1 00:00:02,520 --> 00:00:13,119 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is a 2 00:00:13,200 --> 00:00:16,960 Speaker 1: live from Coast to Coast with Caroline Hyde in New 3 00:00:17,040 --> 00:00:19,520 Speaker 1: York and vlave Low in sentences go. 4 00:00:22,520 --> 00:00:24,040 Speaker 2: This is Bloomberg Tech coming up. 5 00:00:24,079 --> 00:00:27,360 Speaker 3: Broadcom suffers a stock slide after its sales outlook or 6 00:00:27,480 --> 00:00:30,800 Speaker 3: lack of failed to meet investors lofty expectations. 7 00:00:30,920 --> 00:00:34,440 Speaker 4: Plus, China I is the largest ever state MATCHIP incentives, 8 00:00:34,440 --> 00:00:36,920 Speaker 4: with as much as seventy billion dollars of state money 9 00:00:37,040 --> 00:00:38,440 Speaker 4: incident for the pivotal sector. 10 00:00:39,600 --> 00:00:42,960 Speaker 3: And our conversation with White House ais are David Sachs 11 00:00:43,080 --> 00:00:47,360 Speaker 3: on President Trump's executive order aimed at limiting state level 12 00:00:47,400 --> 00:00:48,280 Speaker 3: regulation of AI. 13 00:00:48,800 --> 00:00:52,159 Speaker 4: First, and we check on these markets that are dictated 14 00:00:52,479 --> 00:00:55,319 Speaker 4: by tech, dictated by them, and we say that where 15 00:00:55,320 --> 00:00:57,360 Speaker 4: we're off by eight tenths one point eight percent, let's 16 00:00:57,400 --> 00:00:59,160 Speaker 4: look at it and the Nastak one hundred, we are 17 00:00:59,240 --> 00:01:02,480 Speaker 4: under pressure. We consider not just the macro perspective, and 18 00:01:02,560 --> 00:01:05,400 Speaker 4: vonn yields move what's happening underneath the surface. I'm looking 19 00:01:05,440 --> 00:01:08,240 Speaker 4: at the Golden Dragon Index. Look, this is showing what 20 00:01:08,360 --> 00:01:10,640 Speaker 4: Chinese names trade in the US in terms that eight 21 00:01:10,760 --> 00:01:11,319 Speaker 4: hors are up to. 22 00:01:11,720 --> 00:01:15,559 Speaker 5: What a dichotomy. We've got going what a juxtaposition, China higher, we'll. 23 00:01:15,400 --> 00:01:18,360 Speaker 4: Get to that news later, US lower, and in large 24 00:01:18,360 --> 00:01:19,440 Speaker 4: part it's by one key stock. 25 00:01:19,480 --> 00:01:24,559 Speaker 3: You're looking at some breaking news Bloomberg reporting citing sources 26 00:01:24,840 --> 00:01:28,440 Speaker 3: that Oracle has pushed back some of the completion dates 27 00:01:28,720 --> 00:01:32,640 Speaker 3: of data centers that's developing with and for open AI. 28 00:01:32,840 --> 00:01:36,840 Speaker 3: That pushback is to twenty twenty eight from an earlier 29 00:01:36,880 --> 00:01:39,240 Speaker 3: plan of twenty twenty seven. The market reacted. Look at 30 00:01:39,240 --> 00:01:41,800 Speaker 3: the right hand side of the squiggly line. It's paired 31 00:01:41,840 --> 00:01:43,840 Speaker 3: some of that decline, but at one point session low 32 00:01:43,880 --> 00:01:45,000 Speaker 3: well beyond six percent. 33 00:01:45,520 --> 00:01:46,880 Speaker 2: I think car relating the show. 34 00:01:46,720 --> 00:01:48,640 Speaker 3: We're going to get an opportunity to talk to Brody Ford. 35 00:01:48,920 --> 00:01:51,600 Speaker 3: You broke that story. Get more of the details. Right now, 36 00:01:51,640 --> 00:01:54,520 Speaker 3: the top story is Broadcom. It is on track for 37 00:01:54,560 --> 00:01:59,400 Speaker 3: its biggest decline since January of this year, a seventy 38 00:01:59,400 --> 00:02:03,040 Speaker 3: three billion dollar backlog AI specific, but what the street 39 00:02:03,080 --> 00:02:06,200 Speaker 3: wanted was a very different number. During a conference call, 40 00:02:06,600 --> 00:02:11,519 Speaker 3: CEO Hoc Tan held off giving an annual AI revenue forecast, 41 00:02:11,800 --> 00:02:13,760 Speaker 3: saying it was quote a moving target. 42 00:02:13,760 --> 00:02:14,240 Speaker 2: Listen to this. 43 00:02:15,600 --> 00:02:18,960 Speaker 6: It's hard for me to pinpoint what twenty six is 44 00:02:18,960 --> 00:02:21,880 Speaker 6: going to look like precisely. So I'd rather not give 45 00:02:21,919 --> 00:02:24,400 Speaker 6: you guys any guys, and that's why we don't give 46 00:02:24,440 --> 00:02:30,240 Speaker 6: you guys, but we do give it for two one. 47 00:02:29,240 --> 00:02:32,720 Speaker 3: Carle Ackerman, Managing director of semi Conductors and Networking Hardware 48 00:02:32,720 --> 00:02:35,040 Speaker 3: at BNP Pariber joins us for more is new price 49 00:02:35,120 --> 00:02:38,000 Speaker 3: target four hundred and seventy five dollars, among the highest 50 00:02:38,000 --> 00:02:41,080 Speaker 3: now for analysts covering the stock. So that's the point. 51 00:02:41,360 --> 00:02:43,680 Speaker 3: You have different sets of data. They gave us a 52 00:02:43,680 --> 00:02:48,320 Speaker 3: figure which was a seventy three billion dollar backlog this morning. 53 00:02:48,400 --> 00:02:50,799 Speaker 3: Quite clearly the market would like to see a revenue 54 00:02:51,080 --> 00:02:52,280 Speaker 3: number that's forward looking. 55 00:02:52,600 --> 00:02:54,440 Speaker 2: Yep, yeah, that's true. 56 00:02:54,600 --> 00:02:56,880 Speaker 7: So so you're right, I think the I think what's 57 00:02:56,919 --> 00:02:59,480 Speaker 7: interesting here the reason why brad Armer is down is 58 00:02:59,520 --> 00:03:02,840 Speaker 7: not about out the It's not about how revenue has 59 00:03:02,840 --> 00:03:04,880 Speaker 7: perhaps missed expectations. First and forem with some of the 60 00:03:04,880 --> 00:03:10,720 Speaker 7: company actually beaten raised guidance AI sales or above expectations. 61 00:03:10,800 --> 00:03:12,760 Speaker 7: The outlook for next quarter of eight point two billion 62 00:03:12,840 --> 00:03:15,280 Speaker 7: farc City consensus of six point eight billion of AI sales, 63 00:03:15,320 --> 00:03:18,920 Speaker 7: which doubled on ear of your basis. When queried, the 64 00:03:18,960 --> 00:03:22,680 Speaker 7: company indicated that how Co indicated that revenue could perhaps 65 00:03:22,680 --> 00:03:25,960 Speaker 7: accelerate into fiscal twenty six versus that one hundred percent 66 00:03:26,000 --> 00:03:29,040 Speaker 7: accelerated growth number. We have over fifty billion of AI 67 00:03:29,240 --> 00:03:32,000 Speaker 7: sales in fiscal twenty five. I think the reason why 68 00:03:32,040 --> 00:03:35,720 Speaker 7: the stock is down ed, however, is in part because 69 00:03:35,840 --> 00:03:38,880 Speaker 7: there are some investors a bit worried about the margin 70 00:03:39,000 --> 00:03:42,960 Speaker 7: structure of the Entropic deal. So of that seventy three 71 00:03:43,000 --> 00:03:46,640 Speaker 7: billion in AI sales, twenty one billion will go to 72 00:03:46,640 --> 00:03:49,480 Speaker 7: an Entropic as part of a TPU system sale, and 73 00:03:49,520 --> 00:03:52,360 Speaker 7: that TPU system sale is going to be lower margin 74 00:03:52,440 --> 00:03:54,160 Speaker 7: than what brought Com generates content. 75 00:03:54,320 --> 00:03:56,120 Speaker 3: How much of the content of a server do you 76 00:03:56,160 --> 00:03:57,560 Speaker 3: own beyond just the chair? 77 00:03:57,720 --> 00:03:59,080 Speaker 2: But you like this name right? 78 00:03:59,120 --> 00:04:01,320 Speaker 3: Like you've just rate the price target to full seventy 79 00:04:01,320 --> 00:04:05,240 Speaker 3: five from three to eighty five, that right map, Well, 80 00:04:05,240 --> 00:04:06,280 Speaker 3: what is it you like about? 81 00:04:06,320 --> 00:04:07,280 Speaker 2: Brokem sure? 82 00:04:07,360 --> 00:04:09,480 Speaker 7: I mean Broadcom I think is in a llegue of 83 00:04:09,480 --> 00:04:12,800 Speaker 7: its own, akin to in video. Really where Nvidia and 84 00:04:12,800 --> 00:04:17,000 Speaker 7: Broadcom dominate two of the three main buckets of AI 85 00:04:17,000 --> 00:04:21,320 Speaker 7: infrastructure spending. Those include compute, memory, and networking. They of 86 00:04:21,320 --> 00:04:24,520 Speaker 7: course control two of them, networking and compute more than 87 00:04:24,520 --> 00:04:28,360 Speaker 7: anyone else, And I think, what's what is happening here? 88 00:04:28,440 --> 00:04:31,880 Speaker 7: What the what the investment community I think is overlooking 89 00:04:31,920 --> 00:04:34,600 Speaker 7: today on this on the selloff is the fact that 90 00:04:34,680 --> 00:04:39,000 Speaker 7: Broadcom is moving toward a full solution stack akin to 91 00:04:39,040 --> 00:04:43,359 Speaker 7: what in Video is doing on I'm providing AI compute 92 00:04:43,400 --> 00:04:46,560 Speaker 7: and AI networking as we move to scale up domain 93 00:04:47,040 --> 00:04:51,000 Speaker 7: where you're going to need optical for both the for 94 00:04:51,080 --> 00:04:53,760 Speaker 7: the both the networking A six and the and the compute. 95 00:04:53,800 --> 00:04:57,720 Speaker 7: And they offer that entire IP stack in house. And 96 00:04:57,760 --> 00:05:01,039 Speaker 7: that is what I think people are over miss missing today. 97 00:05:01,160 --> 00:05:03,040 Speaker 5: You're calling it short sighted, Karl. 98 00:05:03,600 --> 00:05:05,400 Speaker 4: I know you don't cover in Video as a name, 99 00:05:05,440 --> 00:05:09,480 Speaker 4: but does broadcom success come at the expense of others 100 00:05:09,480 --> 00:05:10,040 Speaker 4: in the market? 101 00:05:12,200 --> 00:05:14,599 Speaker 7: Thanks Carolyn, It's a good question, you know, I think 102 00:05:15,279 --> 00:05:18,400 Speaker 7: I think it's in a vacuum. You know, we try 103 00:05:18,400 --> 00:05:21,960 Speaker 7: and pigeonhole broad conferences in Vidia or broad conferences AMD 104 00:05:22,120 --> 00:05:26,240 Speaker 7: or GPUs versus customer accelerators. I think what we found 105 00:05:26,240 --> 00:05:29,000 Speaker 7: out is that it is not a it is not 106 00:05:29,120 --> 00:05:32,239 Speaker 7: a winner take Hall, It is not a singular approach. 