1 00:00:02,560 --> 00:00:15,120 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is live 2 00:00:15,200 --> 00:00:18,880 Speaker 1: from the heart of Silicon Valley with Ed Larlow in 3 00:00:19,120 --> 00:00:19,960 Speaker 1: San Francisco. 4 00:00:22,640 --> 00:00:24,239 Speaker 2: This is Bloomberg Tech coming up. 5 00:00:24,320 --> 00:00:27,560 Speaker 3: Open Ai held early stage discussions about giving the US 6 00:00:27,680 --> 00:00:31,040 Speaker 3: government a five percent equity stake, according to reports. 7 00:00:31,240 --> 00:00:32,160 Speaker 2: We have the details. 8 00:00:32,240 --> 00:00:35,440 Speaker 3: Plus Tesla's delivery numbers jump twenty five percent from a 9 00:00:35,520 --> 00:00:39,199 Speaker 3: year ago, beating Wall Streets expectations by a wide margin. 10 00:00:39,520 --> 00:00:42,960 Speaker 3: And we're joined by Judson Holt Hooff, CEO of Microsoft's 11 00:00:42,960 --> 00:00:47,040 Speaker 3: Commercial business, to talk forward deployed engineers. 12 00:00:47,400 --> 00:00:48,680 Speaker 2: Let's get to our top story. 13 00:00:49,080 --> 00:00:53,199 Speaker 3: OpenAI has held early stage discussions about potentially giving the 14 00:00:53,280 --> 00:00:57,560 Speaker 3: US government a five percent equity stake. That's according to 15 00:00:57,600 --> 00:01:01,160 Speaker 3: a report in the Financial Time. Sam Altman is said 16 00:01:01,200 --> 00:01:04,480 Speaker 3: to have held discussions with President Trump, US Commons Secretary 17 00:01:04,520 --> 00:01:09,160 Speaker 3: Howard Lutnik and US Treasury Secretary Scott Bessen. Bloomberg Senior 18 00:01:09,200 --> 00:01:12,000 Speaker 3: Tech headed to Mike Shepherd's with US from DC. Again, 19 00:01:12,160 --> 00:01:16,200 Speaker 3: this is a FT report. Bloomberg's not yet verified that 20 00:01:16,319 --> 00:01:21,040 Speaker 3: reporting or done its own report, but the idea of 21 00:01:22,959 --> 00:01:26,120 Speaker 3: stakes and technology companies, and specifically in Frontier Labs, has 22 00:01:26,280 --> 00:01:29,840 Speaker 3: come up with this administration. Let's start by recapping what's 23 00:01:29,880 --> 00:01:31,119 Speaker 3: in that FT report. 24 00:01:32,200 --> 00:01:35,280 Speaker 4: Well, looking at the FT report, the biggest headline in 25 00:01:35,360 --> 00:01:36,840 Speaker 4: it is the five percent stake. 26 00:01:37,040 --> 00:01:37,679 Speaker 2: You know, this is. 27 00:01:37,640 --> 00:01:41,360 Speaker 4: An idea that has come up before. Even President Donald 28 00:01:41,400 --> 00:01:45,080 Speaker 4: Trump has indicated he embraced at least the vision for 29 00:01:45,160 --> 00:01:48,960 Speaker 4: giving the government a piece of the action in these companies, 30 00:01:49,120 --> 00:01:52,600 Speaker 4: but he hasn't gone into specifics, and they never really 31 00:01:52,600 --> 00:01:56,320 Speaker 4: talked about just how much the government would actually acquire 32 00:01:56,600 --> 00:01:59,560 Speaker 4: or hold in these ventures. But the five percent is new. 33 00:01:59,800 --> 00:02:04,440 Speaker 4: It's unclear ed how advanced these discussions are with the government. 34 00:02:05,600 --> 00:02:08,760 Speaker 4: Sam Altman was here in Washington last month where he 35 00:02:08,880 --> 00:02:12,720 Speaker 4: met with some administration officials and brought the idea up again. 36 00:02:13,080 --> 00:02:15,520 Speaker 4: It also came up during a visit to Capitol Hill, 37 00:02:15,720 --> 00:02:17,960 Speaker 4: and this was an idea that was floated by Open 38 00:02:18,000 --> 00:02:21,919 Speaker 4: AI to the administration back in early twenty twenty five. 39 00:02:21,960 --> 00:02:24,000 Speaker 4: So it's been kicking around and back in early twenty 40 00:02:24,040 --> 00:02:27,000 Speaker 4: twenty five, he'll remember, the President did sign that executive 41 00:02:27,160 --> 00:02:30,760 Speaker 4: order trying to set the stage for creating a sovereign 42 00:02:30,800 --> 00:02:34,160 Speaker 4: wealth fund. That proposal hasn't really gained much traction here. 43 00:02:34,320 --> 00:02:38,000 Speaker 4: It's quite complex and probably would need Congress to get involved. 44 00:02:38,560 --> 00:02:40,720 Speaker 3: At that time, in February twenty twenty five, you know, 45 00:02:40,720 --> 00:02:42,800 Speaker 3: the President was saying, well, many other nations have a 46 00:02:42,840 --> 00:02:45,040 Speaker 3: sovereign wealth fund, the United States should have one. That 47 00:02:45,080 --> 00:02:47,880 Speaker 3: he specifically talks about the idea that that would be 48 00:02:47,919 --> 00:02:51,600 Speaker 3: the vehicle for a US S taken TikTok. That was 49 00:02:51,639 --> 00:02:54,200 Speaker 3: the case study I think that the President gave in 50 00:02:54,240 --> 00:02:57,240 Speaker 3: the FD report. There is a broader idea, which is, 51 00:02:57,600 --> 00:02:59,680 Speaker 3: it seems to be the pitch from Open AI to 52 00:02:59,720 --> 00:03:02,120 Speaker 3: the US government is the US government should do this 53 00:03:02,160 --> 00:03:05,520 Speaker 3: with a broad range of AI companies. 54 00:03:05,720 --> 00:03:08,680 Speaker 2: But they're not named. Well, that's right. 55 00:03:08,760 --> 00:03:12,160 Speaker 4: They took pains not to name the companies. But it 56 00:03:12,280 --> 00:03:15,240 Speaker 4: is an idea that Sam Altman has been pushing. And 57 00:03:15,320 --> 00:03:18,119 Speaker 4: it's really less say a sovereign wealth fund, but more 58 00:03:18,160 --> 00:03:21,160 Speaker 4: a public benefit fund. And that's akin to a proposal 59 00:03:21,280 --> 00:03:24,240 Speaker 4: we've also seen from Bernie Sanders, who has called and 60 00:03:24,280 --> 00:03:27,880 Speaker 4: even for and even proposed legislation that would put a 61 00:03:28,000 --> 00:03:31,680 Speaker 4: one time fifty percent tax on the top AI labs, 62 00:03:32,240 --> 00:03:35,480 Speaker 4: using their stock and then taking the proceeds to seed 63 00:03:35,600 --> 00:03:36,920 Speaker 4: this public benefit fund. 64 00:03:37,080 --> 00:03:38,480 Speaker 2: And the idea would be twofold. 65 00:03:38,680 --> 00:03:41,000 Speaker 4: The goal would be to get the government at least 66 00:03:41,040 --> 00:03:42,840 Speaker 4: some skin in the game to feel like it has 67 00:03:42,880 --> 00:03:46,760 Speaker 4: some responsibility in the development of this technology, but then 68 00:03:46,920 --> 00:03:50,200 Speaker 4: also to use the fund to redistribute the benefits of 69 00:03:50,320 --> 00:03:53,960 Speaker 4: AI more equitably across the society and address some of 70 00:03:54,000 --> 00:03:56,880 Speaker 4: the concerns that we have seen raised, especially recently with 71 00:03:56,960 --> 00:04:01,360 Speaker 4: the oncoming wave of IPOs from Open Ai and Anthrapic, 72 00:04:01,640 --> 00:04:04,800 Speaker 4: that perhaps there could be a new generation of billionaires 73 00:04:04,880 --> 00:04:08,720 Speaker 4: minted from this and increasing the gap between the rich 74 00:04:08,840 --> 00:04:09,960 Speaker 4: and the poor in this country. 75 00:04:10,680 --> 00:04:13,600 Speaker 3: Bloomberg Tech has gone out to Open Ai, the other 76 00:04:13,640 --> 00:04:16,640 Speaker 3: AI labs, the US government to comment on this story. 77 00:04:17,120 --> 00:04:19,960 Speaker 3: Haven't heard back yet. Bloombergs Mike Shepherd, thank you very much. Indeed, 78 00:04:19,960 --> 00:04:24,520 Speaker 3: Anthropic maybe the latest AI company designing its own chips. 79 00:04:24,560 --> 00:04:28,000 Speaker 3: The Information reports that the startup is in early talks 80 00:04:28,200 --> 00:04:32,360 Speaker 3: with Samsung to manufacture a custom AI processor. It's the 81 00:04:32,440 --> 00:04:36,640 Speaker 3: latest SIGNAI companies are looking to diversify beyond Nvidia as 82 00:04:36,720 --> 00:04:40,599 Speaker 3: demand for computing power continues to search again, will track 83 00:04:40,680 --> 00:04:43,840 Speaker 3: that story, staying with chips. It's not just AI companies 84 00:04:43,880 --> 00:04:48,039 Speaker 3: rethinking their supply chains. Apple is also exploring new sources 85 00:04:48,040 --> 00:04:51,440 Speaker 3: for critical components. According to sources, the companies and talks 86 00:04:51,440 --> 00:04:55,160 Speaker 3: to buy memory chips from two Chinese suppliers that are 87 00:04:55,160 --> 00:04:58,280 Speaker 3: on the Pentagon's blacklist for use in devices that are 88 00:04:58,320 --> 00:05:02,200 Speaker 3: sold in China. Discussions are ongoing and no deal has 89 00:05:02,240 --> 00:05:04,920 Speaker 3: been finalized. More Bloombergs Maggie east Land with US also 90 00:05:04,960 --> 00:05:10,360 Speaker 3: in DC, really really detailed reporting. There is slightly separate 91 00:05:10,400 --> 00:05:13,800 Speaker 3: issues here, right. There is this supply constraint that is memory. 92 00:05:14,440 --> 00:05:17,880 Speaker 3: There is getting US approval to do something, and then 93 00:05:18,400 --> 00:05:21,400 Speaker 3: the main point that I just read securing memory tips 94 00:05:21,440 --> 00:05:24,760 Speaker 3: from a Chinese supply for use in that market devices 95 00:05:24,760 --> 00:05:27,520 Speaker 3: that go to China start by bringing us The reporting. 96 00:05:28,760 --> 00:05:31,240 Speaker 5: Right ed a lot of nuance here. So one thing 97 00:05:31,279 --> 00:05:34,720 Speaker 5: to note is that this Pentagon sort of watch list 98 00:05:34,920 --> 00:05:39,480 Speaker 5: does not actually directly restrict Apple from purchasing memory from 99 00:05:39,560 --> 00:05:43,240 Speaker 5: these two Chinese companies, CXMT and YMTC. 100 00:05:43,680 --> 00:05:44,640 Speaker 2: However, it would. 101 00:05:44,480 --> 00:05:49,279 Speaker 5: Be seen as potentially political mismaneuver if they weren't to 102 00:05:49,320 --> 00:05:52,320 Speaker 5: go ahead and get the US permissions, since the Trump 103 00:05:52,320 --> 00:05:55,640 Speaker 5: administration has already shown they have some concerns about these 104 00:05:55,680 --> 00:05:58,880 Speaker 5: memory companies being connected to the Chinese military. 