1 00:00:00,240 --> 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 --> 00:00:18,520 Speaker 1: Eastern on Applecarplay and Android Auto with the Bloomberg Business App. 4 00:00:18,640 --> 00:00:21,840 Speaker 1: Listen on demand wherever you get your podcasts, or watch 5 00:00:21,960 --> 00:00:23,080 Speaker 1: us live on YouTube. 6 00:00:23,760 --> 00:00:26,040 Speaker 2: I did not have Universal Music Group being put in 7 00:00:26,040 --> 00:00:28,960 Speaker 2: play on my being a car but billionaire activist Bill Ackman, 8 00:00:29,480 --> 00:00:32,159 Speaker 2: I mean, I poled that thing, bought it, sold it. 9 00:00:32,760 --> 00:00:34,960 Speaker 2: I don't know why it's public. Billionaire activist Bill Ackman 10 00:00:34,960 --> 00:00:38,760 Speaker 2: has proposed a bid for Universal Music Group to increase 11 00:00:38,800 --> 00:00:41,479 Speaker 2: returns on one of his hedge fund's biggest holdings. Not 12 00:00:41,520 --> 00:00:44,080 Speaker 2: really sure why, but our next guest does. Matthew Bloxham, 13 00:00:44,159 --> 00:00:46,960 Speaker 2: Senior Media and Tech anais Bloomberg Intelligence is usually based 14 00:00:46,960 --> 00:00:49,360 Speaker 2: in London, but he's here in New York, which goes 15 00:00:49,400 --> 00:00:51,720 Speaker 2: to my theory. Yes, we're seeing a lot of London 16 00:00:51,720 --> 00:00:55,000 Speaker 2: based VI people here, which means somebody's buying these people dinner. 17 00:00:55,160 --> 00:00:56,600 Speaker 2: Would not come a number of their own. 18 00:00:56,760 --> 00:00:58,640 Speaker 3: I think we should swamp. I'll go to London for 19 00:00:58,680 --> 00:00:59,840 Speaker 3: a while and do the show from there. 20 00:01:00,120 --> 00:01:03,560 Speaker 2: Matthew tell us what's going on here with United Music 21 00:01:03,600 --> 00:01:05,520 Speaker 2: group and kind of what Blackman's thinking. 22 00:01:06,080 --> 00:01:08,560 Speaker 4: Yes, look, I think a lot of shareholder has been 23 00:01:08,600 --> 00:01:12,200 Speaker 4: frustrated for quite some time with the share price performance 24 00:01:12,440 --> 00:01:16,280 Speaker 4: Universal Music. The numbers it's been posting performance wise have 25 00:01:16,360 --> 00:01:19,959 Speaker 4: been pretty decent, but the share price keeps going down. 26 00:01:19,959 --> 00:01:21,520 Speaker 4: And I think, I mean, I've had a lot of 27 00:01:21,520 --> 00:01:23,759 Speaker 4: incoming a requires some clients over the last no, three 28 00:01:23,840 --> 00:01:26,360 Speaker 4: or four months trying to kind of put this puzzle together. 29 00:01:26,400 --> 00:01:28,160 Speaker 4: You know that the numbers look good, the share price 30 00:01:28,240 --> 00:01:30,320 Speaker 4: going down. What's going on? And I think to some 31 00:01:30,400 --> 00:01:34,120 Speaker 4: degree this is Bill Lackman, you know, expressing some public 32 00:01:34,200 --> 00:01:39,080 Speaker 4: frustration about that kind of mismatch and trying to, I guess, 33 00:01:39,160 --> 00:01:43,959 Speaker 4: propose a different future for Universal Music, but particularly kind 34 00:01:43,959 --> 00:01:47,960 Speaker 4: of a more financially engineered future, so kind of sweating 35 00:01:48,200 --> 00:01:50,360 Speaker 4: the balance sheet more, pushing leveragere two and a half 36 00:01:50,400 --> 00:01:56,080 Speaker 4: times from one times, doing more buybacks, selling their stake 37 00:01:56,120 --> 00:01:58,160 Speaker 4: in Spotify, just to kind of really crystallize some of 38 00:01:58,160 --> 00:02:00,640 Speaker 4: the value that is there now. 39 00:02:00,680 --> 00:02:03,600 Speaker 3: For what I understand this is it's sort of a 40 00:02:03,640 --> 00:02:07,320 Speaker 3: complicated proposal they're putting together here that involves I guess 41 00:02:07,360 --> 00:02:10,720 Speaker 3: a spack here in the US valuing the company. I 42 00:02:10,760 --> 00:02:12,840 Speaker 3: guess it close to sixty five billion dollars. Is that 43 00:02:12,880 --> 00:02:14,919 Speaker 3: truly a seventy eight percent premium? 44 00:02:15,360 --> 00:02:17,040 Speaker 4: It would be, but it's very much a kind of 45 00:02:17,160 --> 00:02:20,880 Speaker 4: paper premium. So if you look at the numbers, basically 46 00:02:20,880 --> 00:02:23,680 Speaker 4: what they've said is that on the twenty twenty six earnings, 47 00:02:23,960 --> 00:02:27,000 Speaker 4: they think Universal Music should trade at about twenty five 48 00:02:27,040 --> 00:02:29,800 Speaker 4: times earnings. It currently trades on about seventeen. And so 49 00:02:29,840 --> 00:02:33,320 Speaker 4: they've applied that mole score to the earnings, creative everything 50 00:02:33,720 --> 00:02:35,799 Speaker 4: else out of that. So kind of really there's there's 51 00:02:35,880 --> 00:02:38,040 Speaker 4: kind of nothing substantial there. It's not that there is 52 00:02:38,080 --> 00:02:40,640 Speaker 4: an element of cash to the bit, but it's not 53 00:02:40,880 --> 00:02:43,359 Speaker 4: very much, and most of that cash is basically being 54 00:02:43,400 --> 00:02:46,960 Speaker 4: funded by leveraging up the UMG balance sheet and by 55 00:02:47,000 --> 00:02:48,160 Speaker 4: selling the Spotify steake. 56 00:02:48,360 --> 00:02:50,679 Speaker 3: Well, then I wonder how real is this or is 57 00:02:50,680 --> 00:02:52,360 Speaker 3: this just is he throwing it out there to shake 58 00:02:52,400 --> 00:02:54,200 Speaker 3: things up or can this thing really happen? 59 00:02:54,520 --> 00:02:57,120 Speaker 4: I think he's throwing it out there to shape things up. 60 00:02:57,320 --> 00:02:59,519 Speaker 4: And I think what we would expect to see from 61 00:02:59,520 --> 00:03:02,919 Speaker 4: the company is perhaps, you know, kind of an acknowledgement 62 00:03:03,160 --> 00:03:05,560 Speaker 4: that you know that there's more perhaps they could do 63 00:03:05,919 --> 00:03:08,960 Speaker 4: to kind of crystallize the value and get it recognized 64 00:03:09,000 --> 00:03:09,639 Speaker 4: in markets. 