1 00:00:02,920 --> 00:00:10,840 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the 2 00:00:10,880 --> 00:00:15,040 Speaker 1: Bloomberg Intelligence podcast. Catch us live weekdays at ten am 3 00:00:15,080 --> 00:00:18,079 Speaker 1: Eastern on Apple Car playing Android Auto with the Bloomberg 4 00:00:18,120 --> 00:00:21,440 Speaker 1: Business app. Listen on demand wherever you get your podcasts, 5 00:00:21,640 --> 00:00:24,040 Speaker 1: or watch us live on YouTube. 6 00:00:25,079 --> 00:00:27,880 Speaker 2: The other big story here in the world of technology 7 00:00:27,960 --> 00:00:32,200 Speaker 2: is Apple. The US Justice Department and sixteen Attorneys General 8 00:00:32,560 --> 00:00:37,519 Speaker 2: sued Apple, accusing the iphonemaker violating antitrust laws by blocking 9 00:00:37,640 --> 00:00:41,760 Speaker 2: rivals from accessing hardware and software features on its popular devices. 10 00:00:41,800 --> 00:00:43,600 Speaker 2: The stocks trading off about three and a half percent 11 00:00:43,680 --> 00:00:47,000 Speaker 2: here today. It's certainly been an underperformer versus some of 12 00:00:47,040 --> 00:00:48,800 Speaker 2: the other big tech names that are really riding in 13 00:00:48,840 --> 00:00:51,479 Speaker 2: the wave of AI. There's concern here about Apple, not 14 00:00:51,560 --> 00:00:54,959 Speaker 2: just with these legal issues, but also with China as 15 00:00:54,960 --> 00:00:57,120 Speaker 2: well in terms of demand and supply chain. So let's 16 00:00:57,160 --> 00:01:00,000 Speaker 2: check it out with anarag Rana along with man Deepca. 17 00:01:00,160 --> 00:01:03,480 Speaker 2: He's our leader of our technology coverage at Bloomberg Intelligence. 18 00:01:03,760 --> 00:01:06,800 Speaker 2: An Rock, what do you make of this latest legal 19 00:01:06,880 --> 00:01:09,720 Speaker 2: challenge from the US Justice Department against Apple. 20 00:01:10,360 --> 00:01:12,440 Speaker 3: So it's been long time coming. There's been, you know, 21 00:01:12,520 --> 00:01:15,080 Speaker 3: so much pressure, legal pressure on them from all over 22 00:01:15,120 --> 00:01:17,920 Speaker 3: the world. Apple is a closed system. Everybody knew that, 23 00:01:18,000 --> 00:01:19,480 Speaker 3: so but you know, it's going to be fun to 24 00:01:19,520 --> 00:01:22,679 Speaker 3: see how these things get proof that they were anti competitive. 25 00:01:23,000 --> 00:01:27,039 Speaker 3: But having said that, big overhang on the stock headline risk, 26 00:01:27,600 --> 00:01:30,000 Speaker 3: nothing good going on for them right now, iPhone saying 27 00:01:30,040 --> 00:01:32,640 Speaker 3: is blowing down, So there's this is going to be 28 00:01:32,720 --> 00:01:34,160 Speaker 3: a tough year for Apple. 29 00:01:34,800 --> 00:01:37,119 Speaker 4: What paulm I were talking about earlier is that what 30 00:01:37,319 --> 00:01:40,840 Speaker 4: problem is this trying to solve for me as a consumer? 31 00:01:42,840 --> 00:01:45,399 Speaker 3: Basically saying, you know, we have a closed system and 32 00:01:45,440 --> 00:01:48,680 Speaker 3: you can't transact outside the system. But Apple would argue 33 00:01:48,680 --> 00:01:51,600 Speaker 3: that that's what makes the iPhone and the Apple ecosystem 34 00:01:51,640 --> 00:01:55,200 Speaker 3: far safer than the open source or the open ecosystems. 35 00:01:55,240 --> 00:01:57,320 Speaker 3: And that's really what a lot of the fight is about. 36 00:01:57,080 --> 00:01:59,760 Speaker 4: Frankly, And it's also like it's easier, Like it makes 37 00:01:59,760 --> 00:02:00,440 Speaker 4: our life, it's easier. 38 00:02:00,520 --> 00:02:01,640 Speaker 5: Don't we want that one click? 39 00:02:01,880 --> 00:02:03,680 Speaker 2: Just just back on the redis story indication a little 40 00:02:03,720 --> 00:02:05,800 Speaker 2: bit higher here. They raised the indication. 41 00:02:05,520 --> 00:02:07,440 Speaker 5: Forty four to forty eight. It was forty two to 42 00:02:07,480 --> 00:02:07,920 Speaker 5: forty six. 43 00:02:07,920 --> 00:02:09,760 Speaker 2: So pushing that indication up a little bit will stay 44 00:02:09,760 --> 00:02:13,320 Speaker 2: on top of that. So we've seen this play before, 45 00:02:13,440 --> 00:02:15,680 Speaker 2: and I know you have ANURAG with your research coverage 46 00:02:15,720 --> 00:02:19,200 Speaker 2: of Microsoft. Is this something where Apple, you know, over 47 00:02:19,200 --> 00:02:22,400 Speaker 2: the next several five ten years, pay some fines, write 48 00:02:22,440 --> 00:02:27,120 Speaker 2: some checks, maybe put some workarounds in their business. How 49 00:02:27,120 --> 00:02:29,520 Speaker 2: do you think this plays out for the company? 50 00:02:29,680 --> 00:02:31,520 Speaker 3: I think you called it right. That's exactly what's going 51 00:02:31,600 --> 00:02:34,240 Speaker 3: to happen. And it could even pressure their services revenue 52 00:02:34,280 --> 00:02:36,280 Speaker 3: a little bit, their app store fee. They'll have to 53 00:02:36,280 --> 00:02:38,720 Speaker 3: figure out to reduce that in certain areas. But I 54 00:02:38,760 --> 00:02:40,839 Speaker 3: would argue that they have the capacity to do make 55 00:02:40,880 --> 00:02:44,320 Speaker 3: it from you know, advertising revenue that they really don't 56 00:02:44,360 --> 00:02:47,040 Speaker 3: generate that much at this point. So you know, the 57 00:02:47,080 --> 00:02:50,360 Speaker 3: ecosystem is there. I don't think you can shake that. 58 00:02:50,760 --> 00:02:52,400 Speaker 3: But it's going to be, as I said, a headline 59 00:02:52,480 --> 00:02:54,000 Speaker 3: risk for the stock for for a long time. 60 00:02:54,040 --> 00:02:58,360 Speaker 4: Now, what do you think resolves it? Like if they 61 00:02:58,400 --> 00:03:00,440 Speaker 4: fix this issue is or something else? What else is 62 00:03:00,480 --> 00:03:03,840 Speaker 4: going to happen? How when is the bottom for this? 63 00:03:04,880 --> 00:03:06,440 Speaker 3: Yeah, I think it's going to be a mix of 64 00:03:06,800 --> 00:03:09,080 Speaker 3: a little bit of fines plus some compression in the 65 00:03:09,120 --> 00:03:12,480 Speaker 3: feast that they charge. But I don't think any structural 66 00:03:12,560 --> 00:03:14,640 Speaker 3: change is going to come out of how Apple does it. 67 00:03:14,680 --> 00:03:17,120 Speaker 4: I mean, that doesn't sound good though, does it? Like 68 00:03:17,160 --> 00:03:19,600 Speaker 4: that's that feels like a big overhang to have to reevaluate. 69 00:03:19,639 --> 00:03:21,840 Speaker 2: Now, this is something that and Honor I've remember is this. 70 00:03:21,919 --> 00:03:24,200 Speaker 2: I mean, this is something that I think the market 71 00:03:24,240 --> 00:03:27,000 Speaker 2: learned from the Microsoft See situation, which was a twenty 72 00:03:27,000 --> 00:03:29,799 Speaker 2: twenty five year issue that at some point and even 73 00:03:29,840 --> 00:03:31,960 Speaker 2: to the tobacco industry, you just kind of power through 74 00:03:33,000 --> 00:03:36,720 Speaker 2: this this overhang. What's the company saying on I mean 75 00:03:36,800 --> 00:03:39,000 Speaker 2: when when they talk about these issues. 76 00:03:39,320 --> 00:03:40,960 Speaker 3: Yeah, they're going to find that. And you know, it 77 00:03:40,960 --> 00:03:43,200 Speaker 3: would have been a different story if iPhone sales were 78 00:03:43,240 --> 00:03:45,920 Speaker 3: really good. But the problem is iPhone sales are also 79 00:03:46,000 --> 00:03:48,080 Speaker 3: not good. The product sales are not there, so there 80 00:03:48,120 --> 00:03:51,320 Speaker 3: isn't much to hangle your hat on. If you're an investor, 81 00:03:51,600 --> 00:03:54,480 Speaker 3: you're looking at, you know, two percent growth in terms 82 00:03:54,520 --> 00:03:58,320 Speaker 3: of top line, maybe five percent bottom or EPs. So 83 00:03:58,520 --> 00:04:01,600 Speaker 3: it's not that exciting right now. Now that may change 84 00:04:01,640 --> 00:04:03,600 Speaker 3: if by summer roared by the end of this year, 85 00:04:03,640 --> 00:04:06,000 Speaker 3: we find out they've done to deal with Google and 86 00:04:06,080 --> 00:04:08,640 Speaker 3: they are able to use Google's large language model on 87 00:04:08,680 --> 00:04:11,640 Speaker 3: their phones, and that leads to foster refresh cycle of 88 00:04:11,640 --> 00:04:13,920 Speaker 3: the iPhone so there is some hope, but you know, 89 00:04:13,960 --> 00:04:15,800 Speaker 3: there is a lot of different butts in between. 