1 00:00:00,080 --> 00:00:13,440 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is alive 2 00:00:13,480 --> 00:00:17,279 Speaker 1: from coast to coast with Caroline Hide in New York 3 00:00:17,560 --> 00:00:19,480 Speaker 1: and Edma low Intend frances Go. 4 00:00:23,000 --> 00:00:24,840 Speaker 2: This is Bloomberg Tech coming up. 5 00:00:24,880 --> 00:00:28,080 Speaker 3: Treasury Secretary Scott Besson says the US is open to 6 00:00:28,200 --> 00:00:31,880 Speaker 3: discussing the use of nvideo chips with China US. 7 00:00:32,000 --> 00:00:35,040 Speaker 4: China's ten Cent shows fast growth across its gaming and 8 00:00:35,120 --> 00:00:38,720 Speaker 4: ad businesses and plans for smart AI spending. 9 00:00:39,400 --> 00:00:42,240 Speaker 3: And our conversation with the CEO of core Weave after 10 00:00:42,280 --> 00:00:45,080 Speaker 3: its earnings we discuss how the company plans to scale 11 00:00:45,440 --> 00:00:46,519 Speaker 3: to meet AI demand. 12 00:00:46,640 --> 00:00:48,519 Speaker 4: But first we check in on these markets that are 13 00:00:49,000 --> 00:00:52,120 Speaker 4: very close, if not at record highs. Once again, ed 14 00:00:52,280 --> 00:00:54,720 Speaker 4: we drive higher and it's more about federal reserve policy. 15 00:00:54,920 --> 00:00:57,240 Speaker 4: Will we get a megacut coming later in the year. 16 00:00:57,320 --> 00:00:59,000 Speaker 4: Now A's at one hundred clint to games, but we 17 00:00:59,040 --> 00:01:01,480 Speaker 4: are near a record at a record high, so too 18 00:01:01,880 --> 00:01:04,880 Speaker 4: for bitcoin seven ten percent Ether is high too. We 19 00:01:04,959 --> 00:01:08,319 Speaker 4: now have four trillion dollars market cap for the entirety 20 00:01:08,560 --> 00:01:11,240 Speaker 4: of the crypto market, just about the same size as 21 00:01:11,280 --> 00:01:13,280 Speaker 4: say in Vidia, what are you looking at? 22 00:01:14,360 --> 00:01:16,960 Speaker 3: Yeah, I'm looking at Nvidia and AMD Now I'm going 23 00:01:17,000 --> 00:01:19,679 Speaker 3: to be really clear here. It's really hard to see 24 00:01:19,680 --> 00:01:22,680 Speaker 3: the catalyst to cause or link for why Nvidia is 25 00:01:22,720 --> 00:01:24,720 Speaker 3: down a percentage point in AMD's up four and a 26 00:01:24,760 --> 00:01:29,399 Speaker 3: half percent. Social media volumes for AMD have quadrupled in 27 00:01:29,440 --> 00:01:32,000 Speaker 3: the last hour. People are talking about it. There's a 28 00:01:32,040 --> 00:01:34,840 Speaker 3: reason why they're talking about it. It's because this is 29 00:01:34,880 --> 00:01:38,000 Speaker 3: what Treasury Secretary Scott Besant told Bloomberg Samory hoard in 30 00:01:38,040 --> 00:01:38,640 Speaker 3: earlier today. 31 00:01:39,480 --> 00:01:41,640 Speaker 5: We would not sell. 32 00:01:41,480 --> 00:01:44,640 Speaker 6: Any of the advanced chips, So the aged twenties, I 33 00:01:44,640 --> 00:01:46,440 Speaker 6: don't know whether you'd say there are four or five 34 00:01:46,600 --> 00:01:50,040 Speaker 6: six levels down the chip stack. What we do not 35 00:01:50,200 --> 00:01:54,440 Speaker 6: want here, em Marie, is for Huawei to have a 36 00:01:54,480 --> 00:01:58,760 Speaker 6: digital Belton road, right, So we do not want the 37 00:01:58,880 --> 00:02:04,760 Speaker 6: standard to become Chinese across the world or even in China. 38 00:02:04,920 --> 00:02:08,720 Speaker 3: Let's understand this administration's policies for chip makers and speaks 39 00:02:08,760 --> 00:02:12,320 Speaker 3: of Bloomberg Surveillance co host Amry Horden, who just conducted 40 00:02:12,360 --> 00:02:16,640 Speaker 3: that interview, the underlying assumptions changed actually this week whether 41 00:02:16,720 --> 00:02:20,640 Speaker 3: or not China even wants America's reduced power chips. But 42 00:02:20,680 --> 00:02:23,320 Speaker 3: what I found some interesting about the content of what 43 00:02:23,360 --> 00:02:26,040 Speaker 3: Beson was telling you is that they feel that it's 44 00:02:26,120 --> 00:02:29,160 Speaker 3: not really even a national security concern. They're very clear 45 00:02:29,160 --> 00:02:32,320 Speaker 3: that these are lower performance chips and they want American 46 00:02:32,360 --> 00:02:33,560 Speaker 3: tech to be present there. 47 00:02:33,880 --> 00:02:35,680 Speaker 2: Give us the digest of what else you said. 48 00:02:35,880 --> 00:02:38,240 Speaker 7: Yeah, that was really his answer to my question of 49 00:02:38,280 --> 00:02:40,960 Speaker 7: what do you say to critics that basically think this 50 00:02:41,080 --> 00:02:47,639 Speaker 7: administration is putting revenue in front of national security concerns 51 00:02:47,639 --> 00:02:51,080 Speaker 7: that export licenses now look to be seemingly for sale. 52 00:02:51,400 --> 00:02:53,239 Speaker 5: He said that the H twenty chip. 53 00:02:53,040 --> 00:02:55,320 Speaker 7: And I guess similar to AMD, the m I three 54 00:02:55,480 --> 00:02:59,040 Speaker 7: or eight is four or five, six stacks down from 55 00:02:59,040 --> 00:03:01,840 Speaker 7: that higher level, and they're never going to allow China 56 00:03:01,880 --> 00:03:04,519 Speaker 7: to get to the higher level chip. He almost sounded 57 00:03:04,560 --> 00:03:07,440 Speaker 7: a little bit like someone you speak to often when 58 00:03:07,440 --> 00:03:10,280 Speaker 7: it comes to Jensen Wang about what it means to 59 00:03:10,360 --> 00:03:14,240 Speaker 7: make sure that Nvidia or AMD have a footprint in 60 00:03:14,360 --> 00:03:17,640 Speaker 7: China because they don't want Huawei to get control of that. 61 00:03:18,040 --> 00:03:19,239 Speaker 5: And the big question. 62 00:03:19,000 --> 00:03:21,400 Speaker 7: Mark is now is that what is the appetite in 63 00:03:21,480 --> 00:03:24,480 Speaker 7: Beijing for these chips given the fact that there's been 64 00:03:24,520 --> 00:03:28,760 Speaker 7: this new urgency since the administration is allowing these export 65 00:03:28,840 --> 00:03:32,880 Speaker 7: licenses once again from the CCP to send out these 66 00:03:32,960 --> 00:03:36,320 Speaker 7: letters to firms telling them to snub these chips and 67 00:03:36,360 --> 00:03:39,040 Speaker 7: go for some of their own national champions. And this 68 00:03:39,120 --> 00:03:42,000 Speaker 7: is something the Treasury Secretary told me and Jonathan that 69 00:03:42,040 --> 00:03:45,360 Speaker 7: he is going to bring up with his Chinese counterpart. 70 00:03:45,320 --> 00:03:45,640 Speaker 5: I Marie. 71 00:03:45,720 --> 00:03:48,320 Speaker 4: What's also interesting is he also told you and Jonathan 72 00:03:48,880 --> 00:03:52,320 Speaker 4: that maybe this could be replicated at the moment. It's unique, 73 00:03:52,720 --> 00:03:55,240 Speaker 4: he mentioned, but maybe it applies to other chip makers 74 00:03:55,240 --> 00:03:56,360 Speaker 4: on the industries. 75 00:03:55,960 --> 00:03:56,240 Speaker 5: He said. 76 00:03:56,240 --> 00:03:59,400 Speaker 7: It's a unique model, something that the President likes to do, 77 00:03:59,520 --> 00:04:03,160 Speaker 7: try to things. But yeah, that's something that caught me 78 00:04:03,200 --> 00:04:05,200 Speaker 7: off guard as well, or something that we've been also 79 00:04:05,680 --> 00:04:07,080 Speaker 7: just exploring. 80 00:04:06,560 --> 00:04:10,280 Speaker 5: Every day with guests. Whether or not this is new. 81 00:04:10,160 --> 00:04:14,240 Speaker 7: Rules of engagement and rules of the road for corporate America. 82 00:04:14,680 --> 00:04:18,880 Speaker 7: Can other companies potentially strike these types of deals with 83 00:04:18,920 --> 00:04:21,720 Speaker 7: the United States or maybe the other way around. Could 84 00:04:21,720 --> 00:04:24,520 Speaker 7: the Oval Office and the President tell other companies, if 85 00:04:24,560 --> 00:04:27,720 Speaker 7: you want to gain access to a market, we're going 86 00:04:27,800 --> 00:04:29,760 Speaker 7: to have to get part of that profit. Because what's 87 00:04:29,800 --> 00:04:31,880 Speaker 7: going on right now, and this has been a really 88 00:04:31,960 --> 00:04:35,040 Speaker 7: long saga, we should note for the H twenty chips, 89 00:04:35,080 --> 00:04:37,839 Speaker 7: remember in April there was an export ban. 90 00:04:37,920 --> 00:04:38,880 Speaker 5: On these chips. 