1 00:00:02,520 --> 00:00:13,399 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is live 2 00:00:13,440 --> 00:00:17,200 Speaker 1: from coast to coast with Caroline Hide in New York 3 00:00:17,560 --> 00:00:19,480 Speaker 1: and Eva Low in Sent Francisco. 4 00:00:24,440 --> 00:00:27,640 Speaker 2: This is Bloomberg Tech coming up. Intel returns to profitability. 5 00:00:27,680 --> 00:00:30,440 Speaker 2: It gives an upbeat revenue forecasts. Are the chip makers 6 00:00:30,520 --> 00:00:32,040 Speaker 2: comeback efforts working. 7 00:00:31,880 --> 00:00:34,919 Speaker 3: Plus banks for preparing to launch a thirty eight billion 8 00:00:35,040 --> 00:00:38,159 Speaker 3: dollar debt offering to help fund data centers tied to Oracle. 9 00:00:38,200 --> 00:00:39,559 Speaker 3: It's a record for AI. 10 00:00:39,440 --> 00:00:43,440 Speaker 2: Infrastructure, and Mistraus's CEO, Arthur Mench joins us on the 11 00:00:43,440 --> 00:00:46,879 Speaker 2: company's release of a new platform to help enterprise clients 12 00:00:47,159 --> 00:00:49,240 Speaker 2: make customizable AI tools. 13 00:00:49,280 --> 00:00:51,560 Speaker 3: An important private market conversation. We get back to the 14 00:00:51,600 --> 00:00:53,680 Speaker 3: public markets to end this week. We are at a 15 00:00:53,680 --> 00:00:55,480 Speaker 3: new record high when you're looking at the SMP, when 16 00:00:55,480 --> 00:00:57,280 Speaker 3: you're looking at the NASDAC, we're up two percent of 17 00:00:57,320 --> 00:00:59,280 Speaker 3: the course of the last five days. But a real 18 00:00:59,360 --> 00:01:01,920 Speaker 3: tick hire on the day ed the macro picture, the 19 00:01:01,960 --> 00:01:05,000 Speaker 3: inflation cooler than many had worried about, and indeed that 20 00:01:05,040 --> 00:01:06,880 Speaker 3: gives a bedroom to run when it comes to maybe 21 00:01:06,880 --> 00:01:09,240 Speaker 3: some more cuts that the market has already been pricing in. 22 00:01:09,360 --> 00:01:11,759 Speaker 3: We've got China us. We've got plenty to be digesting, 23 00:01:11,760 --> 00:01:12,800 Speaker 3: and you're looking at earnings. 24 00:01:13,480 --> 00:01:16,920 Speaker 2: Yeah, in the earnings context, Intel's post earnings rally has 25 00:01:17,000 --> 00:01:20,040 Speaker 2: basically completely faded. A gain of more than seven percent 26 00:01:20,360 --> 00:01:23,399 Speaker 2: is now less than one percent, but profitable for the 27 00:01:23,400 --> 00:01:26,479 Speaker 2: first time in a long time on a net income basis. 28 00:01:26,680 --> 00:01:29,720 Speaker 2: The PC market was better than they expected. They're making 29 00:01:29,760 --> 00:01:33,560 Speaker 2: some progress in server, even a little bit in foundry. 30 00:01:34,200 --> 00:01:36,880 Speaker 2: The issue is that the quarter was all about getting 31 00:01:36,880 --> 00:01:39,559 Speaker 2: money from anyone they could, clearing some of the debt, 32 00:01:39,880 --> 00:01:41,880 Speaker 2: and there's still a lot of unknowns about how far 33 00:01:42,000 --> 00:01:43,600 Speaker 2: there's left to go on this turnaround plan. 34 00:01:43,760 --> 00:01:46,039 Speaker 3: Correct, Yeah, let's get about where some of the holes 35 00:01:46,040 --> 00:01:48,960 Speaker 3: are still left on Intel Counjin surmanis with US beming 36 00:01:49,000 --> 00:01:52,520 Speaker 3: intelligence senior analysts covering semiconductors, and we are still left 37 00:01:52,520 --> 00:01:54,920 Speaker 3: with a lot to chew on. Because clearly PC doing 38 00:01:54,920 --> 00:01:57,760 Speaker 3: a bit better, maybe even CPUs getting into those data centers. 39 00:01:57,760 --> 00:02:02,200 Speaker 3: But what about the next iteration of fabrication of chips. 40 00:02:04,400 --> 00:02:07,160 Speaker 4: This result shows the first sign in the right direction, 41 00:02:07,280 --> 00:02:10,200 Speaker 4: sort of a turnaround, a beginning of a turnaround. You know, 42 00:02:10,400 --> 00:02:12,880 Speaker 4: the gross margin headwinds. Like you said, the challenges are 43 00:02:12,960 --> 00:02:16,000 Speaker 4: not gone away. But what they showed yesterday where they 44 00:02:16,080 --> 00:02:18,960 Speaker 4: are running their demand is running ahead of the supply, 45 00:02:19,040 --> 00:02:21,119 Speaker 4: which it will be for the first chapter twenty six. 46 00:02:21,360 --> 00:02:24,600 Speaker 4: There were structural gross margin improvements, though we will not 47 00:02:24,760 --> 00:02:28,280 Speaker 4: see a gross margin expansion next year, primarily due to 48 00:02:28,360 --> 00:02:31,360 Speaker 4: the new eighteen A coming on their exit from the 49 00:02:31,360 --> 00:02:34,000 Speaker 4: ALTA business, which was their highest gross margin business. 50 00:02:34,200 --> 00:02:35,679 Speaker 5: But structurally under. 51 00:02:35,520 --> 00:02:37,760 Speaker 4: When you peel the onion, we like what they're doing. 52 00:02:37,960 --> 00:02:40,040 Speaker 4: Most of the eighteen A will be moving from Oregon 53 00:02:40,080 --> 00:02:42,800 Speaker 4: to Arizona, which is a better cost structure fab to 54 00:02:42,800 --> 00:02:45,560 Speaker 4: begin with, a lot more volume will be coming back 55 00:02:45,600 --> 00:02:48,680 Speaker 4: to Intel's foundries, which is better for them as they 56 00:02:48,720 --> 00:02:52,000 Speaker 4: go through the initial transition cost and the revenue scale, 57 00:02:52,040 --> 00:02:54,720 Speaker 4: which it is showing from the higher demand and PCA 58 00:02:54,840 --> 00:02:59,400 Speaker 4: Data center improves slowly structurally the overall gross margins to 59 00:02:59,400 --> 00:03:00,240 Speaker 4: start to keep well. 60 00:03:01,480 --> 00:03:03,200 Speaker 2: I don't know what happened, Conjum, but in the time 61 00:03:03,240 --> 00:03:07,000 Speaker 2: you've been speaking, Intel's now flat and eliminated all of 62 00:03:07,040 --> 00:03:09,239 Speaker 2: its gain of the day. And I'm not saying that's 63 00:03:09,280 --> 00:03:13,760 Speaker 2: your fault. I'm just making the observation. Look, when I 64 00:03:13,800 --> 00:03:16,880 Speaker 2: spoke to the CFO Dave's Instagram the phone, he was 65 00:03:17,080 --> 00:03:19,440 Speaker 2: a bit surprised by some of the end markets that 66 00:03:19,440 --> 00:03:22,640 Speaker 2: they're relying on. On the product side, servers in particular. 67 00:03:22,800 --> 00:03:26,480 Speaker 2: The basic argument they're making is the hyperscalers has suddenly 68 00:03:26,520 --> 00:03:30,120 Speaker 2: realized that you have to at some point update your CPUs, 69 00:03:30,400 --> 00:03:32,639 Speaker 2: you have to invest in them, and so now they're 70 00:03:32,639 --> 00:03:34,720 Speaker 2: saying that actually on a year on year basis, they'll 71 00:03:34,720 --> 00:03:35,680 Speaker 2: see unit growth. 72 00:03:35,840 --> 00:03:36,760 Speaker 6: What did you make of that? 73 00:03:38,400 --> 00:03:41,040 Speaker 4: You know, that is a very credible story to believe in. 74 00:03:41,120 --> 00:03:44,400 Speaker 4: We have seen signs of this in other markets. For example, 75 00:03:44,480 --> 00:03:47,240 Speaker 4: the storage server market has been seeing a big demand 76 00:03:47,240 --> 00:03:49,480 Speaker 4: when it comes to HDD. So when you think about 77 00:03:49,520 --> 00:03:52,040 Speaker 4: every time when we're pinging something like a co pilot, 78 00:03:52,480 --> 00:03:56,040 Speaker 4: it's going and clearing or analyzing data which was sitting 79 00:03:56,080 --> 00:03:58,520 Speaker 4: dormant for the past six months, so the storage servers 80 00:03:58,560 --> 00:03:59,520 Speaker 4: were not really. 81 00:03:59,280 --> 00:04:00,360 Speaker 5: Using them cuddly. 82 00:04:00,400 --> 00:04:03,040 Speaker 4: Now we're pinging them four to five times, So that 83 00:04:03,120 --> 00:04:05,840 Speaker 4: does you know, it is a credible story to believe 84 00:04:05,880 --> 00:04:09,440 Speaker 4: that the need for CPO, even outside AI servers, is 85 00:04:09,480 --> 00:04:13,240 Speaker 4: going to increase now as we involve more and more AI. 86 00:04:13,040 --> 00:04:13,560 Speaker 5: In our world. 87 00:04:13,600 --> 00:04:17,760 Speaker 2: Day Conjensavania Bloomberg Intelligence. Later in the show, we'll get 88 00:04:17,800 --> 00:04:21,120 Speaker 2: more on Intel from the cell side. Meanwhile, banks are 89 00:04:21,160 --> 00:04:25,360 Speaker 2: reportedly preparing a thirty eight billion dollar debt offering for 90 00:04:25,560 --> 00:04:28,920 Speaker 2: data centers tied to Oracle. Sources say the deal could 91 00:04:28,960 --> 00:04:32,280 Speaker 2: launch as soon as Monday, with JP Morgan a MUFG 92 00:04:32,520 --> 00:04:35,799 Speaker 2: among the lead banks. Here to discuss, Bloomberg Intelligence Senior 93 00:04:35,839 --> 00:04:39,960 Speaker 2: tech analyst Anna rag Rana, there's a key point of 94 00:04:40,040 --> 00:04:44,200 Speaker 2: clarification here that Caroline made to the team earlier in 95 00:04:44,240 --> 00:04:46,839 Speaker 2: the chat, and it's not Oracle taking on this debt. 96 00:04:47,200 --> 00:04:51,279 Speaker 2: Its advantage the developer who will do the project. Even so, 97 00:04:52,080 --> 00:04:54,600 Speaker 2: when you see a news piece like that about that 98 00:04:54,720 --> 00:04:57,640 Speaker 2: level of debt supporting the build out in infrastructure, what 99 00:04:57,800 --> 00:04:58,840 Speaker 2: is your reaction to it. 100 00:05:00,360 --> 00:05:02,560 Speaker 7: No, that's a very good point, and in fact, you know, 101 00:05:02,600 --> 00:05:05,560 Speaker 7: I had a very good conversation with our credit analyst, 102 00:05:06,000 --> 00:05:08,960 Speaker 7: Rob Schiffman, and we discussed this quite a bit. We 103 00:05:09,040 --> 00:05:12,080 Speaker 7: have seen something like this coming from other places as well, 104 00:05:12,120 --> 00:05:16,040 Speaker 7: which is when you have a contract from a particular vendor, 105 00:05:16,360 --> 00:05:19,520 Speaker 7: you know you can create, you could an asset back 106 00:05:19,560 --> 00:05:24,800 Speaker 7: securitization product where the contract itself says there is revenue 107 00:05:24,800 --> 00:05:26,960 Speaker 7: that's going to come in the future. So the question 108 00:05:27,120 --> 00:05:30,640 Speaker 7: is whether they're going to be appetite for such large 109 00:05:31,120 --> 00:05:33,600 Speaker 7: dead deals going forward as well, because I think that's 110 00:05:33,640 --> 00:05:37,520 Speaker 7: critical for recognizing a lot of that RPO that's coming 111 00:05:37,560 --> 00:05:41,280 Speaker 7: in into revenue. Otherwise, you know it's going to be 112 00:05:41,400 --> 00:05:43,480 Speaker 7: very difficult to convert that into sales. 