107 00:05:32,640 --> 00:05:36,200 Speaker 7: What you're seeing is that hyper scales are adopting custom 108 00:05:36,560 --> 00:05:42,200 Speaker 7: compute as well as GPUs for frontier model training, and 109 00:05:42,360 --> 00:05:45,560 Speaker 7: that will continue to progress as we move toward inferencing, 110 00:05:45,680 --> 00:05:50,560 Speaker 7: So it's not so clear sighted there. I think what's 111 00:05:50,600 --> 00:05:54,160 Speaker 7: important here is that Broadcom offers the full solution stack 112 00:05:54,760 --> 00:06:00,479 Speaker 7: across networking and compute, and similar to Nvidia, those are 113 00:06:00,480 --> 00:06:04,080 Speaker 7: about the only two companies in all of tech, including Semis, 114 00:06:04,440 --> 00:06:05,680 Speaker 7: that offer that capability. 115 00:06:06,560 --> 00:06:10,680 Speaker 4: Of course, hocktans very much aligned in terms of his 116 00:06:10,760 --> 00:06:14,839 Speaker 4: own pay package with hitting certain revenue numbers for AI 117 00:06:14,960 --> 00:06:18,400 Speaker 4: in particular. But from your perspective, is there a supply 118 00:06:18,480 --> 00:06:19,400 Speaker 4: side headache going on. 119 00:06:19,360 --> 00:06:19,760 Speaker 5: At the moment. 120 00:06:19,839 --> 00:06:22,640 Speaker 4: We're hearing reports that Dell, for example, is having to 121 00:06:22,720 --> 00:06:25,040 Speaker 4: jack up pricing because of the pricing that it's feeding 122 00:06:25,040 --> 00:06:27,080 Speaker 4: on memory were Broadly, we're seeing the breaking news that 123 00:06:27,120 --> 00:06:29,400 Speaker 4: Oracle's having to delay some of its data centers. There 124 00:06:29,560 --> 00:06:33,119 Speaker 4: is a tussle for the infrastructure that's necessary right now, 125 00:06:33,440 --> 00:06:35,240 Speaker 4: and is that just not going to happen in the 126 00:06:35,279 --> 00:06:37,280 Speaker 4: overnight way that the market is anticipating. 127 00:06:39,720 --> 00:06:42,440 Speaker 7: Great question, Carolyn, I think what's interesting to hear is 128 00:06:42,839 --> 00:06:45,040 Speaker 7: I would like to tie in this idea that are 129 00:06:45,080 --> 00:06:47,560 Speaker 7: we in a bubble of AI infrastructure? 130 00:06:47,560 --> 00:06:51,280 Speaker 2: I think that's no. The answer is definitive. No, I think. 131 00:06:53,080 --> 00:06:58,400 Speaker 7: Gigawatt capacity and announcements take time to ramp that ramp 132 00:06:58,440 --> 00:07:04,320 Speaker 7: in that qualification and filling up that fab is now 133 00:07:04,360 --> 00:07:07,280 Speaker 7: extending the visibility across the entire supply chain, whether it's 134 00:07:07,600 --> 00:07:11,680 Speaker 7: hard drives, whether it's memory, whether it's networking, whether it's compute, 135 00:07:12,000 --> 00:07:16,120 Speaker 7: and that is giving companies like Broadcom, companies like Nvidia, 136 00:07:16,200 --> 00:07:18,360 Speaker 7: companies like everyone across the supply chain. 137 00:07:18,400 --> 00:07:19,480 Speaker 2: Very long visibility. 138 00:07:20,680 --> 00:07:24,760 Speaker 7: And right now things are very tight, and so some 139 00:07:24,760 --> 00:07:26,920 Speaker 7: of the areas that are the most tight in our 140 00:07:27,560 --> 00:07:32,800 Speaker 7: AI ecosystem coverage include lasers for optical transceiver components. There 141 00:07:32,840 --> 00:07:36,960 Speaker 7: are ways to ameliorate those that tightness among the supply chain, 142 00:07:37,400 --> 00:07:42,400 Speaker 7: and Hawk and Broadcom announced how they have the sufficient 143 00:07:42,480 --> 00:07:45,720 Speaker 7: capacity for their chips to meet the demand that they 144 00:07:45,800 --> 00:07:49,080 Speaker 7: see in fiscal twenty six and in fiscal twenty seven. 145 00:07:49,480 --> 00:07:50,880 Speaker 5: Who doesn't love talking lasers. 146 00:07:51,080 --> 00:07:54,440 Speaker 4: Kyle Ackerman of BNP paraba, it's been great getting your take. 147 00:07:54,520 --> 00:07:57,640 Speaker 4: As we do see stocks fallswe the NASDAK more broadly 148 00:07:57,680 --> 00:08:01,040 Speaker 4: now under pressure is some two percent pop. The discussion 149 00:08:01,040 --> 00:08:03,880 Speaker 4: that's happening between the US and China, because look, chip 150 00:08:03,920 --> 00:08:06,040 Speaker 4: markets are in the eye of the storm. They're China 151 00:08:06,080 --> 00:08:08,280 Speaker 4: planning to pour up to seventy billion dollars of state 152 00:08:08,320 --> 00:08:11,840 Speaker 4: money into the sector, dem pivotal to its technological conflict 153 00:08:12,040 --> 00:08:15,200 Speaker 4: with the United States. Bloomberg's Maggie Eastland joins US now, 154 00:08:15,520 --> 00:08:19,720 Speaker 4: and seventy billion dollars would be an extraordinary amount of 155 00:08:19,760 --> 00:08:21,840 Speaker 4: government support that we've ever seen worldwide. 156 00:08:21,920 --> 00:08:25,440 Speaker 5: Right, Yes, this is a huge number. 157 00:08:25,560 --> 00:08:29,560 Speaker 8: This would be you know, China's biggest semiconductor specific packaging. 158 00:08:29,600 --> 00:08:32,480 Speaker 8: And according to Bloomberg reporting, that number could be anywhere 159 00:08:32,559 --> 00:08:35,480 Speaker 8: between as you said, seventy billion, and it could go 160 00:08:35,520 --> 00:08:37,199 Speaker 8: down to twenty eight billion, So it depends. 161 00:08:37,240 --> 00:08:38,680 Speaker 5: Here we'll see how large it is. 162 00:08:38,760 --> 00:08:42,800 Speaker 8: That compares to the US effort at industrial policy for semiconductors, 163 00:08:42,840 --> 00:08:44,400 Speaker 8: which is fifty two billion dollars. 164 00:08:44,679 --> 00:08:45,240 Speaker 5: So this is a. 165 00:08:45,200 --> 00:08:48,440 Speaker 8: Similar scale to what the US has undertaken in recent years. 166 00:08:49,559 --> 00:08:52,080 Speaker 3: Maggie, there are some questions to which we just don't 167 00:08:52,160 --> 00:08:55,400 Speaker 3: have answers, and that largely relates to what China specifically 168 00:08:55,440 --> 00:08:57,960 Speaker 3: will do with the funds and where they'll go. But 169 00:08:58,080 --> 00:09:01,559 Speaker 3: within that Bloomberg reporting, where do we think China is 170 00:09:01,600 --> 00:09:04,720 Speaker 3: going to prioritize using the funding to you know, which 171 00:09:04,840 --> 00:09:06,600 Speaker 3: champions is it going to elevate. 172 00:09:08,400 --> 00:09:10,760 Speaker 8: Yes, So of course China is always really looking to 173 00:09:10,800 --> 00:09:13,720 Speaker 8: support it's AI chip makers that compete with in Vidia, 174 00:09:13,800 --> 00:09:17,640 Speaker 8: so that includes companies like Huawei and Camber kN But 175 00:09:17,720 --> 00:09:21,520 Speaker 8: there are other chip companies including SMIC or Smith which 176 00:09:21,640 --> 00:09:26,720 Speaker 8: does the manufacturing, so that would be the corollary to TSMC. 177 00:09:27,040 --> 00:09:30,120 Speaker 8: So there's a range of companies that could see this investment. 178 00:09:30,600 --> 00:09:33,400 Speaker 8: But China will face headwinds because it still has restrictions 179 00:09:33,480 --> 00:09:36,719 Speaker 8: on many of the equipment technologies and the foundries that 180 00:09:36,800 --> 00:09:37,960 Speaker 8: can't access TSMC. 181 00:09:38,040 --> 00:09:39,480 Speaker 5: For those advanced node chips. 182 00:09:39,960 --> 00:09:43,200 Speaker 4: You have many worrying about just what yields are like 183 00:09:43,840 --> 00:09:46,679 Speaker 4: from an SMIC from a SMICK when they're actually producing 184 00:09:46,679 --> 00:09:49,520 Speaker 4: these homegrown, domestically made chips. But I'm looking at video 185 00:09:49,640 --> 00:09:52,600 Speaker 4: under pressure again today, Maggie. Well, broadly, are we getting 186 00:09:52,600 --> 00:09:55,000 Speaker 4: any sense whether this is meaning that China will say 187 00:09:55,040 --> 00:09:56,680 Speaker 4: no thank you to the H two hundreds in the 188 00:09:56,679 --> 00:09:58,199 Speaker 4: same way that they did the H twenties. 189 00:10:00,320 --> 00:10:03,120 Speaker 8: As you know, China has certainly never been shy about 190 00:10:03,160 --> 00:10:06,000 Speaker 8: saying no to US technology when they have their own 191 00:10:06,120 --> 00:10:09,920 Speaker 8: local champions. But what I will say is we don't 192 00:10:10,000 --> 00:10:12,560 Speaker 8: know the exact number of AGE two hundreds China will 193 00:10:12,600 --> 00:10:15,240 Speaker 8: accept if any What we do know is they're clearly 194 00:10:15,280 --> 00:10:17,600 Speaker 8: not backing down on their commitment to their own chip 195 00:10:17,640 --> 00:10:20,040 Speaker 8: supply chain, and they're not going to readily give way 196 00:10:20,080 --> 00:10:23,720 Speaker 8: to this US strategy of selling advanced DAIDE chips in 197 00:10:23,840 --> 00:10:26,520 Speaker 8: order to undermine their local competitors. So we'll have to 198 00:10:26,520 --> 00:10:28,280 Speaker 8: wait and see what happens on h two hundreds. 199 00:10:29,280 --> 00:10:32,600 Speaker 3: Bloomberg's Maggie Eastland, who's been across China's chip efforts all 200 00:10:32,640 --> 00:10:35,400 Speaker 3: week long, thank you very much. Coming up, we're going 201 00:10:35,440 --> 00:10:37,920 Speaker 3: to get more on that breaking news report from Bloomberg 202 00:10:37,960 --> 00:10:42,640 Speaker 3: about Oracle delaying open AI specific data center project by 203 00:10:42,640 --> 00:10:44,640 Speaker 3: one year back to twenty twenty eight. It had an 204 00:10:44,679 --> 00:10:47,120 Speaker 3: impact on the markets, and as that one hundred is 205 00:10:47,160 --> 00:10:50,120 Speaker 3: now two percent actually Caroen as of Thursday night, the 206 00:10:50,160 --> 00:10:52,040 Speaker 3: state of play was the NAS that one hundred was 207 00:10:52,080 --> 00:10:54,200 Speaker 3: flat for the week, so we are now down two 208 00:10:54,240 --> 00:10:56,800 Speaker 3: percent on the NAS that one hundred or weekly basis. 209 00:10:56,840 --> 00:11:01,160 Speaker 3: Of course, the reaction to Broadcom and some other AI 210 00:11:01,600 --> 00:11:04,640 Speaker 3: angst is part of what's weighing on this market, and 211 00:11:04,679 --> 00:11:05,920 Speaker 3: we're going to go a lot more on that very 212 00:11:06,000 --> 00:11:06,400 Speaker 3: very soon. 213 00:11:06,440 --> 00:11:07,040 Speaker 2: Stay with us. 214 00:11:07,440 --> 00:11:24,280 Speaker 3: This is Bloomberg Tech okay shares Oracle down almost five percent. 215 00:11:24,280 --> 00:11:27,160 Speaker 3: They'd hit session loads of six point five percent decline 216 00:11:27,200 --> 00:11:30,520 Speaker 3: after Bloomberg's Brodi Ford broke the story that the firm 217 00:11:30,520 --> 00:11:33,880 Speaker 3: will be delaying data centers for open AI to twenty 218 00:11:33,920 --> 00:11:37,120 Speaker 3: twenty eight instead of a previously planned twenty twenty seven. 