91 00:04:39,120 --> 00:04:42,720 Speaker 7: Then this was reversed in the meantime, we had US 92 00:04:42,800 --> 00:04:46,800 Speaker 7: and Chinese counterparts to having trade negotiations, and a lot 93 00:04:46,839 --> 00:04:49,480 Speaker 7: of people glean into this, and the Treasury Secretary told 94 00:04:49,480 --> 00:04:52,120 Speaker 7: me in a previous interview this H twenty was a 95 00:04:52,240 --> 00:04:55,520 Speaker 7: chip part of the mosaic of these trade negotiations because 96 00:04:55,560 --> 00:04:58,880 Speaker 7: the US needed rare earths. And now that the US 97 00:04:58,960 --> 00:05:02,800 Speaker 7: has lifted the ex control instead of just allowing the 98 00:05:02,839 --> 00:05:05,839 Speaker 7: export licenses to come back, it seems a president struck 99 00:05:05,880 --> 00:05:07,839 Speaker 7: this deal one on one with Jensen Wang in the 100 00:05:07,880 --> 00:05:11,040 Speaker 7: Oval Office. Reported the President throughout twenty percent, and then 101 00:05:11,120 --> 00:05:14,159 Speaker 7: Jensen Wang said, well, how about fifteen percent? And then 102 00:05:14,360 --> 00:05:17,160 Speaker 7: what does this mean is a big question for other 103 00:05:17,360 --> 00:05:20,120 Speaker 7: companies in corporate America down the road. 104 00:05:21,240 --> 00:05:23,440 Speaker 3: The very quick question is what happens next? Right, because 105 00:05:23,440 --> 00:05:26,600 Speaker 3: Treasury Secretary Beston, on top of what the President said 106 00:05:26,640 --> 00:05:29,400 Speaker 3: earlier in the week, says that they'll discuss the idea 107 00:05:29,480 --> 00:05:34,279 Speaker 3: of unenhanced Blackwell chips essentially with China. He leads talks 108 00:05:34,360 --> 00:05:36,440 Speaker 3: just very quick, what does happen next? 109 00:05:36,680 --> 00:05:39,240 Speaker 7: Well, I think it depends on the leverage in these 110 00:05:39,240 --> 00:05:42,279 Speaker 7: negotiations and what the US wants to get out of China. 111 00:05:42,320 --> 00:05:44,520 Speaker 7: We also had the President the other day talk about 112 00:05:44,560 --> 00:05:47,920 Speaker 7: the purchasing agreement he struck in his first administration when 113 00:05:47,920 --> 00:05:50,719 Speaker 7: it comes to things like soybeans. There is now a 114 00:05:50,880 --> 00:05:54,360 Speaker 7: ninety day extension which brings us to November for these 115 00:05:54,400 --> 00:05:57,200 Speaker 7: trade talks between these two counterparts. And in my previous 116 00:05:57,200 --> 00:06:00,240 Speaker 7: interviews with the Treasury Secretary in July, he taught talked 117 00:06:00,240 --> 00:06:03,599 Speaker 7: about how now there'll be more of a frequent cadence 118 00:06:03,720 --> 00:06:06,800 Speaker 7: between him and his Chinese counterpart to have these discussions. 119 00:06:07,120 --> 00:06:09,560 Speaker 7: All of this likely will lead up potentially to a 120 00:06:09,600 --> 00:06:13,599 Speaker 7: meeting between Chairman she and President Trump, either on the 121 00:06:13,640 --> 00:06:16,520 Speaker 7: sidelines of the APEC summit or even maybe the President 122 00:06:16,560 --> 00:06:17,239 Speaker 7: going to China. 123 00:06:17,760 --> 00:06:20,159 Speaker 4: New Max Savanien's co host amriy hold On it was 124 00:06:20,200 --> 00:06:22,880 Speaker 4: a brilliant interview. Thanks for breaking it down for us. 125 00:06:23,279 --> 00:06:27,640 Speaker 4: Let's delve more into the corporate implications China US the 126 00:06:27,720 --> 00:06:31,880 Speaker 4: AI competition major it is with US Alien Spernstein joining 127 00:06:31,920 --> 00:06:35,200 Speaker 4: US now, and I'm really interested as to how Alliance 128 00:06:35,200 --> 00:06:38,960 Speaker 4: Spernstein thinks about pricing this in if at all, How 129 00:06:39,000 --> 00:06:42,960 Speaker 4: are you looking at the opportunity to access the Chinese 130 00:06:42,960 --> 00:06:43,960 Speaker 4: market going forward? 131 00:06:44,720 --> 00:06:46,800 Speaker 8: Well, I think China has always remained one of the 132 00:06:46,800 --> 00:06:51,279 Speaker 8: most strategic markets and will remain so, and particularly in 133 00:06:51,279 --> 00:06:54,919 Speaker 8: the AI world. If you think about AI, how we 134 00:06:55,000 --> 00:07:00,480 Speaker 8: think about the scale benefit right the ecosystems. It's always 135 00:07:00,480 --> 00:07:03,440 Speaker 8: been a bit for a big part of the origination 136 00:07:03,640 --> 00:07:08,800 Speaker 8: of innovations, particularly technology innovations, but China has done a 137 00:07:08,800 --> 00:07:11,920 Speaker 8: phenomenal job in terms of using it and then using 138 00:07:11,920 --> 00:07:14,960 Speaker 8: it at a very large scale. When you think about 139 00:07:14,960 --> 00:07:18,960 Speaker 8: in the AI context having the ecosystem globally, it's this 140 00:07:19,200 --> 00:07:23,320 Speaker 8: very important strategic advantage long term. The more data you have, 141 00:07:23,600 --> 00:07:26,760 Speaker 8: the better the model becomes. And that's not just for 142 00:07:26,880 --> 00:07:30,000 Speaker 8: China alone, but think about globally, who wants to be 143 00:07:30,040 --> 00:07:34,280 Speaker 8: the dominant standard? Having the operating system that layer is 144 00:07:34,520 --> 00:07:39,080 Speaker 8: very very strategic for most companies' longer term. So that's 145 00:07:39,080 --> 00:07:42,000 Speaker 8: why we're thinking. That's what Jensen said, That's what leads 146 00:07:42,040 --> 00:07:44,720 Speaker 8: us to at AMD said, and then I think that's 147 00:07:45,040 --> 00:07:47,760 Speaker 8: how we're thinking about it, which is who will be 148 00:07:47,800 --> 00:07:51,160 Speaker 8: the dominant AI standard? We want to have a one 149 00:07:51,240 --> 00:07:54,280 Speaker 8: global ecosystem or are we going to have different forks 150 00:07:54,320 --> 00:07:55,080 Speaker 8: into the future. 151 00:07:55,200 --> 00:07:58,200 Speaker 4: But these so will dumb down in President Trump even 152 00:07:58,240 --> 00:08:02,040 Speaker 4: call them obsolete chips being allowed into China, does that 153 00:08:02,200 --> 00:08:04,200 Speaker 4: ensure that they remain part of the tech stack. 154 00:08:05,120 --> 00:08:07,760 Speaker 5: Well, it's too early to tell. 155 00:08:07,960 --> 00:08:12,640 Speaker 8: For the most part, I think necessity usually drives innovation. 156 00:08:13,320 --> 00:08:17,600 Speaker 8: So when we don't export anything, then it probably is 157 00:08:17,600 --> 00:08:20,480 Speaker 8: a greater incentive for China to develop its own domestic 158 00:08:20,520 --> 00:08:22,920 Speaker 8: ecosystem that's completely separate. 159 00:08:23,440 --> 00:08:24,560 Speaker 5: So this is a bridge. 160 00:08:24,600 --> 00:08:27,560 Speaker 8: I think in my mind that we can abridge that 161 00:08:28,080 --> 00:08:31,480 Speaker 8: big drastic action that we've seen earlier on this year. 162 00:08:32,360 --> 00:08:35,560 Speaker 8: I think China does have advantages to some extent, and 163 00:08:35,760 --> 00:08:40,880 Speaker 8: it has a more newly developed power infrastructure system, it 164 00:08:40,960 --> 00:08:44,000 Speaker 8: has vast amount of data, and it's developed a lot 165 00:08:44,040 --> 00:08:49,000 Speaker 8: of these open source models that they are really rapidly pushing. 166 00:08:49,520 --> 00:08:51,319 Speaker 5: So it remains to be seen. 167 00:08:51,679 --> 00:08:55,000 Speaker 8: But I think it's quite important and quite strategic for 168 00:08:55,040 --> 00:08:57,800 Speaker 8: the US companies to think about the global standard. 169 00:08:58,080 --> 00:08:59,559 Speaker 5: Think about iPhone. 170 00:08:59,160 --> 00:09:03,160 Speaker 8: For instance, right, yes, the iPhone or Tesla, the data 171 00:09:03,200 --> 00:09:06,280 Speaker 8: resides in China. We respect that. But that said, there's 172 00:09:06,280 --> 00:09:09,880 Speaker 8: still lessons that we learn from adoption at this point. 173 00:09:10,000 --> 00:09:12,560 Speaker 8: If you think about a lot of AI models, we've 174 00:09:12,600 --> 00:09:16,400 Speaker 8: trained a lot of datas already, but going forward, the 175 00:09:16,520 --> 00:09:19,760 Speaker 8: use of AI, the use of applications, and that's new 176 00:09:19,840 --> 00:09:22,720 Speaker 8: sets of data that's constantly being generated and we don't 177 00:09:22,720 --> 00:09:24,240 Speaker 8: want to not have access. 178 00:09:23,920 --> 00:09:25,800 Speaker 2: To that lay. 179 00:09:26,120 --> 00:09:29,440 Speaker 3: The Treasury Secretary indicated to us that this pay to 180 00:09:29,520 --> 00:09:34,080 Speaker 3: play or quid pro quo of a revenue share in 181 00:09:34,160 --> 00:09:38,599 Speaker 3: exchange for access to the Chinese market could be expanded. 182 00:09:39,520 --> 00:09:40,960 Speaker 3: What I want to know from you is, if that 183 00:09:41,000 --> 00:09:43,320 Speaker 3: were to be the case with high bandwidth memory or 184 00:09:43,360 --> 00:09:47,240 Speaker 3: telematics or other parts of the server design, would you 185 00:09:47,320 --> 00:09:52,640 Speaker 3: then upgrade your overall outlook for in megawatt terms or 186 00:09:52,679 --> 00:09:55,560 Speaker 3: giga what terms the amount of installed capacity we could 187 00:09:55,559 --> 00:09:56,480 Speaker 3: see around the world. 