65 00:03:10,360 --> 00:03:12,320 Speaker 5: But we'll see. I mean, obviously that the big. 66 00:03:12,040 --> 00:03:17,639 Speaker 4: Fundamental risk to universal music, which is keeping that earning 67 00:03:18,000 --> 00:03:21,520 Speaker 4: multiple down, is AI and whether in future we're going 68 00:03:21,600 --> 00:03:25,400 Speaker 4: to be fans of real human artists fans. 69 00:03:26,240 --> 00:03:29,799 Speaker 2: Sell Oh yeah, yeah, all right, we've got some big 70 00:03:29,840 --> 00:03:31,639 Speaker 2: shareholders here. I'm going to go back to an old 71 00:03:31,880 --> 00:03:34,880 Speaker 2: acquaintance mind, Vincent Belory. What does he want to do 72 00:03:34,920 --> 00:03:36,760 Speaker 2: with the stocking? It was eighteen percent of the stock here, 73 00:03:36,800 --> 00:03:40,080 Speaker 2: and I know there's always been concerned in this company 74 00:03:40,120 --> 00:03:42,840 Speaker 2: and in other companies. He has holdings that he's a seller, 75 00:03:42,840 --> 00:03:44,360 Speaker 2: he's a better seller here, and that could keep a 76 00:03:44,400 --> 00:03:45,000 Speaker 2: lid on this thing. 77 00:03:45,120 --> 00:03:48,440 Speaker 4: Yeah, that's certainly been a bit of an overhang. I'd 78 00:03:48,480 --> 00:03:51,080 Speaker 4: be surprised at this level he's a seller, and it's 79 00:03:51,120 --> 00:03:53,120 Speaker 4: even more complished than that, because fora Vendi, you know, 80 00:03:53,120 --> 00:03:55,160 Speaker 4: owns the stake in it, and he's the kind of 81 00:03:55,160 --> 00:03:58,800 Speaker 4: most influential shareholder in Forvendy two. So yeah, you know, obviously, 82 00:03:58,840 --> 00:04:02,040 Speaker 4: I think he's probably playing a longer term game, kind 83 00:04:02,040 --> 00:04:04,800 Speaker 4: of wants to get value cristicization at some point, But 84 00:04:04,880 --> 00:04:07,320 Speaker 4: he's not the kind of person to be pressurized into 85 00:04:07,320 --> 00:04:10,200 Speaker 4: something that doesn't fit his agenda, whatever that is. 86 00:04:10,640 --> 00:04:12,760 Speaker 3: He also Acman says he wants to He's very adamant 87 00:04:12,760 --> 00:04:15,640 Speaker 3: about wanting to move the listing out of Amsterdam and 88 00:04:15,680 --> 00:04:17,719 Speaker 3: move it here to the New York Stock Exchange. 89 00:04:18,000 --> 00:04:18,640 Speaker 6: Why is that? 90 00:04:18,920 --> 00:04:22,520 Speaker 4: I think the principal reason is because typically companies get 91 00:04:22,520 --> 00:04:25,080 Speaker 4: a higher multiple on earnings in the US than they 92 00:04:25,080 --> 00:04:28,160 Speaker 4: do in Europe, and so to some degree it shouldn't 93 00:04:28,160 --> 00:04:30,200 Speaker 4: really be this way. But by kind of shifting the 94 00:04:30,320 --> 00:04:34,719 Speaker 4: listing from one jurisdiction to another, you magically create value 95 00:04:35,040 --> 00:04:37,360 Speaker 4: by getting a lift in the multiple. As I said, 96 00:04:37,400 --> 00:04:39,880 Speaker 4: I think that the big pushback on that for me 97 00:04:40,320 --> 00:04:43,800 Speaker 4: is the AI threat. You know, we've seen multiple contraction 98 00:04:43,960 --> 00:04:46,600 Speaker 4: for lots of industries on the back of the perceived 99 00:04:46,680 --> 00:04:49,480 Speaker 4: AI risk, and I think that's very much in play 100 00:04:49,480 --> 00:04:52,160 Speaker 4: here for the record labels, particularly Universal. 101 00:04:53,040 --> 00:04:55,799 Speaker 2: There's another public trade and music company out there, Warner 102 00:04:55,880 --> 00:04:58,040 Speaker 2: Music Group. And how do the two What are the 103 00:04:58,120 --> 00:04:59,920 Speaker 2: valuation differences between those two? 104 00:05:00,000 --> 00:05:03,240 Speaker 4: They're pretaby saying they're both trained on about seventeen times earnings. 105 00:05:03,680 --> 00:05:06,680 Speaker 4: You know, I think people see them very similarly. There's 106 00:05:06,680 --> 00:05:11,159 Speaker 4: a much lower free float in Warner. I think almost 107 00:05:11,240 --> 00:05:16,039 Speaker 4: the kind of public company. They both face similar risks. 108 00:05:16,080 --> 00:05:17,719 Speaker 4: I think, obviously, for the last ten years or so, 109 00:05:17,880 --> 00:05:21,200 Speaker 4: Universe has been my finer way, the number one record 110 00:05:21,320 --> 00:05:24,400 Speaker 4: label kind of dominates the kind of charts in terms 111 00:05:24,480 --> 00:05:27,760 Speaker 4: of its artists. In recent times we have seen Warner 112 00:05:28,600 --> 00:05:31,919 Speaker 4: kind of take some share, but it's kind of relatively 113 00:05:31,960 --> 00:05:34,719 Speaker 4: gradual thing. But I think largely investors kind of see 114 00:05:34,720 --> 00:05:37,880 Speaker 4: them both as you know, a play on the same fundamentals. 115 00:05:38,520 --> 00:05:41,440 Speaker 2: Stay with us. More from Bloomberg Intelligence coming up after this. 116 00:05:45,080 --> 00:05:48,760 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 117 00:05:48,839 --> 00:05:51,960 Speaker 1: weekdays at ten am Eastern on Apple Coarclay and Android 118 00:05:51,960 --> 00:05:55,279 Speaker 1: Otto with the Bloomberg Business app. Listen on demand wherever 119 00:05:55,320 --> 00:05:59,400 Speaker 1: you get your podcasts, or watch us live on YouTube. 120 00:06:00,080 --> 00:06:02,599 Speaker 2: What's still happening despite all of the uncertainty in the 121 00:06:02,640 --> 00:06:06,520 Speaker 2: world is technology companies are doing deals, They are investing 122 00:06:06,560 --> 00:06:10,640 Speaker 2: in AI, A lot of stuff going on even today. 123 00:06:10,640 --> 00:06:12,880 Speaker 2: So we asked Man Deep Same to step in and 124 00:06:13,000 --> 00:06:15,599 Speaker 2: Deep runs all the tech research for Bloomberg Intelligence, and 125 00:06:15,640 --> 00:06:17,560 Speaker 2: we appreciate getting a few minutes of this time. Mandy. 