1 00:00:02,520 --> 00:00:13,239 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. Bloomberg Tech is a 2 00:00:13,320 --> 00:00:17,080 Speaker 1: live from Coast to Coast with Caroline Hide in New 3 00:00:17,160 --> 00:00:19,640 Speaker 1: York and Va Lowe in Sentrancisco. 4 00:00:22,800 --> 00:00:26,160 Speaker 2: This is Bloomberg Tech coming up. Salesforce sell off as 5 00:00:26,239 --> 00:00:30,400 Speaker 2: lackluster top line growth forecast suggests AI isn't paying. 6 00:00:30,120 --> 00:00:30,840 Speaker 3: Off just yet. 7 00:00:30,920 --> 00:00:32,240 Speaker 4: Plus, Apple plans. 8 00:00:31,920 --> 00:00:34,159 Speaker 5: To up its AI game with a web search for 9 00:00:34,240 --> 00:00:37,560 Speaker 5: Siri as it leans towards Google's Gemini for its next 10 00:00:37,640 --> 00:00:39,360 Speaker 5: gen voice assistant. 11 00:00:39,640 --> 00:00:43,200 Speaker 2: An HPE, where there's a profit squeeze as AI hits 12 00:00:43,240 --> 00:00:45,680 Speaker 2: the server maker's margins despite demand. 13 00:00:46,040 --> 00:00:48,080 Speaker 4: First, let's take a look at the broader markets. 14 00:00:48,080 --> 00:00:49,960 Speaker 5: You're going to dig into the details of these earnings. 15 00:00:50,040 --> 00:00:52,000 Speaker 5: Z I look at a context that it's up three 16 00:00:52,120 --> 00:00:56,080 Speaker 5: ten percent on the NASDAG. We are digesting pretty woful 17 00:00:56,120 --> 00:00:58,560 Speaker 5: labor data once more, but all eyes on the FED 18 00:00:58,600 --> 00:01:01,320 Speaker 5: to cut ninety chance the money markets that there will 19 00:01:01,320 --> 00:01:04,280 Speaker 5: move as soon as this month, as we still are 20 00:01:04,319 --> 00:01:06,960 Speaker 5: looking at what the Senate is discussing on the future 21 00:01:07,040 --> 00:01:09,240 Speaker 5: of the FED and who's actually sitting on it. 22 00:01:10,400 --> 00:01:13,000 Speaker 2: There's a lot going on this week, but software in 23 00:01:13,040 --> 00:01:16,360 Speaker 2: particular now earnings in that context are driving markets lower 24 00:01:16,600 --> 00:01:19,160 Speaker 2: in this case. So Salesforce is talking of its kind 25 00:01:19,160 --> 00:01:23,120 Speaker 2: of historic growth rates, but the outlook for its top 26 00:01:23,160 --> 00:01:25,240 Speaker 2: line growth, particularly as it relates to AI, it's just 27 00:01:25,240 --> 00:01:27,399 Speaker 2: not there yet. We're going to get into the analysis 28 00:01:27,400 --> 00:01:29,920 Speaker 2: in just a second now, Figma, this is its first 29 00:01:29,959 --> 00:01:31,960 Speaker 2: earnings post IPO at the end of July. 30 00:01:32,560 --> 00:01:33,640 Speaker 6: Big drop on the stock. 31 00:01:33,680 --> 00:01:35,840 Speaker 2: Remember it jumped to one hundred and fifty percent in 32 00:01:35,920 --> 00:01:38,480 Speaker 2: its debut. Carrow, you were there, you lived through it. 33 00:01:38,480 --> 00:01:41,400 Speaker 2: It basically met estimates, but it just shows how high 34 00:01:41,440 --> 00:01:44,039 Speaker 2: and lofty expectations of the market are. Right now, I 35 00:01:44,080 --> 00:01:46,400 Speaker 2: want to dig into numbers, starting with Salesforce. Let's get 36 00:01:46,400 --> 00:01:49,320 Speaker 2: out to Blomberg Intelligence senior tech analyst and rag Rana. 37 00:01:49,400 --> 00:01:51,040 Speaker 2: Maybe you caught Benny off on the call, maybe you 38 00:01:51,080 --> 00:01:53,600 Speaker 2: caught him in interviews on other networks. He was talking 39 00:01:53,680 --> 00:01:56,240 Speaker 2: up about like Salesforce growth rates and a RAG they 40 00:01:56,240 --> 00:01:59,360 Speaker 2: are better than anyone out there. But the story seems 41 00:01:59,360 --> 00:02:01,760 Speaker 2: to be the out and how AI is contributing. 