105 00:05:59,160 --> 00:06:00,800 Speaker 6: So the pitch here, and we've. 106 00:06:00,520 --> 00:06:04,360 Speaker 5: Reported that Tim Cook has reached out to Treasury Secretary 107 00:06:04,400 --> 00:06:08,760 Speaker 5: Scott Bessant because Apple has been forced to raise prices 108 00:06:09,480 --> 00:06:12,240 Speaker 5: due to the memory shortage. So the pitch here is 109 00:06:12,240 --> 00:06:15,559 Speaker 5: that the shortage is so intense, maybe the US should 110 00:06:15,640 --> 00:06:18,320 Speaker 5: let up on some of its restrictions on these Chinese 111 00:06:18,360 --> 00:06:19,160 Speaker 5: memory companies. 112 00:06:19,960 --> 00:06:22,960 Speaker 3: Maggie, this is your reporting with the team, right, and 113 00:06:23,000 --> 00:06:27,000 Speaker 3: it's based on sources explaining the situation. What is Apple 114 00:06:27,120 --> 00:06:30,880 Speaker 3: said and what is the US government said about our report? 115 00:06:32,440 --> 00:06:35,120 Speaker 5: Look, I think the best evidence we have here is 116 00:06:35,160 --> 00:06:38,120 Speaker 5: that Tim Cook went to Scott Bessont, obviously someone who 117 00:06:38,200 --> 00:06:42,080 Speaker 5: cares a lot about inflation. Apple has also been talking 118 00:06:42,120 --> 00:06:45,400 Speaker 5: a lot about this, talking about how memory price increases 119 00:06:45,760 --> 00:06:50,400 Speaker 5: are driving the price increases for things like laptops and iPads, 120 00:06:50,640 --> 00:06:53,719 Speaker 5: as Mark German has reported and who's also helped on 121 00:06:53,760 --> 00:06:56,640 Speaker 5: this report. So I think the pitch here is that 122 00:06:56,720 --> 00:06:59,960 Speaker 5: even though the US government might have some security concerns, 123 00:07:00,320 --> 00:07:03,719 Speaker 5: maybe it makes sense to allow Apple to purchase Chinese 124 00:07:03,720 --> 00:07:07,640 Speaker 5: memory in these scenarios, just because the price of consumer 125 00:07:07,680 --> 00:07:10,880 Speaker 5: electronics is increasing so rapidly. But of course there are 126 00:07:10,920 --> 00:07:13,120 Speaker 5: going to be China Hawks in Washington who. 127 00:07:13,000 --> 00:07:14,520 Speaker 2: Have concerns about this. 128 00:07:15,400 --> 00:07:19,160 Speaker 5: We included in our report from Chairman Brian mass who 129 00:07:19,240 --> 00:07:23,680 Speaker 5: leads a committee here in the House that oversees foreign affairs, 130 00:07:24,280 --> 00:07:26,680 Speaker 5: and he is very against this move and is advising 131 00:07:26,720 --> 00:07:28,800 Speaker 5: the Trump administration not to do this. So we're certainly 132 00:07:28,840 --> 00:07:30,800 Speaker 5: going to see a fight here in Washington over this. 133 00:07:31,440 --> 00:07:33,600 Speaker 2: Bloomberg's Maggie Eastland, thank you very much. 134 00:07:33,680 --> 00:07:38,400 Speaker 3: Coming up, Tesla surprises wool Street with the strength of 135 00:07:38,440 --> 00:07:42,280 Speaker 3: its second quarter deliveries. Cox Automotives Director of Industry and Slights, 136 00:07:42,320 --> 00:07:47,120 Speaker 3: Stephanie baudiestri d back on Bloomberg Tech stock. Kind of 137 00:07:47,160 --> 00:07:48,720 Speaker 3: interesting reaction here, we'll get to it. 138 00:07:48,760 --> 00:07:49,680 Speaker 2: This is Bloomberg Tech. 139 00:08:01,040 --> 00:08:04,280 Speaker 3: Tesla's released its vehicle delivery numbers for the second quarter. 140 00:08:04,360 --> 00:08:07,480 Speaker 3: The ev maker delivering four hundred and eighty thousand, one 141 00:08:07,520 --> 00:08:11,680 Speaker 3: hundred and twenty six vehicles globally, outstripping analyst estimates by 142 00:08:11,720 --> 00:08:14,160 Speaker 3: more than twenty percent. I think this is the best 143 00:08:14,200 --> 00:08:18,000 Speaker 3: second quarter that they've ever had. The stock is down 144 00:08:18,080 --> 00:08:20,600 Speaker 3: almost seven percent. It's on track for its biggest drop 145 00:08:20,880 --> 00:08:25,640 Speaker 3: in almost a year. So that's an interesting market reaction 146 00:08:25,840 --> 00:08:29,640 Speaker 3: to that news. Joining us is Bloomberg's managing editor Trepe Trudel. 147 00:08:31,160 --> 00:08:35,560 Speaker 3: So you know, this was warehead of consensus. It's a 148 00:08:35,679 --> 00:08:39,280 Speaker 3: change in the trajectory of what's been happening with Tesla's 149 00:08:39,360 --> 00:08:42,200 Speaker 3: vehicle sales story overall, what else do we need to know? 150 00:08:42,240 --> 00:08:44,760 Speaker 3: What else do we know from the limited release the 151 00:08:44,760 --> 00:08:45,559 Speaker 3: company put. 152 00:08:45,400 --> 00:08:49,160 Speaker 7: Out, Yeah, ahead of competitors, with the one big exception 153 00:08:49,280 --> 00:08:51,840 Speaker 7: of BYD, But I don't think that that's something to 154 00:08:51,920 --> 00:08:53,800 Speaker 7: really get you know, sort of too hung up on. 155 00:08:54,760 --> 00:08:57,720 Speaker 7: This is a release where the numbers are great. I mean, 156 00:08:58,000 --> 00:09:01,199 Speaker 7: it's you know, I think the expertations were low going 157 00:09:01,240 --> 00:09:04,560 Speaker 7: into this print. That being said, we did see you know, 158 00:09:04,679 --> 00:09:07,400 Speaker 7: four sessions where the stock ran up thirteen percent. So 159 00:09:07,440 --> 00:09:09,400 Speaker 7: when you kind of, you know, just pan back maybe 160 00:09:09,440 --> 00:09:12,920 Speaker 7: over the last week, is this move quite as dramatic 161 00:09:12,920 --> 00:09:15,880 Speaker 7: as it looks at first glance? Maybe not, But I think, 162 00:09:15,960 --> 00:09:18,960 Speaker 7: you know, the big takeaway here is that Tesla's vehicle 163 00:09:19,040 --> 00:09:22,480 Speaker 7: business is recovering, and also that maybe the first quarter 164 00:09:22,840 --> 00:09:25,960 Speaker 7: on the energy side was maybe a bit of a blip. 165 00:09:26,000 --> 00:09:29,520 Speaker 7: It was quite disappointing their energy storage deployments, and then 166 00:09:29,559 --> 00:09:32,880 Speaker 7: the second quarter we saw a pickup that was fairly substantial. 167 00:09:33,920 --> 00:09:36,719 Speaker 3: The limited cell cyclementry is that, you know, Europe and 168 00:09:36,800 --> 00:09:40,120 Speaker 3: China seems to be improving for Tesla. Comparing controls, Rivian 169 00:09:40,120 --> 00:09:42,760 Speaker 3: is up ten percent, and Rivian that's kind of cut 170 00:09:42,800 --> 00:09:46,160 Speaker 3: back its annual forecast for delivery and production, has now 171 00:09:46,240 --> 00:09:47,000 Speaker 3: raised it again. 172 00:09:47,040 --> 00:09:47,520 Speaker 2: What do we know? 173 00:09:48,080 --> 00:09:51,240 Speaker 7: Yeah, I think with Rivian and also with Lucid, which 174 00:09:51,280 --> 00:09:53,680 Speaker 7: is out with numbers this morning, I think the bar 175 00:09:53,920 --> 00:09:57,040 Speaker 7: has been set much lower for them because they've had 176 00:09:57,080 --> 00:10:00,240 Speaker 7: so much of an issue with kind of chasing Tesla, right. 177 00:10:00,280 --> 00:10:03,439 Speaker 7: I think there were expectations when these companies went public, 178 00:10:03,720 --> 00:10:06,959 Speaker 7: in Rivian's case, by IPO, in Lucid's by way of 179 00:10:07,679 --> 00:10:11,400 Speaker 7: SPAC deal, there were expectations that these companies would sort of, 180 00:10:11,480 --> 00:10:13,880 Speaker 7: you know, take on Musk in a much more meaningful way. 181 00:10:14,080 --> 00:10:17,640 Speaker 7: But we've really seen them struggle to gain traction. We're 182 00:10:17,640 --> 00:10:21,000 Speaker 7: seeing this morning more sort of moves at the executive 183 00:10:21,120 --> 00:10:23,760 Speaker 7: level for Lucid and with Rivian. I think, you know, 184 00:10:23,800 --> 00:10:27,600 Speaker 7: there's a lot of hopes and anticipation of the R two, 185 00:10:27,840 --> 00:10:31,080 Speaker 7: this you know, lower cost platform that's coming to market, 186 00:10:31,360 --> 00:10:34,600 Speaker 7: and if this company can execute better with these lower 187 00:10:34,600 --> 00:10:38,160 Speaker 7: priced vehicles, it unlocks maybe much more of a market 188 00:10:38,400 --> 00:10:39,640 Speaker 7: for this company going forward. 189 00:10:40,320 --> 00:10:42,400 Speaker 3: The invest created out thank you very much, as a 190 00:10:42,440 --> 00:10:46,880 Speaker 3: story that definitely merits more analysis and discussion. Stephanie Valdis 191 00:10:46,880 --> 00:10:50,720 Speaker 3: Street is the director of Industry Insights at Cox Automotive 192 00:10:50,960 --> 00:10:51,560 Speaker 3: and joins US. 193 00:10:51,600 --> 00:10:53,600 Speaker 2: Now let's start with the Tesla numba. 194 00:10:53,720 --> 00:10:56,800 Speaker 3: I mean it was we are comparing it to an 195 00:10:56,840 --> 00:11:00,360 Speaker 3: average of analysts estimates, and so from that staff point, 196 00:11:00,400 --> 00:11:03,760 Speaker 3: it was a massive surprise. You know, the other way 197 00:11:03,760 --> 00:11:05,360 Speaker 3: of looking at it is the most vehicles they've ever 198 00:11:05,440 --> 00:11:08,520 Speaker 3: delivered in a second quarter. Is there anything that you 199 00:11:08,679 --> 00:11:10,520 Speaker 3: see that explains it? 200 00:11:12,480 --> 00:11:12,720 Speaker 2: Yeah? 201 00:11:12,840 --> 00:11:15,680 Speaker 8: I think you know, the market was expecting some stabilization, 202 00:11:15,760 --> 00:11:18,920 Speaker 8: which we got, but then Tesla actually delivered some acceleration. 