1 00:00:00,120 --> 00:00:13,680 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. Bloomberg Tech is live 2 00:00:13,720 --> 00:00:17,520 Speaker 1: from coast to coast with Caroline Hide in New York 3 00:00:17,800 --> 00:00:20,560 Speaker 1: and Eva Low in San Francisco. 4 00:00:23,000 --> 00:00:24,639 Speaker 2: This is Bloomberg Tech coming up. 5 00:00:24,760 --> 00:00:28,440 Speaker 3: China tightens its grip on AI, this time targeting overseas 6 00:00:28,480 --> 00:00:30,600 Speaker 3: travel by top AI professionals. 7 00:00:30,640 --> 00:00:33,240 Speaker 4: Plus how big banks are looking to hire more AI 8 00:00:33,320 --> 00:00:36,160 Speaker 4: specialists and shrink traditional banking roles. 9 00:00:36,800 --> 00:00:39,480 Speaker 3: And we'll look at the tech IPO landscape as SpaceX 10 00:00:39,600 --> 00:00:42,360 Speaker 3: kicks off an IPO bonanza and. 11 00:00:42,479 --> 00:00:44,400 Speaker 4: Quite the timing for any sort of IPO right now, 12 00:00:44,400 --> 00:00:47,360 Speaker 4: because a new record high once again ed it's risk 13 00:00:47,440 --> 00:00:50,400 Speaker 4: one and that means we're buying semiconductors, we're buying hardware. 14 00:00:50,400 --> 00:00:52,440 Speaker 4: Then how's that one hundred and a new record high? 15 00:00:52,440 --> 00:00:54,920 Speaker 4: We're at one point on an in today basis, That is, 16 00:00:55,080 --> 00:00:58,840 Speaker 4: we're looking at the Semiconductor index on fire up five 17 00:00:58,840 --> 00:01:01,400 Speaker 4: percent for the socks. Why dig into some of the 18 00:01:01,400 --> 00:01:04,840 Speaker 4: individual movers. We're seeing Micron and a new record high 19 00:01:04,959 --> 00:01:08,840 Speaker 4: as we see analysts or pile in an extraordinary uplift 20 00:01:08,840 --> 00:01:11,039 Speaker 4: from ubs in terms of a price target that more 21 00:01:11,040 --> 00:01:13,560 Speaker 4: than doubles and where it's currently training. We're up seventeen 22 00:01:13,600 --> 00:01:15,959 Speaker 4: percent for Micron. But also you're shining a light what's 23 00:01:16,000 --> 00:01:18,560 Speaker 4: happening with Qualcom getting a real boost as well as 24 00:01:18,600 --> 00:01:20,280 Speaker 4: we start to see new buyers of its A six. 25 00:01:20,319 --> 00:01:24,200 Speaker 3: It's all about the hardware ed from Asia to the 26 00:01:24,319 --> 00:01:27,559 Speaker 3: US session. There's a massive rally in ship stocks. Also 27 00:01:27,600 --> 00:01:31,240 Speaker 3: because of a breakthrough in technology. China's Huawei says it 28 00:01:31,280 --> 00:01:34,520 Speaker 3: has a new technique, logic folding, that changes how a 29 00:01:34,640 --> 00:01:38,360 Speaker 3: signal passes through a transistor, so you can do away 30 00:01:38,400 --> 00:01:41,440 Speaker 3: with extreme miniaturization. You don't have to worry about the 31 00:01:41,480 --> 00:01:45,480 Speaker 3: limits of extreme ultraviolet lithography. It's a new design but 32 00:01:45,560 --> 00:01:48,360 Speaker 3: also method of chip manufacturing, and that has really sent 33 00:01:48,640 --> 00:01:51,880 Speaker 3: all kinds of chip stocks or supply chain exposure stocks 34 00:01:52,520 --> 00:01:55,920 Speaker 3: sending much higher. Here's the catch, this is a technology 35 00:01:55,920 --> 00:01:58,160 Speaker 3: that's many years away. Let's get more with Bloomberg Senior 36 00:01:58,200 --> 00:02:02,160 Speaker 3: Tech editor Mike Shephard. You know, so interesting because Huawei 37 00:02:02,360 --> 00:02:05,920 Speaker 3: is coming out saying, well, we've got something here technology wise, 38 00:02:06,480 --> 00:02:08,120 Speaker 3: but you're going to have to wait until the next 39 00:02:08,160 --> 00:02:10,960 Speaker 3: decade to see it. In a race with TESMC give 40 00:02:11,040 --> 00:02:11,680 Speaker 3: us more detail. 41 00:02:12,800 --> 00:02:16,760 Speaker 5: Well, they are promising something that people have been wondering about. 42 00:02:16,760 --> 00:02:19,520 Speaker 5: What would be the next version of War's law, and 43 00:02:19,520 --> 00:02:22,120 Speaker 5: that is the idea that every two years you would 44 00:02:22,120 --> 00:02:24,680 Speaker 5: see a doubling of the number of transistors that you 45 00:02:24,720 --> 00:02:27,400 Speaker 5: could fit on a tiny chip. And in recent years 46 00:02:27,639 --> 00:02:30,000 Speaker 5: that has started to slow because the chips have just 47 00:02:30,040 --> 00:02:33,240 Speaker 5: gotten so small and so much harder to produce and 48 00:02:33,280 --> 00:02:38,359 Speaker 5: really requiring such sophisticated machinery like the kind of EUV 49 00:02:38,520 --> 00:02:42,560 Speaker 5: machines produced by ASML, the Dutch company that really has 50 00:02:42,560 --> 00:02:45,880 Speaker 5: a stranglehold on that, and that has really been a bottleneck, 51 00:02:46,040 --> 00:02:49,360 Speaker 5: especially for China, which faces export controls on being able 52 00:02:49,360 --> 00:02:53,919 Speaker 5: to acquire that technology. So their solution innovate around the problem, 53 00:02:53,960 --> 00:02:56,360 Speaker 5: at least in the view of Huawei. They are promising 54 00:02:56,440 --> 00:02:59,799 Speaker 5: this new method and even a new law to define 55 00:03:00,120 --> 00:03:02,720 Speaker 5: how to pack all those transistors onto a chip, and 56 00:03:02,760 --> 00:03:05,840 Speaker 5: they are calling it Tao's law and really trying to 57 00:03:05,960 --> 00:03:09,480 Speaker 5: forge their own path. Now. The cautionary note, of course, ED, 58 00:03:09,680 --> 00:03:13,000 Speaker 5: is that this is all theoretical. Right now, they say 59 00:03:13,040 --> 00:03:15,840 Speaker 5: that in the Cure inship, the new line coming up soon. 60 00:03:16,360 --> 00:03:19,079 Speaker 5: We may see signs of it, but it may take years, 61 00:03:19,200 --> 00:03:21,720 Speaker 5: and ED can they produce it at a yield that 62 00:03:21,840 --> 00:03:23,280 Speaker 5: produces a profit for them? 63 00:03:23,520 --> 00:03:26,440 Speaker 4: But the focus clearly is on owning their own supply 64 00:03:26,560 --> 00:03:29,600 Speaker 4: chain controlling it, and they're also looking to control their 65 00:03:29,600 --> 00:03:32,320 Speaker 4: own talent chain. It feels as though as well might 66 00:03:32,520 --> 00:03:37,440 Speaker 4: more limitations on those building AI startups in the country. 67 00:03:37,680 --> 00:03:41,160 Speaker 5: Kara, We are seeing this competition between the US and 68 00:03:41,320 --> 00:03:46,280 Speaker 5: China for leadership and artificial intelligence and advanced technology, not 69 00:03:46,360 --> 00:03:49,200 Speaker 5: only in the chip and software arena, but in the 70 00:03:49,280 --> 00:03:52,720 Speaker 5: people arena and sphere as well. And what China is 71 00:03:52,760 --> 00:03:55,520 Speaker 5: doing is saying to its AI research is that look, 72 00:03:55,560 --> 00:03:57,920 Speaker 5: if you want to go outside the country for leisure, 73 00:03:58,000 --> 00:04:00,640 Speaker 5: for business, you have to come to us first, come 74 00:04:00,680 --> 00:04:03,240 Speaker 5: to the authorities for permission. Now, for years they have 75 00:04:03,320 --> 00:04:06,000 Speaker 5: required this sort of okay ahead of any sort of 76 00:04:06,040 --> 00:04:10,240 Speaker 5: travel for college researchers, for nuclear scientists, and even executives 77 00:04:10,320 --> 00:04:13,360 Speaker 5: that state owned firms. But now they are extending this 78 00:04:13,480 --> 00:04:16,920 Speaker 5: reach into the private sector and specifically for companies that 79 00:04:17,040 --> 00:04:20,240 Speaker 5: deal with artificial intelligence, which just like the US, is 80 00:04:20,240 --> 00:04:25,000 Speaker 5: the clear for China it is a national strategic priority, 81 00:04:25,279 --> 00:04:29,680 Speaker 5: and that also includes the personnel who produce it, the researchers, 82 00:04:29,720 --> 00:04:32,920 Speaker 5: the scientists, even the executives and founders. We don't know 83 00:04:32,960 --> 00:04:36,000 Speaker 5: how restrictive Caro this will be. Is it an automatic note? 84 00:04:36,040 --> 00:04:37,799 Speaker 5: Does that mean you can never go to the US? 85 00:04:38,120 --> 00:04:40,440 Speaker 5: Is it more pro former rubber stamp? We just want 86 00:04:40,440 --> 00:04:43,240 Speaker 5: to know where you are. But nonetheless it is a 87 00:04:43,320 --> 00:04:46,839 Speaker 5: signal that they want to keep those resources, those crown 88 00:04:46,920 --> 00:04:48,719 Speaker 5: jewels of knowledge there at. 89 00:04:48,560 --> 00:04:51,480 Speaker 4: Home, particularly after we see the investigation into the MANUS 90 00:04:51,520 --> 00:04:55,279 Speaker 4: purchase by Meta as well bloembugs Mike Shepherd always across 91 00:04:55,320 --> 00:04:57,520 Speaker 4: all things geopolitics. We want to now get you all 92 00:04:57,560 --> 00:05:01,120 Speaker 4: across the markets more broadly, IPEC with US Swiss quote 93 00:05:01,120 --> 00:05:04,520 Speaker 4: see market analysts. Look, we are seeing once again a 94 00:05:04,560 --> 00:05:07,680 Speaker 4: furious rally, whether it be in hardware in China, whether 95 00:05:07,720 --> 00:05:09,320 Speaker 4: it be the US names as well. 96 00:05:09,279 --> 00:05:13,200 Speaker 6: Kind of continued, Well, that's a billion dollar question. I 97 00:05:13,279 --> 00:05:16,400 Speaker 6: guess we have seen this AI optimism take over again 98 00:05:16,520 --> 00:05:20,279 Speaker 6: since especially three months the RAN wars started, as investors 99 00:05:20,360 --> 00:05:23,960 Speaker 6: just try to forget about the AR problems they're funding 100 00:05:24,600 --> 00:05:29,839 Speaker 6: the financing of new debt on debt and the AR restrictions, 101 00:05:29,920 --> 00:05:32,680 Speaker 6: and then the competition and then supply chain problems, and 102 00:05:32,760 --> 00:05:36,360 Speaker 6: decided to just focus on the potential. And hardware is 103 00:05:36,560 --> 00:05:40,440 Speaker 6: at the very center of this huge potential for AI adoption. 