90 00:04:16,160 --> 00:04:18,680 Speaker 4: So if I'm looking at this valuation real quick, is 91 00:04:18,720 --> 00:04:21,599 Speaker 4: it worth twenty six times estimated price to earnings? 92 00:04:21,600 --> 00:04:25,680 Speaker 3: There I try not to look at estimated earnings. I 93 00:04:25,720 --> 00:04:28,000 Speaker 3: try to look at free cash flow one hundred plus 94 00:04:28,000 --> 00:04:30,280 Speaker 3: billion growing at three to five percent for a long 95 00:04:30,279 --> 00:04:32,560 Speaker 3: period of time. You know, there isn't a company that 96 00:04:32,640 --> 00:04:36,080 Speaker 3: has better financials than this one. So I you know, 97 00:04:36,120 --> 00:04:38,520 Speaker 3: if I was to look at from that point, you know, 98 00:04:38,600 --> 00:04:40,599 Speaker 3: the yardstick is a bit different. 99 00:04:41,040 --> 00:04:41,719 Speaker 5: Yeah, it's interesting. 100 00:04:41,800 --> 00:04:44,440 Speaker 2: I think this June Developer conference is going to be 101 00:04:44,520 --> 00:04:47,039 Speaker 2: key for Apple. They need to try to get an 102 00:04:47,080 --> 00:04:48,800 Speaker 2: AI narrative. 103 00:04:48,440 --> 00:04:49,440 Speaker 5: Out there for the company. 104 00:04:49,480 --> 00:04:51,039 Speaker 2: On rag Rana, thanks so much for joining us on 105 00:04:51,040 --> 00:04:55,039 Speaker 2: a rag Ruana Senior Technology annels for Bloomberg Intelligence. Just 106 00:04:55,080 --> 00:04:58,640 Speaker 2: talking about the Justice Department suing Apple. They got some 107 00:04:58,680 --> 00:05:00,840 Speaker 2: issues that they're gonna have to work Workaround's going to 108 00:05:00,839 --> 00:05:04,000 Speaker 2: be a long drawn out process, as they typically are. 109 00:05:04,480 --> 00:05:06,200 Speaker 2: The question is, you know, how does the stock perform 110 00:05:06,320 --> 00:05:07,440 Speaker 2: with that overhang. 111 00:05:10,080 --> 00:05:13,960 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 112 00:05:14,040 --> 00:05:17,560 Speaker 1: weekdays at ten am Eastern on applecar Play and Android 113 00:05:17,600 --> 00:05:20,359 Speaker 1: Auto with the Bloomberg Business app. You can also listen 114 00:05:20,480 --> 00:05:23,560 Speaker 1: live on Amazon Alexa from our flagship New York station. 115 00:05:23,960 --> 00:05:27,680 Speaker 1: Just say Alexa play Bloomberg eleven thirty. 116 00:05:28,520 --> 00:05:31,560 Speaker 2: All right, now we all turn to Reddit. Here Man 117 00:05:31,600 --> 00:05:33,880 Speaker 2: deep sing joints and sees a senior technology anels for 118 00:05:33,880 --> 00:05:35,440 Speaker 2: Bloomberg Intelligence. 119 00:05:36,080 --> 00:05:36,440 Speaker 5: Reddit. 120 00:05:36,680 --> 00:05:41,400 Speaker 2: Is this just another social media company, like a Pinterest, 121 00:05:41,520 --> 00:05:44,520 Speaker 2: like a I don't know what, like a smaller meta. 122 00:05:44,680 --> 00:05:45,760 Speaker 5: What is Reddit? 123 00:05:46,640 --> 00:05:46,880 Speaker 6: Yeah? 124 00:05:47,240 --> 00:05:49,960 Speaker 7: I think the best way to think about Reddit is 125 00:05:50,880 --> 00:05:54,040 Speaker 7: it's very similar to Twitter in the sense that it 126 00:05:54,120 --> 00:05:58,240 Speaker 7: is a community interest based platform. But the difference is 127 00:05:59,360 --> 00:06:01,719 Speaker 7: obviously if you've heard about Wall Street bets and you 128 00:06:01,760 --> 00:06:06,280 Speaker 7: know how meme stocks really originated and the whole trend 129 00:06:06,360 --> 00:06:10,080 Speaker 7: originated on Reddit. So it's got a different type of 130 00:06:10,120 --> 00:06:13,080 Speaker 7: community aspect to it. And in terms of user base, 131 00:06:13,120 --> 00:06:17,360 Speaker 7: it's very similar to Twitter or pinterest or Snapchat, so 132 00:06:17,400 --> 00:06:20,760 Speaker 7: it's of the same size. The one big difference is 133 00:06:21,040 --> 00:06:25,320 Speaker 7: reddits engagement when it comes to DAUS to MAUS, which. 134 00:06:25,160 --> 00:06:27,480 Speaker 5: Is daily active users to monthly after users. 135 00:06:27,560 --> 00:06:30,680 Speaker 8: You want them to be more active, right exactly, And 136 00:06:30,720 --> 00:06:33,760 Speaker 8: so that's where they have struggled over the course of 137 00:06:33,800 --> 00:06:37,960 Speaker 8: their fifteen to Eighteen years is years, folks, not months. 138 00:06:38,120 --> 00:06:40,360 Speaker 4: Yeah, it's been like I mean, haven't they been around 139 00:06:40,360 --> 00:06:41,080 Speaker 4: for like twenty years? 140 00:06:41,360 --> 00:06:43,160 Speaker 7: They have been around for eighteen years. 141 00:06:43,000 --> 00:06:43,640 Speaker 4: I mean something. 142 00:06:44,480 --> 00:06:47,400 Speaker 5: I'm still still not making money, I know, that's the thing. 143 00:06:47,560 --> 00:06:49,320 Speaker 4: So I'm just wondering, like what they want to get 144 00:06:49,320 --> 00:06:52,320 Speaker 4: out of this. What would success look like for this 145 00:06:52,400 --> 00:06:54,719 Speaker 4: IPO based in the fact that they're an unprofitable social 146 00:06:54,720 --> 00:06:58,440 Speaker 4: media company. That's not like a popular sentence to say, yeah, and. 147 00:06:58,480 --> 00:07:01,680 Speaker 7: Social media companies, I mean, the ones that have done 148 00:07:01,680 --> 00:07:04,920 Speaker 7: well are the ones with scale and notably meta other 149 00:07:05,040 --> 00:07:08,760 Speaker 7: ones snap Pinterest, Stock hasn't gone anywhere if you look 150 00:07:08,800 --> 00:07:11,360 Speaker 7: at you know, long term eight to ten years, these 151 00:07:11,400 --> 00:07:15,560 Speaker 7: stocks haven't. Yes, they had their way up during the pandemic, 152 00:07:15,600 --> 00:07:19,400 Speaker 7: but then they came down sharply. So clearly profitability is 153 00:07:19,440 --> 00:07:22,240 Speaker 7: a concern for a lot of the smaller social media names, 154 00:07:22,280 --> 00:07:25,240 Speaker 7: and Reddit is no exception. The thing that excites me 155 00:07:25,280 --> 00:07:28,239 Speaker 7: the most is their data licensing part. I think that's 156 00:07:28,280 --> 00:07:31,880 Speaker 7: the part. The timing of it is quite good with 157 00:07:31,960 --> 00:07:35,760 Speaker 7: the Genai wave and everyone focusing on these large language models. 158 00:07:36,200 --> 00:07:39,240 Speaker 7: I mean, at the end of the day, these llms 159 00:07:39,280 --> 00:07:43,080 Speaker 7: have to be trained and retrained every two three months. 160 00:07:43,280 --> 00:07:46,480 Speaker 7: And the way you can retrain these algorithms is through 161 00:07:46,520 --> 00:07:51,080 Speaker 7: the corpus of data like Reddit possesses or like Twitter possesses, 162 00:07:51,120 --> 00:07:54,360 Speaker 7: And that to me is something that every company will 163 00:07:54,360 --> 00:07:56,960 Speaker 7: license from them. We know Google already has a two 164 00:07:57,040 --> 00:08:00,440 Speaker 7: hundred million dollar license. I wouldn't be surprised if Apple 165 00:08:00,640 --> 00:08:03,720 Speaker 7: or Microsoft or others start doing the same, and there 166 00:08:03,760 --> 00:08:06,840 Speaker 7: will be a gold rush for training data at some point, 167 00:08:07,040 --> 00:08:08,280 Speaker 7: like there is for semis. 168 00:08:08,440 --> 00:08:09,400 Speaker 5: So a couple of. 169 00:08:09,400 --> 00:08:11,680 Speaker 2: Hours ago, right an hour ago, we had Men Deep 170 00:08:11,720 --> 00:08:13,640 Speaker 2: in here talking about Reddit to Bailey and I and 171 00:08:13,680 --> 00:08:16,160 Speaker 2: I Billy, and I asked them to pitch us, like 172 00:08:16,160 --> 00:08:17,560 Speaker 2: we're a couple of head fund man and why we 173 00:08:17,560 --> 00:08:18,200 Speaker 2: should buy this thing. 174 00:08:18,200 --> 00:08:19,840 Speaker 5: And I did put in ten percent orders. So we'll 175 00:08:19,840 --> 00:08:21,520 Speaker 5: see how I do today. 176 00:08:21,160 --> 00:08:24,640 Speaker 2: Say, but it is all about that data aspect, is 177 00:08:24,680 --> 00:08:26,640 Speaker 2: Men Deep was highlighting. And so if you're an investor, 178 00:08:26,680 --> 00:08:29,080 Speaker 2: I think you if you're buying stock this morning, I 179 00:08:29,120 --> 00:08:30,880 Speaker 2: think you have to buy off that this is a 180 00:08:31,000 --> 00:08:34,319 Speaker 2: viable aspect to the investment story, that in fact they 181 00:08:34,360 --> 00:08:37,640 Speaker 2: can monetize their data to people that need you know, 182 00:08:37,640 --> 00:08:39,199 Speaker 2: that are running these larger language models. 