203 00:11:19,600 --> 00:11:21,880 Speaker 8: And when I look at the market, I think if 204 00:11:21,880 --> 00:11:25,319 Speaker 8: you look layered, it piled the onion, it's the European 205 00:11:25,400 --> 00:11:28,079 Speaker 8: market that's really I think helping Tesla in Q two. 206 00:11:28,679 --> 00:11:32,200 Speaker 8: Our estimates for Q two in the US are down. 207 00:11:32,400 --> 00:11:35,480 Speaker 8: Tesla down sales twenty percent year every year, in about 208 00:11:35,480 --> 00:11:38,400 Speaker 8: two point two percent quarter over quarter. So I think 209 00:11:38,400 --> 00:11:41,719 Speaker 8: the European market is really driving sales for Tesla and 210 00:11:41,800 --> 00:11:44,520 Speaker 8: Q two. And you know it makes sense. The German, 211 00:11:44,720 --> 00:11:48,920 Speaker 8: the French and Sentence came back high gas prices, right, 212 00:11:49,080 --> 00:11:53,200 Speaker 8: That's another headwind that really our tailwind that helped Tesla 213 00:11:53,280 --> 00:11:55,040 Speaker 8: in Q two. So I think that's kind of looking 214 00:11:55,040 --> 00:11:57,760 Speaker 8: at it broadly, that's what's really helped TESSELA in Q two. 215 00:11:58,720 --> 00:12:03,240 Speaker 3: Yeah, the high oil price and gas prices narrative is 216 00:12:03,280 --> 00:12:06,480 Speaker 3: very interesting. What you were talking there about, you know, 217 00:12:06,559 --> 00:12:10,840 Speaker 3: Europe relative to other markets from a regulatory or consumer 218 00:12:10,880 --> 00:12:12,400 Speaker 3: in center standpoint is interesting. 219 00:12:13,080 --> 00:12:14,079 Speaker 2: Where are we at. 220 00:12:13,920 --> 00:12:17,199 Speaker 3: In this kind of multi speed market where Europe was 221 00:12:17,240 --> 00:12:20,280 Speaker 3: ahead on adoption anyway, China was ahead and has a 222 00:12:20,360 --> 00:12:24,199 Speaker 3: much greater proportion of new energy vehicle sales but pure 223 00:12:24,320 --> 00:12:40,000 Speaker 3: battery electric sales relatives to the US anyway. 224 00:12:36,559 --> 00:12:38,760 Speaker 8: China and the US, and I think the one thing 225 00:12:38,800 --> 00:12:43,440 Speaker 8: in Europe right they have once again, they have better infrastructure, 226 00:12:43,880 --> 00:12:47,040 Speaker 8: they have the incentives coming back. China's kind of slowing down, 227 00:12:47,360 --> 00:12:51,480 Speaker 8: but the Chinese OEMs right. They're exporting to all these countries, 228 00:12:51,520 --> 00:12:53,840 Speaker 8: so they're gaining share, and so I think they're providing 229 00:12:53,880 --> 00:12:57,080 Speaker 8: a lot of affordable evs. So I think the European 230 00:12:57,080 --> 00:13:00,439 Speaker 8: market's going to continue to grow. I had a allegue 231 00:13:00,480 --> 00:13:04,600 Speaker 8: post something earlier today saying in Australia for the second 232 00:13:04,800 --> 00:13:07,200 Speaker 8: month at a row, Tesla is number one, and so 233 00:13:07,280 --> 00:13:09,560 Speaker 8: I think Tesla's trying to it's find its way to 234 00:13:09,679 --> 00:13:12,400 Speaker 8: kind of beat out some of the Chinese OEMs. But 235 00:13:12,480 --> 00:13:14,280 Speaker 8: I think there's a lot of competition. If you look 236 00:13:14,280 --> 00:13:16,280 Speaker 8: at the second half of this year, they're going to 237 00:13:16,280 --> 00:13:18,720 Speaker 8: have to contend with that as well, in both Europe 238 00:13:18,760 --> 00:13:19,680 Speaker 8: and China market. 239 00:13:20,559 --> 00:13:22,520 Speaker 3: Stephanie, I looked a little confused for a second there 240 00:13:22,559 --> 00:13:24,960 Speaker 3: because we lost your microphone just for the first five 241 00:13:25,000 --> 00:13:26,240 Speaker 3: seconds of your answer on that. 242 00:13:26,400 --> 00:13:30,120 Speaker 2: But I think we have you back. Worry not right now. 243 00:13:30,720 --> 00:13:34,480 Speaker 3: I think there is a big focus on probably still 244 00:13:34,600 --> 00:13:37,760 Speaker 3: consumer spending power and affordability. So you had told us 245 00:13:37,760 --> 00:13:42,120 Speaker 3: that your your data pointed to a Tesla sales decline 246 00:13:42,120 --> 00:13:45,320 Speaker 3: in the United States market. What's the bigger picture of 247 00:13:45,360 --> 00:13:47,199 Speaker 3: the US auto buyer right now? 248 00:13:51,280 --> 00:13:54,199 Speaker 8: The price premium between a new EV and a new 249 00:13:54,240 --> 00:13:56,720 Speaker 8: ICE vehicle's got into about fifty five hundred, so the 250 00:13:56,760 --> 00:13:59,760 Speaker 8: lowest it's ever been. But that's more about a product. 251 00:14:01,000 --> 00:14:03,440 Speaker 8: But I think looking forward to the rest of the year, 252 00:14:03,480 --> 00:14:06,840 Speaker 8: you have some more affordable EV's launching. You have you know, 253 00:14:06,920 --> 00:14:10,920 Speaker 8: Toyota has a CHR, the Woodland has come out. You 254 00:14:10,960 --> 00:14:13,959 Speaker 8: have Subaru launching a couple, so I think there's some 255 00:14:14,040 --> 00:14:15,880 Speaker 8: new product coming out. But the end of the day, 256 00:14:15,920 --> 00:14:18,800 Speaker 8: I think getting that monthly payment down is the biggest 257 00:14:18,880 --> 00:14:21,840 Speaker 8: prohibitor for any vieh of right and especially for EV's 258 00:14:21,840 --> 00:14:24,320 Speaker 8: where there's still a price premium. So I think at 259 00:14:24,360 --> 00:14:26,600 Speaker 8: the end of the day, we need more affordable evs 260 00:14:26,680 --> 00:14:29,400 Speaker 8: launched in the US and that's going to help. Fortunately, 261 00:14:29,440 --> 00:14:32,200 Speaker 8: we're seeing infrastructure growth, so I think that's a positive sign. 262 00:14:32,800 --> 00:14:36,240 Speaker 8: But once again, I think the affordability continues to be 263 00:14:36,320 --> 00:14:38,800 Speaker 8: the theme throughout the automotive sector. 264 00:14:40,360 --> 00:14:43,520 Speaker 3: Director of Industry in sits at Cox Automotive, Stephanie BALDESTRIDI 265 00:14:43,600 --> 00:14:44,520 Speaker 3: back on Bloomberg Tech. 266 00:14:44,560 --> 00:14:46,360 Speaker 2: It's been great to have you, Thank you very much. 267 00:14:46,720 --> 00:14:47,760 Speaker 2: A now the news story. 268 00:14:47,960 --> 00:14:51,840 Speaker 3: Uber has dismissed two tech leaders at its nascent AI 269 00:14:52,000 --> 00:14:56,280 Speaker 3: data labeling business, shaking up a key division that the 270 00:14:56,360 --> 00:14:58,560 Speaker 3: right Hail company is positioned as a key growth driver. 271 00:14:58,840 --> 00:15:01,360 Speaker 3: Uba says the departures are part of a broader leadership 272 00:15:01,400 --> 00:15:05,080 Speaker 3: transition at the division. The unit, which launched in twenty 273 00:15:05,080 --> 00:15:09,000 Speaker 3: twenty four, uses a network of gig workers to handle 274 00:15:09,080 --> 00:15:13,600 Speaker 3: tasks needed for preparing data to be used in AI models. 275 00:15:14,120 --> 00:15:15,160 Speaker 2: Okay, coming up, we're. 276 00:15:15,000 --> 00:15:17,560 Speaker 3: Going to take the pulse of tech markets with Fionas 277 00:15:17,640 --> 00:15:21,240 Speaker 3: Encoder from City Index. In what is a short week 278 00:15:21,280 --> 00:15:23,880 Speaker 3: here in the United States for trading days, but. 279 00:15:23,960 --> 00:15:25,720 Speaker 2: A lot to discuss. This is Bloomberg Tech. 280 00:15:35,400 --> 00:15:38,920 Speaker 3: US hiring slowed sharply last month, with non farm pay 281 00:15:39,000 --> 00:15:42,040 Speaker 3: rolls rise by just fifty seven thousand. The jobs market 282 00:15:42,120 --> 00:15:45,840 Speaker 3: is facing headwinds from the Iran war, but also downbeat 283 00:15:46,080 --> 00:15:49,360 Speaker 3: consumer sentiment. When it comes to tech's impact, these figures 284 00:15:49,400 --> 00:15:54,680 Speaker 3: show manufacturing construction jobs rose, possibly linked to the AI buildout, 285 00:15:54,720 --> 00:15:58,160 Speaker 3: while as we discussed yesterday, big tech firms have been 286 00:15:58,200 --> 00:16:02,520 Speaker 3: cutting rolls to offset AI spending. Kind of competing dynamics. 287 00:16:02,760 --> 00:16:06,280 Speaker 3: This is what markets look like and how the technology 288 00:16:06,320 --> 00:16:09,000 Speaker 3: sector has kind of reacted in part to that job 289 00:16:09,040 --> 00:16:11,160 Speaker 3: sat And as that one hundred is down one point 290 00:16:11,200 --> 00:16:15,080 Speaker 3: four percent, the Philadelphia Semiconductor Index or SOCKS is. 291 00:16:15,040 --> 00:16:16,960 Speaker 2: Down four and a half percent. 292 00:16:17,000 --> 00:16:20,240 Speaker 3: We've seen big swings in both directions on the SOCKS. 293 00:16:19,920 --> 00:16:21,680 Speaker 2: For a couple of weeks. 294 00:16:21,680 --> 00:16:24,400 Speaker 3: Now we're on track for back to back weekly declines 295 00:16:24,800 --> 00:16:28,280 Speaker 3: on the SOCKS for the first time since March. Then, 296 00:16:28,320 --> 00:16:31,000 Speaker 3: as that one hundred on the week still up a 297 00:16:31,040 --> 00:16:33,640 Speaker 3: percentage fright, I say on the week it is a 298 00:16:33,680 --> 00:16:36,080 Speaker 3: short week, it is a holiday in the United States 299 00:16:36,520 --> 00:16:40,360 Speaker 3: tomorrow Friday, July third. Because of the July fourth holiday, 300 00:16:40,680 --> 00:16:42,920 Speaker 3: the socks down three point four percent, and as I said, 301 00:16:42,960 --> 00:16:45,920 Speaker 3: back to back weekly drops again a shortened week. Let's 302 00:16:45,960 --> 00:16:48,600 Speaker 3: get more on what's happening in markets. Fiona Sinkoda, City 303 00:16:48,640 --> 00:16:52,320 Speaker 3: Index senior market analyst joins us, I guess let's start 304 00:16:52,360 --> 00:16:54,800 Speaker 3: with the moment in time that was the latest economic data. 305 00:16:55,200 --> 00:16:57,800 Speaker 3: And what I did not say in a bit of 306 00:16:57,800 --> 00:17:00,720 Speaker 3: a ramble just then, was you know how the market's 307 00:17:00,760 --> 00:17:03,240 Speaker 3: recalculating what they think the Fed will do this year, 308 00:17:03,240 --> 00:17:05,800 Speaker 3: pushing back the idea of a hike to December. 309 00:17:06,080 --> 00:17:07,040 Speaker 2: Why is that important? 