1 00:00:02,480 --> 00:00:10,480 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. This is Bloomberg Business 2 00:00:10,480 --> 00:00:14,640 Speaker 1: Weekdaily reporting from the magazine that helps global leaders stay 3 00:00:14,680 --> 00:00:18,759 Speaker 1: ahead with insight on the people, companies, and trends shaping 4 00:00:18,760 --> 00:00:23,720 Speaker 1: today's complex economy, plus global business, finance and tech news 5 00:00:23,760 --> 00:00:27,760 Speaker 1: as it happens. The Bloomberg Business Week Daily Podcast with 6 00:00:27,880 --> 00:00:31,840 Speaker 1: Carol Masser and Tim Stenebeck on Bloomberg Radio. 7 00:00:32,440 --> 00:00:35,440 Speaker 2: Coming from The New York Times, the Federal Reserve, or 8 00:00:35,520 --> 00:00:38,159 Speaker 2: rather Kevin Warsh, is considering reducing the number of regularly 9 00:00:38,200 --> 00:00:41,319 Speaker 2: scheduled meetings at which the FED sets interest rates. This 10 00:00:41,520 --> 00:00:43,360 Speaker 2: from The New York Times. I want to bring in 11 00:00:43,479 --> 00:00:47,000 Speaker 2: Kate Davidson, Managing editor of US Economic Policy. She joins 12 00:00:47,080 --> 00:00:49,640 Speaker 2: US from Washington, DC. Kate, this would be a very 13 00:00:49,680 --> 00:00:52,159 Speaker 2: significant shift for the Federal Reserve. 14 00:00:53,560 --> 00:00:56,280 Speaker 3: Yeah, this would be, as the Time says, a seismic change. 15 00:00:56,280 --> 00:00:59,360 Speaker 3: It would certainly be the biggest change that Kevin Warsh 16 00:00:59,760 --> 00:01:03,160 Speaker 3: has contemplated or undertaken. We've seen some what seemed at 17 00:01:03,160 --> 00:01:05,959 Speaker 3: the time big changes, shortening quite a bit the fed's 18 00:01:06,000 --> 00:01:08,680 Speaker 3: post meeting policy statement, and he has suggested that he 19 00:01:08,720 --> 00:01:12,000 Speaker 3: could reduce the number of press conferences that he delivers 20 00:01:12,040 --> 00:01:15,479 Speaker 3: after FED decisions, but reducing the number of meetings would 21 00:01:15,480 --> 00:01:19,120 Speaker 3: be a very large break with precedent, and I think 22 00:01:19,160 --> 00:01:22,720 Speaker 3: certainly would would rattle could you know, potentially rattle markets 23 00:01:22,720 --> 00:01:25,160 Speaker 3: and leave them, I suppose guessing more about what the 24 00:01:25,200 --> 00:01:27,800 Speaker 3: FED is going to do next, which you know we 25 00:01:27,840 --> 00:01:30,680 Speaker 3: saw this week they don't really like not knowing where 26 00:01:30,680 --> 00:01:31,360 Speaker 3: the FED is heading. 27 00:01:32,319 --> 00:01:36,640 Speaker 4: Yeah, I mean, is this a result of the meeting 28 00:01:36,680 --> 00:01:40,360 Speaker 4: not going so well or at least the interpretation, I mean, 29 00:01:40,360 --> 00:01:42,319 Speaker 4: the timing is kind of interesting here, Kate. 30 00:01:43,720 --> 00:01:46,880 Speaker 3: I mean, I really couldn't speculate. We obviously are asking 31 00:01:46,920 --> 00:01:50,240 Speaker 3: all of our sources to, you know, to help us 32 00:01:50,280 --> 00:01:53,480 Speaker 3: confirm this. According to the report, Kevin Warsh brought it 33 00:01:53,600 --> 00:01:56,720 Speaker 3: up at the meeting this week, and they reported he 34 00:01:56,800 --> 00:02:00,320 Speaker 3: suggested this could be a decision that's made before or 35 00:02:00,480 --> 00:02:03,920 Speaker 3: their next gathering in September. That would be surprising a 36 00:02:03,960 --> 00:02:07,200 Speaker 3: decision that consequential to be made that quickly. In other areas, 37 00:02:07,240 --> 00:02:10,640 Speaker 3: when worsh was asked or has been asked about potential changes, 38 00:02:10,760 --> 00:02:12,760 Speaker 3: he's kind of signaled that he's going to leave a 39 00:02:12,800 --> 00:02:15,400 Speaker 3: lot of the discussion on these bigger questions up to 40 00:02:15,480 --> 00:02:18,400 Speaker 3: the five task forces that he's assembled to look at 41 00:02:18,400 --> 00:02:22,320 Speaker 3: different areas of how the FED conducts policy. So I 42 00:02:22,360 --> 00:02:24,639 Speaker 3: don't know, but it would be it would certainly seem 43 00:02:24,680 --> 00:02:26,720 Speaker 3: to be a very quick decision if it was made 44 00:02:26,880 --> 00:02:28,000 Speaker 3: before the next FED meeting. 45 00:02:28,000 --> 00:02:31,800 Speaker 2: Okay, would it make the FED less nimble to react quickly? 46 00:02:32,320 --> 00:02:35,160 Speaker 2: Because can't they can just do emergency rate moves. We've 47 00:02:35,200 --> 00:02:37,320 Speaker 2: seen that in recent history. They don't have to meet 48 00:02:37,360 --> 00:02:37,799 Speaker 2: to do this. 49 00:02:38,840 --> 00:02:41,240 Speaker 3: That's true, Yeah, I mean I think they would probably 50 00:02:41,320 --> 00:02:43,640 Speaker 3: argue that it doesn't. Anytime they need to respond to 51 00:02:44,600 --> 00:02:47,520 Speaker 3: changes in the economy in between their meetings, they can. 52 00:02:48,120 --> 00:02:50,360 Speaker 3: They can hold emergency meetings and they've done that. 53 00:02:50,360 --> 00:02:52,239 Speaker 4: That's a really good point. I mean, I do remember 54 00:02:52,240 --> 00:02:54,320 Speaker 4: when we get surprise moves. I think about that, and 55 00:02:54,320 --> 00:02:55,800 Speaker 4: it sound like, well like, oh remember. 56 00:02:55,520 --> 00:02:57,960 Speaker 2: The days came in that long ago during COVID, we 57 00:02:58,000 --> 00:02:58,320 Speaker 2: got it. 58 00:02:58,440 --> 00:03:01,440 Speaker 4: That's true, but I mean, and it really would have 59 00:03:01,440 --> 00:03:03,680 Speaker 4: an impact on the markets, right, And I do feel like, 60 00:03:04,000 --> 00:03:06,840 Speaker 4: I mean, I wonder what's next. Does he limit the 61 00:03:06,919 --> 00:03:10,560 Speaker 4: FED members from speaking because they speak a lot? Like 62 00:03:10,600 --> 00:03:13,560 Speaker 4: if you want a limit communication or is that a 63 00:03:13,680 --> 00:03:15,880 Speaker 4: useful tool in kind of getting some of the message 64 00:03:15,919 --> 00:03:17,720 Speaker 4: out or differing points of views? 65 00:03:18,800 --> 00:03:21,080 Speaker 3: Sure, the communications piece of it had there has been 66 00:03:21,120 --> 00:03:22,640 Speaker 3: a really big question. We talked to a lot of 67 00:03:22,680 --> 00:03:25,360 Speaker 3: people because Warsh of course had made these comments and 68 00:03:25,480 --> 00:03:28,280 Speaker 3: floated these ideas even before he was confirmed as the chairman. 69 00:03:28,360 --> 00:03:31,639 Speaker 3: And you know, most people seem to agree or believe 70 00:03:31,680 --> 00:03:36,240 Speaker 3: that you can't really restrict other policymakers from getting out 71 00:03:36,240 --> 00:03:38,960 Speaker 3: there and speaking. So I think that, you know, we 72 00:03:39,040 --> 00:03:41,680 Speaker 3: expect that they will continue to Now it seems like 73 00:03:41,720 --> 00:03:43,520 Speaker 3: there's been a little bit of it's been a little 74 00:03:43,520 --> 00:03:45,920 Speaker 3: bit quiet lately. That does tend to happen in the summertime, 75 00:03:45,960 --> 00:03:47,960 Speaker 3: so it's a little early to tell whether there has 76 00:03:48,040 --> 00:03:50,080 Speaker 3: been any kind of influence. I mean, there could be 77 00:03:50,080 --> 00:03:52,040 Speaker 3: a little bit of a grace period or differing a 78 00:03:52,040 --> 00:03:54,840 Speaker 3: bit for some of them to the new chairman. But 79 00:03:54,880 --> 00:03:57,480 Speaker 3: I don't think we would be very surprised if we 80 00:03:57,560 --> 00:04:00,600 Speaker 3: saw a big change, as you say, maybe the number 81 00:04:00,680 --> 00:04:02,760 Speaker 3: of a public remarks from other officials. 82 00:04:02,760 --> 00:04:04,520 Speaker 5: Things change, Things change. 83 00:04:04,880 --> 00:04:08,360 Speaker 2: Well, it raises the question too about the communicating because 84 00:04:08,720 --> 00:04:13,520 Speaker 2: communication happens a lot of different ways. One of the 85 00:04:13,560 --> 00:04:16,040 Speaker 2: ways is when FED speakers are out there and they're 86 00:04:16,360 --> 00:04:19,720 Speaker 2: allowed to speak, and they're all able to say really 87 00:04:19,720 --> 00:04:22,400 Speaker 2: whatever they want to. The press and to give press 88 00:04:22,400 --> 00:04:26,640 Speaker 2: conference or to give speeches rather do interviews. The other 89 00:04:26,680 --> 00:04:28,800 Speaker 2: part of it has to do when the FED chair 90 00:04:28,920 --> 00:04:31,960 Speaker 2: actually speaks, and that's certainly when everybody tunes in at 91 00:04:32,000 --> 00:04:35,200 Speaker 2: the same time. So there's no you know that it's 92 00:04:35,200 --> 00:04:38,000 Speaker 2: not really I think people could argue, well, the members 93 00:04:38,000 --> 00:04:40,080 Speaker 2: of the FED will still be able to communicate, would 94 00:04:40,120 --> 00:04:42,240 Speaker 2: still be able to communicate even if there were fewer 95 00:04:42,240 --> 00:04:44,280 Speaker 2: press conferences and they met fewer times. 96 00:04:46,200 --> 00:04:50,960 Speaker 3: Sure, Sure, And if those members wanted to give guidance 97 00:04:51,000 --> 00:04:52,880 Speaker 3: on where they see the economy headed and where they 98 00:04:52,880 --> 00:04:55,960 Speaker 3: see interest rates headed, they could certainly do that, even 99 00:04:56,120 --> 00:04:59,320 Speaker 3: if Kevin worsh couldn't. So it's hard to know what 100 00:04:59,360 --> 00:05:01,840 Speaker 3: the argument really would be. And then to argue, you know, 101 00:05:01,880 --> 00:05:04,400 Speaker 3: our give the counterpoint when we don't fully know what 102 00:05:04,440 --> 00:05:07,200 Speaker 3: would be the reason him behind this. But we'll keep 103 00:05:07,279 --> 00:05:09,800 Speaker 3: we'll keep asking and reporting it out ourselves. 