183 00:08:39,240 --> 00:08:42,680 Speaker 4: So this would be like a third derivative of AI. Yeah, 184 00:08:42,760 --> 00:08:43,880 Speaker 4: is that a fair thing to say? 185 00:08:44,120 --> 00:08:47,400 Speaker 7: And right now everyone is too fixated on semis and 186 00:08:47,440 --> 00:08:50,760 Speaker 7: getting the chips. In the end, it comes down to 187 00:08:50,960 --> 00:08:53,880 Speaker 7: how does AI solve your problem? Whether it's a chatbot 188 00:08:53,960 --> 00:08:57,319 Speaker 7: or a copilot. What does a copilot need to be intelligent? 189 00:08:57,480 --> 00:08:58,440 Speaker 7: It needs data? 190 00:08:58,520 --> 00:09:00,280 Speaker 4: See this is so interesting because I feel like AI 191 00:09:00,360 --> 00:09:02,679 Speaker 4: conversation is now broadening out to different sectors. Paul and 192 00:09:02,720 --> 00:09:04,800 Speaker 4: I talked yesterday. I was just in Houston, and all 193 00:09:04,800 --> 00:09:07,680 Speaker 4: the energy companies are talking about is power demand for 194 00:09:07,760 --> 00:09:10,480 Speaker 4: the data centers for AI? And there just isn't enough 195 00:09:10,520 --> 00:09:12,080 Speaker 4: and like how to solve for that? So now you 196 00:09:12,160 --> 00:09:14,720 Speaker 4: have the AI craze going to social media, and you 197 00:09:14,720 --> 00:09:17,640 Speaker 4: have it going to energy and then chips and then software. 198 00:09:17,679 --> 00:09:18,400 Speaker 4: It's it's kind of. 199 00:09:18,320 --> 00:09:20,280 Speaker 5: Cool, it is, And that's why I. 200 00:09:21,800 --> 00:09:23,959 Speaker 4: Kind of cool. AI is kind of cool. There we 201 00:09:24,040 --> 00:09:24,839 Speaker 4: go drop the mind. 202 00:09:24,920 --> 00:09:26,679 Speaker 5: I think this Internet thing is it's just it's just 203 00:09:26,679 --> 00:09:27,160 Speaker 5: gonna pass. 204 00:09:27,400 --> 00:09:30,600 Speaker 2: Actually, I actually gave that advice once to an analyst 205 00:09:30,679 --> 00:09:32,880 Speaker 2: colleague mind who was following the newspaper industry and they 206 00:09:32,880 --> 00:09:35,120 Speaker 2: asked him and he's a highly ranked analist, and there's 207 00:09:35,160 --> 00:09:37,319 Speaker 2: this little thing called America Online out there and some 208 00:09:37,360 --> 00:09:40,200 Speaker 2: stuff that was coming along Netscape and things like that, 209 00:09:40,360 --> 00:09:42,960 Speaker 2: and they wanted him to drop his coverage where he 210 00:09:42,960 --> 00:09:45,599 Speaker 2: had a franchise and go do this internet thing. You 211 00:09:45,679 --> 00:09:49,120 Speaker 2: know what, I told him, stick with newspapers, baby, to be. 212 00:09:49,120 --> 00:09:53,280 Speaker 4: Fair, to be fair. Where's Netscape? 213 00:09:53,520 --> 00:09:55,040 Speaker 5: Yeah, but I mean aol. 214 00:09:55,640 --> 00:09:58,440 Speaker 2: He Fortunately he ignored me and went on to great 215 00:09:58,440 --> 00:10:03,840 Speaker 2: fame and fortune. So good for landing. Okay, So what's 216 00:10:03,880 --> 00:10:06,200 Speaker 2: the feeling out there about digital advertising in general, because 217 00:10:06,240 --> 00:10:09,040 Speaker 2: that still is, at least in the near term, the 218 00:10:09,040 --> 00:10:11,280 Speaker 2: big driver for Reddit. 219 00:10:11,960 --> 00:10:15,120 Speaker 7: It is, and I think when it comes to ads, clearly, 220 00:10:15,280 --> 00:10:20,000 Speaker 7: Meta has a clear dominance when it comes to showing 221 00:10:20,320 --> 00:10:23,600 Speaker 7: the users the most targeted ads. That's where Twitter struggle. 222 00:10:23,760 --> 00:10:26,559 Speaker 7: That's where I think Reddit struggles to an extent as well, 223 00:10:26,920 --> 00:10:30,080 Speaker 7: is that ad targeting and advertisers go to platforms with 224 00:10:30,240 --> 00:10:34,720 Speaker 7: scale and the best at targeting. So overall environment seems 225 00:10:34,760 --> 00:10:37,240 Speaker 7: to be getting better. But what Meta has going for 226 00:10:37,280 --> 00:10:41,400 Speaker 7: them right now is they're actually applying large angrod models 227 00:10:41,760 --> 00:10:45,200 Speaker 7: for improving their ad targeting. It's not possible for a 228 00:10:45,200 --> 00:10:48,360 Speaker 7: company of Reddit scale or Twitter scale or Snap scale 229 00:10:48,360 --> 00:10:51,520 Speaker 7: to do that because they just don't have that kapex 230 00:10:51,600 --> 00:10:54,800 Speaker 7: investment going in terms of applying large angroid models. So 231 00:10:55,040 --> 00:10:58,040 Speaker 7: that's what it comes down to, scale of investments. 232 00:10:58,120 --> 00:11:01,080 Speaker 4: Okay, before we let you go, they also put like 233 00:11:01,120 --> 00:11:04,360 Speaker 4: what eight percent aside to like regular Reddit users. Are 234 00:11:04,400 --> 00:11:05,800 Speaker 4: they gonna buy it? Are they gonna short? What are 235 00:11:05,840 --> 00:11:06,280 Speaker 4: they gonna do? 236 00:11:06,640 --> 00:11:09,960 Speaker 7: I think, Given again, Wall Street Bets is such a big, 237 00:11:10,040 --> 00:11:12,959 Speaker 7: powerful community on Reddit, I wouldn't be surprised if they 238 00:11:12,960 --> 00:11:15,400 Speaker 7: are interested in buying their own stock. And that's where 239 00:11:15,480 --> 00:11:19,720 Speaker 7: I feel the IPO was priced relatively attractively when it 240 00:11:19,760 --> 00:11:22,440 Speaker 7: comes to, you know, a first dapop up, I wouldn't 241 00:11:22,440 --> 00:11:24,400 Speaker 7: be surprised if if you do end up seeing that 242 00:11:24,480 --> 00:11:27,160 Speaker 7: kind of pop and the eight percent allocation goes to 243 00:11:27,280 --> 00:11:28,960 Speaker 7: moderators and the advanced using way. 244 00:11:28,800 --> 00:11:29,440 Speaker 5: I'm glad I don't. 245 00:11:29,480 --> 00:11:31,240 Speaker 2: I don't have to like moderate the trading this the 246 00:11:31,280 --> 00:11:33,360 Speaker 2: first few days, like as the bookmaker, because I don't 247 00:11:33,360 --> 00:11:35,599 Speaker 2: know what these redditors are gonna do. I don't know 248 00:11:35,640 --> 00:11:37,160 Speaker 2: if they're gonna go crazy like they do for some 249 00:11:37,160 --> 00:11:38,360 Speaker 2: of these other Why would they. 250 00:11:38,320 --> 00:11:40,520 Speaker 7: Shot their own stocks? Give me one good reason. 251 00:11:40,600 --> 00:11:40,959 Speaker 2: I agree. 252 00:11:41,360 --> 00:11:43,600 Speaker 4: They've been talking about like not buying, they've been talking 253 00:11:43,600 --> 00:11:45,520 Speaker 4: about it though, haven't they. 254 00:11:45,960 --> 00:11:48,160 Speaker 2: I don't know this scene could it could be one 255 00:11:48,160 --> 00:11:50,120 Speaker 2: of those things where the you know, the marketmakers like, 256 00:11:50,120 --> 00:11:51,599 Speaker 2: I don't know where these buyers are coming from, but 257 00:11:51,640 --> 00:11:53,720 Speaker 2: they're flooding me in with these one hundred chair orders 258 00:11:53,800 --> 00:11:55,480 Speaker 2: left and right. All right, men Deep saying thank you 259 00:11:55,480 --> 00:11:56,959 Speaker 2: so much for joining us. Man Deep saying he's a 260 00:11:57,040 --> 00:12:01,280 Speaker 2: senior tech industry analyst for Bloomberg Intelligence. He doesn't melod in, folks. 261 00:12:01,320 --> 00:12:04,400 Speaker 2: He comes into the studio just like John Tucker, coming 262 00:12:04,400 --> 00:12:05,480 Speaker 2: and showing up every day. 263 00:12:05,520 --> 00:12:06,440 Speaker 5: A big part of life. 264 00:12:06,360 --> 00:12:08,480 Speaker 9: Is just showing up every day. 265 00:12:08,520 --> 00:12:10,600 Speaker 4: Ain't that the truth? A big part of life is 266 00:12:10,640 --> 00:12:14,319 Speaker 4: showing It's just showing up every day. 267 00:12:14,760 --> 00:12:18,640 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 268 00:12:18,720 --> 00:12:21,400 Speaker 1: weekdays at ten am Eastern on AFO, car Playing and 269 00:12:21,520 --> 00:12:24,440 Speaker 1: broyd Otto with the Bloomberg Business app. Listen on demand 270 00:12:24,480 --> 00:12:28,800 Speaker 1: wherever you get your podcasts, or watch us live on YouTube. 271 00:12:29,600 --> 00:12:31,560 Speaker 4: Well, we get that economic data that came out about 272 00:12:31,559 --> 00:12:35,400 Speaker 4: fifteen minutes ago, that was the pmis over at SMP Global. 