310 00:17:08,920 --> 00:17:10,800 Speaker 9: So, I mean, the fact that we've got the market 311 00:17:10,840 --> 00:17:14,960 Speaker 9: getting a little bit of bland about what Federal Reserve 312 00:17:15,080 --> 00:17:18,480 Speaker 9: could be doing with interest rates is sort of helping 313 00:17:18,640 --> 00:17:22,000 Speaker 9: investors sort of reassess where they're positioning. And the reason 314 00:17:22,080 --> 00:17:25,600 Speaker 9: this is important is because when you have higher interest rates, 315 00:17:26,400 --> 00:17:30,359 Speaker 9: you often find that this weighs on high growth tech 316 00:17:30,400 --> 00:17:35,240 Speaker 9: stocks just because of their future valuations, so they're less 317 00:17:35,320 --> 00:17:36,359 Speaker 9: valuable in the future. 318 00:17:36,400 --> 00:17:38,040 Speaker 10: If we've got higher interest rates. 319 00:17:39,040 --> 00:17:41,480 Speaker 9: Now, the fact that we've got those interest rate hike 320 00:17:41,680 --> 00:17:47,280 Speaker 9: expectations decreasing is usually beneficial for tech stocks, so we 321 00:17:47,320 --> 00:17:51,720 Speaker 9: would usually expect that to see and actually an increase 322 00:17:51,960 --> 00:17:54,800 Speaker 9: in the textos, but that's interestingly, is not what we're 323 00:17:54,800 --> 00:17:57,720 Speaker 9: necessarily seeing today. And I do think that this is 324 00:17:57,760 --> 00:18:03,520 Speaker 9: potentially related to, you know, some concerns over that sort 325 00:18:03,560 --> 00:18:07,800 Speaker 9: of AI trade, the really strong rally that we've seen 326 00:18:08,480 --> 00:18:12,239 Speaker 9: in memory stocks and chip stocks and tech stocks, and 327 00:18:12,480 --> 00:18:14,919 Speaker 9: you know, we're seeing some profit taking, as you've mentioned, 328 00:18:14,960 --> 00:18:17,320 Speaker 9: we've seen a couple of weeks now where we've seen 329 00:18:17,400 --> 00:18:21,679 Speaker 9: some lower closes, and I think this is all just 330 00:18:21,720 --> 00:18:24,160 Speaker 9: coming ahead of earning season, you know, I think we're 331 00:18:24,240 --> 00:18:28,199 Speaker 9: just seeing this recalibration and repositioning because obviously, you know, 332 00:18:28,720 --> 00:18:31,479 Speaker 9: investors are nervous that there is a potential for this 333 00:18:31,560 --> 00:18:34,320 Speaker 9: rally to have overextended, and so I think that's what 334 00:18:34,359 --> 00:18:35,840 Speaker 9: we're seeing Clay out right now. 335 00:18:37,760 --> 00:18:41,480 Speaker 3: One of the drivers of this market has been semiconductors, 336 00:18:41,480 --> 00:18:44,159 Speaker 3: but in particular memory, and something that keeps coming up 337 00:18:44,240 --> 00:18:46,600 Speaker 3: time and time again on the show is that if 338 00:18:46,640 --> 00:18:50,560 Speaker 3: you take Micron as a case study, it's quite reasonably valued, 339 00:18:50,800 --> 00:18:53,960 Speaker 3: you know, based on forward twelve months price to earnings, 340 00:18:54,680 --> 00:18:56,960 Speaker 3: and the question for everyone in the market, well, what 341 00:18:57,000 --> 00:18:59,080 Speaker 3: happens next, right, Does it continue to go on the 342 00:18:59,160 --> 00:19:01,639 Speaker 3: run that it is has been? Is that where you 343 00:19:01,760 --> 00:19:05,359 Speaker 3: look kind of at a sort of fundamentals and valuation level. 344 00:19:06,680 --> 00:19:08,320 Speaker 10: Yes, I think you've got to take into quite a 345 00:19:08,359 --> 00:19:09,120 Speaker 10: few things. 346 00:19:09,160 --> 00:19:11,920 Speaker 9: In you look at the fundamentals evaluation, you also need 347 00:19:11,960 --> 00:19:13,000 Speaker 9: to look at the technicals. 348 00:19:13,400 --> 00:19:17,280 Speaker 10: Is the rally overrun? Is it in overbought territory? 349 00:19:17,400 --> 00:19:19,199 Speaker 9: But then we've also got to have a look at 350 00:19:19,200 --> 00:19:22,040 Speaker 9: the bigger macro picture as well. As we've talked about here. 351 00:19:22,240 --> 00:19:25,760 Speaker 9: You know, the potential for federal reserve rate hikes or not. 352 00:19:25,880 --> 00:19:29,840 Speaker 9: I think also does have some sort of implication and 353 00:19:29,960 --> 00:19:32,720 Speaker 9: where we are, so, you know, taking all that into account. 354 00:19:32,760 --> 00:19:34,480 Speaker 9: But I mean what we have seen, as you said, 355 00:19:34,600 --> 00:19:39,080 Speaker 9: is this phenomenal rally in the memory chips memory stock 356 00:19:39,560 --> 00:19:41,719 Speaker 9: chip stocks as well, And so I think there is 357 00:19:42,240 --> 00:19:43,960 Speaker 9: naturally going to be pullbacks. 358 00:19:44,000 --> 00:19:45,800 Speaker 10: I mean, we know these stocks don't just. 359 00:19:45,840 --> 00:19:49,720 Speaker 9: Go up, but if it is considered to be reasonably priced, 360 00:19:49,760 --> 00:19:51,000 Speaker 9: which is what we're seeing. 361 00:19:50,800 --> 00:19:53,600 Speaker 10: Right now, then that does leave a potential for further games. 362 00:19:55,000 --> 00:19:58,640 Speaker 3: Another big technology news story today, SAP will cut back 363 00:19:58,720 --> 00:20:02,360 Speaker 3: hiring and travel to save costs as it devotes more 364 00:20:02,440 --> 00:20:06,399 Speaker 3: resources to developing AI and fending off new competitors. According 365 00:20:06,440 --> 00:20:09,000 Speaker 3: to an email to staff from the executive board that 366 00:20:09,080 --> 00:20:13,280 Speaker 3: was reviewed by Bloomberg, SAP will quote exclusively focus new 367 00:20:13,359 --> 00:20:18,040 Speaker 3: hiring on selected profiles only mainly core AI roles that 368 00:20:18,119 --> 00:20:22,680 Speaker 3: are critical for our long term success end quote. I 369 00:20:23,560 --> 00:20:25,359 Speaker 3: wanted to do that news story because I think it's 370 00:20:25,400 --> 00:20:27,800 Speaker 3: something that's crossed your desk this morning, right, and that 371 00:20:27,840 --> 00:20:30,119 Speaker 3: you have seen in the news cycle. What do you 372 00:20:30,160 --> 00:20:33,520 Speaker 3: make of that, particularly in the European tech context as 373 00:20:33,560 --> 00:20:34,240 Speaker 3: a case study. 374 00:20:35,160 --> 00:20:37,280 Speaker 9: Yeah, So I think this is really interesting because I 375 00:20:37,280 --> 00:20:39,840 Speaker 9: mean there's very much a focus I think of, you know, 376 00:20:40,080 --> 00:20:43,239 Speaker 9: how are businesses dealing with these increased costs, how are 377 00:20:43,240 --> 00:20:43,720 Speaker 9: they going. 378 00:20:43,600 --> 00:20:44,400 Speaker 10: To balance them out? 379 00:20:44,680 --> 00:20:47,560 Speaker 9: What it means for hiring as well, you know, from 380 00:20:47,720 --> 00:20:52,160 Speaker 9: from from a personal perspective and for you know, people 381 00:20:52,200 --> 00:20:54,840 Speaker 9: looking for jobs. So the fact that they are looking 382 00:20:54,960 --> 00:20:55,960 Speaker 9: to sort of. 383 00:20:56,119 --> 00:20:58,840 Speaker 10: Rain in spending in one area in. 384 00:20:58,920 --> 00:21:02,240 Speaker 9: Order to be able to fous on you know, the 385 00:21:02,240 --> 00:21:07,000 Speaker 9: the that AI related investment is really interesting because obviously 386 00:21:07,000 --> 00:21:09,080 Speaker 9: that's what we do want to see. We can't just 387 00:21:09,280 --> 00:21:11,480 Speaker 9: continue to spend without the means to doing it. 388 00:21:11,840 --> 00:21:12,720 Speaker 10: But also this. 389 00:21:12,800 --> 00:21:16,120 Speaker 9: Idea that they are going to continue hiring for very 390 00:21:16,200 --> 00:21:21,040 Speaker 9: AI specific positions I think is really key. I think 391 00:21:21,080 --> 00:21:23,359 Speaker 9: this is just something that we are sort of thinking 392 00:21:23,359 --> 00:21:27,200 Speaker 9: about more broadly, as you know, what does employment, what 393 00:21:27,240 --> 00:21:29,800 Speaker 9: does hiring look like in this sort of. 394 00:21:29,760 --> 00:21:31,000 Speaker 10: New AI world? 395 00:21:31,080 --> 00:21:34,879 Speaker 9: And there obviously been some sort of changing perspectives, you know, 396 00:21:35,000 --> 00:21:36,840 Speaker 9: does it mean loads of layoffs? 397 00:21:37,520 --> 00:21:39,359 Speaker 10: You know, such as Oracle. 398 00:21:39,000 --> 00:21:42,959 Speaker 9: We've seen them laying off staff and citing the reason 399 00:21:43,119 --> 00:21:45,800 Speaker 9: for job carts as AI. 400 00:21:46,119 --> 00:21:47,080 Speaker 10: But then you've also. 401 00:21:46,920 --> 00:21:50,359 Speaker 9: Got Federal Reserve to Kevin Walsh yesterday who was actually 402 00:21:50,400 --> 00:21:53,720 Speaker 9: suggesting the opposite, that technical innovations have the potential to 403 00:21:53,760 --> 00:21:55,800 Speaker 9: lift productivity and increase employment. 404 00:21:56,480 --> 00:21:59,560 Speaker 10: So this is definitely sort of an argument that we're 405 00:21:59,600 --> 00:22:00,000 Speaker 10: looking at. 406 00:22:00,119 --> 00:22:02,680 Speaker 9: But for the SAP to hear that they are actually 407 00:22:02,720 --> 00:22:06,920 Speaker 9: making clear decisions to going towards AI, I think should 408 00:22:06,960 --> 00:22:08,840 Speaker 9: be a good thing for the company. 409 00:22:09,680 --> 00:22:12,680 Speaker 3: Piano Sincodo a City Index, Thank you very much. Indeed, 410 00:22:12,720 --> 00:22:16,920 Speaker 3: now coming up Judson Althoff, CEO of Microsoft's commercial businesses 411 00:22:17,000 --> 00:22:19,840 Speaker 3: joining us. They're making a two point five billion dollar 412 00:22:19,920 --> 00:22:25,320 Speaker 3: bet on forward deployed Engineers FDE. We're going to discuss that. 413 00:22:25,359 --> 00:22:28,560 Speaker 3: Next is halftime here in San Francisco. Do not go 414 00:22:28,640 --> 00:22:30,560 Speaker 3: far We've got so much more to come in the show. 415 00:22:30,640 --> 00:22:41,080 Speaker 3: This is Bloomberg Tech. Welcome back to Bloomberg Tech. We're 416 00:22:41,119 --> 00:22:43,360 Speaker 3: taking a very quick look at shares of SpaceX. It's 417 00:22:43,440 --> 00:22:46,520 Speaker 3: kind of been interesting to track what has been up 418 00:22:46,560 --> 00:22:49,000 Speaker 3: and down in a little bit sideways trading one hundred 419 00:22:49,000 --> 00:22:52,040 Speaker 3: and fifty seven one hundred and fifty eight dollars a share. 