104 00:05:09,960 --> 00:05:12,080 Speaker 4: Yeah, so that means some work for you guys this weekend. 105 00:05:12,120 --> 00:05:16,920 Speaker 4: I'm just gonna say, late tonight, Kate, thank you so much, 106 00:05:16,960 --> 00:05:19,000 Speaker 4: really appreciate that you weighing in here and giving us 107 00:05:19,320 --> 00:05:22,640 Speaker 4: someone Elysis Kate Davidson. She's mamaging editor vieus economic policy. 108 00:05:22,720 --> 00:05:25,839 Speaker 4: She's out there in the Bloomberg News DC Bureau. 109 00:05:26,279 --> 00:05:30,120 Speaker 1: You're listening to the Bloomberg Business Week Daily podcast. Catch 110 00:05:30,200 --> 00:05:32,880 Speaker 1: us live weekday afternoons from two to five e's during 111 00:05:32,880 --> 00:05:36,320 Speaker 1: this Listen on Applecarplay and Android Auto with the Bloomberg 112 00:05:36,360 --> 00:05:39,760 Speaker 1: Business app, or watch us live on YouTube. 113 00:05:41,200 --> 00:05:44,440 Speaker 2: It's being told through mag seven earnings, at least this week, 114 00:05:44,480 --> 00:05:48,280 Speaker 2: when four of the big companies reported Amazon shares surging 115 00:05:48,320 --> 00:05:51,599 Speaker 2: after the company reported cloud computing revenue accelerated for a 116 00:05:51,640 --> 00:05:55,080 Speaker 2: fifth straight quarter, it eased investors concern that it won't 117 00:05:55,080 --> 00:05:58,040 Speaker 2: produce a return on huge expenditures to meet the booming 118 00:05:58,080 --> 00:06:01,120 Speaker 2: demand for AI. And then Carol, there's Apple. 119 00:06:00,920 --> 00:06:04,120 Speaker 4: Tumbling after component shortages wait on the company's sales forecast, 120 00:06:04,160 --> 00:06:08,039 Speaker 4: signaling that industry wide supply constraints are taking a bigger 121 00:06:08,720 --> 00:06:11,600 Speaker 4: toll than anticipated. He's been one of the voices guiding 122 00:06:11,680 --> 00:06:14,240 Speaker 4: us through all of these earnings this week and really 123 00:06:14,320 --> 00:06:16,680 Speaker 4: last ed La, the host of Bloomberg Tech in the 124 00:06:16,680 --> 00:06:20,520 Speaker 4: Bloomberg San Francisco Bureau, ed, Amazon and Microsoft were cheered, 125 00:06:20,600 --> 00:06:25,159 Speaker 4: Apple and Alphabet not so much. Is there a clear 126 00:06:25,200 --> 00:06:27,600 Speaker 4: AI narrative or is it all company specific? 127 00:06:29,720 --> 00:06:31,400 Speaker 6: There was a note that hit my inbox from a 128 00:06:31,480 --> 00:06:34,840 Speaker 6: zoo this morning that had an image at the top 129 00:06:34,880 --> 00:06:37,840 Speaker 6: of it that said it was a red hat that 130 00:06:37,880 --> 00:06:39,760 Speaker 6: people will be familiar with with something else, but it 131 00:06:39,839 --> 00:06:44,760 Speaker 6: said make fundamentals great again, and it was trying to. 132 00:06:44,800 --> 00:06:45,960 Speaker 5: Kind of apply that. 133 00:06:46,320 --> 00:06:48,240 Speaker 6: You know, I think if we should probably strip out 134 00:06:48,240 --> 00:06:51,880 Speaker 6: Apple from the hyperscalus right, because it's muddled. But you know, 135 00:06:51,880 --> 00:06:54,320 Speaker 6: why is it that Alphabet was punished and the other 136 00:06:54,400 --> 00:06:55,640 Speaker 6: two really cheered. 137 00:06:56,000 --> 00:06:56,440 Speaker 5: It's hard. 138 00:06:56,640 --> 00:06:59,679 Speaker 6: It's hard to answer that because one of the things 139 00:06:59,680 --> 00:07:03,800 Speaker 6: that the streetlights about Microsoft was there was stuff beyond 140 00:07:03,839 --> 00:07:06,480 Speaker 6: the top line growth. So they gave data around Copilot 141 00:07:06,520 --> 00:07:09,320 Speaker 6: and how well that's doing. You know, Amazon gave us 142 00:07:09,360 --> 00:07:12,320 Speaker 6: the extra figures of revenue run rate for the AI 143 00:07:12,440 --> 00:07:15,440 Speaker 6: business and revenue run rate for the chips business. But 144 00:07:15,680 --> 00:07:17,920 Speaker 6: Alphabet also gave us stuff like that. They told us 145 00:07:17,920 --> 00:07:21,680 Speaker 6: about Gemini and tokens per minute, and for one reason. 146 00:07:21,480 --> 00:07:23,920 Speaker 5: Or another, you know, it just wasn't enough. 147 00:07:24,040 --> 00:07:29,160 Speaker 6: But in general, all three of them showed increased commitment spending. 148 00:07:29,480 --> 00:07:32,600 Speaker 6: Microsoft said it will protect free cash flow, and they 149 00:07:32,640 --> 00:07:37,040 Speaker 6: all showed massive cloud growth. And that's the summary if 150 00:07:37,120 --> 00:07:39,280 Speaker 6: you just take away whatever the market reaction was in 151 00:07:39,320 --> 00:07:39,840 Speaker 6: any case. 152 00:07:39,920 --> 00:07:42,600 Speaker 2: So, yeah, the market reaction for each of these on 153 00:07:42,640 --> 00:07:47,240 Speaker 2: their own notwithstanding, but the narrative hasn't changed at all 154 00:07:47,640 --> 00:07:49,920 Speaker 2: since before Alphabet reported last week. 155 00:07:50,680 --> 00:07:51,160 Speaker 7: Not really. 156 00:07:51,240 --> 00:07:53,320 Speaker 6: I mean like there's a lot of specifics that are 157 00:07:53,320 --> 00:07:57,400 Speaker 6: worth discussion. Amazon raised capex by twenty billion dollars for 158 00:07:57,480 --> 00:08:01,720 Speaker 6: this year in large part because the host of building 159 00:08:01,720 --> 00:08:05,280 Speaker 6: infrastructures going up, right, So it's gone from two hundred 160 00:08:05,440 --> 00:08:07,400 Speaker 6: billion dollars to two hundred and twenty billion dollars. But 161 00:08:07,480 --> 00:08:10,200 Speaker 6: what Andy Jesse said was that's largely because of higher 162 00:08:10,280 --> 00:08:15,040 Speaker 6: memory prices. It's not necessarily raising capex because they feel 163 00:08:15,080 --> 00:08:18,400 Speaker 6: like that would make them move faster on the infrastructure. 164 00:08:19,200 --> 00:08:20,600 Speaker 5: But the cloud growth is there. 165 00:08:20,760 --> 00:08:24,000 Speaker 6: You know, Aws growth of thirty seven percent was pretty 166 00:08:24,040 --> 00:08:29,040 Speaker 6: handsomely above street expectations. Azure's growth of forty three percent 167 00:08:29,200 --> 00:08:31,840 Speaker 6: was near it to being in line, but it was 168 00:08:31,920 --> 00:08:34,160 Speaker 6: like really cheered for one reason or another. 169 00:08:34,760 --> 00:08:42,280 Speaker 5: Nothing's changed. Spending go up, cloud growth go up. To 170 00:08:42,400 --> 00:08:44,120 Speaker 5: put it simply, I love that. 171 00:08:46,600 --> 00:08:50,960 Speaker 4: Qualcom. I don't know should we bring is there anybody else. 172 00:08:50,800 --> 00:08:52,880 Speaker 2: We could bring? In Rivian I we want to talk about. 173 00:08:53,080 --> 00:08:53,920 Speaker 4: Okay, But even though. 174 00:08:53,800 --> 00:08:55,520 Speaker 2: It's not one of the mag because I not a 175 00:08:55,520 --> 00:08:57,439 Speaker 2: great conversation with the company's CFO. 176 00:08:57,600 --> 00:09:00,600 Speaker 4: He did, Yeah, Ed talk more of. 177 00:09:00,520 --> 00:09:02,839 Speaker 2: The MAG seven. But I want to talk to you 178 00:09:02,880 --> 00:09:05,079 Speaker 2: about Rivian because this is a company you've followed since 179 00:09:05,320 --> 00:09:09,920 Speaker 2: literally before it went public. You understand this industry better 180 00:09:09,960 --> 00:09:12,240 Speaker 2: than pretty much anybody else. But the fact of the 181 00:09:12,240 --> 00:09:15,559 Speaker 2: matter is Rivian's facing the same problems that Ford is facing. 182 00:09:15,600 --> 00:09:18,640 Speaker 2: The general motors are sitting that Tesla's facing, and that's well, 183 00:09:18,679 --> 00:09:21,280 Speaker 2: what is the appetite for evs in this country? 184 00:09:22,240 --> 00:09:26,520 Speaker 6: Yeah, I mean the EV market generally has slowed over 185 00:09:26,559 --> 00:09:30,680 Speaker 6: a number of years in America. Enthusiasm is gone. Even 186 00:09:30,720 --> 00:09:33,360 Speaker 6: with the short term of the war in Iran and 187 00:09:33,400 --> 00:09:37,360 Speaker 6: what that's done for gas prices, you know, it's not 188 00:09:37,480 --> 00:09:41,560 Speaker 6: really changed trajectory. Rivian open higher two percent and it's 189 00:09:41,600 --> 00:09:44,880 Speaker 6: now down more than seven percent in the session. But 190 00:09:44,920 --> 00:09:47,920 Speaker 6: they had a good quarter where basically they've been losing 191 00:09:47,960 --> 00:09:50,880 Speaker 6: money for a long time. Those losses have narrowed and 192 00:09:50,920 --> 00:09:53,760 Speaker 6: they launched their mass market product in a really small 193 00:09:53,800 --> 00:09:54,880 Speaker 6: way at first, the R two. 194 00:09:55,440 --> 00:09:56,440 Speaker 5: But they're now like. 195 00:09:56,400 --> 00:09:58,160 Speaker 6: Have something to show for it in the real world. 196 00:09:58,280 --> 00:10:00,720 Speaker 6: So you know, the conversation I have Claimic's onto the 197 00:10:00,720 --> 00:10:04,280 Speaker 6: CFO was very much like, Okay, this is it. Now, 198 00:10:04,360 --> 00:10:06,319 Speaker 6: You're you're in the You're to your mind, you're in 199 00:10:06,360 --> 00:10:08,360 Speaker 6: the bigger leagues. When you're going to start seeing some 200 00:10:08,400 --> 00:10:11,120 Speaker 6: financial returns on that, and you know, the back half 201 00:10:11,160 --> 00:10:12,400 Speaker 6: of this year is the answer. 