273 00:12:35,679 --> 00:12:37,720 Speaker 4: That they came in a little light. So what we 274 00:12:37,880 --> 00:12:39,640 Speaker 4: like to do with you here is get the guy 275 00:12:39,679 --> 00:12:42,360 Speaker 4: who did the data right after they dropped Chris Williamson, 276 00:12:42,400 --> 00:12:45,439 Speaker 4: his chief business economist over at SMP Global Market Intelligence, 277 00:12:45,840 --> 00:12:49,079 Speaker 4: and he joins us Now, what is my read from 278 00:12:49,120 --> 00:12:50,480 Speaker 4: the uspmis right now? 279 00:12:52,120 --> 00:12:54,559 Speaker 10: The April read is one of further solid growth in 280 00:12:54,679 --> 00:12:58,080 Speaker 10: March ends quite a good first quarter. So we're running 281 00:12:58,080 --> 00:13:01,400 Speaker 10: at levels that are realy indicted of GDP rising and 282 00:13:01,400 --> 00:13:04,800 Speaker 10: annualized rate around two percent, which I think matches a 283 00:13:04,800 --> 00:13:09,680 Speaker 10: lot of other sort of NowCast models. So quite a 284 00:13:09,679 --> 00:13:13,160 Speaker 10: good quarter. What's interesting is I think the split of data, 285 00:13:14,720 --> 00:13:19,400 Speaker 10: because we've got signs of demand shifting back towards manufacturing now, 286 00:13:19,840 --> 00:13:23,840 Speaker 10: which is really doing quite well again. Services growth slipping slightly. 287 00:13:24,280 --> 00:13:26,440 Speaker 10: It looks like we're seeing some demand shift come back 288 00:13:26,480 --> 00:13:29,080 Speaker 10: from services towards goods. 289 00:13:29,640 --> 00:13:32,520 Speaker 2: So on the manufacturing side again, it came into fifty 290 00:13:32,520 --> 00:13:35,400 Speaker 2: two point five. The consensus was fifty two I'm sorry, 291 00:13:35,400 --> 00:13:38,000 Speaker 2: fifty one point eight, so well above consensus for this 292 00:13:38,080 --> 00:13:40,360 Speaker 2: month and a little bit higher than last month as well. 293 00:13:40,679 --> 00:13:44,040 Speaker 2: So is that simply manufacturer saying, hey, we've taken our 294 00:13:44,120 --> 00:13:46,880 Speaker 2: inventories down, it's time to start refilling and start making 295 00:13:46,920 --> 00:13:47,440 Speaker 2: stuff again. 296 00:13:48,720 --> 00:13:51,199 Speaker 10: No, it's not just that, it's it's overall demand levels 297 00:13:51,240 --> 00:13:53,520 Speaker 10: as well starting to rise, So the inventory cycle is 298 00:13:53,520 --> 00:13:57,200 Speaker 10: playing a part in that, but it's also final demand 299 00:13:57,400 --> 00:14:00,960 Speaker 10: sharing signs of picking up nice So it's a more 300 00:14:01,000 --> 00:14:04,640 Speaker 10: broad based picture than just turn in the stocking cycle. 301 00:14:05,280 --> 00:14:07,839 Speaker 10: And if you look beyond that headline PMI, if you 302 00:14:07,880 --> 00:14:09,560 Speaker 10: look at something like the output index, I mean that 303 00:14:09,600 --> 00:14:11,120 Speaker 10: was up fifty four point nine. 304 00:14:11,160 --> 00:14:13,480 Speaker 9: That's really quite a respectable reading. That's the highest since 305 00:14:13,520 --> 00:14:15,040 Speaker 9: May twenty twenty two. 306 00:14:15,440 --> 00:14:17,840 Speaker 10: So it really does thing look like production is starting 307 00:14:17,840 --> 00:14:19,360 Speaker 10: to turn around quite quite nicely. 308 00:14:19,400 --> 00:14:22,720 Speaker 4: Now, so here's my question then, I mean, let's get 309 00:14:22,720 --> 00:14:25,600 Speaker 4: to the raid cut situation in the second, but what 310 00:14:25,640 --> 00:14:29,000 Speaker 4: are prices when it comes to manufacturing and also services? 311 00:14:29,040 --> 00:14:30,680 Speaker 4: And that really does lead to the FED, right, because 312 00:14:30,720 --> 00:14:33,120 Speaker 4: if we get cuts, is it just sort of jumpstart 313 00:14:33,120 --> 00:14:35,120 Speaker 4: demand even more and then jumpstart infletion. 314 00:14:36,400 --> 00:14:40,040 Speaker 10: Well that's the kicker, yeah, because the price gauges are 315 00:14:40,040 --> 00:14:43,040 Speaker 10: on the rise again the manufacturing. So we've got two 316 00:14:43,080 --> 00:14:45,280 Speaker 10: lots of price gauges. They one is input costs and 317 00:14:45,320 --> 00:14:48,080 Speaker 10: one is their prices that they charge to customers for 318 00:14:48,200 --> 00:14:52,640 Speaker 10: manufacturing series. All those gauges rose in March coming and 319 00:14:52,680 --> 00:14:55,320 Speaker 10: say they're costs a rising because of increasing wages as 320 00:14:55,360 --> 00:14:58,320 Speaker 10: well as the oil and gas prices starting to come 321 00:14:58,360 --> 00:15:02,720 Speaker 10: through hitting costs is well, so they're passed these on 322 00:15:02,760 --> 00:15:05,560 Speaker 10: to their customers. So rates the selling price inflation they 323 00:15:05,600 --> 00:15:08,800 Speaker 10: accelerated really quite sharply, in manufacturing at a thirteen month 324 00:15:08,920 --> 00:15:12,360 Speaker 10: high now and services at an eight month high now. 325 00:15:12,520 --> 00:15:16,320 Speaker 10: The peer this overall gauge of selling price inflation is 326 00:15:16,360 --> 00:15:18,120 Speaker 10: around the highest for a year now. It's done a 327 00:15:18,200 --> 00:15:21,920 Speaker 10: good job of anticipating where CPI is going to go, 328 00:15:22,440 --> 00:15:25,080 Speaker 10: and it tracked the upturning the downturn through the pandemic 329 00:15:25,160 --> 00:15:28,720 Speaker 10: really quite nicely. And this latest reading means that having 330 00:15:28,800 --> 00:15:31,600 Speaker 10: come down to sort of closed store maybe even passing 331 00:15:31,680 --> 00:15:34,800 Speaker 10: two percent target, you're climbing back up to a sort 332 00:15:34,800 --> 00:15:37,000 Speaker 10: of four percent rate again with these numbers. 333 00:15:37,360 --> 00:15:39,320 Speaker 2: Hey, Chris, based upon the data that you guys see, 334 00:15:39,360 --> 00:15:42,720 Speaker 2: do you feel like this recent I guess pick up 335 00:15:42,760 --> 00:15:43,320 Speaker 2: an inflation? 336 00:15:43,560 --> 00:15:46,240 Speaker 5: Is it short term? Is it just a blip? 337 00:15:46,360 --> 00:15:49,240 Speaker 2: Or is it maybe something a little bit more longer term? 338 00:15:49,720 --> 00:15:51,720 Speaker 10: But there's a lot of speculation, isn't there that there 339 00:15:51,800 --> 00:15:55,440 Speaker 10: might be some seasonality creeping into inflation numbers. At the moment, 340 00:15:56,120 --> 00:16:00,960 Speaker 10: it's too early to say, is the honest answer. We've 341 00:16:01,000 --> 00:16:04,840 Speaker 10: seen gas prices come up and the oil price come up. 342 00:16:04,920 --> 00:16:08,200 Speaker 10: That's feeding through. So it's fairly obvious where that's coming from. 343 00:16:08,720 --> 00:16:12,600 Speaker 10: The wage growth. I mean that that's still being passed 344 00:16:12,640 --> 00:16:14,520 Speaker 10: through now that The hope is, of course, and this 345 00:16:14,560 --> 00:16:17,280 Speaker 10: applies to the other central backs as well as the FED, 346 00:16:17,840 --> 00:16:21,360 Speaker 10: is that as you get your headline inflation numbers come down, 347 00:16:21,600 --> 00:16:25,120 Speaker 10: then that feed through to wake away weaker wage negotiations. 348 00:16:25,280 --> 00:16:26,440 Speaker 10: So there's always going to be a bit of a 349 00:16:26,480 --> 00:16:29,040 Speaker 10: lag there. So what's hoped is that this little up 350 00:16:29,080 --> 00:16:30,560 Speaker 10: to him we've got is still a bit of that 351 00:16:30,680 --> 00:16:34,800 Speaker 10: lag feeding through and as the year goes on, this, 352 00:16:34,960 --> 00:16:38,360 Speaker 10: as we move into the summer, hopefully you'll see those 353 00:16:38,400 --> 00:16:39,440 Speaker 10: wage day to come down. 354 00:16:39,560 --> 00:16:39,720 Speaker 6: Yep. 355 00:16:39,800 --> 00:16:41,520 Speaker 5: Excellent, Chris, thanks so much for jumping on with us. 356 00:16:41,520 --> 00:16:42,120 Speaker 5: Really appreciated. 357 00:16:42,200 --> 00:16:46,200 Speaker 2: Chris Williamson, chief business economist at SMP Global Market Intelligence, 358 00:16:46,280 --> 00:16:47,600 Speaker 2: joining us from London via zoom. 359 00:16:48,920 --> 00:16:52,800 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 360 00:16:52,880 --> 00:16:55,960 Speaker 1: weekdays at ten am Eastern on Affle Card, playing Enroud 361 00:16:56,000 --> 00:16:59,080 Speaker 1: Otto with the Bloomberg Business app. Listen on demand wherever 362 00:16:59,120 --> 00:17:02,880 Speaker 1: you get your podcast, or watch just Live on you too. 363 00:17:04,320 --> 00:17:05,840 Speaker 4: I want to get more insight here and sort of 364 00:17:05,880 --> 00:17:08,080 Speaker 4: how you manage the momentum, how you manage the market. 