07,760 Speaker 2: like Nvideo, A m D right, which are which are 54 00:03:07,840 --> 00:03:10,200 Speaker 2: pretty pricey. I mean, should they be worried about that? 55 00:03:11,200 --> 00:03:13,440 Speaker 3: Well, you know, the hope is is that once we 56 00:03:13,480 --> 00:03:17,760 Speaker 3: start moving away from these hyper scale and neocloud type 57 00:03:17,760 --> 00:03:22,680 Speaker 3: of deals, right because they're selling you know, fifty fifty 58 00:03:22,720 --> 00:03:26,320 Speaker 3: thousand servers plus to each of these each of these companies, 59 00:03:27,400 --> 00:03:29,680 Speaker 3: you know, they're not going to get as much they're 60 00:03:29,840 --> 00:03:32,000 Speaker 3: they're heavily discounted. But if they start selling to the 61 00:03:32,160 --> 00:03:38,680 Speaker 3: enterprise over time, the gross margin profile should get better 62 00:03:38,800 --> 00:03:42,920 Speaker 3: and be more in line with traditional service. Now, that's 63 00:03:42,960 --> 00:03:45,920 Speaker 3: going to take a couple of years to materialize. But 64 00:03:45,960 --> 00:03:47,560 Speaker 3: the more important thing is if we think about it 65 00:03:47,600 --> 00:03:50,520 Speaker 3: from a longer term perspective, as long as Dell is 66 00:03:50,560 --> 00:03:55,640 Speaker 3: ahead of from from a competitive standpoint, they should continue 67 00:03:55,680 --> 00:03:59,360 Speaker 3: to win this AI game, not only on the neocloud side, 68 00:03:59,360 --> 00:04:02,280 Speaker 3: but also on the enterprise side, which should help profitability 69 00:04:02,320 --> 00:04:04,360 Speaker 3: longer term. But you're gonna have to wait. 70 00:04:05,000 --> 00:04:06,760 Speaker 4: And you know, when I did a little more digging 71 00:04:06,840 --> 00:04:11,000 Speaker 4: into this earnings report, I found that Dell spent one 72 00:04:11,000 --> 00:04:15,720 Speaker 4: point three billion dollars on share repurchases and dividends during 73 00:04:15,720 --> 00:04:18,560 Speaker 4: the quarter. That's an enviable position to be in. But 74 00:04:18,600 --> 00:04:21,359 Speaker 4: do you think it's the best use of Dell's money? 75 00:04:22,120 --> 00:04:28,000 Speaker 3: Well, so, I think they've They've they've always been since 76 00:04:28,600 --> 00:04:30,479 Speaker 3: they came back to public and then spun off the 77 00:04:30,560 --> 00:04:35,920 Speaker 3: VMware business. They've been very focused on shareholder returns. Right now, 78 00:04:36,200 --> 00:04:40,040 Speaker 3: if you think about from a valuation standpoint, you know, 79 00:04:40,440 --> 00:04:42,840 Speaker 3: M and A is probably going to be something that's 80 00:04:42,880 --> 00:04:45,320 Speaker 3: going to be tough for them to do. They've already 81 00:04:45,400 --> 00:04:47,880 Speaker 3: learned a lesson from big m and A with a 82 00:04:47,960 --> 00:04:50,200 Speaker 3: VMware deal, and which is one of the reasons why 83 00:04:50,200 --> 00:04:54,960 Speaker 3: they spunted out. So if from a shareholder standpoint, if 84 00:04:55,040 --> 00:04:58,479 Speaker 3: there's nothing that Dell can buy, I'd rather have it 85 00:04:58,560 --> 00:05:02,240 Speaker 3: back in dividends and and buybacks. How is it changing, sure, 86 00:05:02,279 --> 00:05:03,040 Speaker 3: like a day like today? 87 00:05:03,440 --> 00:05:05,880 Speaker 4: Well yeah, oh yeah. 88 00:05:05,920 --> 00:05:09,080 Speaker 2: How is how is Dell shaping up against its competitors, 89 00:05:09,120 --> 00:05:11,800 Speaker 2: Let's say, like an HP or super micro computer. 90 00:05:12,560 --> 00:05:14,320 Speaker 3: Yeah, so so let's let me take it from a 91 00:05:14,720 --> 00:05:18,960 Speaker 3: two standpoints. Right from super Micro, we're thinking about it 92 00:05:18,960 --> 00:05:21,600 Speaker 3: more along the lines from AI servers. Super Micro still 93 00:05:21,680 --> 00:05:24,960 Speaker 3: leads the way in the AI server market. Now, one 94 00:05:24,960 --> 00:05:27,680 Speaker 3: of the things that we can glean from the numbers 95 00:05:27,760 --> 00:05:31,800 Speaker 3: is that Dell has been heavily discounting to win to 96 00:05:31,839 --> 00:05:35,480 Speaker 3: win its market share, and they actually have the financial 97 00:05:35,480 --> 00:05:37,920 Speaker 3: have to do so with a strong balance sheet. Now, 98 00:05:37,920 --> 00:05:41,239 Speaker 3: from an HP standpoint, this is more personal computing side, 99 00:05:41,279 --> 00:05:43,200 Speaker 3: and this is one of the This is another reason 100 00:05:43,240 --> 00:05:46,159 Speaker 3: why the shares may be pulling back