113 00:05:44,360 --> 00:05:47,719 Speaker 3: This is about yield, and for the facilities related to advantage, 114 00:05:47,720 --> 00:05:50,360 Speaker 3: they're expected to come to you in about four years 115 00:05:50,520 --> 00:05:53,200 Speaker 3: is about two one year extension options. You're getting two 116 00:05:53,200 --> 00:05:55,680 Speaker 3: and a half percentage points over benchmark those. So people 117 00:05:55,880 --> 00:05:59,280 Speaker 3: who are clamoring to get exposure to the AI narrative 118 00:05:59,600 --> 00:06:01,800 Speaker 3: now just have to do it through equity. They can 119 00:06:01,839 --> 00:06:03,360 Speaker 3: do it through debt, and they can do it in 120 00:06:03,400 --> 00:06:06,120 Speaker 3: a nice yield. More broadly, are we going to see 121 00:06:06,160 --> 00:06:08,919 Speaker 3: these sorts of packages come in this sort of sheer 122 00:06:09,080 --> 00:06:11,280 Speaker 3: scale because of the need that we've got out there 123 00:06:11,360 --> 00:06:11,839 Speaker 3: at the moment. 124 00:06:13,480 --> 00:06:16,240 Speaker 7: So you have to because I think about it, if 125 00:06:16,279 --> 00:06:19,800 Speaker 7: Open Eye has signed a deal worth three hundred billion 126 00:06:19,839 --> 00:06:22,960 Speaker 7: dollars with Oracle, you know, how are you going to 127 00:06:23,000 --> 00:06:26,040 Speaker 7: finance that? How are you going to convert that contract 128 00:06:26,160 --> 00:06:28,880 Speaker 7: into sales? And you need data centers to come there, 129 00:06:29,080 --> 00:06:31,600 Speaker 7: you need equipment, and finally that needs to be realized. 130 00:06:31,640 --> 00:06:34,359 Speaker 7: So we are expecting a lot more in the market. 131 00:06:34,400 --> 00:06:37,000 Speaker 7: The question is whether the private debt market has the 132 00:06:37,040 --> 00:06:41,120 Speaker 7: ability to, you know, basically absorb this level of. 133 00:06:42,640 --> 00:06:43,159 Speaker 5: Debt or not. 134 00:06:44,200 --> 00:06:47,040 Speaker 3: Arak Rana, I'm pretty big intelligence. We'll see how this 135 00:06:47,320 --> 00:06:49,719 Speaker 3: does get absorbed. It's coming to the market as soon 136 00:06:49,760 --> 00:06:52,560 Speaker 3: as Monday. But let's just talk more broadly about what's 137 00:06:52,560 --> 00:06:54,240 Speaker 3: happening in the debt markets, when it comes to tech, 138 00:06:54,240 --> 00:06:56,440 Speaker 3: when it's happening in the equity markets, which are actually 139 00:06:56,920 --> 00:06:59,400 Speaker 3: tech help performing in that particular area. Today, you've got earnings, 140 00:06:59,400 --> 00:07:01,280 Speaker 3: you've got hopes on the China US trade talks, you've 141 00:07:01,279 --> 00:07:04,160 Speaker 3: got stock ticketing on record. After that CPI number came 142 00:07:04,200 --> 00:07:07,000 Speaker 3: in with well a relief that the Fed will potentially 143 00:07:07,120 --> 00:07:08,599 Speaker 3: keep on cutting at the rate in the market things. 144 00:07:08,640 --> 00:07:11,600 Speaker 3: Martin Norton's with US Chief Investment Strategies at EMPOWER. I 145 00:07:11,640 --> 00:07:13,320 Speaker 3: want to go back to what we're just talking about 146 00:07:13,520 --> 00:07:15,600 Speaker 3: and the debt that's coming to the market and the 147 00:07:15,680 --> 00:07:18,120 Speaker 3: absorption that's going to be happening. I'm looking at a 148 00:07:18,120 --> 00:07:20,040 Speaker 3: story right now saying that the Bank of England is 149 00:07:20,040 --> 00:07:23,520 Speaker 3: actually probing data center lending because they're weren't about AI 150 00:07:23,600 --> 00:07:26,440 Speaker 3: bubbles brewing. Is this something you're starting to hear about 151 00:07:26,440 --> 00:07:26,920 Speaker 3: in the market. 152 00:07:26,960 --> 00:07:27,280 Speaker 8: Martyr. 153 00:07:28,440 --> 00:07:31,520 Speaker 9: Well, it's so interesting because a lot of the rationale 154 00:07:31,760 --> 00:07:35,480 Speaker 9: for the I guess complacency around the AI trade has 155 00:07:35,520 --> 00:07:41,000 Speaker 9: been that this is largely being funded by very well capitalized, 156 00:07:41,160 --> 00:07:45,720 Speaker 9: very strong hyperscalers, and the companies are not taking on debt. 157 00:07:45,760 --> 00:07:49,320 Speaker 9: They're using what they have to extend into this space. 158 00:07:49,720 --> 00:07:53,000 Speaker 9: But now in the most recent month, we are beginning 159 00:07:53,040 --> 00:07:55,440 Speaker 9: to see more debt issuance, and I think when you 160 00:07:55,480 --> 00:07:58,000 Speaker 9: think about the scale of investment and the ratio of 161 00:07:58,040 --> 00:08:01,480 Speaker 9: capex to revenue that we're seeing, even the hyperscalers, it 162 00:08:01,560 --> 00:08:04,000 Speaker 9: does argue that we're going to have to use a 163 00:08:04,040 --> 00:08:07,280 Speaker 9: broader range of financing to meet some of the targets 164 00:08:07,280 --> 00:08:10,000 Speaker 9: that we have, And of course that's the signal that 165 00:08:10,360 --> 00:08:13,200 Speaker 9: folks are looking for that there is an AI bubble now, 166 00:08:13,440 --> 00:08:17,240 Speaker 9: you know. I think there's a real difference between extreme valuations, 167 00:08:17,280 --> 00:08:19,800 Speaker 9: which is where I think we are in an AI bubble. 168 00:08:19,840 --> 00:08:22,520 Speaker 9: I think the sentiment has to get more aggressive. I 169 00:08:22,520 --> 00:08:24,920 Speaker 9: think we would have to see far more debt issue. 170 00:08:25,120 --> 00:08:29,720 Speaker 9: I think we've our I guess kind of wildness around it. 171 00:08:30,520 --> 00:08:32,840 Speaker 3: We're getting a few hits to the line. Mart we 172 00:08:32,840 --> 00:08:37,000 Speaker 3: need more compute I'm interested in. Look, five trillion is 173 00:08:37,000 --> 00:08:38,640 Speaker 3: what the spending is likely to be up to twenty 174 00:08:38,640 --> 00:08:40,559 Speaker 3: thirty if we're going to get the data center and 175 00:08:40,559 --> 00:08:45,600 Speaker 3: compute necessary to fuel the AI viewpoint. To that end, 176 00:08:45,640 --> 00:08:48,080 Speaker 3: when you're thinking about clients coming to you saying I 177 00:08:48,120 --> 00:08:50,679 Speaker 3: want exposure, I want it to be cross asset. Are 178 00:08:50,720 --> 00:08:53,959 Speaker 3: you saying don't how you talking about the diversification between 179 00:08:54,160 --> 00:08:57,160 Speaker 3: equity exposure and debt exposure foot bonds and the like. 180 00:08:58,240 --> 00:09:00,920 Speaker 9: Well, at this point, I mean the primary to AI 181 00:09:01,160 --> 00:09:03,679 Speaker 9: still within the equity market. I think this is something 182 00:09:03,679 --> 00:09:06,600 Speaker 9: that especially for the active credit managers, it is an 183 00:09:06,640 --> 00:09:07,880 Speaker 9: opportunity to vet. 184 00:09:08,040 --> 00:09:10,040 Speaker 8: You know, you can get that added yield. 185 00:09:09,800 --> 00:09:12,080 Speaker 9: As suggested, but I do think people want to be 186 00:09:12,120 --> 00:09:14,560 Speaker 9: really cautious in terms of adding that debt. One thing 187 00:09:14,600 --> 00:09:17,000 Speaker 9: that we're talking about a lot in the credit market 188 00:09:17,080 --> 00:09:19,560 Speaker 9: is just how tight spreads are, and so that is 189 00:09:20,480 --> 00:09:23,120 Speaker 9: we want to watch to make sure that isn't you know, 190 00:09:23,160 --> 00:09:25,959 Speaker 9: evaluation risk within the within the credit market. 191 00:09:27,040 --> 00:09:29,840 Speaker 2: Martya earnings was a factor in this market. 192 00:09:29,840 --> 00:09:30,240 Speaker 6: This morning. 193 00:09:30,280 --> 00:09:32,400 Speaker 2: When I came to my desk, we showed Intel actually 194 00:09:32,480 --> 00:09:36,480 Speaker 2: is now basically flat. Even so, in the course of 195 00:09:36,480 --> 00:09:40,080 Speaker 2: a conversation we had with Intel CFO Dave's insner. He 196 00:09:40,200 --> 00:09:42,520 Speaker 2: made for an interesting case study, which is that he 197 00:09:42,600 --> 00:09:45,920 Speaker 2: said they had been very cautious about tariffs, but the 198 00:09:45,960 --> 00:09:48,679 Speaker 2: impact wasn't there in the end, and actually in the 199 00:09:48,679 --> 00:09:52,400 Speaker 2: PC segment on which they depend, shipments were very strong, 200 00:09:52,520 --> 00:09:55,520 Speaker 2: stronger than they had anticipated. Just as a case study, 201 00:09:55,880 --> 00:09:57,680 Speaker 2: you know, that's really interesting data to me. 202 00:09:57,760 --> 00:09:58,600 Speaker 6: What do you make of it? 203 00:09:59,440 --> 00:10:02,720 Speaker 9: I mean, it's totally interesting, and it really echoes what 204 00:10:02,800 --> 00:10:05,400 Speaker 9: we've seen over the course of twenty twenty five, which 205 00:10:05,440 --> 00:10:09,320 Speaker 9: is this sea change in trade policy and yet really 206 00:10:09,360 --> 00:10:13,600 Speaker 9: no discernible effect from either an earnings perspective or from 207 00:10:13,679 --> 00:10:17,640 Speaker 9: an inflation perspective. Our emphasis over this period has been 208 00:10:17,880 --> 00:10:21,520 Speaker 9: expecting to see some hit to earnings, less concern on 209 00:10:21,559 --> 00:10:24,280 Speaker 9: the inflation front, and I think one thing that we're 210 00:10:24,280 --> 00:10:26,600 Speaker 9: really learning over this process is that you can see 211 00:10:26,600 --> 00:10:30,320 Speaker 9: a sea change in policy and yet not necessarily see 212 00:10:30,320 --> 00:10:33,280 Speaker 9: the impact immediately. I think the concern I would raise 213 00:10:33,320 --> 00:10:35,600 Speaker 9: to investors is just because you don't see an immediate 214 00:10:35,640 --> 00:10:38,520 Speaker 9: impact doesn't mean there isn't an impact. When we look 215 00:10:38,520 --> 00:10:42,400 Speaker 9: at that long term implications of globalization on earnings, it 216 00:10:42,400 --> 00:10:45,960 Speaker 9: has been a real positive for the US and globally, 217 00:10:46,040 --> 00:10:48,480 Speaker 9: and so as we roll that back, it stands to 218 00:10:48,600 --> 00:10:51,240 Speaker 9: reason that it is a headwind. Maybe a headwind that 219 00:10:51,280 --> 00:10:53,480 Speaker 9: we can overcome, but a headwind nevertheless. 