365 00:17:08,160 --> 00:17:11,000 Speaker 4: Nicole Web the senior vice president financial advisor at Wealth 366 00:17:11,080 --> 00:17:14,760 Speaker 4: Enhancement Group, and she joins us, now, okay, you can't 367 00:17:14,760 --> 00:17:17,280 Speaker 4: get in the way of this momentum, right, No, can't 368 00:17:17,359 --> 00:17:20,640 Speaker 4: do You buy into it? You do even at these levels. 369 00:17:20,760 --> 00:17:23,800 Speaker 6: I'm sorry, but you do. And I think this is 370 00:17:23,840 --> 00:17:27,280 Speaker 6: where it's really It's an interesting moment and it's supported 371 00:17:27,359 --> 00:17:29,440 Speaker 6: by the breath we're seeing in the rustle, It's supported 372 00:17:29,440 --> 00:17:32,760 Speaker 6: by credit spreads, it is supported by earnings. You take 373 00:17:32,800 --> 00:17:35,199 Speaker 6: fed off the table, you still can look at earnings 374 00:17:35,200 --> 00:17:39,360 Speaker 6: and profitability. And then you look at the forefront of digitization, 375 00:17:39,520 --> 00:17:43,719 Speaker 6: and you mentioned Micron, and here we see just so 376 00:17:43,960 --> 00:17:47,040 Speaker 6: clearly the thirst, the hunger for the next leg of AI. 377 00:17:47,720 --> 00:17:52,840 Speaker 6: And it's interesting so storage speed all of these things. 378 00:17:53,160 --> 00:17:54,879 Speaker 2: And then we and then we had, you know, for 379 00:17:54,920 --> 00:17:57,119 Speaker 2: a lot of people. Was another confirming piece of data. 380 00:17:57,960 --> 00:18:01,359 Speaker 2: Astera Labs comes out public yesterday. The stock just Rips 381 00:18:01,480 --> 00:18:04,160 Speaker 2: was up seventy percent yesterday on's first day of trading. 382 00:18:04,160 --> 00:18:06,880 Speaker 2: It's some of the nineteen percent today. Again, I guess 383 00:18:06,880 --> 00:18:10,080 Speaker 2: you could say, well, it's a cour like one of 384 00:18:10,160 --> 00:18:13,560 Speaker 2: our reporters sources said, well, of course this sing ripped. 385 00:18:13,640 --> 00:18:15,960 Speaker 5: My mother could have taken this public, that's how good 386 00:18:16,000 --> 00:18:17,000 Speaker 5: a story it was. 387 00:18:17,119 --> 00:18:19,400 Speaker 2: But still it's a great performance. We're going to see 388 00:18:19,440 --> 00:18:22,600 Speaker 2: with Reddit see how that trades today. But the IPO 389 00:18:22,640 --> 00:18:25,160 Speaker 2: market is maybe a little bit of a confirming factor here. 390 00:18:25,280 --> 00:18:27,399 Speaker 6: Yeah, I think the IPO market is really interesting, and 391 00:18:27,400 --> 00:18:31,000 Speaker 6: I think there's going to be differences in the names 392 00:18:31,000 --> 00:18:33,359 Speaker 6: that are brought forward. You know, the one thing I 393 00:18:33,400 --> 00:18:35,480 Speaker 6: want to go back to when we think about going 394 00:18:35,520 --> 00:18:38,399 Speaker 6: down the cap spectrum, when we think about investors taking 395 00:18:38,440 --> 00:18:41,280 Speaker 6: bets maybe on names that they don't know at the 396 00:18:41,320 --> 00:18:44,679 Speaker 6: headline level. In the same way, what we also know 397 00:18:44,920 --> 00:18:47,760 Speaker 6: intrinsically is that there's been trimming of positions. If you 398 00:18:47,840 --> 00:18:50,760 Speaker 6: had a META in your portfolio and it was three percent, 399 00:18:50,840 --> 00:18:53,000 Speaker 6: it's now nine percent, you trimmed that back to five. 400 00:18:53,040 --> 00:18:55,520 Speaker 6: And so you're hearing some of these mega tech names 401 00:18:55,960 --> 00:18:59,320 Speaker 6: likened to being atm machines for reinvestment, and so you 402 00:18:59,359 --> 00:19:01,640 Speaker 6: know the amount of cash that was on the sidelines, 403 00:19:01,920 --> 00:19:04,359 Speaker 6: and then the trimming of positions, and so you're seeing 404 00:19:04,400 --> 00:19:07,720 Speaker 6: some of this down the cap weighting momentum trade and 405 00:19:07,800 --> 00:19:09,680 Speaker 6: even that little bit of fade out that we're seeing 406 00:19:09,720 --> 00:19:12,359 Speaker 6: in momentum around semis and so when we look to 407 00:19:12,400 --> 00:19:14,960 Speaker 6: the IPO market, you know, redd, it's going to be 408 00:19:15,000 --> 00:19:17,960 Speaker 6: a really interesting test case and that it's not profitable. 409 00:19:18,080 --> 00:19:20,800 Speaker 6: It's been a round for a long time. What is 410 00:19:20,840 --> 00:19:24,000 Speaker 6: that narrative though? About the deep language that they own, 411 00:19:24,080 --> 00:19:26,840 Speaker 6: what kind of learning? What can you translate that into? 412 00:19:27,160 --> 00:19:28,919 Speaker 6: And I think that story is yet to unfold, but 413 00:19:28,960 --> 00:19:31,639 Speaker 6: we have to see kind of what enthusiasm comes from that. 414 00:19:31,720 --> 00:19:32,280 Speaker 5: Now we're just. 415 00:19:32,240 --> 00:19:35,080 Speaker 4: Talking about like Reddit being a third derivative AI play 416 00:19:35,160 --> 00:19:38,000 Speaker 4: because of the language models needed, So that sort of 417 00:19:38,119 --> 00:19:40,760 Speaker 4: is different than just hey, your unprofitable social media company 418 00:19:40,800 --> 00:19:43,280 Speaker 4: at the end of the day. Okay, so help me 419 00:19:43,359 --> 00:19:47,840 Speaker 4: understand what the next catalyst is going to be. Deutsche 420 00:19:47,840 --> 00:19:50,240 Speaker 4: Bank was talking over the weekend that you know, maybe 421 00:19:50,240 --> 00:19:52,760 Speaker 4: we priced in sort of higher growth and higher inflation, 422 00:19:52,880 --> 00:19:54,879 Speaker 4: higher for longer rates now, so it's really going to 423 00:19:54,880 --> 00:19:57,080 Speaker 4: be the growth narrative that leads. Others are saying no, 424 00:19:57,200 --> 00:19:59,639 Speaker 4: straight up fundamental, straight up profit, like what is going 425 00:19:59,680 --> 00:20:00,560 Speaker 4: to be the now? 426 00:20:00,760 --> 00:20:04,680 Speaker 6: Yeah, I think that those two things are intrinsically true. 427 00:20:04,760 --> 00:20:08,840 Speaker 6: We went from a FED pivot. I mean it was 428 00:20:08,880 --> 00:20:10,320 Speaker 6: called a pivot. I don't know if it was really 429 00:20:10,359 --> 00:20:13,600 Speaker 6: the pivot, but back in December a little bit, the 430 00:20:13,680 --> 00:20:16,399 Speaker 6: wording's a little strong for me. Then we went into 431 00:20:16,720 --> 00:20:19,080 Speaker 6: the momentum of AI and then all of that was 432 00:20:19,119 --> 00:20:23,240 Speaker 6: supported by earnings, by GDP revisions to the upside above 433 00:20:23,320 --> 00:20:27,000 Speaker 6: trend growth expectation. You have Viisa who just continues to say, 434 00:20:27,000 --> 00:20:30,600 Speaker 6: the consumer actually looks pretty good. When we put all 435 00:20:30,640 --> 00:20:34,720 Speaker 6: of that together, what you get is just this fundamental 436 00:20:34,800 --> 00:20:39,040 Speaker 6: belief that companies will continue to be profitable, that earnings 437 00:20:39,040 --> 00:20:42,000 Speaker 6: will be there. We were so unsure of the ten 438 00:20:42,080 --> 00:20:45,280 Speaker 6: percent earnings per share growth that was baked into the 439 00:20:45,320 --> 00:20:46,679 Speaker 6: SMP at the beginning of the year, and now that 440 00:20:46,800 --> 00:20:50,119 Speaker 6: sounds likely, and so you have kind of all of 441 00:20:50,160 --> 00:20:52,879 Speaker 6: this momentum. The more interesting thing, I think is what 442 00:20:53,040 --> 00:20:55,600 Speaker 6: is that catalyst to the first pullback here? And then 443 00:20:55,720 --> 00:20:58,800 Speaker 6: is the pullback of a self fulfilling prophecy for everybody 444 00:20:58,800 --> 00:21:00,919 Speaker 6: who's been sitting on the side lines feeling like they 445 00:21:01,080 --> 00:21:04,080 Speaker 6: missed the opportunity, and so it's short lived, And you know, 446 00:21:04,119 --> 00:21:06,760 Speaker 6: I think that's where I continue to say the same thing. 447 00:21:07,040 --> 00:21:09,280 Speaker 6: I'm grateful to not be a trader in this market. 448 00:21:09,359 --> 00:21:11,520 Speaker 6: I am grateful to be an investor in this market. 449 00:21:11,560 --> 00:21:15,480 Speaker 6: This market has a lot of opportunity for investors. 450 00:21:15,960 --> 00:21:19,639 Speaker 2: One of the names is really missing out, arguably on 451 00:21:19,680 --> 00:21:22,480 Speaker 2: the AI plays Apple, Yes, and that's one of the 452 00:21:22,480 --> 00:21:25,480 Speaker 2: big issues. I know they're having a developer conference in June, 453 00:21:25,520 --> 00:21:28,240 Speaker 2: but what's your take on Apple? 