1 00:00:02,720 --> 00:00:10,559 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the 2 00:00:10,600 --> 00:00:14,560 Speaker 1: Bloomberg Intelligence podcast. Catch us live weekdays at ten am. 3 00:00:14,600 --> 00:00:17,239 Speaker 1: He's done on Apple, Cocklay and Android Auto with the 4 00:00:17,280 --> 00:00:21,040 Speaker 1: Bloomberg Business App. Listen on demand wherever you get your podcasts, 5 00:00:21,360 --> 00:00:23,560 Speaker 1: or watch us live on YouTube. 6 00:00:24,480 --> 00:00:26,840 Speaker 2: It is earning season and Paul, you gave a stat 7 00:00:26,880 --> 00:00:29,160 Speaker 2: earlier of Z one hundred and seventy companies have reported. 8 00:00:29,240 --> 00:00:30,440 Speaker 3: Yes, SMP five hundred. 9 00:00:30,480 --> 00:00:33,280 Speaker 2: The banks are all done, most of the MAGS seven 10 00:00:33,520 --> 00:00:34,960 Speaker 2: is done, but we still have a couple of stray 11 00:00:35,080 --> 00:00:37,519 Speaker 2: names reporting this week and then of course in videos 12 00:00:37,560 --> 00:00:42,000 Speaker 2: not till much later. But all the spending on AI continues. 13 00:00:42,120 --> 00:00:44,959 Speaker 2: And Oracle is the latest one. I mean, it's it's 14 00:00:45,000 --> 00:00:46,959 Speaker 2: been in the headlines for a while now, but we're 15 00:00:47,040 --> 00:00:50,120 Speaker 2: learning that it wants to raise up to fifty billion 16 00:00:50,200 --> 00:00:53,920 Speaker 2: dollars in debt and equity this year. That's a tremendous 17 00:00:54,080 --> 00:00:56,720 Speaker 2: number here for Oracle, so we needed to bring in 18 00:00:56,800 --> 00:00:59,000 Speaker 2: Man Deep Sing. He's our global tech research head here 19 00:00:59,040 --> 00:01:02,840 Speaker 2: at Bloomberg intelligen and Oracle raising up to fifty billion, 20 00:01:02,880 --> 00:01:04,800 Speaker 2: A big chunk of that, up to twenty five billion 21 00:01:04,800 --> 00:01:07,440 Speaker 2: of it will be through debt is really eye opening 22 00:01:07,520 --> 00:01:12,720 Speaker 2: given that it's credit has not traded as well, meaning 23 00:01:12,840 --> 00:01:16,080 Speaker 2: the spreads have widened and credit default swaps on Oracle 24 00:01:16,160 --> 00:01:18,520 Speaker 2: have also blown out a little bit. They've come back 25 00:01:18,520 --> 00:01:20,880 Speaker 2: in certainly, but there are a lot of questions over 26 00:01:20,920 --> 00:01:23,640 Speaker 2: the financial health of a company like Oracle versus say 27 00:01:24,000 --> 00:01:25,600 Speaker 2: a company like Microsoft. 28 00:01:26,240 --> 00:01:30,360 Speaker 4: Yeah. Look, I mean Oracle had given a revenue guide 29 00:01:30,400 --> 00:01:33,400 Speaker 4: for the next four years. So what they said was, 30 00:01:33,560 --> 00:01:36,520 Speaker 4: we have an eighteen billion dollar cloud business that's going 31 00:01:36,560 --> 00:01:39,640 Speaker 4: to go to one hundred and fifty billion dollar plus 32 00:01:39,680 --> 00:01:43,199 Speaker 4: over the next four years. The problem that the street 33 00:01:43,280 --> 00:01:47,680 Speaker 4: had was there wasn't really explanation of how they would, 34 00:01:47,760 --> 00:01:51,960 Speaker 4: you know, raise the funding, build the infrastructure, and how 35 00:01:52,000 --> 00:01:56,200 Speaker 4: that revenue would come about because it was all attached 36 00:01:56,240 --> 00:01:59,160 Speaker 4: to Open AI, the three hundred billion dollar backlog, which 37 00:01:59,200 --> 00:02:02,920 Speaker 4: is saying sixty billion dollars per year just from one company. 38 00:02:03,480 --> 00:02:08,080 Speaker 4: So now what they're saying is, Okay, we have visibility 39 00:02:08,120 --> 00:02:12,240 Speaker 4: to how we are going to build the initial tranch 40 00:02:12,360 --> 00:02:15,160 Speaker 4: of that AI infrastructure and data centers we need for 41 00:02:15,240 --> 00:02:19,280 Speaker 4: the twenty twenty seven target, which is essentially forty four 42 00:02:19,360 --> 00:02:23,119 Speaker 4: billion dollars in revenue that they want to have by 43 00:02:23,240 --> 00:02:24,239 Speaker 4: twenty twenty seven. 44 00:02:24,560 --> 00:02:25,560 Speaker 5: So for that to. 45 00:02:25,600 --> 00:02:29,240 Speaker 4: Happen, they need to invest, you know, up to fifty 46 00:02:29,240 --> 00:02:33,040 Speaker 4: billion dollars plus. So I compare them to the capex 47 00:02:33,080 --> 00:02:36,720 Speaker 4: that Meta and Google and Amazon will be making this year, 48 00:02:36,760 --> 00:02:39,360 Speaker 4: which is all in excess of one hundred billion. Where 49 00:02:39,360 --> 00:02:42,520 Speaker 4: does Oracles stack up so far? The consensus was they 50 00:02:42,560 --> 00:02:45,639 Speaker 4: would be below fifty billion dollars in capex. Then how 51 00:02:45,639 --> 00:02:47,920 Speaker 4: do you add forty four billion dollars in revenue when 52 00:02:48,000 --> 00:02:51,200 Speaker 4: Microsoft is not adding forty four billion dollars in cloud 53 00:02:51,200 --> 00:02:53,960 Speaker 4: revenue in twenty twenty seven. And that's where I think 54 00:02:54,000 --> 00:02:57,480 Speaker 4: they are making that upfront investments you need, which all 55 00:02:57,520 --> 00:03:00,000 Speaker 4: these companies are making. Yes, you have to do it 56 00:03:00,080 --> 00:03:02,560 Speaker 4: through debt, and you're already over levered to your point 57 00:03:02,639 --> 00:03:06,680 Speaker 4: that their CDs spreads were head widened, and that's where 58 00:03:06,720 --> 00:03:09,320 Speaker 4: you know they may they're using a combination of equity 59 00:03:09,320 --> 00:03:13,240 Speaker 4: issuance and debt to raise that money set up the 60 00:03:13,360 --> 00:03:16,760 Speaker 4: AI data centers, which in turn will translate into forty 61 00:03:16,760 --> 00:03:19,960 Speaker 4: four billion dollars in cloud revenue by twenty twenty seven. 