1 00:00:02,759 --> 00:00:10,600 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the 2 00:00:10,640 --> 00:00:14,600 Speaker 1: Bloomberg Intelligence Podcast. Catch us live weekdays at ten am 3 00:00:14,640 --> 00:00:17,880 Speaker 1: Eastern on Apple, Cocklay and Android Auto with the Bloomberg 4 00:00:17,960 --> 00:00:21,080 Speaker 1: Business App. Listen on demand wherever you get your podcasts, 5 00:00:21,400 --> 00:00:23,120 Speaker 1: or watch us live on YouTube. 6 00:00:23,760 --> 00:00:25,560 Speaker 2: For now, we want to go from the markets and 7 00:00:25,600 --> 00:00:28,880 Speaker 2: shift over to Tesla. Tesla shares have been down there 8 00:00:28,920 --> 00:00:31,600 Speaker 2: more than seven percent right now here to tell us 9 00:00:31,600 --> 00:00:34,559 Speaker 2: about it more? Why is Craig for Trudell? He's Bloomberg 10 00:00:34,560 --> 00:00:38,120 Speaker 2: Global Auditors Editor Craig want to start out and talk 11 00:00:38,120 --> 00:00:40,960 Speaker 2: about this our investors. Are they just tired? I guess 12 00:00:41,000 --> 00:00:43,559 Speaker 2: this is assuming going according to what Elon Musk has 13 00:00:43,600 --> 00:00:46,920 Speaker 2: been saying. Are they just tired of his kind of 14 00:00:46,960 --> 00:00:50,080 Speaker 2: talking about this and putting himself out there and talking 15 00:00:50,080 --> 00:00:53,280 Speaker 2: about politics when he should be focused on the company. 16 00:00:54,320 --> 00:00:57,200 Speaker 3: I think they see all sorts of risks here. You know, 17 00:00:57,560 --> 00:01:00,880 Speaker 3: this is a matter of now, you know, just alienate, 18 00:01:01,040 --> 00:01:06,480 Speaker 3: alienating Democrats, but but also now going after Republicans and 19 00:01:06,480 --> 00:01:09,959 Speaker 3: and you know, really uh, sort of ticking off Donald Trump. 20 00:01:10,000 --> 00:01:12,960 Speaker 3: And we've seen that with Trump going from you know, 21 00:01:13,040 --> 00:01:16,560 Speaker 3: kind of biting his tongue when Musk was first attacking uh, 22 00:01:16,640 --> 00:01:19,800 Speaker 3: you know, the big beautiful Bill to really going after 23 00:01:19,920 --> 00:01:23,280 Speaker 3: Musk in a more sort of pitched way. And you know, 24 00:01:23,360 --> 00:01:25,760 Speaker 3: so so this is uh, you know, a risk for 25 00:01:25,880 --> 00:01:29,560 Speaker 3: him to to sort of make himself in an enemy 26 00:01:29,600 --> 00:01:33,120 Speaker 3: and of of both sides of the aisle in Washington, 27 00:01:33,480 --> 00:01:37,400 Speaker 3: Washington potentially, but also you know, just a great big 28 00:01:37,440 --> 00:01:41,960 Speaker 3: distraction after he's assured everybody, you know, on multiple occasions, look, 29 00:01:41,959 --> 00:01:44,240 Speaker 3: I'm going to you know, sort of get back to 30 00:01:44,280 --> 00:01:47,640 Speaker 3: business and and uh, you know, tend to to Tesla 31 00:01:47,720 --> 00:01:50,680 Speaker 3: more than I have been, you know, since last year. 32 00:01:51,400 --> 00:01:54,400 Speaker 4: So I have to ask this question, is there a 33 00:01:54,440 --> 00:01:57,840 Speaker 4: board here at this company that can reign Elon Musk? 34 00:01:57,880 --> 00:02:02,320 Speaker 3: Here? There is, You wouldn't necessarily know it from the 35 00:02:02,360 --> 00:02:05,720 Speaker 3: actions of the board, right, you know, to the extent 36 00:02:05,760 --> 00:02:09,040 Speaker 3: that we've heard from the board recently, it's been to say, 37 00:02:09,639 --> 00:02:11,680 Speaker 3: you know, Elon's are our guy. 38 00:02:12,440 --> 00:02:12,640 Speaker 5: You know. 39 00:02:12,680 --> 00:02:16,160 Speaker 3: They they batted down a report in the Wall Street 40 00:02:16,200 --> 00:02:18,640 Speaker 3: Journal just in the last few months about you know, 41 00:02:18,720 --> 00:02:23,240 Speaker 3: potential succession planning at the company. I think the sort 42 00:02:23,280 --> 00:02:25,880 Speaker 3: of read of that, a close read of that story, 43 00:02:26,160 --> 00:02:29,400 Speaker 3: it wasn't necessarily the case that what the journal was 44 00:02:29,400 --> 00:02:31,800 Speaker 3: saying was that they are you know, were actively looking 45 00:02:31,800 --> 00:02:34,960 Speaker 3: to replace Musk. It was potentially more of a matter 46 00:02:35,040 --> 00:02:37,400 Speaker 3: of of you know, sort of doing the job that 47 00:02:37,440 --> 00:02:39,600 Speaker 3: you would expect a board to do. I should sort of, 48 00:02:39,880 --> 00:02:42,200 Speaker 3: you know, give them a credit in that regard that 49 00:02:42,240 --> 00:02:46,880 Speaker 3: at least they're preparing for, you know, the potential of 50 00:02:46,880 --> 00:02:49,400 Speaker 3: of needing to to look for a next CEO. But 51 00:02:49,840 --> 00:02:52,680 Speaker 3: you know, Musk is very much in control of this 52 00:02:52,760 --> 00:02:56,120 Speaker 3: company and that was something that you know, the Delaware 53 00:02:56,520 --> 00:02:59,920 Speaker 3: Chancery Court judge