420 00:22:52,080 --> 00:22:54,040 Speaker 3: Remember this is an IPO. The price one hundred and 421 00:22:54,080 --> 00:22:56,600 Speaker 3: thirty five, the opening trade was one hundred and fifty 422 00:22:56,960 --> 00:22:59,680 Speaker 3: and now we're getting more information. One of the key 423 00:22:59,720 --> 00:23:04,280 Speaker 3: questions asked about the Ela Muscle company is it valued properly? 424 00:23:04,440 --> 00:23:07,320 Speaker 3: Next week, investors may get a clearer picture when a 425 00:23:07,359 --> 00:23:10,359 Speaker 3: host of you research, price targets and growth estaments come 426 00:23:10,400 --> 00:23:13,720 Speaker 3: out from the banks that worked on the IPO. Bloombos 427 00:23:13,760 --> 00:23:16,600 Speaker 3: Carmen Rhinikey is here with the dates come and what. 428 00:23:16,560 --> 00:23:17,119 Speaker 2: Do we need to know? 429 00:23:17,480 --> 00:23:19,560 Speaker 11: Yeah, so what we need to know here is just 430 00:23:19,760 --> 00:23:23,639 Speaker 11: exactly how Wall Street is going to or justify this 431 00:23:23,840 --> 00:23:26,600 Speaker 11: huge valuation that we're seeing on SpaceX. So we have 432 00:23:26,680 --> 00:23:29,080 Speaker 11: a little bit of an indication here, right. We've gotten 433 00:23:29,200 --> 00:23:32,760 Speaker 11: some analyst research in the week since the blockbuster IPO 434 00:23:32,840 --> 00:23:35,520 Speaker 11: from banks that were not involved in that process, so 435 00:23:35,880 --> 00:23:38,040 Speaker 11: we know now we can see that the price to 436 00:23:38,080 --> 00:23:40,600 Speaker 11: sales ratio for SpaceX, which has always been quite high, 437 00:23:40,680 --> 00:23:43,760 Speaker 11: is trading much higher than its peers, even ones like 438 00:23:43,880 --> 00:23:47,960 Speaker 11: Palenteer and a software defense company that is often called 439 00:23:47,960 --> 00:23:50,240 Speaker 11: out as having one of the highest valuations in the 440 00:23:50,320 --> 00:23:53,360 Speaker 11: s and P five hundred and Microsoft. So, for example, 441 00:23:53,480 --> 00:23:56,080 Speaker 11: Microsoft trades at a much lower price to sales ratio 442 00:23:56,119 --> 00:23:58,760 Speaker 11: than SpaceX and is expected to bring in about ten 443 00:23:58,880 --> 00:24:02,760 Speaker 11: times the revenue this year as SpaceX, which is about 444 00:24:02,840 --> 00:24:06,439 Speaker 11: thirty six billion four SpaceX more than three hundred billion 445 00:24:06,680 --> 00:24:10,320 Speaker 11: for Microsoft. Something that is key here to these large 446 00:24:10,400 --> 00:24:14,560 Speaker 11: valuations is explosive revenue growth that Wall Street is seeing. 447 00:24:14,640 --> 00:24:19,439 Speaker 11: So our own Bloomberg Intelligence analysts see that SpaceX could 448 00:24:19,600 --> 00:24:22,400 Speaker 11: swing to a slight profit by twenty twenty eight and 449 00:24:22,480 --> 00:24:25,240 Speaker 11: see it's revenue growth more than go more than eight 450 00:24:25,320 --> 00:24:28,640 Speaker 11: hundred percent by twenty thirty. So other estimates that we're 451 00:24:28,640 --> 00:24:31,960 Speaker 11: seeing so far are seeing this more than quadruple into 452 00:24:31,960 --> 00:24:34,439 Speaker 11: twenty twenty eight as well, and this is really going 453 00:24:34,520 --> 00:24:37,640 Speaker 11: to be key to what we're looking at when more 454 00:24:37,760 --> 00:24:41,400 Speaker 11: of these estimates and analyst reports come out next week, 455 00:24:41,440 --> 00:24:44,679 Speaker 11: so it should be Tuesday. That's twenty five days since 456 00:24:45,040 --> 00:24:47,600 Speaker 11: the IPO. This is when the quiet period ends, and 457 00:24:47,880 --> 00:24:51,280 Speaker 11: the most important things that we'll be getting are analyst 458 00:24:51,320 --> 00:24:55,720 Speaker 11: research from banks that underwrote the IPO. So that includes Goldman, Sachs, Morgan, Stanley, 459 00:24:55,760 --> 00:24:59,960 Speaker 11: Bank of America, GP Morgan, and eighteen other banks that participate. 460 00:25:00,600 --> 00:25:02,640 Speaker 2: Back to you, Ed, I wonder. 461 00:25:02,400 --> 00:25:04,560 Speaker 3: If they'll be bullish when they come out with those reports. 462 00:25:04,600 --> 00:25:08,520 Speaker 3: Wimbers come, Ryanicky, thank you very much. Indeed, Microsoft is 463 00:25:08,560 --> 00:25:12,199 Speaker 3: mobilizing six thousand people in a new unit aimed at 464 00:25:12,280 --> 00:25:17,720 Speaker 3: helping enterprise clients better utilize AI. We're talking forward deployed 465 00:25:18,080 --> 00:25:21,160 Speaker 3: Engineers FDE. It's a step we've seen from other tech 466 00:25:21,240 --> 00:25:24,360 Speaker 3: firms quite a lot recently. So what's driving the move? 467 00:25:24,560 --> 00:25:28,119 Speaker 3: What impact does Microsoft hope to see? Judson Otof, CEO 468 00:25:28,440 --> 00:25:33,200 Speaker 3: of Microsoft's Commercial business, joins us from Microsoft campus in Redmond, Washington. 469 00:25:33,440 --> 00:25:36,720 Speaker 3: I think the best place to start with this justin 470 00:25:36,800 --> 00:25:39,840 Speaker 3: is what was Microsoft trying to solve for right? What 471 00:25:39,960 --> 00:25:44,359 Speaker 3: was identified among the very diverse and wide base of 472 00:25:44,359 --> 00:25:47,439 Speaker 3: customers that Microsoft has that would say, Okay, we actually 473 00:25:47,520 --> 00:25:49,320 Speaker 3: need these people to go in and do this. 474 00:25:50,600 --> 00:25:53,159 Speaker 6: Well, Thanks Ed for taking the time today. I appreciate it. 475 00:25:53,200 --> 00:25:56,600 Speaker 12: We're really excited about the launch of Microsoft Frontier Company. 476 00:25:56,880 --> 00:25:59,879 Speaker 12: The aim of the business is really to help customers 477 00:26:00,600 --> 00:26:04,840 Speaker 12: drive frontier transformation across their businesses. It's about their outcomes, 478 00:26:04,880 --> 00:26:08,760 Speaker 12: about them getting value out of AI while having intelligence 479 00:26:08,800 --> 00:26:12,320 Speaker 12: compound within their organization so that they're taking control of 480 00:26:12,359 --> 00:26:15,119 Speaker 12: the outcomes that AI drives, versus the other way around. 481 00:26:15,200 --> 00:26:18,399 Speaker 12: So we felt it was necessary to assemble a world 482 00:26:18,400 --> 00:26:21,399 Speaker 12: class team with the right skill, the right scale, and 483 00:26:21,440 --> 00:26:23,560 Speaker 12: the right platform to drive these outcomes. 484 00:26:24,840 --> 00:26:28,239 Speaker 3: The bearish view on this is that those companies just 485 00:26:28,320 --> 00:26:30,359 Speaker 3: haven't been able to work out yet what to do 486 00:26:30,400 --> 00:26:30,840 Speaker 3: with AI. 487 00:26:32,080 --> 00:26:33,119 Speaker 2: Is that? Is that fair? 488 00:26:34,320 --> 00:26:37,000 Speaker 12: I think the thing to really grasp here is that 489 00:26:37,080 --> 00:26:38,600 Speaker 12: AI has to serve the business. 490 00:26:38,640 --> 00:26:40,240 Speaker 6: It has to serve business outcomes. 491 00:26:40,280 --> 00:26:44,920 Speaker 12: It's less about deploying FDEs to just simply drive AI adoption, 492 00:26:45,280 --> 00:26:49,840 Speaker 12: but rather infusing the right level of skill around industry expertise, 493 00:26:49,960 --> 00:26:53,119 Speaker 12: around change management and continuous improvement, and then of course 494 00:26:53,160 --> 00:26:56,439 Speaker 12: world class AI engineering. That's what's really different about what 495 00:26:56,480 --> 00:26:59,159 Speaker 12: we're doing with Microsoft Frontier Company. Sure, we're going to 496 00:26:59,200 --> 00:27:01,080 Speaker 12: put a lot of great en on the ground at 497 00:27:01,080 --> 00:27:03,520 Speaker 12: customers to help them with AI, but we're first going 498 00:27:03,560 --> 00:27:06,480 Speaker 12: to be methodical about making sure that the AI solutions 499 00:27:06,480 --> 00:27:09,359 Speaker 12: that they're building are really driving business outcomes and that 500 00:27:09,400 --> 00:27:12,000 Speaker 12: are infused into the way they work. AI has to 501 00:27:12,000 --> 00:27:15,600 Speaker 12: empower human ambition and it has to empower AI outcomes 502 00:27:15,359 --> 00:27:18,320 Speaker 12: for customers, and that's where we're really focused here. That's 503 00:27:18,359 --> 00:27:20,560 Speaker 12: differentiated from how others are approaching this. 504 00:27:22,119 --> 00:27:24,760 Speaker 3: That different from how others approach this is really interesting. 505 00:27:24,920 --> 00:27:27,439 Speaker 3: I talked to a lot of FDEs, you know, all 506 00:27:27,520 --> 00:27:30,400 Speaker 3: kinds of companies that they would probably point out right 507 00:27:30,440 --> 00:27:33,680 Speaker 3: that there is a distinction between forward deployed engineer the 508 00:27:33,800 --> 00:27:38,840 Speaker 3: noun and forward deployed engineering the verb, right, what the 509 00:27:39,480 --> 00:27:42,880 Speaker 3: actual outcome Microsoft trying to affect is. So I think 510 00:27:42,880 --> 00:27:45,640 Speaker 3: that the question I have few does is how much 511 00:27:45,720 --> 00:27:48,639 Speaker 3: is this a go to market enablement and strategy for 512 00:27:48,720 --> 00:27:51,359 Speaker 3: you guys, or is it a way for you to 513 00:27:51,440 --> 00:27:54,840 Speaker 3: build out a product, a specific Microsoft product. 514 00:27:56,119 --> 00:27:56,840 Speaker 6: It's a great question. 515 00:27:56,880 --> 00:27:59,800 Speaker 12: I'm really glad that you asked that because it's super 516 00:28:00,000 --> 00:28:03,680 Speaker 12: important to understand how customers get value out of these 517 00:28:03,720 --> 00:28:06,560 Speaker 12: types of investments and frankly, what's left behind. 518 00:28:06,920 --> 00:28:08,159 Speaker 6: We're really really. 