62 00:03:20,040 --> 00:03:22,720 Speaker 4: So that's where if you believe their plan is going 63 00:03:22,760 --> 00:03:25,560 Speaker 4: to be successful, which cloud demand is the one thing 64 00:03:25,639 --> 00:03:28,800 Speaker 4: you know with AI, whether or not they are you know, 65 00:03:28,840 --> 00:03:32,560 Speaker 4: big applications, nobody knows, but everyone will be consuming compute 66 00:03:32,600 --> 00:03:34,960 Speaker 4: on the cloud. That's the kind of the part of 67 00:03:35,000 --> 00:03:36,480 Speaker 4: the business that's visible, right. 68 00:03:37,000 --> 00:03:40,280 Speaker 3: Chech investors that you've been dealing with for years, they've 69 00:03:40,320 --> 00:03:43,480 Speaker 3: been used to funding big cappecs, big R and D 70 00:03:43,800 --> 00:03:45,280 Speaker 3: out of internal cash. 71 00:03:45,840 --> 00:03:47,600 Speaker 5: Now that's changed. 72 00:03:47,640 --> 00:03:49,360 Speaker 3: They need to go to the capital markets where that's 73 00:03:49,400 --> 00:03:52,320 Speaker 3: the debt capital markets, equity capital markets. This is something 74 00:03:52,360 --> 00:03:55,920 Speaker 3: new for your investors. How are they digesting it there? 75 00:03:56,520 --> 00:03:59,120 Speaker 4: That's why you know there was a panic around Oracle 76 00:03:59,120 --> 00:04:01,840 Speaker 4: and you saw that for twenty percent draw down because 77 00:04:02,080 --> 00:04:06,760 Speaker 4: you're right in the case of Microsoft Meta, you know Google, 78 00:04:07,080 --> 00:04:10,040 Speaker 4: they generate up two hundred billion dollars in free cash 79 00:04:10,080 --> 00:04:13,240 Speaker 4: flow in a year. So with an Oracle it generates 80 00:04:13,280 --> 00:04:16,080 Speaker 4: about twenty billion dollars in free cash flow. How do 81 00:04:16,200 --> 00:04:19,160 Speaker 4: you make a fifty billion dollar plus capex investment? And 82 00:04:19,200 --> 00:04:21,440 Speaker 4: that's where you know the gap needs to be bridge. 83 00:04:21,480 --> 00:04:25,880 Speaker 4: And I think they're just maybe thinking too big in 84 00:04:25,960 --> 00:04:28,880 Speaker 4: terms of how they want to ramp up that cloud business. 85 00:04:29,240 --> 00:04:31,359 Speaker 4: And you know right now they are four percent of 86 00:04:31,520 --> 00:04:35,520 Speaker 4: the overall cloud market share pile based on the numbers 87 00:04:35,560 --> 00:04:37,920 Speaker 4: that they have given in terms of the guidance, they 88 00:04:37,960 --> 00:04:40,920 Speaker 4: would be fifteen to twenty percent of overall cloud market, 89 00:04:40,960 --> 00:04:44,080 Speaker 4: which is growing, by the way thirty forty percent plus 90 00:04:44,720 --> 00:04:48,320 Speaker 4: and expanding at that growth rate. So that's where I 91 00:04:48,360 --> 00:04:52,640 Speaker 4: think there was some skepticism around what is it that 92 00:04:52,760 --> 00:04:55,760 Speaker 4: Oracle can accomplish given they don't have the free cash 93 00:04:55,800 --> 00:04:58,159 Speaker 4: flow to fund this build out. And it will be 94 00:04:58,160 --> 00:05:00,720 Speaker 4: interesting to see how the bond trades and they you know, 95 00:05:00,920 --> 00:05:03,080 Speaker 4: issue this and there are a lot of unknown still 96 00:05:03,120 --> 00:05:04,480 Speaker 4: when it comes to the Oracle story. 97 00:05:04,600 --> 00:05:08,240 Speaker 2: Like I said, tremendous numbers here for Oracle. Another story 98 00:05:08,279 --> 00:05:11,680 Speaker 2: we're following, mandeep is Elon's Musk said to be in 99 00:05:11,800 --> 00:05:17,920 Speaker 2: advanced talks to combine SpaceX with Xai, his startup AI company. 100 00:05:18,600 --> 00:05:21,719 Speaker 2: What does this mean for SpaceX's planned IPO later on 101 00:05:21,760 --> 00:05:22,200 Speaker 2: this year. 102 00:05:22,760 --> 00:05:25,200 Speaker 4: Well, so I tie it to you know, the funding 103 00:05:25,279 --> 00:05:30,440 Speaker 4: needs for building your AI large angrid model infrastructure and 104 00:05:30,520 --> 00:05:34,200 Speaker 4: then rolling it out to millions of users. Same thing 105 00:05:34,240 --> 00:05:38,360 Speaker 4: with xai X When you compare XAI GROC to let's 106 00:05:38,360 --> 00:05:44,000 Speaker 4: say Gemini or you know, open AICHGPT XAI. Even though 107 00:05:44,000 --> 00:05:47,840 Speaker 4: they are frontier model, their user base is like twenty 108 00:05:48,000 --> 00:05:51,640 Speaker 4: thirty million compared to open ai, which is nine hundred million. 109 00:05:52,200 --> 00:05:55,040 Speaker 4: So one, they have a much smaller customer base when 110 00:05:55,080 --> 00:05:57,760 Speaker 4: it comes to the traffic that they're serving. And these 111 00:05:57,800 --> 00:06:01,120 Speaker 4: companies have to constantly invest in training their large anguid 112 00:06:01,160 --> 00:06:04,159 Speaker 4: model because you know, the three frontier models, Open Ai 113 00:06:04,240 --> 00:06:07,760 Speaker 4: and Thropic, Gemini are going forward in terms of you know, 114 00:06:07,760 --> 00:06:10,720 Speaker 4: the capabilities that they're adding. So Xai doesn't have a 115 00:06:10,839 --> 00:06:14,719 Speaker 4: choice but to keep investing. Problem is because of their 116 00:06:14,800 --> 00:06:18,680 Speaker 4: smaller user base. No one wants to keep you know, 117 00:06:19,160 --> 00:06:22,760 Speaker 4: funding Xai with another ten billion round or twenty billion 118 00:06:22,960 --> 00:06:25,120 Speaker 4: when they don't have free cash flow either. So it's 119 00:06:25,160 --> 00:06:28,880 Speaker 4: the same problem that Oracle has and they don't even 120 00:06:29,080 --> 00:06:33,040 Speaker 4: have you know, that user base. So that's where combining 121 00:06:33,240 --> 00:06:37,120 Speaker 4: Xai with SpaceX does make sense because SpaceX is a 122 00:06:37,200 --> 00:06:40,600 Speaker 4: much bigger entity. At least they have EBITDA margins for 123 00:06:40,640 --> 00:06:43,680 Speaker 4: around fifty percent, even though it's a very high fixed 124 00:06:43,680 --> 00:06:46,960 Speaker 4: cost business, so the roiic is much lower for you know, 125 00:06:47,160 --> 00:06:51,000 Speaker 4: some like an entity like SpaceX, but combining it makes 126 00:06:51,040 --> 00:06:54,000 Speaker 4: it more palatable for anybody who is putting money in 127 00:06:54,080 --> 00:06:57,039 Speaker 4: that combined entity and saying okay, at least you've got 128 00:06:57,040 --> 00:06:59,880 Speaker 4: two entities where I am ready to put some money 129 00:07:00,120 --> 00:07:01,600 Speaker 4: as opposed to just to XAI. 130 00:07:01,520 --> 00:07:04,480 Speaker 2: And SpaceX also has visibility. I mean, it's got these 131 00:07:04,520 --> 00:07:07,200 Speaker 2: projects with the governments. Yeah, it can project out. 132 00:07:07,320 --> 00:07:09,359 Speaker 3: Which we have any sense when that IPO might happen. 