a little bit 101 00:05:46,680 --> 00:05:50,800 Speaker 3: their PC growth. That segment only grew one percent, and 102 00:05:51,279 --> 00:05:54,160 Speaker 3: on contrast, HP grew five percent. So there's a lot 103 00:05:54,200 --> 00:05:57,240 Speaker 3: of questions in terms of the competitive nature for Dell 104 00:05:57,400 --> 00:06:00,919 Speaker 3: versus HP on the PC market. Now that being said, 105 00:06:01,040 --> 00:06:03,240 Speaker 3: what we can glean from the guide and it is 106 00:06:03,279 --> 00:06:07,480 Speaker 3: the second half of this calendar year. HP should get 107 00:06:07,480 --> 00:06:09,719 Speaker 3: back on track from back to school spending as well 108 00:06:09,760 --> 00:06:12,960 Speaker 3: as Windows eleven upgrade, So I think they should do 109 00:06:12,960 --> 00:06:15,839 Speaker 3: about five percent growth in the second half of the year. 110 00:06:16,720 --> 00:06:19,080 Speaker 4: In the seconds we have left, can you tell us 111 00:06:19,120 --> 00:06:22,520 Speaker 4: how Dell is stacking up against the competition, namely HP. 112 00:06:23,839 --> 00:06:28,080 Speaker 3: Yeah, so from a PC stamp from HP, you know, 113 00:06:29,279 --> 00:06:31,640 Speaker 3: HP is actually winning the game over the last couple 114 00:06:31,720 --> 00:06:33,880 Speaker 3: of quarters, but it's going to be neck and neck 115 00:06:33,880 --> 00:06:36,479 Speaker 3: over the next couple of years. But from an AI 116 00:06:36,680 --> 00:06:39,240 Speaker 3: and a server standpoint, Dell should be fine. 117 00:06:39,440 --> 00:06:41,279 Speaker 2: And in the last minute we have where does Dell 118 00:06:41,400 --> 00:06:43,599 Speaker 2: go from here? I mean, what should their focus be? 119 00:06:44,680 --> 00:06:46,760 Speaker 3: Oh, I really do think it should be on the 120 00:06:46,800 --> 00:06:50,559 Speaker 3: traditional server side as well as source side with AI, 121 00:06:50,720 --> 00:06:53,000 Speaker 3: because they're all going to be melded into one type 122 00:06:53,000 --> 00:06:55,560 Speaker 3: of business going forward, and the Dell's well positioned their 123 00:06:55,600 --> 00:06:56,279 Speaker 3: longer term. 124 00:06:56,560 --> 00:06:59,040 Speaker 2: Stay with us for more Bloomberg Intelligence coming. 125 00:06:58,880 --> 00:07:04,799 Speaker 1: Up after this, you're listening to the Bloomberg Intelligence podcast. 126 00:07:05,160 --> 00:07:08,080 Speaker 1: Catch us live weekdays at ten am. He's Dene on Apple, 127 00:07:08,120 --> 00:07:11,360 Speaker 1: Cocklay and Android Auto with the Bloomberg Business app, listen 128 00:07:11,440 --> 00:07:14,560 Speaker 1: on demand wherever you get your podcasts, or watch us 129 00:07:14,600 --> 00:07:15,560 Speaker 1: live on YouTube. 130 00:07:16,560 --> 00:07:18,880 Speaker 4: One of the big movers today is Caterpillar. Mover to 131 00:07:18,920 --> 00:07:22,080 Speaker 4: the downside, that is off nearly four percent right now. 132 00:07:22,120 --> 00:07:24,720 Speaker 4: It's warning investors that tariffs are expected to have an 133 00:07:24,720 --> 00:07:27,960 Speaker 4: even greater impact, take an even bigger bite out of 134 00:07:28,000 --> 00:07:30,880 Speaker 4: its bottom line, expected to cost CAT as much as 135 00:07:30,880 --> 00:07:34,600 Speaker 4: one point eight billion dollars this year. Let's dig into 136 00:07:34,600 --> 00:07:37,080 Speaker 4: it a little more with Christopher Ciolino. He is Bloomberg 137 00:07:37,120 --> 00:07:41,760 Speaker 4: Intelligence Senior US Machinery analyst. So what is it about 138 00:07:41,760 --> 00:07:45,920 Speaker 4: this report that's got investors in a tizzy? 139 00:07:46,040 --> 00:07:48,600 Speaker 5: Well, you're right, I mean, tariff's will be a bigger 140 00:07:48,680 --> 00:07:52,840 Speaker 5: cost headwind this year, more than KAT previously expected. And 141 00:07:52,880 --> 00:07:56,800 Speaker 5: the revision really seems to be driven by additional clarifications 142 00:07:56,880 --> 00:08:00,120 Speaker 5: around the Section two thirty two steal in aluminum tariffs 143 00:08:00,320 --> 00:08:03,160 Speaker 5: and some of the reciprocal rates on India as you 144 00:08:03,200 --> 00:08:05,600 Speaker 5: alluded to. You know, KAT thinks these TIFFs could be 145 00:08:05,760 --> 00:08:07,560 Speaker 5: you know, up to a one point eight billion dollar 146 00:08:07,640 --> 00:08:10,760 Speaker 5: impact in twenty twenty five. That's up you know, two 147 00:08:10,760 --> 00:08:13,240 Speaker 5: to three hundred million versus their prior view, so a 148 00:08:13,280 --> 00:08:16,800 