104 00:05:40,680 --> 00:05:41,719 Speaker 7: The demand is strong. 105 00:05:41,920 --> 00:05:45,000 Speaker 6: We know that the results from the technology companies, especially 106 00:05:45,080 --> 00:05:47,640 Speaker 6: in the US, have come in better than expected. They 107 00:05:47,720 --> 00:05:51,240 Speaker 6: beat the Uestimus and it looks like, yes, this could continue. 108 00:05:51,240 --> 00:05:54,400 Speaker 6: But on well there are some problems and that risks 109 00:05:54,400 --> 00:05:57,800 Speaker 6: that are building today. One the Macray climbing set up, 110 00:05:58,160 --> 00:06:01,479 Speaker 6: the mac Ray climb backshop is not necessarily ideal. The 111 00:06:01,560 --> 00:06:05,320 Speaker 6: rising borrowing costs our at risk. The other riskers the 112 00:06:05,440 --> 00:06:09,360 Speaker 6: energy crisis, the supply chain problems and the competition. 113 00:06:10,880 --> 00:06:15,240 Speaker 3: Epek our Markets team are writing that stocks arising because 114 00:06:15,279 --> 00:06:18,839 Speaker 3: of Iran piece hopes. But I'm looking at the S 115 00:06:18,880 --> 00:06:22,640 Speaker 3: and P five hundred information technology massively outperforming the Nazak 116 00:06:22,680 --> 00:06:27,560 Speaker 3: one hundred, pushing records. Semiconductors are going absolutely bonkers because. 117 00:06:27,320 --> 00:06:28,239 Speaker 2: Of the Huawei report. 118 00:06:28,240 --> 00:06:30,400 Speaker 3: I think you just heard shep give the details of 119 00:06:30,440 --> 00:06:34,919 Speaker 3: Huawei's new chip manufacturing process. What's happening right now in 120 00:06:34,960 --> 00:06:36,839 Speaker 3: tech well. 121 00:06:36,560 --> 00:06:39,440 Speaker 6: In tech well tech has become one major driver of 122 00:06:39,560 --> 00:06:41,919 Speaker 6: the global markets. It's not only the US, but we 123 00:06:42,000 --> 00:06:47,160 Speaker 6: also see it in the emerging markets, with Korean memoryship makers, 124 00:06:47,160 --> 00:06:50,600 Speaker 6: for example, really carrying this rally almost alone on their 125 00:06:50,640 --> 00:06:53,800 Speaker 6: own shoulders to all time higher levels, whereas the rest 126 00:06:53,880 --> 00:06:57,880 Speaker 6: of the sectors are struggling. They're struggling with an unideal 127 00:06:58,040 --> 00:07:02,680 Speaker 6: macracline backdop rising those rising borrowing costs and supply chain risks. 128 00:07:02,800 --> 00:07:04,960 Speaker 6: So what we see today is that the market bread 129 00:07:05,200 --> 00:07:08,359 Speaker 6: between the technology sector and the rest is increasing in 130 00:07:08,400 --> 00:07:11,640 Speaker 6: a way that when we look at the MSCI markets 131 00:07:11,720 --> 00:07:15,280 Speaker 6: while the rest of the market is if you just 132 00:07:15,440 --> 00:07:19,080 Speaker 6: stripped out s kah Nich, sums On or TSMC, for example, 133 00:07:19,320 --> 00:07:22,000 Speaker 6: while they have fallen to the levels that we have 134 00:07:22,200 --> 00:07:25,120 Speaker 6: last seen during the April death last year, past a 135 00:07:25,160 --> 00:07:26,080 Speaker 6: Liberation Day. 136 00:07:27,680 --> 00:07:31,560 Speaker 4: This hardware focus and momentum has really made certain names 137 00:07:31,560 --> 00:07:33,160 Speaker 4: start to outshine here in the US. 138 00:07:33,240 --> 00:07:34,360 Speaker 7: I'm all eyes on Micron. 139 00:07:34,560 --> 00:07:36,960 Speaker 4: We actually spoke with the CEO of Micron on Friday impact. 140 00:07:37,120 --> 00:07:38,880 Speaker 7: Just listen to what you said about the memory side 141 00:07:38,920 --> 00:07:39,440 Speaker 7: of the business. 142 00:07:40,240 --> 00:07:43,760 Speaker 8: Of course, the demand for memory has really searched, and 143 00:07:43,920 --> 00:07:47,040 Speaker 8: that is because of the importance and the value and 144 00:07:47,120 --> 00:07:51,640 Speaker 8: the capability of memory that is really essential for all 145 00:07:52,120 --> 00:07:56,080 Speaker 8: advanced systems. And yes there is a shortage, but Micron 146 00:07:56,200 --> 00:08:00,400 Speaker 8: is working hard to increase supply through these projects here 147 00:08:00,760 --> 00:08:05,800 Speaker 8: in americaa here in Manassa's Virginia, Boise and New York 148 00:08:06,160 --> 00:08:10,440 Speaker 8: and we see this shortage continuing beyond, well beyond twenty 149 00:08:10,520 --> 00:08:11,720 Speaker 8: twenty six time frame. 150 00:08:12,560 --> 00:08:14,720 Speaker 4: In fact, this is an industry that we knew for 151 00:08:14,800 --> 00:08:17,440 Speaker 4: booms and busts, but the moment it's just on a 152 00:08:17,520 --> 00:08:20,760 Speaker 4: one way boom trajectory. Do you think that really is 153 00:08:20,880 --> 00:08:21,800 Speaker 4: the right way for the. 154 00:08:21,760 --> 00:08:23,120 Speaker 7: Market to be seeing it right now? 155 00:08:24,000 --> 00:08:28,440 Speaker 6: Well, obviously there is never just one way, especially when 156 00:08:28,440 --> 00:08:31,840 Speaker 6: we're looking at the market prices, they are parabolic, so 157 00:08:32,120 --> 00:08:34,480 Speaker 6: in terms of technical levels or in terms of what 158 00:08:34,600 --> 00:08:37,880 Speaker 6: happened in the past, we do expect a correction because 159 00:08:37,880 --> 00:08:41,000 Speaker 6: the valuations have done absolutely ballistic, and we know that 160 00:08:41,040 --> 00:08:45,240 Speaker 6: there are boom and bus circles in this industry. It 161 00:08:45,320 --> 00:08:48,520 Speaker 6: is just that AI and the demand for AI hardware 162 00:08:48,640 --> 00:08:51,400 Speaker 6: will probably make these cycles a little bit longer than 163 00:08:51,440 --> 00:08:53,920 Speaker 6: they have been before, but they're not going to just 164 00:08:54,400 --> 00:08:57,280 Speaker 6: you know, make them an existent anymore. So I think 165 00:08:57,320 --> 00:08:59,720 Speaker 6: that there is a risk that all of those who 166 00:08:59,800 --> 00:09:04,000 Speaker 6: are predicting that there will be no bus cycles anymore 167 00:09:04,040 --> 00:09:06,600 Speaker 6: in the memories of industry are probably mistaken. 168 00:09:07,960 --> 00:09:10,839 Speaker 3: Eupe Oscar desh Gayer Swiss quote all across the news 169 00:09:10,840 --> 00:09:11,400 Speaker 3: and the markets. 170 00:09:11,400 --> 00:09:12,040 Speaker 2: Thank you so much. 171 00:09:12,080 --> 00:09:13,839 Speaker 3: Now, coming up, we're going to hear a lot more 172 00:09:13,840 --> 00:09:16,840 Speaker 3: from Micron CEO on demand for memory and what they're 173 00:09:16,840 --> 00:09:19,160 Speaker 3: doing to adjust the supply constraint. 174 00:09:19,160 --> 00:09:20,520 Speaker 2: That's next. This is Bloomberg Tech. 175 00:09:34,720 --> 00:09:37,640 Speaker 3: Qual Com reached the deal with TikTok owner bike Dance 176 00:09:37,720 --> 00:09:40,880 Speaker 3: to supply chips for AI data centers. That's, according to sources, 177 00:09:41,000 --> 00:09:43,840 Speaker 3: marking a key win for a company trying to expand 178 00:09:43,880 --> 00:09:48,200 Speaker 3: from smartphone processes into AI infrastructure. Bloomberg's Chip reported Inking 179 00:09:48,559 --> 00:09:51,440 Speaker 3: just broke that story. The markets responding qual come up 180 00:09:51,440 --> 00:09:53,600 Speaker 3: seven percent, a fresh record high. 181 00:09:53,920 --> 00:09:55,280 Speaker 2: You remember when Christiano was. 182 00:09:55,200 --> 00:09:56,680 Speaker 3: On the show a few weeks ago and he wouldn't 183 00:09:56,720 --> 00:09:58,600 Speaker 3: say who the customer was. He was saying, Oh, it's 184 00:09:58,640 --> 00:10:01,000 Speaker 3: a hyperscaler, it's byte Dance. 185 00:10:01,640 --> 00:10:04,160 Speaker 9: This is according to our reporting, Yes, and we believe 186 00:10:04,160 --> 00:10:06,560 Speaker 9: there's more to come, that this is kind of a 187 00:10:06,559 --> 00:10:09,920 Speaker 9: breakthrough for them in at least one area of this market. 188 00:10:10,320 --> 00:10:13,600 Speaker 9: And according to our reporting, we should expect more to 189 00:10:13,600 --> 00:10:14,680 Speaker 9: come on the customer list. 190 00:10:15,280 --> 00:10:19,079 Speaker 4: And it's millions of a six And so where and 191 00:10:19,120 --> 00:10:22,120 Speaker 4: why does a company like byte Dance come to Qualcom 192 00:10:22,160 --> 00:10:22,679 Speaker 4: at this moment? 193 00:10:23,520 --> 00:10:26,880 Speaker 9: Yeah, I mean Qualcom has a long history in the 194 00:10:26,920 --> 00:10:30,040 Speaker 9: chip industry. It's very skilled very It was a pioneer 195 00:10:30,080 --> 00:10:32,199 Speaker 9: of something on the sc system on chips, which is 196 00:10:32,200 --> 00:10:34,760 Speaker 9: putting a lot of components together on one piece of silicon, 197 00:10:35,400 --> 00:10:38,160 Speaker 9: and it's done very well in very high volume market. 198 00:10:38,240 --> 00:10:40,360 Speaker 9: So obviously it has a lot of skills. Though it 199 00:10:40,360 --> 00:10:42,360 Speaker 9: would be useful if you are trying to get your 200 00:10:42,360 --> 00:10:44,600 Speaker 9: own solutions to market and volume quickly. 201 00:10:44,720 --> 00:10:47,120 Speaker 3: So this is what's interesting about the A six part right. 