133 00:07:09,680 --> 00:07:10,960 Speaker 3: They're suggesting this year. 134 00:07:11,200 --> 00:07:14,520 Speaker 4: They are suggested. I mean even open Ai and Entropic 135 00:07:14,600 --> 00:07:16,800 Speaker 4: want to go public this year. So this year could 136 00:07:16,800 --> 00:07:18,840 Speaker 4: be huge in terms of you know IPOs. 137 00:07:18,920 --> 00:07:22,240 Speaker 3: Oh, by the way, the underwriters can't write research on 138 00:07:22,280 --> 00:07:25,640 Speaker 3: these companies, but who can? Yes, Bloomberg Intelligence be ahead, 139 00:07:25,880 --> 00:07:29,480 Speaker 3: and so what happens is we write the definitive research 140 00:07:29,560 --> 00:07:32,640 Speaker 3: report on these big IPO companies and. 141 00:07:32,720 --> 00:07:34,800 Speaker 4: Already have primers on opening Idanthropic. 142 00:07:35,520 --> 00:07:38,680 Speaker 5: Stay with us. More from Bloomberg Intelligence coming up after this. 143 00:07:42,520 --> 00:07:46,200 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 144 00:07:46,280 --> 00:07:49,400 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 145 00:07:49,400 --> 00:07:52,720 Speaker 1: Auto with the Bloomberg Business app. Listen on demand wherever 146 00:07:52,760 --> 00:07:56,120 Speaker 1: you get your podcasts, or watch us live on YouTube. 147 00:07:56,760 --> 00:08:01,240 Speaker 2: Let's talk about media companies because Disney just reported results 148 00:08:01,400 --> 00:08:06,880 Speaker 2: and the company reported record revenue in the last quarter, 149 00:08:07,560 --> 00:08:10,200 Speaker 2: which jumps six percent of record ten billion dollars, but 150 00:08:10,320 --> 00:08:13,720 Speaker 2: it's outlook for this quarter not so great. Keetha Rongganathan 151 00:08:13,840 --> 00:08:16,840 Speaker 2: is our US media analyst here at Bloomberg Intelligence and Keetha, 152 00:08:17,400 --> 00:08:20,400 Speaker 2: how do you square this idea that the forecast it's 153 00:08:20,440 --> 00:08:25,320 Speaker 2: given is kind of tappid, saying that it expects international 154 00:08:25,360 --> 00:08:28,760 Speaker 2: tourists to perhaps not show up at its different parks 155 00:08:29,120 --> 00:08:32,440 Speaker 2: when revenue did very well in the quarter ended. Is 156 00:08:32,480 --> 00:08:35,360 Speaker 2: this a case of Disney lowering expectations for a new 157 00:08:35,480 --> 00:08:37,640 Speaker 2: CEO that it plans a name pretty soon. 158 00:08:38,640 --> 00:08:41,120 Speaker 6: Would very well be Scarlet? I mean, this is your 159 00:08:41,120 --> 00:08:43,400 Speaker 6: classic case of you know, when good is you know, 160 00:08:43,480 --> 00:08:46,480 Speaker 6: not good enough? I guess. But yeah, they absolutely, I 161 00:08:46,480 --> 00:08:49,360 Speaker 6: think performed very well in the quarter that they just reported. 162 00:08:49,920 --> 00:08:53,120 Speaker 6: They have been citing some headwinds when it comes to 163 00:08:53,280 --> 00:08:56,880 Speaker 6: international visitation at domestic parks, but I think they are, 164 00:08:56,960 --> 00:09:00,000 Speaker 6: as you just mentioned, setting the bar a little bit lower, 165 00:09:01,080 --> 00:09:03,400 Speaker 6: not coming out, not raising guidance for the full year, 166 00:09:03,440 --> 00:09:06,880 Speaker 6: even though they had a really strong fiscal first quarter. Remember, 167 00:09:06,920 --> 00:09:09,120 Speaker 6: we do expect, I mean, we think that there will 168 00:09:09,160 --> 00:09:12,360 Speaker 6: be a lot of international visitation this year just because 169 00:09:12,400 --> 00:09:14,880 Speaker 6: of the World Cup, and you know, who knows, maybe 170 00:09:14,920 --> 00:09:17,640 Speaker 6: there could be some tailwinds there for Disney too. But 171 00:09:17,679 --> 00:09:20,040 Speaker 6: other than that, if you just look across the board, 172 00:09:20,080 --> 00:09:23,760 Speaker 6: I mean you look at the parks overall. Yes, there 173 00:09:23,760 --> 00:09:26,360 Speaker 6: has been some slow down in attendance here and there, 174 00:09:26,800 --> 00:09:29,640 Speaker 6: but they are undertaking investments across the board. So even 175 00:09:29,720 --> 00:09:32,280 Speaker 6: in this quarter alone, we're going to see this big 176 00:09:32,320 --> 00:09:35,520 Speaker 6: opening of World of Frozen, which will almost double the 177 00:09:35,559 --> 00:09:39,120 Speaker 6: size of Disneyland Paris. That's a huge investment. Again, yeah, 178 00:09:39,160 --> 00:09:41,040 Speaker 6: we're going to see some preopening costs, which is why 179 00:09:41,040 --> 00:09:44,400 Speaker 6: we're seeing that deeped outlook in the fiscal second quarter. 180 00:09:44,640 --> 00:09:46,520 Speaker 6: But I think if you look at the long term 181 00:09:46,559 --> 00:09:48,760 Speaker 6: thesis that is still very very much intact. 