188 00:09:57,880 --> 00:09:59,680 Speaker 5: I think it's too early to tell. 189 00:09:59,760 --> 00:10:02,280 Speaker 8: I think think, as you've seen from a policy standpoint, 190 00:10:02,320 --> 00:10:05,720 Speaker 8: there has been quite a bit of fluidity in terms 191 00:10:05,800 --> 00:10:09,320 Speaker 8: of the changes back and forth. But I think it's 192 00:10:09,320 --> 00:10:13,079 Speaker 8: certainly promising that you know, some of the really drastic 193 00:10:13,080 --> 00:10:15,520 Speaker 8: assumption that we had in April, some of it is 194 00:10:15,559 --> 00:10:16,800 Speaker 8: being discounted today. 195 00:10:17,200 --> 00:10:19,520 Speaker 5: So it remains to be seen. 196 00:10:19,559 --> 00:10:23,560 Speaker 8: And I would say it's very early, and I would 197 00:10:24,040 --> 00:10:28,080 Speaker 8: refer from making any assumptions, whether too aggressive or I 198 00:10:28,080 --> 00:10:31,280 Speaker 8: would say it is definitely an improvement from the worst 199 00:10:31,360 --> 00:10:32,040 Speaker 8: case scenario. 200 00:10:33,320 --> 00:10:35,800 Speaker 2: Late tu of a Linespernstein, thank you very much. 201 00:10:41,920 --> 00:10:44,040 Speaker 4: Shares of ten cent, well, look they are rising today 202 00:10:44,040 --> 00:10:47,480 Speaker 4: after posting second quarter revenue that beat analyst expectations. The 203 00:10:47,520 --> 00:10:50,680 Speaker 4: company says it plans to accelerate spending on AI research, 204 00:10:50,920 --> 00:10:53,839 Speaker 4: will focus on integrating it across its services, across its 205 00:10:53,880 --> 00:10:55,319 Speaker 4: content from all Bloomergs. 206 00:10:55,320 --> 00:10:56,280 Speaker 5: Henry Wren joins us. 207 00:10:56,320 --> 00:10:59,520 Speaker 4: And it's interesting though they said they're going to invest smartly. 208 00:11:00,120 --> 00:11:01,800 Speaker 2: Is this prudent capex? 209 00:11:01,840 --> 00:11:06,000 Speaker 9: It feels like, yeah, thanks for having me. And it's 210 00:11:06,040 --> 00:11:08,600 Speaker 9: pretty interesting because when you look at their CAPEX budget 211 00:11:08,640 --> 00:11:11,920 Speaker 9: for the quarter, they spent about nineteen billion R and 212 00:11:12,000 --> 00:11:14,439 Speaker 9: B in a quarter, so that has been you would say, 213 00:11:14,440 --> 00:11:17,200 Speaker 9: a fraction of what US tech giants have been spending. 214 00:11:17,240 --> 00:11:19,360 Speaker 9: And on the court they mentioned that they will be 215 00:11:20,160 --> 00:11:23,080 Speaker 9: spending on AI chips, that's a priority. They also be 216 00:11:23,160 --> 00:11:27,720 Speaker 9: recruiting talents. However, they will adopt this more prudent approach, 217 00:11:27,800 --> 00:11:30,160 Speaker 9: so it does seem that they're not in a rush 218 00:11:30,240 --> 00:11:32,560 Speaker 9: to spend as much as they can. They say that 219 00:11:32,640 --> 00:11:35,120 Speaker 9: they have enough AI chips for now. They say that 220 00:11:35,880 --> 00:11:40,600 Speaker 9: their stockpile is enough for training and for inferences. And 221 00:11:40,640 --> 00:11:41,959 Speaker 9: that's probably why. 222 00:11:43,120 --> 00:11:45,880 Speaker 3: There is some skepticism from the anless community. In the 223 00:11:45,920 --> 00:11:48,280 Speaker 3: same way that they look at the American companies on 224 00:11:48,280 --> 00:11:52,760 Speaker 3: how CAPEX translates to top line growth anyway, specific AI growth, 225 00:11:53,080 --> 00:11:55,080 Speaker 3: but in the courter gone, they're just parts of the 226 00:11:55,120 --> 00:11:58,319 Speaker 3: business that are doing well. Where's ten cents strong, Henry. 227 00:11:59,280 --> 00:12:03,520 Speaker 9: Yeah, I would say they're firing on all cylinders for 228 00:12:03,600 --> 00:12:07,080 Speaker 9: this quarter. So the games has been a standout. International 229 00:12:07,080 --> 00:12:09,319 Speaker 9: games grew by about thirty five percent in a quarter. 230 00:12:09,679 --> 00:12:13,040 Speaker 9: They launched some new games, including one called Dune Awakening 231 00:12:13,360 --> 00:12:17,360 Speaker 9: in international markets, but domestically it's about their evergreen games. 232 00:12:17,360 --> 00:12:19,840 Speaker 9: So we're talking about the peace Keeper Elite, which is 233 00:12:19,880 --> 00:12:22,200 Speaker 9: a six to zero old game. The company said that 234 00:12:22,320 --> 00:12:24,959 Speaker 9: it's gaining traction because of a new game model. That 235 00:12:25,080 --> 00:12:28,800 Speaker 9: game saw a thirty percent increase in user volume. 236 00:12:28,679 --> 00:12:29,320 Speaker 2: For the quarter. 237 00:12:29,559 --> 00:12:33,240 Speaker 9: That's about games, but at revenue site it's growing very 238 00:12:33,280 --> 00:12:36,080 Speaker 9: strong as well, twenty percent increase for the quarter. 239 00:12:36,480 --> 00:12:37,640 Speaker 2: The company said it's. 240 00:12:37,480 --> 00:12:40,400 Speaker 9: Benefiting from AI tools being adopted over there as well, 241 00:12:40,480 --> 00:12:44,200 Speaker 9: so it's basically strength across the board. 242 00:12:44,840 --> 00:12:47,360 Speaker 3: Bloombergs Henry Wren, thank you very much. Let's get more 243 00:12:47,400 --> 00:12:51,880 Speaker 3: and bring in Jacob co founder and CEO WPIC Marketing 244 00:12:51,920 --> 00:12:56,000 Speaker 3: and Technologies and e commerce and technology consultancy focused on 245 00:12:56,040 --> 00:12:58,640 Speaker 3: the Asian region. Somebody asked me a question earlier today 246 00:12:58,679 --> 00:13:01,200 Speaker 3: that fits into the ten Cent story so well, which 247 00:13:01,280 --> 00:13:04,000 Speaker 3: is we've been so focused on the movement of chips 248 00:13:04,040 --> 00:13:06,520 Speaker 3: across borders or a lack of we haven't really talked 249 00:13:06,559 --> 00:13:09,079 Speaker 3: about the movement of software, right, And when I think 250 00:13:09,080 --> 00:13:12,320 Speaker 3: about ten Cent and the gaming portfolio in particular, are 251 00:13:12,360 --> 00:13:16,840 Speaker 3: there Chinese domestic companies that are getting international foothold across 252 00:13:16,840 --> 00:13:19,440 Speaker 3: e commerce, gaming and other digital businesses? 253 00:13:21,000 --> 00:13:21,800 Speaker 2: Yeah, definitely. 254 00:13:21,880 --> 00:13:23,480 Speaker 10: I mean even ten Cent is one of those with 255 00:13:23,559 --> 00:13:26,040 Speaker 10: their big investments and a shoppie really kind of being 256 00:13:26,080 --> 00:13:28,600 Speaker 10: a top leading player in Southeast Asia in terms of 257 00:13:28,640 --> 00:13:31,040 Speaker 10: e commerce. But yeah, I mean ten Center is they're 258 00:13:31,080 --> 00:13:33,720 Speaker 10: taking a lot of the advertising dollars you know, that 259 00:13:33,800 --> 00:13:36,080 Speaker 10: are coming from that big e commerce boom inside China 260 00:13:36,120 --> 00:13:37,880 Speaker 10: as well too. They're not so much of a player 261 00:13:37,880 --> 00:13:40,400 Speaker 10: as as say Ali Baba, you know in terms of 262 00:13:40,400 --> 00:13:42,080 Speaker 10: the B to B software that they have a whole 263 00:13:42,080 --> 00:13:44,559 Speaker 10: suite of, but you know, in terms of the advertising 264 00:13:44,640 --> 00:13:46,720 Speaker 10: becoming a bigger and bigger player in that in that part, 265 00:13:46,760 --> 00:13:49,200 Speaker 10: we saw that revenue also up by five percent this quarter. 266 00:13:50,840 --> 00:13:54,120 Speaker 3: You know, the theme from Meta's earnings if there was 267 00:13:54,160 --> 00:13:58,239 Speaker 3: some softness in advertising was a pullback of Chinese advertisers 268 00:13:58,280 --> 00:14:00,920 Speaker 3: in the European region in particular, perhaps in the United 269 00:14:00,960 --> 00:14:04,840 Speaker 3: States because of the geopolitical environment. I'm trying to read 270 00:14:04,840 --> 00:14:06,600 Speaker 3: through what's going on with ten Cent, and I just 271 00:14:06,640 --> 00:14:10,839 Speaker 3: don't see that macro level headwind, do you. 272 00:14:10,880 --> 00:14:11,040 Speaker 5: No? 273 00:14:11,160 --> 00:14:14,160 Speaker 10: And I think that really what you're seeing though, is 274 00:14:14,200 --> 00:14:16,320 Speaker 10: because a lot of that advertising is still based in China. 