219 00:11:37,360 --> 00:11:41,880 Speaker 3: The reason labor and material shortages. Bluemo's Brody Ford runs 220 00:11:41,880 --> 00:11:44,600 Speaker 3: to set and joins us. Now important reporting for you 221 00:11:45,000 --> 00:11:49,079 Speaker 3: because this is what a part of Oracle's debate is. Okay, great, 222 00:11:49,120 --> 00:11:52,520 Speaker 3: you have a great backlog of business, but we are 223 00:11:52,800 --> 00:11:56,600 Speaker 3: very closely monitoring the ability to execute on it and 224 00:11:56,640 --> 00:11:58,640 Speaker 3: then book revenue on it. And open AI is a 225 00:11:58,640 --> 00:12:01,280 Speaker 3: big chunk of the exposure fill the banks for us. 226 00:12:01,320 --> 00:12:03,320 Speaker 3: More reporting, What are the details have you got? 227 00:12:03,960 --> 00:12:07,400 Speaker 9: These are unprecedented scale data centers, right, I mean, giggle 228 00:12:07,440 --> 00:12:10,600 Speaker 9: watse scale data centers unprecedented, and Oracles trying to do 229 00:12:10,640 --> 00:12:13,400 Speaker 9: effectively five and them at once. And so what we 230 00:12:13,480 --> 00:12:17,040 Speaker 9: have today is that the initial completion dates, the initial 231 00:12:17,120 --> 00:12:20,600 Speaker 9: full delivery dates have been pushed backed in some cases 232 00:12:20,640 --> 00:12:23,360 Speaker 9: from twenty seven to twenty eight. And you know, I 233 00:12:23,360 --> 00:12:25,800 Speaker 9: think if you've spoken with data center folks over the 234 00:12:25,880 --> 00:12:29,319 Speaker 9: last couple of months. It's not a huge shocker because 235 00:12:29,360 --> 00:12:32,120 Speaker 9: I mean, these are such crazy projects, right, and the 236 00:12:32,200 --> 00:12:34,600 Speaker 9: idea of getting them done in two years was always 237 00:12:34,640 --> 00:12:37,240 Speaker 9: going to be ambitious. So now getting them done by 238 00:12:37,280 --> 00:12:40,360 Speaker 9: twenty eight it's still a tight timeline. It's still, frankly 239 00:12:40,400 --> 00:12:43,280 Speaker 9: an impressive turnaround, but it's maybe just not as quick 240 00:12:43,320 --> 00:12:45,000 Speaker 9: as the company had initially hoped. 241 00:12:45,360 --> 00:12:48,280 Speaker 4: We're looking at Abelaine, Texas right now, where on the 242 00:12:48,320 --> 00:12:51,880 Speaker 4: conference call doing earnings we had the co CEO one 243 00:12:51,920 --> 00:12:53,840 Speaker 4: of them saying that they had more than ninety six 244 00:12:53,880 --> 00:12:56,880 Speaker 4: thousand in video chips delivered, giving you the sense of scale. 245 00:12:56,920 --> 00:13:01,360 Speaker 4: But is it a hindrance to what the revenue is 246 00:13:01,520 --> 00:13:05,000 Speaker 4: ultimately for Oracle here or is it just investors having 247 00:13:05,000 --> 00:13:07,960 Speaker 4: to be like, oh, it's still jammed tomorrow, not today. 248 00:13:08,559 --> 00:13:12,240 Speaker 9: Right, I mean, Oracle, I'm sure will say that as 249 00:13:12,240 --> 00:13:15,520 Speaker 9: you put they deliver these sites in chunks, right, And 250 00:13:15,559 --> 00:13:18,559 Speaker 9: so Abilene is already being turned on this massive data center. 251 00:13:18,440 --> 00:13:19,160 Speaker 2: In West Texas. 252 00:13:19,240 --> 00:13:22,120 Speaker 9: Once you get the servers running open, AI uses them, 253 00:13:22,320 --> 00:13:24,920 Speaker 9: that's revenue recognition, yeah, right, And so really what we're 254 00:13:24,960 --> 00:13:27,880 Speaker 9: thinking about is the further out sites beyond Abilene. 255 00:13:27,920 --> 00:13:28,040 Speaker 10: Right. 256 00:13:28,120 --> 00:13:32,679 Speaker 9: We keep seeing these Stargate announcements for Michigan and New Mexico. Right, 257 00:13:33,040 --> 00:13:35,360 Speaker 9: these sites which are still being kind of put together, 258 00:13:35,520 --> 00:13:38,760 Speaker 9: and Oracle and other vendors too are finding that, Wow, 259 00:13:38,840 --> 00:13:42,240 Speaker 9: there's a lot of stuff out there that's backlogged. 260 00:13:41,720 --> 00:13:42,600 Speaker 5: NAMA for one of them. 261 00:13:42,679 --> 00:13:45,319 Speaker 9: There's only so many electricians, right, I mean, you want 262 00:13:45,360 --> 00:13:48,439 Speaker 9: to build in rural Texas, it's a smaller pool of 263 00:13:48,480 --> 00:13:49,600 Speaker 9: people you have access to. 264 00:13:50,400 --> 00:13:52,800 Speaker 5: It's a fascinating story. It's going to run and run. 265 00:13:52,880 --> 00:13:55,680 Speaker 4: Blomberg's Brodie Ford with a real market moving bit of 266 00:13:55,679 --> 00:13:58,640 Speaker 4: reporting that. Let's talk more about the market implications. We've 267 00:13:58,640 --> 00:14:00,600 Speaker 4: got Margie Battel with us. You put any manager and 268 00:14:00,640 --> 00:14:03,760 Speaker 4: headed capital allocation of all Spring Global investments to have 269 00:14:03,800 --> 00:14:06,640 Speaker 4: six hundred twenty nine billion dollars an assets and advisement, 270 00:14:06,880 --> 00:14:11,479 Speaker 4: and Margie, you worried these drip drip bits of information 271 00:14:11,600 --> 00:14:14,120 Speaker 4: that maybe the revenue streams. 272 00:14:13,679 --> 00:14:15,120 Speaker 5: Aren't able to be booked tomorrow. 273 00:14:15,200 --> 00:14:16,840 Speaker 4: It has to be waited out a little bit more 274 00:14:16,880 --> 00:14:18,960 Speaker 4: in terms of the returns on AI investment. 275 00:14:21,400 --> 00:14:24,080 Speaker 11: No, I think the long term trends are still in place. 276 00:14:24,400 --> 00:14:27,800 Speaker 11: I actually thought that Broadcom's numbers were quite good and 277 00:14:27,800 --> 00:14:29,760 Speaker 11: people were just I think very nervous at the end 278 00:14:29,800 --> 00:14:32,960 Speaker 11: of the year, particularly with some bad news we've seen, 279 00:14:33,000 --> 00:14:36,040 Speaker 11: such as from Oracle, and I think it's really more 280 00:14:36,200 --> 00:14:39,520 Speaker 11: just end of your jitters rather than anything fundamental. I 281 00:14:39,520 --> 00:14:41,480 Speaker 11: think when you look out into twenty twenty six, you 282 00:14:41,520 --> 00:14:45,080 Speaker 11: still have to like the tech sector, especially the semi 283 00:14:45,160 --> 00:14:48,480 Speaker 11: the memory those companies. I think you still have to 284 00:14:48,480 --> 00:14:50,240 Speaker 11: stick with them, that there are to continue to be 285 00:14:50,640 --> 00:14:54,800 Speaker 11: high growers, and these little hiccups we have here and 286 00:14:54,840 --> 00:14:58,280 Speaker 11: there don't change the fundamental trend of very very strong 287 00:14:58,320 --> 00:15:00,120 Speaker 11: growth in a year, which would be very much lot 288 00:15:00,160 --> 00:15:03,000 Speaker 11: of growth next year. So we still like the whole sector. 289 00:15:03,240 --> 00:15:05,160 Speaker 4: So Maggie, on a day where BRAUN comes up by 290 00:15:05,160 --> 00:15:07,280 Speaker 4: eleven percent when the nasdak's off by two percent, is 291 00:15:07,280 --> 00:15:08,720 Speaker 4: that hacup a buying opportunity? 292 00:15:11,400 --> 00:15:13,440 Speaker 11: Well, I think it is actually because if you look 293 00:15:13,480 --> 00:15:16,000 Speaker 11: at the leading stocks that have stuck to their plan, 294 00:15:16,120 --> 00:15:20,520 Speaker 11: that have great growth, great profit margins, great innovation, and 295 00:15:20,840 --> 00:15:23,640 Speaker 11: they're down ten to fifteen, even twenty percent from their 296 00:15:23,640 --> 00:15:25,720 Speaker 11: peaks of a few months ago. So I think that 297 00:15:25,800 --> 00:15:28,960 Speaker 11: looks like a pretty attractive time to add to these names. 298 00:15:29,000 --> 00:15:31,280 Speaker 11: Because there's end of your uncertainty, a lot of short 299 00:15:31,360 --> 00:15:35,520 Speaker 11: term traders who preserve their games cash out, And I 300 00:15:35,560 --> 00:15:37,800 Speaker 11: think that's what you're seeing, is this pressure on the 301 00:15:37,840 --> 00:15:40,960 Speaker 11: sector rather than the change in the fundamentals the cash flow. 302 00:15:41,040 --> 00:15:42,040 Speaker 5: The big companies are so. 303 00:15:42,120 --> 00:15:45,880 Speaker 11: Large, this isn't going to be derailed anytime soon. So 304 00:15:45,920 --> 00:15:47,520 Speaker 11: I think next year looks pretty good. 305 00:15:47,560 --> 00:15:50,760 Speaker 2: Sailing too, Margie, It's good to see you. 306 00:15:50,840 --> 00:15:53,360 Speaker 3: It sounds like at your end you don't personally have 307 00:15:53,480 --> 00:15:56,120 Speaker 3: many jitters. One of the best read stories on the 308 00:15:56,120 --> 00:15:59,960 Speaker 3: Bloomberg Ternal today is about the debt and the lens 309 00:16:00,600 --> 00:16:05,080 Speaker 3: that is behind the build out in that infrastructure, where 310 00:16:05,600 --> 00:16:09,440 Speaker 3: the debt does debt as a factor in consideration sit 311 00:16:09,520 --> 00:16:12,280 Speaker 3: for you when you are tracking all sorts of different 312 00:16:12,640 --> 00:16:14,960 Speaker 3: hard and soft data sets to work out what's going 313 00:16:14,960 --> 00:16:15,440 Speaker 3: on here. 314 00:16:17,600 --> 00:16:19,920 Speaker 11: Well, I look at the debt as really a company's 315 00:16:20,000 --> 00:16:22,200 Speaker 11: choice of how they want to allocate capital. Do they 316 00:16:22,240 --> 00:16:25,440 Speaker 11: want to borrow, do they want to increase the dividend, 317 00:16:25,440 --> 00:16:28,720 Speaker 11: do they want to do share buybacks? And particularly the 318 00:16:28,840 --> 00:16:32,920 Speaker 11: large successful companies really have no need to borrow. Even 319 00:16:33,320 --> 00:16:35,880 Speaker 11: paying for the CAPPAC, they still have plenty of excess 320 00:16:35,920 --> 00:16:39,240 Speaker 11: cash flow that they have to decide how to utilize. 321 00:16:39,880 --> 00:16:43,560 Speaker 11: Whereas I think Oracle has really taken on a lot 322 00:16:43,600 --> 00:16:45,920 Speaker 11: of debt compared to their cash flow, But the rest 323 00:16:45,960 --> 00:16:47,120 Speaker 11: I think all look pretty good. 324 00:16:47,360 --> 00:16:48,320 Speaker 2: It's a vital. 