519 00:28:07,920 --> 00:28:11,359 Speaker 12: Focused on our customers intelligence and their outcome. So every 520 00:28:11,400 --> 00:28:13,199 Speaker 12: bit of work that we do at the face of 521 00:28:13,240 --> 00:28:16,640 Speaker 12: the customer is going to be about compounding their intelligence 522 00:28:16,800 --> 00:28:20,400 Speaker 12: and their unique value. So any IP that's built, any 523 00:28:20,560 --> 00:28:25,120 Speaker 12: data and semantic context that's derived, the evaluation thinking, all 524 00:28:25,119 --> 00:28:27,199 Speaker 12: of that belongs to the customer at the end of 525 00:28:27,200 --> 00:28:31,040 Speaker 12: the engagement, which is fairly differentiated here. Again, the skill 526 00:28:31,080 --> 00:28:34,200 Speaker 12: sets required to do this, I think are quite unique. 527 00:28:34,359 --> 00:28:37,159 Speaker 12: We've got folks that have been in banking for twenty years, 528 00:28:37,200 --> 00:28:40,840 Speaker 12: in retail for twenty years. Energy life science is getting 529 00:28:40,880 --> 00:28:43,800 Speaker 12: to the meat of what customers actually need to achieve 530 00:28:43,800 --> 00:28:46,160 Speaker 12: with their business, Putting the right folks on the ground 531 00:28:46,160 --> 00:28:49,600 Speaker 12: that actually understand how to evolve the business process, getting 532 00:28:49,600 --> 00:28:52,720 Speaker 12: the right AI capabilities in place, and then establishing a 533 00:28:52,760 --> 00:28:55,680 Speaker 12: continuous loop of improvement so that you know, whether it's 534 00:28:55,680 --> 00:28:59,400 Speaker 12: the supply chain or the finance organization or the HR organization, 535 00:28:59,840 --> 00:29:03,880 Speaker 12: the agentic business flows that we're establishing continuously get better 536 00:29:04,000 --> 00:29:07,600 Speaker 12: through model diversity and openness and optimization, and then what's 537 00:29:07,720 --> 00:29:11,880 Speaker 12: left behind is really unique intelligence for the customer. Of course, 538 00:29:11,960 --> 00:29:13,440 Speaker 12: if there are things that we have to do in 539 00:29:13,440 --> 00:29:16,760 Speaker 12: the Microsoft platform to make our assets better to serve 540 00:29:16,800 --> 00:29:18,600 Speaker 12: the customer, we're going to do that too. 541 00:29:18,720 --> 00:29:20,120 Speaker 6: That's the unique linkage of. 542 00:29:20,440 --> 00:29:24,320 Speaker 12: The forward deployed engineering into the Microsoft engineering teams to 543 00:29:24,400 --> 00:29:26,240 Speaker 12: better serve the customer. But really, at the end of 544 00:29:26,280 --> 00:29:29,360 Speaker 12: the day, the outcomes that are delivered belong to the customer, 545 00:29:29,400 --> 00:29:31,040 Speaker 12: and that's what's really unique here. 546 00:29:31,960 --> 00:29:36,480 Speaker 3: The composition of that six thousand people as a group. 547 00:29:36,800 --> 00:29:38,280 Speaker 2: I find that fascinating. 548 00:29:38,760 --> 00:29:40,600 Speaker 3: You're saying that this is a two point five billion 549 00:29:40,640 --> 00:29:44,240 Speaker 3: dollar investment into what is a unit. But I think 550 00:29:44,240 --> 00:29:46,280 Speaker 3: we've spent a lot of time Judson is you know, 551 00:29:46,400 --> 00:29:50,800 Speaker 3: talking about the cost of talent, particularly on the engineering side, 552 00:29:50,920 --> 00:29:54,880 Speaker 3: and you know even on research. How competitively are you 553 00:29:54,920 --> 00:29:57,600 Speaker 3: going to have to put together that group. 554 00:29:57,400 --> 00:29:59,680 Speaker 2: Of six thousand? Where will you hire them from? 555 00:29:59,720 --> 00:29:59,760 Speaker 5: You? 556 00:29:59,800 --> 00:30:02,720 Speaker 3: Men banks, I think the consulting firms would be a 557 00:30:02,720 --> 00:30:04,840 Speaker 3: little fearful that they will have people go to this. 558 00:30:06,240 --> 00:30:08,280 Speaker 12: I think the thing to really latch on to here 559 00:30:08,400 --> 00:30:12,320 Speaker 12: is the notion of model diversity. Customers understand the business 560 00:30:12,320 --> 00:30:15,240 Speaker 12: processes that need to be evolved, and when I talk 561 00:30:15,280 --> 00:30:17,920 Speaker 12: to CEOs and when I talk to their boards, it's 562 00:30:17,920 --> 00:30:20,280 Speaker 12: super clear that they want to shift left and shift right, 563 00:30:20,680 --> 00:30:23,080 Speaker 12: put the bulk of their employee skill and working on 564 00:30:23,760 --> 00:30:26,720 Speaker 12: engaging with customers and developing new products, and then to 565 00:30:26,800 --> 00:30:30,000 Speaker 12: try to automate everything in between through use of model 566 00:30:30,040 --> 00:30:32,520 Speaker 12: diversity and having the right talent that knows how to 567 00:30:32,560 --> 00:30:35,160 Speaker 12: select the right model for the right task, for the 568 00:30:35,240 --> 00:30:38,560 Speaker 12: right outcome at the right price point is a super 569 00:30:38,600 --> 00:30:41,120 Speaker 12: important skill, and so we're going to hire a ton 570 00:30:41,200 --> 00:30:44,400 Speaker 12: of world class AI engineers to add to the skill 571 00:30:44,440 --> 00:30:47,440 Speaker 12: that we already have to meet the customer with where 572 00:30:47,520 --> 00:30:49,680 Speaker 12: they are in terms of adopting all of this. 573 00:30:49,840 --> 00:30:51,320 Speaker 6: So it's not about anyone model. 574 00:30:51,640 --> 00:30:54,280 Speaker 12: It's about choosing the right model for the right outcomes 575 00:30:54,280 --> 00:30:57,120 Speaker 12: of the right price point, and the types of optimization 576 00:30:57,320 --> 00:31:00,200 Speaker 12: that we can do with customers is really dry being 577 00:31:00,240 --> 00:31:03,080 Speaker 12: an impact. Customers are excited all the way up to 578 00:31:03,080 --> 00:31:06,000 Speaker 12: the c suite and into the boardroom around around the 579 00:31:06,000 --> 00:31:09,920 Speaker 12: opportunity here and this is about putting scale and delivering 580 00:31:09,920 --> 00:31:13,120 Speaker 12: those outcomes. Of course working with our partner ecosystem as well, 581 00:31:13,200 --> 00:31:15,640 Speaker 12: but really driving the tip of the spear engagement with 582 00:31:15,720 --> 00:31:16,400 Speaker 12: our customers. 583 00:31:17,400 --> 00:31:21,520 Speaker 3: Gods and many would say that Palenteer pioneered the FD 584 00:31:21,760 --> 00:31:25,440 Speaker 3: role and deployment. What have you learned from how they've 585 00:31:25,480 --> 00:31:25,840 Speaker 3: done it? 586 00:31:27,080 --> 00:31:29,960 Speaker 12: Look, I think Pallenteers to be applauded for the work 587 00:31:29,960 --> 00:31:33,320 Speaker 12: that they've done with FD. I think for us it's 588 00:31:33,360 --> 00:31:37,040 Speaker 12: more than FD. It's about having the right skills that 589 00:31:37,080 --> 00:31:39,880 Speaker 12: actually understand the business and the business outcomes, and it's 590 00:31:39,880 --> 00:31:44,200 Speaker 12: about having the right platform. Only Microsoft has a platform 591 00:31:44,360 --> 00:31:47,640 Speaker 12: that has world class AI assistance at the face of 592 00:31:47,720 --> 00:31:51,600 Speaker 12: human ambition with our Copilot portfolio and even with assets 593 00:31:51,640 --> 00:31:54,440 Speaker 12: like teams where AI agents can come to life and 594 00:31:54,480 --> 00:31:58,320 Speaker 12: collaborate with people around the business. We have a unique 595 00:31:58,320 --> 00:32:02,480 Speaker 12: IQ platform that's modeled VERSE. We support over eleven thousand models, 596 00:32:02,480 --> 00:32:05,239 Speaker 12: so that you can start with a frontier model, optimize it, 597 00:32:05,320 --> 00:32:07,720 Speaker 12: maybe use an open source model, fine tune it, get 598 00:32:07,720 --> 00:32:09,680 Speaker 12: it down to the right outcome at the right price 599 00:32:09,720 --> 00:32:13,720 Speaker 12: point to avoid the cost explosion around token yield. And 600 00:32:13,760 --> 00:32:16,480 Speaker 12: then we have an observability platform that allows you to 601 00:32:16,520 --> 00:32:19,000 Speaker 12: look closed loop at all of this, see every agent 602 00:32:19,040 --> 00:32:21,360 Speaker 12: that's running in your environment, make sure that it's driving 603 00:32:21,400 --> 00:32:24,320 Speaker 12: the outcomes that you want, make sure it's CyberSecure, and 604 00:32:24,360 --> 00:32:27,320 Speaker 12: make sure that the financial operations around the totality of 605 00:32:27,360 --> 00:32:29,840 Speaker 12: the business flows are intact. So Pallenteer has done a 606 00:32:29,840 --> 00:32:32,480 Speaker 12: great job with FDE, but again that's only one part 607 00:32:32,520 --> 00:32:34,360 Speaker 12: of the equation. You have to have this left to 608 00:32:34,440 --> 00:32:38,080 Speaker 12: right platform that allows AI to empower human ambition and 609 00:32:38,120 --> 00:32:41,200 Speaker 12: do it in a model, diverse, open and heterogeneous way 610 00:32:41,240 --> 00:32:42,600 Speaker 12: across every layer of the stack. 611 00:32:43,440 --> 00:32:46,080 Speaker 3: Jad's an off CEO of Microsoft's commercial business. Thank you 612 00:32:46,160 --> 00:32:49,000 Speaker 3: so much for joining us on Bloomberg Tech now coming 613 00:32:49,080 --> 00:32:53,320 Speaker 3: up a milestone for AI and nuclear energy. Valaratomic CEO 614 00:32:53,440 --> 00:32:56,760 Speaker 3: Zia Taylor joins us after his company used an advanced 615 00:32:56,800 --> 00:33:01,600 Speaker 3: reactor to power and nvidiate AI chip the single chip but. 616 00:33:01,640 --> 00:33:03,280 Speaker 2: Interesting, nonetheless, this has been a bug. 617 00:33:03,320 --> 00:33:15,000 Speaker 3: Dac AI's powered demands are putting nuclear back in the spotlight. 618 00:33:15,040 --> 00:33:18,040 Speaker 3: Now Atomics says it's the first company in the US 619 00:33:18,160 --> 00:33:22,080 Speaker 3: to use an advanced nuclear reactor to actually generate electricity, 620 00:33:22,200 --> 00:33:25,640 Speaker 3: and then it powered an Nvidia Blackwell chip. It was 621 00:33:25,680 --> 00:33:28,560 Speaker 3: a small demonstration, but it comes as the two companies 622 00:33:28,600 --> 00:33:32,680 Speaker 3: announce a partnership to explore nuclear powered AI systems and 623 00:33:32,680 --> 00:33:34,360 Speaker 3: actually there's a bit more in there as well. Joining 624 00:33:34,400 --> 00:33:38,240 Speaker 3: us now as Valor Atomic CEO Asaiah Taylor. I want 625 00:33:38,280 --> 00:33:43,080 Speaker 3: to be transparent about the scale of the demonstration, but 626 00:33:43,160 --> 00:33:44,560 Speaker 3: it was a number of firsts. 