202 00:10:12,760 --> 00:10:15,160 Speaker 4: Right, every kind of growth company or a new company 203 00:10:15,160 --> 00:10:17,480 Speaker 4: has to grow up at some point become a teenager 204 00:10:17,480 --> 00:10:21,200 Speaker 4: and an adult. Essentially. Hey, I want to sorry, Well, 205 00:10:21,240 --> 00:10:26,240 Speaker 4: it's true, it's the reality, right, I do want to 206 00:10:26,280 --> 00:10:29,040 Speaker 4: go back to Apple. You know, we talked about Apple 207 00:10:29,120 --> 00:10:33,600 Speaker 4: kind of looking smart regarding cash flow and capex spend, 208 00:10:33,960 --> 00:10:36,160 Speaker 4: and yet we have seen the stock under pressure. 209 00:10:37,080 --> 00:10:42,560 Speaker 6: Yeah, I mean, gosh, you also mentioned Qualcomm in passing 210 00:10:42,640 --> 00:10:45,160 Speaker 6: a second ago, so there's something common there. But this 211 00:10:45,240 --> 00:10:47,079 Speaker 6: is like a really profound reaction in. 212 00:10:47,040 --> 00:10:48,240 Speaker 5: The stock from Apple. 213 00:10:48,600 --> 00:10:50,920 Speaker 6: Yeah, you know, it's down nine and a half percent, 214 00:10:50,960 --> 00:10:52,960 Speaker 6: but put a better way, it's the biggest drop since 215 00:10:53,000 --> 00:10:56,040 Speaker 6: the world shut down for COVID in twenty twenty March sixteenth, 216 00:10:56,080 --> 00:11:02,400 Speaker 6: twenty twenty, and the store put the numbers aside. Was 217 00:11:02,480 --> 00:11:06,199 Speaker 6: that Tim Cook, in his final weather call was CEO 218 00:11:06,320 --> 00:11:09,920 Speaker 6: of Apple, made an admission that they'd got it wrong 219 00:11:10,120 --> 00:11:13,040 Speaker 6: in the supply chain. So it's not just that memory 220 00:11:13,120 --> 00:11:15,960 Speaker 6: chip prices are higher. They said those will continue to 221 00:11:15,960 --> 00:11:19,000 Speaker 6: be higher into the September quarter. It's that they basically 222 00:11:19,040 --> 00:11:22,880 Speaker 6: said they misjudged demand and they placed the wrong volume 223 00:11:22,920 --> 00:11:26,280 Speaker 6: of orders for lead edge processes with their suppliers, and 224 00:11:26,360 --> 00:11:30,120 Speaker 6: so in the end, they the demand is there for iPhones, 225 00:11:30,440 --> 00:11:32,920 Speaker 6: they couldn't build enough of them because they got the 226 00:11:33,000 --> 00:11:37,199 Speaker 6: math wrong on supply of components, which from yeah. 227 00:11:37,120 --> 00:11:40,960 Speaker 2: Yeah, where demand will demand still be there when they 228 00:11:41,040 --> 00:11:41,720 Speaker 2: raise prices? 229 00:11:41,760 --> 00:11:44,240 Speaker 6: So the next one, well, you know, Anarag made this 230 00:11:44,280 --> 00:11:46,880 Speaker 6: point with us right that he felt the iPhone cycle 231 00:11:47,200 --> 00:11:50,000 Speaker 6: for the seventeen generation had one good quarter left in it. 232 00:11:50,520 --> 00:11:52,560 Speaker 6: When you get to September and then suddenly you're in 233 00:11:52,600 --> 00:11:56,560 Speaker 6: the release of the iPhone eighteen. That's where the higher 234 00:11:56,600 --> 00:11:59,800 Speaker 6: memory pricing issue will show up. So I don't know, really, 235 00:11:59,840 --> 00:12:02,960 Speaker 6: I can't really answer that. The guide was that revenue 236 00:12:02,960 --> 00:12:05,240 Speaker 6: growth in the September quarter will be nine percent to 237 00:12:05,280 --> 00:12:08,280 Speaker 6: eleven percent, and the street was looking for twelve percent, 238 00:12:08,480 --> 00:12:11,480 Speaker 6: which was already taking into account a very tough environment. 239 00:12:11,800 --> 00:12:15,240 Speaker 6: And so Apple's projection came in below that there was 240 00:12:15,280 --> 00:12:18,480 Speaker 6: no sentimentality for the fact that it was it was 241 00:12:18,480 --> 00:12:21,880 Speaker 6: Tim Cook's final call. You know that's that's not what 242 00:12:22,160 --> 00:12:23,040 Speaker 6: the market trades on. 243 00:12:23,200 --> 00:12:25,400 Speaker 4: Well as the guy who oversaw a supply check, right, 244 00:12:25,440 --> 00:12:26,560 Speaker 4: that's a rough way to go out. 245 00:12:27,360 --> 00:12:28,160 Speaker 2: He'll see's still there. 246 00:12:28,200 --> 00:12:28,600 Speaker 5: He's not out. 247 00:12:28,679 --> 00:12:30,760 Speaker 4: He's not out, but you know what I mean, Ed Ludlow, 248 00:12:30,840 --> 00:12:32,520 Speaker 4: thank you so much, Realie, thank you appreciate it. 249 00:12:32,600 --> 00:12:32,840 Speaker 7: Yep. 250 00:12:32,880 --> 00:12:35,480 Speaker 4: Host to Bloomberg Tech out there on the West Coast. 251 00:12:35,760 --> 00:12:38,560 Speaker 2: Stay with us. More from Bloomberg Business Week Daily coming 252 00:12:38,600 --> 00:12:39,559 Speaker 2: up after this. 253 00:12:43,480 --> 00:12:47,320 Speaker 1: You're listening to the Bloomberg Business Week Daily Podcast. Catch 254 00:12:47,400 --> 00:12:50,080 Speaker 1: us live weekday afternoons from two to five yes during 255 00:12:50,280 --> 00:12:54,240 Speaker 1: listen on Applecarplay and Android Atto with the Bloomberg Business app, 256 00:12:54,400 --> 00:12:57,199 Speaker 1: or watch us live on YouTube. 257 00:12:57,720 --> 00:13:00,200 Speaker 2: It is the perfect time to bring back As because 258 00:13:00,200 --> 00:13:01,560 Speaker 2: we've got a lot to talk about with him. We 259 00:13:01,600 --> 00:13:03,600 Speaker 2: spent a lot of our first couple of hours today 260 00:13:03,679 --> 00:13:07,520 Speaker 2: talking about the drama around Situational Awareness selling a chunk 261 00:13:07,520 --> 00:13:10,679 Speaker 2: of its AI related public equities. Then there's the latest 262 00:13:10,679 --> 00:13:14,280 Speaker 2: from the mag seven. We did see shares of Meta 263 00:13:14,360 --> 00:13:16,600 Speaker 2: fall eight percent yesterday, I think after it gave that 264 00:13:16,600 --> 00:13:19,680 Speaker 2: disappointing quarterly revenue forecast. At the same time, though Carol 265 00:13:19,880 --> 00:13:23,719 Speaker 2: aggressive AI spending plans by Amazon, Microsoft, and Alphabet gave 266 00:13:23,760 --> 00:13:26,640 Speaker 2: fresh evidence that demand for chips and related equipment will 267 00:13:26,679 --> 00:13:28,959 Speaker 2: remain strong and offered relief to a sector that's been 268 00:13:28,960 --> 00:13:30,640 Speaker 2: battered just in the last few days. 269 00:13:30,720 --> 00:13:33,199 Speaker 4: Can't wait to see what he has to say. Edzititren 270 00:13:33,240 --> 00:13:35,560 Speaker 4: is back with a CEO of Easy Primary Research, host 271 00:13:35,559 --> 00:13:37,959 Speaker 4: of the Better Offline podcast. He also writes the Where's 272 00:13:38,000 --> 00:13:41,760 Speaker 4: Your ed At? Newsletter. To say he's an AI skeptic 273 00:13:42,120 --> 00:13:44,120 Speaker 4: would be putting it likely. Some might say he's an 274 00:13:44,120 --> 00:13:47,480 Speaker 4: AI hater. Either way, we're always interested in his perspective. 275 00:13:47,520 --> 00:13:50,520 Speaker 4: He joins us in our Bloomberg Interactive Broker studio, Where 276 00:13:50,559 --> 00:13:53,840 Speaker 4: are we in terms of the AI narrative in your 277 00:13:53,920 --> 00:13:55,079 Speaker 4: view and what's the reality? 278 00:13:55,480 --> 00:13:58,160 Speaker 7: Well, I think investors have to ask a question right now, 279 00:13:58,280 --> 00:14:00,520 Speaker 7: what am I getting into when I invest in Microsoft, 280 00:14:00,559 --> 00:14:04,320 Speaker 7: Google and Amazon. So UBS estimates that twenty seven percent 281 00:14:04,360 --> 00:14:07,080 Speaker 7: of Google Clouds revenue this year will be open AI 282 00:14:07,200 --> 00:14:10,680 Speaker 7: and anthropic, increasing to over forty eight percent next year. 283 00:14:11,080 --> 00:14:12,920 Speaker 7: That is a remarkable amount of money. It's going to 284 00:14:12,920 --> 00:14:15,800 Speaker 7: be over one hundred and twenty four billion dollars next year. 285 00:14:16,240 --> 00:14:18,760 Speaker 7: Everyone is buying into these stocks because they believe all 286 00:14:18,800 --> 00:14:22,080 Speaker 7: of that capex is going towards diverse and spread out 287 00:14:22,120 --> 00:14:24,880 Speaker 7: AI demand, when in fact, what it's actually doing is 288 00:14:24,920 --> 00:14:29,600 Speaker 7: helping create infrastructure for two unprofitable, unsustainable companies. 289 00:14:30,200 --> 00:14:33,200 Speaker 2: So those the other one would be anthropic. Yes, you argue, 290 00:14:33,240 --> 00:14:34,960 Speaker 2: so give us more data because you have the micro 291 00:14:35,000 --> 00:14:37,760 Speaker 2: you're citing Microsoft. But what about AWS? 292 00:14:37,800 --> 00:14:39,800 Speaker 7: Well, that was what I was saying. So Barclay's actually 293 00:14:39,880 --> 00:14:42,680 Speaker 7: says that this year thirteen percent of AWS revenue will 294 00:14:42,720 --> 00:14:45,600 Speaker 7: be both open air and anthropic, and next year will 295 00:14:45,600 --> 00:14:49,080 Speaker 7: be eighteen percent. AWS much bigger business than Google Cloud. Now, 296 00:14:49,160 --> 00:14:50,880 Speaker 7: just to be clear, when I was saying that twenty 297 00:14:50,960 --> 00:14:54,000 Speaker 7: seven percent this year and forty eight percent next year 298 00:14:54,040 --> 00:14:57,160 Speaker 7: for Google Cloud, I meant both anthropic and open al Okay, 299 00:14:57,200 --> 00:14:59,280 Speaker 7: most people don't know that open ai is a large 300 00:14:59,280 --> 00:15:02,360 Speaker 7: customer of Google Cloud. It's not a well, it's not 301 00:15:02,400 --> 00:15:04,920 Speaker 7: a well known fact. But this was This was actually 302 00:15:04,960 --> 00:15:07,040 Speaker 7: mentioned by ubs Is Stephen Jew. 303 00:15:07,200 --> 00:15:10,080 Speaker 2: So where would those companies be right now without anthropic 304 00:15:10,120 --> 00:15:11,200 Speaker 2: and without open ai? 305 00:15:11,360 --> 00:15:13,760 Speaker 7: Well, I have serious questions about that. So in counter 306 00:15:13,880 --> 00:15:16,480 Speaker 7: year twenty twenty five, according to my own reporting about 307 00:15:16,480 --> 00:15:19,880 Speaker 7: open aiy's numbers, sixty nine percent of the year over 308 00:15:19,960 --> 00:15:23,680 Speaker 7: year growth of Microsoft Intelligent Cloud segment was actually from 309 00:15:23,720 --> 00:15:26,520 Speaker 7: open Ai. Without that, it would have only grown eight 310 00:15:26,520 --> 00:15:29,320 Speaker 7: percent year of view, which is barely beating inflation. And 311 00:15:29,400 --> 00:15:32,360 Speaker 7: so everyone is being sold what I consider kind of 312 00:15:32,400 --> 00:15:34,440 Speaker 7: a lie. It's honestly kind of a scandal. 