325 00:16:48,080 --> 00:16:50,640 Speaker 11: Sector and that's why the returns are higher, because you 326 00:16:50,680 --> 00:16:53,480 Speaker 11: have to be prepared for these little down drafts in 327 00:16:53,600 --> 00:16:55,239 Speaker 11: order to get the upside. 328 00:16:56,120 --> 00:17:00,000 Speaker 3: Maggie Brodie's report and Oracle was very specific that Oracles 329 00:17:00,120 --> 00:17:03,520 Speaker 3: delaying those projects by a year because of labor and 330 00:17:03,560 --> 00:17:07,679 Speaker 3: material shortages elsewhere in the US economy. We have all 331 00:17:07,720 --> 00:17:10,399 Speaker 3: the chips we need, clearly, are we good at the 332 00:17:10,400 --> 00:17:12,760 Speaker 3: other stuff? And is the other stuff where it needs 333 00:17:12,760 --> 00:17:14,440 Speaker 3: to be to support this build out? 334 00:17:17,200 --> 00:17:18,919 Speaker 11: Yes, I think it is. I think when you have 335 00:17:19,040 --> 00:17:22,720 Speaker 11: this explosion in demand of these very complex centers, I 336 00:17:22,720 --> 00:17:26,320 Speaker 11: think you should expect there will be short term problems 337 00:17:26,320 --> 00:17:29,360 Speaker 11: of supply and so forth. But really that's a good 338 00:17:29,359 --> 00:17:32,400 Speaker 11: problem to have rather than lack of demand or pricing pressure. 339 00:17:32,440 --> 00:17:36,160 Speaker 11: And we're really seeing very strong pricing for the summaris 340 00:17:36,160 --> 00:17:39,080 Speaker 11: that are going into the data centers, so we think 341 00:17:39,119 --> 00:17:42,280 Speaker 11: it's just nothing to worry about, and the fundamentals are 342 00:17:42,280 --> 00:17:43,240 Speaker 11: still very strong. 343 00:17:43,840 --> 00:17:47,199 Speaker 4: Briefly though, there's reports today from other outlets saying that 344 00:17:47,240 --> 00:17:48,920 Speaker 4: Dell's going to have to Jack of its prices because 345 00:17:48,960 --> 00:17:51,879 Speaker 4: of pricing and strength and memory. Are there areas of 346 00:17:51,880 --> 00:17:54,320 Speaker 4: this AI trade that are overvalued that you shouldn't be 347 00:17:54,359 --> 00:17:56,440 Speaker 4: piling into From a margin perspective. 348 00:17:58,359 --> 00:17:59,879 Speaker 11: Well, I think when you look at check it's like 349 00:18:00,119 --> 00:18:03,959 Speaker 11: any other sector. Is the best companies usually trade rather richly. 350 00:18:04,320 --> 00:18:06,920 Speaker 11: The cheap companies usually have problems. They don't have the 351 00:18:07,000 --> 00:18:09,480 Speaker 11: leading edge, they don't have the innovation. And when you 352 00:18:09,520 --> 00:18:11,320 Speaker 11: look at chech it's just and you can see even 353 00:18:11,359 --> 00:18:14,879 Speaker 11: here with the data centers and concern about what approach 354 00:18:14,960 --> 00:18:18,960 Speaker 11: that companies are using Broadcom or nvideo whatever in the 355 00:18:19,000 --> 00:18:21,720 Speaker 11: new products. It's really about innovation and who are the 356 00:18:21,800 --> 00:18:24,480 Speaker 11: leading innovators, and so the companies that don't have that 357 00:18:24,560 --> 00:18:26,840 Speaker 11: innovation are just going to fall behind. So I think 358 00:18:27,240 --> 00:18:30,640 Speaker 11: this year up till say the summer, everything moved up 359 00:18:30,920 --> 00:18:33,600 Speaker 11: and now we're seeing a separation between the companies that 360 00:18:34,200 --> 00:18:36,480 Speaker 11: have leading edge and the companies that are really falling 361 00:18:36,480 --> 00:18:38,120 Speaker 11: behind and aren't going to catch up. So I think 362 00:18:38,119 --> 00:18:41,040 Speaker 11: it'll be much more stock selection next year than we've 363 00:18:41,040 --> 00:18:42,680 Speaker 11: had for the first part of this year. 364 00:18:43,280 --> 00:18:46,040 Speaker 3: With a message that in tech there's nothing to worry about. 365 00:18:46,359 --> 00:18:49,000 Speaker 3: Margie Patel from all Spring Global Investments. Great to have 366 00:18:49,040 --> 00:18:49,840 Speaker 3: you back on the show. 367 00:18:50,200 --> 00:18:51,040 Speaker 2: Thank you very much. 368 00:18:51,119 --> 00:18:53,480 Speaker 3: Now coming up, we're going to bring you Bloomberg's exclusive 369 00:18:53,520 --> 00:18:58,600 Speaker 3: conversation with Uber's CEO and the company's international ambitions, particular 370 00:18:58,680 --> 00:18:59,760 Speaker 3: focus on Asia. 371 00:19:00,240 --> 00:19:02,200 Speaker 2: Next this is Bloomberg Tech. 372 00:19:08,080 --> 00:19:09,520 Speaker 5: Ouba si Jari Koswa. 373 00:19:09,560 --> 00:19:12,840 Speaker 4: Shahi says the company expects to offer robotaxi services in 374 00:19:12,880 --> 00:19:14,880 Speaker 4: more than ten markets by the end of next year. 375 00:19:15,160 --> 00:19:17,560 Speaker 5: He spoke with Bloomberg Tech Asia's Annabel. 376 00:19:17,320 --> 00:19:20,960 Speaker 4: Druders about why he's optimistic, in particular about growth potentially in. 377 00:19:20,920 --> 00:19:25,760 Speaker 12: Asia, the APAC market and in particular the North Asia 378 00:19:25,840 --> 00:19:29,520 Speaker 12: markets as well. They are huge growth markets for us, 379 00:19:29,680 --> 00:19:32,000 Speaker 12: and if you look, for example, in the ride share business, 380 00:19:32,560 --> 00:19:36,280 Speaker 12: over thirty percent of our global first trips coming into 381 00:19:36,359 --> 00:19:42,520 Speaker 12: the category come from the Apac region. The area is 382 00:19:42,560 --> 00:19:45,879 Speaker 12: growing very quickly, including taxi as well, which is actually 383 00:19:45,880 --> 00:19:49,240 Speaker 12: one of our newest products on the platform. So for 384 00:19:49,359 --> 00:19:53,320 Speaker 12: me coming here, seeing the teams, meeting with local business 385 00:19:53,320 --> 00:19:57,359 Speaker 12: people and regulators and talking about how we can be 386 00:19:57,440 --> 00:19:59,960 Speaker 12: part of the future growth of the region is really 387 00:20:00,040 --> 00:20:00,760 Speaker 12: what my agenda is. 388 00:20:01,560 --> 00:20:03,920 Speaker 13: Early this year, you also put out a statement on 389 00:20:04,720 --> 00:20:08,200 Speaker 13: the robot taxi push as well, and so the Middle 390 00:20:08,200 --> 00:20:11,359 Speaker 13: East and Asia were the markets for twenty twenty five 391 00:20:11,480 --> 00:20:13,880 Speaker 13: to launch, and we've seen of course that initial deployment 392 00:20:13,880 --> 00:20:18,760 Speaker 13: in the Middle East already. What's happening on the Asia side, well, lots. 393 00:20:18,480 --> 00:20:21,920 Speaker 12: Of discussions on the Asia side. I think what's really 394 00:20:21,960 --> 00:20:26,320 Speaker 12: important is to set up a regulatory framework to go forward. 395 00:20:27,119 --> 00:20:30,199 Speaker 12: For example, Hong Kong has various trials and pilots going on, 396 00:20:30,280 --> 00:20:33,520 Speaker 12: and in many other markets we're talking to regulators about 397 00:20:33,560 --> 00:20:36,600 Speaker 12: how we can be a part of shaping right share 398 00:20:36,640 --> 00:20:40,280 Speaker 12: and autonomous right shair going forward. The technology is absolutely 399 00:20:40,320 --> 00:20:44,160 Speaker 12: getting there. These are the robot driver. It doesn't get tired, 400 00:20:44,520 --> 00:20:48,359 Speaker 12: doesn't get distracted, and we very much look forward to 401 00:20:48,760 --> 00:20:53,080 Speaker 12: working with various authorities to introduce right shair into the 402 00:20:53,119 --> 00:20:56,399 Speaker 12: markets we're now live in for markets now as we 403 00:20:56,440 --> 00:21:00,359 Speaker 12: speak in the US and in the Middle East to 404 00:21:00,400 --> 00:21:05,080 Speaker 12: be in ten plus markets by next year, and we 405 00:21:05,119 --> 00:21:07,080 Speaker 12: want those markets to be in the Asia Pacific region 406 00:21:07,080 --> 00:21:07,480 Speaker 12: as well. 407 00:21:08,000 --> 00:21:10,080 Speaker 13: Where then in Asia do you think is the most 408 00:21:10,200 --> 00:21:11,400 Speaker 13: likely place. 409 00:21:11,520 --> 00:21:16,760 Speaker 12: We'll see I think that certainly Japan has great potential, 410 00:21:17,760 --> 00:21:18,320 Speaker 12: you know, with. 411 00:21:18,400 --> 00:21:20,560 Speaker 5: They behind on their regulation. 412 00:21:20,480 --> 00:21:22,399 Speaker 12: They are behind in their regulation, but I think that 413 00:21:22,440 --> 00:21:27,000 Speaker 12: they also understand that with an aging population. There's a 414 00:21:27,080 --> 00:21:30,680 Speaker 12: real need for transportation, not just in the large cities, 415 00:21:30,720 --> 00:21:31,160 Speaker 12: but in. 416 00:21:31,119 --> 00:21:32,160 Speaker 2: The rural areas. 417 00:21:32,520 --> 00:21:35,439 Speaker 12: And for example, I experienced that personally going to Kaga 418 00:21:35,440 --> 00:21:39,120 Speaker 12: City and where we have communal ride share and kind 419 00:21:39,119 --> 00:21:41,719 Speaker 12: of took a ride share trip and understood what the 420 00:21:41,760 --> 00:21:46,040 Speaker 12: needs are there. So we're talking with various countries regulatory authorities. 421 00:21:46,080 --> 00:21:47,760 Speaker 12: I think Japan is going to be part of it. 422 00:21:47,880 --> 00:21:49,720 Speaker 12: I certainly hope that Hong Kong is going to be 423 00:21:49,720 --> 00:21:52,760 Speaker 12: a part of it. Australia, where we were just talking about, 424 00:21:52,920 --> 00:21:55,440 Speaker 12: is a huge market for us. So we're having those 425 00:21:55,480 --> 00:21:59,800 Speaker 12: dialogues and I think that the picture will shape up 426 00:22:00,000 --> 00:22:02,400 Speaker 12: over the next two years because the technology is definitely 427 00:22:02,400 --> 00:22:02,960 Speaker 12: getting there. 428 00:22:03,600 --> 00:22:06,760 Speaker 3: Uber CEO Dara Kostrashahi there along with our animl drawers 429 00:22:06,760 --> 00:22:09,439 Speaker 3: and aw sticking with Uber. The company, along with door Dash, 430 00:22:09,600 --> 00:22:13,000 Speaker 3: is suing New York City to block requirements that the 431 00:22:13,040 --> 00:22:16,640 Speaker 3: delivery tipping option be available at the time of checkout 432 00:22:16,880 --> 00:22:19,520 Speaker 3: and set to at least ten percent. The two companies 433 00:22:19,640 --> 00:22:23,880 Speaker 3: argue this would worsen sticker shock for inflation weary consumers. 