126 00:06:17,640 --> 00:06:23,159 Speaker 2: Let's start with Anthropic Broadcom Google. They're expanding a strategic 127 00:06:23,200 --> 00:06:26,680 Speaker 2: collaboration that will allow Anthropic access to about three and 128 00:06:26,720 --> 00:06:29,760 Speaker 2: a half gigawat's worth of computing power starting in twenty 129 00:06:29,800 --> 00:06:32,440 Speaker 2: twenty seven. I'm just that what's going on with Anthropic 130 00:06:32,520 --> 00:06:33,640 Speaker 2: and broad common Google? 131 00:06:34,320 --> 00:06:37,360 Speaker 7: Yeah, I mean you remember the time when OpenAI signed 132 00:06:37,400 --> 00:06:40,159 Speaker 7: all those deals for ten gigawatt capacity? 133 00:06:40,320 --> 00:06:41,920 Speaker 5: Yep, Well things have changed. 134 00:06:41,960 --> 00:06:45,760 Speaker 7: The momentum has shifted towards Anthropic in a big way. 135 00:06:46,279 --> 00:06:48,720 Speaker 7: And now we see this deal, which really is a 136 00:06:48,760 --> 00:06:53,040 Speaker 7: reflection of the momentum that Entropic has generated from coding 137 00:06:53,080 --> 00:06:58,800 Speaker 7: agents from enterprise. In fact, and Tropics revenue has tripled 138 00:06:59,120 --> 00:07:02,760 Speaker 7: from nine billion to thirty billion in a span of 139 00:07:02,880 --> 00:07:07,159 Speaker 7: four months. What this is breakneck growth that we have 140 00:07:07,320 --> 00:07:10,679 Speaker 7: never seen, at least till the time that I've covered 141 00:07:10,720 --> 00:07:13,240 Speaker 7: this space. And you know now they are short of 142 00:07:13,360 --> 00:07:16,840 Speaker 7: compute capacity, so they're signing all these multi year deals 143 00:07:16,880 --> 00:07:18,040 Speaker 7: to secure compute. 144 00:07:18,400 --> 00:07:21,640 Speaker 8: Okay, So this might be like a basic question for 145 00:07:21,800 --> 00:07:24,920 Speaker 8: someone who follows Ai so closely, But is this all 146 00:07:24,960 --> 00:07:29,160 Speaker 8: because people want to use Claude like Anthropics Claude versus 147 00:07:29,280 --> 00:07:32,520 Speaker 8: open AI's chat gept. I'm still using chat GPT. I 148 00:07:32,560 --> 00:07:33,760 Speaker 8: don't know if I'm very behind. 149 00:07:33,880 --> 00:07:37,040 Speaker 7: Well, so it all comes down to use case and 150 00:07:37,120 --> 00:07:41,560 Speaker 7: what Anthropic decided, which in hindsight and hindsight is just 151 00:07:41,680 --> 00:07:44,200 Speaker 7: a week's here, you know, seems to be a very 152 00:07:44,200 --> 00:07:49,480 Speaker 7: smart move is really double down on coding agents as 153 00:07:49,520 --> 00:07:53,360 Speaker 7: a use case. And this is really you know, tools 154 00:07:53,360 --> 00:07:58,800 Speaker 7: that developers use to complete their code right, full on code. 155 00:07:59,280 --> 00:08:02,800 Speaker 7: You know that can save them hours. And now Entropic 156 00:08:02,920 --> 00:08:08,080 Speaker 7: has got thousand enterprise customers that are paying over one 157 00:08:08,160 --> 00:08:11,920 Speaker 7: million dollars plus each in a span of weeks. 158 00:08:12,240 --> 00:08:13,880 Speaker 5: They've landed all these. 159 00:08:13,720 --> 00:08:19,120 Speaker 7: Customers just for one tool, one product that they conceived 160 00:08:19,280 --> 00:08:22,080 Speaker 7: in weeks and they've been able to ramp that up 161 00:08:22,120 --> 00:08:23,120 Speaker 7: so fast. 162 00:08:23,320 --> 00:08:25,960 Speaker 2: So who are the peers for Anthropic? Again? Just remind 163 00:08:26,000 --> 00:08:27,960 Speaker 2: me because I can't I need my float chart. Remember 164 00:08:27,960 --> 00:08:30,040 Speaker 2: who's who here? Who are the peers or who the 165 00:08:30,080 --> 00:08:31,120 Speaker 2: competitors for Anthropic? 166 00:08:31,640 --> 00:08:33,120 Speaker 5: I mean on the coding side. 167 00:08:33,240 --> 00:08:36,400 Speaker 7: You know, you can think of names like Atlasian they 168 00:08:37,120 --> 00:08:41,800 Speaker 7: used to manage code, and coding agent is a new category. 169 00:08:41,920 --> 00:08:44,400 Speaker 7: So when you think about you know, an agent take 170 00:08:44,480 --> 00:08:49,200 Speaker 7: AI that's solving code end to end. This is the 171 00:08:49,280 --> 00:08:52,120 Speaker 7: use case that everyone was waiting when they were asking. 172 00:08:51,800 --> 00:08:55,120 Speaker 5: The ROI question. This is the ROI. 173 00:08:54,920 --> 00:08:57,120 Speaker 7: That you know they were looking for. And think of 174 00:08:57,600 --> 00:09:00,440 Speaker 7: the CAPEX for twenty twenty seven. Now, now that we 175 00:09:00,480 --> 00:09:04,160 Speaker 7: have seen this revenue ramp from Entropic, I bet you 176 00:09:04,240 --> 00:09:06,360 Speaker 7: twenty twenty seven CAPEX numbers are going. 177 00:09:06,200 --> 00:09:09,040 Speaker 2: When of these companies coming public, when do we see them? 178 00:09:09,600 --> 00:09:10,800 Speaker 2: Let me know who these people. 179 00:09:10,520 --> 00:09:13,240 Speaker 5: Are in the back half of the year, and you 180 00:09:13,280 --> 00:09:13,720 Speaker 5: know it's. 181 00:09:13,559 --> 00:09:14,400 Speaker 2: Going to be Entropic. 182 00:09:14,480 --> 00:09:16,400 Speaker 5: You think maybe Entropic for sure. 183 00:09:16,720 --> 00:09:18,839 Speaker 7: Sure, I would be very surprised if they don't use 184 00:09:18,840 --> 00:09:19,679 Speaker 7: this opportunity. 185 00:09:19,679 --> 00:09:21,800 Speaker 2: Shat gpt exactly open Ai. 186 00:09:22,000 --> 00:09:24,040 Speaker 5: But open Ai has got some trouble. 