313 00:15:35,480 --> 00:15:37,720 Speaker 4: So this goes back to I feel like we have 314 00:15:37,840 --> 00:15:42,400 Speaker 4: companies the circular financing the circularity of it all and 315 00:15:42,520 --> 00:15:48,560 Speaker 4: kind of creating demand for their products. So when does 316 00:15:48,600 --> 00:15:51,200 Speaker 4: it start? When does the I asked this earlier with 317 00:15:51,200 --> 00:15:53,920 Speaker 4: the guests, when does the party end? In your view? 318 00:15:53,520 --> 00:15:56,600 Speaker 7: And yeah, so with open Aiy's IPO, I think that 319 00:15:56,640 --> 00:15:58,760 Speaker 7: could be one of the flashpoints. Remember, this company was 320 00:15:58,800 --> 00:16:01,080 Speaker 7: meant to go public this year. They about a month 321 00:16:01,160 --> 00:16:03,040 Speaker 7: or two ago, and now The New York Times has 322 00:16:03,080 --> 00:16:07,000 Speaker 7: reported that they're considering they are delaying until twenty twenty seven. 323 00:16:07,160 --> 00:16:09,720 Speaker 7: That's lethal for a number of people. But open Ai 324 00:16:09,840 --> 00:16:13,320 Speaker 7: and Anthropic need continual flows of capital. They do not 325 00:16:13,520 --> 00:16:16,400 Speaker 7: pay their bills out of existing cash flow, So when 326 00:16:16,400 --> 00:16:18,880 Speaker 7: anything happens to that cash, I think that's the first 327 00:16:19,720 --> 00:16:22,240 Speaker 7: kind of domino to four. But then again, there's also 328 00:16:22,320 --> 00:16:24,800 Speaker 7: the overall problem of data center's just not getting built 329 00:16:24,920 --> 00:16:28,240 Speaker 7: very fast, taking about twelve to thirty six months, depending 330 00:16:28,240 --> 00:16:31,000 Speaker 7: on how small or larger data center is actually being 331 00:16:31,040 --> 00:16:34,400 Speaker 7: built at. And the problem is is that everyone believes 332 00:16:34,400 --> 00:16:36,880 Speaker 7: that AI is coming out of cash flow, that AI 333 00:16:37,000 --> 00:16:39,320 Speaker 7: is coming out of just this diverse revenue base, when 334 00:16:39,360 --> 00:16:42,200 Speaker 7: it's really not. It's extremely narrow. The Information reported a 335 00:16:42,240 --> 00:16:44,920 Speaker 7: few months ago that eighty nine percent of the largest 336 00:16:44,960 --> 00:16:48,120 Speaker 7: AI companies, well, their revenue comes just from open AI 337 00:16:48,160 --> 00:16:50,360 Speaker 7: and anthropic. It's heavily centralized. 338 00:16:50,440 --> 00:16:52,880 Speaker 4: Doesn't it have to be centralized to some extent? This 339 00:16:52,920 --> 00:16:55,400 Speaker 4: is expensive to do or no in terms of data 340 00:16:55,400 --> 00:16:57,160 Speaker 4: center build out and so on and so forth. And 341 00:16:57,200 --> 00:17:02,040 Speaker 4: what's going to make AI rid of AI? The ability 342 00:17:02,080 --> 00:17:04,679 Speaker 4: for it to be really really good is having access 343 00:17:04,720 --> 00:17:06,639 Speaker 4: to lots of information. So doesn't it have to be 344 00:17:06,720 --> 00:17:08,760 Speaker 4: to some extent ed concentrated. 345 00:17:08,960 --> 00:17:11,880 Speaker 7: Well, when I say concentration, I mean concentration of revenue 346 00:17:12,000 --> 00:17:12,959 Speaker 7: in these two companies. 347 00:17:13,000 --> 00:17:15,000 Speaker 4: No, I understand, but to make it good, So doesn't 348 00:17:15,000 --> 00:17:17,840 Speaker 4: it make sense that those who are expose the most 349 00:17:17,960 --> 00:17:19,760 Speaker 4: it's going to be concentrated to some extent. 350 00:17:19,800 --> 00:17:22,480 Speaker 7: Well, I mean when we're talking about so Siteline Climates 351 00:17:22,520 --> 00:17:25,000 Speaker 7: said that they saw back in February about one hundred 352 00:17:25,040 --> 00:17:27,720 Speaker 7: and ninety gig what's worth of data center capacity being 353 00:17:27,760 --> 00:17:30,760 Speaker 7: built in the next few years. It was built rounder planning. 354 00:17:31,119 --> 00:17:32,840 Speaker 7: Now if you work that out with a PUE, so 355 00:17:33,080 --> 00:17:35,560 Speaker 7: just the efficiency rating of one point three, you're coming 356 00:17:35,560 --> 00:17:38,280 Speaker 7: out to twelve million a megawatt over one point six 357 00:17:38,359 --> 00:17:42,600 Speaker 7: trillion dollars of annual revenue needed to satiate those data centers. 358 00:17:42,800 --> 00:17:45,680 Speaker 7: Having two customers is not going to do that. Even 359 00:17:45,720 --> 00:17:49,600 Speaker 7: that they're most spendy and Robert and open Ai they 360 00:17:49,600 --> 00:17:51,840 Speaker 7: can't afford anything. They need venture capital, but there only 361 00:17:51,840 --> 00:17:54,400 Speaker 7: can spend four hundred billion a year. And that's if 362 00:17:54,400 --> 00:17:56,080 Speaker 7: they get that far, which I don't believe they will. 363 00:17:56,280 --> 00:17:58,240 Speaker 4: How much do we know about their balance youets really 364 00:17:58,480 --> 00:17:59,320 Speaker 4: really well. 365 00:17:59,359 --> 00:18:02,680 Speaker 7: I from personal experience a great deal about open a 366 00:18:02,760 --> 00:18:05,199 Speaker 7: Eyes because I reported their audo do financials with the 367 00:18:05,200 --> 00:18:08,480 Speaker 7: Financial Times right, and it's a company just burning cash. 368 00:18:08,480 --> 00:18:10,760 Speaker 7: They lost twenty point nine billion dollars in twenty twenty 369 00:18:10,800 --> 00:18:13,919 Speaker 7: five and things are only getting worse. And what's crazy 370 00:18:13,960 --> 00:18:17,000 Speaker 7: as well, was over eight hundred million dollars of Open 371 00:18:17,040 --> 00:18:20,480 Speaker 7: Eyes revenue came from soft Bank for their crystall intelligence 372 00:18:20,480 --> 00:18:23,600 Speaker 7: and guess that's really what it's called Their Crystalli intelligence program, 373 00:18:23,680 --> 00:18:27,040 Speaker 7: which I can find no evidence of actually anything happening. 374 00:18:27,440 --> 00:18:29,760 Speaker 7: And soft Bank a large shareholder of open aie with 375 00:18:29,840 --> 00:18:30,760 Speaker 7: no board seats. 376 00:18:32,280 --> 00:18:33,960 Speaker 2: So oh, go ahead, Carol. 377 00:18:34,040 --> 00:18:36,840 Speaker 4: One more question though, Like you talk about for Google 378 00:18:36,920 --> 00:18:41,000 Speaker 4: Cloud the exposure right, and you said forty eight percent 379 00:18:41,040 --> 00:18:44,120 Speaker 4: next year. In terms of these two customers, I have 380 00:18:44,200 --> 00:18:47,960 Speaker 4: to say, there are smart people running these companies, and 381 00:18:48,640 --> 00:18:50,840 Speaker 4: normally you would say your exposure to just a handful 382 00:18:50,880 --> 00:18:53,960 Speaker 4: of customers is not a great thing. Do you say 383 00:18:53,960 --> 00:18:56,359 Speaker 4: that these companies that aren't doing their due diligence be 384 00:18:56,440 --> 00:18:59,480 Speaker 4: it Alphabet or you know, pick your hyperscaler. 385 00:19:00,000 --> 00:19:02,280 Speaker 7: I think they did their due diligence in the sense 386 00:19:02,320 --> 00:19:04,960 Speaker 7: that they said, we are going to create our largest customers, 387 00:19:05,000 --> 00:19:07,159 Speaker 7: and we're going to own large parts of them, and 388 00:19:07,359 --> 00:19:09,359 Speaker 7: on top of that, we're going to own all of 389 00:19:09,400 --> 00:19:12,680 Speaker 7: their infrastructure. Google has a nice they have a nice 390 00:19:12,680 --> 00:19:16,240 Speaker 7: thing going here to buy TPUs from well, sorry, Broadcom 391 00:19:16,320 --> 00:19:20,000 Speaker 7: sells TPUs to Google. They are then sold to Anthropic 392 00:19:20,040 --> 00:19:22,920 Speaker 7: and then rented back to Anthropic through Google, Google gets 393 00:19:22,960 --> 00:19:25,720 Speaker 7: to double up on revenue. This sounds really good right 394 00:19:25,760 --> 00:19:29,200 Speaker 7: up until you realize that Anthropic and open Ai are unsustainable, 395 00:19:29,600 --> 00:19:32,160 Speaker 7: so what they may be. And the problem is we're 396 00:19:32,160 --> 00:19:34,240 Speaker 7: saying these are smart people as it immediately makes me 397 00:19:34,280 --> 00:19:36,719 Speaker 7: think of Enron the smartest guys in the room. Not 398 00:19:36,760 --> 00:19:38,960 Speaker 7: saying anything like that's happening, but I'm. 399 00:19:38,800 --> 00:19:41,440 Speaker 4: Just saying, you have a fiduciary responsibility and you're right 400 00:19:41,520 --> 00:19:44,480 Speaker 4: if you go back to RAN And. 401 00:19:44,400 --> 00:19:48,080 Speaker 7: I think the point I'm making is with Google, they 402 00:19:48,200 --> 00:19:50,639 Speaker 7: probably thought they would be more customers. I imagine with 403 00:19:50,680 --> 00:19:53,919 Speaker 7: Azure and with Aws they thought would be more large players. 