434 00:22:24,200 --> 00:22:25,480 Speaker 2: New tipping laws. 435 00:22:25,200 --> 00:22:27,800 Speaker 3: Are set to become effective January twenty sixth carrot. 436 00:22:27,840 --> 00:22:28,480 Speaker 5: I want to watch it. 437 00:22:28,600 --> 00:22:32,280 Speaker 4: Meanwhile, coming up, you're reporting to watch how Rivian is 438 00:22:32,320 --> 00:22:37,040 Speaker 4: replacing invideos tech in future vehicles with its own chips. 439 00:22:37,400 --> 00:22:40,080 Speaker 4: From New York, From San Francisco, this is Bloomberg Tech. 440 00:23:00,640 --> 00:23:02,200 Speaker 2: Welcome back to Bloomberg Tech. 441 00:23:02,520 --> 00:23:06,600 Speaker 3: Rivian take a look at its shares up currently sixteen 442 00:23:06,680 --> 00:23:09,680 Speaker 3: percent at one point in the session, up more than 443 00:23:09,760 --> 00:23:13,000 Speaker 3: nineteen percent, trading at its highest level since January of 444 00:23:13,080 --> 00:23:16,159 Speaker 3: twenty twenty four, so its highest level in two years. 445 00:23:16,560 --> 00:23:19,880 Speaker 3: Yesterday it fell quite a lot after it told investors 446 00:23:20,119 --> 00:23:24,400 Speaker 3: and the world its plans for autonomous driving. Rivian's plan 447 00:23:24,760 --> 00:23:28,760 Speaker 3: for autonomous driving is based on two big technology bets, 448 00:23:29,040 --> 00:23:34,720 Speaker 3: and we went to see them. Rivian's developed its own 449 00:23:34,760 --> 00:23:39,680 Speaker 3: artificial intelligence chip for its future cars that gamble might 450 00:23:39,800 --> 00:23:45,919 Speaker 3: pave the way to fully autonomous driving. A lot of 451 00:23:45,920 --> 00:23:48,320 Speaker 3: the tech world imagines a future where we don't own 452 00:23:48,440 --> 00:23:51,480 Speaker 3: cars at all. We're talking about fleets of robotaxis that 453 00:23:51,520 --> 00:23:54,200 Speaker 3: are summoned through an app, maybe no steering wheel or 454 00:23:54,240 --> 00:23:57,040 Speaker 3: driver controls at all. But Rivian's in the camp that 455 00:23:57,200 --> 00:23:59,520 Speaker 3: does see people owning their own cars in the future 456 00:23:59,560 --> 00:24:02,200 Speaker 3: and being willing to pay top dollar for a software 457 00:24:02,240 --> 00:24:05,720 Speaker 3: platform that allows the car to drive itself. If this 458 00:24:05,840 --> 00:24:10,080 Speaker 3: idea seems familiar, Tesla has been selling a version of 459 00:24:10,119 --> 00:24:11,000 Speaker 3: it for years. 460 00:24:11,440 --> 00:24:13,400 Speaker 2: Full self driving supervised is not. 461 00:24:13,520 --> 00:24:16,320 Speaker 3: Technically full autonomy if you read the fine print, but 462 00:24:16,400 --> 00:24:18,680 Speaker 3: it can get you from point A to point B 463 00:24:19,240 --> 00:24:20,560 Speaker 3: without needing to put. 464 00:24:20,400 --> 00:24:21,760 Speaker 2: Your hands on the steering wheel. 465 00:24:25,320 --> 00:24:28,360 Speaker 3: Rivian's path to autonomy is rooted in two big bets. 466 00:24:28,400 --> 00:24:32,320 Speaker 3: The first a custom AI chip developed in house, which 467 00:24:32,359 --> 00:24:34,960 Speaker 3: marks a big break from Nvidia. 468 00:24:35,119 --> 00:24:37,960 Speaker 14: This is a wrap one chip, it's a multitip module. 469 00:24:38,440 --> 00:24:41,520 Speaker 14: In the middle is a Rivian design custom silicon surrounded 470 00:24:41,560 --> 00:24:45,080 Speaker 14: by memory on two sides. The decision to build an 471 00:24:45,080 --> 00:24:48,560 Speaker 14: in house was based on a very rigorous analysis of 472 00:24:48,720 --> 00:24:51,359 Speaker 14: the benefits we could come and those benefits are velocity 473 00:24:51,480 --> 00:24:53,920 Speaker 14: or ability to get to market, break quickly with it, 474 00:24:54,040 --> 00:24:55,119 Speaker 14: performance and cost. 475 00:24:55,760 --> 00:24:59,640 Speaker 3: The second a major change in how Rivian vehicles see 476 00:24:59,680 --> 00:25:02,879 Speaker 3: the world. The next generation Rivian R two will have 477 00:25:03,000 --> 00:25:05,480 Speaker 3: indented lidar sensors in it. 478 00:25:05,480 --> 00:25:07,840 Speaker 14: It's not just about the computer, it's also about the 479 00:25:07,880 --> 00:25:10,119 Speaker 14: sensors and it's about how they all come together. 480 00:25:12,400 --> 00:25:15,160 Speaker 15: This is really in mark one what the Gen three 481 00:25:15,240 --> 00:25:19,080 Speaker 15: architecture does with compute levels that are dramatically expanded, such 482 00:25:19,080 --> 00:25:21,760 Speaker 15: as to put some numbers to this at the platform level, 483 00:25:21,840 --> 00:25:25,160 Speaker 15: sixteen hundred sparse tops where you can process five billion 484 00:25:25,200 --> 00:25:29,400 Speaker 15: pixels per second, beautifully integreated lightar that raises the ceiling 485 00:25:29,440 --> 00:25:31,640 Speaker 15: to allow us to take your eyes off the road. 486 00:25:32,640 --> 00:25:34,240 Speaker 2: This will cause some debate. 487 00:25:35,119 --> 00:25:39,240 Speaker 3: Tesla vehicles only use cameras as sensors for their systems, 488 00:25:39,280 --> 00:25:42,639 Speaker 3: and what Elon Musk company has always argued is that 489 00:25:42,720 --> 00:25:47,640 Speaker 3: other sensors like lidar or radar are too expensive to scale. 490 00:25:48,080 --> 00:25:50,560 Speaker 3: Until now, Rivian didn't really have an autonomous system. It 491 00:25:50,640 --> 00:25:54,480 Speaker 3: had advanced driver assistance tools powered by cameras and radar, 492 00:25:54,800 --> 00:25:57,679 Speaker 3: and Rivian used Nvidia chips as the brain in the 493 00:25:57,760 --> 00:26:01,040 Speaker 3: vehicle to interpret the world around it. Rivian says it's 494 00:26:01,160 --> 00:26:04,360 Speaker 3: new AI model will keep improving those older cars too, 495 00:26:04,480 --> 00:26:08,400 Speaker 3: eventually adding capabilities like hands off point to point driving. 496 00:26:08,840 --> 00:26:11,560 Speaker 3: Rivian doing its own chip and ditching in Nvidia is 497 00:26:11,560 --> 00:26:12,560 Speaker 3: a surprise. 498 00:26:12,600 --> 00:26:16,600 Speaker 15: On the Rivian processor side. This represents a significant cost 499 00:26:16,640 --> 00:26:19,040 Speaker 15: savings to us. There is a lot of margin, of 500 00:26:19,080 --> 00:26:22,880 Speaker 15: course in the in the semiconductor space, and working directly 501 00:26:22,920 --> 00:26:25,320 Speaker 15: with PSMC, we have a great relationship with them. 502 00:26:25,680 --> 00:26:28,760 Speaker 3: The new hardware is the unlock. It should allow Rivian 503 00:26:28,760 --> 00:26:31,800 Speaker 3: to go from that driver assistance software in its existing 504 00:26:31,840 --> 00:26:34,960 Speaker 3: lineup to true autonomy in the next gen R two. 505 00:26:35,240 --> 00:26:37,800 Speaker 15: And the next big step is personal level for it. 506 00:26:37,800 --> 00:26:40,000 Speaker 15: And what I mean is the vehicle can operate empty, 507 00:26:40,359 --> 00:26:42,639 Speaker 15: it can operate without anyone in the driver's seat. It 508 00:26:42,680 --> 00:26:45,080 Speaker 15: can pick your kids up from school, it can drop 509 00:26:45,119 --> 00:26:47,440 Speaker 15: you at the airport. It's a complete shift in how 510 00:26:47,440 --> 00:26:49,240 Speaker 15: we think about the vehicle experience. 511 00:26:51,040 --> 00:26:53,560 Speaker 3: Looking back, this was the company that pulled off the 512 00:26:53,600 --> 00:26:56,800 Speaker 3: sixth largest IPO in US history, and it was first 513 00:26:56,800 --> 00:26:59,960 Speaker 3: to market with full size battery electric pickups and sau 514 00:27:00,920 --> 00:27:05,720 Speaker 3: beating out Tesla, Forward and General Motors. But today Rivian 515 00:27:05,760 --> 00:27:09,880 Speaker 3: struggling with the basics. Production of its evs hasn't really scaled. 516 00:27:10,320 --> 00:27:13,679 Speaker 3: Rivian Soul plant in Illinois is capable of building two 517 00:27:13,800 --> 00:27:16,600 Speaker 3: hundred and fifty thousand units a year, but in twenty 518 00:27:16,640 --> 00:27:20,320 Speaker 3: twenty five it probably won't hit fifty thousand. The truest 519 00:27:20,400 --> 00:27:23,439 Speaker 3: representation of that struggle, the stock is at a fraction 520 00:27:23,560 --> 00:27:24,480 Speaker 3: of its peak. 521 00:27:26,920 --> 00:27:27,280 Speaker 2: Right now. 522 00:27:27,280 --> 00:27:29,280 Speaker 3: In the world of tech, you have to have something 523 00:27:29,320 --> 00:27:32,120 Speaker 3: to say about AI, and Rivian is diving deep into 524 00:27:32,160 --> 00:27:37,240 Speaker 3: autonomy to appease its investors, an ai chiplidar and a 525 00:27:37,320 --> 00:27:40,280 Speaker 3: large driving model right now. It's a promise from Rivian 526 00:27:40,640 --> 00:27:46,280 Speaker 3: that their next generation vehicles will have genuine autonomous capabilities. 527 00:27:48,760 --> 00:27:51,600 Speaker 4: Extraordin and reporting deep dive and Rivian, as you said, 528 00:27:51,720 --> 00:27:54,440 Speaker 4: ed doing very well on the day, unlike the rest 529 00:27:54,480 --> 00:27:56,960 Speaker 4: of the markets. Just check in what's happening to the Nasdak. 530 00:27:57,000 --> 00:27:58,200 Speaker 4: We're down on the week, We were down on the 531 00:27:58,280 --> 00:27:59,600 Speaker 4: day and as at one hundred, off by more than 532 00:27:59,600 --> 00:28:01,960 Speaker 4: two percent andach points tech in the line of fire 533 00:28:02,000 --> 00:28:04,760 Speaker 4: today even dragging Chinese names now into the red. They 534 00:28:04,840 --> 00:28:07,760 Speaker 4: started the trade and our show in the green as 535 00:28:07,760 --> 00:28:09,760 Speaker 4: we understood that the Chinese government was going to be 536 00:28:09,760 --> 00:28:13,520 Speaker 4: going all in on funding its own domestic chips apply 537 00:28:13,680 --> 00:28:17,080 Speaker 4: up to seventy billion dollars worth of government incentives, is 538 00:28:17,119 --> 00:28:20,120 Speaker 4: the reporting coming out of Bloomberg News at the moment. 