275 00:14:16,480 --> 00:14:18,040 Speaker 10: That you know, we're coming out of a year of 276 00:14:18,120 --> 00:14:20,840 Speaker 10: pretty big stimulus in terms of the government and e 277 00:14:20,880 --> 00:14:23,880 Speaker 10: commerce spending, so we should naturally see that trickle down 278 00:14:23,880 --> 00:14:26,080 Speaker 10: come into about now Q three and Q four as 279 00:14:26,120 --> 00:14:28,480 Speaker 10: well being pretty strong in terms of the advertising dollars 280 00:14:28,480 --> 00:14:31,680 Speaker 10: that they're coming in. No, they never really had that 281 00:14:31,880 --> 00:14:34,560 Speaker 10: major post COVID stimulus in China and they waited a 282 00:14:34,600 --> 00:14:37,360 Speaker 10: little while, So we're seeing good numbers now, and we 283 00:14:37,400 --> 00:14:39,560 Speaker 10: would expect that they would hold because you know, low 284 00:14:39,560 --> 00:14:42,280 Speaker 10: inflation numbers in China as well. It also bides really 285 00:14:42,280 --> 00:14:45,160 Speaker 10: well for the consumers. So we're pretty excited about ten 286 00:14:45,200 --> 00:14:47,160 Speaker 10: cents earnings and we think that probably you're going to 287 00:14:47,160 --> 00:14:48,920 Speaker 10: see some pretty more good news from the e commerce 288 00:14:48,960 --> 00:14:51,240 Speaker 10: providers in China in the coming weeks as well. 289 00:14:51,480 --> 00:14:53,840 Speaker 4: Yeah, we braced ourselves to Alibaba later in the week, 290 00:14:53,880 --> 00:14:57,360 Speaker 4: for example, called Jacob, I want to hear how much 291 00:14:57,400 --> 00:15:00,320 Speaker 4: access they're having to GPUs, how much AI and to 292 00:15:00,360 --> 00:15:04,000 Speaker 4: AI might be held back by ultimately the infrastructure they need. 293 00:15:04,040 --> 00:15:07,160 Speaker 4: It sounded as though, once again ten Cent trying to say, 294 00:15:07,240 --> 00:15:09,400 Speaker 4: we've got all the chips we need for inference, we're 295 00:15:09,400 --> 00:15:11,160 Speaker 4: not worried about it. They wouldn't go into the nitty 296 00:15:11,160 --> 00:15:13,680 Speaker 4: gritty about in video access for example. 297 00:15:13,840 --> 00:15:15,080 Speaker 5: But Jacob, is it a worry? 298 00:15:16,520 --> 00:15:19,200 Speaker 10: Well, I mean we've all been saying this, but we've 299 00:15:19,240 --> 00:15:22,560 Speaker 10: now seen you know, three successive like the QN model 300 00:15:22,600 --> 00:15:25,200 Speaker 10: exactly from Ali Baba that's now leading, not leading, but 301 00:15:25,280 --> 00:15:27,600 Speaker 10: certainly up there in terms of its ability to code, 302 00:15:27,800 --> 00:15:29,920 Speaker 10: and they're going down a little bit different path at Alibaba, 303 00:15:29,960 --> 00:15:31,560 Speaker 10: but and Deep Seek as well. I mean, all of 304 00:15:31,600 --> 00:15:35,280 Speaker 10: those models are competing internationally despite the chip band. So 305 00:15:35,320 --> 00:15:37,200 Speaker 10: if ten Cent comes and says that you know, they 306 00:15:37,240 --> 00:15:39,160 Speaker 10: have all the chips they need, there's no reason not 307 00:15:39,240 --> 00:15:39,840 Speaker 10: to believe that. 308 00:15:40,680 --> 00:15:45,160 Speaker 4: More broadly, the geopolitical context, it doesn't seem to be 309 00:15:45,240 --> 00:15:47,880 Speaker 4: knocking the wind out are owning these Chinese companies sales. 310 00:15:47,960 --> 00:15:50,640 Speaker 4: I mean, they've all recovered significantly from their lows. 311 00:15:52,280 --> 00:15:54,080 Speaker 10: Yeah, I think that one of the things, you know, 312 00:15:54,200 --> 00:15:56,080 Speaker 10: for us that are boots on the ground in China. 313 00:15:56,240 --> 00:15:59,080 Speaker 10: You know, there is the really high level government that 314 00:15:59,800 --> 00:16:01,560 Speaker 10: you know, where the relations are not great, and we 315 00:16:01,600 --> 00:16:03,520 Speaker 10: see the headlines, but you know, for boots on the 316 00:16:03,520 --> 00:16:06,120 Speaker 10: ground and for the local level, it's actually been very 317 00:16:06,200 --> 00:16:08,880 Speaker 10: very strong. You know, people to people connection is still 318 00:16:09,000 --> 00:16:10,720 Speaker 10: very good over there, and there's still a lot of 319 00:16:10,800 --> 00:16:13,960 Speaker 10: businesses that are setting records international business that are setting 320 00:16:13,960 --> 00:16:17,240 Speaker 10: sales records in China. So you know, there's the headlines, 321 00:16:17,240 --> 00:16:19,760 Speaker 10: but actually on the ground, I think people have been 322 00:16:19,760 --> 00:16:22,040 Speaker 10: doing business over there for quite a long time. Relationships 323 00:16:22,040 --> 00:16:25,680 Speaker 10: have been built up over decades. So we're kind of 324 00:16:25,680 --> 00:16:27,720 Speaker 10: expecting this to blow over, just like it kind of 325 00:16:27,720 --> 00:16:29,800 Speaker 10: did with the first Trump administration, and people will get 326 00:16:29,840 --> 00:16:30,520 Speaker 10: back to business. 327 00:16:32,240 --> 00:16:35,560 Speaker 3: You still have a president that in a press conference 328 00:16:35,640 --> 00:16:38,480 Speaker 3: is talking about a paid to play arrangement where the 329 00:16:38,480 --> 00:16:41,600 Speaker 3: CEO of the biggest company in the world, Nvidia, has 330 00:16:41,640 --> 00:16:44,360 Speaker 3: gone to him and agreed to a revenue share right 331 00:16:44,680 --> 00:16:47,560 Speaker 3: to get access to the Chinese market. In a tariff 332 00:16:47,680 --> 00:16:52,000 Speaker 3: or a trade dispute in China, does the same thing happen? 333 00:16:52,440 --> 00:16:53,520 Speaker 2: Do you have the leaders of. 334 00:16:53,520 --> 00:16:58,160 Speaker 3: These biggest technology companies talking about and acknowledging their government's 335 00:16:58,240 --> 00:17:00,240 Speaker 3: policies in the same way and vice us. 336 00:17:02,680 --> 00:17:05,879 Speaker 10: Well, no, you don't, certainly, but I mean there's almost 337 00:17:06,119 --> 00:17:08,440 Speaker 10: the exact opposite approach. I mean there's been an export 338 00:17:08,520 --> 00:17:10,520 Speaker 10: tax credit out of China for a long time too, 339 00:17:10,560 --> 00:17:12,199 Speaker 10: so it's almost like they're going the other way and 340 00:17:12,240 --> 00:17:15,480 Speaker 10: trying to reduce prices for international consumers as opposed to 341 00:17:15,640 --> 00:17:20,600 Speaker 10: the strategy of essentially taxing exports. So no, you know, 342 00:17:20,680 --> 00:17:23,040 Speaker 10: through all these things, you know, like we said, you know, 343 00:17:23,080 --> 00:17:25,720 Speaker 10: no one's really had a problem getting access to what 344 00:17:25,760 --> 00:17:28,399 Speaker 10: they needed to get access to, and pricing seems to 345 00:17:28,400 --> 00:17:31,399 Speaker 10: be okay in the Chinese market. So yes, there's going 346 00:17:31,440 --> 00:17:34,680 Speaker 10: to be some headwinds. Q one was you know, particularly 347 00:17:34,680 --> 00:17:38,280 Speaker 10: tumultuous in the US China business cycle. But you know, 348 00:17:38,400 --> 00:17:41,000 Speaker 10: we've been through this before and we're probably going to 349 00:17:41,040 --> 00:17:42,560 Speaker 10: get through it again. And the numbers I think are 350 00:17:42,600 --> 00:17:45,120 Speaker 10: starting to say that we're probably getting over the hump here. 351 00:17:45,800 --> 00:17:47,680 Speaker 4: We'll see how the rest of the earnings come through 352 00:17:47,800 --> 00:17:50,080 Speaker 4: for these Chinese giants. Jacob Kok is always great to 353 00:17:50,160 --> 00:18:02,200 Speaker 4: check out with you. The CEO of WPIC marketing and technologies. 354 00:18:00,119 --> 00:18:00,600 Speaker 5: To a company. 355 00:18:00,640 --> 00:18:03,280 Speaker 4: Bullish raised more than a billion dollars in an IPO, 356 00:18:03,400 --> 00:18:05,760 Speaker 4: pricing it shares above the marketed range and the digital 357 00:18:05,800 --> 00:18:08,199 Speaker 4: asset exchange operator and also the owner of Media Outlook 358 00:18:08,240 --> 00:18:12,280 Speaker 4: coindesk so thirty million shares yesterday for thirty seven dollars each. 359 00:18:12,680 --> 00:18:15,560 Speaker 4: Bloomberg's Anthony Hughes joins us as we await the company 360 00:18:15,760 --> 00:18:19,240 Speaker 4: to actually start training on the NYSE that indicated to 361 00:18:19,280 --> 00:18:22,919 Speaker 4: open sixty five to seventy dollars each. That not quite double. 362 00:18:23,280 --> 00:18:27,359 Speaker 4: There's another big pop for another hot retail EPO. 363 00:18:27,480 --> 00:18:28,800 Speaker 5: It feels like, Yes. 364 00:18:28,640 --> 00:18:32,199 Speaker 11: We've had a number of strong IPOs recently, obviously Circle 365 00:18:32,240 --> 00:18:34,400 Speaker 11: in June and then Figma a few weeks ago, So 366 00:18:34,680 --> 00:18:35,919 Speaker 11: this is really directionally a. 367 00:18:35,960 --> 00:18:38,240 Speaker 2: Very similar story. And we've seen very stronger. 368 00:18:37,920 --> 00:18:40,560 Speaker 11: Man and we reported earlier today that there was north 369 00:18:40,560 --> 00:18:42,879 Speaker 11: of twenty times out of subscription levels for this IPO 370 00:18:43,000 --> 00:18:45,879 Speaker 11: and that a lot of institutional investors got no shares 371 00:18:45,920 --> 00:18:48,600 Speaker 11: in this offering, and from all accounts, there's been pretty 372 00:18:48,800 --> 00:18:50,439 Speaker 11: a lot of action amongst the retail brokers. 