404 00:19:53,960 --> 00:19:56,320 Speaker 7: But the problem with Anthropic and open Ai is they've 405 00:19:56,400 --> 00:19:59,000 Speaker 7: raised two hundred and three hundred billion dollars of funding, 406 00:19:59,359 --> 00:20:02,560 Speaker 7: but they've actually raised more because open Ai and Anthropic 407 00:20:02,640 --> 00:20:05,600 Speaker 7: got all of their infrastructure built for them by Microsoft, 408 00:20:05,600 --> 00:20:08,119 Speaker 7: Google and Amazon. They didn't have to pay. I think 409 00:20:08,280 --> 00:20:11,520 Speaker 7: in the samman Elon Musk trial, one of the Microsoft 410 00:20:11,640 --> 00:20:14,680 Speaker 7: executives said that they cost one hundred billion dollars, so 411 00:20:14,840 --> 00:20:17,439 Speaker 7: call it like seventy eighty billion dollars of infrastructure. So 412 00:20:17,480 --> 00:20:19,840 Speaker 7: the problem is is that nobody else can get as 413 00:20:19,840 --> 00:20:22,040 Speaker 7: big as them. No one else can get that much compute, 414 00:20:22,040 --> 00:20:24,080 Speaker 7: no one else could afford that compute and have the 415 00:20:24,160 --> 00:20:27,240 Speaker 7: chance to do the pre training runs necessary, except now 416 00:20:27,359 --> 00:20:31,200 Speaker 7: China is coming up behind them, and it's unclear how 417 00:20:31,240 --> 00:20:33,879 Speaker 7: anyone really deals with any of the problems I've been 418 00:20:33,920 --> 00:20:37,880 Speaker 7: listening for years, which is unsustainable, unprofitable, and also not 419 00:20:37,920 --> 00:20:39,560 Speaker 7: really funding the ROI and AI. 420 00:20:40,119 --> 00:20:43,200 Speaker 2: We're speaking with Ed Zetron, the CEO of Easy Primary Research. 421 00:20:43,240 --> 00:20:47,000 Speaker 2: He joins us on set in the Bloomberg Interactive Brokers studio. 422 00:20:47,680 --> 00:20:50,919 Speaker 2: Ed play this out for us because I think a 423 00:20:50,920 --> 00:20:54,640 Speaker 2: lot of people think, okay, for there to be some 424 00:20:54,680 --> 00:20:57,800 Speaker 2: sort of ROI on this, one thing has to happen. 425 00:20:58,160 --> 00:21:01,399 Speaker 2: And like, the best case scenario for all this money 426 00:21:01,440 --> 00:21:06,200 Speaker 2: being spent is that productivity increases, Fewer people are needed 427 00:21:06,240 --> 00:21:09,280 Speaker 2: to do more things. There are some serious implications if 428 00:21:09,320 --> 00:21:11,119 Speaker 2: that were to come true and to the labor for 429 00:21:11,240 --> 00:21:14,159 Speaker 2: us and Dario Amideo Panthropic has talked about this in 430 00:21:14,200 --> 00:21:16,680 Speaker 2: the past. Maybe he's talking his book. I don't know. 431 00:21:16,920 --> 00:21:19,000 Speaker 2: The other side of this is, well, if that doesn't 432 00:21:19,000 --> 00:21:21,800 Speaker 2: come true, then what does it mean for these stocks 433 00:21:21,800 --> 00:21:25,399 Speaker 2: that have gained so much on hopes that they would 434 00:21:25,440 --> 00:21:28,560 Speaker 2: be responsible for some of this productivity increase? Like how 435 00:21:28,560 --> 00:21:30,240 Speaker 2: does the shoe drop? What happens? 436 00:21:30,400 --> 00:21:32,600 Speaker 7: Well, the thing is, if you think about what Amazon 437 00:21:32,640 --> 00:21:34,639 Speaker 7: Google and Microsoft had done in met to some extent, 438 00:21:34,680 --> 00:21:37,720 Speaker 7: but they're not selling compute capacity yet. Is they have 439 00:21:37,800 --> 00:21:40,960 Speaker 7: gone from being these cash heavy, these cash machines. They 440 00:21:41,040 --> 00:21:45,560 Speaker 7: just spill out money, low cash, burn high revenue, low 441 00:21:45,640 --> 00:21:50,080 Speaker 7: assets into these bulbous GPU filled asset mangus who are 442 00:21:50,119 --> 00:21:53,320 Speaker 7: just full of these semi built data centers for two 443 00:21:53,400 --> 00:21:56,920 Speaker 7: customers or three customers at best, so that they can 444 00:21:57,359 --> 00:21:59,600 Speaker 7: do want rent them out, so that they can rent 445 00:21:59,640 --> 00:22:02,160 Speaker 7: them all. And it isn't really clear what the plan 446 00:22:02,320 --> 00:22:04,720 Speaker 7: is at this point. And the problem is for me 447 00:22:04,800 --> 00:22:07,520 Speaker 7: to be right, it doesn't even have to go that badly. 448 00:22:08,000 --> 00:22:11,720 Speaker 7: Open Ai and Anthropic have to grow so large to 449 00:22:11,800 --> 00:22:14,840 Speaker 7: be able to make all of this data center capacity good. 450 00:22:14,920 --> 00:22:18,080 Speaker 7: I mean Google's I think the ubs estemate was like 451 00:22:18,080 --> 00:22:21,200 Speaker 7: seventy six billion dollars in twenty twenty seven of Google 452 00:22:21,240 --> 00:22:24,040 Speaker 7: Clouds revenue will come from Anthropic. How's Anthropic going to 453 00:22:24,080 --> 00:22:26,520 Speaker 7: afford that they burned tens of billions of dollars? So 454 00:22:27,080 --> 00:22:29,920 Speaker 7: it's not just that these companies are unprofitable and unsustainable, 455 00:22:30,000 --> 00:22:33,760 Speaker 7: but they have to grow so very large to make 456 00:22:33,800 --> 00:22:37,560 Speaker 7: aipay off because otherwise they just isn't demand for compute 457 00:22:37,560 --> 00:22:38,080 Speaker 7: at scale. 458 00:22:38,440 --> 00:22:41,200 Speaker 2: Last time you're on with us, we got a really 459 00:22:41,200 --> 00:22:43,760 Speaker 2: incredible response, to be honest, and a lot of people 460 00:22:43,760 --> 00:22:47,720 Speaker 2: who weren't typical viewers or listeners of our show saw 461 00:22:47,760 --> 00:22:49,560 Speaker 2: what you did and listened to what you did, and 462 00:22:49,640 --> 00:22:52,200 Speaker 2: it really seemed like there's this what you're saying is 463 00:22:52,240 --> 00:22:54,639 Speaker 2: resonating with a lot of people, like there's a It 464 00:22:54,680 --> 00:22:58,200 Speaker 2: was almost like there's this anti AI fervor that that's 465 00:22:58,240 --> 00:23:00,919 Speaker 2: out there, and I'm just curious why you think that is. 466 00:23:01,280 --> 00:23:04,560 Speaker 7: So I'm not sure it is ANTIAI don't get me wrong, 467 00:23:04,600 --> 00:23:08,440 Speaker 7: but I think it's also anti financial shenanigans. I think 468 00:23:08,480 --> 00:23:12,280 Speaker 7: everyone sees the circular financing. I think they see that Microsoft, 469 00:23:12,280 --> 00:23:15,720 Speaker 7: Google and Amazon gets basically all of their AI revenues 470 00:23:15,920 --> 00:23:18,680 Speaker 7: either through products they're pushing on their customers or indeed 471 00:23:18,840 --> 00:23:22,040 Speaker 7: compute span from anthropic and open AI. And the average 472 00:23:22,080 --> 00:23:26,200 Speaker 7: person's existence right now is so expensive, so hard, so difficult. 473 00:23:26,240 --> 00:23:28,960 Speaker 7: Getting a mortgage as a regular person is so difficult. 474 00:23:29,000 --> 00:23:31,520 Speaker 7: But if you're standing up a theoretical data center in 475 00:23:31,560 --> 00:23:34,400 Speaker 7: thirty six months full of Nvidia GPUs, the banks fall 476 00:23:34,440 --> 00:23:36,720 Speaker 7: over themselves to give you the money. Or we've just 477 00:23:36,800 --> 00:23:39,600 Speaker 7: raised what a nine percent bond. I mean, you can 478 00:23:39,760 --> 00:23:41,840 Speaker 7: raise anything if you have a data center. And I 479 00:23:41,880 --> 00:23:45,200 Speaker 7: think regular people can see that AI does not deliver 480 00:23:45,320 --> 00:23:48,560 Speaker 7: what people promise. They can see the opulence of the 481 00:23:48,560 --> 00:23:50,520 Speaker 7: people at the top of the AI industry, and they 482 00:23:50,560 --> 00:23:52,800 Speaker 7: can also see that they're being lied to and being 483 00:23:52,840 --> 00:23:57,560 Speaker 7: deliberately scared on top of all of this egregious circular financing. 484 00:23:57,880 --> 00:24:01,080 Speaker 4: So you think people are actually lying, like, oh, do 485 00:24:01,119 --> 00:24:03,920 Speaker 4: you think people specifically? I don't know, Like, is it 486 00:24:04,160 --> 00:24:08,359 Speaker 4: the companies at the hyperscalers, the CEOs, the bankers, like 487 00:24:08,520 --> 00:24:11,399 Speaker 4: do you think you know? And to be fair, we 488 00:24:11,440 --> 00:24:14,960 Speaker 4: really should reach out to everybody. But I mean, is 489 00:24:15,000 --> 00:24:17,240 Speaker 4: that what you're saying that I believe or do they 490 00:24:17,280 --> 00:24:18,920 Speaker 4: not or do they not really know? 491 00:24:19,280 --> 00:24:22,160 Speaker 7: I think they're overstating things. I think lying would suggest 492 00:24:22,160 --> 00:24:24,199 Speaker 7: the certain malice what have you. I don't want to 493 00:24:24,200 --> 00:24:27,240 Speaker 7: accuse anyone of but I believe that they are massively 494 00:24:27,240 --> 00:24:30,240 Speaker 7: overstating what AI will do. You'll notice that AI people 495 00:24:30,440 --> 00:24:32,800 Speaker 7: tend to speak in the future tense. They tend not 496 00:24:32,880 --> 00:24:35,359 Speaker 7: to say, oh, well today it can it's always AI 497 00:24:35,480 --> 00:24:38,680 Speaker 7: will AI will, Oh we're going to get the singularity. 