627 00:33:44,680 --> 00:33:45,560 Speaker 2: Explain what happened. 628 00:33:46,560 --> 00:33:48,040 Speaker 13: Yeah, thanks so much for having me on ED. 629 00:33:48,120 --> 00:33:50,320 Speaker 14: We're standing here right now in front of the War 630 00:33:50,400 --> 00:33:54,480 Speaker 14: two fifty reactor where we just powered the Nvidio Spark yesterday, 631 00:33:54,840 --> 00:33:57,480 Speaker 14: the first ever advanced nuclear reactor to power. 632 00:33:57,440 --> 00:33:58,240 Speaker 13: An AI ship. 633 00:33:58,560 --> 00:34:00,520 Speaker 14: And you're right, it was a very small demonstr This 634 00:34:00,560 --> 00:34:02,360 Speaker 14: reactor on who makes one hundred kilootts. 635 00:34:02,600 --> 00:34:04,600 Speaker 13: That's very intentional. It's part of our philosophy. 636 00:34:04,640 --> 00:34:06,720 Speaker 14: We like to move quickly in small steps, right, So 637 00:34:06,760 --> 00:34:09,400 Speaker 14: it's a small demonstration, but it is a big first. 638 00:34:09,520 --> 00:34:12,319 Speaker 14: It's also the first time an advanced reactor has been 639 00:34:12,360 --> 00:34:15,160 Speaker 14: built in American soil outside of the National lab system. 640 00:34:15,360 --> 00:34:18,200 Speaker 14: And yesterday we actually became the first ever startup to 641 00:34:18,239 --> 00:34:21,480 Speaker 14: make nuclear electricity. So a bunch of awesome historic things 642 00:34:21,719 --> 00:34:24,040 Speaker 14: and a small demonstration, and we're really proud to partner 643 00:34:24,080 --> 00:34:25,000 Speaker 14: with Nvidia to do it. 644 00:34:26,320 --> 00:34:31,080 Speaker 3: I think what is interesting about this is the technology itself. Right, 645 00:34:31,239 --> 00:34:33,319 Speaker 3: could you just bring us up to datas on where 646 00:34:33,520 --> 00:34:36,440 Speaker 3: the sort of technology stands today. I appreciate you've outlined 647 00:34:36,520 --> 00:34:40,560 Speaker 3: it was a first, but the challenges of scaling the 648 00:34:40,600 --> 00:34:44,520 Speaker 3: benefits of using that technology relative to other energy sources. 649 00:34:45,120 --> 00:34:45,799 Speaker 13: One hundred percent. 650 00:34:45,960 --> 00:34:48,239 Speaker 14: So I mean, listen, nuclear has been around for a 651 00:34:48,280 --> 00:34:50,880 Speaker 14: long time and we've built these very large scale plants 652 00:34:51,200 --> 00:34:53,400 Speaker 14: that have made a lot of electricity, but the problem 653 00:34:53,400 --> 00:34:55,200 Speaker 14: with them is that they haven't scaled very well. They 654 00:34:55,200 --> 00:34:57,120 Speaker 14: take a long time to build, they use a lot 655 00:34:57,120 --> 00:34:59,440 Speaker 14: of civil infrastructure, and these are things that were not 656 00:34:59,480 --> 00:35:01,960 Speaker 14: as good at the United States anymore. So the philosophy 657 00:35:01,960 --> 00:35:05,200 Speaker 14: of valor Atomics is we want to build modular plants 658 00:35:05,280 --> 00:35:07,960 Speaker 14: that are manufactured. And the other really unique thing is 659 00:35:07,960 --> 00:35:10,719 Speaker 14: that they are high temperature reactors. This standing behind the 660 00:35:10,800 --> 00:35:13,480 Speaker 14: service is a high temperature gas reactor, and those high 661 00:35:13,480 --> 00:35:16,920 Speaker 14: temperatures are actually really good for both efficiency. 662 00:35:16,680 --> 00:35:18,960 Speaker 13: But also for things like air cooling. 663 00:35:19,040 --> 00:35:21,400 Speaker 14: So a lot of the power debate and AI scaling 664 00:35:21,400 --> 00:35:23,920 Speaker 14: debate right now is how do we do this without 665 00:35:23,960 --> 00:35:26,920 Speaker 14: having to tax local communities of water usage. One of 666 00:35:26,960 --> 00:35:28,719 Speaker 14: the best ways to do that is just to raise 667 00:35:28,719 --> 00:35:30,800 Speaker 14: the temperature of the reactor. This allows it to reject 668 00:35:30,800 --> 00:35:32,839 Speaker 14: you to a higher temperature, which means that you don't 669 00:35:32,880 --> 00:35:34,520 Speaker 14: need water cooling anymore. And that was part of our 670 00:35:34,560 --> 00:35:35,520 Speaker 14: announcement yesterday. 671 00:35:36,840 --> 00:35:39,359 Speaker 3: I want to stay with the waterless component of it. 672 00:35:39,800 --> 00:35:43,160 Speaker 3: You know, Nvidia has been speaking publicly a lot about 673 00:35:43,680 --> 00:35:47,120 Speaker 3: the economics of cooling through different technology sets. 674 00:35:47,440 --> 00:35:48,600 Speaker 2: It is a big focus. 675 00:35:48,640 --> 00:35:52,360 Speaker 3: So they've tried to dispel some misunderstanding that's out there. 676 00:35:53,320 --> 00:35:56,480 Speaker 3: How does your technology work in that respect and how 677 00:35:56,600 --> 00:35:57,800 Speaker 3: unique is it in the field. 678 00:35:58,920 --> 00:36:01,600 Speaker 14: Absolutely to this equation right, we need to get the 679 00:36:02,040 --> 00:36:04,719 Speaker 14: energy generation side through waterless, and we need to get 680 00:36:04,719 --> 00:36:07,279 Speaker 14: the data center cooling side through waterless. And that's why 681 00:36:07,360 --> 00:36:09,839 Speaker 14: with this collaboration within Video is really exciting to us. 682 00:36:10,120 --> 00:36:12,360 Speaker 14: We realized that we were both working on the problem 683 00:36:12,360 --> 00:36:14,719 Speaker 14: from different angles. We're working on a nuclear reactor that 684 00:36:14,760 --> 00:36:18,000 Speaker 14: doesn't need water cooling due to high reject temperatures, and 685 00:36:18,360 --> 00:36:20,920 Speaker 14: Video is artagubly working on the data center architecture to 686 00:36:20,960 --> 00:36:23,480 Speaker 14: do that. And so when you bring these two technologies together, 687 00:36:23,880 --> 00:36:26,960 Speaker 14: this collaboration for a thirty megal wade data center with 688 00:36:27,200 --> 00:36:31,120 Speaker 14: no water cooling needed to extract water from the local community, 689 00:36:31,480 --> 00:36:33,920 Speaker 14: that's really what's going to allow us to scale. We 690 00:36:33,960 --> 00:36:36,360 Speaker 14: think it is very important for the United States to 691 00:36:36,360 --> 00:36:38,960 Speaker 14: win on AI to win this scaling race, but we 692 00:36:39,040 --> 00:36:41,560 Speaker 14: need to do that without taxing local communities in both 693 00:36:41,640 --> 00:36:44,600 Speaker 14: power price and water usage. And so Nvidia and val 694 00:36:44,640 --> 00:36:47,839 Speaker 14: Atomics coming together in this collaboration is really solving both 695 00:36:47,880 --> 00:36:49,200 Speaker 14: sides of that problem. 696 00:36:50,320 --> 00:36:57,560 Speaker 3: In Vidia has historically made equity investments in all layers 697 00:36:57,600 --> 00:37:01,400 Speaker 3: of the stack, with the argument that they want to 698 00:37:01,440 --> 00:37:05,920 Speaker 3: support the ecosystem to get them moving faster. Have you 699 00:37:06,000 --> 00:37:09,440 Speaker 3: had any discussion with Jensen or within video about the 700 00:37:09,480 --> 00:37:14,000 Speaker 3: idea of there being a financial relationship between Valor and Nvidia. 701 00:37:15,280 --> 00:37:18,680 Speaker 14: You know, I can't announce anything on fundraising today. You know, 702 00:37:18,719 --> 00:37:20,279 Speaker 14: we have a lot of work to do here that 703 00:37:20,280 --> 00:37:22,720 Speaker 14: we're focusing on, and a lot of awesome capital providers 704 00:37:22,760 --> 00:37:24,839 Speaker 14: behind as allowing as to go do that. But what 705 00:37:24,920 --> 00:37:27,480 Speaker 14: I will say is that this collaboration is focused on 706 00:37:27,800 --> 00:37:30,279 Speaker 14: how do we take the next step of scale right. 707 00:37:30,320 --> 00:37:31,840 Speaker 14: I think that in Nvidia has done a lot of 708 00:37:31,880 --> 00:37:35,239 Speaker 14: fundamental work on scaling the compute side and the architecture 709 00:37:35,239 --> 00:37:37,399 Speaker 14: and their DSX architecture. They've done a lot of it's 710 00:37:37,440 --> 00:37:40,280 Speaker 14: really fundamental work on scale, and we know that energy 711 00:37:40,320 --> 00:37:42,960 Speaker 14: has been what is missing. You know, natural gas is 712 00:37:43,000 --> 00:37:44,719 Speaker 14: going to be a bridge. It's going to be a 713 00:37:44,719 --> 00:37:46,960 Speaker 14: good bridge, but it only goes so far, and we 714 00:37:47,080 --> 00:37:49,719 Speaker 14: continue to have the climate change question associated with that, 715 00:37:50,120 --> 00:37:52,240 Speaker 14: and so if we really want to scale, and especially 716 00:37:52,520 --> 00:37:55,640 Speaker 14: outside of the pre existing natural gas infrastructure in terms. 717 00:37:55,440 --> 00:37:58,080 Speaker 13: Of pipelines, we're going to have to do that with granium. 718 00:37:59,320 --> 00:37:59,480 Speaker 2: Is there. 719 00:37:59,560 --> 00:38:02,759 Speaker 3: We just have forty five seconds to end demo one 720 00:38:02,920 --> 00:38:06,000 Speaker 3: a single spark. What are the milestones that come next 721 00:38:06,040 --> 00:38:10,080 Speaker 3: in terms of scaling the demo and infrastructure at different levels. 722 00:38:10,960 --> 00:38:13,759 Speaker 13: Yeah, Valo Atomics likes to take small steps quickly. We're 723 00:38:13,800 --> 00:38:15,880 Speaker 13: going to go build another reactor. The next one is 724 00:38:15,920 --> 00:38:16,839 Speaker 13: going to be a lot. 725 00:38:16,760 --> 00:38:18,920 Speaker 14: More powerful than this one and will take the next 726 00:38:18,920 --> 00:38:21,359 Speaker 14: step in demonstration on the compute side as well. 727 00:38:21,400 --> 00:38:23,640 Speaker 13: So stay tuned in the next sixty twelve months. 