220 00:10:54,240 --> 00:10:56,440 Speaker 2: Marta, please respond to what is one of the top 221 00:10:56,440 --> 00:10:59,800 Speaker 2: news stories of the day. President Trump says he's halted 222 00:11:00,000 --> 00:11:04,560 Speaker 2: trade talks with Canada because of an advertisement that they ran, 223 00:11:05,880 --> 00:11:10,040 Speaker 2: citing a Reagan era comment, you're aware of it. In response, 224 00:11:10,880 --> 00:11:14,240 Speaker 2: Mark Carney says that trade talks were making progress before 225 00:11:15,000 --> 00:11:18,480 Speaker 2: the president's post on true Social again as a case 226 00:11:18,520 --> 00:11:22,040 Speaker 2: study of trade and policy in this market. 227 00:11:22,320 --> 00:11:23,520 Speaker 6: Your reaction to it. 228 00:11:24,559 --> 00:11:26,920 Speaker 9: Well, I guess I would say that that trade talks 229 00:11:26,960 --> 00:11:29,120 Speaker 9: are the toddler that just won't go to bed. 230 00:11:29,400 --> 00:11:32,200 Speaker 8: I don't think this story is really over yet. 231 00:11:32,280 --> 00:11:36,440 Speaker 9: I mean, we have a lot of certainty, I guess 232 00:11:36,520 --> 00:11:39,440 Speaker 9: in terms of the overall effective terrif rate, but the 233 00:11:39,600 --> 00:11:42,640 Speaker 9: fine details of what those trade talks look like, yes, 234 00:11:42,720 --> 00:11:45,160 Speaker 9: with Canada, but also of course there's still a lot. 235 00:11:45,000 --> 00:11:46,800 Speaker 8: Of negotiation with China. 236 00:11:46,880 --> 00:11:48,920 Speaker 9: So I think this is something that will be this 237 00:11:49,040 --> 00:11:51,520 Speaker 9: kind of lingering volatility within the market. 238 00:11:51,840 --> 00:11:55,280 Speaker 3: Marta, you have a sea of parents of young children 239 00:11:55,360 --> 00:11:59,760 Speaker 3: who are just feeling that pain analogy really beautifully. Thank 240 00:11:59,800 --> 00:12:02,880 Speaker 3: your just I want to go back to the very 241 00:12:02,960 --> 00:12:06,640 Speaker 3: star of our conversation and they say that valuations you 242 00:12:06,760 --> 00:12:12,160 Speaker 3: think are extended where exactly and what will earnings have 243 00:12:12,240 --> 00:12:14,439 Speaker 3: to vindicate which types of companies. 244 00:12:15,720 --> 00:12:20,040 Speaker 9: Well, when we're looking at the US market broadly, really 245 00:12:20,200 --> 00:12:24,400 Speaker 9: every sector from our vantage point, with one exception, is 246 00:12:24,520 --> 00:12:27,880 Speaker 9: quite expensive. And when we talk about expensiveness, we're looking 247 00:12:27,920 --> 00:12:31,320 Speaker 9: at sectors and de siles of valuation relative to their 248 00:12:31,360 --> 00:12:34,240 Speaker 9: own history, and what we're seeing is valuations that are 249 00:12:34,280 --> 00:12:36,880 Speaker 9: really in those ninth and tenth deciles. And that's when 250 00:12:36,920 --> 00:12:40,160 Speaker 9: that starts to matter to perspective three year returns. When 251 00:12:40,200 --> 00:12:42,720 Speaker 9: we look under the hood and technology, we really see 252 00:12:42,720 --> 00:12:45,520 Speaker 9: it across industries. Now, that doesn't mean that these stocks 253 00:12:45,520 --> 00:12:48,720 Speaker 9: can't grind higher, and if we do see upside surprise 254 00:12:48,840 --> 00:12:53,160 Speaker 9: within earnings, potentially that could push the stock market even further. 255 00:12:53,480 --> 00:12:56,319 Speaker 9: I think the idea here is that there's just low immunity. 256 00:12:56,600 --> 00:12:58,840 Speaker 9: So if we were to get an earning season that 257 00:12:59,120 --> 00:13:01,840 Speaker 9: people expect, I think that's a lot harder to move 258 00:13:01,880 --> 00:13:02,600 Speaker 9: the stock market. 259 00:13:02,840 --> 00:13:04,440 Speaker 8: I will do a shout out to healthcare. 260 00:13:04,520 --> 00:13:07,200 Speaker 9: This is something we've been surfacing since the summer This 261 00:13:07,240 --> 00:13:10,560 Speaker 9: is one of those areas that is more attractively priced. 262 00:13:10,600 --> 00:13:13,360 Speaker 9: It has a lot of problems that it faces, but 263 00:13:13,440 --> 00:13:15,920 Speaker 9: it also has, you know, the potential to benefit from 264 00:13:15,960 --> 00:13:18,440 Speaker 9: something like AI. So that's one of those areas that 265 00:13:18,480 --> 00:13:20,240 Speaker 9: we're looking to in this environment. 266 00:13:21,320 --> 00:13:24,960 Speaker 2: Martin Orton, chief investment Strategist to empower, thank you very much. 267 00:13:25,520 --> 00:13:28,920 Speaker 2: A Clara Resources and Exploration and Mining Services provide a 268 00:13:29,000 --> 00:13:31,440 Speaker 2: plans to build a two hundred and twenty seventy seven 269 00:13:31,440 --> 00:13:34,520 Speaker 2: million dollar rare Earth's plant in Louisiana, the first of 270 00:13:34,559 --> 00:13:37,760 Speaker 2: its type in the US. This comes as Western nations 271 00:13:37,760 --> 00:13:41,720 Speaker 2: attempt to reduce reliance on China, currently the dominant supplier. 272 00:13:42,000 --> 00:13:45,439 Speaker 2: The facility will process material from m clara's clay deposits 273 00:13:45,440 --> 00:13:49,040 Speaker 2: in Brazil and Chile for magnets used in evs and 274 00:13:49,080 --> 00:13:53,000 Speaker 2: wind turbines, and construction is expected to be completed by 275 00:13:53,000 --> 00:13:54,160 Speaker 2: the end of twenty twenty seven. 276 00:13:54,760 --> 00:13:57,840 Speaker 3: And coming up so much for pet rocks, hey. JP 277 00:13:58,000 --> 00:14:00,439 Speaker 3: Morgan takes another big step into the crypto world. More 278 00:14:00,440 --> 00:14:02,320 Speaker 3: on that next. This is Bloomberg Tech. 279 00:14:17,760 --> 00:14:20,800 Speaker 2: JP Morgan is set to allow clients to use bitcoin 280 00:14:20,960 --> 00:14:24,560 Speaker 2: in Ether as collateral for loans. That's according to sources 281 00:14:24,920 --> 00:14:27,640 Speaker 2: the move marks a deeper step into crypto for Wall Street. 282 00:14:27,640 --> 00:14:31,640 Speaker 2: Bloomberg's digital finance reporter Emily Nicole broke the story, joins us, now, 283 00:14:32,280 --> 00:14:34,840 Speaker 2: I think it's really important to go through the mechanics 284 00:14:35,000 --> 00:14:40,440 Speaker 2: of what we think this will work as right, institutional clients, 285 00:14:40,920 --> 00:14:42,920 Speaker 2: what they can do is collateral and then what the 286 00:14:42,960 --> 00:14:44,440 Speaker 2: bank will do in return take it away. 287 00:14:45,000 --> 00:14:47,440 Speaker 10: Yes, so what we've been hearing is that JP Morgan 288 00:14:47,480 --> 00:14:49,520 Speaker 10: will be allowing this by the end of this year. 289 00:14:50,000 --> 00:14:52,600 Speaker 10: What the process would look like is where institutional clients 290 00:14:52,640 --> 00:14:55,320 Speaker 10: come to JP Morgan with holdings of bitcoin and ether 291 00:14:55,400 --> 00:14:58,080 Speaker 10: that they already own that would then be transferred to 292 00:14:58,160 --> 00:15:00,920 Speaker 10: a third party custodian that JP Morgan well the point, 293 00:15:01,120 --> 00:15:03,000 Speaker 10: who will look after the cryptos so the bank doesn't 294 00:15:03,040 --> 00:15:05,400 Speaker 10: have to touch themselves, and that can be used as 295 00:15:05,440 --> 00:15:08,360 Speaker 10: collateral for financing that the bank can lend against. 296 00:15:09,200 --> 00:15:12,560 Speaker 3: What's really interesting is the context of JP Morgan and 297 00:15:12,600 --> 00:15:15,240 Speaker 3: shall I say Jamie Diamond's relationship with crypto, because it 298 00:15:15,240 --> 00:15:17,960 Speaker 3: was a few years ago he was calling them pet rocks, 299 00:15:18,240 --> 00:15:21,400 Speaker 3: hyped up fraud and now most recently in your story, 300 00:15:21,400 --> 00:15:23,760 Speaker 3: which is a beautiful quote talking about I don't think 301 00:15:23,800 --> 00:15:26,160 Speaker 3: we should smoke, but I defend your right to smoke. 302 00:15:26,280 --> 00:15:28,720 Speaker 3: Is that why they're not going to be custodian while 303 00:15:28,720 --> 00:15:30,840 Speaker 3: they're letting others like State Street Bank of New York, 304 00:15:30,840 --> 00:15:34,120 Speaker 3: Mellon Fidelity still play that game rather than JP Morgan itself. 305 00:15:36,040 --> 00:15:38,160 Speaker 10: There's definitely a bit of a divide in terms of 306 00:15:38,240 --> 00:15:41,640 Speaker 10: how banks want to touch crypto. Some like JP Morgan 307 00:15:41,680 --> 00:15:43,680 Speaker 10: are happy for clients to touch it, but they don't 308 00:15:43,680 --> 00:15:46,320 Speaker 10: necessarily want to be involved in touching it themselves. So 309 00:15:46,440 --> 00:15:48,920 Speaker 10: earlier this summer, for example, this started out with JP 310 00:15:49,000 --> 00:15:52,000 Speaker 10: Morgan allowing clients to use crypto ETFs as clateral, so 311 00:15:52,360 --> 00:15:54,920 Speaker 10: traditional finance rappers that they're used to touching, but it 312 00:15:55,040 --> 00:15:57,640 Speaker 10: tracks the price of a cryptocurrency. This is a step 313 00:15:57,680 --> 00:15:59,240 Speaker 10: further than that, but they're still not getting to the 314 00:15:59,280 --> 00:16:01,440 Speaker 10: point of why they'd want to touch the crypto directly. 