187 00:09:24,120 --> 00:09:27,960 Speaker 7: Now there was a point when open Ai was the 188 00:09:28,000 --> 00:09:31,839 Speaker 7: clear leader, they had the best growth. Well, Entropic has 189 00:09:31,920 --> 00:09:35,440 Speaker 7: actually surpassed open Ai in terms of revenue run rate. 190 00:09:35,840 --> 00:09:39,040 Speaker 7: Just to put it in context, open Ai raised money 191 00:09:39,080 --> 00:09:41,960 Speaker 7: at eight hundred and fifty two billion dollars in valuation 192 00:09:42,080 --> 00:09:45,400 Speaker 7: in the last private funding ground, Entropica was valued at 193 00:09:45,400 --> 00:09:48,880 Speaker 7: three hundred and eighty billion. So imagine a company growing 194 00:09:48,960 --> 00:09:53,360 Speaker 7: faster having surpassed open Ai was valued at half the 195 00:09:53,480 --> 00:09:56,720 Speaker 7: valuation of open Ai. So I would be very curious 196 00:09:56,720 --> 00:09:59,319 Speaker 7: to see what is the next funding round for Entropic 197 00:09:59,400 --> 00:10:02,720 Speaker 7: look like. And I think they should narrow the evaluation 198 00:10:02,840 --> 00:10:04,240 Speaker 7: gap that they have with open Ai. 199 00:10:04,480 --> 00:10:06,520 Speaker 8: And then so what does it mean for Broadcom because 200 00:10:06,520 --> 00:10:11,199 Speaker 8: we're seeing that stock hire three percent today? But do 201 00:10:11,240 --> 00:10:14,880 Speaker 8: they does does Broadcom benefit from this this long term 202 00:10:14,960 --> 00:10:15,559 Speaker 8: runway of. 203 00:10:16,320 --> 00:10:21,000 Speaker 7: I mean clearly, anything touching entropic ecosystem right now should 204 00:10:21,000 --> 00:10:24,360 Speaker 7: do well, whether it's Broadcom, whether it's Google on the 205 00:10:24,440 --> 00:10:28,560 Speaker 7: chip side, Google as a standalone chip company will have 206 00:10:28,640 --> 00:10:32,080 Speaker 7: a sizeable revenue from this entropic deal. And that's where 207 00:10:32,160 --> 00:10:36,040 Speaker 7: you know in video or anything touching open AI will 208 00:10:36,080 --> 00:10:38,560 Speaker 7: probably see some headwind at least on the back of 209 00:10:39,200 --> 00:10:39,760 Speaker 7: this news. 210 00:10:39,840 --> 00:10:42,720 Speaker 2: How often does like an entrop How often does this 211 00:10:42,760 --> 00:10:46,920 Speaker 2: technology evolved? How quickly does it evolve? Like if I 212 00:10:46,960 --> 00:10:49,079 Speaker 2: buy a piece of software today, or I'm not even 213 00:10:49,080 --> 00:10:51,800 Speaker 2: sure what I'm buying. I'm not buying a piece of software, 214 00:10:51,800 --> 00:10:56,000 Speaker 2: I'm buying some AI product. Yeah, how long is that 215 00:10:56,120 --> 00:10:58,439 Speaker 2: relevant for before some new technology comes along and makes 216 00:10:58,440 --> 00:10:59,959 Speaker 2: it irrelevant? Like I don't buy something else. 217 00:11:00,040 --> 00:11:04,800 Speaker 7: These companies are releasing new features every week. In fact, 218 00:11:04,840 --> 00:11:08,800 Speaker 7: this coding agent product, as I said, was consumed in 219 00:11:08,840 --> 00:11:12,240 Speaker 7: a matter of weeks, and so the next model release 220 00:11:12,320 --> 00:11:17,160 Speaker 7: from open ai could be you know better than Entropic. 221 00:11:17,640 --> 00:11:21,360 Speaker 7: The problem that open ai may run into is enterprise. 222 00:11:22,720 --> 00:11:26,000 Speaker 7: You know, contracts are very sticky. Once you start using 223 00:11:26,000 --> 00:11:29,680 Speaker 7: a product and it's a new product, new category, you're 224 00:11:29,679 --> 00:11:31,920 Speaker 7: not going to rip and replace. And that's where what 225 00:11:32,080 --> 00:11:35,520 Speaker 7: Entropic is doing with coding agents. It's gonna be sticky 226 00:11:35,559 --> 00:11:40,120 Speaker 7: revenue because companies are signing, assigning million dollar plus contracts. Now, 227 00:11:40,520 --> 00:11:43,559 Speaker 7: They're not just gonna go back and start using open 228 00:11:43,600 --> 00:11:47,680 Speaker 7: ai if their next product is better. So this is 229 00:11:47,679 --> 00:11:51,280 Speaker 7: sticky and that's why I think Entropic has created a 230 00:11:51,320 --> 00:11:55,079 Speaker 7: new category. Whereas open ai was focused on the consumer side. 231 00:11:55,240 --> 00:11:58,880 Speaker 7: They did really well with chatchipet subscriptions, but they missed 232 00:11:58,920 --> 00:12:01,800 Speaker 7: out on this opportunity in terms of focusing on coding 233 00:12:01,800 --> 00:12:02,800 Speaker 7: agents and enterprise. 234 00:12:03,360 --> 00:12:03,959 Speaker 5: Stay with us. 235 00:12:04,160 --> 00:12:06,440 Speaker 2: More from Bloomberg Intelligence coming up after this. 236 00:12:10,360 --> 00:12:14,040 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 237 00:12:14,120 --> 00:12:17,240 Speaker 1: weekdays at ten am Eastern on Apple, Coarclay, and Android 238 00:12:17,240 --> 00:12:20,559 Speaker 1: Auto with the Bloomberg Business app. Listen on demand wherever 239 00:12:20,600 --> 00:12:23,720 Speaker 1: you get your podcasts, or watch us live on YouTube. 240 00:12:24,320 --> 00:12:26,319 Speaker 2: It's another day, which means it's another m and a 241 00:12:26,480 --> 00:12:29,680 Speaker 2: trade in the healthcare space. Jilliad Sciences agrees to buy 242 00:12:29,720 --> 00:12:33,600 Speaker 2: private German biotech Tubulus in a deal worth up the 243 00:12:33,640 --> 00:12:37,160 Speaker 2: five billion dollars to boost its portfolio and cancer drug development. 244 00:12:37,360 --> 00:12:39,640 Speaker 2: Let's start there with Sam Fazzelli, covers all the healthcare 245 00:12:39,640 --> 00:12:43,760 Speaker 2: stuff for Bloomberg Intelligence. He's based in London, lives in France, 246 00:12:43,800 --> 00:12:45,839 Speaker 2: I think, but he's in New York. Go figure here, 247 00:12:45,880 --> 00:12:47,160 Speaker 2: today's we got him in studio. 248 00:12:47,800 --> 00:12:48,040 Speaker 6: Sam. 249 00:12:48,080 --> 00:12:50,839 Speaker 2: What's Jilliad doing here? What are they buying here? And 250 00:12:50,960 --> 00:12:51,840 Speaker 2: what's the strategy? 