182 00:09:48,840 --> 00:09:51,600 Speaker 3: Scarlett and Githa looks like we're gonna get a new 183 00:09:51,600 --> 00:09:54,800 Speaker 3: CEO for Disney. Tell us how that may take place 184 00:09:55,000 --> 00:09:56,040 Speaker 3: and who this person may be. 185 00:09:57,320 --> 00:09:59,640 Speaker 6: Yeah, so there have been, you know, a two front 186 00:10:00,200 --> 00:10:03,520 Speaker 6: for the job, Paul, it's been internal candidates, Josh Tomorrow, 187 00:10:03,559 --> 00:10:06,720 Speaker 6: who heads the parks division, and Dana Walden, who came 188 00:10:06,800 --> 00:10:10,439 Speaker 6: to Disney from Fox and who heads up all of content. Now, 189 00:10:10,480 --> 00:10:12,640 Speaker 6: as you know Dana Walden, she's a huge, huge, She 190 00:10:12,679 --> 00:10:15,600 Speaker 6: has a huge presence in Hollywood. I mean, stars absolutely 191 00:10:15,640 --> 00:10:18,560 Speaker 6: love her. She's she's got a great presence within the 192 00:10:18,600 --> 00:10:21,679 Speaker 6: creative community. But I think, you know, there has been 193 00:10:21,720 --> 00:10:24,520 Speaker 6: obviously rumors that Josh Tomorrow is in the leading position 194 00:10:24,600 --> 00:10:27,199 Speaker 6: right now, and I think that just really reflects how 195 00:10:27,240 --> 00:10:31,560 Speaker 6: the company's, you know, Earning's position has completely changed. I 196 00:10:31,600 --> 00:10:33,880 Speaker 6: mean a few years ago, as you just pointed out, 197 00:10:34,320 --> 00:10:36,560 Speaker 6: you know, a while ago, this was really a TV 198 00:10:36,640 --> 00:10:39,520 Speaker 6: networks company, and that has completely changed now with this 199 00:10:39,640 --> 00:10:43,080 Speaker 6: being really the biggest theme park operator in the world, 200 00:10:43,120 --> 00:10:46,000 Speaker 6: attracting about one hundred and fifty million global visitors each 201 00:10:46,120 --> 00:10:49,040 Speaker 6: year and only poised to get stronger and stronger. So 202 00:10:49,120 --> 00:10:52,040 Speaker 6: they're already making about sixty percent of company profits comes 203 00:10:52,040 --> 00:10:54,559 Speaker 6: from just theme parks division alone. And as we kind 204 00:10:54,559 --> 00:10:56,360 Speaker 6: of look forward, Paul, I mean, you look at all 205 00:10:56,400 --> 00:10:58,720 Speaker 6: of the new cruise ships they're planning to basically double 206 00:10:58,760 --> 00:11:01,840 Speaker 6: triple capacity in the next three to four years. You 207 00:11:01,840 --> 00:11:05,040 Speaker 6: look at all of the park expansions. You know, park 208 00:11:05,120 --> 00:11:07,520 Speaker 6: profit could very well be three quarters of you know, 209 00:11:07,559 --> 00:11:09,720 Speaker 6: total company profits in the next few years time. 210 00:11:10,960 --> 00:11:12,880 Speaker 2: What is your confidence, Githa, that they're going to get 211 00:11:12,880 --> 00:11:15,360 Speaker 2: the succession right this time around, because not so long 212 00:11:15,400 --> 00:11:18,480 Speaker 2: ago they appointed Bob Chapek, who also headed up the 213 00:11:18,600 --> 00:11:23,280 Speaker 2: park's division to succeed Bob Eiger, and that lasted for 214 00:11:23,520 --> 00:11:26,160 Speaker 2: no more than a year, was it? I know, whatever 215 00:11:26,160 --> 00:11:28,120 Speaker 2: it was, it didn't last very long. Bob Iger ended 216 00:11:28,200 --> 00:11:30,640 Speaker 2: up coming back. Why is it different this time around? 217 00:11:31,600 --> 00:11:34,760 Speaker 6: I think it's different this time around because the company 218 00:11:34,800 --> 00:11:37,880 Speaker 6: isn't you know. I think they finally got their priority straight. 219 00:11:37,960 --> 00:11:40,480 Speaker 6: I think at that point, Disney was really trying to 220 00:11:40,600 --> 00:11:42,800 Speaker 6: still figure out what it was. Was it a TV 221 00:11:42,880 --> 00:11:45,400 Speaker 6: network company, was it a Disney plus streaming company? Was 222 00:11:45,400 --> 00:11:48,040 Speaker 6: it really a theme parks company? Was it a film studio? 223 00:11:48,320 --> 00:11:50,440 Speaker 6: So I think there were just so many different you know, 224 00:11:51,080 --> 00:11:52,600 Speaker 6: they had so many different balls up in the air. 225 00:11:52,640 --> 00:11:54,880 Speaker 6: But I think right now and streaming, obviously, they were 226 00:11:54,960 --> 00:11:57,880 Speaker 6: kind of in the early innings of streaming, chasing subscribers 227 00:11:57,880 --> 00:12:00,000 Speaker 6: at all costs, and that's the game that kind of 228 00:12:00,120 --> 00:12:03,320 Speaker 6: Bob Chapek played, but didn't play very well because he 229 00:12:03,440 --> 00:12:06,160 Speaker 6: was not very you know, obviously not very well versed. 230 00:12:06,160 --> 00:12:08,439 Speaker 6: But the content part of the business ended up really 231 00:12:08,600 --> 00:12:11,120 Speaker 6: overpaying in terms of content costs. We saw Disney pay 232 00:12:11,200 --> 00:12:14,440 Speaker 6: something like thirty two billion dollars in content costs, which 233 00:12:14,559 --> 00:12:16,680 Speaker 6: led to about I think four billion dollars in losses 234 00:12:16,679 --> 00:12:19,520 Speaker 6: for the streaming unit alone. They've come down from thirty 235 00:12:19,520 --> 00:12:22,200 Speaker 6: two billion dollars in content costs to twenty three billion 236 00:12:22,360 --> 00:12:24,760 Speaker 6: under Bob Eiger. So that was a lot of you know, 237 00:12:25,080 --> 00:12:28,000 Speaker 6: the right sizing of costs, really riding the ship, you know, 238 00:12:28,040 --> 00:12:31,560 Speaker 6: course correction, all of that happened. So I think definitely 239 00:12:31,640 --> 00:12:34,040 Speaker 6: the company is in much much better shape right now. 240 00:12:34,080 --> 00:12:36,880 Speaker 6: And again this is now I think people who were 241 00:12:36,960 --> 00:12:40,000 Speaker 6: kind of underappreciating the theme park portion of the business 242 00:12:40,080 --> 00:12:42,960 Speaker 6: now really look at this as mainly a parks company. 