who throughout his pay package, you know, 54 00:03:00,080 --> 00:03:02,720 Speaker 3: really emphasized in her ruling last year when she said, 55 00:03:03,040 --> 00:03:05,800 Speaker 3: you know, he's very much in control of this company 56 00:03:05,800 --> 00:03:09,200 Speaker 3: and its board, and you know on those grounds, uh, 57 00:03:09,360 --> 00:03:13,320 Speaker 3: you know, throughout his compensation package, which has created you know, 58 00:03:13,360 --> 00:03:17,000 Speaker 3: another mess and and you know, I think this you know, 59 00:03:17,120 --> 00:03:23,239 Speaker 3: political endeavors, you know, only only complicates the board's attempt 60 00:03:23,280 --> 00:03:26,440 Speaker 3: to try and get him him compensated in a in 61 00:03:26,480 --> 00:03:28,639 Speaker 3: a way that he's going to be happy with now quick. 62 00:03:28,760 --> 00:03:30,800 Speaker 2: Not too long ago, we heard Ilama saying, you know what, 63 00:03:30,919 --> 00:03:32,239 Speaker 2: I'm going to get back to it. I'm going to 64 00:03:32,320 --> 00:03:35,080 Speaker 2: focus on Tessel. This was after the last earnings and 65 00:03:35,200 --> 00:03:38,000 Speaker 2: now we're seeing the shift right, he's talking about this 66 00:03:38,160 --> 00:03:41,920 Speaker 2: America Party. I mean, is is this something that investors 67 00:03:41,960 --> 00:03:43,840 Speaker 2: should be concerned about? He's kind of going back on his. 68 00:03:43,800 --> 00:03:47,480 Speaker 3: Word there, Yeah, I mean, I think you know some 69 00:03:47,560 --> 00:03:49,839 Speaker 3: of the it's it's not the only way in which 70 00:03:49,840 --> 00:03:53,280 Speaker 3: he's he's sort of undermined himself. And and you know, 71 00:03:53,360 --> 00:03:58,400 Speaker 3: potentially you made an investors question the things that he's 72 00:03:58,400 --> 00:04:01,600 Speaker 3: been telling them because he also, you know, said to 73 00:04:01,640 --> 00:04:05,200 Speaker 3: Bloomberg back in May that our sales are turning around, right, 74 00:04:05,360 --> 00:04:08,440 Speaker 3: and that was not born out in the deliveries numbers 75 00:04:08,480 --> 00:04:10,960 Speaker 3: that the company reported last week. They had a thirteen 76 00:04:10,960 --> 00:04:14,680 Speaker 3: percent year over year decline in worldwide vehicle sales. That 77 00:04:14,760 --> 00:04:17,520 Speaker 3: was almost bang on what they posted for the first quarter. 78 00:04:18,040 --> 00:04:20,680 Speaker 3: So you know, for him to say, you know that 79 00:04:21,120 --> 00:04:24,240 Speaker 3: he thinks in terms of political spendings, he's done enough 80 00:04:25,040 --> 00:04:26,880 Speaker 3: that he's going to you know, do a lot less 81 00:04:26,920 --> 00:04:29,240 Speaker 3: of it in the future. You know, that was what 82 00:04:29,279 --> 00:04:32,080 Speaker 3: he said in May, and this is is pretty much 83 00:04:32,120 --> 00:04:35,080 Speaker 3: one hundred and eighty degrees different from from what he 84 00:04:35,160 --> 00:04:35,480 Speaker 3: was saying. 85 00:04:35,520 --> 00:04:35,680 Speaker 5: Then. 86 00:04:36,080 --> 00:04:38,600 Speaker 4: All right, Greig, thank you so much. I appreciate your reporting. 87 00:04:38,600 --> 00:04:41,760 Speaker 4: Craig Trudel Global Auto's editor for Bloomberg News. 88 00:04:42,040 --> 00:04:43,239 Speaker 6: He is in London. 89 00:04:43,360 --> 00:04:47,279 Speaker 4: I mean, it just feels like the brand has suffered damage, 90 00:04:47,360 --> 00:04:48,480 Speaker 4: the Tesla brand. 91 00:04:50,600 --> 00:04:52,240 Speaker 6: I guess the data will prove that out, and. 92 00:04:52,200 --> 00:04:53,440 Speaker 2: That's just kind of expected. 93 00:04:53,680 --> 00:04:56,479 Speaker 4: I know, I don't know, but but it seems like 94 00:04:56,640 --> 00:04:59,640 Speaker 4: if you do a third party, you're kind of upsetting everybody. 95 00:05:00,360 --> 00:05:01,880 Speaker 4: It's like both sides of the aisle. I don't know 96 00:05:01,880 --> 00:05:04,359 Speaker 4: how that's a good marketing strategy. 97 00:05:06,080 --> 00:05:09,760 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 98 00:05:09,839 --> 00:05:12,960 Speaker 1: weekdays at ten am Eastern on Apple, Coarclay, and Android 99 00:05:12,960 --> 00:05:16,279 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 100 00:05:16,320 --> 00:05:19,440 Speaker 1: you get your podcasts, or watch us live on YouTube. 101 00:05:20,160 --> 00:05:24,120 Speaker 2: All right, well, the House past President Trump's latest tax 102 00:05:24,160 --> 00:05:26,720 Speaker 2: and spending bill. But what does that mean for the 103 00:05:26,760 --> 00:05:30,600 Speaker 2: pharmaceutical industry? Well, we're about to learn more. I introduce 104 00:05:30,640 --> 00:05:33,320 Speaker 2: to you Sam Fazzelli. He's Bloomberg with Intelligence, Director of 105 00:05:33,320 --> 00:05:36,840 Speaker 2: Research for Global Industry Senior Pharmaceuticals. Sam, I want to 106 00:05:36,880 --> 00:05:41,000 Speaker 2: start there. I mean, what does this mean for pharma? 