251 00:12:52,080 --> 00:12:54,720 Speaker 9: Friscus Can I just say, I'm so happy to be here. 252 00:12:54,760 --> 00:12:58,440 Speaker 2: You know, I love I know you you I mean. 253 00:13:00,160 --> 00:13:00,760 Speaker 5: I tell you what. 254 00:13:00,920 --> 00:13:03,920 Speaker 10: The door my flight door opened at sixteen fifty last night. 255 00:13:04,280 --> 00:13:07,560 Speaker 10: I was in the cab at seventeen fifteen. That is 256 00:13:08,000 --> 00:13:09,680 Speaker 10: twenty five minutes. 257 00:13:09,679 --> 00:13:12,360 Speaker 9: Door to door to the cab. Where are these TSA issues? 258 00:13:12,400 --> 00:13:14,400 Speaker 10: I'm not belittle in that now, but it didn't affect 259 00:13:14,400 --> 00:13:18,199 Speaker 10: me so unhappy if you were exit special air unspecial 260 00:13:19,040 --> 00:13:24,439 Speaker 10: special especially, So what's Gilly are doing? This is the 261 00:13:24,480 --> 00:13:26,760 Speaker 10: second deal they've done in the past a few months, 262 00:13:26,800 --> 00:13:30,240 Speaker 10: a couple of months, I would say they are continuing 263 00:13:30,280 --> 00:13:35,240 Speaker 10: to build an increasingly oncology focused They do have various 264 00:13:35,559 --> 00:13:38,360 Speaker 10: assets as you know, in HIV and oncology, and they've 265 00:13:38,360 --> 00:13:41,200 Speaker 10: been building this out. This is a very interesting acquisition. 266 00:13:41,240 --> 00:13:43,800 Speaker 10: I have to say. It's a private German company. I've 267 00:13:43,840 --> 00:13:44,360 Speaker 10: met them. 268 00:13:44,200 --> 00:13:46,400 Speaker 9: Two or three times. Listen to their presentation. 269 00:13:47,000 --> 00:13:51,800 Speaker 10: It's in a space Paul, that had been kind of 270 00:13:51,880 --> 00:13:54,680 Speaker 10: thought of, maybe China's taken over all of it, the 271 00:13:54,800 --> 00:13:58,960 Speaker 10: ADC's antibody drug conjugate world, and that there isn't really 272 00:13:59,080 --> 00:14:01,880 Speaker 10: much to play for here. So they build this company 273 00:14:02,160 --> 00:14:06,080 Speaker 10: four hundred and one million dollars, the biggest European Series 274 00:14:06,120 --> 00:14:09,120 Speaker 10: C ever announced about a few months ago. And now 275 00:14:09,120 --> 00:14:10,480 Speaker 10: I'm going to come back to that and connect you 276 00:14:10,480 --> 00:14:13,880 Speaker 10: all up and in a space that you think China 277 00:14:13,880 --> 00:14:16,800 Speaker 10: has overtaken the rest of the world in Europe, and 278 00:14:16,840 --> 00:14:19,440 Speaker 10: here comes to Gilliad buying it for a hefty price, 279 00:14:19,520 --> 00:14:20,960 Speaker 10: right that one hundred one million. I don't know what 280 00:14:21,000 --> 00:14:23,960 Speaker 10: the valuation was at that time, but this is a 281 00:14:24,000 --> 00:14:25,280 Speaker 10: good deal for the investors. 282 00:14:25,600 --> 00:14:28,440 Speaker 8: And what kind of treatments are they now going to 283 00:14:28,440 --> 00:14:30,760 Speaker 8: be able to offer with this acquisition. 284 00:14:30,920 --> 00:14:35,720 Speaker 10: Yeah, so Gillad already has a well known true delv 285 00:14:37,240 --> 00:14:39,360 Speaker 10: ADC antibody. So what do you do is that you 286 00:14:39,400 --> 00:14:42,640 Speaker 10: put the drug that's a chemotherapy often that you want 287 00:14:42,680 --> 00:14:46,000 Speaker 10: to avoid having the overall exposure in your body to 288 00:14:46,040 --> 00:14:48,680 Speaker 10: an antibody that homes in on a tumor. That's the 289 00:14:48,760 --> 00:14:52,360 Speaker 10: principle much harder than in reality to make work. So 290 00:14:52,440 --> 00:14:54,440 Speaker 10: here what they're doing is buying a brand new, a 291 00:14:54,440 --> 00:14:58,280 Speaker 10: pretty broad profile platform and two drugs with it. 292 00:14:58,960 --> 00:15:02,000 Speaker 9: So it's it's it's exactly in their wheelhouse. 293 00:15:03,040 --> 00:15:05,120 Speaker 2: All right, Let's move on to the weight wall stuff, 294 00:15:05,160 --> 00:15:08,160 Speaker 2: because that's always in the news. Novo nord school price. 295 00:15:08,160 --> 00:15:11,000 Speaker 2: It's new high dose w GOV which is what we 296 00:15:11,120 --> 00:15:14,120 Speaker 2: use in the household at three ninety nine a month 297 00:15:14,160 --> 00:15:18,400 Speaker 2: for cash pay patients, undercutting the cost of most doses 298 00:15:18,400 --> 00:15:21,080 Speaker 2: of rival Eli Lily is zep bound. Is this just 299 00:15:21,120 --> 00:15:23,240 Speaker 2: another example where this market it is we're now moving 300 00:15:23,280 --> 00:15:24,600 Speaker 2: on to really competing on price. 301 00:15:24,840 --> 00:15:26,600 Speaker 10: Yeah, but they have been pulled for a while, and 302 00:15:26,720 --> 00:15:28,360 Speaker 10: you know a lot of the times we don't actually 303 00:15:28,440 --> 00:15:30,840 Speaker 10: see the price that people are paying because it goes 304 00:15:30,840 --> 00:15:33,440 Speaker 10: to a different channel, the rebates, the discounts, you know, 305 00:15:33,480 --> 00:15:36,560 Speaker 10: all that story of how everybody is so focused on 306 00:15:36,600 --> 00:15:40,360 Speaker 10: the list price and where actually people are getting the 307 00:15:40,320 --> 00:15:42,560 Speaker 10: the is a much lower price at least through the insurance, 308 00:15:42,840 --> 00:15:45,680 Speaker 10: So it is not a surprise. It's going to keep happening. 