728 00:38:26,440 --> 00:38:29,120 Speaker 3: Amazing sort of visual and the sound behind you Isaiah 729 00:38:29,160 --> 00:38:33,520 Speaker 3: Taylor of bala Atomics with the technology literally in the background, 730 00:38:33,600 --> 00:38:36,520 Speaker 3: Thank you very much. Indeed, now coming up, Palmer Lucky's 731 00:38:36,600 --> 00:38:39,919 Speaker 3: errabor Bank is in talks to raise funds at evaluation 732 00:38:40,360 --> 00:38:43,879 Speaker 3: of eight billion dollars. According to Bloomberg's reporting, that story's next. 733 00:38:43,960 --> 00:38:44,839 Speaker 2: This is Bloomberg Tech. 734 00:38:57,960 --> 00:39:01,160 Speaker 15: It's time now for talking tech stuff. Soft Bank and 735 00:39:01,239 --> 00:39:04,960 Speaker 15: its telecom unit will start ranting AI computing resources to 736 00:39:05,120 --> 00:39:08,160 Speaker 15: US companies starting next fiscal year. They'll offer AI chips 737 00:39:08,480 --> 00:39:12,920 Speaker 15: and cloud services to large customers, including hyperscalers. The move 738 00:39:12,960 --> 00:39:16,960 Speaker 15: puts them in competition with companies like Coreweave and Mebius, 739 00:39:17,000 --> 00:39:21,880 Speaker 15: and potentially Meta plus, Nvidia is giving AI startups a 740 00:39:21,920 --> 00:39:25,319 Speaker 15: new way to access computing power. Instead of paying the 741 00:39:25,400 --> 00:39:28,319 Speaker 15: full cost up front, they'll give Nvidia a share of 742 00:39:28,440 --> 00:39:32,040 Speaker 15: future revenue. The company will do that by connecting AI 743 00:39:32,120 --> 00:39:35,680 Speaker 15: data center operators with cloud providers, making it easier for 744 00:39:35,800 --> 00:39:39,800 Speaker 15: researchers and startups to get the computing resources that they need. 745 00:39:40,280 --> 00:39:43,600 Speaker 15: And Google has lost its long running anti trust fight 746 00:39:43,640 --> 00:39:45,799 Speaker 15: with the European Unit and will now have to pay 747 00:39:45,840 --> 00:39:49,560 Speaker 15: a roughly four point seven billion dollar fine Europe's highest 748 00:39:49,560 --> 00:39:53,880 Speaker 15: court Worlds. Google illegally used Android to cement the dominance 749 00:39:53,920 --> 00:39:57,480 Speaker 15: of its Search and Chrome apps by requiring phonemakers to 750 00:39:57,560 --> 00:39:58,520 Speaker 15: pre install them. 751 00:39:58,840 --> 00:40:02,680 Speaker 3: Ed Jahira, Let's take a look at today's big number, 752 00:40:02,800 --> 00:40:07,680 Speaker 3: eight billion dollars. That's the valuation Parma Lucky's reportedly targeting 753 00:40:07,960 --> 00:40:12,120 Speaker 3: for his new venture, back by investor Peter Tiel. Errorbor 754 00:40:12,239 --> 00:40:16,200 Speaker 3: Bank reference to the Lonely Mountain of the Middle Earth 755 00:40:17,160 --> 00:40:20,520 Speaker 3: world of Tolkien's mind. According to sources, the startups looking 756 00:40:20,520 --> 00:40:23,799 Speaker 3: to raise fresh funding at evaluation of at least eight 757 00:40:23,840 --> 00:40:26,120 Speaker 3: billion dollars as it aims to build a bank focused 758 00:40:26,160 --> 00:40:29,439 Speaker 3: on serving startups and the innovation economy. Blimost Finance editor, 759 00:40:29,480 --> 00:40:32,319 Speaker 3: Jenny Surrains with us. We've been trying to track this 760 00:40:32,360 --> 00:40:35,600 Speaker 3: one for a little while. Palmer Lucky is, you know, 761 00:40:35,920 --> 00:40:39,080 Speaker 3: the face of it, but it's basically a nationally chartered bank. 762 00:40:39,960 --> 00:40:43,880 Speaker 3: The valuation's interesting, what's the valuation based on? Like, do 763 00:40:43,920 --> 00:40:46,440 Speaker 3: we know how this this effort is going. 764 00:40:47,600 --> 00:40:51,080 Speaker 16: Yeah, So we reported today that they've seen their deposits 765 00:40:51,080 --> 00:40:54,080 Speaker 16: actually quadruple in the last few months alone, so he's 766 00:40:54,120 --> 00:40:57,920 Speaker 16: definitely seeing success and traction with the customers that he's acquiring. 767 00:40:58,560 --> 00:41:00,799 Speaker 16: We also reported today that they've at about four hundred 768 00:41:00,840 --> 00:41:03,720 Speaker 16: customers in the last few months. It's important to remember 769 00:41:03,719 --> 00:41:07,280 Speaker 16: that a lot of these customers are business customers, although 770 00:41:07,400 --> 00:41:10,359 Speaker 16: we got an on record statement from Palmer Lucky himself saying, 771 00:41:10,400 --> 00:41:12,239 Speaker 16: you know, these aren't customers that are just related to 772 00:41:12,280 --> 00:41:16,520 Speaker 16: my businesses. He is seeing a much broader uptake. And 773 00:41:16,640 --> 00:41:18,239 Speaker 16: you know, we've seen a lot of interest in going 774 00:41:18,239 --> 00:41:21,000 Speaker 16: towards these FinTechs over the last few years, and we've 775 00:41:21,000 --> 00:41:23,120 Speaker 16: seen a lot of FinTechs from overseas trying to make 776 00:41:23,120 --> 00:41:25,440 Speaker 16: their mark in the US, and so we're really starting 777 00:41:25,440 --> 00:41:28,040 Speaker 16: to see some traction here and it'll be interesting if 778 00:41:28,040 --> 00:41:30,080 Speaker 16: we start to see some of the bigger banks, the 779 00:41:30,160 --> 00:41:33,040 Speaker 16: JP Morgan's, the Bank of America's start to fight back. 780 00:41:32,960 --> 00:41:37,280 Speaker 3: In any way, the name a tolky Middle Earth reference. 781 00:41:37,320 --> 00:41:41,239 Speaker 3: There are many pizzatiol back companies that have names from 782 00:41:41,239 --> 00:41:43,840 Speaker 3: the world, from the Middle Elf world. Could you just 783 00:41:43,880 --> 00:41:45,320 Speaker 3: go back to what we're saying a second ago, what 784 00:41:45,719 --> 00:41:48,440 Speaker 3: is arable distinct from any other bank, Like, what is 785 00:41:48,560 --> 00:41:51,040 Speaker 3: that makes it different? Or a technology company? 786 00:41:51,680 --> 00:41:53,520 Speaker 16: I think we haven't actually seen a lot of these 787 00:41:53,520 --> 00:41:57,520 Speaker 16: FinTechs catered to business customers yet, and so for many startups, 788 00:41:57,520 --> 00:42:00,359 Speaker 16: for many companies, their only option is really to go 789 00:42:00,400 --> 00:42:02,040 Speaker 16: to the likes of a JP morgan or a Bank 790 00:42:02,080 --> 00:42:04,520 Speaker 16: of America. Those are the types of places that have 791 00:42:04,560 --> 00:42:06,520 Speaker 16: built out, you know, the suite of services that a 792 00:42:06,600 --> 00:42:09,040 Speaker 16: business really needs as opposed to a consumer. And so 793 00:42:09,480 --> 00:42:11,439 Speaker 16: a lot of these early FinTechs, you know, they start 794 00:42:11,480 --> 00:42:15,319 Speaker 16: out with money movement or high you'ld savings or things 795 00:42:15,320 --> 00:42:18,640 Speaker 16: that often really cater to consumers, airbars, different air bars 796 00:42:18,680 --> 00:42:21,600 Speaker 16: looking to kind of cater to these, you know, small 797 00:42:21,600 --> 00:42:24,680 Speaker 16: business and business customers that bring with them higher deposits, 798 00:42:24,680 --> 00:42:26,920 Speaker 16: and so that's why we've seen their deposits kind of 799 00:42:26,920 --> 00:42:29,480 Speaker 16: take off. So dramatically in the last few months, and 800 00:42:29,520 --> 00:42:31,040 Speaker 16: it'll be interesting to see if they can kind of 801 00:42:31,120 --> 00:42:32,200 Speaker 16: keep that momentum going. 802 00:42:33,600 --> 00:42:36,520 Speaker 3: We'll just point out that, you know, this is early 803 00:42:36,560 --> 00:42:40,120 Speaker 3: stage talks technically Errorbor declined to comment on I guess 804 00:42:40,200 --> 00:42:42,800 Speaker 3: the terms of the valuation in the discussions, but we 805 00:42:42,880 --> 00:42:44,600 Speaker 3: got that on the record statement from Palmelacky. 806 00:42:44,640 --> 00:42:45,879 Speaker 2: Go check out the story on. 807 00:42:45,840 --> 00:42:48,879 Speaker 3: The Bloomberg terminal on bloomberg dot com bloombogs Jennifer's reign. 808 00:42:49,120 --> 00:42:49,960 Speaker 2: Thank you very much. 809 00:42:50,040 --> 00:42:53,360 Speaker 3: Indeed, before we let you go for the July fourth weekend, 810 00:42:53,480 --> 00:42:58,320 Speaker 3: a quick look at what's been trending following Balligan scoring again, 811 00:42:58,880 --> 00:43:02,839 Speaker 3: this time on Google trends after the US striker and 812 00:43:02,920 --> 00:43:05,239 Speaker 3: top goal scorer for the team so far that the 813 00:43:05,280 --> 00:43:09,399 Speaker 3: FIFA World Cup, earned himself a red card. If there's 814 00:43:09,440 --> 00:43:12,520 Speaker 3: another tech story here, it's the difference between what the 815 00:43:12,520 --> 00:43:18,000 Speaker 3: referee sees live and video assistant referee Yes Vaar. Still 816 00:43:18,120 --> 00:43:20,719 Speaker 3: even a man down, the US team closed the game 817 00:43:20,760 --> 00:43:25,120 Speaker 3: out to win two nil. Tillman free kick waterballer. After 818 00:43:25,160 --> 00:43:27,239 Speaker 3: their win here in the Bay Area, the US men's 819 00:43:27,280 --> 00:43:30,120 Speaker 3: national team heads back to another tech cub, Seattle, to 820 00:43:30,160 --> 00:43:33,840 Speaker 3: take on Belgium in the round of sixteen. Okay, that 821 00:43:33,960 --> 00:43:37,879 Speaker 3: does it for this edition of Bloomberg Tech. Don't forget 822 00:43:37,920 --> 00:43:40,560 Speaker 3: to tune on Saturday, July fourth for a special edition 823 00:43:40,880 --> 00:43:44,400 Speaker 3: of Bloomberg This Weekend, live from the Intrepid as America 824 00:43:44,480 --> 00:43:48,000 Speaker 3: celebrates it's two hundred and fifty anniversary. Happy July fourth, 825 00:43:48,200 --> 00:43:49,400 Speaker 3: Happy birthday America. 826 00:43:49,640 --> 00:43:50,640 Speaker 2: This is Bloomberg Tech.