539 00:28:20,200 --> 00:28:22,600 Speaker 4: But even China starts to dip at the moment. We 540 00:28:22,640 --> 00:28:26,160 Speaker 4: see Broadcom in the video in the red, Pallanteer, Amazon, Micron, 541 00:28:26,440 --> 00:28:29,399 Speaker 4: some key names currently on the downside as we have 542 00:28:29,440 --> 00:28:31,280 Speaker 4: that AI bubble anxiety all over again. 543 00:28:32,040 --> 00:28:35,280 Speaker 3: Right coming up, actually, Caro, we're going to talk about 544 00:28:35,320 --> 00:28:37,679 Speaker 3: the United Kingdom. We're going to be joined by British 545 00:28:37,760 --> 00:28:40,840 Speaker 3: Business Bank CEO Lewis Taylor for his take on the 546 00:28:40,920 --> 00:28:44,200 Speaker 3: UK's tech sector. He's in town in San Francisco and 547 00:28:44,200 --> 00:28:48,120 Speaker 3: Silicon Valley to think about how technology might work across 548 00:28:48,160 --> 00:28:48,760 Speaker 3: the Atlantic. 549 00:28:48,880 --> 00:28:50,720 Speaker 2: That's next, This is Sploomberg Tech. 550 00:28:59,840 --> 00:29:02,719 Speaker 3: The UK economy is at risk of its first coarsely 551 00:29:02,800 --> 00:29:07,720 Speaker 3: contraction since labor returned to power after growth, disappointed again 552 00:29:07,720 --> 00:29:10,600 Speaker 3: by shrinking ahead of Chancellor of the Exchequer Rachel Reeves's 553 00:29:10,720 --> 00:29:15,080 Speaker 3: tax raising budget. Can the UK tech sector come to 554 00:29:15,120 --> 00:29:18,680 Speaker 3: the rescue? Louis Taylor, CEO of the British Business Bank, 555 00:29:18,760 --> 00:29:20,880 Speaker 3: joins us now and it's great to have you in 556 00:29:20,920 --> 00:29:22,440 Speaker 3: town in San Francisco. 557 00:29:23,120 --> 00:29:24,680 Speaker 16: Really great to be here, ed, thank you very much. 558 00:29:24,720 --> 00:29:30,120 Speaker 3: Indeed, you have an annual budget essentially to invest in 559 00:29:30,960 --> 00:29:35,160 Speaker 3: and lend to and support the technology industry in the 560 00:29:35,240 --> 00:29:37,200 Speaker 3: United Kingdom. 561 00:29:37,440 --> 00:29:38,600 Speaker 2: Why are you in San Francisco? 562 00:29:38,640 --> 00:29:38,800 Speaker 11: Then? 563 00:29:38,840 --> 00:29:40,560 Speaker 2: What brings you in San Francisco? 564 00:29:40,800 --> 00:29:44,080 Speaker 16: Well, look, we're here pitching to us VC's a really 565 00:29:44,120 --> 00:29:47,000 Speaker 16: great new growth opportunity for them, which is based on 566 00:29:47,040 --> 00:29:49,160 Speaker 16: three things. Firstly, as you say, the quality of the 567 00:29:49,280 --> 00:29:53,280 Speaker 16: UK tech industry for the top ten universities globally producing 568 00:29:53,320 --> 00:29:58,440 Speaker 16: great research with some really excellent entrepreneurs and the ability 569 00:29:58,480 --> 00:30:02,040 Speaker 16: to scale businesses as well. So that's where they come in. Secondly, 570 00:30:02,440 --> 00:30:04,880 Speaker 16: a new pool of capital coming on stream domestically in 571 00:30:04,920 --> 00:30:07,560 Speaker 16: the UK from pension funds hopefully. And then thirdly the 572 00:30:07,600 --> 00:30:09,680 Speaker 16: opportunity to partner with the bank, which is the biggest 573 00:30:09,800 --> 00:30:13,160 Speaker 16: LP in UK venture and growth equity connected and knowing 574 00:30:13,200 --> 00:30:14,640 Speaker 16: the landscape pretty well. 575 00:30:14,840 --> 00:30:17,520 Speaker 5: Luis the landscape we know so well? Is fintech? 576 00:30:17,880 --> 00:30:20,480 Speaker 4: I think of Revolute, I think a Monso the standouts. 577 00:30:20,640 --> 00:30:23,040 Speaker 4: But where else is really thriving? Where else should VC 578 00:30:23,120 --> 00:30:24,280 Speaker 4: come in as port in the UK? 579 00:30:25,640 --> 00:30:28,240 Speaker 16: Well, look, I think you're absolutely right. Fintech is very strong. 580 00:30:28,280 --> 00:30:32,240 Speaker 16: And just today Go Cardless did a deal with Molly 581 00:30:32,760 --> 00:30:35,560 Speaker 16: and that a unicorn that we invested in twelve years ago. 582 00:30:35,600 --> 00:30:37,400 Speaker 16: So you need a bit of patience on this. So 583 00:30:37,440 --> 00:30:41,480 Speaker 16: fintech's very strong. AI in different places is very strong. 584 00:30:41,560 --> 00:30:43,320 Speaker 16: Not so much on the hardware side, not so much 585 00:30:43,360 --> 00:30:46,280 Speaker 16: on the larger language models, but more broadly, if I 586 00:30:46,280 --> 00:30:49,920 Speaker 16: think about companies like Synthesia or eleven Labs, all of 587 00:30:49,960 --> 00:30:53,360 Speaker 16: those companies coming out of the UK, So I think 588 00:30:53,400 --> 00:30:56,120 Speaker 16: those tech areas are great, but also the application of 589 00:30:56,200 --> 00:30:59,640 Speaker 16: AI into life sciences is incredibly strong as well, and 590 00:30:59,680 --> 00:31:03,720 Speaker 16: the UK has an incredibly strong life sciences industry. So 591 00:31:04,240 --> 00:31:07,360 Speaker 16: I think we see AI as being a theme across 592 00:31:07,400 --> 00:31:10,320 Speaker 16: the sectors of the industrial strategy the government announced and 593 00:31:10,360 --> 00:31:11,800 Speaker 16: the UK being strong in those. 594 00:31:12,360 --> 00:31:14,840 Speaker 3: To be fair, many of those companies you name, you know, 595 00:31:15,040 --> 00:31:17,479 Speaker 3: they come on this program regularly, you know, and they 596 00:31:17,480 --> 00:31:19,920 Speaker 3: are making advancements in their respective fields. 597 00:31:20,000 --> 00:31:21,040 Speaker 2: We want to go back to what you. 598 00:31:20,920 --> 00:31:24,000 Speaker 3: Said, the big pot of pool of money coming online 599 00:31:24,320 --> 00:31:27,120 Speaker 3: a little bit more. Please, Yeah, how big? How certain 600 00:31:27,200 --> 00:31:31,800 Speaker 3: is it? And that's important right because the lesson of 601 00:31:31,800 --> 00:31:36,440 Speaker 3: AI in this country at least is the capital requirements 602 00:31:36,480 --> 00:31:37,440 Speaker 3: are much bigger. 603 00:31:37,240 --> 00:31:37,800 Speaker 2: Much bigger. 604 00:31:38,080 --> 00:31:41,200 Speaker 16: So the UK we incubate companies incredibly well, we scale 605 00:31:41,200 --> 00:31:43,239 Speaker 16: them less well, and we haven't had the scale up 606 00:31:43,280 --> 00:31:45,280 Speaker 16: capital we need. It's not that we don't have the money, 607 00:31:45,280 --> 00:31:47,960 Speaker 16: because we have the second largest funded pension scheme in 608 00:31:48,000 --> 00:31:50,560 Speaker 16: the world at around four trillion pounds, but we have 609 00:31:50,560 --> 00:31:54,680 Speaker 16: an allocation issue with that pension money, which is changing 610 00:31:54,720 --> 00:31:57,560 Speaker 16: the government encouraging pension funds to invest more in the 611 00:31:57,560 --> 00:32:00,400 Speaker 16: domestic economy and in the growth economy. I think what 612 00:32:00,440 --> 00:32:02,720 Speaker 16: we're looking for is some of the expertise here in 613 00:32:02,760 --> 00:32:05,560 Speaker 16: the VC industry in the US about scaling those companies. 614 00:32:05,800 --> 00:32:08,040 Speaker 16: As I say, we incubate well, but it's that scaling 615 00:32:08,080 --> 00:32:10,400 Speaker 16: stage and the expertise needed there where. Of course you 616 00:32:10,440 --> 00:32:13,120 Speaker 16: need capital, but you need other things as well, network's 617 00:32:13,640 --> 00:32:18,240 Speaker 16: capabilities and many other things. Mentoring of leadership teams. 618 00:32:18,480 --> 00:32:22,280 Speaker 4: Luis what is the state of brain drain when you 619 00:32:22,360 --> 00:32:25,200 Speaker 4: actually do get a really successful company. Now, eleven labs 620 00:32:25,200 --> 00:32:27,680 Speaker 4: are staying there since these years as well, but many 621 00:32:27,840 --> 00:32:30,160 Speaker 4: up and even come to Silicon Valley or to the US. 622 00:32:30,280 --> 00:32:31,440 Speaker 5: Is that something that's still happening. 623 00:32:32,440 --> 00:32:34,200 Speaker 16: Well, look, I think it does happen to an extent. 624 00:32:34,280 --> 00:32:36,520 Speaker 16: I think we really want to try and address that 625 00:32:36,560 --> 00:32:38,280 Speaker 16: and try and stop it and actually capture some more 626 00:32:38,320 --> 00:32:40,200 Speaker 16: of the value in the UK economy. As I say 627 00:32:41,120 --> 00:32:43,120 Speaker 16: this is the companies have largely come over here because 628 00:32:43,160 --> 00:32:44,600 Speaker 16: is where the capital is. If you've got a new 629 00:32:44,640 --> 00:32:47,640 Speaker 16: capital stream with some expertise based on it in the UK, 630 00:32:48,080 --> 00:32:49,800 Speaker 16: we're going to hope to retain those companies in the 631 00:32:49,880 --> 00:32:53,000 Speaker 16: UK longer. And actually the innovation ecosystem I think is 632 00:32:53,160 --> 00:32:56,520 Speaker 16: quite self perpetuating success breed success. We've got a lot 633 00:32:56,520 --> 00:32:58,880 Speaker 16: of the right things in place, but it's just this 634 00:32:58,960 --> 00:33:00,800 Speaker 16: top end that we need to to really make sure 635 00:33:00,840 --> 00:33:03,600 Speaker 16: that we realize more potential and keep the flywheel going. 636 00:33:04,080 --> 00:33:06,080 Speaker 3: So your strategy here, and one of the reasons you're 637 00:33:06,080 --> 00:33:09,040 Speaker 3: in town, is to go to the American VCS, the 638 00:33:09,120 --> 00:33:10,560 Speaker 3: Value v season say. 639 00:33:10,880 --> 00:33:12,840 Speaker 2: Give us your capital, come to the UK. We have 640 00:33:12,880 --> 00:33:13,640 Speaker 2: something to offer. 641 00:33:14,040 --> 00:33:16,440 Speaker 3: But that strategy then carries risks with what you're just 642 00:33:16,480 --> 00:33:17,560 Speaker 3: talking with Carolina about. 643 00:33:17,640 --> 00:33:17,840 Speaker 2: Right. 644 00:33:18,040 --> 00:33:20,160 Speaker 16: Yeah, we're not quite saying that, we're saying, bring us 645 00:33:20,200 --> 00:33:22,479 Speaker 16: your expertise, will help you raise capital locally. 646 00:33:22,560 --> 00:33:25,360 Speaker 2: This is a growth opportunity for capital locally. That's a key, 647 00:33:25,440 --> 00:33:26,600 Speaker 2: absolute distinction. 