202 00:10:47,480 --> 00:10:51,600 Speaker 3: Qualcon is a fabulous chip maker, but essentially instead of 203 00:10:51,920 --> 00:10:54,720 Speaker 3: having its chip, it's doing it on behalf of a 204 00:10:54,760 --> 00:10:57,720 Speaker 3: customer kind of how broadcomes done for various people, for 205 00:10:57,720 --> 00:10:58,600 Speaker 3: example TPU. 206 00:10:58,880 --> 00:10:59,760 Speaker 2: How does that work? 207 00:11:00,040 --> 00:11:02,520 Speaker 9: Yeah, I mean the way it looks at the moment, 208 00:11:02,520 --> 00:11:04,880 Speaker 9: and we'll get more when Qualcomm does its analyst day 209 00:11:04,920 --> 00:11:08,840 Speaker 9: coming up this summer. They're pursuing two strategies. Their own chips, 210 00:11:08,880 --> 00:11:12,199 Speaker 9: their own processors, so rivals to in videos products if 211 00:11:12,200 --> 00:11:15,640 Speaker 9: you like, but also the broadcrom strategy as well, which is, look, 212 00:11:15,760 --> 00:11:17,680 Speaker 9: you've got your ideas, you've got your designs, but you 213 00:11:17,720 --> 00:11:20,200 Speaker 9: don't really know quite how to get this done in 214 00:11:20,200 --> 00:11:22,080 Speaker 9: the kind of volumes that you need to do. Give 215 00:11:22,080 --> 00:11:24,000 Speaker 9: it to UDS, we'll get it across the line for you. 216 00:11:24,120 --> 00:11:26,320 Speaker 9: That's kind of the role that they're looking at. 217 00:11:26,160 --> 00:11:29,600 Speaker 7: Here thinking on all things qual Com. We thank you 218 00:11:29,640 --> 00:11:30,000 Speaker 7: so much. 219 00:11:30,040 --> 00:11:33,000 Speaker 4: We've got plenty more on chips because shares a Micron 220 00:11:33,160 --> 00:11:36,679 Speaker 4: absolutely spiking today. It is now a one trillion dollar 221 00:11:36,760 --> 00:11:39,920 Speaker 4: company if it holds this almost seventeen percent game UBS 222 00:11:39,960 --> 00:11:41,880 Speaker 4: actually raised its price target on the memory chip, make 223 00:11:41,920 --> 00:11:42,160 Speaker 4: it to. 224 00:11:42,120 --> 00:11:42,720 Speaker 7: A street high. 225 00:11:42,720 --> 00:11:46,160 Speaker 4: I've get this and twenty five dollars from five hundred 226 00:11:46,160 --> 00:11:48,320 Speaker 4: and thirty five, and the new target implies the company's 227 00:11:48,360 --> 00:11:51,160 Speaker 4: valuation could reach one point eight trillion now. On Friday, 228 00:11:51,240 --> 00:11:53,720 Speaker 4: Blue Moost Tyler Kendles sat down with Micron President and 229 00:11:53,760 --> 00:11:57,160 Speaker 4: CEO san Jamirotra about the company's expansion of chip production. 230 00:11:57,360 --> 00:11:58,920 Speaker 7: When here in the United States, take a listen. 231 00:12:00,679 --> 00:12:06,280 Speaker 8: Memory today is absolutely key across all industries that have 232 00:12:06,360 --> 00:12:10,520 Speaker 8: electronic systems, and Micron is of course investing in Boise, 233 00:12:10,720 --> 00:12:15,200 Speaker 8: Idaho building our leading ASH fab that's for leading ash 234 00:12:15,600 --> 00:12:21,079 Speaker 8: memory that goes into smartphones, PC's servers, and that leading 235 00:12:21,160 --> 00:12:25,040 Speaker 8: edge memory in Boise, Idaho will bring first wafers out 236 00:12:25,240 --> 00:12:28,040 Speaker 8: middle of next year and then ramp up from there on. 237 00:12:28,320 --> 00:12:31,320 Speaker 8: We'll have a second fab in Boise, Idaho soon to 238 00:12:31,440 --> 00:12:34,520 Speaker 8: follow that start first wave first by end of twenty 239 00:12:34,600 --> 00:12:40,079 Speaker 8: twenty eight there and then we have production planned for Syracuse, 240 00:12:40,120 --> 00:12:43,560 Speaker 8: New York area, where we will build over time a 241 00:12:43,600 --> 00:12:47,800 Speaker 8: mega cluster or four fabs. And you can see two 242 00:12:47,880 --> 00:12:51,479 Speaker 8: hundred billion dollars of investments that Micron is making here 243 00:12:51,679 --> 00:12:55,840 Speaker 8: in America to bring these long life cycle production that 244 00:12:55,920 --> 00:12:59,880 Speaker 8: will be managed here in Manassas, Virginia, along with production 245 00:13:00,160 --> 00:13:04,280 Speaker 8: in Boise, Idaho, and Syracuse, New York. And that will 246 00:13:04,320 --> 00:13:08,559 Speaker 8: bring Micron's total production over the course of about next 247 00:13:08,640 --> 00:13:11,880 Speaker 8: ten years as we ramp up all these multiple fabs 248 00:13:12,080 --> 00:13:16,120 Speaker 8: to about forty percent of our production. By comparison, it 249 00:13:16,240 --> 00:13:19,600 Speaker 8: is about ten percent today and all of that ten 250 00:13:19,640 --> 00:13:23,880 Speaker 8: percent comes from this site here in Manassas for Micron, 251 00:13:24,120 --> 00:13:28,240 Speaker 8: and this will totally our investments massive investments in long 252 00:13:28,280 --> 00:13:32,199 Speaker 8: life cycle technology nodes as well as leading as technology 253 00:13:32,240 --> 00:13:36,000 Speaker 8: nodes to serve these vast markets that are really surging 254 00:13:36,040 --> 00:13:39,320 Speaker 8: in demand driven by AI. Micron is going to be 255 00:13:39,320 --> 00:13:43,160 Speaker 8: bringing those investments that's semiconductive manufacturing and in the process 256 00:13:43,559 --> 00:13:47,280 Speaker 8: create ninety thousand new jobs here in the US as well. 257 00:13:47,400 --> 00:13:47,559 Speaker 5: Well. 258 00:13:47,600 --> 00:13:50,760 Speaker 10: On this point of demand and how this investment is 259 00:13:50,880 --> 00:13:55,240 Speaker 10: seeking to help breach that growing demand. I'm wondering, how 260 00:13:55,240 --> 00:13:58,720 Speaker 10: long do you expect the shortage of memory chips to last? 261 00:13:58,800 --> 00:14:00,640 Speaker 10: When can we expect an easy. 262 00:14:00,760 --> 00:14:04,360 Speaker 8: Of course, the demand for memory has really searched, and 263 00:14:04,440 --> 00:14:07,600 Speaker 8: that is because of the importance and the value and 264 00:14:07,640 --> 00:14:12,200 Speaker 8: the capability of memory that is really essential for all 265 00:14:12,640 --> 00:14:16,640 Speaker 8: advanced systems. And yes, there is a shortage, but Micron 266 00:14:16,720 --> 00:14:20,920 Speaker 8: is working hard to increase supply through these projects here 267 00:14:21,280 --> 00:14:26,320 Speaker 8: in America, here in Manassa's Virginia, Boise and New York, 268 00:14:26,680 --> 00:14:30,960 Speaker 8: and we see this shortage continuing beyond, well beyond twenty 269 00:14:31,040 --> 00:14:34,800 Speaker 8: twenty six timeframe. But the important thing is that Micron 270 00:14:34,880 --> 00:14:38,760 Speaker 8: is working hard with our customers, working also on the 271 00:14:38,880 --> 00:14:43,440 Speaker 8: long term the supply agreements with our customers to really 272 00:14:43,640 --> 00:14:47,240 Speaker 8: ensure that they can have predictability for supply, and of 273 00:14:47,280 --> 00:14:52,000 Speaker 8: course Micron can have the confidence for the investments that 274 00:14:52,080 --> 00:14:54,080 Speaker 8: we are really committing to here for the long haul. 275 00:14:54,280 --> 00:14:54,440 Speaker 2: Well. 276 00:14:55,120 --> 00:14:58,760 Speaker 10: Historically, memory is a cyclical business, right periods of boom, 277 00:14:58,800 --> 00:15:01,360 Speaker 10: periods a bus I'm wondering if two hundred billion dollar 278 00:15:01,480 --> 00:15:04,920 Speaker 10: investment here in the US signals perhaps more of a 279 00:15:05,000 --> 00:15:08,560 Speaker 10: confidence that that demand, that high demand is going to 280 00:15:08,560 --> 00:15:12,520 Speaker 10: be permanent, or are their concerns here that the industry 281 00:15:12,520 --> 00:15:14,240 Speaker 10: could be overbuilding capacity. 282 00:15:14,800 --> 00:15:17,040 Speaker 8: You know, of course, what we are doing is building 283 00:15:17,080 --> 00:15:21,040 Speaker 8: these fabs which are very long lead time items. As 284 00:15:21,080 --> 00:15:23,480 Speaker 8: you can see in terms of what we are doing 285 00:15:23,560 --> 00:15:26,560 Speaker 8: in Boise in New York, it really takes several years 286 00:15:26,680 --> 00:15:30,600 Speaker 8: just to build construct the shell. How we equip that 287 00:15:31,640 --> 00:15:36,080 Speaker 8: shell really very much depends on our latest assessments of 288 00:15:36,160 --> 00:15:38,960 Speaker 8: demand at a given time. So important thing is to 289 00:15:39,040 --> 00:15:42,880 Speaker 8: have that preparedness to meet the market demand, and memory 290 00:15:42,920 --> 00:15:46,200 Speaker 8: has become a key enabler. It is a strategic asset 291 00:15:46,600 --> 00:15:49,880 Speaker 8: for our customers today. It is a strategic asset for 292 00:15:50,000 --> 00:15:55,800 Speaker 8: AI across consumer as well as data center industries, because 293 00:15:55,840 --> 00:15:59,880 Speaker 8: without memory, you don't really have that intelligence that is 294 00:16:00,040 --> 00:16:04,720 Speaker 8: critically important for the future roadmaps the doward customers have. 295 00:16:06,400 --> 00:16:10,000 Speaker 3: That was Micron President and CEO Sanjay Morota speaking with 296 00:16:10,080 --> 00:16:12,320 Speaker 3: our own Tyler Kendle. Now coming up, big banks are 297 00:16:12,320 --> 00:16:16,720 Speaker 3: looking to hire more AI specialists and shrink traditional banking roles. 298 00:16:17,040 --> 00:16:18,240 Speaker 2: This is Bloomberg Tech. 299 00:16:30,800 --> 00:16:31,280 Speaker 7: Wall Street. 300 00:16:31,360 --> 00:16:33,760 Speaker 4: Well, it's getting caught up in aianks of course, and 301 00:16:33,920 --> 00:16:37,200 Speaker 4: looking to hire more AI specialists and actually shrink traditional 302 00:16:37,240 --> 00:16:40,360 Speaker 4: banking roles. Bloomberg has the latest on too highly sought 303 00:16:40,400 --> 00:16:43,680 Speaker 4: after trainers in finance teaching Wall Street bankers how to 304 00:16:43,800 --> 00:16:46,360 Speaker 4: use AI tools. Get this, They're chatting twenty five thousand 305 00:16:46,400 --> 00:16:46,720 Speaker 4: dollars a. 306 00:16:46,760 --> 00:16:47,640 Speaker 7: Day for the training. 