373 00:18:50,440 --> 00:18:51,680 Speaker 2: You've got a little bit of the stock as well. 374 00:18:51,760 --> 00:18:55,520 Speaker 3: So yeah, I didn't and see I don't know too 375 00:18:55,600 --> 00:18:57,359 Speaker 3: much about Bullish, but I was interested to read that 376 00:18:57,480 --> 00:19:00,560 Speaker 3: like across co founders and board members taking a big 377 00:19:00,640 --> 00:19:02,800 Speaker 3: chunk of the shares or have a big chunk. 378 00:19:03,560 --> 00:19:06,440 Speaker 11: Yes, So from what we heard that when the shares 379 00:19:06,440 --> 00:19:10,719 Speaker 11: are allocated here that people had a relationship with management 380 00:19:10,760 --> 00:19:15,240 Speaker 11: did receive some of the shares. And that's not completely unusual. 381 00:19:15,280 --> 00:19:16,160 Speaker 2: But often with. 382 00:19:16,080 --> 00:19:18,160 Speaker 11: These hot IPOs you get management having a big say 383 00:19:18,200 --> 00:19:20,159 Speaker 11: in the allocations because they want to place the shares 384 00:19:20,200 --> 00:19:22,960 Speaker 11: with I guess, you know, people who they think will 385 00:19:22,960 --> 00:19:25,159 Speaker 11: be long term supporters of the shares or long term 386 00:19:25,200 --> 00:19:27,840 Speaker 11: supporters of the company, or you know, they may have 387 00:19:27,880 --> 00:19:29,200 Speaker 11: other reasons for giving. 388 00:19:28,960 --> 00:19:29,480 Speaker 2: Them the stock. 389 00:19:29,560 --> 00:19:31,800 Speaker 11: But certainly in this case, that seems to be something 390 00:19:31,840 --> 00:19:35,639 Speaker 11: that sort of is you know, it's quite you know, 391 00:19:36,119 --> 00:19:38,760 Speaker 11: a big ass a major aspect of the way in 392 00:19:38,760 --> 00:19:41,160 Speaker 11: which the shares were allocated here, Brendon Bloomer. 393 00:19:40,920 --> 00:19:42,840 Speaker 4: Block one CEO, co founder, he's going to be the 394 00:19:42,880 --> 00:19:45,600 Speaker 4: biggest holder about thirty percent. ARC gets a cut, so 395 00:19:45,680 --> 00:19:48,639 Speaker 4: does black Rock. What's interesting, though, is to think about 396 00:19:48,880 --> 00:19:52,240 Speaker 4: how Tom Farley became the CEO. Originally, it's because he 397 00:19:52,400 --> 00:19:56,040 Speaker 4: was leading a spack, a special acquisition company that was 398 00:19:56,080 --> 00:19:58,119 Speaker 4: going to buy and merge back in the day for 399 00:19:58,240 --> 00:19:59,360 Speaker 4: nine billion dollars. 400 00:19:59,640 --> 00:20:00,840 Speaker 2: This is a strong. 401 00:20:00,520 --> 00:20:03,600 Speaker 4: IPO, but it's not nine billion valuation. It's interesting we 402 00:20:03,640 --> 00:20:05,720 Speaker 4: saw Circle have to do the scene there, spak Han 403 00:20:05,720 --> 00:20:08,160 Speaker 4: wound back in a few years ago. Then they come 404 00:20:08,160 --> 00:20:10,520 Speaker 4: back to the market and IPO strongly e Toro another 405 00:20:11,280 --> 00:20:13,359 Speaker 4: they are managing to come but not perhaps at the 406 00:20:13,400 --> 00:20:15,000 Speaker 4: head e valuations of the past for. 407 00:20:15,200 --> 00:20:18,520 Speaker 11: A bullish yeah, although I think in the case of 408 00:20:18,840 --> 00:20:22,160 Speaker 11: Circle it quickly reclaimed the back valuation and went much 409 00:20:22,240 --> 00:20:24,680 Speaker 11: much higher. So you know, it is really interesting that 410 00:20:25,080 --> 00:20:27,359 Speaker 11: a lot of these back mergers back in that twenty 411 00:20:27,560 --> 00:20:30,400 Speaker 11: twenty one era that fell over for reasons that were 412 00:20:30,760 --> 00:20:34,399 Speaker 11: partly to do with uncertainty around the ones that were 413 00:20:34,400 --> 00:20:37,399 Speaker 11: crypto related, and it was uncertainly around cryptoregulation and aspects 414 00:20:37,480 --> 00:20:39,280 Speaker 11: like that, but also there was just a big sort 415 00:20:39,280 --> 00:20:42,280 Speaker 11: of sell off in a lot of growth names as 416 00:20:42,320 --> 00:20:43,920 Speaker 11: well in that period. So you know, it just tells 417 00:20:43,960 --> 00:20:45,640 Speaker 11: you that we're sort of somewhat back to that sort 418 00:20:45,640 --> 00:20:48,480 Speaker 11: of twenty one twenty twenty one period, not quite as 419 00:20:48,520 --> 00:20:51,480 Speaker 11: extreme as that, but you know, we're certainly in a 420 00:20:51,520 --> 00:20:54,199 Speaker 11: situation in an environment where we're looking at sort of 421 00:20:54,200 --> 00:20:56,399 Speaker 11: lower rates and the market at record highs. You know, 422 00:20:56,440 --> 00:20:58,399 Speaker 11: we're sort of starting to get a lot of a 423 00:20:58,400 --> 00:21:00,920 Speaker 11: lot of hot money in the ip market, but also, 424 00:21:01,640 --> 00:21:04,159 Speaker 11: you know, a lot more IPOs are probably going to 425 00:21:04,160 --> 00:21:06,680 Speaker 11: come in the later stages of twenty twenty five as well. 426 00:21:07,720 --> 00:21:09,160 Speaker 2: We're waiting for trading to start. 427 00:21:09,160 --> 00:21:12,280 Speaker 3: But bullishees indicated open somewhere sixty to sixty five dollars 428 00:21:12,320 --> 00:21:14,920 Speaker 3: each after pricing at thirty seven. Blueberg's anenty hughes. Thank 429 00:21:14,960 --> 00:21:17,800 Speaker 3: you very much, indeed. 430 00:21:23,200 --> 00:21:25,359 Speaker 4: Welcome back to Bloomberg Tech. Check in on these markets 431 00:21:25,480 --> 00:21:27,600 Speaker 4: richer floating between gains and losses on the last that 432 00:21:27,600 --> 00:21:29,840 Speaker 4: one hundred are currently just off by eight points, but 433 00:21:29,920 --> 00:21:33,159 Speaker 4: we are near record highs once again. All eyes on 434 00:21:33,160 --> 00:21:35,160 Speaker 4: the Fed policy, whether we get the big cuts. It's 435 00:21:35,160 --> 00:21:35,880 Speaker 4: helping crypto. 436 00:21:35,960 --> 00:21:36,920 Speaker 5: We're up four tens percent. 437 00:21:36,920 --> 00:21:39,760 Speaker 4: We're coming down from the previous highs earlier in the session, 438 00:21:39,800 --> 00:21:42,280 Speaker 4: but still one hundred and twenty thousand. You're at a 439 00:21:42,280 --> 00:21:44,159 Speaker 4: record high in the market cap of crypto now for 440 00:21:44,400 --> 00:21:46,680 Speaker 4: trillion at the same as in video. Let's look at Vidio. 441 00:21:46,720 --> 00:21:48,520 Speaker 4: Let's look at the chip stocks more broadly ed, because 442 00:21:48,560 --> 00:21:50,760 Speaker 4: they are in the eye of the geopolitical storm right 443 00:21:50,800 --> 00:21:53,320 Speaker 4: now in video off by one point six percent after 444 00:21:53,359 --> 00:21:56,280 Speaker 4: we all digest really what a fifteen percent payment on 445 00:21:56,359 --> 00:21:58,960 Speaker 4: all your age twenties to China really means for the business. 446 00:21:59,040 --> 00:22:00,919 Speaker 4: How much that's going to extra uplating to China? Not 447 00:22:01,000 --> 00:22:03,679 Speaker 4: wanting those chips? AMD though up three point ten percent. 448 00:22:03,960 --> 00:22:06,920 Speaker 4: Interesting the difference here that we're seeing in the two 449 00:22:07,040 --> 00:22:09,480 Speaker 4: key names I'm looking at all Micron off by. 450 00:22:09,359 --> 00:22:11,520 Speaker 5: More than two percent. Ed you've been pointing this out now. 451 00:22:11,560 --> 00:22:14,359 Speaker 4: Remember has rallied the four days prior to this almost 452 00:22:14,440 --> 00:22:17,560 Speaker 4: twenty percent after it pre announced some of its numbers. 453 00:22:17,560 --> 00:22:20,600 Speaker 4: They look strong in dram but interesting reports of course 454 00:22:20,600 --> 00:22:21,919 Speaker 4: that they are laying off people. 455 00:22:21,680 --> 00:22:22,560 Speaker 5: In China at the moment. 456 00:22:24,160 --> 00:22:26,600 Speaker 3: Let's look at another mover, and actually this decline is 457 00:22:26,680 --> 00:22:30,400 Speaker 3: massively accelerated. Shares of Core we've now down almost nineteen 458 00:22:30,480 --> 00:22:33,280 Speaker 3: twenty percent in the session. They'd been down nearer to 459 00:22:33,359 --> 00:22:37,520 Speaker 3: ten percent after the company posted a disappointing earnings outlook. 460 00:22:37,760 --> 00:22:40,320 Speaker 3: Margins are under pressure from this kind of rapid AI 461 00:22:40,840 --> 00:22:43,840 Speaker 3: data center expansion. We spoke with the CEO MI coin 462 00:22:43,880 --> 00:22:45,480 Speaker 3: traitor earlier today. 463 00:22:45,720 --> 00:22:46,680 Speaker 2: The message was. 464 00:22:47,160 --> 00:22:51,800 Speaker 3: Training demand, sustained inference demand, fast growing. 465 00:22:51,840 --> 00:22:56,879 Speaker 2: Listen to this, we continue. 