498 00:24:38,760 --> 00:24:41,040 Speaker 7: Oh AI will do this and that that's because when 499 00:24:41,080 --> 00:24:43,920 Speaker 7: they talk about what's happening today, it's pretty mediocre outside 500 00:24:43,920 --> 00:24:46,479 Speaker 7: of code. And on top of that, these things are 501 00:24:46,520 --> 00:24:49,440 Speaker 7: horribly unsustainable and unprofitable. And on top of that, they've 502 00:24:49,440 --> 00:24:52,480 Speaker 7: got these destructive data centers, these massive eye saws that 503 00:24:52,680 --> 00:24:56,320 Speaker 7: poisoned black communities, these massive eye saws that need billions 504 00:24:56,320 --> 00:24:58,240 Speaker 7: of dollars at a time when it's hard for a 505 00:24:58,280 --> 00:25:01,160 Speaker 7: regular person to get a dime from the b So yeah, 506 00:25:01,280 --> 00:25:04,439 Speaker 7: I think that there is beyond just the misleading, this 507 00:25:04,600 --> 00:25:07,879 Speaker 7: general sense of unfairness that AI taps into. And on 508 00:25:07,920 --> 00:25:11,680 Speaker 7: top of that, if this all goes pair shaped, these 509 00:25:11,720 --> 00:25:14,040 Speaker 7: people are going to realize that there was an authority 510 00:25:14,080 --> 00:25:17,800 Speaker 7: crisis happening, that so many people got beguiled by hyperscalar 511 00:25:17,840 --> 00:25:20,119 Speaker 7: promises and what it ultimately is, and I'm quoting ed 512 00:25:20,160 --> 00:25:24,960 Speaker 7: Elson of profg Markets here. Our media, I believe has 513 00:25:25,040 --> 00:25:27,800 Speaker 7: a cult like worship of the wealthy, that they believe 514 00:25:27,840 --> 00:25:30,520 Speaker 7: that whatever the wealthy says will come true. And in 515 00:25:30,560 --> 00:25:33,200 Speaker 7: the past, with the tech industry, that's kind of come true, 516 00:25:33,359 --> 00:25:35,800 Speaker 7: except it stopped really coming true about ten to eleven 517 00:25:35,880 --> 00:25:39,119 Speaker 7: years ago, and we exited the era of hypergrowth, and 518 00:25:39,160 --> 00:25:42,200 Speaker 7: that's all AI is AI is an attempt to restart 519 00:25:42,280 --> 00:25:45,160 Speaker 7: hypergrowth for hyperscalers who don't have a new Google Search, 520 00:25:45,280 --> 00:25:48,000 Speaker 7: who don't have a new iPhone, and certainly do not 521 00:25:48,160 --> 00:25:49,960 Speaker 7: have a next Amazon Web Services. 522 00:25:50,480 --> 00:25:53,080 Speaker 4: You know, the narrative and the conversation though around AI. 523 00:25:53,359 --> 00:25:55,000 Speaker 4: I mean we've been covering it from day one. I 524 00:25:55,000 --> 00:25:57,720 Speaker 4: can remember, you know, the Microsoft and Open AI investment. 525 00:25:58,359 --> 00:26:01,119 Speaker 4: Everything are world changed in terms of every conversation that 526 00:26:01,119 --> 00:26:04,240 Speaker 4: we've been having. But as of late, easily the last 527 00:26:04,320 --> 00:26:07,480 Speaker 4: six months, maybe longer, this idea of return on investment, 528 00:26:07,520 --> 00:26:10,200 Speaker 4: which wasn't there initially. If the companies weren't you know, 529 00:26:10,240 --> 00:26:12,960 Speaker 4: their capex wasn't growing, they weren't spending. Every company wasn't 530 00:26:13,000 --> 00:26:16,400 Speaker 4: talking AI. You got punished. Now it's getting a little 531 00:26:16,400 --> 00:26:20,240 Speaker 4: bit more discriminating, if you will, or specific in terms 532 00:26:20,240 --> 00:26:22,440 Speaker 4: of looking at cases and what are we getting out. 533 00:26:22,480 --> 00:26:25,960 Speaker 4: We had an investment advisors earlier and she said the 534 00:26:26,000 --> 00:26:28,639 Speaker 4: same thing, like companies are starting to look at what 535 00:26:29,160 --> 00:26:30,879 Speaker 4: is the cost of tokens? What does it cost to 536 00:26:30,920 --> 00:26:33,280 Speaker 4: have all these models for our employees? What are you 537 00:26:33,400 --> 00:26:36,359 Speaker 4: using it for? Really? You know, just do that on 538 00:26:36,400 --> 00:26:39,879 Speaker 4: your own. So the conversation narrative is changing. Don't you 539 00:26:39,920 --> 00:26:42,520 Speaker 4: think it will continue to change and it might be 540 00:26:42,640 --> 00:26:45,520 Speaker 4: uncomfortable in terms of how it plays out in financial markets. 541 00:26:45,680 --> 00:26:48,720 Speaker 4: I think because as the reality comes in your view. 542 00:26:48,680 --> 00:26:51,000 Speaker 7: Yes, I think this conversation is only going to a 543 00:26:51,080 --> 00:26:54,040 Speaker 7: salary open. AI didn't cut prices because they found some 544 00:26:54,200 --> 00:26:57,320 Speaker 7: mystical way of making from things cheaper. It makes something 545 00:26:57,359 --> 00:27:00,159 Speaker 7: eighty percent cheaper. They saw the danger from China, and 546 00:27:00,200 --> 00:27:02,560 Speaker 7: they saw the competition from ananthropic and they said, well, 547 00:27:02,560 --> 00:27:04,800 Speaker 7: we're allowed to burn billions of dollars, so why don't 548 00:27:04,800 --> 00:27:06,960 Speaker 7: we just cut prices and then make it up in 549 00:27:07,040 --> 00:27:10,440 Speaker 7: volume for an unprofitable product. I think the ROI conversation 550 00:27:10,520 --> 00:27:13,439 Speaker 7: is only going to accelerate too, because we should have 551 00:27:13,480 --> 00:27:15,560 Speaker 7: really had it years ago. We really should have had 552 00:27:15,560 --> 00:27:19,439 Speaker 7: it immediately. But again, people believe everything the tech industry says, 553 00:27:19,560 --> 00:27:21,919 Speaker 7: and they just thought, well, they wouldn't say this and 554 00:27:21,960 --> 00:27:22,800 Speaker 7: be wrong, would they. 555 00:27:23,160 --> 00:27:26,720 Speaker 2: Wearing your view, does Elon Musk and SpaceX fit into 556 00:27:26,720 --> 00:27:28,879 Speaker 2: this conversation? I bring it up because we learned this 557 00:27:28,960 --> 00:27:31,520 Speaker 2: afternoon that Elon Musk's net worth has fallen to six 558 00:27:31,640 --> 00:27:34,960 Speaker 2: hundred and eighty four billion dollars, which, yes, is a 559 00:27:35,000 --> 00:27:38,320 Speaker 2: lot of money. It has a race though the IPO 560 00:27:38,440 --> 00:27:41,399 Speaker 2: gains from SpaceX. And we haven't been with you. 561 00:27:41,080 --> 00:27:43,720 Speaker 5: You've been on with us rich still race scalary. 562 00:27:44,200 --> 00:27:49,600 Speaker 2: Okay, you you haven't joined us since SpaceX iPod. But 563 00:27:49,920 --> 00:27:52,600 Speaker 2: there's a data point there for at least in the 564 00:27:52,640 --> 00:27:56,639 Speaker 2: short term reception to a public company that has pretty 565 00:27:56,640 --> 00:27:58,280 Speaker 2: significant exposure with AI. 566 00:27:58,640 --> 00:28:01,480 Speaker 7: Well, I think SpaceX is kind the proof point you need. 567 00:28:01,720 --> 00:28:04,280 Speaker 7: We have someone who can sink unlimited capital into this, 568 00:28:04,359 --> 00:28:07,240 Speaker 7: who can hire anyone who can theoretically stand up as 569 00:28:07,320 --> 00:28:10,120 Speaker 7: much capacity as possible, breaking multiple laws at the same 570 00:28:10,160 --> 00:28:12,720 Speaker 7: time not getting the permits. And what did we. 571 00:28:12,680 --> 00:28:13,159 Speaker 2: Get for it? 572 00:28:13,200 --> 00:28:17,040 Speaker 7: We got groc And what is grok? Well, it's a third, fourth, 573 00:28:17,160 --> 00:28:20,359 Speaker 7: fifth tier LLM that really only some people use by 574 00:28:20,400 --> 00:28:22,840 Speaker 7: accident when they turn on Twitter. So we have this 575 00:28:22,880 --> 00:28:26,040 Speaker 7: thing where we've had our third anthropic and open AI. 576 00:28:26,119 --> 00:28:28,800 Speaker 7: We've seen someone else try it. We've had what should 577 00:28:28,840 --> 00:28:32,720 Speaker 7: be the proof point that AI is an industry that 578 00:28:32,760 --> 00:28:35,119 Speaker 7: we can have many AI labs and oh, one thousand 579 00:28:35,200 --> 00:28:38,080 Speaker 7: flowers will bloom. And what we have is manure. We 580 00:28:38,160 --> 00:28:41,040 Speaker 7: have a company that loses billions of dollars to do 581 00:28:41,200 --> 00:28:42,360 Speaker 7: what I don't know. 582 00:28:43,280 --> 00:28:45,760 Speaker 2: So should the US be in an arms race with 583 00:28:45,880 --> 00:28:46,920 Speaker 2: China for AI. 584 00:28:47,320 --> 00:28:50,200 Speaker 7: Oh, I think that the arms race with China in 585 00:28:50,280 --> 00:28:53,080 Speaker 7: and of itself is a marketing ploy. What oh no, 586 00:28:53,400 --> 00:28:55,480 Speaker 7: what's China going to do? Make a cheaper and better 587 00:28:55,600 --> 00:29:00,160 Speaker 7: llam Oh it already happened. Nothing happened, nothing happened? And 588 00:29:00,160 --> 00:29:00,760 Speaker 7: shine And what. 589 00:29:00,720 --> 00:29:04,520 Speaker 2: About the security risks that these llms or these these 590 00:29:04,560 --> 00:29:07,760 Speaker 2: some of these agents are exposing, those from open ai 591 00:29:07,840 --> 00:29:09,120 Speaker 2: and those from Anthropic Well. 592 00:29:09,040 --> 00:29:11,400 Speaker 7: I think the biggest risk with open ai and Anthropics 593 00:29:11,440 --> 00:29:14,800 Speaker 7: agents is they don't appear to do basic security practices. 594 00:29:15,040 --> 00:29:17,480 Speaker 7: They don't appear to take care of how they're using 595 00:29:17,480 --> 00:29:21,200 Speaker 7: their systems. Open Ai, say, I actually questioned this entire 596 00:29:21,240 --> 00:29:25,520 Speaker 7: story that their agent ran autonomously for multiple days, burning 597 00:29:25,560 --> 00:29:29,160 Speaker 7: what sounds like unlimited compute. Either this company's run so 598 00:29:29,400 --> 00:29:32,160 Speaker 7: terribly that they were running up millions of dollars of 599 00:29:32,240 --> 00:29:35,600 Speaker 7: bills to randomly do stuff, and also they don't watch 600 00:29:35,680 --> 00:29:37,720 Speaker 7: what it's doing. Software does what it's told to do. 601 00:29:37,760 --> 00:29:39,320 Speaker 7: We don't know the prompt, we don't know the training, 602 00:29:39,360 --> 00:29:40,480 Speaker 7: and they're not releasing the model. 