Speaker 5: little bit higher. So you know, even though that we're 149 00:08:16,840 --> 00:08:19,240 Speaker 5: looking at these incremental costs this year, we think it's 150 00:08:19,280 --> 00:08:23,800 Speaker 5: pretty easily digestible for CAT and probably represents, you know, 151 00:08:23,880 --> 00:08:27,280 Speaker 5: the peak headwind that we'll likely see. They really haven't 152 00:08:27,280 --> 00:08:31,960 Speaker 5: implemented significant cost mitigation or pricing actions yet. I suspect 153 00:08:32,000 --> 00:08:34,280 Speaker 5: you'll see more of those measured than twenty twenty six, 154 00:08:34,800 --> 00:08:37,000 Speaker 5: which could ultimately offset these impacts. 155 00:08:37,240 --> 00:08:41,040 Speaker 2: So is it steal an aluminum? Is that the main focus? 156 00:08:42,440 --> 00:08:44,680 Speaker 5: Yeah, we think so. So we did get an update 157 00:08:44,720 --> 00:08:47,599 Speaker 5: on the section two thirty two taraffs for steel and 158 00:08:47,679 --> 00:08:50,280 Speaker 5: aluminum that expanded the coverage to you know, I think 159 00:08:50,280 --> 00:08:53,560 Speaker 5: an additional four hundred different products. So you know, we 160 00:08:53,600 --> 00:08:57,160 Speaker 5: had CAT report earlier this month and we had that 161 00:08:57,240 --> 00:09:00,240 Speaker 5: subsequent update, So I think that's probably the big driver 162 00:09:00,360 --> 00:09:03,600 Speaker 5: behind it. Obviously, heavy machinery companies use a lot of 163 00:09:03,640 --> 00:09:06,960 Speaker 5: steel and aluminum. It's their largest input costs, so that 164 00:09:07,080 --> 00:09:09,000 Speaker 5: certainly does move the needle. 165 00:09:09,880 --> 00:09:12,560 Speaker 4: We're talking about headwinds, but what about tailwinds any of 166 00:09:12,559 --> 00:09:13,640 Speaker 4: those for Caterpillar. 167 00:09:14,880 --> 00:09:18,280 Speaker 5: Yeah, you know, despite some of these near term costs headwinds, 168 00:09:18,840 --> 00:09:21,600 Speaker 5: I don't think it really ultimately changes the narrative here. 169 00:09:21,640 --> 00:09:24,120 Speaker 5: You know, we're still quite optimistic that earnings are going 170 00:09:24,200 --> 00:09:27,360 Speaker 5: to bottom this year. There's a number of cyclical and 171 00:09:27,400 --> 00:09:29,880 Speaker 5: secular tailwinds that we think are going to drive higher 172 00:09:29,880 --> 00:09:33,640 Speaker 5: earnings in twenty six and twenty seven. The backlocks is 173 00:09:33,679 --> 00:09:36,679 Speaker 5: sitting at a record high. We've seen very solid order 174 00:09:36,760 --> 00:09:40,319 Speaker 5: trends these past you know, four quarters, and dealer inventories 175 00:09:40,800 --> 00:09:44,680 Speaker 5: remain at you know, pretty healthy levels considering softness in 176 00:09:44,760 --> 00:09:48,280 Speaker 5: the broader economy. So all of these are really positive 177 00:09:48,360 --> 00:09:49,959 Speaker 5: leading indicators for Caterpillar. 178 00:09:50,400 --> 00:09:52,760 Speaker 2: And Chris, you follow this company very closely. So when 179 00:09:52,760 --> 00:09:57,120 Speaker 2: we have an economics flowdown, what segments of Caterpillar's business 180 00:09:57,200 --> 00:09:58,720 Speaker 2: tend to hold up the best. 181 00:10:00,160 --> 00:10:02,520 Speaker 5: So right now, the segment holding up the best would 182 00:10:02,559 --> 00:10:05,480 Speaker 5: be their E and T or energy and transportation business, 183 00:10:06,160 --> 00:10:08,640 Speaker 5: and really I think the big driver behind that is 184 00:10:08,720 --> 00:10:12,760 Speaker 5: power generation, particularly on the data center side. Those are 185 00:10:12,880 --> 00:10:17,319 Speaker 5: much longer cycle products have you know, very extended backlogs 186 00:10:17,320 --> 00:10:21,480 Speaker 5: for many years. Caterpillars adding capacity there, so we've seen 187 00:10:21,520 --> 00:10:24,760 Speaker 5: that business hold up very well. On the flip side, 188 00:10:25,160 --> 00:10:28,839 Speaker 5: the more cyclical construction industry's business is probably the one 189 00:10:29,160 --> 00:10:33,520 Speaker 5: more harder hit, and also their resource industry's business, which 190 00:10:33,640 --> 00:10:36,199 Speaker 5: is a lot of mining equipment that's been a little 191 00:10:36,200 --> 00:10:38,680 Speaker 5: softer as well. But you know, I think, you know, 192 00:10:38,679 --> 00:10:41,120 Speaker 5: if we're looking at a lower rate environment moving forward, 193 00:10:42,280 --> 00:10:44,480 Speaker 5: we're certainly a little bit more optimistic on some of 194 00:10:44,480 --> 00:10:47,640 Speaker 5: the growth prospects and those two businesses moving forward. 