466 00:22:56,359 --> 00:22:59,520 Speaker 12: To see massive demand for training. Right like that, that 467 00:22:59,560 --> 00:23:03,440 Speaker 12: hasn't in any way. But what you're seeing is a 468 00:23:03,520 --> 00:23:07,760 Speaker 12: continue cranking up of the demand for inference, and we 469 00:23:07,800 --> 00:23:14,000 Speaker 12: see it within our portfolio of data centers because when 470 00:23:14,040 --> 00:23:17,320 Speaker 12: when the compute is being dispatched, if it's being used 471 00:23:17,359 --> 00:23:19,719 Speaker 12: for training, you'll see a step function right the training 472 00:23:19,800 --> 00:23:23,240 Speaker 12: job begins, it runs, it steps down when it's over. 473 00:23:23,680 --> 00:23:26,840 Speaker 12: But when you're when you're viewing the compute being used 474 00:23:26,880 --> 00:23:29,840 Speaker 12: for inference, what you see is a much more gradual 475 00:23:29,920 --> 00:23:32,720 Speaker 12: increase and decrease as you move through the day, as 476 00:23:32,760 --> 00:23:35,960 Speaker 12: people begin to come on and off their demands for 477 00:23:36,040 --> 00:23:40,040 Speaker 12: artificial intelligence and the the uh. You know, we haven't 478 00:23:40,080 --> 00:23:43,120 Speaker 12: lost demand for training new models, but we have been 479 00:23:43,320 --> 00:23:50,679 Speaker 12: incredibly pressed across the industry for compute for additional inference capacity. 480 00:23:51,480 --> 00:23:55,040 Speaker 3: What's the percentage split inference training for you? 481 00:23:57,040 --> 00:23:59,280 Speaker 12: The last time I looked, and it does move a lot, 482 00:23:59,840 --> 00:24:02,280 Speaker 12: it was over fifty percent for inference at this point. 483 00:24:03,720 --> 00:24:05,920 Speaker 3: Okay, that's an interesting change because I think I ask 484 00:24:05,960 --> 00:24:08,640 Speaker 3: you that quite regularly and it seems to be at 485 00:24:08,640 --> 00:24:11,920 Speaker 3: that mark. The thing that I've been thinking about a 486 00:24:12,000 --> 00:24:15,959 Speaker 3: lot recently is the aging the aging GPU. You know, 487 00:24:16,160 --> 00:24:19,760 Speaker 3: basically a video commits to that change right on an 488 00:24:19,760 --> 00:24:23,080 Speaker 3: annual basis in the context of the demand picture you 489 00:24:23,200 --> 00:24:25,840 Speaker 3: just outlined, but also what you're trying to do in scaling, 490 00:24:26,160 --> 00:24:28,720 Speaker 3: how do you keep up with the aging GPU scenario. 491 00:24:29,800 --> 00:24:38,000 Speaker 12: Yeah, so, look, what we're seeing in our infrastructure is 492 00:24:38,200 --> 00:24:45,600 Speaker 12: a consistent movement of the newest iterations of architecture that 493 00:24:45,680 --> 00:24:49,120 Speaker 12: come out of in video being used to drive the 494 00:24:49,160 --> 00:24:54,200 Speaker 12: most bleeding edge training infrastructure jobs required. And what happens 495 00:24:54,280 --> 00:24:58,760 Speaker 12: is is the prior generation begins to pick up the 496 00:24:58,840 --> 00:25:01,960 Speaker 12: load on infernt and you see it kind of passing 497 00:25:02,280 --> 00:25:05,200 Speaker 12: from one generation to a next generation to the next generation. 498 00:25:05,760 --> 00:25:06,280 Speaker 13: We are not. 499 00:25:06,359 --> 00:25:10,360 Speaker 12: Seeing meaningful declines in the H one hundred demand, which 500 00:25:10,440 --> 00:25:14,040 Speaker 12: is the prior generation to the Grace Blackwell that is 501 00:25:14,080 --> 00:25:17,000 Speaker 12: the cutting edge right now. We're also not seeing any 502 00:25:17,280 --> 00:25:21,280 Speaker 12: real decreasing demand for the Ampire series, which is even 503 00:25:21,400 --> 00:25:25,879 Speaker 12: prior to the H one hundreds. There is broad based 504 00:25:26,000 --> 00:25:28,720 Speaker 12: inference demand absorbing that compute. 505 00:25:28,840 --> 00:25:31,240 Speaker 13: It's being picked up into term. 506 00:25:31,160 --> 00:25:34,160 Speaker 12: Contracts by many of the same players that are looking 507 00:25:34,200 --> 00:25:36,560 Speaker 12: to support the ever growing demands of inference. 508 00:25:39,160 --> 00:25:43,440 Speaker 3: You diversify the business. Mica away from just open AI 509 00:25:43,480 --> 00:25:44,199 Speaker 3: and Microsoft. 510 00:25:45,400 --> 00:25:45,640 Speaker 13: Yeah. 511 00:25:45,680 --> 00:25:50,960 Speaker 12: Look, it's a huge focus for our organization. We've made 512 00:25:51,080 --> 00:25:53,479 Speaker 12: tremendous progress. I talked a little bit about it in 513 00:25:53,520 --> 00:25:59,040 Speaker 12: the earnings last night. As we take on new clients, 514 00:25:59,080 --> 00:26:05,439 Speaker 12: as we basically penetrate additional layers of the enterprise space. 515 00:26:06,160 --> 00:26:08,360 Speaker 12: I talked a little bit about how we're not only 516 00:26:08,440 --> 00:26:13,640 Speaker 12: seeing diversification of clients, but we're also seeing green shoots 517 00:26:13,640 --> 00:26:16,199 Speaker 12: and new parts of the economy that are beginning to 518 00:26:16,280 --> 00:26:19,680 Speaker 12: integrate artificial intelligence. And I focused a little bit on, 519 00:26:19,840 --> 00:26:22,240 Speaker 12: you know, two sectors, and it's just two sectors that 520 00:26:22,320 --> 00:26:26,000 Speaker 12: we chose. The one was the VFX space, where we 521 00:26:26,040 --> 00:26:29,199 Speaker 12: saw companies like Moon Valley come in and begin to 522 00:26:29,359 --> 00:26:32,280 Speaker 12: integrate artificial intelligence into visual effects. 523 00:26:32,720 --> 00:26:32,840 Speaker 13: Uh. 524 00:26:33,160 --> 00:26:36,040 Speaker 12: You know, it's an incredible growth sector for us. We're 525 00:26:36,080 --> 00:26:39,760 Speaker 12: seeing a lot of new companies begin to ramp there. 526 00:26:39,920 --> 00:26:44,240 Speaker 12: We're also seeing real developments so begin to occur in 527 00:26:44,480 --> 00:26:49,679 Speaker 12: the life sciences portion of the market. There are you know, 528 00:26:49,800 --> 00:26:53,520 Speaker 12: I spoke about hipocratic AI and you know, like those 529 00:26:53,520 --> 00:26:58,600 Speaker 12: are wonderful developments. It really is speaking to a resilient 530 00:26:58,920 --> 00:27:03,680 Speaker 12: broadening of artificial intelligence as it penetrates the economy. 531 00:27:04,560 --> 00:27:08,160 Speaker 3: Michael We've been studying really closely how x Ai went 532 00:27:08,200 --> 00:27:11,560 Speaker 3: about building Colossus and what Meta plans to do with 533 00:27:11,640 --> 00:27:13,480 Speaker 3: its next gen capacity. 534 00:27:14,160 --> 00:27:15,760 Speaker 2: They very much kind of go it alone. 535 00:27:16,040 --> 00:27:17,800 Speaker 3: And I wondered if you talk a little bit about 536 00:27:17,800 --> 00:27:21,240 Speaker 3: the opportunity or maybe lack of opportunity you see to 537 00:27:21,320 --> 00:27:22,959 Speaker 3: work with those two names. 538 00:27:23,760 --> 00:27:26,000 Speaker 12: Yeah, so that is a client of ours, you know, 539 00:27:27,040 --> 00:27:30,160 Speaker 12: and and we we we are you know, we work 540 00:27:30,200 --> 00:27:32,360 Speaker 12: with them very well. We think there's lots of opportunities 541 00:27:32,400 --> 00:27:36,439 Speaker 12: for us to expand our relationship with them and and 542 00:27:36,600 --> 00:27:41,040 Speaker 12: to broaden their use of our computational infrastructure. 543 00:27:41,960 --> 00:27:44,920 Speaker 13: We think that, you know, the work that x is. 544 00:27:44,880 --> 00:27:51,679 Speaker 12: Doing at at their sites is incredibly impressive, you know, 545 00:27:52,000 --> 00:27:55,080 Speaker 12: but we believe that ultimately, when you're dealing with the 546 00:27:55,200 --> 00:27:59,520 Speaker 12: scaling exercise that looks like what is going on within Ai, 547 00:28:00,080 --> 00:28:03,280 Speaker 12: you're always going to wind up using partners. 548 00:28:03,440 --> 00:28:05,359 Speaker 13: It's just the nature of it. You need to build 549 00:28:05,440 --> 00:28:06,639 Speaker 13: so much so fast. 550 00:28:06,760 --> 00:28:11,440 Speaker 12: So broadly, we're very confident that there's really great opportunities 551 00:28:11,440 --> 00:28:13,040 Speaker 12: for us to continue to work with. 552 00:28:14,720 --> 00:28:16,879 Speaker 13: A broad set of companies. You know. 553 00:28:17,359 --> 00:28:19,960 Speaker 12: I spoke a little bit about this on the earnings also, 554 00:28:20,000 --> 00:28:22,840 Speaker 12: which was you know, in the last eight weeks, we've 555 00:28:22,840 --> 00:28:26,680 Speaker 12: seen two of our hyper scale our clients come back 556 00:28:26,880 --> 00:28:34,919 Speaker 12: and execute extensions and broaden their contractual relationship with us. 557 00:28:34,920 --> 00:28:38,120 Speaker 12: It's very exciting and it is representative of space that's 558 00:28:38,160 --> 00:28:43,840 Speaker 12: broadly trying to address this systemic imbalance of which you know, 559 00:28:43,920 --> 00:28:48,120 Speaker 12: Corewave is a wonderful solution. We deliver, you know, best 560 00:28:48,120 --> 00:28:51,240 Speaker 12: in class technology, best in class software stack to be 561 00:28:51,320 --> 00:28:55,760 Speaker 12: able to allow different users across the space to really 562 00:28:56,200 --> 00:28:58,320 Speaker 12: take advantage of the infrastructure that we're building. 