107 00:05:41,480 --> 00:05:45,919 Speaker 5: So the one big beautiful bill had in it a 108 00:05:46,000 --> 00:05:49,640 Speaker 5: couple of things, many things, obviously, I can't remember how 109 00:05:49,640 --> 00:05:51,839 Speaker 5: many pages it was supposed to be. But for the 110 00:05:51,839 --> 00:05:54,160 Speaker 5: farmer industry, I'm going to focus on two things right now. 111 00:05:54,200 --> 00:05:56,840 Speaker 5: Right one is a good thing. So there is an 112 00:05:56,960 --> 00:06:02,159 Speaker 5: orphan drug change and impacts the IRA and actually impacts 113 00:06:02,160 --> 00:06:05,200 Speaker 5: some really big drugs. Here. What's an ophan drug. When 114 00:06:05,200 --> 00:06:07,880 Speaker 5: you develop a drug for a patient population that less 115 00:06:07,880 --> 00:06:10,680 Speaker 5: than two hundred thousand in the US, you called an 116 00:06:10,720 --> 00:06:14,200 Speaker 5: orphan drug. You get a special exemption. It really helps 117 00:06:14,240 --> 00:06:17,479 Speaker 5: you in terms of your duration of time that it 118 00:06:17,520 --> 00:06:20,280 Speaker 5: can be on the market. It's a respective of your 119 00:06:20,560 --> 00:06:24,120 Speaker 5: patent expiry. It was all set up to help companies 120 00:06:24,600 --> 00:06:28,000 Speaker 5: develop drugs for these underserved markets. Two hundred thousand. Okay, 121 00:06:28,000 --> 00:06:30,839 Speaker 5: it's not small. It's not big, but it's not that small. 122 00:06:31,200 --> 00:06:34,080 Speaker 5: So it helped. One of the big drugs that had 123 00:06:34,120 --> 00:06:37,280 Speaker 5: this was Cutruder, which is the biggest selling drug at 124 00:06:37,279 --> 00:06:40,719 Speaker 5: the minute, and that's for cancer from merk. So when 125 00:06:40,800 --> 00:06:43,640 Speaker 5: IRA came along, it said, what we're going to do 126 00:06:44,320 --> 00:06:48,719 Speaker 5: is say your drug twenty fourteen approval for Truder under 127 00:06:48,800 --> 00:06:52,240 Speaker 5: orphan drug. Great, if you're an ophen drug, you don't 128 00:06:52,279 --> 00:06:55,160 Speaker 5: fall into IRA the renegotiation or price and all that. 129 00:06:55,480 --> 00:06:57,560 Speaker 5: But as soon as you get another indication then that 130 00:06:57,640 --> 00:07:01,440 Speaker 5: clock starts from the original date of approval. So if 131 00:07:01,440 --> 00:07:03,800 Speaker 5: you had a drug orphant drug in twenty fourteen and 132 00:07:03,839 --> 00:07:06,000 Speaker 5: you get some other indication in twenty twenty two, they 133 00:07:06,120 --> 00:07:08,720 Speaker 5: date back to count the clock counting to twenty fourteen. 134 00:07:09,000 --> 00:07:12,040 Speaker 5: That was terrible. It really means that nobody would want 135 00:07:12,040 --> 00:07:18,000 Speaker 5: to do multi indication tests, et cetera. So that's been changed. 136 00:07:18,400 --> 00:07:21,480 Speaker 5: Once an ophn drug is you can keep that drug date. 137 00:07:21,840 --> 00:07:23,960 Speaker 5: And so what does that mean for Ktruder from Merk 138 00:07:24,400 --> 00:07:28,559 Speaker 5: one extra year before price negotiations by Medicare, and that's 139 00:07:28,680 --> 00:07:33,520 Speaker 5: a twenty thirty billion dollar drug selling something like fifty 140 00:07:33,520 --> 00:07:35,960 Speaker 5: percent of his revenues in the US. That's a huge 141 00:07:36,000 --> 00:07:37,000 Speaker 5: win for the industry. 142 00:07:37,800 --> 00:07:39,520 Speaker 4: Sam, I'm looking at some of the bigger names, the 143 00:07:39,560 --> 00:07:41,680 Speaker 4: Mark down eighteen percent, and you know some of these 144 00:07:41,720 --> 00:07:45,640 Speaker 4: other names, the big farmer companies, Bristol Meyers down seventeen percent. 145 00:07:45,720 --> 00:07:47,360 Speaker 4: Is the markets? What's that reflect? 146 00:07:47,400 --> 00:07:47,480 Speaker 5: That? 147 00:07:47,560 --> 00:07:50,160 Speaker 6: Just uncertainty around trade, around teriffs. 148 00:07:51,560 --> 00:07:53,840 Speaker 5: All of it. So on the one hand, we've got 149 00:07:53,880 --> 00:07:56,120 Speaker 5: this positive. On the other hand, we have two big 150 00:07:56,160 --> 00:08:01,160 Speaker 5: things hanging over the farmer industry in general. One is 151 00:08:01,200 --> 00:08:05,080 Speaker 5: the tariffs, sectoral tariffs that are still being discussed. We 152 00:08:05,160 --> 00:08:08,360 Speaker 5: don't know yet. This is to try and incentivize companies 153 00:08:08,640 --> 00:08:11,920 Speaker 5: to bring their products to a manufacturing into the US 154 00:08:12,000 --> 00:08:14,040 Speaker 5: if they want to sell in the US market, et cetera. 