309 00:15:46,120 --> 00:15:48,600 Speaker 10: Novo needs to get its footing back in here. And 310 00:15:48,640 --> 00:15:51,320 Speaker 10: it's interesting that it's happening just the week after that 311 00:15:51,680 --> 00:15:56,160 Speaker 10: Lily has been approved to launch their oral drug. Right, wow, 312 00:15:56,160 --> 00:16:00,200 Speaker 10: and that's the first week or two. This friday, I'd 313 00:16:00,240 --> 00:16:03,320 Speaker 10: see some of the prescriptions flow through. Everyone's focused on 314 00:16:03,360 --> 00:16:05,480 Speaker 10: that how strong a launch will that be? 315 00:16:06,720 --> 00:16:08,880 Speaker 2: That even though you have to take this pill daily, 316 00:16:09,760 --> 00:16:11,560 Speaker 2: people take pills all the time. It's no big deal 317 00:16:11,600 --> 00:16:13,040 Speaker 2: that this is going to really open up the market. 318 00:16:13,080 --> 00:16:13,320 Speaker 9: Is that? 319 00:16:13,440 --> 00:16:13,640 Speaker 6: Yeah? 320 00:16:13,720 --> 00:16:15,680 Speaker 10: I mean, so the thing is that it doesn't give 321 00:16:15,680 --> 00:16:17,920 Speaker 10: you as much weight loss as the job. The job 322 00:16:18,040 --> 00:16:21,000 Speaker 10: is super powerful, right, But so you could think about 323 00:16:21,000 --> 00:16:22,120 Speaker 10: it in many different ways. 324 00:16:22,200 --> 00:16:23,560 Speaker 9: I'll just add it to my box. 325 00:16:23,760 --> 00:16:25,160 Speaker 10: You know a lot of people have these boxes with 326 00:16:25,200 --> 00:16:27,720 Speaker 10: their vitamins and minerals and all that I just added 327 00:16:27,800 --> 00:16:28,120 Speaker 10: in there. 328 00:16:28,240 --> 00:16:31,400 Speaker 9: Ticket. It doesn't have any food restrictions or anything. So 329 00:16:31,560 --> 00:16:32,680 Speaker 9: you get some side effects. 330 00:16:32,680 --> 00:16:37,480 Speaker 10: But and maybe you do it after you've done your 331 00:16:37,640 --> 00:16:41,320 Speaker 10: major weight loss, so you've got your three pounds, four pounds, 332 00:16:41,320 --> 00:16:43,440 Speaker 10: ten pounds that you wanted to lose, and you're feeling 333 00:16:43,480 --> 00:16:45,560 Speaker 10: great and you don't want to be taking the job anymore. 334 00:16:45,560 --> 00:16:48,000 Speaker 10: Although a lot of people are fine with the injection, 335 00:16:48,440 --> 00:16:49,240 Speaker 10: it just helps. 336 00:16:49,360 --> 00:16:51,200 Speaker 9: There are needle phobic people it helps. 337 00:16:51,600 --> 00:16:54,840 Speaker 8: And what's the expectation for Is the pill necessarily going 338 00:16:54,920 --> 00:16:56,320 Speaker 8: to be cheap and. 339 00:16:56,320 --> 00:16:58,840 Speaker 10: The job, well, it should be for the patient like 340 00:16:58,840 --> 00:17:00,880 Speaker 10: what they're I don't think so. I think that would 341 00:17:00,880 --> 00:17:04,480 Speaker 10: be a really odd thing for them to massively undercut massively. 342 00:17:04,640 --> 00:17:07,160 Speaker 10: But I think you can play with pricing there, especially 343 00:17:07,200 --> 00:17:10,600 Speaker 10: as it's got probably better margins than the injectable. 344 00:17:10,800 --> 00:17:14,640 Speaker 2: I mean is are these weight loss drugs as popular 345 00:17:14,680 --> 00:17:16,040 Speaker 2: outside of the US as they are. 346 00:17:15,960 --> 00:17:16,480 Speaker 5: In the US? 347 00:17:16,600 --> 00:17:17,240 Speaker 9: Absolutely? 348 00:17:17,359 --> 00:17:19,880 Speaker 10: In the UK, you know, we are a backward country 349 00:17:20,000 --> 00:17:22,720 Speaker 10: sometimes when it comes to medicine at least, which try 350 00:17:23,000 --> 00:17:25,639 Speaker 10: wait for two years before things get approved. There's a 351 00:17:25,840 --> 00:17:27,840 Speaker 10: massive self pay market. 352 00:17:27,800 --> 00:17:28,080 Speaker 5: All right. 353 00:17:28,119 --> 00:17:30,920 Speaker 2: I have messing for a friend here. Okay, is there 354 00:17:30,960 --> 00:17:33,720 Speaker 2: a baldness drug potentially? 355 00:17:34,560 --> 00:17:36,879 Speaker 10: Well, when you find one, can you let me know. 356 00:17:36,920 --> 00:17:39,240 Speaker 10: I mean this is there is already marketed drugs for 357 00:17:39,280 --> 00:17:40,480 Speaker 10: it first, but. 358 00:17:40,520 --> 00:17:43,520 Speaker 2: Something that's as effective as we go. 359 00:17:43,840 --> 00:17:45,800 Speaker 10: So once you've lost it, I think you just have 360 00:17:45,880 --> 00:17:47,440 Speaker 10: to gracefully accept your fate. 361 00:17:48,160 --> 00:17:50,159 Speaker 9: If you're in the process of losing it. There are 362 00:17:50,200 --> 00:17:53,600 Speaker 9: approved drugs. You can use it to fluff out. 363 00:17:53,600 --> 00:17:57,160 Speaker 2: There's follygles, but there's no there's nothing in the pipeline. 364 00:17:57,200 --> 00:18:01,720 Speaker 10: That's just so don't forget that. As we go up 365 00:18:01,760 --> 00:18:03,640 Speaker 10: the evolutionary tree, we don't really need hair. 366 00:18:04,080 --> 00:18:07,000 Speaker 9: So perhaps it's evolution that's taking place here, right. 367 00:18:07,040 --> 00:18:08,480 Speaker 8: Have you heard that that's a good perspective. 368 00:18:08,520 --> 00:18:09,920 Speaker 5: I've never heard that. 369 00:18:11,320 --> 00:18:12,200 Speaker 2: A good way to look at it. 370 00:18:12,480 --> 00:18:15,280 Speaker 8: You mentioned China when when you first came in, the 371 00:18:15,400 --> 00:18:19,120 Speaker 8: FDA is trying to streamline clinical trials. What does that 372 00:18:19,200 --> 00:18:21,480 Speaker 8: mean for you? Know how the US competes with China and. 373 00:18:21,600 --> 00:18:23,440 Speaker 9: I separately needed desperately needed. 374 00:18:23,480 --> 00:18:26,320 Speaker 10: It takes months, if not a year or so to 375 00:18:26,480 --> 00:18:29,320 Speaker 10: start a first in human clinical trial, all for the 376 00:18:29,440 --> 00:18:31,560 Speaker 10: right reasons, but a lot of it is red tape. 377 00:18:31,760 --> 00:18:34,320 Speaker 10: So what China has been able to do is to 378 00:18:34,440 --> 00:18:37,639 Speaker 10: really streamline that process. So it's so much cheaper to 379 00:18:37,720 --> 00:18:40,480 Speaker 10: go over there. Imagine if you gain nine months or 380 00:18:40,520 --> 00:18:42,760 Speaker 10: a year in your development plans and you can get 381 00:18:42,760 --> 00:18:45,960 Speaker 10: an answer very much quicker there as patients are enrolled 382 00:18:45,960 --> 00:18:48,600 Speaker 10: in your trials. So this is not about risking people. 