563 00:28:58,800 --> 00:29:01,560 Speaker 5: What a rich deep dive with the call we CEO. 564 00:29:03,080 --> 00:29:05,240 Speaker 3: This is Bloomberg Tech, and you're looking at a live 565 00:29:05,240 --> 00:29:08,640 Speaker 3: shot of the principal room. Check out the Bloomberg Tech podcast. 566 00:29:08,840 --> 00:29:10,479 Speaker 3: You can find it on the terminal as well as 567 00:29:10,520 --> 00:29:14,520 Speaker 3: online on Apple, Spotify and iHeart this is Bloomberg. 568 00:29:22,680 --> 00:29:27,240 Speaker 6: This is a very unique solution allows Invidia to expand 569 00:29:27,560 --> 00:29:33,280 Speaker 6: into China. It can make in Vidia chips the bellweather 570 00:29:33,760 --> 00:29:37,520 Speaker 6: for Chinese technology, and then the US taxpayer gets a 571 00:29:37,560 --> 00:29:38,000 Speaker 6: share of that. 572 00:29:38,320 --> 00:29:41,360 Speaker 3: Key words unique, Is it unique to Invidia an amt 573 00:29:41,640 --> 00:29:43,560 Speaker 3: or is this a model for other companies? 574 00:29:43,920 --> 00:29:44,480 Speaker 2: I think we. 575 00:29:44,480 --> 00:29:47,440 Speaker 6: Could see it in other industries over time. I think 576 00:29:47,520 --> 00:29:52,120 Speaker 6: you know right now this is unique. But now that 577 00:29:52,160 --> 00:29:55,000 Speaker 6: we have the model and the beta test, why not 578 00:29:55,120 --> 00:29:55,640 Speaker 6: expand it? 579 00:29:56,040 --> 00:29:59,760 Speaker 4: Treasury Secretary Scott beston joining Bloomberg TV earlier today. Let's 580 00:29:59,760 --> 00:30:02,600 Speaker 4: talk more about what this unique deal can mean for 581 00:30:02,640 --> 00:30:05,120 Speaker 4: companies in the US and in China. Mischeal Green has 582 00:30:05,200 --> 00:30:07,479 Speaker 4: found a managing partner of lead Edge Capital. You're an 583 00:30:07,520 --> 00:30:11,080 Speaker 4: investor in Chinese names of the past, the IPOs, Valie, Baba, 584 00:30:11,120 --> 00:30:13,680 Speaker 4: Byte Dance, you hold a course, but you're also in 585 00:30:13,800 --> 00:30:17,200 Speaker 4: many other areas and industries. We heard in that conversation 586 00:30:17,360 --> 00:30:20,200 Speaker 4: with Scott Besson that maybe this does apply to other 587 00:30:20,280 --> 00:30:23,160 Speaker 4: industries and maybe will this be a pay for play? 588 00:30:23,280 --> 00:30:24,920 Speaker 5: More broadly, what do you make of it? 589 00:30:27,080 --> 00:30:29,320 Speaker 14: You can figure out how to read the US and 590 00:30:29,400 --> 00:30:33,360 Speaker 14: Chinese government relations between you know what they say and 591 00:30:33,400 --> 00:30:37,400 Speaker 14: what they all do. Please please keep me enlightened and 592 00:30:37,440 --> 00:30:39,800 Speaker 14: inform me, because you know we're as confused as every 593 00:30:39,800 --> 00:30:44,880 Speaker 14: other viewer that you listen to. I do think both 594 00:30:44,880 --> 00:30:48,320 Speaker 14: of these countries leaders fully know that they need to 595 00:30:48,320 --> 00:30:51,600 Speaker 14: work together. You know, one hundred and fifty percent tariffs 596 00:30:51,600 --> 00:30:54,960 Speaker 14: on our companies selling to them, their companies selling to 597 00:30:55,000 --> 00:30:58,479 Speaker 14: us is just stupidity and all facets of it. 598 00:30:58,800 --> 00:30:59,800 Speaker 13: We're going to work together. 599 00:31:00,200 --> 00:31:00,400 Speaker 5: You know. 600 00:31:00,600 --> 00:31:05,000 Speaker 14: Look clear as it comes back to technology, you know AI, 601 00:31:06,040 --> 00:31:09,160 Speaker 14: the implementation of it is very global. I mean, I'm 602 00:31:09,160 --> 00:31:11,760 Speaker 14: talking in my own book here that we were big 603 00:31:11,800 --> 00:31:15,080 Speaker 14: investors on a dollar basis, and White Dance obviously very 604 00:31:15,080 --> 00:31:17,240 Speaker 14: small as a percentage just giving up big the company is, 605 00:31:17,280 --> 00:31:19,920 Speaker 14: but we think White Dance is one of the foremost 606 00:31:20,000 --> 00:31:21,280 Speaker 14: AI companies on the planet. 607 00:31:21,520 --> 00:31:22,040 Speaker 2: Hey, is there a. 608 00:31:22,040 --> 00:31:26,680 Speaker 4: Wary Mitchell though that if their own government is telling 609 00:31:26,720 --> 00:31:29,560 Speaker 4: them that they shouldn't really be going for age twenties. Yes, 610 00:31:29,600 --> 00:31:32,280 Speaker 4: they're called obsolete by President Trump and they're not really 611 00:31:32,320 --> 00:31:34,479 Speaker 4: able to access them as much as they'd like. Mitchell, 612 00:31:34,600 --> 00:31:37,120 Speaker 4: Is that a worry for the future of Bite Dances 613 00:31:37,160 --> 00:31:39,920 Speaker 4: the AI powerhouse alongside some of the other Chinese rivals. 614 00:31:41,120 --> 00:31:43,240 Speaker 13: I would not bet against. 615 00:31:44,600 --> 00:31:51,040 Speaker 14: Chinese ingenuity in designing systems, solutions and systems around You know, 616 00:31:51,120 --> 00:31:52,440 Speaker 14: you saw what happened. 617 00:31:52,120 --> 00:31:52,680 Speaker 13: In deep Sea. 618 00:31:53,640 --> 00:31:56,680 Speaker 14: Who knows how much they spent, but obviously they trained 619 00:31:56,720 --> 00:31:59,760 Speaker 14: a model and used it in independent tests. That was 620 00:32:00,080 --> 00:32:02,080 Speaker 14: you know, a fraction of a fraction of a fraction 621 00:32:02,120 --> 00:32:02,480 Speaker 14: what it. 622 00:32:02,400 --> 00:32:04,440 Speaker 13: Costs some of these US people to do without. Who 623 00:32:04,520 --> 00:32:05,440 Speaker 13: knows a bad access to. 624 00:32:05,440 --> 00:32:08,479 Speaker 14: These chips are not I wouldn't bet against the Chinese 625 00:32:08,480 --> 00:32:11,840 Speaker 14: semiconductor industry. Now it's not I'm actually we're not semi 626 00:32:11,840 --> 00:32:15,160 Speaker 14: conductor experts, but like I think, if Nvidia chips are 627 00:32:15,160 --> 00:32:17,400 Speaker 14: not allowed over there are certain chips aren't allowed in there. 628 00:32:17,600 --> 00:32:20,240 Speaker 14: I wouldn't bet against these companies and these entrepreneurs from 629 00:32:20,280 --> 00:32:26,040 Speaker 14: figuring out, you know, ingenious solutions around designing them. 630 00:32:26,400 --> 00:32:26,640 Speaker 13: Right. 631 00:32:26,720 --> 00:32:30,240 Speaker 3: The underlying assumption the Treasury secretaries mating is that China 632 00:32:30,280 --> 00:32:34,320 Speaker 3: wants America's chips, irrespective of how much revenue those companies 633 00:32:34,360 --> 00:32:36,960 Speaker 3: pays the Treasury or wherever it goes. Anyway, I actually 634 00:32:37,000 --> 00:32:39,320 Speaker 3: wanted to ask you about software. I had a fun 635 00:32:39,360 --> 00:32:42,800 Speaker 3: a few week here in London and various European and 636 00:32:42,800 --> 00:32:47,040 Speaker 3: British software names kind of went down and Monday dot 637 00:32:47,080 --> 00:32:49,040 Speaker 3: Com is at the heart of it. That's the story 638 00:32:49,200 --> 00:32:54,440 Speaker 3: where it's like no code, traditional SaaS has bad print, 639 00:32:54,480 --> 00:32:56,720 Speaker 3: and the market's like, oh AI makes all of this 640 00:32:56,800 --> 00:32:58,960 Speaker 3: kind of legacy software stuff not very good anymore. 641 00:32:59,240 --> 00:32:59,520 Speaker 13: Right? 642 00:33:00,040 --> 00:33:01,480 Speaker 2: Could you explain that to me? You kind of know 643 00:33:01,560 --> 00:33:02,720 Speaker 2: this this field. 644 00:33:04,360 --> 00:33:06,120 Speaker 13: Yeah, So it's it's funny. 645 00:33:06,680 --> 00:33:09,480 Speaker 14: At a higher level, a lot of these like software 646 00:33:09,480 --> 00:33:14,920 Speaker 14: companies are actually in no man's land. You have half 647 00:33:15,000 --> 00:33:18,240 Speaker 14: the investors out there screaming for growth. You have the 648 00:33:18,280 --> 00:33:21,120 Speaker 14: other half of the investors out there screaming for profits 649 00:33:21,400 --> 00:33:23,920 Speaker 14: and on a value on multiples of profits. And it's 650 00:33:23,920 --> 00:33:27,120 Speaker 14: like this tuggle work. The companies aren't growing as fast 651 00:33:27,160 --> 00:33:31,400 Speaker 14: now because they're really really freaking big, and the much 652 00:33:31,400 --> 00:33:34,360 Speaker 14: smaller companies and software are still growing fast because there's 653 00:33:34,440 --> 00:33:36,840 Speaker 14: not nearly as big. When you're two billion of revenue, 654 00:33:36,880 --> 00:33:39,160 Speaker 14: it's a lot harder and forty percent than it is 655 00:33:39,160 --> 00:33:42,560 Speaker 14: if you're like two hundred million of revenue. Right, I 656 00:33:42,600 --> 00:33:46,320 Speaker 14: can tell you we are investors in our primary business 657 00:33:46,400 --> 00:33:53,440 Speaker 14: is investing in application software companies, you know, And I 658 00:33:53,480 --> 00:33:56,360 Speaker 14: will tell you that almost every one of our companies 659 00:33:56,920 --> 00:33:59,800 Speaker 14: is using AI to become more productive. 