155 00:08:14,560 --> 00:08:17,360 Speaker 5: If we did hear that perhaps in the trade deal 156 00:08:17,440 --> 00:08:21,160 Speaker 5: with the Switzerland they're giving a special dispensation for the 157 00:08:21,160 --> 00:08:24,280 Speaker 5: Swiss farmer companies rash and no artists and their shore 158 00:08:24,320 --> 00:08:26,840 Speaker 5: prices were up. But we don't know. We haven't seen 159 00:08:26,840 --> 00:08:29,560 Speaker 5: this trade deal yet. And then you've got the most 160 00:08:29,560 --> 00:08:33,520 Speaker 5: favored nation, which is the one that's particularly draconian, and 161 00:08:33,600 --> 00:08:35,719 Speaker 5: that is to say that whatever price do you want 162 00:08:35,760 --> 00:08:38,720 Speaker 5: to charge in the US, it's got to be closer 163 00:08:38,720 --> 00:08:42,760 Speaker 5: to the lower end of companies with a similar GDP 164 00:08:43,080 --> 00:08:47,080 Speaker 5: or something in the West. So that really is where 165 00:08:47,160 --> 00:08:49,840 Speaker 5: I think the biggest problem is we haven't heard anything, 166 00:08:50,120 --> 00:08:53,120 Speaker 5: but that's still under discussion and under consideration. Might be 167 00:08:53,160 --> 00:08:55,520 Speaker 5: another six to nine months before we hear anything. 168 00:08:55,880 --> 00:09:00,480 Speaker 4: Sam Another big I guess component of this administration policy 169 00:09:00,520 --> 00:09:02,960 Speaker 4: has been cutting funding or maybe threatening the cut funding 170 00:09:03,559 --> 00:09:07,320 Speaker 4: for research universities. And I have long experience with Duke University, 171 00:09:07,320 --> 00:09:12,120 Speaker 4: which is a huge medical center and research area. Here's 172 00:09:12,280 --> 00:09:14,800 Speaker 4: what's your industry saying about those potential cuts. 173 00:09:16,000 --> 00:09:19,280 Speaker 5: Yeah, the industry itself is relatively quiet, Paul, because what 174 00:09:19,320 --> 00:09:22,079 Speaker 5: they don't want to do is is, I don't know 175 00:09:22,120 --> 00:09:24,720 Speaker 5: whether the right phrases here, shake the target, tiger's cage 176 00:09:24,800 --> 00:09:28,760 Speaker 5: or whatever, you know, rattle the whole set here. But 177 00:09:29,240 --> 00:09:32,240 Speaker 5: in reality, there is a I think what I heard 178 00:09:32,240 --> 00:09:36,400 Speaker 5: the last number was a twelve percent increase in applications 179 00:09:36,400 --> 00:09:39,720 Speaker 5: to some of the top universities in Europe versus what 180 00:09:39,800 --> 00:09:43,960 Speaker 5: they were last year from the US. So that's folks 181 00:09:43,960 --> 00:09:46,400 Speaker 5: that would have gone to or wanted to go to Harvard, 182 00:09:46,559 --> 00:09:49,920 Speaker 5: they're now looking at Oxford, Cambridge, Siance, Pool, et cetera, 183 00:09:50,080 --> 00:09:53,199 Speaker 5: these very brilliant universities across Europe. So there's that issue. 184 00:09:53,280 --> 00:09:57,520 Speaker 5: But remember in the OBBB there's also another area where 185 00:09:57,559 --> 00:10:00,600 Speaker 5: there is a cup to mediciate spending. That's a million 186 00:10:00,679 --> 00:10:04,280 Speaker 5: Medicaid covered folks that lose it. That will also have 187 00:10:04,400 --> 00:10:08,720 Speaker 5: repercussions for pharma companies, healthcare in general. And of course 188 00:10:08,760 --> 00:10:11,480 Speaker 5: you go to a hospital you don't have insurance, they're 189 00:10:11,480 --> 00:10:13,360 Speaker 5: going to treat you. Who's going to pay for that? 190 00:10:13,480 --> 00:10:15,920 Speaker 5: It's going to go on your premium. There's a tax 191 00:10:16,000 --> 00:10:19,280 Speaker 5: on you, you know, let's see how this all pans out. 192 00:10:19,320 --> 00:10:20,920 Speaker 5: But not good there either. 193 00:10:21,240 --> 00:10:23,960 Speaker 2: All right, Sam, I want to talk about the Medicaid cuts. 194 00:10:24,080 --> 00:10:25,559 Speaker 2: I'm going to kind of put you on the spot there, 195 00:10:25,600 --> 00:10:29,559 Speaker 2: but it's going to affect insurers who focus on Medicaid. 196 00:10:29,559 --> 00:10:32,080 Speaker 2: They might lose customers. So what does this mean for like, 197 00:10:32,160 --> 00:10:35,480 Speaker 2: let's say Elevant's Health, United Health companies that do deal 198 00:10:35,520 --> 00:10:35,800 Speaker 2: with this. 199 00:10:37,120 --> 00:10:39,880 Speaker 5: Yeah, so they are clearly under pressure and there's a 200 00:10:39,960 --> 00:10:43,120 Speaker 5: risk for them. And one of the issues is exactly 201 00:10:43,120 --> 00:10:47,440 Speaker 5: what you just said. You know, this is completely upsetting 202 00:10:47,440 --> 00:10:50,880 Speaker 5: the card here for the insurance in general. The point is, 203 00:10:51,600 --> 00:10:54,280 Speaker 5: I'm not convinced that they will necessarily lose out. I mean, 204 00:10:55,200 --> 00:10:58,319 Speaker 5: we have dedicated expert analysts who cover the sector, et cetera. 205 00:10:58,840 --> 00:11:01,440 Speaker 5: But usually what's going to happen is that if they're 206 00:11:01,440 --> 00:11:03,640 Speaker 5: not making money elsewhere, they're going to try and raise 207 00:11:03,640 --> 00:11:06,200 Speaker 5: premium somewhere else, which is what I said to start with, 208 00:11:06,600 --> 00:11:10,000 Speaker 5: that there will be a way that they'll get through this. 209 00:11:10,960 --> 00:11:13,000 Speaker 5: But clearly uncertainty in the new time. 210 00:11:13,520 --> 00:11:14,800 Speaker 6: There's that word again, uncertainty. 