195 00:10:48,160 --> 00:10:51,280 Speaker 2: Stay with us for more Bloomberg Intelligence coming up after this. 196 00:10:53,840 --> 00:10:57,520 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 197 00:10:57,600 --> 00:11:00,720 Speaker 1: weekdays at ten am Eastern on apple Cock and Android 198 00:11:00,720 --> 00:11:03,520 Speaker 1: Auto with the Blue Work Business app. Listen on demand 199 00:11:03,640 --> 00:11:07,200 Speaker 1: wherever you get your podcasts, or watch us live on YouTube. 200 00:11:08,120 --> 00:11:11,200 Speaker 4: In Video and AI, it was out with earnings this 201 00:11:11,280 --> 00:11:15,120 Speaker 4: week and it impressed with more proof that that AI 202 00:11:15,200 --> 00:11:17,480 Speaker 4: spending continues to be strong. I want to talk more 203 00:11:17,480 --> 00:11:21,400 Speaker 4: about AI in the real world with Binran. He is 204 00:11:21,480 --> 00:11:24,760 Speaker 4: founder and CEO at the software company sig Tech. He 205 00:11:24,880 --> 00:11:28,400 Speaker 4: joins us from London. Ben, thanks so much for being 206 00:11:28,480 --> 00:11:31,040 Speaker 4: with us. Before we get into Sigtech and what you 207 00:11:31,080 --> 00:11:33,240 Speaker 4: do with AI agents, we'll get into what all of 208 00:11:33,280 --> 00:11:35,800 Speaker 4: that is. I just want your take your thoughts on 209 00:11:36,160 --> 00:11:37,760 Speaker 4: In Video's earnings report this week. 210 00:11:38,280 --> 00:11:42,040 Speaker 6: I think we are seeing unprecedented demand for AI services, 211 00:11:42,080 --> 00:11:46,040 Speaker 6: AI inference. If you look at the you know, not 212 00:11:46,160 --> 00:11:49,960 Speaker 6: only the hyperscaters, purchasing GPUs and building data centers. 213 00:11:50,000 --> 00:11:51,000 Speaker 7: It's keep going up. 214 00:11:51,440 --> 00:11:55,680 Speaker 6: And if you look at the consumptions of tokens by 215 00:11:56,240 --> 00:11:59,880 Speaker 6: large language model providers such as Opening Ai and Google 216 00:12:00,080 --> 00:12:04,880 Speaker 6: and the Anthropic, it's growing at one hundred percent every 217 00:12:04,880 --> 00:12:10,360 Speaker 6: six months. So the adoption, the usage, the consumption is 218 00:12:10,400 --> 00:12:15,280 Speaker 6: all going up the trend. There's no no reason why 219 00:12:15,280 --> 00:12:18,079 Speaker 6: it's going to slow down or certainly all stopping. 220 00:12:19,200 --> 00:12:21,920 Speaker 2: We've heard a lot about different types of AI. Jen 221 00:12:21,960 --> 00:12:24,439 Speaker 2: AI is a huge one. I mean, I know everyone's 222 00:12:24,480 --> 00:12:28,319 Speaker 2: on the CHADGBT or whatever whatever else you have, but 223 00:12:28,520 --> 00:12:31,360 Speaker 2: do generic AI tools They can help out in a 224 00:12:31,400 --> 00:12:34,679 Speaker 2: lot of fields. But what about financial institutions, I mean 225 00:12:35,160 --> 00:12:37,440 Speaker 2: you focus more on on custom AI? 226 00:12:37,520 --> 00:12:38,120 Speaker 6: Is that correct? 227 00:12:39,600 --> 00:12:39,800 Speaker 7: Yeah? 228 00:12:39,800 --> 00:12:43,920 Speaker 6: We focused on building entirely bespoke and custom AI agents 229 00:12:43,920 --> 00:12:47,480 Speaker 6: for customers in capital markets. I think people now one 230 00:12:47,559 --> 00:12:51,480 Speaker 6: hundreds of millions of people have used CHGBT, so we all 231 00:12:51,520 --> 00:12:54,880 Speaker 6: have a good idea of you know, what a chat 232 00:12:54,960 --> 00:12:58,920 Speaker 6: bolt can do for us, which is extremely useful. But 233 00:12:58,960 --> 00:13:02,840 Speaker 6: when it comes to business is there's an increasing gap 234 00:13:03,400 --> 00:13:07,439 Speaker 6: between what the large language models are capable of and 235 00:13:07,640 --> 00:13:11,840 Speaker 6: what actually value users in businesses are getting out of 236 00:13:13,000 --> 00:13:16,960 Speaker 6: the getting out of the applications using using the same models. 237 00:13:17,840 --> 00:13:20,920 Speaker 6: You know, the large nugree model capability has been improving 238 00:13:22,120 --> 00:13:30,839 Speaker 6: dramatically and frankly the probably the most improved applications unfortunately 239 00:13:30,920 --> 00:13:34,440 Speaker 6: have been restricted to only a few areas, mainly about 240 00:13:35,120 --> 00:13:40,520 Speaker 6: writing code. That that has been the killer app outside chatboard. 