648 00:33:26,440 --> 00:33:29,680 Speaker 16: Absolutely, and the connections that we have with all the 649 00:33:29,760 --> 00:33:32,480 Speaker 16: gps LPs but also the pension funds. I mean, we 650 00:33:32,560 --> 00:33:34,760 Speaker 16: actually are raising our own fund at the moment for 651 00:33:34,800 --> 00:33:39,080 Speaker 16: a co invest fund in the UK from UK pension 652 00:33:39,120 --> 00:33:41,120 Speaker 16: funds and we'll do the first close end of January 653 00:33:41,120 --> 00:33:43,880 Speaker 16: early February. And this is a thing, it's. 654 00:33:43,720 --> 00:33:44,240 Speaker 2: A real thing. 655 00:33:44,840 --> 00:33:46,160 Speaker 4: It's a real thing, and we'll let you go out 656 00:33:46,160 --> 00:33:48,320 Speaker 4: and have real conversations with those vcs and the Value 657 00:33:48,320 --> 00:33:51,440 Speaker 4: the Louis Taylor, thanks for stopping by. CEO the British 658 00:33:51,480 --> 00:33:55,479 Speaker 4: Business Bank. Coming up, White House AI and Cryptos are 659 00:33:55,800 --> 00:33:58,000 Speaker 4: David Sachs joins us to talk about the President trump 660 00:33:58,440 --> 00:34:00,680 Speaker 4: executive Order on a regulation. 661 00:34:01,120 --> 00:34:02,000 Speaker 5: This is ring back Tap. 662 00:34:15,760 --> 00:34:19,400 Speaker 3: Welcome to our global radio and TV audiences. President Trump 663 00:34:19,440 --> 00:34:23,320 Speaker 3: signed an executive order aimed at limiting state level regulation 664 00:34:23,400 --> 00:34:26,759 Speaker 3: of AI. The move is supported by tech leaders who 665 00:34:26,760 --> 00:34:30,480 Speaker 3: have argued local rules could stifle innovation. We're joined by 666 00:34:30,560 --> 00:34:33,920 Speaker 3: David Sachs, the White House AI and Crypto ZA or 667 00:34:34,120 --> 00:34:37,160 Speaker 3: Senior Advisor, David. I think it's a really good place 668 00:34:37,200 --> 00:34:41,239 Speaker 3: to start in your work with the President in consulting 669 00:34:41,280 --> 00:34:44,840 Speaker 3: and advising on the formulation of this executive order. 670 00:34:45,440 --> 00:34:46,400 Speaker 2: What was the. 671 00:34:46,280 --> 00:34:50,200 Speaker 3: Problem that you were trying to solve for and what 672 00:34:50,320 --> 00:34:52,960 Speaker 3: is it that you said to the President about why 673 00:34:53,040 --> 00:34:56,840 Speaker 3: this EO was the right approach to focus on state 674 00:34:56,920 --> 00:34:57,600 Speaker 3: level laws? 675 00:34:58,920 --> 00:35:01,960 Speaker 10: Well, thanks for having The problem that we see is 676 00:35:02,000 --> 00:35:04,799 Speaker 10: that you've got one thousand different bills going through state 677 00:35:04,880 --> 00:35:08,120 Speaker 10: legislatures right now to regulate AI, and over one hundred 678 00:35:08,160 --> 00:35:11,480 Speaker 10: measures already passed. Some of these bills are contradictory, and 679 00:35:11,520 --> 00:35:14,080 Speaker 10: you've got fifty different states running in fifty different directions. 680 00:35:14,440 --> 00:35:15,920 Speaker 2: That type of compliance. 681 00:35:15,520 --> 00:35:18,240 Speaker 10: Regime is going to be very hard for small companies 682 00:35:18,239 --> 00:35:22,319 Speaker 10: and startups, especially innovators to comply with. And so what 683 00:35:22,360 --> 00:35:27,000 Speaker 10: we need is a single federal or national framework for 684 00:35:27,080 --> 00:35:29,480 Speaker 10: AI regulation. And that's what the President has supported, and 685 00:35:29,520 --> 00:35:31,520 Speaker 10: by the way, he supported this for a long time. 686 00:35:31,560 --> 00:35:34,640 Speaker 10: If you go back to his July speech on AI, 687 00:35:34,880 --> 00:35:37,920 Speaker 10: he called for a single national framework then. And what 688 00:35:37,960 --> 00:35:40,640 Speaker 10: we've done with THISEO now is to make clear that 689 00:35:40,640 --> 00:35:43,799 Speaker 10: that is the administration's policy and to task members of the 690 00:35:43,800 --> 00:35:47,040 Speaker 10: administration to work with Congress to try and enact that 691 00:35:47,080 --> 00:35:50,600 Speaker 10: framework through legislation, because ultimately this needs to be a law, 692 00:35:51,000 --> 00:35:53,960 Speaker 10: and in the meantime create tools that the administration can 693 00:35:54,080 --> 00:35:57,360 Speaker 10: use to push back on examples of the most onerous 694 00:35:57,360 --> 00:35:59,160 Speaker 10: and excessive state regulations. 695 00:36:00,280 --> 00:36:02,840 Speaker 3: David, there is of course some pushback you know, on 696 00:36:02,920 --> 00:36:06,640 Speaker 3: the executive order from the states themselves, from other Republicans 697 00:36:07,440 --> 00:36:10,600 Speaker 3: you know, as you know, like I studied the July 698 00:36:12,239 --> 00:36:15,719 Speaker 3: speech and strategy closely, a big part of it, you know, 699 00:36:15,840 --> 00:36:20,480 Speaker 3: was infrastructure related and about deregulation. The concern about this 700 00:36:20,680 --> 00:36:24,200 Speaker 3: latest executive order is that while it addresses your concerns 701 00:36:24,280 --> 00:36:28,040 Speaker 3: about many different pieces of state regulation, it does not 702 00:36:28,160 --> 00:36:30,879 Speaker 3: provide for a single federal framework. 703 00:36:32,960 --> 00:36:35,200 Speaker 10: Well, at the end of the day, that single federal 704 00:36:35,200 --> 00:36:38,320 Speaker 10: framework has be enacted through law, and we need Congress 705 00:36:38,360 --> 00:36:40,680 Speaker 10: to do that. And so the President has asked Congress 706 00:36:40,719 --> 00:36:43,080 Speaker 10: to do that, and these tasked members the administration to 707 00:36:43,160 --> 00:36:46,560 Speaker 10: work with Congress to produce that framework. In the meantime. 708 00:36:46,560 --> 00:36:48,680 Speaker 10: What we've done here is articulated set of principles. We 709 00:36:48,760 --> 00:36:52,359 Speaker 10: said what values are important to us. We said that 710 00:36:52,840 --> 00:36:55,960 Speaker 10: we want to protect child safety, that's important. We want 711 00:36:56,000 --> 00:36:59,200 Speaker 10: to respect copyright, we want to preserve the ability of 712 00:36:59,280 --> 00:37:03,840 Speaker 10: local community is to choose what infrastructures and their communities. 713 00:37:03,880 --> 00:37:06,920 Speaker 10: We're not seeking to preempt the states in any of 714 00:37:06,960 --> 00:37:09,880 Speaker 10: those areas. So this is an important set of principles 715 00:37:09,920 --> 00:37:13,080 Speaker 10: that we have put forth. And at the same time, 716 00:37:13,320 --> 00:37:16,120 Speaker 10: the EO provides for a number of tools that can 717 00:37:16,160 --> 00:37:19,719 Speaker 10: be used to push back on excessive state regulation. And 718 00:37:20,080 --> 00:37:22,400 Speaker 10: let me just illustrate why I think this is so necessary. 719 00:37:23,440 --> 00:37:26,320 Speaker 10: What we're really talking about here is regulation of AI 720 00:37:26,400 --> 00:37:30,400 Speaker 10: models and algorithms. Well, think about how an AI model 721 00:37:30,600 --> 00:37:33,759 Speaker 10: is developed. You can have developers in one state of 722 00:37:33,840 --> 00:37:37,080 Speaker 10: multiple states writing the code. It can then be trained 723 00:37:37,120 --> 00:37:39,600 Speaker 10: in a data center in another state. You then can 724 00:37:39,680 --> 00:37:43,120 Speaker 10: have inference happen in another state, and the entire service 725 00:37:43,280 --> 00:37:47,799 Speaker 10: is provided over the Internet using national telecommunications infrastructure. So 726 00:37:47,840 --> 00:37:49,840 Speaker 10: you're dealing there with at least four different states, and 727 00:37:49,920 --> 00:37:53,880 Speaker 10: all of them can lay claim to regulating those AI models, 728 00:37:54,160 --> 00:37:56,879 Speaker 10: and those regulations can be in contradiction with each other. 729 00:37:57,200 --> 00:38:00,239 Speaker 10: Even Democrat governors have admitted this as a problem. Just 730 00:38:00,320 --> 00:38:03,040 Speaker 10: the other day, Kathy Hockle, the governor of New York It, 731 00:38:03,080 --> 00:38:07,480 Speaker 10: basically said that she might prefer to enact California's SB 732 00:38:07,600 --> 00:38:10,160 Speaker 10: fifty three, which is a regulation that they just passed 733 00:38:10,160 --> 00:38:13,120 Speaker 10: in California, rather than the bill that her own assembly 734 00:38:13,160 --> 00:38:15,520 Speaker 10: gave her the raise act, because she sees that, wait, 735 00:38:15,560 --> 00:38:17,959 Speaker 10: do we really want to create this patchwork in different regulations. 736 00:38:18,160 --> 00:38:20,920 Speaker 10: So even Democrat governors are realizing this is a problem, 737 00:38:20,960 --> 00:38:23,520 Speaker 10: and if they all run in different directions, then we're 738 00:38:23,520 --> 00:38:26,000 Speaker 10: going to end up with a patchwork or a misshmash 739 00:38:26,360 --> 00:38:28,839 Speaker 10: of regulations that are impossible for companies to comply with. 740 00:38:28,880 --> 00:38:32,040 Speaker 10: What the President is calling for here is just common sense. 741 00:38:32,280 --> 00:38:35,680 Speaker 10: We want to get to a single national framework of 742 00:38:35,760 --> 00:38:38,920 Speaker 10: compliance as opposed to fifty states running in different directions. 743 00:38:39,280 --> 00:38:41,880 Speaker 4: Meanwhile, Kathy Hokle actually is getting a bit of criticism 744 00:38:41,920 --> 00:38:45,959 Speaker 4: perhaps for narrowing and what some are saying is bowing. 745 00:38:45,640 --> 00:38:48,200 Speaker 5: Down to business. David, I'm really interested in. 746 00:38:48,120 --> 00:38:51,360 Speaker 4: How you oppose that view, because there is anxiety in 747 00:38:51,400 --> 00:38:56,120 Speaker 4: the population AI versus jobs, AI versus energy bills. How 748 00:38:56,160 --> 00:38:58,839 Speaker 4: are you giving them the sense that we haven't seen 749 00:38:58,960 --> 00:39:01,799 Speaker 4: federal government and India now state government's just handing over 750 00:39:01,840 --> 00:39:04,920 Speaker 4: the reins to big tech billionaires as people call them. 751 00:39:05,520 --> 00:39:05,719 Speaker 6: Right. 