211 00:11:14,840 --> 00:11:17,040 Speaker 4: We heard her so many times the day across so 212 00:11:17,040 --> 00:11:19,959 Speaker 4: many different industries. Sam Fazelli, thanks so much for your time. 213 00:11:19,960 --> 00:11:22,439 Speaker 4: Always appreciate checking in with you. Sam Fazzelli. He's a 214 00:11:22,440 --> 00:11:26,440 Speaker 4: director of Research for Global Industries, Senior Pharmaceuticals and Senior 215 00:11:26,480 --> 00:11:28,520 Speaker 4: Wine analyst for Bloomberg Intelligence. 216 00:11:28,559 --> 00:11:31,120 Speaker 6: Based over there in London. 217 00:11:32,880 --> 00:11:36,600 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 218 00:11:36,679 --> 00:11:39,720 Speaker 1: weekdays at ten am Eastern on Apple, Coarclay and Android 219 00:11:39,760 --> 00:11:43,079 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 220 00:11:43,120 --> 00:11:46,280 Speaker 1: you get your podcasts, or watch us live on YouTube. 221 00:11:46,640 --> 00:11:48,200 Speaker 2: All right, we're going to shift gears now. I want 222 00:11:48,240 --> 00:11:50,640 Speaker 2: to take us to honorad Rona. He is Bloomberg Intelligence 223 00:11:50,679 --> 00:11:56,000 Speaker 2: Technology analyst corwe That is the big headline buying Core Scientific. 224 00:11:56,080 --> 00:11:59,160 Speaker 2: It's an all stock transaction, an rog. I want to 225 00:11:59,200 --> 00:12:01,480 Speaker 2: bring you in and talk about this for core Weve. 226 00:12:01,559 --> 00:12:03,520 Speaker 2: What is the benefit from this? What do they gain 227 00:12:03,559 --> 00:12:03,840 Speaker 2: from this? 228 00:12:05,280 --> 00:12:08,080 Speaker 7: Mean, think about it that they have capacity to process 229 00:12:08,120 --> 00:12:10,880 Speaker 7: ex summer of transactions or the backlock that they have 230 00:12:11,520 --> 00:12:14,400 Speaker 7: with this particular deal, they are expanding their infrastructure. 231 00:12:14,440 --> 00:12:15,720 Speaker 5: I mean it's a very simple deal. 232 00:12:15,800 --> 00:12:18,000 Speaker 7: As if you know, they're just buying more factories to 233 00:12:18,080 --> 00:12:20,920 Speaker 7: produce what they do. So is you know, it's it's 234 00:12:21,080 --> 00:12:21,880 Speaker 7: as simple as that. 235 00:12:22,400 --> 00:12:23,000 Speaker 6: All right, So this. 236 00:12:23,240 --> 00:12:27,800 Speaker 4: I'm not a tech person, so, but I know, tell 237 00:12:27,880 --> 00:12:30,880 Speaker 4: us what Core We've is, what do they do and 238 00:12:30,920 --> 00:12:33,520 Speaker 4: why are they shouting out nine billion dollars to get bigger? 239 00:12:33,559 --> 00:12:35,199 Speaker 6: I guess yeah. 240 00:12:35,280 --> 00:12:38,120 Speaker 7: So in the purest of pure forms, they are just 241 00:12:38,280 --> 00:12:41,640 Speaker 7: renting computing resources to anybody that wants to run an 242 00:12:41,640 --> 00:12:42,640 Speaker 7: AI infrastructure. 243 00:12:42,880 --> 00:12:44,559 Speaker 5: They are a very big Invidia shop. 244 00:12:44,640 --> 00:12:48,319 Speaker 7: They basically buy GPUs from Invidia, They create a network 245 00:12:48,400 --> 00:12:50,640 Speaker 7: or an infrastructure, and they give it to people to 246 00:12:50,679 --> 00:12:53,440 Speaker 7: go out and experiment or do whatever they need to 247 00:12:53,440 --> 00:12:56,800 Speaker 7: do on that infrastructure. It's no different than what AWS does, 248 00:12:57,160 --> 00:13:00,520 Speaker 7: but very heavy focus on GPUs rather than the CPO. 249 00:13:00,640 --> 00:13:03,240 Speaker 7: So that's really the big difference between a pure play 250 00:13:03,720 --> 00:13:06,600 Speaker 7: provider like Core Weve versus Amazon Web Services. 251 00:13:06,880 --> 00:13:09,240 Speaker 2: Now, if you can dig into some of the background, 252 00:13:09,240 --> 00:13:12,040 Speaker 2: what kind of challenges has has Core We've had in 253 00:13:12,080 --> 00:13:14,360 Speaker 2: the past. I mean, didn't they have a pretty dismal IPO. 254 00:13:15,400 --> 00:13:15,600 Speaker 5: Yeah. 255 00:13:15,679 --> 00:13:18,200 Speaker 7: I think that's really the most important thing is, you know, 256 00:13:18,280 --> 00:13:20,959 Speaker 7: they everybody thought when they're going to come out as 257 00:13:20,960 --> 00:13:24,280 Speaker 7: the first pure play you know AI infrastructure IPO, it's 258 00:13:24,320 --> 00:13:27,320 Speaker 7: going to be extremely popular, but it didn't happen. And 259 00:13:27,320 --> 00:13:30,360 Speaker 7: the reason for that is because they need a large 260 00:13:30,400 --> 00:13:33,839 Speaker 7: amount of upfront capital to build these data centers, and 261 00:13:33,920 --> 00:13:35,560 Speaker 7: then the workload comes in over the. 262 00:13:35,600 --> 00:13:36,480 Speaker 5: Next several years. 