315 00:16:01,800 --> 00:16:03,960 Speaker 10: It should be no though, it's pretty difficult for banks 316 00:16:03,960 --> 00:16:06,560 Speaker 10: to touch cryptodirectly sometimes because there are rules like the 317 00:16:06,600 --> 00:16:10,160 Speaker 10: buzz or rules on banking that prevent them from touching 318 00:16:10,200 --> 00:16:12,880 Speaker 10: crypto without having to hold an equivalent amount of capital 319 00:16:12,920 --> 00:16:15,040 Speaker 10: and reserve at the same time. It can get pretty 320 00:16:15,080 --> 00:16:17,160 Speaker 10: expensive unless you've got the right structures in place. 321 00:16:17,960 --> 00:16:20,040 Speaker 3: There's a lot of institutions and a lot of private 322 00:16:20,040 --> 00:16:22,280 Speaker 3: individuals have a lot of crypto gains they want to 323 00:16:22,320 --> 00:16:24,680 Speaker 3: be able to use as collateral. Emily Nicole, it's a 324 00:16:24,680 --> 00:16:28,600 Speaker 3: great story. Thank you coming up. Google says it's reached 325 00:16:28,640 --> 00:16:31,680 Speaker 3: another new milestone in quantum technology. It's a step that 326 00:16:31,840 --> 00:16:34,440 Speaker 3: could bring the long promise power of quantum computing closer 327 00:16:34,440 --> 00:16:36,880 Speaker 3: to reality. One of the next this has been their tech. 328 00:16:52,200 --> 00:16:55,800 Speaker 2: Google says it achieved a major milestone in quantum computing, 329 00:16:55,840 --> 00:16:59,760 Speaker 2: bringing the technology's immense processing power a step closer to 330 00:16:59,800 --> 00:17:02,280 Speaker 2: real world use. The company says it ran an algorithm 331 00:17:02,520 --> 00:17:06,520 Speaker 2: on its Willow quantum chip that is verifiable and thirteen 332 00:17:06,600 --> 00:17:11,960 Speaker 2: thousand times faster than today's best supercomputers. Let's discuss with 333 00:17:12,040 --> 00:17:16,359 Speaker 2: Koreana Chow, chief operating officer at Google Quantum AI. I 334 00:17:16,359 --> 00:17:18,240 Speaker 2: think actually the best place to start is the basics 335 00:17:18,240 --> 00:17:22,280 Speaker 2: of quantum computing versus accelerated or supercomputing, because if you 336 00:17:22,440 --> 00:17:27,119 Speaker 2: explain why that thirteen thousand x performance is notable in 337 00:17:27,200 --> 00:17:30,399 Speaker 2: simple terms, it gives some measure of why it's a 338 00:17:30,400 --> 00:17:31,800 Speaker 2: piece of news this week. 339 00:17:32,000 --> 00:17:36,760 Speaker 11: Absolutely, today's computers classical computers, they use bits right zeros 340 00:17:36,800 --> 00:17:39,720 Speaker 11: and once they use that to calculate, it's useful. 341 00:17:39,400 --> 00:17:41,479 Speaker 6: For a number of different problems across the world. 342 00:17:41,800 --> 00:17:45,560 Speaker 11: However, quantum computing is different uses a combination of zeros 343 00:17:45,560 --> 00:17:48,199 Speaker 11: and ones at the same time that enables access to 344 00:17:48,240 --> 00:17:51,280 Speaker 11: different types of problems, like the quantum echoes algorithm we 345 00:17:51,280 --> 00:17:52,199 Speaker 11: announced this week. 346 00:17:52,359 --> 00:17:54,439 Speaker 2: You have brought Willow with you, You've put it in 347 00:17:54,440 --> 00:17:58,199 Speaker 2: an impenetrable safe housing and casing. There it is on 348 00:17:58,240 --> 00:17:59,840 Speaker 2: the desk in front of me. I read a lot 349 00:17:59,840 --> 00:18:03,320 Speaker 2: of academic papers this week, and many point out that 350 00:18:03,359 --> 00:18:06,919 Speaker 2: you didn't use a scalable or fault tolerant chip for 351 00:18:06,960 --> 00:18:09,520 Speaker 2: this demo, and so the argument follows that it would 352 00:18:09,560 --> 00:18:12,280 Speaker 2: be a big challenge for you to commercialize or scale 353 00:18:12,320 --> 00:18:16,119 Speaker 2: out that technology. Is that a fair concern from the 354 00:18:16,160 --> 00:18:17,119 Speaker 2: academic community. 355 00:18:17,240 --> 00:18:20,000 Speaker 11: That is the goal of quantum computing, to get to 356 00:18:20,119 --> 00:18:23,200 Speaker 11: fault tolerant quantum computing. Nobody is there yet. It is 357 00:18:23,280 --> 00:18:25,880 Speaker 11: a long journey, but it is very exciting. We've been 358 00:18:25,920 --> 00:18:28,520 Speaker 11: excited last December to announce for the first time that 359 00:18:28,640 --> 00:18:32,000 Speaker 11: error correction can work. We demonstrated that with our Willow chip, 360 00:18:32,200 --> 00:18:34,840 Speaker 11: and we continue on this journey pushing the number of 361 00:18:34,880 --> 00:18:37,360 Speaker 11: cubits and also bringing the errors way down. 362 00:18:37,840 --> 00:18:40,800 Speaker 3: And it's the timing now, Karina, what is it five 363 00:18:40,880 --> 00:18:43,600 Speaker 3: years do we get something that actually will show quantum 364 00:18:43,600 --> 00:18:48,120 Speaker 3: computing being really applicable and useful in the areas of science, 365 00:18:48,160 --> 00:18:51,440 Speaker 3: in the area of medicine. Why that timeline in particular. 366 00:18:52,359 --> 00:18:55,920 Speaker 11: Yeah, we are optimistic that we'll see real world applications 367 00:18:55,920 --> 00:18:59,720 Speaker 11: that are only possible on quantum computers in the next 368 00:18:59,760 --> 00:19:03,120 Speaker 11: five five years. You know, this breakthrough that we announced 369 00:19:03,119 --> 00:19:06,879 Speaker 11: this week is a great milestone towards that path. We 370 00:19:07,040 --> 00:19:10,520 Speaker 11: showed that quantum echoes, this algorithm is not only thirteen 371 00:19:10,560 --> 00:19:13,560 Speaker 11: thousand times faster on a quantum chip, but that it 372 00:19:13,600 --> 00:19:17,760 Speaker 11: can be used to simulate and calculate the exact structure 373 00:19:17,760 --> 00:19:19,879 Speaker 11: of a molecule. So we think this is an important 374 00:19:19,880 --> 00:19:20,600 Speaker 11: step on the past. 375 00:19:20,640 --> 00:19:23,200 Speaker 3: Someone on your team, we're on the twenty twenty five 376 00:19:23,280 --> 00:19:26,119 Speaker 3: Nobel Prize in physics was among the winners. You have 377 00:19:26,200 --> 00:19:30,480 Speaker 3: hert and leading the charge. We have real stellar well talent, 378 00:19:30,680 --> 00:19:32,960 Speaker 3: but also a lot of investment. What did you make 379 00:19:33,000 --> 00:19:35,760 Speaker 3: of the news the flow that maybe the US government 380 00:19:35,880 --> 00:19:38,480 Speaker 3: is there to support other smaller quantum players here in 381 00:19:38,480 --> 00:19:41,399 Speaker 3: the United States? Is that important? Yeah? 382 00:19:41,480 --> 00:19:44,000 Speaker 11: We are really excited and pleased to see all of 383 00:19:44,040 --> 00:19:48,120 Speaker 11: the investment, the support, the excitement about quantum computing across 384 00:19:48,160 --> 00:19:52,040 Speaker 11: the board. US government has been a strong supporter and 385 00:19:52,240 --> 00:19:55,280 Speaker 11: partner in this for the last many years, and we're 386 00:19:55,359 --> 00:19:59,200 Speaker 11: very excited about those investments and continue partnership across the ecosystem. 387 00:19:59,359 --> 00:20:02,880 Speaker 2: Crini, the COO of the Quantum Group, right, And we 388 00:20:02,920 --> 00:20:05,600 Speaker 2: reflected earlier in the week on the show when the 389 00:20:05,640 --> 00:20:10,360 Speaker 2: headline hit the Bloomberg about this breakthrough. Actually markets reacted, 390 00:20:10,480 --> 00:20:13,959 Speaker 2: alphabet shares moved markedly. Would you reflect a little bit 391 00:20:13,960 --> 00:20:17,840 Speaker 2: on what the days that followed that were, like, did 392 00:20:17,880 --> 00:20:21,200 Speaker 2: the phone ring off the hook from various parties that 393 00:20:21,280 --> 00:20:23,400 Speaker 2: are interested now to know more about how they might 394 00:20:23,400 --> 00:20:24,480 Speaker 2: be able to use the tech. 395 00:20:24,760 --> 00:20:25,040 Speaker 6: Yeah. 396 00:20:25,080 --> 00:20:28,040 Speaker 11: For us at Google, we are really excited about all 397 00:20:28,080 --> 00:20:31,199 Speaker 11: the interests that we're seeing across the board. Our mission 398 00:20:31,240 --> 00:20:33,679 Speaker 11: at Google Quantum AI is to build quantum computing for 399 00:20:33,880 --> 00:20:37,880 Speaker 11: otherwise unsolvable problems. I think that's why there's increasing interest 400 00:20:37,920 --> 00:20:40,800 Speaker 11: with every breakthrough. People in other fields are getting excited 401 00:20:40,840 --> 00:20:43,520 Speaker 11: about what can be possible, and we look forward to continue. 402 00:20:43,720 --> 00:20:46,679 Speaker 2: So the bar has been set now for you, what 403 00:20:46,800 --> 00:20:49,320 Speaker 2: is the next milestone that we should judge you by 404 00:20:49,680 --> 00:20:50,360 Speaker 2: in progress. 405 00:20:50,640 --> 00:20:53,119 Speaker 11: Yeah, there's going to be continued work across the board. 406 00:20:53,200 --> 00:20:56,320 Speaker 11: One really important marker of progress is continuing to push 407 00:20:56,320 --> 00:20:58,480 Speaker 11: the hardware. So you can see on this Willow chip 408 00:20:58,600 --> 00:21:01,359 Speaker 11: here it says one hundred and five Q. That's one 409 00:21:01,440 --> 00:21:03,600 Speaker 11: hundred and five cubits on our willow too fast. 410 00:21:03,640 --> 00:21:05,320 Speaker 6: Give the camera man a chance to catch up, but 411 00:21:05,359 --> 00:21:05,960 Speaker 6: he will get it. 412 00:21:06,040 --> 00:21:10,080 Speaker 11: Yeah, yes, one hundred and five cubits. 413 00:21:10,280 --> 00:21:11,280 Speaker 6: So that is great. 414 00:21:11,280 --> 00:21:14,440 Speaker 11: This has been honestly cutting edge ship. But to get 415 00:21:14,480 --> 00:21:16,840 Speaker 11: to where we want to go to solve these important 416 00:21:16,840 --> 00:21:21,199 Speaker 11: problems in chemistry, in physics, in material science, batteries, energy, 417 00:21:21,359 --> 00:21:24,040 Speaker 11: and more, we want to get to a million cubits. 