454 00:21:28,280 --> 00:21:28,480 Speaker 1: Here? 455 00:21:28,560 --> 00:21:32,919 Speaker 5: Have they missed AI? I can't imagine, but they're certainly 456 00:21:33,000 --> 00:21:33,800 Speaker 5: late to it. I guess. 457 00:21:33,840 --> 00:21:37,360 Speaker 6: Okay, So I'm not everybody's favorite in our investment committee 458 00:21:37,359 --> 00:21:40,199 Speaker 6: meetings right now because I am a bullish on Apple. 459 00:21:40,359 --> 00:21:43,320 Speaker 6: I mean I find a lot. I think they're playing 460 00:21:43,359 --> 00:21:46,159 Speaker 6: chessnut checkers. I mean not to use that analogy, but 461 00:21:46,640 --> 00:21:49,800 Speaker 6: when you step away from the production of cars, but 462 00:21:49,920 --> 00:21:52,119 Speaker 6: you know, below the surface, there's a lot coming with 463 00:21:52,160 --> 00:21:55,800 Speaker 6: Apple car play that's interesting to me. What if it 464 00:21:55,880 --> 00:21:58,680 Speaker 6: is more of a technology development and watching the likes 465 00:21:58,720 --> 00:22:03,000 Speaker 6: of Tesla being there's just nothing positive that's coming out 466 00:22:03,000 --> 00:22:05,840 Speaker 6: of right now. The narrative around Tesla is, oh, should 467 00:22:05,840 --> 00:22:08,639 Speaker 6: we price them like a car company? Right because you know, 468 00:22:08,640 --> 00:22:11,240 Speaker 6: what if you spin off robotics. When I think about 469 00:22:11,320 --> 00:22:14,479 Speaker 6: the Apple just saying we're going to use Gemini, well 470 00:22:14,520 --> 00:22:17,520 Speaker 6: that's natural. You were using chrome already. I already think 471 00:22:17,560 --> 00:22:20,680 Speaker 6: it's interesting that with Gmail we have so much deep 472 00:22:20,800 --> 00:22:25,240 Speaker 6: language learning accessible to Google. So you know, for me, 473 00:22:25,560 --> 00:22:28,240 Speaker 6: I think the next leg of AI has the potential 474 00:22:28,280 --> 00:22:32,639 Speaker 6: to really be the ISO operating platform, the hardware sales, 475 00:22:32,680 --> 00:22:35,680 Speaker 6: and the services infrastructure that goes hand in hand, because 476 00:22:35,720 --> 00:22:40,240 Speaker 6: if you continue to be the platform for application based technology, 477 00:22:40,440 --> 00:22:43,080 Speaker 6: then you're going to need the systems behind it to operate. 478 00:22:43,119 --> 00:22:46,199 Speaker 4: And the thing with Apple is, as we know, the 479 00:22:46,200 --> 00:22:48,280 Speaker 4: car thing aside is that they get into all of 480 00:22:48,320 --> 00:22:50,240 Speaker 4: this stuff, they just get in late. They want to 481 00:22:50,240 --> 00:22:52,080 Speaker 4: see what everyone else is doing, they want to see 482 00:22:52,119 --> 00:22:54,119 Speaker 4: the best model, and then they're going to spend money 483 00:22:54,160 --> 00:22:57,359 Speaker 4: to do it. So would you be buying Apple as 484 00:22:57,359 --> 00:23:00,720 Speaker 4: a valuation play looking ahead to them, or it is 485 00:23:00,760 --> 00:23:02,320 Speaker 4: by Apple because you know why not? 486 00:23:02,359 --> 00:23:04,000 Speaker 6: We all have iPhones you got to keep it. I 487 00:23:04,000 --> 00:23:06,000 Speaker 6: think you can buy Apple for both of those reasons. 488 00:23:06,280 --> 00:23:08,360 Speaker 6: Where it sits today. It's not historically cheap and it's 489 00:23:08,400 --> 00:23:13,320 Speaker 6: not historically expensive. And I don't think that the last 490 00:23:13,400 --> 00:23:15,080 Speaker 6: launch of the iPhone. And I say this as an 491 00:23:15,040 --> 00:23:16,920 Speaker 6: eye statement because again there's a lot of people out 492 00:23:16,920 --> 00:23:19,400 Speaker 6: there who wouldn't be of consensus with this, but they 493 00:23:19,480 --> 00:23:22,520 Speaker 6: launched the last iPhone to buy themselves time. I believe 494 00:23:22,560 --> 00:23:25,360 Speaker 6: that the next iterations of iPhone are meaningful and they 495 00:23:25,440 --> 00:23:28,800 Speaker 6: drive sales, and they drive sales globally because there will 496 00:23:28,800 --> 00:23:30,719 Speaker 6: need to be a platform. When we look at some 497 00:23:30,760 --> 00:23:32,920 Speaker 6: of these analyst reports out of Meadow, or we hear 498 00:23:33,280 --> 00:23:36,080 Speaker 6: what they have in store when they build upon the 499 00:23:36,160 --> 00:23:40,520 Speaker 6: meta platforms, they want to bring in applications that generate revenue, 500 00:23:40,720 --> 00:23:43,719 Speaker 6: where people can buy add ons to lay over AI. 501 00:23:44,320 --> 00:23:48,440 Speaker 6: All of that has to be supported speed, memory, battery life. 502 00:23:48,480 --> 00:23:50,280 Speaker 6: I mean, you can go on and on, and Apple 503 00:23:50,640 --> 00:23:53,119 Speaker 6: is the products platform for that. 504 00:23:53,520 --> 00:23:55,240 Speaker 4: Are you worried about the China exposure though? 505 00:23:56,040 --> 00:23:59,320 Speaker 6: I think the China exposure continues to be incredibly opaque 506 00:23:59,359 --> 00:24:03,680 Speaker 6: and slightly confusing. And I believe that that the read 507 00:24:03,720 --> 00:24:07,560 Speaker 6: through from China affects businesses across the board always. But 508 00:24:07,600 --> 00:24:10,600 Speaker 6: I wouldn't say that's a reason to not invest in Apple. 509 00:24:11,200 --> 00:24:11,640 Speaker 5: Interesting. 510 00:24:11,720 --> 00:24:15,080 Speaker 2: How about Intel. Let's talk about you know tech one point, 511 00:24:15,119 --> 00:24:15,880 Speaker 2: oh if you will. 512 00:24:16,119 --> 00:24:21,119 Speaker 6: Yeah, Intel and on shoring production of chips is also 513 00:24:22,880 --> 00:24:26,840 Speaker 6: feels innately necessary, and government support to bring us up 514 00:24:26,880 --> 00:24:31,600 Speaker 6: to speed to you know, propel that forward quickly seems 515 00:24:31,600 --> 00:24:34,240 Speaker 6: also necessary. You had the CEO of Navidia a few 516 00:24:34,240 --> 00:24:36,200 Speaker 6: weeks ago, what was it three weeks ago, now already 517 00:24:36,359 --> 00:24:40,760 Speaker 6: sitting in Dubai saying we all countries need to be producer, 518 00:24:40,920 --> 00:24:43,359 Speaker 6: sovereign producers of chips. I mean, it is just going 519 00:24:43,400 --> 00:24:46,720 Speaker 6: to be that necessary, you know. I think there was 520 00:24:46,760 --> 00:24:49,760 Speaker 6: some confusion over some money going to Taiwan Semi, some 521 00:24:49,840 --> 00:24:52,280 Speaker 6: money going to Samsung, But at the end of the day, 522 00:24:52,320 --> 00:24:56,240 Speaker 6: to onshore that piece of supply, it's going to take 523 00:24:56,280 --> 00:24:58,879 Speaker 6: three to four years, and so we also need to 524 00:24:58,960 --> 00:25:02,800 Speaker 6: continue to have access to the production today. 525 00:25:02,880 --> 00:25:05,480 Speaker 2: I mean, just on Apple, it's news crossing tape. US 526 00:25:05,520 --> 00:25:09,520 Speaker 2: Justice Apartment sues Apple an antitrust case over iPhone thirty seconds. 527 00:25:09,520 --> 00:25:10,760 Speaker 5: How do you kind of factor that in? 528 00:25:11,200 --> 00:25:14,880 Speaker 6: I think that it's like it's it's a constant. I mean, 529 00:25:15,080 --> 00:25:17,760 Speaker 6: the anti trust is a constant, especially with all of 530 00:25:17,800 --> 00:25:22,760 Speaker 6: these big technology names. How you think about that. You 531 00:25:22,800 --> 00:25:24,520 Speaker 6: don't want the big to get so big that they 532 00:25:24,520 --> 00:25:27,639 Speaker 6: can own everything. You also don't want to over respond 533 00:25:27,760 --> 00:25:30,720 Speaker 6: to any of these issues because they will continue to 534 00:25:30,760 --> 00:25:34,960 Speaker 6: forge forward, and so in that way, I think, you know, 535 00:25:35,040 --> 00:25:37,920 Speaker 6: to an over response, one looks at it as again 536 00:25:38,480 --> 00:25:42,000 Speaker 6: not a trader, but an investor, perhaps an opportunity to 537 00:25:42,040 --> 00:25:42,760 Speaker 6: think about an. 538 00:25:42,760 --> 00:25:46,400 Speaker 4: Entry point great stuff. Really appreciate that, Nicole Webb, Senior 539 00:25:46,520 --> 00:25:49,479 Speaker 4: vice president, Financial advisor at Wealth Enhancement Group. And to 540 00:25:49,480 --> 00:25:51,919 Speaker 4: the point of like say, for example, TikTok, right, like 541 00:25:51,960 --> 00:25:54,320 Speaker 4: if you have to divest it, who's buying it? 542 00:25:54,560 --> 00:25:55,040 Speaker 5: Exactly? 