752 00:39:05,760 --> 00:39:07,680 Speaker 10: No, I understand there's a lot of fear out there 753 00:39:07,719 --> 00:39:10,680 Speaker 10: about AI and job loss specifically, and a lot of 754 00:39:10,719 --> 00:39:13,319 Speaker 10: those fears have been drummed up. Let me just say 755 00:39:13,320 --> 00:39:15,040 Speaker 10: on the job loss question, because I think this is 756 00:39:15,080 --> 00:39:17,800 Speaker 10: really important that Yale just released a study and it 757 00:39:17,920 --> 00:39:20,600 Speaker 10: showed that in the thirty three months after the launch 758 00:39:20,640 --> 00:39:23,759 Speaker 10: of chat GPT, there was no discernible disruption to the 759 00:39:23,840 --> 00:39:27,319 Speaker 10: US job market none. They said, no discernible disruption. And 760 00:39:27,360 --> 00:39:29,680 Speaker 10: in fact, if you look right now, more jobs are 761 00:39:29,680 --> 00:39:31,920 Speaker 10: being created than being lost. So this whole idea of 762 00:39:32,000 --> 00:39:34,279 Speaker 10: job losses just isn't true. There was an article on 763 00:39:34,280 --> 00:39:36,920 Speaker 10: the Wall Street Journal just last week talking about the 764 00:39:37,600 --> 00:39:41,840 Speaker 10: construction boom that's happening that's benefiting construction workers like electricians 765 00:39:41,920 --> 00:39:45,480 Speaker 10: like plumbers like workers who pour concrete or hang drywall. 766 00:39:45,680 --> 00:39:48,680 Speaker 10: Their wages are up thirty percent because this infrastructure boom 767 00:39:48,719 --> 00:39:51,400 Speaker 10: that's happening right now, and there's actually a job shortage 768 00:39:51,800 --> 00:39:54,800 Speaker 10: in many of those trades, meaning we need more workers 769 00:39:54,840 --> 00:39:57,239 Speaker 10: going into those trades. So what we're seeing right now 770 00:39:57,320 --> 00:40:00,480 Speaker 10: is an overall AI boom that's benefiting the economy. You know, 771 00:40:00,640 --> 00:40:04,360 Speaker 10: the the GDP growth rate was tracking about four percent, 772 00:40:04,800 --> 00:40:06,880 Speaker 10: and half of that up to half of it's been 773 00:40:06,880 --> 00:40:10,920 Speaker 10: attributed to AI. So I just think that this narrative 774 00:40:10,960 --> 00:40:14,240 Speaker 10: about job loss has been blown out of proportion. Certainly 775 00:40:14,239 --> 00:40:16,640 Speaker 10: there could be job displacement in the future, but we 776 00:40:16,680 --> 00:40:18,879 Speaker 10: haven't seen any of that so far. It's been quite 777 00:40:18,920 --> 00:40:20,280 Speaker 10: the opposite. It has been job gains. 778 00:40:21,080 --> 00:40:24,080 Speaker 3: David Final one on the EO, If I may, you 779 00:40:24,120 --> 00:40:27,759 Speaker 3: know what this EO allows for. Is it the sort 780 00:40:27,760 --> 00:40:31,240 Speaker 3: of hope that it will lead to the DOJ sewing 781 00:40:31,440 --> 00:40:35,320 Speaker 3: states like New York and California. And if that's the case, 782 00:40:35,800 --> 00:40:38,759 Speaker 3: you know, the President and the administration's confidence that you'd 783 00:40:38,760 --> 00:40:40,320 Speaker 3: win them. 784 00:40:40,640 --> 00:40:42,480 Speaker 10: Well, that is one of the tools that is in 785 00:40:42,520 --> 00:40:45,440 Speaker 10: the EO is that the DOJ has been tasked to 786 00:40:45,440 --> 00:40:49,280 Speaker 10: form a litigation task force that would have the ability 787 00:40:49,320 --> 00:40:53,680 Speaker 10: to push back on excessively burn some state laws, laws 788 00:40:53,719 --> 00:40:57,120 Speaker 10: that may be unconstitutional, violate the First Amendment, things like that. 789 00:40:57,160 --> 00:40:59,600 Speaker 10: By the way, the DOJ already had that power, So 790 00:40:59,640 --> 00:41:02,600 Speaker 10: this is a novel power. But what's being done here 791 00:41:02,600 --> 00:41:04,719 Speaker 10: in the CEO is we're marshaling all the resources of 792 00:41:04,760 --> 00:41:07,360 Speaker 10: the federal government behind the strategy of the President to 793 00:41:07,400 --> 00:41:09,799 Speaker 10: create a national framework. Now, in terms of what laws 794 00:41:09,800 --> 00:41:11,840 Speaker 10: we go after, that's a decision that has been made. 795 00:41:13,080 --> 00:41:16,160 Speaker 10: We haven't decided whether California and New York should be 796 00:41:16,200 --> 00:41:19,279 Speaker 10: targets in that way. The one that I think is 797 00:41:19,320 --> 00:41:23,080 Speaker 10: probably the most excessive is this Colorado law that seeks 798 00:41:23,080 --> 00:41:26,640 Speaker 10: to prohibit algorithmic discrimination. What that basically says is that 799 00:41:26,640 --> 00:41:28,960 Speaker 10: if an AI model has a disparate impact on a 800 00:41:29,000 --> 00:41:33,400 Speaker 10: protected group, then that model is violating the law. Model developers, 801 00:41:33,440 --> 00:41:34,880 Speaker 10: by the way, I have no idea how to comply 802 00:41:34,960 --> 00:41:37,680 Speaker 10: with this because they're not aware of all the downstream 803 00:41:37,760 --> 00:41:40,000 Speaker 10: uses of their model. I mean, if a business decides 804 00:41:40,040 --> 00:41:42,920 Speaker 10: to use an AI model in a hiring decision, for example, 805 00:41:43,440 --> 00:41:45,520 Speaker 10: that business is already on the hook for discrimination. So 806 00:41:45,560 --> 00:41:48,600 Speaker 10: how would the model developer know that it was being 807 00:41:48,680 --> 00:41:50,600 Speaker 10: used in that way. But what Colorado was trying to 808 00:41:50,640 --> 00:41:54,520 Speaker 10: do there is get their ideology inserted into the model. 809 00:41:54,560 --> 00:41:56,480 Speaker 10: That's very concerning to us. We think there's a First 810 00:41:56,480 --> 00:41:59,080 Speaker 10: Amendment issue there, but look, we haven't made any decisions 811 00:41:59,160 --> 00:42:01,320 Speaker 10: in terms of how that litigation task for US to 812 00:42:01,320 --> 00:42:01,719 Speaker 10: be used. 813 00:42:01,800 --> 00:42:04,320 Speaker 4: David Briefly, all of this is set in the context 814 00:42:04,400 --> 00:42:08,120 Speaker 4: of US versus China and a deemed to run forward 815 00:42:08,360 --> 00:42:11,279 Speaker 4: on AI development. Meanwhile, it's been a busy week and 816 00:42:11,400 --> 00:42:14,200 Speaker 4: H two hundreds might indeed be able to get to China. 817 00:42:14,440 --> 00:42:16,200 Speaker 4: How many do you think you'll do in volumes and 818 00:42:16,200 --> 00:42:17,719 Speaker 4: what do you think the appetite is of China to 819 00:42:17,760 --> 00:42:19,640 Speaker 4: buy in videos more sophisticated chips. 820 00:42:20,880 --> 00:42:23,040 Speaker 10: Well, it's interesting. I just saw an article that said 821 00:42:23,080 --> 00:42:25,560 Speaker 10: that China was rejecting the H two hundreds, So apparently 822 00:42:25,600 --> 00:42:27,680 Speaker 10: they don't want them, and I think the reason for 823 00:42:27,719 --> 00:42:30,560 Speaker 10: that is they want semiconductor independence the same way that 824 00:42:30,600 --> 00:42:33,200 Speaker 10: the United States wanted to be energy independent. They want 825 00:42:33,200 --> 00:42:36,520 Speaker 10: to be semiconductor independent, So they're rejecting our chips, and 826 00:42:36,880 --> 00:42:39,240 Speaker 10: that's part of the calculation that goes into the decision 827 00:42:39,280 --> 00:42:42,279 Speaker 10: of what we authorized to be sold to China. The 828 00:42:42,360 --> 00:42:44,560 Speaker 10: US policy has always been that we don't allow the 829 00:42:44,600 --> 00:42:47,520 Speaker 10: leading edged chips, and we're not. This is this H 830 00:42:47,560 --> 00:42:49,680 Speaker 10: two hundred chip. It was state of the art a 831 00:42:49,680 --> 00:42:52,120 Speaker 10: couple of years ago, but now it's been superseded by 832 00:42:52,160 --> 00:42:55,120 Speaker 10: the new or Blackwell architecture and the Ruben architecture that's 833 00:42:55,120 --> 00:42:57,879 Speaker 10: coming out next year. So this is now a lagging chip, 834 00:42:57,960 --> 00:43:00,560 Speaker 10: not a leading chip. But what you see is not 835 00:43:00,600 --> 00:43:04,320 Speaker 10: taking them because they want to prop up and subsidize Hahwei. 836 00:43:04,320 --> 00:43:06,880 Speaker 10: They want to create a national champion, and that was 837 00:43:06,920 --> 00:43:09,799 Speaker 10: part of our calculation of selling not the best but 838 00:43:09,920 --> 00:43:12,200 Speaker 10: lagging chips to China's. You can take market share away 839 00:43:12,200 --> 00:43:14,719 Speaker 10: from Huawei, but I think the Chinese government's figured that 840 00:43:14,800 --> 00:43:16,959 Speaker 10: out and that's why they're not allowing them. 841 00:43:17,160 --> 00:43:19,919 Speaker 4: David Sachs, we always wish we had more time White House, 842 00:43:19,960 --> 00:43:22,440 Speaker 4: AI and cryptos Are. We thank you for joining us 843 00:43:22,440 --> 00:43:25,200 Speaker 4: today on the executive order and indeed on in videos 844 00:43:25,320 --> 00:43:27,200 Speaker 4: H two hundreds. That does it for this edition of 845 00:43:27,239 --> 00:43:29,600 Speaker 4: Bloomberg Tech. The market is in sell off motored as 846 00:43:29,600 --> 00:43:31,440 Speaker 4: we wrap up this week. We're down by more than 847 00:43:31,440 --> 00:43:33,520 Speaker 4: two percent on the NASDAC more broadly and indeed for 848 00:43:33,560 --> 00:43:36,600 Speaker 4: the week, but really all eyes on well Broadcom. 849 00:43:36,080 --> 00:43:37,080 Speaker 5: And its numbers. 850 00:43:37,480 --> 00:43:40,640 Speaker 3: Yeah, Broadcom in the earnings context investors, what is more 851 00:43:40,680 --> 00:43:43,760 Speaker 3: But Bloomberg reporting on Oracle is what moved the needle, 852 00:43:44,360 --> 00:43:46,640 Speaker 3: believe it or not. This is my last show of 853 00:43:46,640 --> 00:43:50,560 Speaker 3: twenty twenty five. An astonishing year and a lot of 854 00:43:50,560 --> 00:43:53,239 Speaker 3: the themes in today's show what we've been talking about 855 00:43:53,239 --> 00:43:55,600 Speaker 3: all year long. Recap on the podcast. You can find 856 00:43:55,600 --> 00:43:58,279 Speaker 3: it on the terminal and online. You know where to Caro. 857 00:43:58,440 --> 00:43:59,839 Speaker 3: I'll see you in twenty twenty six. 858 00:44:00,800 --> 00:44:02,799 Speaker 5: Have a great break. Mmmmmm