418 00:21:24,040 --> 00:21:26,479 Speaker 11: So we're going to keep pushing the performance of our system. 419 00:21:26,680 --> 00:21:29,280 Speaker 11: We're also going to keep pushing the algorithm in software 420 00:21:29,320 --> 00:21:31,199 Speaker 11: developments so that we can solve these problems. 421 00:21:31,240 --> 00:21:33,480 Speaker 3: What does that take, Karina? What does that take in 422 00:21:33,560 --> 00:21:35,680 Speaker 3: terms of supply chain? What does that take in terms 423 00:21:35,680 --> 00:21:37,480 Speaker 3: of talent? What does that take in terms of focus? 424 00:21:38,640 --> 00:21:41,719 Speaker 11: Yeah, these are all really important questions. I'll start with talent. 425 00:21:41,880 --> 00:21:44,560 Speaker 11: You mentioned a Nobel Prize winner on our team. 426 00:21:44,600 --> 00:21:45,720 Speaker 3: We are super proud of. 427 00:21:45,680 --> 00:21:51,240 Speaker 11: Michelle Deveray and the entire group of teammates and body 428 00:21:51,280 --> 00:21:53,520 Speaker 11: of work that's happened over the last many decades. 429 00:21:54,200 --> 00:21:55,480 Speaker 3: We're super proud of our team. 430 00:21:55,520 --> 00:22:00,000 Speaker 11: We've got a super talented team of engineers, technicians, research scientists, 431 00:22:00,440 --> 00:22:03,439 Speaker 11: program managers and others who are pushing the boundaries of 432 00:22:03,480 --> 00:22:06,240 Speaker 11: this technology. We've got to keep bringing the best and 433 00:22:06,280 --> 00:22:09,240 Speaker 11: the brightest to our team to push the performance of 434 00:22:09,280 --> 00:22:10,240 Speaker 11: what is possible. 435 00:22:11,280 --> 00:22:13,880 Speaker 3: Kaarina Chow, it's been great speaking with you, chief operating 436 00:22:13,880 --> 00:22:16,359 Speaker 3: officer at Google Quantum AI, on the back of what 437 00:22:16,480 --> 00:22:19,720 Speaker 3: has been quite a week for your team. Congratulations. Now 438 00:22:19,720 --> 00:22:22,399 Speaker 3: coming up, we get back to Intel's earnings and the 439 00:22:22,520 --> 00:22:25,919 Speaker 3: chip makers efforts and come back from New York from 440 00:22:25,920 --> 00:22:27,800 Speaker 3: San Francisco. This is Bloomberg Tech. 441 00:22:48,040 --> 00:22:50,120 Speaker 2: Welcome back to Bloomberg Tech if you're just joining us. 442 00:22:50,160 --> 00:22:53,000 Speaker 2: Intel and its earnings were our top story, and the 443 00:22:53,040 --> 00:22:56,360 Speaker 2: stock actually has eliminated most of the gain that it had. 444 00:22:56,400 --> 00:22:59,159 Speaker 2: It opened up almost eight percent, is now up just 445 00:22:59,520 --> 00:23:02,000 Speaker 2: half of the percentage point, but trading at its highest 446 00:23:02,040 --> 00:23:05,359 Speaker 2: level since April of twenty twenty four. It has returned 447 00:23:05,359 --> 00:23:09,639 Speaker 2: to profitability. It saw surprising demand across PC and server, 448 00:23:09,960 --> 00:23:13,000 Speaker 2: and it had some fighting talk about its place in 449 00:23:13,040 --> 00:23:19,040 Speaker 2: the AI infrastructure industry, which largely was around wayfer and packaging. 450 00:23:19,280 --> 00:23:22,920 Speaker 2: Not as exciting as GPU. But it's worth digging into numbers. 451 00:23:22,640 --> 00:23:24,720 Speaker 3: Character and is we can do that with a perfect person. 452 00:23:24,800 --> 00:23:27,119 Speaker 3: Pierre Farrago is with US New Street Research, head of 453 00:23:27,160 --> 00:23:30,160 Speaker 3: Global Tech Infrastructure joining us and look, we have seen 454 00:23:30,400 --> 00:23:32,879 Speaker 3: the games fade. What did you make of the numbers? 455 00:23:32,960 --> 00:23:35,080 Speaker 3: Was there enough there to keep the share price rallying 456 00:23:35,119 --> 00:23:35,720 Speaker 3: as it has been. 457 00:23:37,320 --> 00:23:41,040 Speaker 12: Yeah, so the numbers for Intel on the day like 458 00:23:41,200 --> 00:23:46,679 Speaker 12: yesterday are but relatively short tone on trend. And so 459 00:23:46,720 --> 00:23:49,080 Speaker 12: the PC market has been very weak for some time. 460 00:23:50,480 --> 00:23:53,280 Speaker 12: Meeting actually expectations that we are very high because everybody 461 00:23:53,920 --> 00:23:56,679 Speaker 12: was very excited about the AIPC and things like that, 462 00:23:56,800 --> 00:24:00,359 Speaker 12: which didn't really move the needle for the math. And 463 00:24:00,400 --> 00:24:03,159 Speaker 12: so now what we see is the more traditional driver 464 00:24:03,359 --> 00:24:07,040 Speaker 12: like the Windows refresh cycle helping enterprise demand and that's 465 00:24:07,040 --> 00:24:10,040 Speaker 12: great of course. And then servers, we've seen the server 466 00:24:10,160 --> 00:24:13,960 Speaker 12: market been weak for quarters and quarters, if not years, 467 00:24:14,720 --> 00:24:17,240 Speaker 12: because you had so much focus on deploying like AI 468 00:24:17,359 --> 00:24:20,480 Speaker 12: servers that a lot of very large players were kind 469 00:24:20,480 --> 00:24:25,159 Speaker 12: of you know, deprioritizing the deployment of traditional services and 470 00:24:25,200 --> 00:24:27,040 Speaker 12: now we are entering a phase of catch ups. So 471 00:24:27,760 --> 00:24:30,000 Speaker 12: the new term for Intel looks good and it reminds 472 00:24:30,000 --> 00:24:32,600 Speaker 12: you that it's a good business, that there is operating leverage. 473 00:24:33,200 --> 00:24:35,080 Speaker 12: But even if they've lost a lot of market shirts 474 00:24:35,080 --> 00:24:37,879 Speaker 12: with MD, there are still like a market leader. So 475 00:24:37,920 --> 00:24:43,879 Speaker 12: that's great, but a very surprisingly positive but relatively short ter. 476 00:24:43,920 --> 00:24:46,320 Speaker 12: I mean, that's the way I interpret the stock movement. 477 00:24:46,400 --> 00:24:49,159 Speaker 12: You know, yeah, big grip on the news floor, and 478 00:24:49,200 --> 00:24:51,080 Speaker 12: then you look back and you're like, well, but at 479 00:24:51,080 --> 00:24:53,240 Speaker 12: the end of the day, word does really matter for Intel? 480 00:24:53,320 --> 00:24:56,280 Speaker 12: Is that really like PC demand over the next couple 481 00:24:56,320 --> 00:24:57,639 Speaker 12: of years or is that more so? 482 00:24:57,680 --> 00:25:01,399 Speaker 3: What matters. What matters is fourteen A. What matters is 483 00:25:01,440 --> 00:25:03,240 Speaker 3: are they going to be the cutting edge of the 484 00:25:03,280 --> 00:25:05,879 Speaker 3: next iteration of chips? Are they going to really rival 485 00:25:05,880 --> 00:25:10,160 Speaker 3: ty SMC and get others than Intel's own fabrication? Going, 486 00:25:10,760 --> 00:25:13,640 Speaker 3: what did you hear from Bhutan the team about that? 487 00:25:14,880 --> 00:25:18,080 Speaker 12: So I heard two things. The first one is mixed signal, 488 00:25:18,240 --> 00:25:22,320 Speaker 12: which is at eighteen A, the manufacturing is ramping, is 489 00:25:22,359 --> 00:25:25,720 Speaker 12: going to get into volumes immediately, you know, like for 490 00:25:25,800 --> 00:25:29,080 Speaker 12: the beginning of next year. But comments but the yield, 491 00:25:29,320 --> 00:25:31,680 Speaker 12: so you know, the quality of the process are still 492 00:25:31,840 --> 00:25:34,960 Speaker 12: very very mixed. Let's face it, the yields are not 493 00:25:35,040 --> 00:25:38,920 Speaker 12: good today, so early yields not being good is almost 494 00:25:38,960 --> 00:25:42,480 Speaker 12: business as usual. But I think eighteen a's performance in 495 00:25:42,560 --> 00:25:47,000 Speaker 12: terms of manufacturing performance is disappointing. And then the second 496 00:25:47,000 --> 00:25:49,760 Speaker 12: piece of news that that rematters the most for the 497 00:25:49,800 --> 00:25:53,199 Speaker 12: long term of Intel is like more positive comments. But 498 00:25:53,240 --> 00:25:56,960 Speaker 12: fourteen A. Remember three months ago, the CEO had very 499 00:25:57,119 --> 00:26:00,000 Speaker 12: cautious comments, even mentioned in writing in the ten case 500 00:26:00,480 --> 00:26:04,000 Speaker 12: as a possibility of not developing fortein a if Intel 501 00:26:04,040 --> 00:26:07,159 Speaker 12: didn't find enough customers, you got to do it. And 502 00:26:07,160 --> 00:26:10,119 Speaker 12: now they're talking positively about Fatina. On the technical front, 503 00:26:10,400 --> 00:26:14,040 Speaker 12: like the road map is progressing well. And also I 504 00:26:14,040 --> 00:26:16,359 Speaker 12: don't even want to call that the commercial front, but 505 00:26:16,480 --> 00:26:19,560 Speaker 12: more like the coalition front. Decided that if you really 506 00:26:19,640 --> 00:26:23,600 Speaker 12: want Intel to be successful in manufacturing, you need more 507 00:26:23,600 --> 00:26:26,879 Speaker 12: than clients. You need industrial policy, you need a coalition. 508 00:26:27,359 --> 00:26:30,800 Speaker 12: You need partners that deeply engage with Intel, invest in Intel, 509 00:26:31,160 --> 00:26:33,560 Speaker 12: commit to Intel, to work with Intel. That's the only 510 00:26:33,600 --> 00:26:36,800 Speaker 12: way the foundry is really going to do well. And honestly, 511 00:26:36,960 --> 00:26:39,960 Speaker 12: on that front, it's very very early signals, but I 512 00:26:40,000 --> 00:26:40,920 Speaker 12: think they are positive. 513 00:26:42,680 --> 00:26:45,800 Speaker 2: I tried to get a sense from Intel CFO Daves 514 00:26:45,840 --> 00:26:47,680 Speaker 2: and when I spoke to him on the phone about 515 00:26:48,400 --> 00:26:50,720 Speaker 2: that long term you were talking about and in an 516 00:26:50,760 --> 00:26:54,879 Speaker 2: AI world AI, his answer was quite simple. They do 517 00:26:54,920 --> 00:26:58,320 Speaker 2: see opportunity and accelerators, but the foundry bit is what 518 00:26:58,400 --> 00:27:00,639 Speaker 2: I was like most surprise. That is saying that the 519 00:27:00,640 --> 00:27:04,919 Speaker 2: foundry opportunity for them in AI is in wafers and packaging. 