307 00:16:47,800 --> 00:16:51,880 Speaker 4: Bloomberg Sally Bakwell is here with one particular evidence that 308 00:16:52,040 --> 00:16:56,800 Speaker 4: banks might be apologizing for calling certain people lower value 309 00:16:56,880 --> 00:16:59,560 Speaker 4: human capital, but on the other side of things, are 310 00:16:59,560 --> 00:17:01,600 Speaker 4: still really committing to the training side of things. 311 00:17:01,960 --> 00:17:03,960 Speaker 11: That is right. I think what we're seeing here is 312 00:17:03,960 --> 00:17:06,760 Speaker 11: Wall Street having a little bit of an AI reality check. 313 00:17:07,000 --> 00:17:09,359 Speaker 11: It's recognizing that AI is not just a tool for 314 00:17:09,400 --> 00:17:13,600 Speaker 11: efficiency anymore. It is also a requirement for survival. And 315 00:17:13,800 --> 00:17:17,480 Speaker 11: so we have these two former soft bank fund managers 316 00:17:17,760 --> 00:17:20,520 Speaker 11: who have who are basically cashing in on that they've 317 00:17:20,560 --> 00:17:23,280 Speaker 11: set up this firm. It's called Wall Street Prompt and 318 00:17:23,320 --> 00:17:26,919 Speaker 11: it's essentially to teach elite bankers how to stop their 319 00:17:27,000 --> 00:17:30,359 Speaker 11: jobs from being automated. And indeed, the eyewatering numbers that 320 00:17:30,359 --> 00:17:32,439 Speaker 11: they can charge twenty five thousand dollars a day and 321 00:17:32,480 --> 00:17:34,800 Speaker 11: that they have a two month backlog. And what this 322 00:17:34,920 --> 00:17:37,840 Speaker 11: really speaks to is that the biggest hurdle to banks 323 00:17:37,960 --> 00:17:41,679 Speaker 11: now is not essentially accessing the AI software they can 324 00:17:41,760 --> 00:17:43,040 Speaker 11: get all of that, they can pay for that, and 325 00:17:43,080 --> 00:17:45,919 Speaker 11: they have invested millions and billions into doing that. But 326 00:17:46,000 --> 00:17:50,320 Speaker 11: the hurdle is ensuring that their senior professional professionals have 327 00:17:50,359 --> 00:17:53,679 Speaker 11: a kind of AI fluency that makes them productive and 328 00:17:53,720 --> 00:17:56,399 Speaker 11: that can keep the financial institution competitive. 329 00:17:57,359 --> 00:18:00,760 Speaker 3: Sally, what's wild about Wall Street prompt It's like less 330 00:18:00,800 --> 00:18:03,760 Speaker 3: than a year old and it has real customers Like 331 00:18:04,320 --> 00:18:06,320 Speaker 3: this is obviously one of the most read stories on 332 00:18:06,359 --> 00:18:09,160 Speaker 3: Bluebow Tunnel. You get why, but just explain to us, 333 00:18:09,160 --> 00:18:10,960 Speaker 3: like what they've achieved and also why they want to 334 00:18:10,960 --> 00:18:11,720 Speaker 3: move to Singapore. 335 00:18:12,560 --> 00:18:12,760 Speaker 12: Right. 336 00:18:13,359 --> 00:18:16,440 Speaker 11: So, Yeah, they were founded just last year and they 337 00:18:16,440 --> 00:18:19,920 Speaker 11: have clients including Bank of America, including City, including t 338 00:18:20,160 --> 00:18:22,840 Speaker 11: row Price. And what they're doing is they're going into 339 00:18:22,880 --> 00:18:25,719 Speaker 11: banks and they're having training sessions with twenty five to 340 00:18:25,800 --> 00:18:30,680 Speaker 11: thirty employees, and they're saying, you know, they're using Google, 341 00:18:30,720 --> 00:18:36,080 Speaker 11: Gemini and alongside FBI style behavioral analysis in order to 342 00:18:36,200 --> 00:18:40,040 Speaker 11: spot red flags in founder pitch videos for example, they're 343 00:18:40,040 --> 00:18:44,040 Speaker 11: also teaching them how to use Chatchibt and Claude in 344 00:18:44,240 --> 00:18:48,840 Speaker 11: order to analyze earnings transcripts for the most market moving 345 00:18:48,960 --> 00:18:54,040 Speaker 11: information and build financial forecasting models on that. Now they 346 00:18:54,040 --> 00:18:57,520 Speaker 11: are potentially looking to expand in Singapore because that is 347 00:18:57,560 --> 00:19:00,840 Speaker 11: where they have put particular focus on it, suring that 348 00:19:01,200 --> 00:19:04,600 Speaker 11: anyone who wants to move into the financial sector is 349 00:19:04,840 --> 00:19:08,320 Speaker 11: very AI fluent. So there is a bit of a 350 00:19:08,320 --> 00:19:12,040 Speaker 11: competitive competitive edge in Asia and Singapore in particular, and 351 00:19:12,200 --> 00:19:16,520 Speaker 11: that's really shining spotlight on the need for US financial 352 00:19:16,560 --> 00:19:18,360 Speaker 11: firms to do that as well. I mean, we've heard 353 00:19:18,400 --> 00:19:22,920 Speaker 11: from so many of them that JP Morgan has rolled 354 00:19:22,920 --> 00:19:26,679 Speaker 11: out LM Suite, a generative AI tool. Goldman is working 355 00:19:26,720 --> 00:19:29,120 Speaker 11: with Anthropic. Bank of America says that it's made its 356 00:19:29,160 --> 00:19:32,399 Speaker 11: developers more productive with AI, and that mean Jamie Diamond 357 00:19:32,400 --> 00:19:35,000 Speaker 11: says he uses it every day. So the need is 358 00:19:35,040 --> 00:19:37,959 Speaker 11: clear that they need to upseeel their staff. 359 00:19:39,359 --> 00:19:43,080 Speaker 3: Bloomberg Sally bake Well absolutely top reporting, Thank you very much. 360 00:19:43,680 --> 00:19:47,960 Speaker 3: Pope Leo the fourteenth says AI should be quote disarmed 361 00:19:48,280 --> 00:19:51,840 Speaker 3: to protect humanity from its dangers, calling for making AI 362 00:19:52,000 --> 00:19:56,399 Speaker 3: more human friendly and freeing it from monopolistic control. The 363 00:19:56,440 --> 00:19:59,600 Speaker 3: comment comes as the Pope and Anthropic co founder Christopher 364 00:19:59,600 --> 00:20:04,800 Speaker 3: Ola launched the Pontiff's first encyclical, a document called Magnifica 365 00:20:05,040 --> 00:20:09,080 Speaker 3: Humanitas Center of the Care of Human dignity in the 366 00:20:09,160 --> 00:20:13,359 Speaker 3: era of Ai Bloomberg. Slavia Ratandi joins us from Rome. 367 00:20:13,960 --> 00:20:18,239 Speaker 3: Flavia fascinating. Let's please just start with the basics, the 368 00:20:18,280 --> 00:20:21,400 Speaker 3: basics of the document, what's in it, and I suppose 369 00:20:21,440 --> 00:20:26,560 Speaker 3: summarizing like the Pope and the attitude towards Ai. 370 00:20:29,800 --> 00:20:34,160 Speaker 13: Absolutely, that was quite I say, the pretty powerful message 371 00:20:34,240 --> 00:20:37,560 Speaker 13: that came from the Pope. Just to give you an idea, 372 00:20:37,600 --> 00:20:40,480 Speaker 13: this is the first encyclical by the new pope elected 373 00:20:40,600 --> 00:20:43,760 Speaker 13: last year, and also the encyclical itself is the most 374 00:20:44,800 --> 00:20:48,960 Speaker 13: the most important, the most official actor from Ope, so 375 00:20:49,080 --> 00:20:53,520 Speaker 13: really includes some of the priorities of a new pope 376 00:20:53,760 --> 00:20:57,439 Speaker 13: and the fact that they chose artificial intelligence. And not 377 00:20:57,560 --> 00:21:02,119 Speaker 13: only that, but the waygual intelligence is changing our lives 378 00:21:02,119 --> 00:21:05,560 Speaker 13: that might change our lives, our lives in the future. 379 00:21:05,640 --> 00:21:09,359 Speaker 13: I think it's really really says something as you said, 380 00:21:09,440 --> 00:21:14,000 Speaker 13: it actually uh used this world deserned and desermed. It 381 00:21:14,040 --> 00:21:17,320 Speaker 13: needs to be desermed. It doesn't mean that the artificial 382 00:21:17,359 --> 00:21:26,040 Speaker 13: intelligence must be somehow blocked, but must be regulated. That 383 00:21:26,320 --> 00:21:30,919 Speaker 13: was the main thing. And and also the fact that 384 00:21:31,440 --> 00:21:33,560 Speaker 13: it basically said that it must be used of course, 385 00:21:34,119 --> 00:21:38,119 Speaker 13: uh for for you know, for for just for for 386 00:21:38,520 --> 00:21:43,560 Speaker 13: good intentions and and kind of indicated all the possible risks. 387 00:21:44,160 --> 00:21:50,480 Speaker 13: For example, indicated the factor that using computing, using artificial 388 00:21:50,520 --> 00:21:54,440 Speaker 13: intelligence in a warfare in the military and defense sector 389 00:21:54,600 --> 00:21:59,080 Speaker 13: is really dangerous, adding and a quote no algorithms can 390 00:21:59,160 --> 00:22:01,600 Speaker 13: make war morally acceptable. 391 00:22:02,560 --> 00:22:04,680 Speaker 4: Seems to be a lot of things going on outside 392 00:22:04,800 --> 00:22:08,000 Speaker 4: the Rome Bureau right now. Flavia Ratney of Bloomberg talking 393 00:22:08,000 --> 00:22:12,359 Speaker 4: about what is about magnificent humanity? That is, ultimately what 394 00:22:12,560 --> 00:22:14,560 Speaker 4: magnifica humanitus is all about. 395 00:22:14,720 --> 00:22:15,639 Speaker 7: Ed well, so interesting. 396 00:22:15,680 --> 00:22:17,600 Speaker 4: It's about one hundred and thirty five years after the 397 00:22:17,680 --> 00:22:21,080 Speaker 4: original pop Leo talked about of new things the first 398 00:22:21,119 --> 00:22:24,240 Speaker 4: Industrial Revolution, how to help humanity through that coming of 399 00:22:24,280 --> 00:22:26,440 Speaker 4: age of technology, and now they look at the age 400 00:22:26,480 --> 00:22:26,800 Speaker 4: of AI. 401 00:22:27,640 --> 00:22:30,160 Speaker 3: Yeah, and one point four billion dollar one point four 402 00:22:30,200 --> 00:22:32,880 Speaker 3: billion Catholics around the world. If you want to talk 403 00:22:32,880 --> 00:22:36,040 Speaker 3: to someone about AI, one message is a pope's address. 404 00:22:36,200 --> 00:22:37,320 Speaker 2: One way of doing. 