241 00:13:41,120 --> 00:13:44,800 Speaker 6: In finance, the difficulty is there actually there are many 242 00:13:44,800 --> 00:13:48,600 Speaker 6: different reasons why the application is not delivering the kind 243 00:13:48,600 --> 00:13:51,480 Speaker 6: of potential we are expecting. One of the reasons is 244 00:13:52,320 --> 00:13:56,000 Speaker 6: in finance we use a lot of private data that 245 00:13:56,440 --> 00:13:59,160 Speaker 6: the large language models are mainly trained on public data. 246 00:14:00,000 --> 00:14:04,400 Speaker 6: And then the question of how to converting the vast 247 00:14:04,480 --> 00:14:09,600 Speaker 6: corpus of financial documents in PDFs, in world documents in 248 00:14:09,679 --> 00:14:15,040 Speaker 6: excels into the right formats that actually can be effectively 249 00:14:15,200 --> 00:14:20,920 Speaker 6: used by large language models. Any error English data conversion 250 00:14:21,320 --> 00:14:27,120 Speaker 6: document processing pipeline will immediately result in very pro qualities 251 00:14:27,280 --> 00:14:32,200 Speaker 6: downstream and in other areas. In finance, we prontion numbers, 252 00:14:32,640 --> 00:14:35,880 Speaker 6: and the large language models are very bad at cremching 253 00:14:35,960 --> 00:14:39,400 Speaker 6: numbers right and it's probably the most expensive calculator we 254 00:14:39,440 --> 00:14:39,920 Speaker 6: can think of. 255 00:14:40,880 --> 00:14:42,240 Speaker 7: So to make large. 256 00:14:42,160 --> 00:14:45,960 Speaker 6: Nuguerte models working in finance we have to provide a 257 00:14:46,280 --> 00:14:51,080 Speaker 6: very wide range of financial tools. These tools can be software, 258 00:14:51,280 --> 00:14:55,400 Speaker 6: can be APIs, can be desktop applications. Then we have 259 00:14:55,480 --> 00:14:58,880 Speaker 6: to train models to use them, and there are other 260 00:14:59,200 --> 00:15:01,880 Speaker 6: challenges to Yeah, that's why everything has to be bespoke. 261 00:15:02,720 --> 00:15:05,400 Speaker 4: Then we keep hearing that AI is going to be 262 00:15:05,480 --> 00:15:08,600 Speaker 4: a job killer, and we're already seeing it. Frankly, a 263 00:15:08,600 --> 00:15:12,920 Speaker 4: lot of you know, entry level positions being taken over 264 00:15:12,960 --> 00:15:15,920 Speaker 4: by AI. That means a lot of recent graduates from 265 00:15:15,960 --> 00:15:18,320 Speaker 4: college or finding it even harder to find a job 266 00:15:18,360 --> 00:15:22,800 Speaker 4: in unemployment during and amidst that demographics about six percent 267 00:15:22,880 --> 00:15:24,680 Speaker 4: right now versus you know, a little more than four 268 00:15:24,720 --> 00:15:28,000 Speaker 4: percent for the rest of us. So what what how 269 00:15:28,040 --> 00:15:30,120 Speaker 4: do you see the future of work looking and how 270 00:15:30,120 --> 00:15:31,120 Speaker 4: does AI play a part? 271 00:15:33,920 --> 00:15:38,360 Speaker 6: I think whatever, there's you know, unprecedented new technology coming along, 272 00:15:38,440 --> 00:15:39,760 Speaker 6: so transformative and. 273 00:15:39,800 --> 00:15:42,000 Speaker 7: So disruptive like AI. 274 00:15:42,240 --> 00:15:46,240 Speaker 6: But previously there was internet, there was industrial revolution, there 275 00:15:46,360 --> 00:15:50,440 Speaker 6: was the invention of airplanes and cars. I mean, inevitably 276 00:15:50,560 --> 00:15:53,680 Speaker 6: some jobs will be killed, I guess you can say that, 277 00:15:54,080 --> 00:15:57,240 Speaker 6: but there will be new jobs created. I think the 278 00:15:57,320 --> 00:16:01,360 Speaker 6: key here is to understand from them mentally what AI 279 00:16:01,440 --> 00:16:05,520 Speaker 6: can do and what AI cannot do and what makes 280 00:16:05,600 --> 00:16:10,000 Speaker 6: us by us, I mean humans special. AI is very 281 00:16:10,040 --> 00:16:18,320 Speaker 6: good at doing repetitive, non non creative work, non creative 282 00:16:18,560 --> 00:16:24,760 Speaker 6: knowledge work. Humans we are uniquely equipped to be creative 283 00:16:24,920 --> 00:16:28,720 Speaker 6: and imaginative. And also, by the way you you probably 284 00:16:28,760 --> 00:16:31,760 Speaker 6: know that AI is really bad at telling a. 285 00:16:31,760 --> 00:16:34,200 Speaker 7: Joke, a good joke, and there's a reason for. 286 00:16:34,200 --> 00:16:39,960 Speaker 6: It, because AI is trained to predict the next the 287 00:16:40,000 --> 00:16:43,640 Speaker 6: next most likely word, the word by word, and to 288 00:16:43,800 --> 00:16:46,560 Speaker 6: deliver a good joke, and the punchline has to be 289 00:16:46,600 --> 00:16:48,480 Speaker 6: surprising and the witty. 