520 00:27:05,520 --> 00:27:07,800 Speaker 2: That doesn't sound hugely exciting. 521 00:27:07,880 --> 00:27:15,919 Speaker 12: Pierre, Well, maybe it doesn't sound hugely exciting, but it 522 00:27:16,040 --> 00:27:20,000 Speaker 12: sounds very realistic and really playing to Intel strength. The 523 00:27:20,040 --> 00:27:24,080 Speaker 12: way it's Intel today is they have two major product franchises. 524 00:27:24,320 --> 00:27:26,440 Speaker 12: One is in the Piece of Business x eighty six 525 00:27:26,560 --> 00:27:30,480 Speaker 12: CPUs for pieces and one was in seven. So I'm 526 00:27:30,480 --> 00:27:33,359 Speaker 12: pretty sure the management wants to maximize the value of 527 00:27:33,359 --> 00:27:35,600 Speaker 12: these two franchises and concentrate on them. 528 00:27:35,640 --> 00:27:36,320 Speaker 6: And it's good. 529 00:27:36,640 --> 00:27:42,520 Speaker 12: You can't invent yourself, you know, like an AI accelerator designer, 530 00:27:42,840 --> 00:27:45,360 Speaker 12: like fifteen years down the lines or ten years down 531 00:27:45,400 --> 00:27:48,359 Speaker 12: the line, and that's very reasonable. And then yes, Intel 532 00:27:48,480 --> 00:27:53,800 Speaker 12: has an edge packaging. Intel is a strategic asset for 533 00:27:53,920 --> 00:27:58,399 Speaker 12: this industry and this is probably what management wants to 534 00:27:58,440 --> 00:28:01,000 Speaker 12: build on and I see that as maybe not as 535 00:28:01,000 --> 00:28:04,240 Speaker 12: exciting as willing to compete against the VIDR, but very 536 00:28:04,240 --> 00:28:07,480 Speaker 12: realistic and the right industrial approach probably. 537 00:28:08,040 --> 00:28:10,800 Speaker 6: You know, and for our audience pre appreciate that answer. 538 00:28:10,800 --> 00:28:13,080 Speaker 2: Because you also cover in video right, you're able to 539 00:28:13,119 --> 00:28:16,679 Speaker 2: make the comparison on xAd six. I think the argument 540 00:28:16,720 --> 00:28:20,199 Speaker 2: Intel were making to us was the hyperscalers have woken 541 00:28:20,280 --> 00:28:22,919 Speaker 2: up a bit to the value of having the latest 542 00:28:22,960 --> 00:28:27,040 Speaker 2: CPU in infrastructure. They're willing to invest and refresh on CPU. 543 00:28:27,359 --> 00:28:31,040 Speaker 2: So again for them Intel, they would argue that it's 544 00:28:31,080 --> 00:28:32,680 Speaker 2: a great opportunity for them. 545 00:28:32,800 --> 00:28:34,879 Speaker 6: Do you see that opportunity. 546 00:28:35,040 --> 00:28:41,120 Speaker 12: Yes, absolutely, no doubt, and it's very very strong. You 547 00:28:41,240 --> 00:28:45,000 Speaker 12: have like clients asking for it. The specifics of the 548 00:28:45,160 --> 00:28:50,040 Speaker 12: XAT six architecture and the way Intel implements it is 549 00:28:50,160 --> 00:28:53,720 Speaker 12: very differentiated. I've always been a great believer in the 550 00:28:53,800 --> 00:28:55,560 Speaker 12: quality of the products of Intel on that from like 551 00:28:55,600 --> 00:28:58,640 Speaker 12: the ability of an intell extaden ship to deal with 552 00:28:58,840 --> 00:29:03,160 Speaker 12: very unforeseen city cuation in very complex work cloud is excellent, 553 00:29:04,400 --> 00:29:08,600 Speaker 12: and you've had so much demand for it that it 554 00:29:08,720 --> 00:29:15,280 Speaker 12: actually triggers NVIDA has moved first to open up envilling 555 00:29:15,480 --> 00:29:18,640 Speaker 12: like the high bandwidth connectivity with their GPS so that 556 00:29:19,200 --> 00:29:24,000 Speaker 12: Excaity six chip can be integrated into na systems, and 557 00:29:24,440 --> 00:29:28,400 Speaker 12: a five billion dollar investment in Intel and a partnership 558 00:29:28,440 --> 00:29:31,680 Speaker 12: with Intel to co develop chip that will be optimized 559 00:29:31,720 --> 00:29:35,000 Speaker 12: to get integrated into Nvidia systems. And my read, having 560 00:29:35,040 --> 00:29:37,600 Speaker 12: followed that for a few years, is that it's not 561 00:29:37,760 --> 00:29:41,480 Speaker 12: just like a nice gesture from Nvidia under political pressure 562 00:29:41,560 --> 00:29:44,040 Speaker 12: or anything like that. It is a genuine, thorough and 563 00:29:44,080 --> 00:29:48,200 Speaker 12: deep interest for Intel products in the industry for that role. Now, 564 00:29:48,680 --> 00:29:51,719 Speaker 12: keep things to the scale they are out on NVL 565 00:29:51,800 --> 00:29:56,120 Speaker 12: seventy to server powered by x eighty six Champs chips. 566 00:29:56,320 --> 00:29:59,760 Speaker 12: The chip is going to be single digit percentage of 567 00:29:59,760 --> 00:30:02,000 Speaker 12: the co cost of the overall server and the other 568 00:30:02,080 --> 00:30:04,160 Speaker 12: ninety plus percent would be in video. 569 00:30:04,400 --> 00:30:07,840 Speaker 3: So Pierre within video support, we know the money is 570 00:30:07,920 --> 00:30:09,960 Speaker 3: yet to come through in that settle in the next quarter. 571 00:30:10,640 --> 00:30:13,560 Speaker 3: Will that be enough to see Ohio breakground? Will we 572 00:30:13,720 --> 00:30:16,520 Speaker 3: see an actual commitment not just to co develop, but 573 00:30:16,560 --> 00:30:20,479 Speaker 3: actually to eventually fabricate on site in the United States, 574 00:30:20,480 --> 00:30:21,720 Speaker 3: not just relying on TSMC. 575 00:30:22,960 --> 00:30:27,240 Speaker 12: It's a great question. You need more than that to 576 00:30:27,360 --> 00:30:30,800 Speaker 12: have like a final commitment or to claim victory basically 577 00:30:31,240 --> 00:30:35,479 Speaker 12: in order for Intel to successfully manufacture chips in the 578 00:30:35,600 --> 00:30:39,520 Speaker 12: US package chips in the US for US clients. You 579 00:30:39,600 --> 00:30:43,200 Speaker 12: need the money and major pogrests made on that front 580 00:30:43,240 --> 00:30:45,760 Speaker 12: with money from the government, from NVDR, from South Bank, 581 00:30:45,800 --> 00:30:46,520 Speaker 12: and I'm sure. 582 00:30:46,360 --> 00:30:47,480 Speaker 5: More will furrow. 583 00:30:48,560 --> 00:30:54,720 Speaker 12: You need also like the multi year commitment of a coalition, 584 00:30:55,080 --> 00:30:58,800 Speaker 12: so you're not going to get like the right hip 585 00:30:59,240 --> 00:31:02,160 Speaker 12: in the first go with. It's a dialogue that needs 586 00:31:02,200 --> 00:31:06,000 Speaker 12: to last very multiple years before you get to success. 587 00:31:06,640 --> 00:31:11,000 Speaker 12: And last but not least, you need execution. You needed 588 00:31:11,960 --> 00:31:14,840 Speaker 12: to come up with a fought in a that's going 589 00:31:14,920 --> 00:31:20,320 Speaker 12: to show up like policively, be unveiled and better convinced 590 00:31:20,320 --> 00:31:23,880 Speaker 12: and make potential adopters more confident. It's going to be 591 00:31:23,960 --> 00:31:25,320 Speaker 12: the right not to do something with it. 592 00:31:26,520 --> 00:31:28,760 Speaker 6: Pierre Faragu of New Street Research. Great to have you 593 00:31:28,800 --> 00:31:31,000 Speaker 6: back on Bloomberg Tech. Thank you very much. 594 00:31:31,080 --> 00:31:35,040 Speaker 2: Now coming up MISTRAUS CEO Arthur Mentch joins us to 595 00:31:35,080 --> 00:31:39,320 Speaker 2: discuss the startups new platform designed to help companies get 596 00:31:39,320 --> 00:31:42,320 Speaker 2: the most out of AI. It's a big interview. We've 597 00:31:42,320 --> 00:31:44,520 Speaker 2: been looking forward to this one for some time. Stay 598 00:31:44,560 --> 00:31:46,040 Speaker 2: with us. This is Bloomberg Tech. 599 00:31:56,440 --> 00:31:58,960 Speaker 6: Today. European AI startup Mistra. 600 00:31:58,760 --> 00:32:01,480 Speaker 2: Announced the release of a new platform to help its 601 00:32:01,600 --> 00:32:05,400 Speaker 2: enterprise clients make customizable AI tools that are easy to 602 00:32:05,440 --> 00:32:09,200 Speaker 2: operate throughout the businesses. Delighted to welcome mist our CEO 603 00:32:09,720 --> 00:32:13,280 Speaker 2: after Mensch to the program. This is a path to 604 00:32:13,320 --> 00:32:20,320 Speaker 2: production right and the enterprise category between you anthropic open AI, 605 00:32:20,760 --> 00:32:23,400 Speaker 2: it's a fierce battle. I think let's just start by 606 00:32:23,440 --> 00:32:26,800 Speaker 2: you explaining why you feel this is such a significant 607 00:32:26,840 --> 00:32:27,800 Speaker 2: milestone for Mistra. 608 00:32:29,200 --> 00:32:32,120 Speaker 13: So hello and happy to be here for us to 609 00:32:32,680 --> 00:32:35,640 Speaker 13: We're a global company really focused on creating value for 610 00:32:35,720 --> 00:32:40,000 Speaker 13: the enterprises, and we have had three years of experience 611 00:32:40,040 --> 00:32:42,960 Speaker 13: in doing that, and so AI Studio is basically the 612 00:32:43,000 --> 00:32:46,120 Speaker 13: one stop shop platform where you can build your AA 613 00:32:46,160 --> 00:32:50,160 Speaker 13: application as a business, and so it brings everything that 614 00:32:50,200 --> 00:32:52,840 Speaker 13: we need to create value in the enterprise, to create 615 00:32:52,880 --> 00:32:56,480 Speaker 13: applications that belongs to the enterprises, that contains their IP, 616 00:32:56,840 --> 00:32:59,600 Speaker 13: that is connected to their data, and that improves over time, 617 00:33:00,000 --> 00:33:03,160 Speaker 13: averaging the knowledge that is contained within enterphrises, that is 618 00:33:03,160 --> 00:33:04,520 Speaker 13: contained within employee's mind. 619 00:33:05,320 --> 00:33:08,960 Speaker 3: You are a global company, you're producing foundational models. Author 620 00:33:09,080 --> 00:33:12,200 Speaker 3: I wonder though, how you compete against those that are 621 00:33:12,200 --> 00:33:14,800 Speaker 3: already serving the enterprise. How is your solution different from 622 00:33:14,840 --> 00:33:16,680 Speaker 3: that of anthropics, that of open AI, is that of 623 00:33:16,920 --> 00:33:18,160 Speaker 3: X's and many others. 