405 00:22:37,040 --> 00:22:41,399 Speaker 4: It, Sunny, Well, from the AI humanity question, it's a 406 00:22:41,400 --> 00:22:42,320 Speaker 4: bit of MNA for you. 407 00:22:42,480 --> 00:22:44,520 Speaker 7: Has that as a plot shift delivery Hero up next 408 00:22:44,600 --> 00:22:45,680 Speaker 7: as a Bloomberg Tech. 409 00:22:52,960 --> 00:22:55,280 Speaker 4: Welcome back to Bloomberg Tech, and let's take a look 410 00:22:55,320 --> 00:22:59,800 Speaker 4: at today's big number about eleven billion dollars. That's Delivery 411 00:22:59,800 --> 00:23:02,560 Speaker 4: here current market cap as it stands, and that is 412 00:23:02,560 --> 00:23:05,240 Speaker 4: after Uber has offered to take over the German delivery 413 00:23:05,280 --> 00:23:07,160 Speaker 4: company and a deal that would value it. 414 00:23:07,240 --> 00:23:08,920 Speaker 7: At about ten million euros. 415 00:23:09,240 --> 00:23:10,840 Speaker 4: Now clearly the market thing, so it can be maybe 416 00:23:10,880 --> 00:23:12,600 Speaker 4: pushed a little bit higher and get dig into that 417 00:23:12,720 --> 00:23:15,679 Speaker 4: very thing now with the details from equities report to 418 00:23:15,720 --> 00:23:19,520 Speaker 4: Jordan Fitzgerald. So an offer being made, is there more 419 00:23:19,600 --> 00:23:23,120 Speaker 4: being discussed on the table at the moment, Jordan, thank. 420 00:23:22,960 --> 00:23:24,040 Speaker 14: You, yes. 421 00:23:24,119 --> 00:23:26,760 Speaker 15: So over the weekend, news broke that Uber made this 422 00:23:27,040 --> 00:23:30,439 Speaker 15: thirty three Europa share offer for German based food delivery 423 00:23:30,440 --> 00:23:34,119 Speaker 15: company Delivery Hero, and like you said, this value companied 424 00:23:34,119 --> 00:23:38,680 Speaker 15: about ten billion euros. But we don't have any guarantees yet. 425 00:23:38,680 --> 00:23:42,639 Speaker 15: Delivery Hero has been reviewing its strategic options. It's important 426 00:23:42,640 --> 00:23:44,640 Speaker 15: to note that Uber already has a master at twenty 427 00:23:44,680 --> 00:23:47,640 Speaker 15: percent stake in the company, but there's no guarantees here. 428 00:23:48,359 --> 00:23:51,680 Speaker 15: The Financial time to report that Uber had rebuffed the 429 00:23:51,800 --> 00:23:55,800 Speaker 15: Delivery Hero had rebuffed Uber's offer, but things are still up. 430 00:23:55,720 --> 00:23:56,040 Speaker 14: In the air. 431 00:23:57,440 --> 00:24:00,840 Speaker 3: Delivery here just stopped trading in Europe and thirty eight 432 00:24:00,880 --> 00:24:03,879 Speaker 3: dollars twenty three cents a share. The market's kind of saying, 433 00:24:04,440 --> 00:24:06,880 Speaker 3: you know, we see this going higher than thirty three 434 00:24:06,920 --> 00:24:10,240 Speaker 3: euros a share, But also, like a lot of analysts 435 00:24:10,320 --> 00:24:12,000 Speaker 3: and I think you've been writing about this right saying, 436 00:24:12,119 --> 00:24:14,480 Speaker 3: this makes a lot of sense to do this deal 437 00:24:14,480 --> 00:24:16,159 Speaker 3: from Uber's perspective. 438 00:24:16,119 --> 00:24:19,440 Speaker 15: From Uber's perspective, and from Delivery Heroes. Delivery Hero has 439 00:24:19,480 --> 00:24:21,879 Speaker 15: been reviewing it to options. Shares are up quite a 440 00:24:21,880 --> 00:24:24,720 Speaker 15: bit for the year as the company has been going 441 00:24:24,760 --> 00:24:26,920 Speaker 15: down the path of a strategic review, and for Uber, 442 00:24:26,960 --> 00:24:30,000 Speaker 15: analysts are really saying that this is a strategically sound 443 00:24:30,080 --> 00:24:35,119 Speaker 15: deal for them. Uber is in a space, the food 444 00:24:35,119 --> 00:24:38,920 Speaker 15: delivery space, where things are consolidating, and like I said, 445 00:24:38,960 --> 00:24:41,479 Speaker 15: they've already a massive steake and Delivery Hero and Delivery 446 00:24:41,600 --> 00:24:44,879 Speaker 15: Hero in particular gives them exposure on the delivery side 447 00:24:44,920 --> 00:24:48,800 Speaker 15: to international markets, particularly in Asia and Europe, where they're 448 00:24:48,840 --> 00:24:51,399 Speaker 15: already offering ride shares, but they can expand it too 449 00:24:51,400 --> 00:24:54,119 Speaker 15: that delivery side and really grow their business. 450 00:24:55,280 --> 00:24:55,640 Speaker 2: Doing both. 451 00:24:55,680 --> 00:24:59,040 Speaker 3: Jordan Fitzgerald, Top Reporting, Thank you very much. I want 452 00:24:59,080 --> 00:25:01,359 Speaker 3: to get back to check on Micron because what is 453 00:25:01,359 --> 00:25:06,280 Speaker 3: happening is nuts. It's up seventeen percent, in part because 454 00:25:06,359 --> 00:25:09,320 Speaker 3: UBS upgraded its pist target's one six hundred and twenty 455 00:25:09,359 --> 00:25:11,440 Speaker 3: five dollars a share, which as you can say see 456 00:25:11,480 --> 00:25:13,400 Speaker 3: looking at your screen, would be double basically what it's 457 00:25:13,440 --> 00:25:17,920 Speaker 3: currently trading at. But generally speaking, AI names absolutely ripping 458 00:25:18,000 --> 00:25:20,119 Speaker 3: this Tuesday Micron top of the heat. But as we 459 00:25:20,160 --> 00:25:22,000 Speaker 3: talked about earlier in the show, it is a global 460 00:25:22,119 --> 00:25:25,560 Speaker 3: story here to discuss the AI trade. Daniel Pilling, portfolio 461 00:25:25,560 --> 00:25:29,000 Speaker 3: manager at Sans Capital who counts in video and TSMC 462 00:25:29,160 --> 00:25:32,400 Speaker 3: among top holdings, it's just so interesting to work out 463 00:25:32,400 --> 00:25:33,520 Speaker 3: what's going on here. 464 00:25:34,560 --> 00:25:35,640 Speaker 2: I think that you would. 465 00:25:35,440 --> 00:25:38,080 Speaker 3: Say, similar to what I wrote about and the tech 466 00:25:38,119 --> 00:25:42,240 Speaker 3: in depth overnight and video's sold out. So whether your 467 00:25:42,280 --> 00:25:45,800 Speaker 3: goal in this market is to play this SPACEXIPO for 468 00:25:45,920 --> 00:25:49,159 Speaker 3: space based data center, orbital data center, or you're just 469 00:25:49,160 --> 00:25:52,000 Speaker 3: trying to build out day center on Earth, demand is 470 00:25:52,080 --> 00:25:53,320 Speaker 3: vastly outpacing supply. 471 00:25:53,600 --> 00:25:54,480 Speaker 2: Does that sum it up? 472 00:25:55,359 --> 00:25:55,560 Speaker 14: Yes? 473 00:25:55,640 --> 00:25:58,399 Speaker 16: Indeed, I think so, And maybe to put some numbers 474 00:25:58,400 --> 00:26:01,680 Speaker 16: behind it, I think we think about AI, you can 475 00:26:01,800 --> 00:26:03,640 Speaker 16: break it down a three sort of bullet points right 476 00:26:03,680 --> 00:26:07,600 Speaker 16: like one, it's viral, right, so it's sort of like 477 00:26:07,680 --> 00:26:11,720 Speaker 16: zoom in during COVID. The growth is unparalleled and we 478 00:26:11,720 --> 00:26:14,800 Speaker 16: can see this in the anthropic numbers. Two though, it's 479 00:26:14,840 --> 00:26:18,200 Speaker 16: also highly underpenetrated. So you know, there's a billion office 480 00:26:18,200 --> 00:26:21,480 Speaker 16: workers in the world and a tiny, tiny fraction that 481 00:26:21,520 --> 00:26:24,400 Speaker 16: I'm actually using these tools as of today. We try 482 00:26:24,400 --> 00:26:26,280 Speaker 16: to estimate it. It's maybe two or three percent, so 483 00:26:26,280 --> 00:26:27,600 Speaker 16: it's a very very small number. 484 00:26:27,880 --> 00:26:28,520 Speaker 14: And then three. 485 00:26:28,600 --> 00:26:31,359 Speaker 16: You know, all this sort of virality and underpenetration is 486 00:26:31,440 --> 00:26:34,760 Speaker 16: hitting this market, the semiconductor market, where you have companies 487 00:26:35,000 --> 00:26:39,200 Speaker 16: that have long lead times, they're oligopolistic pricing powers. So 488 00:26:39,280 --> 00:26:41,119 Speaker 16: if you add all these things together, it's likely we're 489 00:26:41,160 --> 00:26:43,080 Speaker 16: going to be supply constrained for quite some time. 490 00:26:43,760 --> 00:26:46,720 Speaker 4: How broad therefore, should the holdings go. When I'm looking 491 00:26:46,760 --> 00:26:49,600 Speaker 4: at some of the funds you manage. Clearly you've got 492 00:26:49,640 --> 00:26:51,800 Speaker 4: with the program when it came to nvidio, but you're 493 00:26:51,840 --> 00:26:54,800 Speaker 4: also thinking about those that are offering not only chips 494 00:26:54,840 --> 00:26:57,040 Speaker 4: but also the entire vertical stack. When I think of 495 00:26:57,080 --> 00:26:59,840 Speaker 4: alphabet that you're in, there's Microsoft and Amazon, But why 496 00:26:59,880 --> 00:27:02,680 Speaker 4: not broad into other areas of the chip stack because 497 00:27:02,680 --> 00:27:04,119 Speaker 4: we've seen them just do so well. 498 00:27:04,960 --> 00:27:08,600 Speaker 14: Yes, we totally agree. So we actually also own memory 499 00:27:08,640 --> 00:27:09,880 Speaker 14: companies such. 500 00:27:09,680 --> 00:27:13,480 Speaker 16: As Eskhaiinex and Samsung in Korea, memory is going to 501 00:27:13,480 --> 00:27:18,000 Speaker 16: be an increasingly significant bottleneck. We're heavily exposed to semi 502 00:27:18,080 --> 00:27:21,399 Speaker 16: kapnix companies business slides such as ASML and research to 503 00:27:21,440 --> 00:27:24,439 Speaker 16: provide the equipment to the foundries of the world. I 504 00:27:24,440 --> 00:27:27,240 Speaker 16: think one should also look at electricity companies, so anybody 505 00:27:27,280 --> 00:27:31,000 Speaker 16: that supplies electricity to data centers. One particular interesting business 506 00:27:31,000 --> 00:27:33,080 Speaker 16: there that we own is called Blume Energy. And then 507 00:27:33,160 --> 00:27:37,440 Speaker 16: last the CPUs. CPUs are back for US. That's particularly 508 00:27:37,440 --> 00:27:40,840 Speaker 16: interesting on arm but agentic AI needs a lot of CPUs, So. 509 00:27:40,800 --> 00:27:41,520 Speaker 14: I think you're right. 