263 00:13:36,600 --> 00:13:39,280 Speaker 7: So there's a lot of questions about whether there's going 264 00:13:39,280 --> 00:13:42,959 Speaker 7: to be sustainability of this GPU demand going forward several 265 00:13:43,040 --> 00:13:45,680 Speaker 7: years out. So that's why you were right. The IPO 266 00:13:45,720 --> 00:13:47,840 Speaker 7: came at forty. In a few days, it was down 267 00:13:47,880 --> 00:13:50,200 Speaker 7: to thirty five. But now we're seeing you know, the 268 00:13:50,240 --> 00:13:53,280 Speaker 7: stock closer won sixty before this deal was announced, so 269 00:13:53,559 --> 00:13:55,360 Speaker 7: I you know, we have talked about it before that. 270 00:13:55,480 --> 00:13:57,640 Speaker 7: You know, why aren't they doing a secondary when it's 271 00:13:57,679 --> 00:13:59,480 Speaker 7: like one hundred and sixty blucks stocks of what they 272 00:13:59,520 --> 00:14:02,040 Speaker 7: did instead? It is they use their stock to go 273 00:14:02,120 --> 00:14:04,840 Speaker 7: out and buy another competitor I should say competitor, but 274 00:14:05,320 --> 00:14:07,960 Speaker 7: you know, another company in that space, so that it 275 00:14:08,040 --> 00:14:10,840 Speaker 7: expands their capacity, and you know, I think they're doing 276 00:14:10,880 --> 00:14:12,880 Speaker 7: the right thing by using stock at this point. 277 00:14:13,080 --> 00:14:15,760 Speaker 4: Are there more core weaves out there on a round 278 00:14:16,280 --> 00:14:20,720 Speaker 4: kind of more pure play AI stories, maybe the kind 279 00:14:20,760 --> 00:14:23,880 Speaker 4: of the sausage of AI if you will, the guts 280 00:14:24,680 --> 00:14:26,440 Speaker 4: that somebody could take public. 281 00:14:27,480 --> 00:14:29,920 Speaker 7: There are multiples of them there, but they are much 282 00:14:29,920 --> 00:14:32,920 Speaker 7: smaller size in korby they I would say there would 283 00:14:32,920 --> 00:14:35,360 Speaker 7: be hundreds of them at this point, because you know, 284 00:14:35,400 --> 00:14:37,560 Speaker 7: you go out, you buy the GPU, you go out 285 00:14:37,600 --> 00:14:40,040 Speaker 7: and start renting it out in the in you know, 286 00:14:40,080 --> 00:14:42,520 Speaker 7: in a long time ago, this high powered computing was 287 00:14:42,720 --> 00:14:45,760 Speaker 7: used for bitcoin mining, and then you know, when that's 288 00:14:45,800 --> 00:14:48,720 Speaker 7: not in favor, these guys are renting out their infrastructure 289 00:14:48,720 --> 00:14:51,600 Speaker 7: for other reasons. So there are other plays out there, 290 00:14:51,640 --> 00:14:54,560 Speaker 7: but almost all of them are much smaller than core 291 00:14:54,640 --> 00:14:56,840 Speaker 7: Viv from a you know, pure play point of view. 292 00:14:57,040 --> 00:15:00,560 Speaker 2: Now we digged into corewey, what about Core Scientific, what's 293 00:15:00,600 --> 00:15:03,080 Speaker 2: the attraction to them? 294 00:15:03,280 --> 00:15:05,400 Speaker 7: I mean, it's just they're expanding the number of you know, 295 00:15:05,440 --> 00:15:08,640 Speaker 7: the capacity that they have to process the transactions. In 296 00:15:08,680 --> 00:15:11,640 Speaker 7: a sense that Corvieve is a massive backlock right now 297 00:15:11,680 --> 00:15:14,520 Speaker 7: they have people wanting to use their services, and then 298 00:15:14,560 --> 00:15:16,440 Speaker 7: these guys have to go out and lease it from 299 00:15:16,680 --> 00:15:19,600 Speaker 7: you know, other companies like our Scientific In this case, 300 00:15:19,600 --> 00:15:21,560 Speaker 7: they said, you know, they have an agreement with them 301 00:15:21,840 --> 00:15:25,080 Speaker 7: to lease their facilities. They just said, you know, we'll 302 00:15:25,120 --> 00:15:27,440 Speaker 7: buy it out and expand their size. And I think 303 00:15:27,480 --> 00:15:28,560 Speaker 7: that's as simple as that. 304 00:15:28,960 --> 00:15:31,440 Speaker 4: And I think I have to point out Lisa core 305 00:15:31,520 --> 00:15:34,200 Speaker 4: Weave based in Livingston, New New Jersey. 306 00:15:34,280 --> 00:15:36,880 Speaker 6: Yes, so it just goes to my folks. 307 00:15:36,840 --> 00:15:40,040 Speaker 4: A little history lesson. Before there was Silicon Valley, there 308 00:15:40,080 --> 00:15:43,240 Speaker 4: was New Jersey. There was Central Jersey, the Institute for 309 00:15:43,320 --> 00:15:48,240 Speaker 4: Advanced Study, Princeton University, Menlo Park, New Jersey. Before there's 310 00:15:48,240 --> 00:15:50,680 Speaker 4: a Menlo Park, California, Menlo. Before there's a sand Hill 311 00:15:50,800 --> 00:15:53,280 Speaker 4: road in Silicon Valley, there's a sand Hill. 312 00:15:53,200 --> 00:15:56,160 Speaker 6: Road in Jersey. So it all, there's all these Jersey 313 00:15:56,160 --> 00:15:58,960 Speaker 6: guys went on New Jersey is back in New Jersey. 