603 00:29:40,520 --> 00:29:44,240 Speaker 2: But it doesn't change the fact that these agents reportedly 604 00:29:44,320 --> 00:29:50,360 Speaker 2: found weaknesses in code that if not exposed or that 605 00:29:50,680 --> 00:29:53,880 Speaker 2: could be vulnerable. Like what I'm saying is if there 606 00:29:53,920 --> 00:29:56,040 Speaker 2: is an idea that if this gets into the wrong hands, 607 00:29:56,600 --> 00:29:59,960 Speaker 2: then systems could break down. 608 00:30:00,160 --> 00:30:02,960 Speaker 7: So briefly, one thing, it's already in the wrong hands, 609 00:30:02,960 --> 00:30:05,480 Speaker 7: open and anthropic. They've shown they do not have the 610 00:30:05,520 --> 00:30:08,680 Speaker 7: responsibility to make security tools. They should not be making them. 611 00:30:08,680 --> 00:30:11,600 Speaker 7: They don't know what they're doing. It's platantly obvious, and 612 00:30:11,680 --> 00:30:15,440 Speaker 7: on top of it, it's the brute forced a hacking agent. 613 00:30:15,560 --> 00:30:18,160 Speaker 7: They shoved as much compute power into it as possible. 614 00:30:18,240 --> 00:30:20,840 Speaker 7: You could also pay hackers to do that. It's illegal. Also, 615 00:30:21,120 --> 00:30:24,120 Speaker 7: this all sounds illegal. I'm no lawyer, I'm no judge, 616 00:30:24,120 --> 00:30:26,440 Speaker 7: but I don't know why they're allowed to do this. Yeah, 617 00:30:26,560 --> 00:30:28,920 Speaker 7: these things are dangerous if they're allowed to be trained 618 00:30:28,920 --> 00:30:32,560 Speaker 7: on cybersecurity measures and execute against them. We I just 619 00:30:32,720 --> 00:30:35,760 Speaker 7: I find the whole thing repugnant because everyone is saying, oh, 620 00:30:35,800 --> 00:30:38,040 Speaker 7: look at the scary ELM versus, looking at the companies 621 00:30:38,080 --> 00:30:38,760 Speaker 7: that run at we. 622 00:30:38,800 --> 00:30:40,800 Speaker 4: Got to run twenty seconds. Anything that would change your 623 00:30:40,840 --> 00:30:43,080 Speaker 4: mind and make you say this is real real quickly? 624 00:30:43,200 --> 00:30:43,680 Speaker 7: Not really? 625 00:30:43,960 --> 00:30:48,760 Speaker 4: No, okay, thank you, thank you, thank you, thank you. 626 00:30:48,800 --> 00:30:51,160 Speaker 4: There's a lot of conversations this week, and it was 627 00:30:51,160 --> 00:30:54,080 Speaker 4: great to get your input at Thank you Editrin. Here's 628 00:30:54,160 --> 00:30:57,160 Speaker 4: CEO Easy Primary Research right here in our studio. 629 00:30:56,880 --> 00:30:59,600 Speaker 2: Glass Stay with us. More from Bloomberg Business Week Daily 630 00:30:59,600 --> 00:31:00,880 Speaker 2: coming up after this. 631 00:31:04,800 --> 00:31:08,640 Speaker 1: You're listening to the Bloomberg Business Week Daily podcast. Catch 632 00:31:08,720 --> 00:31:11,400 Speaker 1: us live weekday afternoons from two to five e's during 633 00:31:11,600 --> 00:31:15,520 Speaker 1: Listen on Applecarplay and Android Auto with the Bloomberg Business app, 634 00:31:15,720 --> 00:31:18,280 Speaker 1: or watch us live on YouTube. 635 00:31:18,920 --> 00:31:21,280 Speaker 2: It's practically an adage on Wall Street by now you 636 00:31:21,320 --> 00:31:24,040 Speaker 2: know you're in trouble when Ken Griffin calls. This time 637 00:31:24,080 --> 00:31:26,520 Speaker 2: the call came for situational awareness. It's a high flying 638 00:31:26,560 --> 00:31:29,160 Speaker 2: hedge funder. Well you do still high flying. I think 639 00:31:29,160 --> 00:31:30,080 Speaker 2: it's fair to say it's. 640 00:31:29,960 --> 00:31:32,560 Speaker 4: Still worth It's still got ten billion dollars it's playing 641 00:31:32,560 --> 00:31:34,520 Speaker 4: with that's I think Kima told us it was the 642 00:31:34,600 --> 00:31:37,760 Speaker 4: largest hedge fund, or one of the largest, the bigger one. 643 00:31:37,800 --> 00:31:40,600 Speaker 2: It's a big deal suddenly though it's come crashing down 644 00:31:40,800 --> 00:31:43,440 Speaker 2: to earth. It's just the beginning of the latest piece 645 00:31:43,520 --> 00:31:46,560 Speaker 2: from Bloomberg News hedge fund reporter Hema Palmar. She joins 646 00:31:46,600 --> 00:31:50,320 Speaker 2: us here in the Bloomberg Interactive Brokers studio. Why were 647 00:31:50,360 --> 00:31:54,160 Speaker 2: so few people surprised that Ken Griffin swooped in to 648 00:31:54,160 --> 00:31:55,120 Speaker 2: pick up the pieces of this. 649 00:31:55,360 --> 00:31:58,560 Speaker 8: So this is classic cit Adel playbook, you know. It's 650 00:31:58,600 --> 00:32:00,960 Speaker 8: what he does is watch all does is They've been 651 00:32:00,960 --> 00:32:04,680 Speaker 8: doing it for decades, which is to seed these distressed companies, 652 00:32:04,760 --> 00:32:09,720 Speaker 8: these firms and take the opportunity to either buy assets 653 00:32:09,760 --> 00:32:13,240 Speaker 8: at a discount, snap up talent at a discount, provide 654 00:32:13,280 --> 00:32:16,960 Speaker 8: some sort of emergency funding with attractive terms. He did 655 00:32:17,000 --> 00:32:21,000 Speaker 8: this with Amaranth, he did this with Melvin Capital most famously, 656 00:32:21,000 --> 00:32:24,760 Speaker 8: and more recently, he's done this with other hedge funds 657 00:32:24,920 --> 00:32:29,000 Speaker 8: and and one he snapped up talent like within hours 658 00:32:29,520 --> 00:32:32,840 Speaker 8: of the bankruptcy of that company. So it is not 659 00:32:32,920 --> 00:32:36,320 Speaker 8: surprising when the news broke that this was Citadel. I 660 00:32:36,320 --> 00:32:38,040 Speaker 8: think the industry was like, yeah, that makes sense. 661 00:32:38,160 --> 00:32:40,520 Speaker 4: Is it a charitable move? It is not always a 662 00:32:40,560 --> 00:32:44,560 Speaker 4: terrible move. Rarely the move is financial. 663 00:32:44,800 --> 00:32:49,000 Speaker 8: It's strategic. It is to snap up things at great 664 00:32:49,000 --> 00:32:53,040 Speaker 8: prices talent. If people are moving, they will take a job, 665 00:32:53,080 --> 00:32:55,160 Speaker 8: and you don't need to be too competitive. And keep 666 00:32:55,160 --> 00:32:58,040 Speaker 8: in mind for multi shread funds, talent is the most 667 00:32:58,080 --> 00:33:02,320 Speaker 8: expensive part of running ahead assets when you can get 668 00:33:02,320 --> 00:33:05,680 Speaker 8: them at a ten percent discount, which is you know 669 00:33:06,200 --> 00:33:10,080 Speaker 8: what this deal was at, then it is a significant 670 00:33:10,120 --> 00:33:13,120 Speaker 8: move and an opportunistic investment for these guys. 671 00:33:13,200 --> 00:33:18,000 Speaker 2: Okay, dumb question incoming. Is there a way? Is there 672 00:33:18,040 --> 00:33:20,640 Speaker 2: a way? I mean obviously there's not. But explain for 673 00:33:20,680 --> 00:33:25,000 Speaker 2: people who might say, well, why not try to unwind 674 00:33:25,040 --> 00:33:28,479 Speaker 2: some of these positions on the open market. Are they 675 00:33:28,520 --> 00:33:30,480 Speaker 2: too big and concentrated to do that? 676 00:33:30,680 --> 00:33:33,000 Speaker 8: The big they're concentrated, and as soon as you start 677 00:33:33,080 --> 00:33:34,480 Speaker 8: selling some of these things. 678 00:33:34,240 --> 00:33:35,160 Speaker 4: You create a spiral. 679 00:33:35,640 --> 00:33:35,840 Speaker 5: Right. 680 00:33:36,040 --> 00:33:39,120 Speaker 8: People see that these asset prices are falling, and then 681 00:33:39,560 --> 00:33:42,160 Speaker 8: the more you sell, the more you're going to be losing. 682 00:33:42,680 --> 00:33:44,840 Speaker 8: So people like to do these block trades where they 683 00:33:44,880 --> 00:33:46,960 Speaker 8: find a buyer, they sell it all in one chunk 684 00:33:47,280 --> 00:33:50,680 Speaker 8: to somebody else, and it still speaks the market less, 685 00:33:50,760 --> 00:33:53,720 Speaker 8: still at a discount, for sure, because that buyer has 686 00:33:53,760 --> 00:33:57,760 Speaker 8: the negotiating power to demand what they seek. So it'll 687 00:33:57,800 --> 00:34:02,120 Speaker 8: spook the market less, it'll protect you assets more, and 688 00:34:02,160 --> 00:34:04,040 Speaker 8: you can do it a little bit more quietly and 689 00:34:04,080 --> 00:34:07,200 Speaker 8: ideally before the market open, which is what took place. 690 00:34:06,960 --> 00:34:09,839 Speaker 4: Here, right exactly right, I mean I think about this 691 00:34:09,920 --> 00:34:13,640 Speaker 4: even during the financial crisis. I'm not makin comparison. But 692 00:34:13,719 --> 00:34:17,280 Speaker 4: when we know that there were problems at different banks 693 00:34:17,320 --> 00:34:21,960 Speaker 4: or institutions, you wanted the least to get out, especially 694 00:34:22,000 --> 00:34:24,759 Speaker 4: if you were trying to negotiating a deal because things 695 00:34:24,760 --> 00:34:27,879 Speaker 4: were rapidly becoming cheaper or not even you know, having 696 00:34:27,880 --> 00:34:32,800 Speaker 4: a value you report. It's unclear exactly what equity Citadel purchased, 697 00:34:33,160 --> 00:34:35,120 Speaker 4: but you do point out that many of the biggest 698 00:34:35,200 --> 00:34:39,120 Speaker 4: names in situational awareness is public book rallied yesterday, So 699 00:34:39,239 --> 00:34:42,200 Speaker 4: Core Weave jumped nearly twenty two percent that day, Bloom 700 00:34:42,320 --> 00:34:46,160 Speaker 4: Energy jump twenty six percent. Again, we can't make any conclusions, 701 00:34:46,200 --> 00:34:47,040 Speaker 4: right when will we know? 702 00:34:47,200 --> 00:34:47,719 Speaker 7: Will it be. 703 00:34:49,200 --> 00:34:51,680 Speaker 4: So well in terms of what citadels Yeah yeah, and 704 00:34:51,719 --> 00:34:53,719 Speaker 4: maybe what Citadel picked up yeah. 705 00:34:53,600 --> 00:34:56,120 Speaker 8: Yeah, So they would have taken a bulk, a huge, 706 00:34:56,160 --> 00:34:58,799 Speaker 8: significant chunk of the assets, so you would assume that 707 00:34:58,840 --> 00:35:02,319 Speaker 8: the fund has is profiting. On how these shares are doing. Now, 708 00:35:02,960 --> 00:35:06,280 Speaker 8: we'll get a better sense of returns early next week 709 00:35:06,440 --> 00:35:09,800 Speaker 8: as they start to tell their investors' numbers, as information 710 00:35:09,880 --> 00:35:10,680 Speaker 8: starts to flow on. 711 00:35:10,640 --> 00:35:11,920 Speaker 4: How these firms are doing. 