243 00:12:42,960 --> 00:12:44,600 Speaker 6: And yes they do have streaming, and yes we can 244 00:12:44,600 --> 00:12:47,040 Speaker 6: see some upside from streaming and films, but this is 245 00:12:47,160 --> 00:12:48,880 Speaker 6: really a theme park operator. 246 00:12:49,600 --> 00:12:53,160 Speaker 3: Oftentimes, when the board picks the CEO and the person 247 00:12:53,160 --> 00:12:55,520 Speaker 3: who did not get the role leaves the company, what's 248 00:12:55,520 --> 00:12:57,600 Speaker 3: the risk here that Dana Walden again, as you mentioned 249 00:12:57,600 --> 00:12:59,959 Speaker 3: so widely respect it and important, that she would leave 250 00:13:00,440 --> 00:13:01,400 Speaker 3: the Walt Disney Company. 251 00:13:02,400 --> 00:13:05,240 Speaker 6: Yeah, definitely, definitely possible. But they do have a deep bench. 252 00:13:05,280 --> 00:13:08,520 Speaker 6: I mean, along with data Walden, Alan Bergman also heads 253 00:13:08,960 --> 00:13:11,840 Speaker 6: you know, the content, so he's been overseeing some of 254 00:13:11,840 --> 00:13:14,760 Speaker 6: the film and TV businesses as well. So you know, 255 00:13:14,760 --> 00:13:16,800 Speaker 6: obviously there is the risk of her leaving, but at 256 00:13:16,840 --> 00:13:18,320 Speaker 6: the same time, I think they do have a deep 257 00:13:18,360 --> 00:13:20,600 Speaker 6: bench that could, you know, fill her shoes. 258 00:13:20,600 --> 00:13:22,439 Speaker 3: Hopefully stay with us. 259 00:13:22,640 --> 00:13:24,920 Speaker 5: More from Bloomberg Intelligence coming up after this. 260 00:13:28,880 --> 00:13:32,600 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 261 00:13:32,679 --> 00:13:35,360 Speaker 1: weekdays at ten am. He's done on Apple, Cocklay and 262 00:13:35,360 --> 00:13:38,640 Speaker 1: Android Auto with the Bloomberg Business app. Listen on demand 263 00:13:38,679 --> 00:13:42,640 Speaker 1: wherever you get your podcasts, or watch us live on YouTube. 264 00:13:43,280 --> 00:13:46,880 Speaker 3: The big global farmer companies reporting earnings. We got a 265 00:13:46,880 --> 00:13:49,120 Speaker 3: couple down, a couple more to go. Sam Fazzelli joins us. 266 00:13:49,160 --> 00:13:51,120 Speaker 3: He's the director of research for Global Industries. 267 00:13:51,280 --> 00:13:52,360 Speaker 5: Have no idea what that means. 268 00:13:52,760 --> 00:13:55,760 Speaker 3: I know him as a senior pharmaceutical zanols to Bloomberg Intelligence. 269 00:13:55,920 --> 00:13:58,839 Speaker 3: He's over there in London ostensibly, but he's always traveling 270 00:13:58,880 --> 00:14:00,760 Speaker 3: around the world, you know, check on all the latest 271 00:14:01,400 --> 00:14:02,959 Speaker 3: drugs and that kind of stuff. 272 00:14:03,000 --> 00:14:04,360 Speaker 5: That's how those folks get smart. 273 00:14:04,440 --> 00:14:09,000 Speaker 3: Hey, sam Sonfi, Roach, Roache and no I'm pronouncing incorrectly. 274 00:14:09,600 --> 00:14:11,160 Speaker 5: They reported some results here. 275 00:14:11,160 --> 00:14:12,600 Speaker 3: What did you see from the big some of those 276 00:14:12,679 --> 00:14:13,680 Speaker 3: big farmer companies. 277 00:14:14,640 --> 00:14:18,320 Speaker 7: Yeah, thanks, Paul. I think the most interesting of the 278 00:14:18,360 --> 00:14:21,720 Speaker 7: company of everything so far, that there are three companies, 279 00:14:21,760 --> 00:14:24,880 Speaker 7: so Santa Fe, Rosch and Johnson and Johnson who reported 280 00:14:24,960 --> 00:14:28,160 Speaker 7: so far was the fact that nobody really seemed to 281 00:14:28,640 --> 00:14:30,840 Speaker 7: be saying much about I mean, the people ask about 282 00:14:30,840 --> 00:14:33,440 Speaker 7: the MFN and the impact of FEN, but numbers were 283 00:14:33,480 --> 00:14:38,400 Speaker 7: in line and growth is as expected. So somehow these 284 00:14:38,440 --> 00:14:40,760 Speaker 7: companies are managing it. I mean, you know, we're going 285 00:14:40,840 --> 00:14:42,160 Speaker 7: to have to wait and see what happens to the 286 00:14:42,200 --> 00:14:46,440 Speaker 7: European countries drug sales, et cetera as they come on. 287 00:14:46,560 --> 00:14:49,800 Speaker 7: But nothing in there. And the one thing that specifically 288 00:14:49,840 --> 00:14:52,320 Speaker 7: stood out in the we talked about Johnson and Johnson 289 00:14:52,360 --> 00:14:55,040 Speaker 7: last time was Santa Fe where they called out the 290 00:14:55,120 --> 00:14:58,320 Speaker 7: vaccine sales in the US. Remember they still traditional vaccines, 291 00:14:58,360 --> 00:15:01,160 Speaker 7: not the m RNA, so it's not like it could 292 00:15:01,200 --> 00:15:03,720 Speaker 7: be something that people don't like. And they're still calling 293 00:15:03,800 --> 00:15:06,840 Speaker 7: for a for a down year in twenty twenty six, 294 00:15:07,160 --> 00:15:11,200 Speaker 7: which is interesting in that we have another company, Moderna, 295 00:15:11,240 --> 00:15:13,920 Speaker 7: that does make amoro vaccines and they're saying that they're 296 00:15:13,920 --> 00:15:16,160 Speaker 7: looking for an up here in twenty twenty six. So 297 00:15:16,200 --> 00:15:18,160 Speaker 7: there's some differences there that I think we need to 298 00:15:18,200 --> 00:15:22,640 Speaker 7: be ironed out between the companies, you know, And that's 299 00:15:23,040 --> 00:15:25,800 Speaker 7: and it's not a good thing that we're seeing less 300 00:15:25,880 --> 00:15:26,960 Speaker 7: vaccine US in the US. 301 00:15:27,160 --> 00:15:27,320 Speaker 4: Right. 302 00:15:27,360 --> 00:15:29,240 Speaker 2: We need to figure out if this is a company 303 00:15:29,240 --> 00:15:32,120 Speaker 2: specific issue or something that tells us about the take 304 00:15:32,160 --> 00:15:35,560 Speaker 2: up in the US. Can they make up these vaccine makers? 305 00:15:35,600 --> 00:15:38,280 Speaker 2: Can they make up that potential loss of business in 306 00:15:38,280 --> 00:15:40,320 Speaker 2: the US in other parts of the world. 