314 00:15:59,040 --> 00:16:00,880 Speaker 6: All right, an, thank you so much. We appreciate it. 315 00:16:00,920 --> 00:16:04,280 Speaker 4: On a rock ron Eastern technologyannels for Bloomberg Intelligence. He's 316 00:16:04,280 --> 00:16:07,360 Speaker 4: in at Chicago. You're trying to establish Chicago as a 317 00:16:07,440 --> 00:16:08,600 Speaker 4: technology hub. 318 00:16:08,640 --> 00:16:09,840 Speaker 6: Here. 319 00:16:10,600 --> 00:16:14,280 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 320 00:16:14,400 --> 00:16:17,480 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 321 00:16:17,480 --> 00:16:20,800 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 322 00:16:20,840 --> 00:16:24,000 Speaker 1: you get your podcasts, or watch us live on YouTube. 323 00:16:24,600 --> 00:16:27,240 Speaker 2: We want to move on now to the latest TikTok news. 324 00:16:27,280 --> 00:16:29,800 Speaker 2: We're going to bring a man deep saying Bloomberg Intelligence 325 00:16:29,800 --> 00:16:32,960 Speaker 2: senior tech industry analysts. Okay, so Mandy, President Trump getting 326 00:16:32,960 --> 00:16:35,080 Speaker 2: ready to begin talks with China. About a possible TikTok 327 00:16:35,120 --> 00:16:37,840 Speaker 2: deal to sell the app. Want to ask you, where 328 00:16:37,880 --> 00:16:39,040 Speaker 2: do we stand in this right now? 329 00:16:39,080 --> 00:16:39,880 Speaker 6: What is the latest? 330 00:16:40,480 --> 00:16:43,520 Speaker 8: I mean, from what we know, President Trump is pretty 331 00:16:43,560 --> 00:16:46,720 Speaker 8: confident that there is a buyer. In fact, there could 332 00:16:46,720 --> 00:16:51,360 Speaker 8: be private equity buyers at Consortium who may be interested 333 00:16:51,440 --> 00:16:55,760 Speaker 8: in buying TikTok us. And at this point, you know, 334 00:16:55,920 --> 00:16:58,080 Speaker 8: they want to make sure that it goes through in 335 00:16:58,160 --> 00:17:01,280 Speaker 8: terms of getting the approval from China. But in the 336 00:17:01,360 --> 00:17:06,000 Speaker 8: process they've launched a new app, TikTok Has, and that 337 00:17:06,440 --> 00:17:09,840 Speaker 8: sort of suggests they want to decouple the algorithm from 338 00:17:09,880 --> 00:17:13,960 Speaker 8: the core TikTok usage. So that was also a point 339 00:17:14,000 --> 00:17:18,040 Speaker 8: of contention in terms of getting the approval. So I 340 00:17:18,080 --> 00:17:20,960 Speaker 8: think the two go hand in hand, that one there 341 00:17:21,000 --> 00:17:23,840 Speaker 8: is a buyer available and the other the app is 342 00:17:23,920 --> 00:17:26,720 Speaker 8: getting a changeover in terms of decoupling the algorithm. 343 00:17:26,720 --> 00:17:29,960 Speaker 4: All right, So am I going to have effectively two 344 00:17:30,080 --> 00:17:33,600 Speaker 4: tiktoks out there? The TikTok app we all know and love, 345 00:17:34,480 --> 00:17:37,320 Speaker 4: and then something that they are doubling internally is M two. 346 00:17:38,680 --> 00:17:42,760 Speaker 4: So now there's gonna be two effective TikTok apps out 347 00:17:42,760 --> 00:17:43,679 Speaker 4: there for all these people. 348 00:17:44,160 --> 00:17:49,720 Speaker 8: Yes, and look with apps, there's always like a date 349 00:17:49,800 --> 00:17:54,199 Speaker 8: when the first app will obviously be phased out and 350 00:17:54,800 --> 00:17:57,280 Speaker 8: folks won't have access to it. I mean, remember what 351 00:17:57,400 --> 00:18:01,240 Speaker 8: happened during the band you know that wasn't even available. 352 00:18:01,320 --> 00:18:04,240 Speaker 8: So in this case, the plan is if and when 353 00:18:04,280 --> 00:18:08,240 Speaker 8: the deal gets announced and the new TikTok owner which 354 00:18:08,359 --> 00:18:11,200 Speaker 8: we don't know who will be ye, will get access 355 00:18:11,200 --> 00:18:13,800 Speaker 8: to the new app, and then the first one gets 356 00:18:13,800 --> 00:18:14,320 Speaker 8: paced down. 357 00:18:14,960 --> 00:18:18,040 Speaker 2: All right, So my kids want to know, asking, okay, 358 00:18:18,400 --> 00:18:21,440 Speaker 2: is there any chance of none of this going through, 359 00:18:21,560 --> 00:18:25,080 Speaker 2: like just TikTok disappearing from the US in general, they'd 360 00:18:25,080 --> 00:18:27,080 Speaker 2: be devastated, Mandy. 361 00:18:27,400 --> 00:18:30,080 Speaker 8: Look, it happened for two days, the app went dark, 362 00:18:30,280 --> 00:18:33,359 Speaker 8: and at that time Instagram got a very nice pop 363 00:18:33,440 --> 00:18:38,080 Speaker 8: in terms of engagement. So from that perspective, this will 364 00:18:38,119 --> 00:18:41,960 Speaker 8: be all positive news for a meta snapchat or you know, 365 00:18:42,160 --> 00:18:45,639 Speaker 8: even if dual lingo was mentioned as a beneficiary of 366 00:18:46,400 --> 00:18:49,080 Speaker 8: app and dark. Yeah, I know, it's all very intuitive, 367 00:18:49,119 --> 00:18:51,800 Speaker 8: but it did happen. In the data you could see 368 00:18:51,840 --> 00:18:54,560 Speaker 8: for those two days, duel Lingo did get a pop 369 00:18:54,600 --> 00:18:56,160 Speaker 8: in the engagement time. 370 00:18:56,280 --> 00:18:56,680 Speaker 6: All right. 