510 00:27:41,720 --> 00:27:43,840 Speaker 16: One should look at the total stack, and there's many, 511 00:27:43,840 --> 00:27:45,520 Speaker 16: many winners across the entire stack. 512 00:27:46,520 --> 00:27:49,000 Speaker 3: Daniel, Our top story in the show today was news 513 00:27:49,040 --> 00:27:53,080 Speaker 3: from Huawei on logic folding, basically a new method of 514 00:27:53,119 --> 00:27:56,480 Speaker 3: passing the signal through the transistor, taking you outside of 515 00:27:56,520 --> 00:28:02,000 Speaker 3: Moore's law, you're not dependent on extreme miniaturization. The way 516 00:28:02,040 --> 00:28:05,720 Speaker 3: the market responded, first in Asia, then in Europe, and 517 00:28:05,720 --> 00:28:09,879 Speaker 3: then in the United States, everything was up irrespective of 518 00:28:09,920 --> 00:28:11,080 Speaker 3: their ties to Huawei. 519 00:28:11,119 --> 00:28:12,200 Speaker 2: Why do you think that is. 520 00:28:14,000 --> 00:28:14,240 Speaker 14: Well? 521 00:28:14,320 --> 00:28:17,120 Speaker 16: I mean, I do think that in Asia, in particular 522 00:28:17,160 --> 00:28:21,280 Speaker 16: in China, there's a sense that they don't have access 523 00:28:21,280 --> 00:28:25,080 Speaker 16: to ASML nor leading edge chips from Taiwan Semi, so 524 00:28:25,240 --> 00:28:27,920 Speaker 16: any sort of announcement that they can make that might 525 00:28:27,960 --> 00:28:30,320 Speaker 16: provide them the opportunity to build their own leading edge 526 00:28:30,400 --> 00:28:33,560 Speaker 16: hips is much appreciated now. The counter to that, though, 527 00:28:33,640 --> 00:28:36,080 Speaker 16: is that this technology has been around for a while. 528 00:28:36,520 --> 00:28:38,520 Speaker 16: This idea of sort of stacking chips on top of 529 00:28:38,600 --> 00:28:41,440 Speaker 16: each other is also something that Taiwan Semis has been 530 00:28:41,680 --> 00:28:44,600 Speaker 16: pursuing for really a decade. The problem with it is 531 00:28:44,640 --> 00:28:47,520 Speaker 16: that is twofold one you have to stack them on 532 00:28:47,560 --> 00:28:48,160 Speaker 16: top of each other. 533 00:28:48,200 --> 00:28:49,200 Speaker 14: In two there's a heat. 534 00:28:49,080 --> 00:28:52,040 Speaker 16: Dissipation issue which is very very difficult to solve. 535 00:28:52,080 --> 00:28:52,920 Speaker 14: So time will tell. 536 00:28:53,000 --> 00:28:56,200 Speaker 16: But we're somewhat skeptical about the Huaii announcements as they 537 00:28:56,200 --> 00:28:56,959 Speaker 16: are as of today. 538 00:28:57,440 --> 00:29:00,840 Speaker 4: How skeptical are you or not of just China's prowess 539 00:29:00,920 --> 00:29:02,680 Speaker 4: when it comes to AI and on its own supply 540 00:29:02,760 --> 00:29:03,400 Speaker 4: chain right now? 541 00:29:04,440 --> 00:29:06,640 Speaker 16: Yes, so I have to say we're very impressed what 542 00:29:06,760 --> 00:29:10,760 Speaker 16: China has been doing, but the core issue remains as 543 00:29:10,800 --> 00:29:13,920 Speaker 16: ever the same, I think. So China does not have 544 00:29:14,080 --> 00:29:19,640 Speaker 16: ASML and or litography manufacturing capabilities that would allow them 545 00:29:19,680 --> 00:29:23,320 Speaker 16: to build leading edged chips, So anything above sort of 546 00:29:23,360 --> 00:29:27,000 Speaker 16: five nanometers plus server, and as long as that doesn't change, 547 00:29:27,160 --> 00:29:29,720 Speaker 16: they will struggle to compete within videos of the world 548 00:29:30,120 --> 00:29:32,160 Speaker 16: with the sc high nexus. 549 00:29:31,800 --> 00:29:34,960 Speaker 14: And microns of the world. And in our opinion there 550 00:29:34,960 --> 00:29:36,200 Speaker 14: may be a decade away from that. 551 00:29:36,280 --> 00:29:39,120 Speaker 16: It took fifteen twenty years for Western nations to build 552 00:29:39,160 --> 00:29:41,120 Speaker 16: something like ASML, so as long as that's the case, 553 00:29:41,160 --> 00:29:42,280 Speaker 16: they will struggle to compete. 554 00:29:43,840 --> 00:29:46,960 Speaker 3: Daniel, how's your math been going post in video earnings? 555 00:29:47,040 --> 00:29:47,200 Speaker 9: Right? 556 00:29:47,320 --> 00:29:49,680 Speaker 3: I think about the one trillion dollar figure, which is 557 00:29:50,080 --> 00:29:55,280 Speaker 3: Blackwell rubin calendar twenty five's calendar twenty seven, and then 558 00:29:55,280 --> 00:29:58,440 Speaker 3: what in video said was they see hyperscale of capex 559 00:29:58,480 --> 00:30:01,120 Speaker 3: one trillion for the com twelve month period. 560 00:30:01,440 --> 00:30:02,280 Speaker 2: So you're trying to work. 561 00:30:02,200 --> 00:30:05,040 Speaker 3: Out how much should they capture in sales and how 562 00:30:05,080 --> 00:30:07,320 Speaker 3: does that translate from video into free cash flow? 563 00:30:07,560 --> 00:30:08,480 Speaker 2: Have you done that math? 564 00:30:09,680 --> 00:30:09,880 Speaker 14: Yeah? 565 00:30:09,920 --> 00:30:12,640 Speaker 16: So the math we have actually done, and I would 566 00:30:12,680 --> 00:30:16,600 Speaker 16: humbly argue is equally interesting. Maybe is so Jensen has 567 00:30:16,600 --> 00:30:19,440 Speaker 16: said something about three to four trillion capex for twenty 568 00:30:19,560 --> 00:30:21,400 Speaker 16: thirty for the entire industry. 569 00:30:21,520 --> 00:30:24,080 Speaker 14: So three to four trillion an enormously large number. 570 00:30:24,480 --> 00:30:26,640 Speaker 16: Now in Vidia tends to have something like we believe 571 00:30:26,680 --> 00:30:30,640 Speaker 16: sixty percent market share across training and inference. Now that 572 00:30:30,760 --> 00:30:34,120 Speaker 16: number is true, which we actually find hard to dismiss. 573 00:30:34,480 --> 00:30:37,720 Speaker 16: That in video would generate something close to forty dollars 574 00:30:37,800 --> 00:30:40,200 Speaker 16: of earnings per share and close to one trillion dollars 575 00:30:40,240 --> 00:30:43,680 Speaker 16: of free cash flow by twenty thirty, and that would 576 00:30:43,680 --> 00:30:45,920 Speaker 16: indicate the stockets sort of five times earnings in that 577 00:30:46,040 --> 00:30:48,680 Speaker 16: time period. So that to us was sort of a 578 00:30:48,720 --> 00:30:52,120 Speaker 16: super interesting number. They've mentioned it before and it seems 579 00:30:52,240 --> 00:30:53,440 Speaker 16: very very large as of now. 580 00:30:53,480 --> 00:30:54,760 Speaker 14: So you'd have to have a lot of growth and 581 00:30:54,800 --> 00:30:55,720 Speaker 14: the anthropics of the. 582 00:30:55,720 --> 00:30:58,760 Speaker 16: World, but Jensen has shown over time, but it tends 583 00:30:58,800 --> 00:31:00,360 Speaker 16: to hit the numbers that you talk about. 584 00:31:00,520 --> 00:31:01,920 Speaker 14: We're very positive on that. 585 00:31:03,320 --> 00:31:06,400 Speaker 3: Daniel Pilling from Sam's Capital good at Math, Thank you 586 00:31:06,560 --> 00:31:08,680 Speaker 3: very much. Care plenty of other news headlines out there. 587 00:31:09,120 --> 00:31:10,840 Speaker 7: It's time now for talking tech ed. Yeah. 588 00:31:10,880 --> 00:31:14,960 Speaker 4: First up, a Samsung union representing workers outside the ultra 589 00:31:15,000 --> 00:31:18,160 Speaker 4: profitable semiconductor division has asked a Korean court to block 590 00:31:18,360 --> 00:31:21,120 Speaker 4: voting on a tentative deal that were distributed about twenty 591 00:31:21,120 --> 00:31:24,640 Speaker 4: six point six billion dollars in bonuses looked a smaller union. 592 00:31:24,880 --> 00:31:25,760 Speaker 7: It's arguing that the. 593 00:31:25,720 --> 00:31:30,320 Speaker 4: Agreement disproportionately favors Samsung's chip business. The semiconductor staff set 594 00:31:30,320 --> 00:31:32,600 Speaker 4: to receive average bonuses about three hundred and forty thousand 595 00:31:32,600 --> 00:31:33,720 Speaker 4: dollars compared. 596 00:31:33,360 --> 00:31:35,280 Speaker 7: With roughly four thousand dollars for. 597 00:31:35,280 --> 00:31:39,880 Speaker 4: Workers in Samsung's Digital Experience division, plus shares of Ferrari 598 00:31:40,160 --> 00:31:43,760 Speaker 4: tumbling after the luxury automaker unveil its first fully electric 599 00:31:43,880 --> 00:31:46,240 Speaker 4: vehicle to a wave of negative. 600 00:31:45,800 --> 00:31:47,320 Speaker 7: Reviews over its design. 601 00:31:47,720 --> 00:31:50,000 Speaker 4: Critics and social media users compared their six round and 602 00:31:50,000 --> 00:31:54,240 Speaker 4: forty thousand dollars Ferrari That's Luccee to mainstream evs, raising 603 00:31:54,320 --> 00:31:56,600 Speaker 4: questions about the company's push into electric vehicles. 604 00:31:56,640 --> 00:31:57,520 Speaker 7: In Johnny Ice. 605 00:31:57,360 --> 00:32:02,080 Speaker 4: Design and Honeywell back to Quon is seeking to raise 606 00:32:02,120 --> 00:32:04,120 Speaker 4: as much as one point zero five billion dollars in 607 00:32:04,120 --> 00:32:06,440 Speaker 4: an IPO now. According to an SEC filing, the Quantum 608 00:32:06,480 --> 00:32:09,400 Speaker 4: Computing Firm and as Yourself, twenty one million chairs close. 609 00:32:09,200 --> 00:32:10,720 Speaker 7: Between forty five and fifty dollars each. 610 00:32:11,000 --> 00:32:13,560 Speaker 4: At the top end of the range, now, Quantumum would 611 00:32:13,560 --> 00:32:17,120 Speaker 4: be valued roughly twelve point seven billion dollars at okay. 612 00:32:17,160 --> 00:32:22,040 Speaker 3: Coming up, SpaceX scores another successful launch, fueling fresh speculation 613 00:32:22,640 --> 00:32:26,160 Speaker 3: about the company's IPO prospects. And Elon Musk growing dominance 614 00:32:26,480 --> 00:32:27,720 Speaker 3: in the commercial space race. 615 00:32:27,760 --> 00:32:30,440 Speaker 2: We have more on that next. This is been Ktech. 