383 00:18:48,640 --> 00:18:50,639 Speaker 10: This is about just getting rid of some bureaucracy and 384 00:18:50,680 --> 00:18:54,600 Speaker 10: allowing companies to catch up with the way that trials 385 00:18:54,600 --> 00:18:58,119 Speaker 10: are done in China. You take away one more competitive 386 00:18:58,119 --> 00:18:59,119 Speaker 10: advantage from China. 387 00:18:59,560 --> 00:19:02,560 Speaker 2: Are all parties here in the US on board with 388 00:19:02,600 --> 00:19:07,280 Speaker 2: this strategy and the pharmaceutical companies the effect that ensure. 389 00:19:07,160 --> 00:19:10,000 Speaker 10: That the farmer companies would love it insurance. I don't 390 00:19:10,000 --> 00:19:11,960 Speaker 10: think they at that stage of the development of a drug, 391 00:19:12,000 --> 00:19:13,920 Speaker 10: they don't care. They wait for the very end of it. 392 00:19:14,080 --> 00:19:17,160 Speaker 10: But certainly the FDA, this is the FDA talking about 393 00:19:17,160 --> 00:19:17,840 Speaker 10: it now, right. 394 00:19:17,760 --> 00:19:19,160 Speaker 5: So we do need this. 395 00:19:19,320 --> 00:19:20,520 Speaker 9: We need this to. 396 00:19:20,560 --> 00:19:24,760 Speaker 10: Take away one more competitive advantage from or disadvantage in 397 00:19:24,840 --> 00:19:25,320 Speaker 10: the US. 398 00:19:26,160 --> 00:19:28,760 Speaker 2: Thirty seconds, So how should we think about the West 399 00:19:28,880 --> 00:19:31,840 Speaker 2: versus China in terms of pharmaceuticals and biotexts and all 400 00:19:31,840 --> 00:19:32,320 Speaker 2: that stuff. 401 00:19:32,960 --> 00:19:36,600 Speaker 10: You need to constantly look over your shoulder. The research, 402 00:19:36,680 --> 00:19:40,879 Speaker 10: the science, the capability is on par and rapidly rising, 403 00:19:41,160 --> 00:19:44,200 Speaker 10: and there is a massive push by the government there 404 00:19:44,720 --> 00:19:48,400 Speaker 10: because they can also have the luxury of being able 405 00:19:48,440 --> 00:19:50,359 Speaker 10: to plan for five, ten, fifteen years. 406 00:19:50,800 --> 00:19:51,400 Speaker 5: Stay with us. 407 00:19:51,560 --> 00:19:53,960 Speaker 2: More from Bloomberg Intelligence coming up after this. 408 00:19:57,840 --> 00:20:01,520 Speaker 1: You're listening to the Bloomberg Intelligence part. Catch us Live 409 00:20:01,600 --> 00:20:04,720 Speaker 1: weekdays at ten am Eastern on Apple Coarclay and Android 410 00:20:04,720 --> 00:20:08,040 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 411 00:20:08,080 --> 00:20:11,359 Speaker 1: you get your podcasts, or watch us live on YouTube. 412 00:20:11,880 --> 00:20:15,080 Speaker 2: One thing that continues to move forward is AI investments 413 00:20:15,119 --> 00:20:19,320 Speaker 2: in AI, and that includes investments in data centers that 414 00:20:19,359 --> 00:20:21,400 Speaker 2: has just been a huge growth. Here we hear about 415 00:20:21,400 --> 00:20:24,720 Speaker 2: that from all different angles. Lloyd Arnold covers this. He's 416 00:20:24,760 --> 00:20:28,359 Speaker 2: a BNF data center reporter joining us here. 417 00:20:29,920 --> 00:20:31,040 Speaker 5: Lloyd, I know you're out. 418 00:20:30,880 --> 00:20:34,040 Speaker 2: With a piece of work here. AI data center build 419 00:20:34,080 --> 00:20:37,159 Speaker 2: advances at full speed. Five things to know? What are 420 00:20:37,200 --> 00:20:40,119 Speaker 2: the five things to know about this rapid buildout in 421 00:20:40,200 --> 00:20:42,320 Speaker 2: data centers across across the world. 422 00:20:42,400 --> 00:20:48,520 Speaker 6: Actually, first is we're seeing a huge amount construction. We're 423 00:20:48,560 --> 00:20:52,080 Speaker 6: seeing a huge amount of capacity being connected, and that's 424 00:20:52,119 --> 00:20:56,359 Speaker 6: continuing to accelerate. This is driving purchases of clean energy. 425 00:20:56,560 --> 00:21:00,800 Speaker 6: It's also driving purchases of natural gas and lemal generation. 426 00:21:01,680 --> 00:21:05,520 Speaker 6: This is help being driven by or more capacity or 427 00:21:05,600 --> 00:21:09,040 Speaker 6: more capital allocated by the big tech companies, by big 428 00:21:09,080 --> 00:21:13,160 Speaker 6: data center developers. And we're expecting this to continue as 429 00:21:13,200 --> 00:21:16,840 Speaker 6: confidence in newcomers to this space and the biggest AI 430 00:21:16,880 --> 00:21:20,560 Speaker 6: companies have positive margins, so a lot of this demand 431 00:21:21,200 --> 00:21:23,320 Speaker 6: is likely to be sustained, you. 432 00:21:23,280 --> 00:21:23,840 Speaker 2: Know, Arnold. 433 00:21:23,880 --> 00:21:26,320 Speaker 3: A front page of the Wall Street Journal today has 434 00:21:26,640 --> 00:21:30,000 Speaker 3: a write up about cities and states that are now 435 00:21:30,080 --> 00:21:35,840 Speaker 3: taking direct aim at data centers, including states like Maine, Georgia. 436 00:21:35,960 --> 00:21:38,600 Speaker 3: They're saying, wait a minute, we need to do more 437 00:21:38,640 --> 00:21:40,840 Speaker 3: studies on what the impact of these data centers are 438 00:21:40,840 --> 00:21:43,160 Speaker 3: going to mean for communities and for the environment. How 439 00:21:43,200 --> 00:21:46,560 Speaker 3: much is that going to be a hurdle for companies 440 00:21:46,720 --> 00:21:49,520 Speaker 3: wanting to expand in the way they want to expand 441 00:21:49,560 --> 00:21:51,600 Speaker 3: and at the level they want to expand. 