307 00:15:42,000 --> 00:15:46,000 Speaker 7: Well, that's the thought potentially for Moderna I mean Sanofi, 308 00:15:46,400 --> 00:15:51,840 Speaker 7: you know, I mean the volume of vaccines that are 309 00:15:51,880 --> 00:15:54,000 Speaker 7: sold the rest of the world. The prices are not 310 00:15:54,160 --> 00:15:57,160 Speaker 7: anywhere near as strong as they are in the US, 311 00:15:57,240 --> 00:16:00,280 Speaker 7: so they can maybe work on the margins. I think 312 00:16:00,280 --> 00:16:02,880 Speaker 7: there's vaccine hesitancy across the board. I mean, why do 313 00:16:02,960 --> 00:16:05,400 Speaker 7: we have quite a few European countries we've lost their 314 00:16:05,440 --> 00:16:11,239 Speaker 7: measles elimination status too, not just the US problem. 315 00:16:10,480 --> 00:16:14,360 Speaker 3: Sam this Most Favored Nations status that President Trump is 316 00:16:14,400 --> 00:16:18,040 Speaker 3: talking about. What are the companies saying. Are they saying, hey, 317 00:16:18,040 --> 00:16:20,760 Speaker 3: this is real, this is going to happen, and are 318 00:16:20,760 --> 00:16:22,520 Speaker 3: they quantifying the potential costs? 319 00:16:22,520 --> 00:16:24,800 Speaker 5: Where are we in that whole process now? 320 00:16:25,040 --> 00:16:29,320 Speaker 7: I mean the cost is potentially coming from them repatriating 321 00:16:29,520 --> 00:16:33,560 Speaker 7: or moving some more investments into the US. What exactly 322 00:16:33,560 --> 00:16:36,080 Speaker 7: that number is? Time will show a lot of these 323 00:16:36,080 --> 00:16:39,120 Speaker 7: companies give big numbers fifty billion, fifty five billion over 324 00:16:39,160 --> 00:16:42,160 Speaker 7: the next five years, but that includes their standard R 325 00:16:42,200 --> 00:16:44,520 Speaker 7: and D, a lot of which is actually a release 326 00:16:44,560 --> 00:16:48,960 Speaker 7: spent in the US. So what that incremental increase of manufacturing, 327 00:16:48,960 --> 00:16:51,880 Speaker 7: et cetera in the US is, I don't know. And 328 00:16:51,960 --> 00:16:53,800 Speaker 7: I think you might have seen in numbers recently that 329 00:16:53,840 --> 00:16:56,880 Speaker 7: came at manufacturing headcamp isn't going up. In fact, they're shrunk. 330 00:16:57,600 --> 00:17:01,120 Speaker 7: So unless Farmer is such a small part of the 331 00:17:01,200 --> 00:17:04,800 Speaker 7: overall manufacturing numbers. But coming to the latest numbers that 332 00:17:04,840 --> 00:17:07,480 Speaker 7: we saw that came out last week, it didn't go up. 333 00:17:07,760 --> 00:17:10,440 Speaker 7: So something's not quite working out here, and maybe it's 334 00:17:10,480 --> 00:17:12,440 Speaker 7: just going to take a year two years before these 335 00:17:12,640 --> 00:17:15,360 Speaker 7: sites are operational before we see those numbers go up. 336 00:17:15,800 --> 00:17:17,439 Speaker 2: Yeah, it feels like there's a lot of room to 337 00:17:17,520 --> 00:17:22,359 Speaker 2: be vague in those big, big committments, right, And we 338 00:17:22,440 --> 00:17:25,439 Speaker 2: know this administration likes big, big numbers, so you can 339 00:17:25,520 --> 00:17:27,400 Speaker 2: kind of include everything under the sun all the better. 340 00:17:27,760 --> 00:17:30,960 Speaker 2: So let's talk a little bit sam about Eli Lilly, 341 00:17:31,000 --> 00:17:33,560 Speaker 2: which will be reporting earnings in two days on Wednesday. 342 00:17:34,359 --> 00:17:37,320 Speaker 2: The outlook right now is for a pretty broad guidance 343 00:17:37,359 --> 00:17:39,760 Speaker 2: for the full year. Walk us through the different things 344 00:17:39,800 --> 00:17:42,240 Speaker 2: that Eli Lilly needs to contend with as it offers 345 00:17:42,320 --> 00:17:42,880 Speaker 2: up guidance. 346 00:17:44,080 --> 00:17:46,160 Speaker 7: Yeah, it's not, by the way, it's not just really 347 00:17:46,240 --> 00:17:48,359 Speaker 7: both Lily and Nova reporting on the same day. That 348 00:17:48,400 --> 00:17:50,520 Speaker 7: makes it more fun for thin Wednesday is an awful 349 00:17:50,560 --> 00:17:52,880 Speaker 7: day for large farmer reporting or fun or fun. Wrong, 350 00:17:52,920 --> 00:17:55,879 Speaker 7: it's six seven well hopefully terms that you have to come. 351 00:17:56,119 --> 00:17:58,000 Speaker 7: You know, you need everybody on the desk to be 352 00:17:58,119 --> 00:17:59,919 Speaker 7: to be listening to these calls. So, I mean they 353 00:18:00,000 --> 00:18:01,680 Speaker 7: there's a few things that we're looking for for both 354 00:18:01,680 --> 00:18:04,240 Speaker 7: of them, frankly, and remember Nova is the first one 355 00:18:04,240 --> 00:18:07,159 Speaker 7: that's launched a oral drug that's out there Oral we 356 00:18:07,280 --> 00:18:10,399 Speaker 7: go be and the prescription volumes for that you can 357 00:18:10,480 --> 00:18:13,639 Speaker 7: check out on the terminal. Are going one of the 358 00:18:13,840 --> 00:18:18,240 Speaker 7: strongest diabete obviousity launchers that we've had in I think 359 00:18:18,240 --> 00:18:22,800 Speaker 7: maybe even ever. So that's looking pretty strong. What the therefore, 360 00:18:22,880 --> 00:18:26,320 Speaker 7: the timing of O forglypron Glypron that's coming from Lily, 361 00:18:26,480 --> 00:18:28,920 Speaker 7: I think that's expected to Queue. Maybe a little update 362 00:18:28,960 --> 00:18:31,159 Speaker 7: on that when exactly to que. Everyone wants to know 363 00:18:31,560 --> 00:18:33,920 Speaker 7: early to Que is the current date. We're also looking 364 00:18:33,960 --> 00:18:37,280 Speaker 7: to see how these deals that they've done with slightly 365 00:18:37,280 --> 00:18:40,199 Speaker 7: lower prices you might have seen those with the medicare prices, 366 00:18:40,240 --> 00:18:43,760 Speaker 7: et cetera. Are they beginning to show in increased volume. 