290 00:16:48,640 --> 00:16:50,040 Speaker 7: So it's large number. 291 00:16:50,120 --> 00:16:52,160 Speaker 6: Models are literally not trained to be able to tell 292 00:16:52,200 --> 00:16:58,600 Speaker 6: a good joke. So all the comedians and they have 293 00:16:58,720 --> 00:17:01,480 Speaker 6: right own stuff, and they have to have inspiration, they 294 00:17:01,520 --> 00:17:04,800 Speaker 6: have to have new experiences, imagination and creativity. I think 295 00:17:04,800 --> 00:17:08,440 Speaker 6: that's probably a good room model for the future work. 296 00:17:08,480 --> 00:17:12,400 Speaker 6: Look like we can spend more time on being imaginative 297 00:17:12,440 --> 00:17:17,000 Speaker 6: and creative and frankly more intellectually satisfying, and less time 298 00:17:17,080 --> 00:17:20,080 Speaker 6: on things frankly we don't wake up and be excited about. 299 00:17:20,440 --> 00:17:23,520 Speaker 2: Stay with us for more Bloomberg Intelligence coming up after this. 300 00:17:26,080 --> 00:17:29,760 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us Live 301 00:17:29,840 --> 00:17:32,960 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 302 00:17:32,960 --> 00:17:36,280 Speaker 1: Auto with the Bloomberg Business app. Listen on demand wherever 303 00:17:36,320 --> 00:17:39,960 Speaker 1: you get your podcasts, or watch us live on YouTube. 304 00:17:40,440 --> 00:17:42,560 Speaker 4: Want to switch gears for a minute and talk about 305 00:17:42,600 --> 00:17:46,840 Speaker 4: the sleepy summer for the housing market would be home buyers. 306 00:17:46,880 --> 00:17:48,680 Speaker 4: We know they've been staying on the sideline, so they're 307 00:17:48,680 --> 00:17:50,800 Speaker 4: waiting for mortgage rates to come down. They're waiting for 308 00:17:51,320 --> 00:17:54,840 Speaker 4: housing prices to come down. So will they And when 309 00:17:55,400 --> 00:17:58,359 Speaker 4: Best Friedman, she's been looking into her crystal ball, we 310 00:17:58,480 --> 00:18:01,720 Speaker 4: called her in for some help. EO at Brown, Harris Stevens, 311 00:18:02,200 --> 00:18:04,239 Speaker 4: that's always good to see you. Thanks so much for 312 00:18:04,359 --> 00:18:07,080 Speaker 4: joining us. So let's just start with a reality check. 313 00:18:07,480 --> 00:18:10,359 Speaker 4: Are things improving? I mean I heard that inventory was 314 00:18:10,400 --> 00:18:12,639 Speaker 4: starting to beef up a little bit, So are you 315 00:18:12,640 --> 00:18:14,360 Speaker 4: seeing some pockets of improvement? 316 00:18:15,359 --> 00:18:17,640 Speaker 8: You know, it's interesting. Good morning, so nice to see 317 00:18:17,640 --> 00:18:19,800 Speaker 8: you as well. Thanks for having me. I think we 318 00:18:19,840 --> 00:18:22,399 Speaker 8: see a step forward and then a step back. And 319 00:18:22,440 --> 00:18:25,800 Speaker 8: I would describe our housing market at least through the summer, 320 00:18:25,840 --> 00:18:30,199 Speaker 8: it's very frustrating people buyers and sellers couldn't get on 321 00:18:30,200 --> 00:18:35,000 Speaker 8: the same page. You know, for buyers things have become unaffordable. 322 00:18:35,080 --> 00:18:37,880 Speaker 8: Rates are too high. Sellers aren't budging on their prices. 323 00:18:37,920 --> 00:18:40,960 Speaker 8: They're taking their homes off the market. So there's been 324 00:18:41,000 --> 00:18:43,480 Speaker 8: a little bit of that, and it's gradual. You know, 325 00:18:43,520 --> 00:18:46,680 Speaker 8: we definitely performed better this year than we did last year. 326 00:18:46,760 --> 00:18:51,640 Speaker 8: It's a better housing market. But having said that, it's 327 00:18:51,760 --> 00:18:53,320 Speaker 8: it's going to take a little bit of time. And 328 00:18:53,359 --> 00:18:56,639 Speaker 8: I know that everybody's expecting or thinking that the FED 329 00:18:56,760 --> 00:19:01,320 Speaker 8: is going to cut the FED fund rate in September. 330 00:19:01,440 --> 00:19:04,200 Speaker 8: Maybe we'll have to see how the jobs report comes out. 331 00:19:04,720 --> 00:19:07,280 Speaker 8: But you know, even that, you know, I don't know 332 00:19:07,320 --> 00:19:08,960 Speaker 8: that's going to have a dramatic impact. 333 00:19:09,000 --> 00:19:11,080 Speaker 7: It's going to take time for us to come. 334 00:19:10,880 --> 00:19:15,120 Speaker 8: To a better place where we see supply and demand intersecting. 