543 00:25:55,320 --> 00:25:57,280 Speaker 4: I mean aside from anution, it's going to be a 544 00:25:57,280 --> 00:25:59,240 Speaker 4: tech company, So you're gonna let that go through. And 545 00:25:59,280 --> 00:26:01,200 Speaker 4: then how does that make? So there you know, sometimes 546 00:26:01,240 --> 00:26:02,840 Speaker 4: one plus one does ant equal five? 547 00:26:02,960 --> 00:26:05,160 Speaker 2: Yep, and interesting to see. I mean, Applestock is trading 548 00:26:05,160 --> 00:26:07,199 Speaker 2: off a little bit here. It's been under pressure all 549 00:26:07,280 --> 00:26:09,479 Speaker 2: year for a variety of reasons. As Nicole was, youre 550 00:26:09,520 --> 00:26:11,760 Speaker 2: just mentioning here, but it's Apple, I. 551 00:26:11,760 --> 00:26:12,520 Speaker 4: Don't know exactly. 552 00:26:12,760 --> 00:26:19,360 Speaker 1: Example, you're listening to the Bloomberg Intelligence Podcast. Catch us 553 00:26:19,400 --> 00:26:22,520 Speaker 1: live weekdays at ten am Eastern on Apple car Play 554 00:26:22,600 --> 00:26:25,399 Speaker 1: and Android Auto with the Bloomberg Business app. You can 555 00:26:25,440 --> 00:26:28,679 Speaker 1: also listen live on Amazon Alexa from our flagship New 556 00:26:28,760 --> 00:26:32,399 Speaker 1: York station. Just say Alexa play Bloomberg eleven thirty. 557 00:26:34,200 --> 00:26:36,160 Speaker 4: Let's go to the ag space. So if you eat food, 558 00:26:36,480 --> 00:26:39,119 Speaker 4: you want to know about this company. This company is Agco. 559 00:26:39,240 --> 00:26:41,560 Speaker 4: It's trading up by about four tenths of one percent. 560 00:26:41,600 --> 00:26:44,640 Speaker 4: It's about one hundred and eighteen dollars a share. So 561 00:26:44,840 --> 00:26:49,640 Speaker 4: it's an American agricultural machinery manufactured company. So it's basically, 562 00:26:49,680 --> 00:26:51,720 Speaker 4: if you're a farmer and you need stuff, you're going 563 00:26:51,760 --> 00:26:55,080 Speaker 4: to go to the companies like AGCO, Deer that kind 564 00:26:55,119 --> 00:26:59,720 Speaker 4: of thing. It's a huge EG equipment industry, and farmers 565 00:26:59,760 --> 00:27:03,119 Speaker 4: are it's so important, particularly as we grow the population 566 00:27:03,240 --> 00:27:05,640 Speaker 4: by billions. Everyone's going to need to eat. So let's 567 00:27:05,640 --> 00:27:08,280 Speaker 4: talk to the CEO of ag CO joining US now, 568 00:27:08,400 --> 00:27:10,879 Speaker 4: Eric han Sotia. He joins us. Eric, it's great to 569 00:27:10,880 --> 00:27:13,240 Speaker 4: get your perspective and everything. So I just want to 570 00:27:13,240 --> 00:27:17,160 Speaker 4: start macro. Usually, higher rates are not good for farmers. 571 00:27:17,160 --> 00:27:19,119 Speaker 4: Plus it's been a tough year if you've been a 572 00:27:19,119 --> 00:27:20,120 Speaker 4: farmer house business. 573 00:27:22,280 --> 00:27:25,440 Speaker 11: Well, we've had two or three extremely strong years over 574 00:27:25,440 --> 00:27:27,600 Speaker 11: the last three years. It's cooling a little bit in 575 00:27:27,640 --> 00:27:30,520 Speaker 11: twenty twenty four. You know, an ag is not so 576 00:27:30,640 --> 00:27:33,600 Speaker 11: much tied to general GDP or interest rates. It's more 577 00:27:33,640 --> 00:27:35,760 Speaker 11: tied to how much grain is in the world and 578 00:27:35,840 --> 00:27:39,399 Speaker 11: grain prices, and that's cooled off a little bit. Interest 579 00:27:39,440 --> 00:27:42,000 Speaker 11: higher interest rates is a bit of a headwind because 580 00:27:42,320 --> 00:27:45,159 Speaker 11: most of these farmers finance their equipment and that costs 581 00:27:45,280 --> 00:27:46,919 Speaker 11: a little bit more to when they want to finance. 582 00:27:46,960 --> 00:27:48,199 Speaker 9: So it's a little bit of a hitd wind, but 583 00:27:48,240 --> 00:27:49,480 Speaker 9: not the biggest issue. 584 00:27:49,560 --> 00:27:51,960 Speaker 2: All right, Eric, I know you guys are involved right 585 00:27:51,960 --> 00:27:54,800 Speaker 2: now and in acquiring an eighty five percent interest in Trimble. 586 00:27:54,840 --> 00:27:57,159 Speaker 2: Tell us what Trimble is, tell us what this deal is. 587 00:27:57,280 --> 00:27:58,399 Speaker 5: Why are you doing it? 588 00:27:59,760 --> 00:27:59,960 Speaker 3: Yeah? 589 00:28:00,080 --> 00:28:01,960 Speaker 11: Yeah, Well you know, if you start with our vision 590 00:28:01,960 --> 00:28:04,359 Speaker 11: of our company, it's to become the trusted partner for 591 00:28:04,520 --> 00:28:08,119 Speaker 11: industry leading smart farming solutions. And essentially what that means 592 00:28:08,200 --> 00:28:11,160 Speaker 11: is machines that have sensors on them that can understand 593 00:28:11,160 --> 00:28:14,040 Speaker 11: their environment, see changes in the soil or the crop, 594 00:28:14,440 --> 00:28:18,280 Speaker 11: and then make onboard calculations, often using AI engines, to 595 00:28:18,359 --> 00:28:21,760 Speaker 11: be able to optimize their own performance. We invest in 596 00:28:21,760 --> 00:28:24,159 Speaker 11: six tech companies over the last several years, increased our 597 00:28:24,200 --> 00:28:27,200 Speaker 11: engineering budget for by sixty percent since I've been leading 598 00:28:27,200 --> 00:28:30,320 Speaker 11: the company, and so we've been gaining a lot of momentum. 599 00:28:30,680 --> 00:28:33,760 Speaker 11: But then Rob Painter, the CEO of Trimble, and I 600 00:28:33,760 --> 00:28:34,760 Speaker 11: had this notion of. 601 00:28:34,760 --> 00:28:36,040 Speaker 9: We could be better together. 602 00:28:36,600 --> 00:28:39,840 Speaker 11: He's got the very best egg tech team that we 603 00:28:39,880 --> 00:28:42,000 Speaker 11: would be able to add to our team. And so 604 00:28:42,080 --> 00:28:46,040 Speaker 11: the combination of that group coming together with our ECO 605 00:28:46,080 --> 00:28:49,280 Speaker 11: group is going to rapidly accelerate our ability to deliver 606 00:28:49,360 --> 00:28:54,920 Speaker 11: solutions for farmers. Machines can do more for themselves, increase 607 00:28:55,000 --> 00:28:56,240 Speaker 11: yields and reduce costs. 608 00:28:56,640 --> 00:28:59,040 Speaker 4: Eric, So, okay, Eric, are you still an Egg company? 609 00:28:59,120 --> 00:29:00,760 Speaker 4: Are you a tech? Egg? A tech company? And I 610 00:29:00,840 --> 00:29:02,360 Speaker 4: know you're going to say you're an agg tech company, 611 00:29:02,400 --> 00:29:05,560 Speaker 4: but like seriously, like where should the valuation be? 612 00:29:07,040 --> 00:29:10,440 Speaker 11: Absolutely for this this type of our work, We're absolutely 613 00:29:10,480 --> 00:29:11,120 Speaker 11: a tech company. 614 00:29:11,520 --> 00:29:13,080 Speaker 9: Uh, there's no question about that. 615 00:29:13,080 --> 00:29:14,960 Speaker 11: That's where all of our investment is, That's where our 616 00:29:15,000 --> 00:29:18,240 Speaker 11: new hiring is, that's where our focus is. Probably two 617 00:29:18,280 --> 00:29:20,920 Speaker 11: thirds of our engineering budget is now on either smart 618 00:29:20,960 --> 00:29:22,880 Speaker 11: machines or clean energy solutions. 619 00:29:23,880 --> 00:29:28,480 Speaker 2: That's interesting, Eric, do you actually manufacture this the equipment 620 00:29:28,560 --> 00:29:30,640 Speaker 2: or is this your a technology that you licensed out 621 00:29:30,640 --> 00:29:31,480 Speaker 2: to other manufacturers? 622 00:29:31,480 --> 00:29:33,320 Speaker 5: How does that work? 623 00:29:34,560 --> 00:29:35,800 Speaker 9: So this is an interesting point. 624 00:29:35,920 --> 00:29:39,160 Speaker 11: We build our own machines, so tractors, combines, sprayers, planters, 625 00:29:39,200 --> 00:29:41,080 Speaker 11: and those types of things. So we provide all the 626 00:29:41,120 --> 00:29:44,080 Speaker 11: machines the farmer needs to do their farming all the 627 00:29:44,120 --> 00:29:45,200 Speaker 11: way through the cropping cycle. 628 00:29:45,600 --> 00:29:46,760 Speaker 9: That's what you would expect. 629 00:29:46,920 --> 00:29:49,360 Speaker 11: The thing that's unique about ag CO is we've also 630 00:29:49,400 --> 00:29:54,520 Speaker 11: got this whole tech division that sells retrofit technology modules 631 00:29:54,680 --> 00:29:57,360 Speaker 11: onto an existing machine, maybe a five year old planter, 632 00:29:58,320 --> 00:30:01,240 Speaker 11: and it brings that capability of that pl sprayer or 633 00:30:01,600 --> 00:30:04,160 Speaker 11: combine from where it was from a dumb machine up 634 00:30:04,160 --> 00:30:06,760 Speaker 11: to a smart machine. And the other unique thing about 635 00:30:06,760 --> 00:30:09,240 Speaker 11: that is that we do it on all brands of equipment, 636 00:30:09,520 --> 00:30:11,560 Speaker 11: So we don't just do it on customers that bought 637 00:30:11,600 --> 00:30:13,640 Speaker 11: from us in the past. We'll do it on John 638 00:30:13,680 --> 00:30:15,840 Speaker 11: to the equipment case, new Holid equipment, others. 