367 00:18:44,040 --> 00:18:47,119 Speaker 7: The theory is if price comes down, volumete go up, right, 368 00:18:47,160 --> 00:18:50,880 Speaker 7: because this is an insatiable market. And then lastly, one 369 00:18:50,880 --> 00:18:53,080 Speaker 7: of the tough things to keep an eye on is 370 00:18:53,320 --> 00:18:56,600 Speaker 7: x US. We have prescription data for US promises, but 371 00:18:56,800 --> 00:18:59,280 Speaker 7: xuas is much harder to follow. So people are going 372 00:18:59,320 --> 00:19:01,680 Speaker 7: to be looking to see how these obesity drugs are 373 00:19:01,720 --> 00:19:04,920 Speaker 7: doing outside of the United States. That's the key thing. 374 00:19:07,720 --> 00:19:10,560 Speaker 5: Stay with us. More from Bloomberg Intelligence coming up here 375 00:19:10,600 --> 00:19:10,800 Speaker 5: for this. 376 00:19:13,880 --> 00:19:17,600 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 377 00:19:17,640 --> 00:19:20,760 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 378 00:19:20,760 --> 00:19:24,080 Speaker 1: Auto with the Bloomberg Business app, listen on demand wherever 379 00:19:24,119 --> 00:19:27,200 Speaker 1: you get your podcasts, or watch us live on YouTube. 380 00:19:28,000 --> 00:19:30,600 Speaker 3: Well, folks, the experts continue to tell us we're in 381 00:19:30,640 --> 00:19:34,200 Speaker 3: the early early innings of this AI story here, and 382 00:19:34,240 --> 00:19:36,159 Speaker 3: a lot of investors continue to look for ways to 383 00:19:36,240 --> 00:19:39,520 Speaker 3: play it, as do we. Fortunately here in Bloomberg Intelligence, 384 00:19:39,520 --> 00:19:42,120 Speaker 3: we've got a lot of technology channels who cover all 385 00:19:42,160 --> 00:19:44,640 Speaker 3: parts of the tech stack, and that includes Woojin host 386 00:19:44,640 --> 00:19:49,000 Speaker 3: senior technology channels for Bloomberg Intelligence. Talk about the global 387 00:19:49,040 --> 00:19:52,240 Speaker 3: communications and networking equipment space what to look for in 388 00:19:52,240 --> 00:19:55,320 Speaker 3: twenty twenty six. Woods, thanks so much for joining us here. 389 00:19:55,960 --> 00:19:58,720 Speaker 3: When your conversations with investors and they say, wooje in 390 00:19:58,760 --> 00:20:02,639 Speaker 3: your space, in the communications space, the network equipment space. 391 00:20:02,880 --> 00:20:04,760 Speaker 5: What's the best way to play AI? How do you 392 00:20:04,840 --> 00:20:05,920 Speaker 5: kind of shape that conversation? 393 00:20:06,880 --> 00:20:11,440 Speaker 8: Yeah, hey, thanks Paul. So it's fairly straightforward, right, It's 394 00:20:11,480 --> 00:20:15,479 Speaker 8: a very fairly concentrated space. The AI networking space is 395 00:20:15,520 --> 00:20:18,600 Speaker 8: expected to grow ninety one percent on the switching hardware 396 00:20:18,600 --> 00:20:22,480 Speaker 8: alone to twenty one billion dollars. Right, The way to 397 00:20:22,480 --> 00:20:26,520 Speaker 8: play it is fairly straightforward. It's A three c's, an 398 00:20:26,520 --> 00:20:32,120 Speaker 8: A and an N. Right, that's my new networking than Cisco, Celestica, 399 00:20:32,280 --> 00:20:38,400 Speaker 8: Corning and CNSO. Four c's Arista and Nvidia, right, and 400 00:20:38,600 --> 00:20:40,919 Speaker 8: those are going to be the leading beneficiaries for the 401 00:20:40,960 --> 00:20:42,439 Speaker 8: networking space in AI. 402 00:20:42,840 --> 00:20:45,960 Speaker 3: So give us a sense of kind of how investors 403 00:20:46,000 --> 00:20:48,560 Speaker 3: should think about the investment cycle for AI. 404 00:20:48,920 --> 00:20:51,919 Speaker 5: I mean, I'm going to say we're two three years 405 00:20:51,960 --> 00:20:52,479 Speaker 5: into it. 406 00:20:53,200 --> 00:20:54,040 Speaker 3: I'm just not sure. 407 00:20:54,400 --> 00:20:55,960 Speaker 5: How do you guys think about the duration here. 408 00:20:56,800 --> 00:21:00,159 Speaker 8: Yeah, you know, it's it's quite odd, right because you know, 409 00:21:00,400 --> 00:21:02,840 Speaker 8: some of us say it's two three years into it. 410 00:21:03,400 --> 00:21:06,080 Speaker 8: Michael Dell had this interesting quote a couple of weeks 411 00:21:06,119 --> 00:21:10,399 Speaker 8: ago saying, what inning are we and his response was, 412 00:21:11,000 --> 00:21:12,440 Speaker 8: we're just entering the stadium. 413 00:21:12,560 --> 00:21:12,800 Speaker 5: Wow. 414 00:21:12,880 --> 00:21:15,720 Speaker 8: Right, Yeah, so he still thinks it's early on in 415 00:21:15,840 --> 00:21:18,440 Speaker 8: terms of the investment phase. You just had a mendeep 416 00:21:18,560 --> 00:21:20,880 Speaker 8: on he and he was talking about the Oracle investment, 417 00:21:21,280 --> 00:21:23,680 Speaker 8: and look, fifty billion dollars is a massive amount of 418 00:21:23,680 --> 00:21:26,320 Speaker 8: money and it's all going into the infrastructure space, and 419 00:21:26,720 --> 00:21:29,640 Speaker 8: networking is going to be one of the leading beneficiars 420 00:21:29,680 --> 00:21:29,920 Speaker 8: of it. 421 00:21:30,119 --> 00:21:33,280 Speaker 3: So how are the networking equipment companies that you follow, 422 00:21:34,000 --> 00:21:36,680 Speaker 3: how are they financing some of their capex? Because again, 423 00:21:36,720 --> 00:21:39,479 Speaker 3: I think most of us grew up when technology companies 424 00:21:39,480 --> 00:21:42,640 Speaker 3: had so much cash flow that they could self fund 425 00:21:42,720 --> 00:21:44,960 Speaker 3: their R and D, their capex, that type of stuff. 426 00:21:44,960 --> 00:21:49,000 Speaker 3: Now many of them need to come to the capital markets. 