442 00:21:52,640 --> 00:21:56,119 Speaker 6: Main in particular, probably not a huge hurdle based on 443 00:21:56,240 --> 00:22:00,399 Speaker 6: BNS data. There are no construction projects in and no 444 00:22:00,520 --> 00:22:05,399 Speaker 6: plan date. Centers in Maine or generally, shifting community attitudes 445 00:22:05,640 --> 00:22:09,160 Speaker 6: are a headwind. This is largely tied to power pricing, 446 00:22:09,359 --> 00:22:12,159 Speaker 6: which is part of what's driving some data center developers 447 00:22:12,600 --> 00:22:16,719 Speaker 6: toward natural gas. BINGOS tracking about one hundred gigawatts of 448 00:22:17,320 --> 00:22:21,720 Speaker 6: data center it capacity associated with on site generation that 449 00:22:21,840 --> 00:22:25,840 Speaker 6: removes reliance on utilities and hopes to shield consumers from 450 00:22:26,040 --> 00:22:27,320 Speaker 6: higher power prices. 451 00:22:28,480 --> 00:22:32,000 Speaker 2: Lloyd I hear a lot of folks asking when is 452 00:22:32,040 --> 00:22:33,399 Speaker 2: it going to be enough? Are we going to know 453 00:22:33,480 --> 00:22:37,080 Speaker 2: when we have enough data center capacity. Because of the 454 00:22:37,119 --> 00:22:39,760 Speaker 2: question I think some people starting to ask, is are 455 00:22:39,760 --> 00:22:43,040 Speaker 2: we overbuilding here? How do we track that? 456 00:22:45,040 --> 00:22:49,600 Speaker 6: That's a really real question. It is an unknown. The 457 00:22:49,680 --> 00:22:53,639 Speaker 6: things we're looking at are how are the AI companies performing, 458 00:22:54,280 --> 00:22:57,679 Speaker 6: Are they continuing to get higher uptake? Are they continue 459 00:22:57,680 --> 00:23:00,680 Speaker 6: to get more users? And how are the neoclas performing. 460 00:23:00,680 --> 00:23:03,320 Speaker 6: So these are companies such as core Weave, such as 461 00:23:03,359 --> 00:23:07,520 Speaker 6: Mebius who are very very exposed to AI workloads and 462 00:23:07,560 --> 00:23:10,840 Speaker 6: developing data centers to serve them. While those companies continue 463 00:23:10,840 --> 00:23:14,200 Speaker 6: to perform, well, that's a strong sign demand is hot. 464 00:23:15,119 --> 00:23:18,119 Speaker 3: And I must apologize, Lloyd, I called your Arnold earlier. 465 00:23:18,160 --> 00:23:19,760 Speaker 3: Did not mean to call you by your last name, 466 00:23:19,800 --> 00:23:22,159 Speaker 3: but that's what happens. Called sometimes when people have last names, that. 467 00:23:22,160 --> 00:23:23,399 Speaker 2: Can be a first names exactly. 468 00:23:23,560 --> 00:23:26,080 Speaker 3: I'm sure it's not the first time, Lloyd, but sorry 469 00:23:26,080 --> 00:23:28,199 Speaker 3: it had to be me. Talk to us about the 470 00:23:28,200 --> 00:23:32,480 Speaker 3: connection between building of data centers and the energy markets, 471 00:23:32,520 --> 00:23:34,840 Speaker 3: because they need a whole lot of energy to make 472 00:23:34,840 --> 00:23:36,080 Speaker 3: those data centers work. 473 00:23:37,400 --> 00:23:39,840 Speaker 6: Not troble flue and lexis. Actually it happens a lot 474 00:23:40,040 --> 00:23:44,760 Speaker 6: in terms of energy. Data centers are huge energy customers. 475 00:23:44,760 --> 00:23:47,800 Speaker 6: That's a big part of why people are interested in 476 00:23:47,920 --> 00:23:52,520 Speaker 6: they center build out. At present, this means data center developers, 477 00:23:52,920 --> 00:23:58,120 Speaker 6: big tech giants like Microsoft, Meta, Amazon, and Google. These 478 00:23:58,160 --> 00:24:03,000 Speaker 6: companies are hugely active in the clean power purchase agreement market. 479 00:24:03,400 --> 00:24:06,160 Speaker 6: They made up over half of that market globally last 480 00:24:06,200 --> 00:24:10,280 Speaker 6: year and over seventy percent in the US. So that's 481 00:24:10,480 --> 00:24:12,720 Speaker 6: one really big impact. And the mob of the other 482 00:24:12,840 --> 00:24:18,200 Speaker 6: story is this growing reliance on natural gas for data centers. 483 00:24:18,640 --> 00:24:20,919 Speaker 6: So now that seems to be a US story, but 484 00:24:21,280 --> 00:24:24,280 Speaker 6: lots not stats into campuses are planning to be powered 485 00:24:24,400 --> 00:24:26,960 Speaker 6: on site by gas engines and gas turbines. 486 00:24:27,880 --> 00:24:31,240 Speaker 2: Thirty seconds left, Lloyd. Is this primarily a US story 487 00:24:31,359 --> 00:24:33,080 Speaker 2: data center buildout or is it global? 488 00:24:35,600 --> 00:24:38,800 Speaker 6: This is primarily a US story for now. We are 489 00:24:38,880 --> 00:24:45,119 Speaker 6: seeing increased projects globally, but this US concentration is really 490 00:24:45,119 --> 00:24:48,159 Speaker 6: because the biggest players get these tech giants and the 491 00:24:48,200 --> 00:24:53,560 Speaker 6: big AI labs creating new demand, companies like OpenAI, Anthropic XAI, 492 00:24:53,920 --> 00:24:58,520 Speaker 6: they're all American companies. That's seeing a consolidation of a 493 00:24:58,600 --> 00:25:02,719 Speaker 6: market already skewed to the US further into the US. 494 00:25:03,359 --> 00:25:06,480 Speaker 6: Over two thirds of construction pipeline we see in the 495 00:25:06,520 --> 00:25:10,119 Speaker 6: Americas for now. Longer term, we're likely to see you 496 00:25:10,200 --> 00:25:12,320 Speaker 6: demand in a lot of emerging markets. 497 00:25:14,280 --> 00:25:18,960 Speaker 1: This is the Bloomberg Intelligence Podcast, available on Apple, Spotify, 498 00:25:19,160 --> 00:25:22,640 Speaker 1: and anywhere else you get your podcasts. Listen live each 499 00:25:22,640 --> 00:25:26,360 Speaker 1: weekday ten am to noon Eastern on Bloomberg dot com, 500 00:25:26,520 --> 00:25:30,080 Speaker 1: the iHeartRadio app tune In, and the Bloomberg Business app. 501 00:25:30,480 --> 00:25:33,440 Speaker 1: You can also watch us live every weekday on YouTube 502 00:25:33,800 --> 00:25:36,040 Speaker 1: and always on the Bloomberg terminal.