42 00:02:01,760 --> 00:02:05,160 Speaker 7: What do you think? Yeah, I think the expectations were 43 00:02:05,200 --> 00:02:07,000 Speaker 7: a little bit high in that case from the AI 44 00:02:07,040 --> 00:02:09,800 Speaker 7: contribution point of view, But if you look at results 45 00:02:09,800 --> 00:02:13,400 Speaker 7: from Workday and other tech companies, out there. We are 46 00:02:13,520 --> 00:02:17,320 Speaker 7: still struggling to see discritionary it spending bounce back. We 47 00:02:17,360 --> 00:02:19,640 Speaker 7: have not seen any of that stuff. And given the 48 00:02:19,680 --> 00:02:22,480 Speaker 7: size of a company salesforces, you're going to see the 49 00:02:22,600 --> 00:02:24,920 Speaker 7: impact of that on bottom lines. If there are no 50 00:02:25,000 --> 00:02:27,800 Speaker 7: massive secrets out there, you're not going to see revenue 51 00:02:27,800 --> 00:02:30,080 Speaker 7: acce rate. And I think that's the story, which is, 52 00:02:30,440 --> 00:02:33,480 Speaker 7: you know, I think common to most of the software landscape, 53 00:02:33,560 --> 00:02:37,320 Speaker 7: except the companies that you know only work on AI, infrastructure, parking. 54 00:02:37,600 --> 00:02:39,840 Speaker 7: If you leave them alone, the rest of the industry 55 00:02:39,880 --> 00:02:40,799 Speaker 7: is struggling. 56 00:02:40,440 --> 00:02:44,440 Speaker 5: Right now, what do you make the first numbers from Figma, 57 00:02:44,560 --> 00:02:47,399 Speaker 5: because in many ways it was a company that pivoted 58 00:02:47,440 --> 00:02:50,000 Speaker 5: well embraced generator of AI was able to show how 59 00:02:50,000 --> 00:02:52,520 Speaker 5: it's working for its bottom line as a public company. 60 00:02:52,880 --> 00:02:54,400 Speaker 4: We are seeing a tunnel in the shares. 61 00:02:55,320 --> 00:02:57,880 Speaker 7: Yeah, I would say that my expectations were pretty bad 62 00:02:58,120 --> 00:03:00,359 Speaker 7: or wrong in this case. I was looking for a 63 00:03:00,480 --> 00:03:03,359 Speaker 7: revenue to improve because of a price increase they have 64 00:03:03,440 --> 00:03:06,040 Speaker 7: put in. But it seems like, you know, they basically 65 00:03:06,120 --> 00:03:08,919 Speaker 7: met the expectations that they gave. And to be very frank, 66 00:03:08,960 --> 00:03:11,360 Speaker 7: in an IPO landscape, it doesn't work like that. The 67 00:03:11,400 --> 00:03:13,960 Speaker 7: first few quoters. You really need to showcase, you know, 68 00:03:14,000 --> 00:03:17,520 Speaker 7: an improvement in fundamentals. This just shows that there is 69 00:03:17,560 --> 00:03:19,519 Speaker 7: a lot they have to do in order to get 70 00:03:19,560 --> 00:03:21,760 Speaker 7: and I would say match up to the valuation that 71 00:03:21,800 --> 00:03:23,000 Speaker 7: they have achieved right now. 72 00:03:23,520 --> 00:03:27,440 Speaker 5: An Agrana holding yourself accountable. We appreciate that. Bluemeg Intelligence. 73 00:03:27,680 --> 00:03:30,440 Speaker 5: We always love the expertise. Let's get a broader look 74 00:03:30,480 --> 00:03:32,800 Speaker 5: at the tech sector right now because Carol Schlife is 75 00:03:32,800 --> 00:03:35,720 Speaker 5: with us BIMO Private Wealth Chief market Strategist. 76 00:03:36,040 --> 00:03:37,000 Speaker 4: Carol, it's been a while. 77 00:03:37,240 --> 00:03:40,280 Speaker 5: Great to have you on Bloomberg Tech and more broadly, 78 00:03:40,320 --> 00:03:42,760 Speaker 5: how are you thinking of the software story the AI 79 00:03:42,880 --> 00:03:45,000 Speaker 5: winners versus Lewis's right now. 80 00:03:45,960 --> 00:03:48,600 Speaker 8: Now we really first up, thanks for having me on. 81 00:03:48,720 --> 00:03:52,200 Speaker 8: It's great to be back again, and it really is important. 82 00:03:52,360 --> 00:03:55,440 Speaker 8: It takes you know, investors are very black and white. 