371 00:18:56,800 --> 00:18:58,880 Speaker 4: I mean, you gotta spend your time somehow, go forbid 372 00:18:58,960 --> 00:19:04,439 Speaker 4: reading a book says the father. You know, Okay, so China. 373 00:19:04,480 --> 00:19:07,240 Speaker 4: If I'm China, what's my incentive to approve a sale 374 00:19:07,320 --> 00:19:11,560 Speaker 4: to say, a group maybe including some like an Oracle, 375 00:19:11,600 --> 00:19:12,440 Speaker 4: what's my incentive? 376 00:19:13,040 --> 00:19:16,159 Speaker 8: The incentive is it's the President of the United States 377 00:19:16,240 --> 00:19:20,679 Speaker 8: who is negotiating the deal, you know. And this is 378 00:19:20,760 --> 00:19:23,919 Speaker 8: part of a much bigger conversation when it comes to 379 00:19:24,000 --> 00:19:29,560 Speaker 8: China tariffs and everything that they are negotiating. So TikTok 380 00:19:29,640 --> 00:19:32,960 Speaker 8: deal to me, is part of that bigger negotiation now, 381 00:19:33,240 --> 00:19:36,760 Speaker 8: and President Trump is obviously keen to have a deal 382 00:19:36,840 --> 00:19:39,439 Speaker 8: for TikTok Us. He doesn't want the app to be banned, 383 00:19:39,680 --> 00:19:42,920 Speaker 8: and as part of that, he wants some concessions on 384 00:19:42,960 --> 00:19:45,000 Speaker 8: the tariff front. So to me, this is part of 385 00:19:45,040 --> 00:19:46,280 Speaker 8: a much bigger negotiation. 386 00:19:46,720 --> 00:19:49,280 Speaker 2: Now you mentioned Oracle, it's Oracle, the only name being 387 00:19:49,280 --> 00:19:49,919 Speaker 2: thrown around. 388 00:19:50,080 --> 00:19:52,880 Speaker 8: They are the trusted one when it comes to Washington. 389 00:19:53,359 --> 00:19:56,720 Speaker 8: They are among all the hyperscalers. I think they get 390 00:19:56,800 --> 00:19:59,760 Speaker 8: the trust of the President in terms of moving. 391 00:19:59,520 --> 00:20:01,600 Speaker 2: Ahead with what's the drug? Why Oracle? 392 00:20:01,960 --> 00:20:07,160 Speaker 8: Well, Oracle clearly hosts all the back end infrastructure for TikTok, 393 00:20:07,600 --> 00:20:09,480 Speaker 8: So this has been going on a while and they 394 00:20:09,520 --> 00:20:13,680 Speaker 8: have moved all the back end infrastructure to Oracles platform, 395 00:20:14,080 --> 00:20:17,159 Speaker 8: and they clearly have some sort of synergy when it 396 00:20:17,200 --> 00:20:20,720 Speaker 8: comes to hosting that making sure nothing gets saved in 397 00:20:21,600 --> 00:20:25,080 Speaker 8: Chinese data centers and none of the data gets transferred there. 398 00:20:25,160 --> 00:20:27,320 Speaker 8: So I think they're in the best position to do. 399 00:20:27,280 --> 00:20:30,680 Speaker 4: That thirty seconds. Any sense of timing when this could happen. 400 00:20:31,440 --> 00:20:35,240 Speaker 8: It sounded like President Trump is confident about this happening 401 00:20:35,640 --> 00:20:38,040 Speaker 8: over the course of the next ninety days, because remember 402 00:20:38,080 --> 00:20:40,520 Speaker 8: he extended the band by another ninety days, so to 403 00:20:40,640 --> 00:20:41,840 Speaker 8: do that, that would be my guest. 404 00:20:41,920 --> 00:20:43,200 Speaker 4: All right, Man Deep, thank you so much. 405 00:20:43,240 --> 00:20:43,800 Speaker 6: Appreciate that. 406 00:20:43,880 --> 00:20:47,280 Speaker 4: Man Deep, seeing senior tech industry anust, I can't imagine 407 00:20:47,320 --> 00:20:50,679 Speaker 4: he's on TikTok, but you never know Bloomberg Intelligence learnings 408 00:20:50,680 --> 00:20:52,879 Speaker 4: here in our Bloomberg Interactive Broker studio at Lisa. 409 00:20:52,920 --> 00:20:54,000 Speaker 6: Are you a TikToker? 410 00:20:54,080 --> 00:20:56,560 Speaker 2: I am not, but I will Actually I take that back, 411 00:20:56,640 --> 00:20:58,879 Speaker 2: I am because I have to follow my kids to 412 00:20:58,880 --> 00:21:01,199 Speaker 2: make sure to spy on them, you know, so I 413 00:21:01,240 --> 00:21:01,800 Speaker 2: have to join in. 414 00:21:02,040 --> 00:21:04,160 Speaker 4: All right, all right, I don't know, and it's it's 415 00:21:04,200 --> 00:21:07,959 Speaker 4: big for one hundred and seventy million US users. 416 00:21:08,720 --> 00:21:12,720 Speaker 6: I know, I know exactly. He's all over that stuff. 417 00:21:13,280 --> 00:21:17,960 Speaker 1: This is the Bloomberg Intelligence Podcast, available on Apple, Spotify, 418 00:21:18,160 --> 00:21:22,120 Speaker 1: and anywhere else you get your podcasts. Listen live each weekday, 419 00:21:22,320 --> 00:21:25,600 Speaker 1: ten am to noon Eastern on Bloomberg dot com, the 420 00:21:25,680 --> 00:21:29,560 Speaker 1: iHeartRadio app, tune In, and the Bloomberg Business app. You 421 00:21:29,600 --> 00:21:32,879 Speaker 1: can also watch us live every weekday on YouTube and 422 00:21:33,119 --> 00:21:35,040 Speaker 1: always on the Bloomberg Terminal