660 00:34:00,120 --> 00:34:00,280 Speaker 13: You know. 661 00:34:00,320 --> 00:34:03,000 Speaker 14: We have a company up in Toronto Gravity that may 662 00:34:03,000 --> 00:34:05,360 Speaker 14: have I don't know, ten to fifteen software engineers. They 663 00:34:05,400 --> 00:34:07,160 Speaker 14: can now use it to have the equivalent of forty 664 00:34:07,160 --> 00:34:09,560 Speaker 14: five software engineers and just be more productive. But they're 665 00:34:09,560 --> 00:34:11,799 Speaker 14: not firing all their software engineers. They think people who 666 00:34:11,800 --> 00:34:15,480 Speaker 14: work with this code, you know. Our belief is that 667 00:34:15,560 --> 00:34:18,280 Speaker 14: if you are like software that's like system of record 668 00:34:18,960 --> 00:34:21,399 Speaker 14: and you have data, we actually think that it's really 669 00:34:21,440 --> 00:34:24,400 Speaker 14: really valuable. And I don't have to tell the viewers 670 00:34:24,440 --> 00:34:26,279 Speaker 14: out there that if you if you know, if the 671 00:34:26,320 --> 00:34:30,200 Speaker 14: work they are going to legacy companies. A lot of 672 00:34:30,280 --> 00:34:35,400 Speaker 14: legacy companies are going to massively benefit from AI, just 673 00:34:35,840 --> 00:34:38,880 Speaker 14: like they did with the Internet. Like the biggest beneficial 674 00:34:38,920 --> 00:34:41,400 Speaker 14: of the Internet may have been like you know, you know, 675 00:34:41,800 --> 00:34:45,719 Speaker 14: you know, literally a iPhone, people like Amazon and Facebook 676 00:34:45,760 --> 00:34:49,440 Speaker 14: and Google and Microsoft. It was it was around before mobile, 677 00:34:49,760 --> 00:34:51,799 Speaker 14: Like these are the guys that benefited. You know, who's 678 00:34:51,800 --> 00:34:58,320 Speaker 14: going to win Snowflake, salesforce, workday, data dog, Private companies 679 00:34:58,360 --> 00:35:01,480 Speaker 14: like Gafana, public companies like Toasts, like all these companies 680 00:35:01,480 --> 00:35:03,400 Speaker 14: are going to use them to be that much more productive. 681 00:35:03,719 --> 00:35:07,080 Speaker 14: We think ninety to ninety five percent of the AI 682 00:35:07,239 --> 00:35:08,919 Speaker 14: application software companies. 683 00:35:08,560 --> 00:35:10,560 Speaker 13: Getting built today are zeros. 684 00:35:10,920 --> 00:35:14,520 Speaker 14: Horrible economics, negative gross margins, burning money like crazy. 685 00:35:15,560 --> 00:35:17,440 Speaker 3: Okay, so in the year's time, let's check back and 686 00:35:17,480 --> 00:35:19,440 Speaker 3: we'll keep track of that. On Mitchell Green, founder and 687 00:35:19,480 --> 00:35:22,719 Speaker 3: managing partner lead Aage Capital, great heavy back on the show. 688 00:35:23,239 --> 00:35:25,880 Speaker 3: Two launches blasting off in the last twenty four hours, 689 00:35:25,960 --> 00:35:29,680 Speaker 3: ULA's Vulcan rocket on its first national security mission in 690 00:35:29,719 --> 00:35:33,719 Speaker 3: Europe's Arian six completing just its third mission. Ever, let's 691 00:35:33,719 --> 00:35:37,080 Speaker 3: get more from Bloomberg'slauren Grass, who leads our space coverage. 692 00:35:37,120 --> 00:35:39,080 Speaker 3: I'm going to start the ULA launch. Tell me about it. 693 00:35:39,120 --> 00:35:40,200 Speaker 3: Why is it significant? 694 00:35:41,080 --> 00:35:41,920 Speaker 2: Well, this was. 695 00:35:41,880 --> 00:35:44,000 Speaker 15: The third launch for the Vulcan rocket, but as you 696 00:35:44,040 --> 00:35:47,399 Speaker 15: mentioned earlier, it was their first national security mission, which 697 00:35:47,400 --> 00:35:49,200 Speaker 15: is really what Vulcan. 698 00:35:49,000 --> 00:35:49,880 Speaker 13: Was designed to do. 699 00:35:50,320 --> 00:35:54,440 Speaker 15: ULA as one of an elite group of launch providers 700 00:35:54,480 --> 00:36:00,360 Speaker 15: that can launch the Defense Department's most sensitive national security satellite, 701 00:36:00,600 --> 00:36:03,600 Speaker 15: but this was their first time doing so with this 702 00:36:03,640 --> 00:36:06,920 Speaker 15: particular rocket. They had to receive certification for it. So 703 00:36:06,960 --> 00:36:10,200 Speaker 15: first they had to launch two rockets or two missions 704 00:36:10,239 --> 00:36:12,640 Speaker 15: with Vulcan to prove to the Space Force that it 705 00:36:12,640 --> 00:36:17,160 Speaker 15: could handle launching national security satellites. And it actually suffered 706 00:36:17,400 --> 00:36:21,000 Speaker 15: a tiny issue on its second flight. A strap on 707 00:36:21,080 --> 00:36:24,359 Speaker 15: booster had a small explosion. The rockets still made it 708 00:36:24,360 --> 00:36:28,440 Speaker 15: to orbit, but it delayed the certification process. However, it 709 00:36:28,480 --> 00:36:31,360 Speaker 15: did receive that certification in March and then ultimately was 710 00:36:31,400 --> 00:36:34,319 Speaker 15: able to do this launch, and so that'll pave the 711 00:36:34,360 --> 00:36:37,160 Speaker 15: way for even more national security missions moving forward. 712 00:36:37,719 --> 00:36:41,200 Speaker 4: And turning our attention to Europe and Ariane six. How 713 00:36:41,280 --> 00:36:45,480 Speaker 4: much is this just countries entire areas of the globe 714 00:36:45,480 --> 00:36:48,960 Speaker 4: trying to wean themselves less on dependency from SpaceX and 715 00:36:49,080 --> 00:36:50,200 Speaker 4: have their own competitives. 716 00:36:50,960 --> 00:36:52,279 Speaker 15: Yeah, I think it was. There was a lot of 717 00:36:52,320 --> 00:36:55,520 Speaker 15: symmetry last night because these were the third flights of 718 00:36:55,560 --> 00:36:59,040 Speaker 15: both of these rockets, and both of these vehicles are 719 00:36:59,680 --> 00:37:02,760 Speaker 15: in this similar class to that of the SpaceX Falcon 720 00:37:02,840 --> 00:37:06,000 Speaker 15: nine rocket, which has essentially had a de facto monopoly 721 00:37:06,200 --> 00:37:08,680 Speaker 15: on the launch market for the last few years, at 722 00:37:08,760 --> 00:37:11,720 Speaker 15: least with this particular class of rockets. So the launches 723 00:37:11,760 --> 00:37:14,759 Speaker 15: of these two vehicles kind of do civilize, you know, 724 00:37:14,840 --> 00:37:17,439 Speaker 15: perhaps there are going to be more options for other 725 00:37:17,520 --> 00:37:21,160 Speaker 15: satellite providers in the future looking for this class of vehicle. 726 00:37:21,480 --> 00:37:24,440 Speaker 15: Of course, it's going to take some time. As I said, 727 00:37:24,520 --> 00:37:27,959 Speaker 15: these are the third flights. They both struggled to ramp 728 00:37:28,080 --> 00:37:30,720 Speaker 15: up in terms of their launch cadence, whereas the Falcon 729 00:37:30,800 --> 00:37:34,200 Speaker 15: nine is launching every few days, So it's going to 730 00:37:34,200 --> 00:37:35,839 Speaker 15: take a while for them to reach up. 731 00:37:35,880 --> 00:37:36,759 Speaker 13: But at least there. 732 00:37:36,680 --> 00:37:39,920 Speaker 15: Are more and more rockets of this caliber coming online 733 00:37:39,960 --> 00:37:41,680 Speaker 15: that satellite operators can turn. 734 00:37:41,560 --> 00:37:45,320 Speaker 4: To perhaps produce that logjam. Bloomberg's long brush. Great reporting 735 00:37:45,360 --> 00:37:47,520 Speaker 4: is always thank you very much. Indeed, Now that does 736 00:37:47,600 --> 00:37:50,160 Speaker 4: it for this edition of Bloomberg Tech. What a lot 737 00:37:50,160 --> 00:37:51,839 Speaker 4: of earnings we still digested and. 738 00:37:51,800 --> 00:37:52,359 Speaker 5: Got to come. 739 00:37:53,400 --> 00:37:56,400 Speaker 3: Yeah, and a critical conversation with a Treasury secretary recap 740 00:37:56,440 --> 00:37:58,040 Speaker 3: on the podcast. You know where to find it on 741 00:37:58,040 --> 00:38:01,759 Speaker 3: the Bloomberg terminal as well as online, Apple, Spotify and 742 00:38:01,880 --> 00:38:05,799 Speaker 3: on iHeart. From London and New York City, this is 743 00:38:05,800 --> 00:38:06,560 Speaker 3: Bloomberg Tech.