335 00:19:15,200 --> 00:19:19,160 Speaker 8: That's a healthy market, and we don't really have that best. 336 00:19:19,200 --> 00:19:21,680 Speaker 2: I have to tell you, I've been kind of caught 337 00:19:21,720 --> 00:19:23,560 Speaker 2: in the middle of all this. I mean, I was 338 00:19:23,560 --> 00:19:25,800 Speaker 2: trying to find a home. I've been out bid by 339 00:19:25,840 --> 00:19:28,280 Speaker 2: like one hundred and seventy thousand dollars in New Jersey. 340 00:19:28,359 --> 00:19:29,680 Speaker 7: I mean, it was rough. 341 00:19:30,520 --> 00:19:32,920 Speaker 2: So can you break it down as far as areas 342 00:19:32,920 --> 00:19:35,439 Speaker 2: of the US right, what areas are are home selling 343 00:19:35,480 --> 00:19:38,000 Speaker 2: at a faster pace or or maybe what areas have 344 00:19:38,160 --> 00:19:39,080 Speaker 2: more inventory. 345 00:19:40,440 --> 00:19:43,360 Speaker 7: I mean, every real estate market is so local. I'm 346 00:19:43,400 --> 00:19:48,040 Speaker 7: sorry that you have that experience. I'm still there are areas. 347 00:19:48,320 --> 00:19:51,320 Speaker 8: I'll give you an example and market that is completely 348 00:19:51,359 --> 00:19:53,960 Speaker 8: on fire. There's no inventory and there's bidding wars. Is 349 00:19:54,080 --> 00:19:58,960 Speaker 8: Upstate New York, Rinebeck. You can't find anything. Whatever comes on, 350 00:19:59,040 --> 00:20:01,040 Speaker 8: there's a bidding war, similar to what happened to you 351 00:20:01,080 --> 00:20:05,000 Speaker 8: in New Jersey. Places like Montclair, New Jersey, very popular, 352 00:20:05,119 --> 00:20:10,119 Speaker 8: a really strong market, and you know, people get discouraged 353 00:20:10,119 --> 00:20:12,480 Speaker 8: when they walk in they see twenty people there waiting, 354 00:20:12,520 --> 00:20:14,480 Speaker 8: and then they know there's going to be multiple bids 355 00:20:14,520 --> 00:20:17,280 Speaker 8: and rates are higher. Price is now going to be higher, 356 00:20:17,320 --> 00:20:19,880 Speaker 8: and so you know, that's very tough. But that's more 357 00:20:19,920 --> 00:20:23,560 Speaker 8: the exception to the rule. Palm Beach is similar, but 358 00:20:23,680 --> 00:20:26,439 Speaker 8: other places like New York is a pretty steady market. 359 00:20:26,440 --> 00:20:29,840 Speaker 8: In New York City right now, the market has been decent, 360 00:20:30,040 --> 00:20:33,919 Speaker 8: not great. The rental market really strong. That's all I 361 00:20:33,960 --> 00:20:36,600 Speaker 8: hear about is people cannot afford to rent in New York. 362 00:20:36,880 --> 00:20:40,960 Speaker 8: There's no vacancies. So it really depends on what's going 363 00:20:41,000 --> 00:20:44,439 Speaker 8: on with supply and demand in the market. Like in Connecticut, 364 00:20:44,480 --> 00:20:48,640 Speaker 8: for example, also really strong demand and lack of supply, 365 00:20:49,320 --> 00:20:51,639 Speaker 8: and so that's starting. 366 00:20:51,680 --> 00:20:54,040 Speaker 7: We're starting to see more inventory come on and so 367 00:20:54,119 --> 00:20:55,000 Speaker 7: that's a good thing. 368 00:20:55,200 --> 00:20:57,480 Speaker 8: And so hopefully if we get a little bit of 369 00:20:57,760 --> 00:20:59,520 Speaker 8: if rates come down a little bit they have come 370 00:20:59,560 --> 00:21:02,600 Speaker 8: down a little bit, that might inspire more buyers to 371 00:21:02,640 --> 00:21:05,800 Speaker 8: get into the market. But it's gonna it's tough. I'm 372 00:21:05,840 --> 00:21:08,920 Speaker 8: sorry that you had that experience. You know, in due time, 373 00:21:09,000 --> 00:21:10,960 Speaker 8: something will come on that you love and you will 374 00:21:11,000 --> 00:21:12,480 Speaker 8: find it and you will bid on it. 375 00:21:13,240 --> 00:21:13,520 Speaker 7: Bess. 376 00:21:13,680 --> 00:21:16,720 Speaker 4: I want your thoughts on a trend we're continuing to 377 00:21:16,760 --> 00:21:20,320 Speaker 4: see grow, and that is corporations backed by private equity 378 00:21:20,359 --> 00:21:24,520 Speaker 4: groups now buying up single family homes. So folks are 379 00:21:24,560 --> 00:21:27,840 Speaker 4: not only competing against other would be home buyers, they're 380 00:21:27,880 --> 00:21:30,680 Speaker 4: competing against the big guns, these institutional investors. I saw 381 00:21:30,720 --> 00:21:34,280 Speaker 4: this one report from MetLife Investment Management. Get this, They 382 00:21:34,280 --> 00:21:38,359 Speaker 4: say investors, institutional investors may control forty percent of the 383 00:21:38,440 --> 00:21:41,879 Speaker 4: single family rental home market by twenty thirty. How's the 384 00:21:41,880 --> 00:21:44,320 Speaker 4: little guys supposed to compete with that? 385 00:21:44,320 --> 00:21:45,840 Speaker 7: That's really hard. I don't know. 386 00:21:45,880 --> 00:21:48,800 Speaker 8: And we are and we have housing shortage in the 387 00:21:48,880 --> 00:21:49,720 Speaker 8: United States. 