712 00:35:12,400 --> 00:35:15,520 Speaker 8: Citadel has done kind of mediocre so far this year 713 00:35:15,640 --> 00:35:18,360 Speaker 8: this month as well, kind of flat, less than fifty 714 00:35:18,400 --> 00:35:19,480 Speaker 8: bases points. 715 00:35:19,480 --> 00:35:21,920 Speaker 4: So this sort of deal should really lift. 716 00:35:21,719 --> 00:35:24,839 Speaker 8: The fund's return. A significant amount is the expectation. 717 00:35:24,719 --> 00:35:29,200 Speaker 2: When a firm like Situal Situational Awareness has a big 718 00:35:29,280 --> 00:35:33,120 Speaker 2: draw down such as this or a large decline in value, 719 00:35:33,160 --> 00:35:35,640 Speaker 2: and has to make block trades to offload some of 720 00:35:35,640 --> 00:35:38,840 Speaker 2: its assets because of margin calls. What typically happens to 721 00:35:39,760 --> 00:35:42,960 Speaker 2: the investors who still have money there? Do they say, great, question, 722 00:35:43,120 --> 00:35:44,080 Speaker 2: I'm done? 723 00:35:44,680 --> 00:35:48,520 Speaker 8: So the investors reaction will depend on when they got in. 724 00:35:48,920 --> 00:35:52,240 Speaker 8: If you were an early investor in Situational Awareness, you 725 00:35:52,400 --> 00:35:55,640 Speaker 8: probably did Okay, you're still up. The fund is up 726 00:35:55,680 --> 00:35:58,640 Speaker 8: eighty percent so far this year, so if you've got 727 00:35:58,640 --> 00:36:01,160 Speaker 8: it in January, you might still be fine. If you're 728 00:36:01,160 --> 00:36:03,719 Speaker 8: an investor that got in in June, you've gotten the 729 00:36:03,719 --> 00:36:06,600 Speaker 8: past couple of months, you're not doing too well because 730 00:36:06,600 --> 00:36:09,440 Speaker 8: you got in right ahead of this decline. The stocks 731 00:36:09,440 --> 00:36:13,200 Speaker 8: have fallen, they've exited these assets or sold it off 732 00:36:13,239 --> 00:36:16,719 Speaker 8: at a discount, so you're not pleased. So there's going 733 00:36:16,800 --> 00:36:19,440 Speaker 8: to be a huge spread in the kinds of returns 734 00:36:19,480 --> 00:36:21,759 Speaker 8: you're seeing for each different type of LP. 735 00:36:21,960 --> 00:36:23,520 Speaker 2: Do we know if it was the type of fund 736 00:36:23,520 --> 00:36:25,120 Speaker 2: that you could just get in and get out of 737 00:36:25,160 --> 00:36:25,880 Speaker 2: when you wanted to. 738 00:36:26,000 --> 00:36:28,000 Speaker 8: And I don't think we know the liquidity terms of 739 00:36:28,040 --> 00:36:32,680 Speaker 8: this fund because some of the investments of privates there 740 00:36:32,719 --> 00:36:34,880 Speaker 8: will likely be a side pocket or some sort of 741 00:36:34,880 --> 00:36:37,400 Speaker 8: restraint on your ability to get out of the anthropic 742 00:36:37,480 --> 00:36:42,800 Speaker 8: stakes for example. That's those chunky private positions are also 743 00:36:42,880 --> 00:36:45,319 Speaker 8: what's allowing the firm to be the stable, because you 744 00:36:45,360 --> 00:36:48,360 Speaker 8: have this stuff that you can't sell really fast generally speaking. 745 00:36:48,120 --> 00:36:50,839 Speaker 4: Right exactly, you have a great little quote. I guess 746 00:36:50,920 --> 00:36:52,920 Speaker 4: did you just speak too clip fastness? 747 00:36:53,560 --> 00:36:58,000 Speaker 8: He wrote in there was a public comment that he 748 00:36:58,040 --> 00:37:00,120 Speaker 8: had made back in two thousand and seven where he 749 00:37:00,200 --> 00:37:03,160 Speaker 8: described what it was like to get the call from Citadel. 750 00:37:03,800 --> 00:37:05,239 Speaker 8: Would you like to would you like to read it? 751 00:37:05,360 --> 00:37:05,760 Speaker 7: Yes? 752 00:37:05,840 --> 00:37:06,759 Speaker 5: So do you want to read it? 753 00:37:07,280 --> 00:37:09,800 Speaker 8: I looked up and saw the valkyries coming, and I 754 00:37:09,920 --> 00:37:13,600 Speaker 8: heard the grim Reaper's skye knocking on my door. I 755 00:37:13,680 --> 00:37:15,160 Speaker 8: did my best to run. 756 00:37:15,040 --> 00:37:20,600 Speaker 4: To the light. I'm trying to also hemm up. What's 757 00:37:20,640 --> 00:37:24,759 Speaker 4: your view on what this means for AI? I mean 758 00:37:25,000 --> 00:37:28,719 Speaker 4: interesting that Citadel like they like a bargain. Yeah, it's 759 00:37:28,760 --> 00:37:30,960 Speaker 4: going to reduce their returns. Be interesting to see how 760 00:37:30,960 --> 00:37:33,520 Speaker 4: long they hold on to this these positions, they've got 761 00:37:33,520 --> 00:37:34,200 Speaker 4: to be careful too. 762 00:37:34,160 --> 00:37:34,840 Speaker 5: On the unwind. 763 00:37:35,280 --> 00:37:38,520 Speaker 4: But like in a market where things are swinging a lot, 764 00:37:38,560 --> 00:37:41,560 Speaker 4: we're trying to understand this AI trade and spend an investment. 765 00:37:42,080 --> 00:37:44,880 Speaker 4: Is there a takeaway from this that Citadel was at 766 00:37:44,960 --> 00:37:46,200 Speaker 4: least interested. 767 00:37:46,600 --> 00:37:49,640 Speaker 8: Well, the Citadel and other multi SATs tend to be. 768 00:37:49,680 --> 00:37:52,359 Speaker 8: They're supposed to be market neutral, meaning they have less 769 00:37:52,400 --> 00:37:54,640 Speaker 8: exposure to the market if it makes a big swings 770 00:37:54,680 --> 00:37:57,200 Speaker 8: up and big swings down. They also train a lot 771 00:37:57,239 --> 00:37:59,840 Speaker 8: of assets that do different things in separate little and 772 00:38:00,080 --> 00:38:03,120 Speaker 8: visual teams, and so that structure should protect you from 773 00:38:03,120 --> 00:38:06,560 Speaker 8: big swings. Granted, they just bought this huge portfolio, but 774 00:38:06,600 --> 00:38:09,160 Speaker 8: also keep in mind to Adell's seventy one billion dollars, 775 00:38:09,160 --> 00:38:11,520 Speaker 8: so whatever size they bought is still going to be 776 00:38:11,560 --> 00:38:14,719 Speaker 8: a fraction of total firm assets. When you look at 777 00:38:14,800 --> 00:38:17,440 Speaker 8: firms and hedge firms that are more concentrated, say long 778 00:38:17,480 --> 00:38:20,560 Speaker 8: short equity funds, say tech focus funds, and you see 779 00:38:20,560 --> 00:38:23,560 Speaker 8: these big swings. We have seen some funds make and 780 00:38:23,560 --> 00:38:26,040 Speaker 8: lose a lot of money based on the month, so 781 00:38:26,120 --> 00:38:29,520 Speaker 8: that's when you see more risk. And again to this point, 782 00:38:29,640 --> 00:38:33,600 Speaker 8: situational awareness was highly levered that's another factory to look at. 783 00:38:33,680 --> 00:38:36,160 Speaker 8: A lot of the funds don't have as much leverage 784 00:38:36,160 --> 00:38:37,800 Speaker 8: as we've seen situational awareness. 785 00:38:37,840 --> 00:38:39,760 Speaker 2: I keep thinking this could have been so much worse. 786 00:38:41,080 --> 00:38:43,200 Speaker 8: It could have been if they didn't find a buyer. 787 00:38:44,560 --> 00:38:47,319 Speaker 8: They were looking at selling both their public stocks and 788 00:38:47,400 --> 00:38:49,680 Speaker 8: the private books. It sounds like they were looking at 789 00:38:49,719 --> 00:38:51,640 Speaker 8: selling whatever they could to get out as fast as 790 00:38:51,680 --> 00:38:53,600 Speaker 8: they could. And that is not a good position for 791 00:38:53,680 --> 00:38:56,200 Speaker 8: a forty five billion dollar fund to be in. That 792 00:38:56,200 --> 00:39:00,120 Speaker 8: can really scare the market. It can scare investors, and 793 00:39:00,160 --> 00:39:03,640 Speaker 8: we saw the tumult yesterday really ripple through until market's 794 00:39:03,680 --> 00:39:05,479 Speaker 8: calmed once we got a sense of who the bio 795 00:39:05,640 --> 00:39:06,520 Speaker 8: was real quickly. 796 00:39:06,520 --> 00:39:09,040 Speaker 4: Twenty seconds of fund is still up a lot this year. 797 00:39:09,520 --> 00:39:13,560 Speaker 8: Citadel no emotional, Yeah, Situational is up a lot this year. 798 00:39:13,719 --> 00:39:16,920 Speaker 8: For the month, it's down a lot. I would judge 799 00:39:16,920 --> 00:39:19,040 Speaker 8: it based on when the investor got in. If you're 800 00:39:19,040 --> 00:39:21,880 Speaker 8: an investor, you're not too happy. If you're early, you 801 00:39:21,960 --> 00:39:22,479 Speaker 8: might be fine. 802 00:39:22,560 --> 00:39:26,839 Speaker 4: Timing is everything isn't so great to have you here 803 00:39:27,040 --> 00:39:29,160 Speaker 4: and really helping us through this story. Bloomberg News Hedge 804 00:39:29,160 --> 00:39:31,280 Speaker 4: fund reporter him of Pormark joining us in our Bloomberg 805 00:39:31,280 --> 00:39:33,080 Speaker 4: Interactive Work for studio. Thank you, Thank you. 806 00:39:33,800 --> 00:39:39,200 Speaker 5: This is the Bloomberg Business Week Daily podcast, available on Apple, Spotify, 807 00:39:39,280 --> 00:39:41,440 Speaker 5: and anywhere else you get your podcasts. 808 00:39:41,880 --> 00:39:45,360 Speaker 2: Listen live weekday afternoons from two to five pm Eastern 809 00:39:45,640 --> 00:39:49,320 Speaker 2: on Bloomberg dot com, the iHeartRadio app, tune In, and 810 00:39:49,560 --> 00:39:51,040 Speaker 2: the Bloomberg Business App. 811 00:39:51,239 --> 00:39:54,000 Speaker 5: You can also watch us live every weekday on YouTube 812 00:39:54,239 --> 00:39:56,400 Speaker 5: and always on the Bloomberg terminal