639 00:30:15,960 --> 00:30:17,640 Speaker 9: You know, we do it for every farmer. 640 00:30:17,680 --> 00:30:19,640 Speaker 11: We want to be the most farmer focused company in 641 00:30:19,680 --> 00:30:22,040 Speaker 11: the industry, so we want to serve all farmers either 642 00:30:22,040 --> 00:30:24,920 Speaker 11: with buying new from us or upgrading their existing machines 643 00:30:24,960 --> 00:30:26,320 Speaker 11: with technology from us. 644 00:30:26,320 --> 00:30:28,080 Speaker 4: Interesting, so it's like a different way of being a 645 00:30:28,120 --> 00:30:32,360 Speaker 4: services company in essence to farmers. So straight up, so 646 00:30:33,000 --> 00:30:36,760 Speaker 4: what's demand like, Like, what's your backlog look like, how's demand, 647 00:30:37,560 --> 00:30:40,680 Speaker 4: what's your visibility? 648 00:30:40,840 --> 00:30:43,920 Speaker 11: And the general machinery business demand is cooling. We had 649 00:30:44,160 --> 00:30:46,480 Speaker 11: incredible demand over these last two or three years. We've 650 00:30:46,480 --> 00:30:48,440 Speaker 11: been running to try and catch up to it had 651 00:30:48,520 --> 00:30:52,280 Speaker 11: actually unhealthy long back orders for the last. 652 00:30:52,040 --> 00:30:52,520 Speaker 9: Couple of years. 653 00:30:52,800 --> 00:30:55,680 Speaker 11: It's still higher than we would target, but it's coming 654 00:30:55,760 --> 00:30:58,920 Speaker 11: back down to normal back order levels. You know, it's 655 00:30:59,000 --> 00:31:01,840 Speaker 11: the frothiness is is coming out. So you know, in 656 00:31:01,880 --> 00:31:04,960 Speaker 11: that regard on the machinery business, it's cooling and getting 657 00:31:05,040 --> 00:31:09,240 Speaker 11: back to a more normal backlog level. On the technology business, though, 658 00:31:09,320 --> 00:31:12,600 Speaker 11: because of this retrofit opportunity, there's a lot of farmers 659 00:31:12,640 --> 00:31:14,360 Speaker 11: that in this kind of a year where they're not 660 00:31:14,360 --> 00:31:16,360 Speaker 11: going to buy a big machine, they may say, you 661 00:31:16,440 --> 00:31:18,800 Speaker 11: know what, I'll upgrade my existing machine with new technology 662 00:31:18,840 --> 00:31:22,360 Speaker 11: to have that capability. So our retrofit business continues to grow, 663 00:31:22,400 --> 00:31:23,720 Speaker 11: We're going to have a growing ear even though the 664 00:31:23,720 --> 00:31:24,560 Speaker 11: industry is cooling. 665 00:31:25,360 --> 00:31:29,160 Speaker 2: Give us a sense just kind of how receptive are 666 00:31:29,200 --> 00:31:32,000 Speaker 2: your customers, the farmer out there, how receptive are they 667 00:31:32,360 --> 00:31:33,280 Speaker 2: to technology. 668 00:31:35,280 --> 00:31:38,120 Speaker 11: Well, the whole thing they don't want to go out 669 00:31:38,120 --> 00:31:39,760 Speaker 11: and buy a technology, but they want to do is 670 00:31:39,760 --> 00:31:43,080 Speaker 11: buy an easier solution. So like, for example, on our planter, 671 00:31:43,120 --> 00:31:45,120 Speaker 11: we've got this thing called smart Firmer. It's a sensor 672 00:31:45,160 --> 00:31:47,800 Speaker 11: that runs on the planter through the soil. It uses 673 00:31:47,840 --> 00:31:51,880 Speaker 11: AI measures soil properties and it can automatically for the farmer. Then, 674 00:31:52,040 --> 00:31:54,920 Speaker 11: since when the planter is running through higher organic matter, 675 00:31:54,920 --> 00:31:57,480 Speaker 11: which means more higher fertility, and I'll tell the planter 676 00:31:57,600 --> 00:32:01,480 Speaker 11: plant more here or adjust the depthomatically to plant into moisture. 677 00:32:01,680 --> 00:32:03,800 Speaker 11: We're the only one that has that kind of capability. 678 00:32:04,000 --> 00:32:06,440 Speaker 11: And essentially that's what the farmer's buying. If buying a 679 00:32:06,480 --> 00:32:09,560 Speaker 11: new capability that does something automatically that improves their yield 680 00:32:09,960 --> 00:32:14,720 Speaker 11: and uses less inputs like seed, chemical, fertilizer, things like that. 681 00:32:15,160 --> 00:32:17,280 Speaker 11: Got a sprayer that uses vision systems they can see 682 00:32:17,280 --> 00:32:20,120 Speaker 11: the difference between a weed and the plant automatically only 683 00:32:20,160 --> 00:32:22,880 Speaker 11: spray the weed, not the plant, save seventy percent of 684 00:32:22,880 --> 00:32:25,560 Speaker 11: the chemical going across the field. That's what they're buying 685 00:32:25,640 --> 00:32:26,840 Speaker 11: and they're really excited about. 686 00:32:27,320 --> 00:32:30,040 Speaker 4: So Eric. In my day as a reporter, I have 687 00:32:30,160 --> 00:32:33,760 Speaker 4: definitely been on some farms, pig farms. I've done the 688 00:32:33,760 --> 00:32:36,560 Speaker 4: thing I have. I feel like if I asked any 689 00:32:36,560 --> 00:32:39,200 Speaker 4: of your peers, they would say something similar about, yes, 690 00:32:39,240 --> 00:32:41,400 Speaker 4: we provide this kind of technology to farmers now too. 691 00:32:41,400 --> 00:32:43,960 Speaker 4: It's much more of a tech industry than an egg industry. 692 00:32:45,080 --> 00:32:46,920 Speaker 4: Where do you differentiate. 693 00:32:48,120 --> 00:32:52,520 Speaker 11: This whole area of retrofit is where we differentiate on product. 694 00:32:52,960 --> 00:32:55,760 Speaker 11: So we have our machines. Fent is our brand that's 695 00:32:55,760 --> 00:32:57,640 Speaker 11: the best of the best. It's that the premium end 696 00:32:57,640 --> 00:33:00,320 Speaker 11: of the market. So we really feel like we're growing 697 00:33:00,360 --> 00:33:02,400 Speaker 11: that segment very fast in North America and South America 698 00:33:02,400 --> 00:33:05,120 Speaker 11: as we globalize it. But where we big time differentiate 699 00:33:05,680 --> 00:33:09,640 Speaker 11: is this retrofit upgradating existing people's machine of any brand 700 00:33:10,200 --> 00:33:13,080 Speaker 11: to have more capability. And then the second thing is 701 00:33:13,080 --> 00:33:14,960 Speaker 11: how we think about going to market. We just launched 702 00:33:14,960 --> 00:33:18,280 Speaker 11: what we call Farmer Core and we're shifting from Instead 703 00:33:18,280 --> 00:33:19,880 Speaker 11: of the farmer having to come into a brick and 704 00:33:19,920 --> 00:33:22,760 Speaker 11: mortar store all the time, we want to be able 705 00:33:22,760 --> 00:33:24,400 Speaker 11: to flip it on its ear one hundred and eighty 706 00:33:24,400 --> 00:33:28,520 Speaker 11: degrees and do everything on farm using digital tools remotely 707 00:33:28,560 --> 00:33:32,440 Speaker 11: monitoring the machines. We want to take all of the service, maintenance, repair, 708 00:33:32,520 --> 00:33:35,080 Speaker 11: all that attack activity out to the farm so the 709 00:33:35,080 --> 00:33:38,640 Speaker 11: farm can engage, farmer can engage digitally, or we can 710 00:33:38,680 --> 00:33:42,040 Speaker 11: remotely monitor and do things. Essentially, it's moving from the 711 00:33:42,120 --> 00:33:45,479 Speaker 11: mall to Amazon. Instead of the customer going to the store, 712 00:33:45,840 --> 00:33:47,800 Speaker 11: the store comes to the customer. 713 00:33:47,880 --> 00:33:51,360 Speaker 4: Smart pitch the Amazon of ag. There you go. You 714 00:33:51,520 --> 00:33:53,720 Speaker 4: just did it all right, Eric, thanks a lot, Eric 715 00:33:53,720 --> 00:33:57,080 Speaker 4: Hanzodia ag co CEO. We appreciate the time. Today. 716 00:33:57,320 --> 00:34:01,840 Speaker 1: This is the Bloomberg Intelligence Podcast, available on apples, Spotify, 717 00:34:02,040 --> 00:34:05,680 Speaker 1: and anywhere else you get your podcasts. Listen live each weekday, 718 00:34:05,840 --> 00:34:08,800 Speaker 1: ten am to noon Eastern on Bloomberg dot com, the 719 00:34:08,920 --> 00:34:12,360 Speaker 1: iHeartRadio app tune In, and the Bloomberg Business app. You 720 00:34:12,400 --> 00:34:15,560 Speaker 1: can also watch us live every weekday on YouTube and 721 00:34:15,719 --> 00:34:17,360 Speaker 1: always on the Bloomberg terminal