427 00:21:49,359 --> 00:21:49,600 Speaker 6: Yeah. 428 00:21:50,040 --> 00:21:55,120 Speaker 8: Fortunately for the networking guys, it's a low capex type 429 00:21:55,119 --> 00:21:58,560 Speaker 8: of business. Right, We're talking about seb ten percent of 430 00:21:59,440 --> 00:22:03,520 Speaker 8: the flow to capex or ten percent of capex ratio 431 00:22:03,560 --> 00:22:07,119 Speaker 8: to sales. So it is a fairly self funded business, 432 00:22:07,119 --> 00:22:10,720 Speaker 8: and it's also high margin business as well. As long 433 00:22:10,840 --> 00:22:14,760 Speaker 8: as the hyperscale cloud providers as well as the tier 434 00:22:14,800 --> 00:22:18,560 Speaker 8: two cloud providers like the Neo clouds, are funded, they'll 435 00:22:18,560 --> 00:22:19,840 Speaker 8: be able to buy the networking gear. 436 00:22:20,960 --> 00:22:23,760 Speaker 3: So how do you I mean, it's interesting here think 437 00:22:23,800 --> 00:22:26,680 Speaker 3: about the tech space and it's hardware, it's software, it's 438 00:22:26,920 --> 00:22:32,119 Speaker 3: the networking equipment here. Who's kind of driving this. 439 00:22:31,600 --> 00:22:32,560 Speaker 5: This AI thing? 440 00:22:32,680 --> 00:22:32,760 Speaker 4: Is? 441 00:22:33,200 --> 00:22:35,399 Speaker 3: Are your networking in communications companies? 442 00:22:35,440 --> 00:22:37,720 Speaker 5: Are they kind of dependent upon I don't know. 443 00:22:37,680 --> 00:22:40,399 Speaker 3: What the hyperscalers are doing or what the chip makers 444 00:22:40,400 --> 00:22:40,720 Speaker 3: are doing. 445 00:22:40,720 --> 00:22:41,919 Speaker 5: Who's kind of leading this? 446 00:22:42,680 --> 00:22:46,439 Speaker 8: So at the end of the day, it's how quickly 447 00:22:46,520 --> 00:22:50,320 Speaker 8: and how fast and how large of the investments that 448 00:22:50,359 --> 00:22:53,960 Speaker 8: the hyperscalers are making on the AI side. I will 449 00:22:53,960 --> 00:22:59,520 Speaker 8: tell you, as these language models grow and the scale 450 00:22:59,640 --> 00:23:03,320 Speaker 8: of the these compute investments grow, you actually need a 451 00:23:03,320 --> 00:23:06,639 Speaker 8: lot more networking. And networking is if you think about 452 00:23:06,920 --> 00:23:11,240 Speaker 8: it as the arteries and the veins of a human body. 453 00:23:12,000 --> 00:23:14,400 Speaker 8: Networking is probably at the center of that right now, 454 00:23:14,400 --> 00:23:15,960 Speaker 8: and that's why you're having a lot of investment on 455 00:23:16,000 --> 00:23:16,720 Speaker 8: their networking front. 456 00:23:17,600 --> 00:23:20,160 Speaker 3: Who are I mean, how are they dealing with again, 457 00:23:20,200 --> 00:23:23,400 Speaker 3: these networking companies I think of these big global companies, 458 00:23:23,840 --> 00:23:26,639 Speaker 3: is that manufacturing dispersed around the globe. Is there a 459 00:23:26,680 --> 00:23:28,920 Speaker 3: pressure to bring it to the US. How are they 460 00:23:28,920 --> 00:23:32,520 Speaker 3: dealing with some of the changes we've seen in global logistics, 461 00:23:32,520 --> 00:23:36,000 Speaker 3: whether it's tariffs or just you know, most favorite nation status, 462 00:23:36,040 --> 00:23:36,840 Speaker 3: those types of things. 463 00:23:37,320 --> 00:23:40,920 Speaker 8: Yeah, that's a fantastic question, Paul. I will tell you 464 00:23:40,960 --> 00:23:43,239 Speaker 8: that there's a couple of things. Right when we had 465 00:23:43,240 --> 00:23:46,360 Speaker 8: the tiraff situation number one, and also the COVID situation 466 00:23:47,280 --> 00:23:49,879 Speaker 8: a few years back, the companies have actually done a 467 00:23:49,920 --> 00:23:52,840 Speaker 8: good job rearranging the supply chain. A lot of manufacturings 468 00:23:52,840 --> 00:23:57,320 Speaker 8: happening out of Mexico. There's some manufacturing that's happening in 469 00:23:57,359 --> 00:24:00,359 Speaker 8: Taiwan as well as in Canada. So we're by passing 470 00:24:00,359 --> 00:24:02,840 Speaker 8: some of the tarriff situation. And quite frankly, tariff's have 471 00:24:02,920 --> 00:24:07,359 Speaker 8: become a non story for the majority of my networking guys. 472 00:24:07,400 --> 00:24:11,120 Speaker 8: And on top of that, the dram story is inconsequential 473 00:24:11,160 --> 00:24:12,280 Speaker 8: for the networking games as well. 474 00:24:12,800 --> 00:24:16,080 Speaker 3: However, the stocks performing here, I've seen so many parts 475 00:24:16,119 --> 00:24:17,600 Speaker 3: of the tech space just rip. 476 00:24:18,480 --> 00:24:19,560 Speaker 5: How have your stocks been doing? 477 00:24:20,840 --> 00:24:23,720 Speaker 8: I will tell you if you know if you looked 478 00:24:23,720 --> 00:24:27,320 Speaker 8: at the Celestica two years back, you're seeing a ten 479 00:24:27,400 --> 00:24:31,439 Speaker 8: time performer to where it is right now. You know, 480 00:24:31,640 --> 00:24:33,960 Speaker 8: it has slowed down because I think people are starting 481 00:24:33,960 --> 00:24:37,800 Speaker 8: to catch up to the name Arista. It's a double 482 00:24:37,840 --> 00:24:41,399 Speaker 8: from from two to three years back. And Cisco, I 483 00:24:41,400 --> 00:24:45,520 Speaker 8: mean we've finally got back to it's two thousand and 484 00:24:45,520 --> 00:24:49,560 Speaker 8: one highs because of the business has actually stabilized, so 485 00:24:49,600 --> 00:24:53,199 Speaker 8: the stocks in itself have done well. The multiples have 486 00:24:53,600 --> 00:24:55,480 Speaker 8: actually gotten a little bit rich. 487 00:24:56,920 --> 00:25:01,639 Speaker 1: This is the Bloomberg Intelligence Podcast, bailable on Apple, Spotify, 488 00:25:01,800 --> 00:25:05,280 Speaker 1: and anywhere else you get your podcasts. Listen live each 489 00:25:05,320 --> 00:25:09,040 Speaker 1: weekday ten am to noon Eastern on Bloomberg dot com, 490 00:25:09,200 --> 00:25:12,720 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app. 491 00:25:13,160 --> 00:25:16,040 Speaker 1: You can also watch us live every weekday on YouTube 492 00:25:16,480 --> 00:25:18,720 Speaker 1: and always on the Bloomberg terminal.