624 00:33:18,960 --> 00:33:21,400 Speaker 13: Well, I think our solution is much more integrated. Is 625 00:33:21,440 --> 00:33:24,560 Speaker 13: that we have thought about all of the bricks that 626 00:33:24,640 --> 00:33:27,040 Speaker 13: needed to be there to go from a model, which 627 00:33:27,040 --> 00:33:29,720 Speaker 13: is how we started to an application with the right 628 00:33:29,720 --> 00:33:31,960 Speaker 13: font end, with the right back ends, and with the 629 00:33:32,040 --> 00:33:35,320 Speaker 13: right learning mechanisms. So that integration is really the reason 630 00:33:35,320 --> 00:33:38,600 Speaker 13: why we've been succeeding in delivering value with enterprises. So 631 00:33:38,640 --> 00:33:42,760 Speaker 13: that's one very strong area of differentiation. The other thing 632 00:33:42,800 --> 00:33:45,880 Speaker 13: is that, in contrast with some of our competitors, we 633 00:33:45,960 --> 00:33:48,880 Speaker 13: really believe that enterprises should build their own AI, that 634 00:33:48,960 --> 00:33:51,600 Speaker 13: they should own the system, that the IP should remain 635 00:33:51,640 --> 00:33:54,360 Speaker 13: their own, that the data should remain where it is 636 00:33:54,400 --> 00:33:57,360 Speaker 13: and should not necessarily flow back to us. And so 637 00:33:57,400 --> 00:33:59,840 Speaker 13: that approach of building a portable platform that can be 638 00:33:59,880 --> 00:34:02,640 Speaker 13: the deployed on prend that can be deployed on private cloud, 639 00:34:02,880 --> 00:34:09,000 Speaker 13: combined with the vertically integrated approach of having just one 640 00:34:09,600 --> 00:34:13,520 Speaker 13: platform allowing you to go from prototype production, I think 641 00:34:13,640 --> 00:34:16,279 Speaker 13: is very very different from the approach for competitors, and 642 00:34:16,320 --> 00:34:18,200 Speaker 13: that has an oders to make a lot of progress 643 00:34:18,200 --> 00:34:19,040 Speaker 13: in particular under. 644 00:34:18,960 --> 00:34:23,360 Speaker 2: Us Arthur, can you talk about how quickly you're able 645 00:34:23,400 --> 00:34:28,760 Speaker 2: to onboard scaled enterprise customers to this and in turn 646 00:34:28,880 --> 00:34:32,879 Speaker 2: therefore what the capacity and compute constraints are for you 647 00:34:33,200 --> 00:34:36,839 Speaker 2: in launching a new product and then trying to run 648 00:34:36,920 --> 00:34:38,560 Speaker 2: workloads with clients. 649 00:34:39,520 --> 00:34:43,120 Speaker 13: Well, a good example that I can give you is 650 00:34:43,400 --> 00:34:45,680 Speaker 13: what we've been doing with one of our big customers, 651 00:34:45,680 --> 00:34:48,560 Speaker 13: which is a logistic company call same Messagem and one 652 00:34:48,600 --> 00:34:51,120 Speaker 13: of the biggest shipping company in the world, and so 653 00:34:51,239 --> 00:34:54,480 Speaker 13: as many other companies, they were a bit struggling with 654 00:34:54,520 --> 00:34:57,120 Speaker 13: the adoption of air. If you look at the MIT reports, 655 00:34:57,160 --> 00:34:59,320 Speaker 13: they state that ninety five percent of use cases just 656 00:34:59,320 --> 00:35:03,040 Speaker 13: don't go intoduction. And the way we have done the 657 00:35:03,080 --> 00:35:05,200 Speaker 13: work with them is we use AI studio and we 658 00:35:05,280 --> 00:35:07,640 Speaker 13: deployed our AI applied engineers or. 659 00:35:07,600 --> 00:35:08,799 Speaker 5: AED applied scientists. 660 00:35:08,960 --> 00:35:11,360 Speaker 13: We made them work with the business unit owners and 661 00:35:11,400 --> 00:35:13,840 Speaker 13: they realized what kind of processes could be automated and 662 00:35:13,920 --> 00:35:17,400 Speaker 13: to end and from ideating what we could automate to 663 00:35:17,480 --> 00:35:21,000 Speaker 13: going into production. So from March to July in formats 664 00:35:21,040 --> 00:35:24,680 Speaker 13: we were able to understand a full function to be automated, 665 00:35:24,680 --> 00:35:28,799 Speaker 13: so cargo release and dispatching of release of containers to 666 00:35:29,000 --> 00:35:32,840 Speaker 13: multiple customers. We're able to go from that to production 667 00:35:33,400 --> 00:35:38,040 Speaker 13: that is now going at the global scale. So the 668 00:35:38,080 --> 00:35:39,800 Speaker 13: way we think about it that it takes a quarter 669 00:35:40,520 --> 00:35:44,080 Speaker 13: to go from a prototype to production, and for him 670 00:35:44,080 --> 00:35:45,719 Speaker 13: to happen, you need to have the right tools. You 671 00:35:45,719 --> 00:35:47,040 Speaker 13: need to have the right tools. You need to have 672 00:35:47,080 --> 00:35:49,839 Speaker 13: the right experts. You need to deeply understand what AI 673 00:35:49,880 --> 00:35:52,520 Speaker 13: agents can do and cannot do. You need to connect 674 00:35:52,640 --> 00:35:55,760 Speaker 13: the agents to the data sources. You need to connect 675 00:35:55,800 --> 00:35:58,359 Speaker 13: them to software which is sometimes legacy, so you need 676 00:35:58,400 --> 00:36:00,400 Speaker 13: to have the right interfaces, the right plumbing. 677 00:36:00,640 --> 00:36:02,080 Speaker 5: That's what AIP studio can bring. 678 00:36:02,400 --> 00:36:04,600 Speaker 13: You also need to have the experts, so that's why 679 00:36:04,640 --> 00:36:06,799 Speaker 13: we deploy people in the companies that we work with. 680 00:36:07,960 --> 00:36:11,759 Speaker 2: After there is intense interest in Mistrau as the European 681 00:36:11,920 --> 00:36:16,479 Speaker 2: champion among AI labs frontier labs. The thing we're most 682 00:36:16,520 --> 00:36:19,320 Speaker 2: interesting to learn about is the progress of the follow 683 00:36:19,360 --> 00:36:24,080 Speaker 2: on fundraising round that's reported. You're undertaking how much money 684 00:36:24,160 --> 00:36:26,680 Speaker 2: you seek in the raise, But beyond the money, why 685 00:36:26,719 --> 00:36:28,880 Speaker 2: do you need to do a quick follow on? What 686 00:36:29,080 --> 00:36:31,960 Speaker 2: is the most pressing need for capital at the moment. 687 00:36:33,120 --> 00:36:34,719 Speaker 13: So I'm not sure we'll talk to you about the 688 00:36:34,760 --> 00:36:37,760 Speaker 13: follow on but we are not raising money at the moment. 689 00:36:37,920 --> 00:36:38,239 Speaker 5: We are. 690 00:36:38,520 --> 00:36:42,440 Speaker 13: We've just actually announced the fundraise with SML, which is 691 00:36:42,480 --> 00:36:45,520 Speaker 13: the biggest European company and with whom we work with 692 00:36:45,560 --> 00:36:48,279 Speaker 13: whom we have a commercial agreement where we help them 693 00:36:48,920 --> 00:36:52,799 Speaker 13: make better products, automate the processes, we help connect their 694 00:36:52,880 --> 00:36:56,960 Speaker 13: vertical expertise to horizontal expertise, We make them create their 695 00:36:57,000 --> 00:37:01,080 Speaker 13: own AI and deploy this AI into the their systems. 696 00:37:01,440 --> 00:37:04,080 Speaker 13: So that was a one point seven billion euro race, 697 00:37:04,520 --> 00:37:09,640 Speaker 13: which which makes us We've raised around three billion euro 698 00:37:09,760 --> 00:37:12,920 Speaker 13: in total, and that in turn has enabled us to 699 00:37:12,920 --> 00:37:15,160 Speaker 13: grow very fast and to create unique technology and to 700 00:37:15,200 --> 00:37:16,879 Speaker 13: release it in particular on the. 701 00:37:16,800 --> 00:37:17,359 Speaker 5: Open source WED. 702 00:37:17,719 --> 00:37:20,840 Speaker 3: That was really interesting, this strategic investment coming from SML. 703 00:37:21,200 --> 00:37:25,799 Speaker 3: You just referenced CMA, CGM, another French based giant. It's 704 00:37:25,800 --> 00:37:27,879 Speaker 3: a global company, but it's French based. You've got work 705 00:37:27,920 --> 00:37:31,240 Speaker 3: with stillants, You've got work with BNP, Parabar. What about 706 00:37:31,400 --> 00:37:34,000 Speaker 3: US companies? How are you managing to penetrate here? 707 00:37:35,160 --> 00:37:37,560 Speaker 5: So we are working with CHIPELU US companies. 708 00:37:37,600 --> 00:37:41,600 Speaker 13: We're working with Cisco for instance, which has chosen us 709 00:37:41,640 --> 00:37:43,759 Speaker 13: because we allowed them to deploy on private cloud and 710 00:37:44,360 --> 00:37:47,000 Speaker 13: we deploy people to work with them in particular on 711 00:37:47,040 --> 00:37:51,040 Speaker 13: the customer experience side, so that's one important customer of hours. 712 00:37:51,040 --> 00:37:55,360 Speaker 13: We also work with Snowflake deployer technology in particular on 713 00:37:55,560 --> 00:38:00,279 Speaker 13: document processing and all of our technology to structure and 714 00:38:00,400 --> 00:38:03,839 Speaker 13: structure knowledge into to take instruct your knowledge and turn 715 00:38:03,880 --> 00:38:07,280 Speaker 13: it into things that can then be crawled by a systems. 