616 00:32:49,120 --> 00:32:51,080 Speaker 3: Taking a look at some of what's going on in 617 00:32:51,080 --> 00:32:53,080 Speaker 3: the space sector. A lot of names are on the 618 00:32:53,160 --> 00:32:58,360 Speaker 3: move simply by association validation that the space sector is legit. 619 00:32:58,520 --> 00:33:02,160 Speaker 3: It is for real post SPACEXS S one last week, 620 00:33:02,200 --> 00:33:07,200 Speaker 3: but also after SpaceX's upgraded Starship successfully deployed mock satellites 621 00:33:07,680 --> 00:33:11,840 Speaker 3: and return to Earth mostly unscathed. That was on Friday night. 622 00:33:12,200 --> 00:33:17,360 Speaker 3: Bloomberg's Space correspondent Lauren Grash is with us for SpaceX success. 623 00:33:18,200 --> 00:33:21,880 Speaker 3: Is the data right, so irrespective really what happens in 624 00:33:21,920 --> 00:33:25,200 Speaker 3: the end. This was a completely new, re engineered, new 625 00:33:25,280 --> 00:33:28,080 Speaker 3: architecture V three Starship and they wanted to see how 626 00:33:28,080 --> 00:33:28,720 Speaker 3: it would work. 627 00:33:29,280 --> 00:33:30,080 Speaker 2: How did it work? 628 00:33:31,280 --> 00:33:33,640 Speaker 17: I would say that it was a largely successful debut 629 00:33:33,680 --> 00:33:36,400 Speaker 17: of the vehicle. As you mentioned, this was a completely 630 00:33:36,440 --> 00:33:40,000 Speaker 17: redesigned version of Starship. Mainly it had a lot of 631 00:33:40,040 --> 00:33:44,320 Speaker 17: new upgrades, new Raptor engines that were supposed to significantly 632 00:33:44,800 --> 00:33:47,600 Speaker 17: increase the thrust at liftoff. Also had a number of 633 00:33:47,680 --> 00:33:50,600 Speaker 17: upgrades to help with the reusability that they're after, and 634 00:33:50,680 --> 00:33:53,360 Speaker 17: so by and large it was a successful test. There 635 00:33:53,400 --> 00:33:56,960 Speaker 17: were some uncomfortable moments. For instance, that super heavy booster 636 00:33:57,080 --> 00:34:00,240 Speaker 17: which you can see climbing and sending Starship to space. 637 00:34:00,680 --> 00:34:03,120 Speaker 17: Once it separated, it was supposed to do a controlled 638 00:34:03,440 --> 00:34:07,120 Speaker 17: splashdown or landing in the Gulf, and that didn't quite 639 00:34:07,160 --> 00:34:09,080 Speaker 17: work as plan. It kind of spun out of control 640 00:34:09,120 --> 00:34:11,719 Speaker 17: at one point and then seemed to break apart. And 641 00:34:11,760 --> 00:34:14,600 Speaker 17: then also there was an engine out on Starship. So 642 00:34:15,000 --> 00:34:17,200 Speaker 17: just a few moments where it did not. 643 00:34:17,080 --> 00:34:18,279 Speaker 11: Go to plan. 644 00:34:18,360 --> 00:34:20,839 Speaker 17: It was a little bit incomplete, but I think it 645 00:34:20,920 --> 00:34:24,080 Speaker 17: was by and large a really successful mission for the 646 00:34:24,160 --> 00:34:26,680 Speaker 17: debut of this upgraded version of the vehicle. 647 00:34:27,160 --> 00:34:29,680 Speaker 4: I leve all the quotes some employee Kate tyst we 648 00:34:29,680 --> 00:34:32,359 Speaker 4: were expecting the re entry to be super spicy, and 649 00:34:32,440 --> 00:34:34,680 Speaker 4: I guess that's what we got. But where does this 650 00:34:34,760 --> 00:34:39,000 Speaker 4: put us in the long term trajectory of the plans 651 00:34:39,040 --> 00:34:42,600 Speaker 4: for satellites, for the business model for malls and the like. 652 00:34:43,480 --> 00:34:46,200 Speaker 17: Yeah, I would say we're still marching forward. There are 653 00:34:46,239 --> 00:34:48,359 Speaker 17: still some kings to work out. For instance, you know, 654 00:34:48,840 --> 00:34:51,080 Speaker 17: the big thing about Starship is that it's supposed to 655 00:34:51,160 --> 00:34:54,640 Speaker 17: be fully reusable. That's never been done before, and so 656 00:34:54,680 --> 00:34:57,400 Speaker 17: that problem that they had with the super heavy booster. 657 00:34:57,880 --> 00:35:01,400 Speaker 17: Not doing that controlled landing complicated that on the path 658 00:35:01,480 --> 00:35:05,360 Speaker 17: to that full reusability. But as they demonstrated during this mission, 659 00:35:05,680 --> 00:35:09,719 Speaker 17: they weren't able to deploy satellites like they had planned. 660 00:35:09,760 --> 00:35:13,040 Speaker 17: They were dummy satellites, but they did demonstrate that could work. 661 00:35:13,360 --> 00:35:16,480 Speaker 17: So it does seem, you know, it stands to reason 662 00:35:16,560 --> 00:35:19,400 Speaker 17: that that could potentially happen soon. I know they're aiming 663 00:35:19,400 --> 00:35:23,400 Speaker 17: at within the next year, but still there's definitely a 664 00:35:23,440 --> 00:35:26,080 Speaker 17: long road ahead in order to really fully unlock this 665 00:35:26,239 --> 00:35:28,040 Speaker 17: vehicle for what it's supposed to be. 666 00:35:28,360 --> 00:35:33,120 Speaker 4: And maybe vindicate evaluation. As we see some extraordinary footage 667 00:35:33,120 --> 00:35:35,160 Speaker 4: coming from the launch on Friday night, Long and Grush, 668 00:35:35,200 --> 00:35:37,080 Speaker 4: thank you so much for breaking it all down for us. 669 00:35:37,719 --> 00:35:41,640 Speaker 4: Let's get the latest on SpaceX's potential listing into the 670 00:35:41,800 --> 00:35:44,799 Speaker 4: market as well as the wider IPO landscape, because we've 671 00:35:44,800 --> 00:35:46,800 Speaker 4: got Ja Rittter with us. He's director of the IPO 672 00:35:46,840 --> 00:35:49,080 Speaker 4: Initiative University of Florida, Mariatage professor. 673 00:35:49,200 --> 00:35:50,640 Speaker 7: They call you mister IPO. 674 00:35:51,239 --> 00:35:54,359 Speaker 4: So mister IPO, tell us as to how we see 675 00:35:54,360 --> 00:35:58,000 Speaker 4: a vindication in the market capitalization of SpaceX as it 676 00:35:58,040 --> 00:36:00,000 Speaker 4: goes public because, as Ed was writing in his news 677 00:36:00,080 --> 00:36:02,200 Speaker 4: letter today, an awful lot has to go right. 678 00:36:03,960 --> 00:36:07,399 Speaker 12: I'm in complete agreement, an awful lot has to go right. 679 00:36:07,600 --> 00:36:12,200 Speaker 12: But this is a great company, as Lauren was indicating, 680 00:36:12,840 --> 00:36:21,120 Speaker 12: Starship is an incredible engineering feet. It's complicated, but this 681 00:36:21,320 --> 00:36:25,360 Speaker 12: is actually a competitive advantage. It's so difficult for a 682 00:36:25,400 --> 00:36:29,440 Speaker 12: competitor to come up with something similar that's going to 683 00:36:29,440 --> 00:36:34,960 Speaker 12: be able to lower launch costs as much as SpaceX can. 684 00:36:35,480 --> 00:36:38,560 Speaker 12: That it's going to allow SpaceX to have a big 685 00:36:38,719 --> 00:36:43,800 Speaker 12: technological lead over any potential competitor, and this will allow 686 00:36:43,840 --> 00:36:50,600 Speaker 12: it to put Starlink satellites into lower orbit and offer 687 00:36:50,800 --> 00:36:56,320 Speaker 12: startlink Internet access at much lower costs than competitors can. 688 00:36:58,320 --> 00:37:03,480 Speaker 3: Jay, Professor, you are called mister IPO, if you don't 689 00:37:03,480 --> 00:37:06,200 Speaker 3: mind me saying, because you're probably the most influential, most 690 00:37:06,239 --> 00:37:10,480 Speaker 3: cited academic researcher in the field of IPOs of the 691 00:37:10,560 --> 00:37:15,600 Speaker 3: last forty years. What is different about this IPO and 692 00:37:15,640 --> 00:37:18,480 Speaker 3: what is the same as those that you have studied 693 00:37:18,520 --> 00:37:20,080 Speaker 3: deeply in your career. 694 00:37:21,280 --> 00:37:24,400 Speaker 12: Well, what's different is this is going to be the 695 00:37:24,560 --> 00:37:30,360 Speaker 12: largest private sector company ever to go public. Evaluation of 696 00:37:30,400 --> 00:37:35,399 Speaker 12: something like one point five trillion dollars, dramatically higher than 697 00:37:36,160 --> 00:37:41,280 Speaker 12: any other of the big companies that have gone public 698 00:37:41,560 --> 00:37:46,320 Speaker 12: in the past. They've generally been large state owned enterprises 699 00:37:46,600 --> 00:37:53,000 Speaker 12: with very large operations and profitability. This is a company 700 00:37:53,200 --> 00:37:57,680 Speaker 12: where the market and venture capitalists have been valuing it 701 00:37:57,840 --> 00:38:04,239 Speaker 12: based upon enormous potential future profitability. But as I was 702 00:38:04,280 --> 00:38:07,359 Speaker 12: mentioned previously, a lot of stuff has to go right 703 00:38:07,400 --> 00:38:08,880 Speaker 12: to justify this valuation. 704 00:38:10,800 --> 00:38:13,239 Speaker 4: When you think about just the multiples that are going 705 00:38:13,280 --> 00:38:14,960 Speaker 4: to be digested, and I know you've looked a lot 706 00:38:15,000 --> 00:38:19,000 Speaker 4: into that, where does it sit in past and historical 707 00:38:19,080 --> 00:38:21,759 Speaker 4: terms compared to those that did list Because as we've 708 00:38:21,800 --> 00:38:24,640 Speaker 4: been talking about time and time again, across this entire network, 709 00:38:25,440 --> 00:38:28,960 Speaker 4: companies are staying much longer private and they're coming in 710 00:38:29,000 --> 00:38:31,480 Speaker 4: extraordinary valuations, And so you wonder how much money is 711 00:38:31,520 --> 00:38:33,320 Speaker 4: left on the table for a retail investor or a 712 00:38:33,360 --> 00:38:35,560 Speaker 4: different type of investor that hasn't been funding it from 713 00:38:35,600 --> 00:38:36,800 Speaker 4: day one. 714 00:38:37,920 --> 00:38:38,200 Speaker 14: Right. 