388 00:21:49,760 --> 00:21:51,920 Speaker 7: You know, we're we need to build. 389 00:21:52,000 --> 00:21:54,879 Speaker 8: We need four million homes here, So I don't know, 390 00:21:54,960 --> 00:21:57,879 Speaker 8: that's not a good sign. Because people find that they 391 00:21:57,920 --> 00:22:01,320 Speaker 8: can't afford rent, they can't afford to buy, and so 392 00:22:01,359 --> 00:22:03,720 Speaker 8: we need to figure out ways to work together with 393 00:22:03,800 --> 00:22:07,760 Speaker 8: our state and local officials to make rules and legislation 394 00:22:07,840 --> 00:22:10,240 Speaker 8: that makes sense so that people can afford to buy 395 00:22:10,320 --> 00:22:11,600 Speaker 8: and can afford to rent. 396 00:22:12,040 --> 00:22:14,560 Speaker 7: And so yeah, the little guy matters. 397 00:22:14,600 --> 00:22:16,880 Speaker 8: We have to make sure that everyday people can afford 398 00:22:16,920 --> 00:22:20,000 Speaker 8: to pursue their dream, which is to buy a home 399 00:22:20,119 --> 00:22:22,600 Speaker 8: or to rent the home, whatever it is. It's really 400 00:22:22,600 --> 00:22:25,119 Speaker 8: important and we've lost a little bit of that in 401 00:22:25,160 --> 00:22:28,080 Speaker 8: the last five years, and I would love to see 402 00:22:28,119 --> 00:22:32,280 Speaker 8: that switch direction. I'm happy to be part of those discussions. 403 00:22:31,920 --> 00:22:33,920 Speaker 2: And best in the last minute we have here. How 404 00:22:33,960 --> 00:22:36,320 Speaker 2: are the builders doing? I mean, how is the sentiment 405 00:22:36,359 --> 00:22:38,680 Speaker 2: among the builders or building these homes? 406 00:22:39,800 --> 00:22:43,320 Speaker 8: You know, it's a great question and it depends, you know. 407 00:22:43,400 --> 00:22:45,760 Speaker 8: I'll give you a real example. A few months ago, 408 00:22:45,800 --> 00:22:48,840 Speaker 8: as working friend of mine, builder developer New York City, 409 00:22:48,960 --> 00:22:51,840 Speaker 8: was looking at a site, very excited. He wanted to 410 00:22:51,840 --> 00:22:54,520 Speaker 8: buy the site to develop it. And then the primary 411 00:22:54,600 --> 00:22:58,360 Speaker 8: came out and it looks like and whether your politics 412 00:22:58,400 --> 00:23:01,200 Speaker 8: are I don't care, but it looks so potentially Mom 413 00:23:01,280 --> 00:23:02,640 Speaker 8: Donnie might win in New York. 414 00:23:02,720 --> 00:23:03,840 Speaker 7: It's a possibility. 415 00:23:04,119 --> 00:23:06,560 Speaker 8: And so he got squee mission backed away from it, 416 00:23:07,000 --> 00:23:10,560 Speaker 8: and so but another developer came in and ended up 417 00:23:10,560 --> 00:23:11,359 Speaker 8: buying the site. 418 00:23:11,400 --> 00:23:12,600 Speaker 7: It just really depends. 419 00:23:12,680 --> 00:23:15,600 Speaker 8: People are very emotional when it comes to these things, 420 00:23:15,600 --> 00:23:17,439 Speaker 8: and it depends how they feel. If they think the 421 00:23:17,480 --> 00:23:20,160 Speaker 8: market's going to be good or strong, they'll invest. 422 00:23:20,640 --> 00:23:23,280 Speaker 7: And builders are the same. It's pencils down. If they think. 423 00:23:23,240 --> 00:23:27,280 Speaker 8: Legislation is sloppy and not helpful and not giving them incentives, 424 00:23:27,280 --> 00:23:28,800 Speaker 8: they're not going to continue to build. 425 00:23:28,960 --> 00:23:32,080 Speaker 7: So it's such a nuanced story. 426 00:23:32,280 --> 00:23:34,840 Speaker 8: So we're seeing some builders do things, some stay on 427 00:23:34,880 --> 00:23:36,080 Speaker 8: the sidelines right now. 428 00:23:36,400 --> 00:23:41,080 Speaker 1: This is the Bloomberg Intelligence Podcast, available on Apple, Spotify, 429 00:23:41,280 --> 00:23:44,760 Speaker 1: and anywhere else you get your podcasts. Listen live each 430 00:23:44,760 --> 00:23:48,480 Speaker 1: weekday ten am to noon Eastern on Bloomberg dot Com, 431 00:23:48,640 --> 00:23:52,200 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business App. 432 00:23:52,600 --> 00:23:55,480 Speaker 1: You can also watch us live every weekday on YouTube 433 00:23:55,920 --> 00:23:58,160 Speaker 1: and always on the Bloomberg terminal. 434 00:24:01,800 --> 00:24:02,000 Speaker 7: Yeah