716 00:38:07,800 --> 00:38:10,080 Speaker 13: We also work, as you know, with Microsoft, which is 717 00:38:10,280 --> 00:38:12,720 Speaker 13: which is a very important bartner of owers and exposes 718 00:38:12,800 --> 00:38:17,880 Speaker 13: on the on voundry on models, being very competitive in 719 00:38:17,920 --> 00:38:21,360 Speaker 13: particular on their cost of performance ratio. We walk with 720 00:38:21,400 --> 00:38:24,600 Speaker 13: A Doubles and GCP and we work with multiple digital 721 00:38:24,680 --> 00:38:25,600 Speaker 13: natives Companion as well. 722 00:38:27,000 --> 00:38:31,400 Speaker 2: Arthur your peers, Dario ama Day from Anthropic, Sam Altman 723 00:38:31,600 --> 00:38:35,200 Speaker 2: OpenAI are looking increasingly to the Middle East, both for 724 00:38:35,320 --> 00:38:39,120 Speaker 2: capital but compute capacity. Right this week we broke the 725 00:38:39,160 --> 00:38:44,480 Speaker 2: news of Anthropic securing one million TPUs with Google and GCP. 726 00:38:45,120 --> 00:38:48,520 Speaker 2: That's the scale that people are talking about. Are you 727 00:38:48,640 --> 00:38:52,040 Speaker 2: making those future plans for scale? Are you looking at 728 00:38:52,080 --> 00:38:56,399 Speaker 2: debt markets to ensure the future of mistrau and what 729 00:38:56,440 --> 00:38:57,160 Speaker 2: you want to do? 730 00:38:58,440 --> 00:39:00,719 Speaker 13: So the future of if you should diligence is very 731 00:39:00,719 --> 00:39:04,239 Speaker 13: linked to infrastructure, as you know, and as a consequence 732 00:39:04,239 --> 00:39:07,520 Speaker 13: of that, we have created a new business unit called 733 00:39:07,560 --> 00:39:12,960 Speaker 13: Mistile Compute, which is creating digital infrastructure GPUs, in particular 734 00:39:13,719 --> 00:39:17,439 Speaker 13: in Europe, which is lacking infrastructure today, and so we've 735 00:39:17,440 --> 00:39:21,920 Speaker 13: been growing that very fast and we are acquiring multiple 736 00:39:22,040 --> 00:39:25,680 Speaker 13: hundreds of Mega what capacity in the coming year to 737 00:39:25,719 --> 00:39:28,759 Speaker 13: actually be able to serve our customers, to serve AI startups, 738 00:39:29,520 --> 00:39:33,360 Speaker 13: to serve all of our existing customers and customers that 739 00:39:33,400 --> 00:39:36,160 Speaker 13: come to us because they are looking for sovereign capacity. 740 00:39:36,560 --> 00:39:39,080 Speaker 13: We also use that capacity to train our own models 741 00:39:39,120 --> 00:39:41,919 Speaker 13: and to maintain our leadership on the open source font. 742 00:39:43,000 --> 00:39:46,160 Speaker 3: With that comes the need to continue to invest. You 743 00:39:46,280 --> 00:39:48,920 Speaker 3: raised money, and is that what's being used to finance 744 00:39:49,400 --> 00:39:52,600 Speaker 3: the exploration and data center build out. Because I'm looking 745 00:39:52,600 --> 00:39:54,000 Speaker 3: at a headline at the moment that the Bank of 746 00:39:54,000 --> 00:39:57,280 Speaker 3: England itself is really worried about a circled AI bubble 747 00:39:57,320 --> 00:39:59,839 Speaker 3: and some of the debt and the financing that's going 748 00:39:59,840 --> 00:40:01,680 Speaker 3: on data centers at the moment. Is that something that 749 00:40:01,719 --> 00:40:02,360 Speaker 3: gives you pause? 750 00:40:02,400 --> 00:40:06,920 Speaker 13: Author, Well, we've raised equity and we are deploying that 751 00:40:06,960 --> 00:40:08,960 Speaker 13: equity to actually train models. 752 00:40:09,000 --> 00:40:11,680 Speaker 5: So RANT is financed by our equity. 753 00:40:11,800 --> 00:40:14,839 Speaker 13: We also have long term contacts for our compute facilities, 754 00:40:15,160 --> 00:40:17,880 Speaker 13: and with those long term contacts, we are able to 755 00:40:17,920 --> 00:40:22,000 Speaker 13: actually finance them through that that's not this is bank 756 00:40:22,040 --> 00:40:26,000 Speaker 13: debt and gives us confidence that we are not overly 757 00:40:26,040 --> 00:40:30,760 Speaker 13: exposed to that there is a lot of investment happening 758 00:40:30,800 --> 00:40:34,840 Speaker 13: on the infrastructure side today. We're really focused on creating 759 00:40:34,840 --> 00:40:37,920 Speaker 13: the long term value that will justify with investments. Because 760 00:40:37,960 --> 00:40:40,439 Speaker 13: we operate with enterprises, because we go all the way 761 00:40:40,719 --> 00:40:42,040 Speaker 13: to delivering value for. 762 00:40:41,960 --> 00:40:44,200 Speaker 5: Them, to identifying their use cases, to. 763 00:40:44,360 --> 00:40:47,840 Speaker 13: Making things that transforming what looks like magic to something 764 00:40:47,840 --> 00:40:51,160 Speaker 13: that looks like money, we are not exposed to whatever 765 00:40:51,200 --> 00:40:54,680 Speaker 13: may happen on overly investing on the infrastructure site. 766 00:40:54,719 --> 00:40:57,120 Speaker 5: We invest on the infastructure site in a wise way 767 00:40:57,920 --> 00:40:58,440 Speaker 5: to help. 768 00:40:58,239 --> 00:41:01,520 Speaker 3: Build mister Lai studio. Mench. Great to have you on 769 00:41:01,560 --> 00:41:04,120 Speaker 3: that news today. Thank you so much, the CEO of 770 00:41:04,200 --> 00:41:06,759 Speaker 3: Mistrell and co founder. Now coming up, we'll come back 771 00:41:06,840 --> 00:41:09,799 Speaker 3: on the AWS shortage and outage. But it is one 772 00:41:09,800 --> 00:41:11,799 Speaker 3: of the biggest in history. Remember and what would that 773 00:41:11,800 --> 00:41:14,160 Speaker 3: mean for cloud Giant's future in the age of AI. 774 00:41:14,320 --> 00:41:15,160 Speaker 3: This has really big ten. 775 00:41:24,800 --> 00:41:28,719 Speaker 2: Amazon basically invented the cloud business, but now it's struggling 776 00:41:28,800 --> 00:41:31,560 Speaker 2: as Monday's outage shows one of the worst outages in 777 00:41:31,600 --> 00:41:35,080 Speaker 2: the cloud unit's history. Bloomberg's Amazon reporter Matt Day joins 778 00:41:35,160 --> 00:41:38,080 Speaker 2: us to discuss his latest deep dive and why AWS 779 00:41:38,400 --> 00:41:41,960 Speaker 2: is now perceived as trailing its rivals and AI. This 780 00:41:42,000 --> 00:41:47,560 Speaker 2: week's been rough outage, losing some Groundman to GPUs TPUs 781 00:41:47,560 --> 00:41:48,080 Speaker 2: for Google. 782 00:41:48,480 --> 00:41:50,120 Speaker 6: Just give me the headline of your story. 783 00:41:51,000 --> 00:41:52,719 Speaker 14: So the headline of the story is that Amazon is 784 00:41:52,800 --> 00:41:55,440 Speaker 14: essentially no longer the only game in town in cloud computing. 785 00:41:55,440 --> 00:41:57,920 Speaker 14: They've got real credible rivals, you know, down to Oracle 786 00:41:57,960 --> 00:42:00,040 Speaker 14: and Google. Now, five years or so ago was on 787 00:42:00,200 --> 00:42:02,279 Speaker 14: Microsoft that was knocking on the door. And now you 788 00:42:02,280 --> 00:42:04,759 Speaker 14: add on all this AI workloads and that's not a 789 00:42:04,800 --> 00:42:06,800 Speaker 14: business at AIS or that Amazon rather seem to be 790 00:42:06,880 --> 00:42:07,239 Speaker 14: leading in. 791 00:42:08,320 --> 00:42:10,960 Speaker 3: Just for context, though, how successful does it remain, how 792 00:42:11,040 --> 00:42:13,200 Speaker 3: much market shared does it still own? And what are 793 00:42:13,239 --> 00:42:15,719 Speaker 3: we starting to see in terms of inroads and so. 794 00:42:15,680 --> 00:42:18,520 Speaker 14: On on traditional cloud It's something like thirty eight percent, 795 00:42:18,920 --> 00:42:21,280 Speaker 14: reckons Gartner. It's down from about half of the market, 796 00:42:21,320 --> 00:42:22,600 Speaker 14: you know, five or six years ago. 797 00:42:23,440 --> 00:42:24,600 Speaker 6: Folks who have made inroads. 798 00:42:24,640 --> 00:42:28,239 Speaker 14: You know, there's there's Microsoft, there's GCP, there's Oracle and 799 00:42:28,320 --> 00:42:29,520 Speaker 14: a lot of a lot of the threat there is 800 00:42:29,560 --> 00:42:31,640 Speaker 14: just some of the services at Amazon pioneered like those 801 00:42:31,680 --> 00:42:34,200 Speaker 14: are leaning toward commodities. Other companies can offer you a 802 00:42:34,239 --> 00:42:35,600 Speaker 14: similar package of goods. 803 00:42:35,719 --> 00:42:39,520 Speaker 2: Right, Matt, When we break the story about Anthropic using TPUs, 804 00:42:39,800 --> 00:42:42,719 Speaker 2: Google stock up, Amazon stock down, how have you reflected 805 00:42:42,719 --> 00:42:43,600 Speaker 2: on that in the story. 806 00:42:44,719 --> 00:42:47,799 Speaker 14: Also, it's you really can't overstate the importance of Anthropic 807 00:42:47,960 --> 00:42:51,720 Speaker 14: to AWS. You know, they're their marquee artificial intelligence customer. 808 00:42:51,719 --> 00:42:55,160 Speaker 14: They're helping kind of code develop Amazon's artificial intelligence ship 809 00:42:55,239 --> 00:42:58,239 Speaker 14: called Tranium with them. So the fact that they now have, 810 00:42:58,560 --> 00:43:00,800 Speaker 14: you know, what really looks like edge or an option 811 00:43:00,960 --> 00:43:03,640 Speaker 14: to go more toward Google. Should they choose, should they 812 00:43:03,640 --> 00:43:06,560 Speaker 14: like the tech results better? That is a real risk 813 00:43:06,719 --> 00:43:10,319 Speaker 14: or a potential risk rather for Amazon's business. 814 00:43:10,520 --> 00:43:12,239 Speaker 3: I have a feeling it's a story you're going to 815 00:43:12,280 --> 00:43:14,919 Speaker 3: continue to dig into. It's so well read today. Thank 816 00:43:14,960 --> 00:43:17,640 Speaker 3: you so much. Bloomberg's Mack Day reflecting on the week 817 00:43:17,680 --> 00:43:20,239 Speaker 3: that was for Amazon, and we reflect on the show 818 00:43:20,280 --> 00:43:22,000 Speaker 3: that was because it does it for this edition of 819 00:43:22,040 --> 00:43:24,239 Speaker 3: Bloomberg Tech Ed. It was another huge busy one and 820 00:43:24,280 --> 00:43:25,920 Speaker 3: boy next week to lon end. 821 00:43:26,000 --> 00:43:28,120 Speaker 2: Yeah, like we didn't even get to mention really in 822 00:43:28,120 --> 00:43:30,799 Speaker 2: the course of today, but like next week is the 823 00:43:30,840 --> 00:43:34,279 Speaker 2: tech super Bowl, right, Like in an earnings context, it's 824 00:43:34,400 --> 00:43:35,000 Speaker 2: the biggest one. 825 00:43:35,040 --> 00:43:35,760 Speaker 6: It's going to matter. 826 00:43:36,560 --> 00:43:38,839 Speaker 3: Well, is a video there? I guess not. We've got 827 00:43:38,840 --> 00:43:42,880 Speaker 3: everyone else, Meta, Microsoft, Amazon, you name it, the Vindication, 828 00:43:43,040 --> 00:43:45,239 Speaker 3: the Fundamentals. They've got a lot to check out on 829 00:43:45,239 --> 00:43:45,800 Speaker 3: the podcast. 830 00:43:46,400 --> 00:43:49,040 Speaker 2: I am heading to DC for GtC within video so 831 00:43:49,040 --> 00:43:51,000 Speaker 2: that there might be some news there. Check out the pod. 832 00:43:51,080 --> 00:43:53,359 Speaker 2: You know where to find it. This is Bloomberg Tech