715 00:38:38,680 --> 00:38:41,360 Speaker 12: This is a company where last year it had eighteen 716 00:38:41,400 --> 00:38:46,400 Speaker 12: point seven billion dollars in sales, bigger than just about 717 00:38:46,440 --> 00:38:53,719 Speaker 12: any tech startup or private company that hadn't already been 718 00:38:53,760 --> 00:38:57,200 Speaker 12: public has in terms of revenue at the time of 719 00:38:57,280 --> 00:39:04,480 Speaker 12: going public, but it's also got the really huge valuation, 720 00:39:05,360 --> 00:39:16,319 Speaker 12: and to justify a one point five trillion valuation, very 721 00:39:16,320 --> 00:39:19,279 Speaker 12: big future profits have to be there. There have only 722 00:39:19,320 --> 00:39:24,040 Speaker 12: been about eighteen companies that have gone public in the 723 00:39:24,160 --> 00:39:27,960 Speaker 12: US with inflation adjustice revenue of at least one hundred 724 00:39:28,000 --> 00:39:31,440 Speaker 12: million dollars per year and a price to sales racial 725 00:39:31,520 --> 00:39:36,560 Speaker 12: of more than forty at a one point five trillion valuation. 726 00:39:37,200 --> 00:39:38,920 Speaker 14: SpaceX is going to be going. 727 00:39:38,719 --> 00:39:41,840 Speaker 12: Public at a price to sales racial of about eighty. 728 00:39:42,440 --> 00:39:45,920 Speaker 12: So there haven't been all that many companies that have 729 00:39:46,000 --> 00:39:50,719 Speaker 12: done this before, but of those that have, on average, 730 00:39:50,960 --> 00:39:56,120 Speaker 12: the stock has been disappointment to investors. Lots of things 731 00:39:56,200 --> 00:39:56,960 Speaker 12: have to go right. 732 00:39:58,160 --> 00:40:00,560 Speaker 3: Lots things have to go right, Jay repeats throughout the 733 00:40:00,680 --> 00:40:04,040 Speaker 3: s One is a warning that they will be constrained 734 00:40:04,040 --> 00:40:06,719 Speaker 3: by compute now in the future, and starship has to 735 00:40:06,800 --> 00:40:09,680 Speaker 3: work very quickly. Is that just boiler plate or they 736 00:40:09,719 --> 00:40:10,480 Speaker 3: have to say that. 737 00:40:13,040 --> 00:40:20,280 Speaker 12: You know, it's technologically true that the profitability of sending 738 00:40:20,320 --> 00:40:24,239 Speaker 12: people to mys is very questionable, but the ability to 739 00:40:25,760 --> 00:40:30,359 Speaker 12: get things going in the foreseeable future with startling can 740 00:40:30,480 --> 00:40:32,120 Speaker 12: be an enormous source of profits. 741 00:40:34,040 --> 00:40:37,240 Speaker 3: Jay Rider, the IPO initiative the University of Florida. 742 00:40:37,320 --> 00:40:40,160 Speaker 2: They call him mister ip O. Thank you very much. 743 00:40:40,239 --> 00:40:43,200 Speaker 3: Now coming up, Google comes out with the fit Bit Air, 744 00:40:43,400 --> 00:40:46,160 Speaker 3: trying to catch up to Whoop in the AI powered 745 00:40:46,280 --> 00:40:47,160 Speaker 3: wellness space. 746 00:40:47,760 --> 00:40:49,840 Speaker 2: Can have a look. This is Blombog tech. 747 00:41:01,239 --> 00:41:01,920 Speaker 7: Tech companies. 748 00:41:02,080 --> 00:41:04,800 Speaker 4: They are racing into an era of personalized health and 749 00:41:04,920 --> 00:41:07,320 Speaker 4: Google is out with its latest product in the space, 750 00:41:07,680 --> 00:41:08,520 Speaker 4: the Fitbit Air. 751 00:41:08,960 --> 00:41:11,400 Speaker 7: So new one hundred dollars screen is wearable, which. 752 00:41:11,320 --> 00:41:14,319 Speaker 4: Represents a major evolution in what consumers can expect from 753 00:41:14,400 --> 00:41:17,839 Speaker 4: fitness trackers. More, let's speak to Bluma's consumer tech editor 754 00:41:18,200 --> 00:41:22,440 Speaker 4: in a Woman. Now, you have a Whoop, which might 755 00:41:22,600 --> 00:41:24,960 Speaker 4: be a direct comparison here. But what's so interesting is 756 00:41:25,040 --> 00:41:28,160 Speaker 4: Google having more of an sort of open way in 757 00:41:28,239 --> 00:41:30,160 Speaker 4: which they're going to be allowing us to use our data. 758 00:41:31,360 --> 00:41:33,239 Speaker 18: Yes, so I think the business model is going to 759 00:41:33,320 --> 00:41:36,400 Speaker 18: be quite more appealing for a wider swath of consumers. 760 00:41:36,480 --> 00:41:39,279 Speaker 18: So you pay upfront for Google's hardware and then if 761 00:41:39,320 --> 00:41:41,879 Speaker 18: you like, you can just use Google Health for free 762 00:41:41,960 --> 00:41:44,080 Speaker 18: as a free app. They do have a premium tier 763 00:41:44,160 --> 00:41:46,680 Speaker 18: that offers a lot more interesting features, and that's where 764 00:41:46,719 --> 00:41:49,360 Speaker 18: you might be paying locked into a subscription model, but 765 00:41:49,440 --> 00:41:53,399 Speaker 18: Whoop is entirely subscription based. It Technically you aren't even 766 00:41:53,440 --> 00:41:55,880 Speaker 18: paying for the hardware itself. You're paying for these annual 767 00:41:55,960 --> 00:41:59,200 Speaker 18: subscriptions and if you ever cancel, your device is pretty 768 00:41:59,280 --> 00:41:59,720 Speaker 18: much bricked. 769 00:42:01,120 --> 00:42:03,359 Speaker 3: The business models are so different between the two, right, 770 00:42:03,400 --> 00:42:05,560 Speaker 3: I mean, like just last week we were talking about 771 00:42:05,680 --> 00:42:09,920 Speaker 3: different form factor but or arraying and IPO. You're the 772 00:42:10,040 --> 00:42:12,320 Speaker 3: editor on the Consumer Tech team. We do reviews, like 773 00:42:12,400 --> 00:42:14,920 Speaker 3: we get into the tech, how it works. What was 774 00:42:15,000 --> 00:42:17,680 Speaker 3: the team's kind of like impression. 775 00:42:17,800 --> 00:42:20,960 Speaker 18: So we think competition is good. Sorry to sound so 776 00:42:22,360 --> 00:42:25,200 Speaker 18: buttoned up there, but competition is good I think for consumers, and. 777 00:42:25,440 --> 00:42:26,080 Speaker 7: We like both. 778 00:42:26,239 --> 00:42:28,560 Speaker 18: Is really sort of the long and the short of it. 779 00:42:28,680 --> 00:42:32,200 Speaker 18: Whoop is still probably a better choice for more advanced users. 780 00:42:32,280 --> 00:42:34,680 Speaker 18: It has a more data focused approach, so it pulls 781 00:42:34,760 --> 00:42:37,880 Speaker 18: more data. It presents it in a very clean, but 782 00:42:38,000 --> 00:42:40,520 Speaker 18: sort of geeky way. I think if you are looking 783 00:42:40,560 --> 00:42:44,080 Speaker 18: to interact with a device like this, really leaning into 784 00:42:44,120 --> 00:42:47,600 Speaker 18: the AI, having a conversation with a coach that is proactive. 785 00:42:48,320 --> 00:42:50,840 Speaker 18: Google's AI is more advanced than Whoops. I found it 786 00:42:50,960 --> 00:42:55,160 Speaker 18: more natural, more conversational. It was easier, for instance, to explain, hey, 787 00:42:55,560 --> 00:42:56,839 Speaker 18: if I wake up in the middle of the night, 788 00:42:56,880 --> 00:42:59,080 Speaker 18: it's because my toddler woke me up. Briefly, it's not 789 00:42:59,320 --> 00:43:02,120 Speaker 18: because I have I've chosen to wake up at two AM. 790 00:43:02,239 --> 00:43:04,640 Speaker 18: So having conversations like that is a lot easier with 791 00:43:04,719 --> 00:43:07,840 Speaker 18: Google's device. You will get more data still with Whoop, 792 00:43:07,880 --> 00:43:10,560 Speaker 18: and you will, in my opinion, see it presented in 793 00:43:10,640 --> 00:43:12,279 Speaker 18: a way that makes a little more sense and is 794 00:43:12,320 --> 00:43:13,960 Speaker 18: a little more aesthetically pleasing. 795 00:43:14,880 --> 00:43:18,160 Speaker 4: What's interesting is the way in which, briefly we're going 796 00:43:18,200 --> 00:43:20,160 Speaker 4: to be using them with so much more than sleep 797 00:43:20,280 --> 00:43:23,040 Speaker 4: or heart rate and the like, oh, I'm sorry when 798 00:43:23,080 --> 00:43:24,800 Speaker 4: we go using them more for like you're using for 799 00:43:24,880 --> 00:43:27,359 Speaker 4: meal plans, for example, how you can fold it in more. 800 00:43:27,800 --> 00:43:28,680 Speaker 2: Yes, absolutely so. 801 00:43:28,760 --> 00:43:30,759 Speaker 18: I used it for a combination of I tried to 802 00:43:30,880 --> 00:43:32,719 Speaker 18: use it really like any consumer would. I used it 803 00:43:32,800 --> 00:43:35,879 Speaker 18: for a combination of sleep tracking overnight analyzing my sleep 804 00:43:35,960 --> 00:43:38,480 Speaker 18: and my readiness for the coming day. And I really 805 00:43:38,560 --> 00:43:41,240 Speaker 18: played around a lot with the food tracking. 806 00:43:41,280 --> 00:43:41,440 Speaker 2: Here. 807 00:43:41,560 --> 00:43:44,160 Speaker 18: I took pictures of my meals. I said, how many 808 00:43:44,239 --> 00:43:49,760 Speaker 18: calories is this? And actually the estimate seemed pretty accurate 809 00:43:49,800 --> 00:43:50,520 Speaker 18: as far as I could tell. 810 00:43:50,600 --> 00:43:53,440 Speaker 4: Right, Dana great getting up aspective woman. 811 00:43:53,280 --> 00:43:54,040 Speaker 12: And it to you. 812 00:43:54,840 --> 00:43:57,600 Speaker 3: Yeah, check out the four review on Bloomberg dot com. Unfortunately, 813 00:43:57,719 --> 00:43:59,560 Speaker 3: that does it. First edition of Bloomberg Tech. 814 00:44:00,200 --> 00:44:01,560 Speaker 7: Don't forget to check out this podcast. 815 00:44:01,680 --> 00:44:02,880 Speaker 4: You can find it on the terminal as well as 816 00:44:02,880 --> 00:44:05,400 Speaker 4: online on Apple, Spotify, and iHeart This is Blueberg.