83 00:03:55,440 --> 00:03:58,000 Speaker 8: They want to see instantaneous results, but all of this 84 00:03:58,040 --> 00:04:00,520 Speaker 8: stuff takes some time to filter through a figure out 85 00:04:00,560 --> 00:04:04,560 Speaker 8: how we're going to deploy it. But the software and 86 00:04:04,320 --> 00:04:07,600 Speaker 8: that moving away from, if you will, the picks and 87 00:04:07,640 --> 00:04:11,200 Speaker 8: shovels of building out the infrastructure into the use cases 88 00:04:11,240 --> 00:04:14,080 Speaker 8: and how that factors in. That is definitely a way 89 00:04:14,120 --> 00:04:17,600 Speaker 8: that we see things playing out in the intermediate to 90 00:04:17,720 --> 00:04:20,520 Speaker 8: longer term because you're not going to be able to 91 00:04:20,520 --> 00:04:22,880 Speaker 8: get away from AI. A lot of companies are trying 92 00:04:22,920 --> 00:04:24,880 Speaker 8: to figure out how to deploy it, how to use it, 93 00:04:25,360 --> 00:04:28,279 Speaker 8: how to train their employees in using it. Because you've 94 00:04:28,279 --> 00:04:30,839 Speaker 8: got those early adopters who are using it actively, and 95 00:04:30,880 --> 00:04:33,839 Speaker 8: you've got the others that are not as willing to 96 00:04:33,839 --> 00:04:35,760 Speaker 8: be on the bleeding edge, if you will, of the 97 00:04:35,839 --> 00:04:36,839 Speaker 8: day to day use case. 98 00:04:37,680 --> 00:04:41,880 Speaker 5: What therefore, is the likelihood that some of the older 99 00:04:42,120 --> 00:04:45,719 Speaker 5: companies with big presence in the market, such as a salesforce, 100 00:04:46,160 --> 00:04:48,599 Speaker 5: can fend off new competition. How much you having to 101 00:04:48,640 --> 00:04:51,400 Speaker 5: build that in to an invest the risk right now 102 00:04:51,440 --> 00:04:54,200 Speaker 5: that we are seeing a totally new cohort come to 103 00:04:54,279 --> 00:04:58,560 Speaker 5: a powerful place in general to AI, you are, but. 104 00:04:58,520 --> 00:05:02,479 Speaker 8: You're also seeing those the old line, old guard have 105 00:05:02,640 --> 00:05:05,040 Speaker 8: the cash flow to be able to snap up some 106 00:05:05,120 --> 00:05:08,200 Speaker 8: of those. It's almost like a whales and krill kind 107 00:05:08,279 --> 00:05:12,160 Speaker 8: of scenario out there, and you look at, for example, 108 00:05:12,200 --> 00:05:14,240 Speaker 8: in the build out of the infrastructure, You've got a 109 00:05:14,240 --> 00:05:16,760 Speaker 8: lot of that going on too, where the largest companies 110 00:05:17,120 --> 00:05:20,560 Speaker 8: are buying up the smaller companies in the competition, so 111 00:05:20,640 --> 00:05:25,160 Speaker 8: that really smart, really useful competition. One of the ways 112 00:05:25,200 --> 00:05:29,120 Speaker 8: they get leverage and into a lot of end users too, 113 00:05:29,440 --> 00:05:32,560 Speaker 8: is through the distribution channel of some of those larger companies. 114 00:05:32,600 --> 00:05:35,000 Speaker 8: So there's a use case to be made or an 115 00:05:35,040 --> 00:05:37,400 Speaker 8: investment case to be made for a whole lot of 116 00:05:37,760 --> 00:05:39,840 Speaker 8: sizes in that software industry. 117 00:05:40,720 --> 00:05:43,360 Speaker 2: Carol, I really appreciate that the command you've got over 118 00:05:43,440 --> 00:05:47,000 Speaker 2: what's happening right particularly in software. We've been talking about 119 00:05:47,000 --> 00:05:49,480 Speaker 2: it all week. I mean, one of our guests this 120 00:05:49,560 --> 00:05:53,080 Speaker 2: week said that September was the most hated month for investors. 121 00:05:53,400 --> 00:05:57,440 Speaker 2: But basically, you know, we're going back to old fashioned 122 00:05:57,440 --> 00:06:01,719 Speaker 2: earnings talk. Did they meet or excited high expectation, particularly 123 00:06:01,720 --> 00:06:05,400 Speaker 2: in software sense? Not really? Did AI have a tangible 124 00:06:05,400 --> 00:06:06,840 Speaker 2: contribution to top line growth? 125 00:06:07,120 --> 00:06:07,200 Speaker 9: Not? 126 00:06:07,320 --> 00:06:07,640 Speaker 4: Really? 127 00:06:07,960 --> 00:06:11,719 Speaker 2: Is that the way that you approach a week like this, Well, I. 128 00:06:11,760 --> 00:06:14,560 Speaker 8: Think a piece of it is is investors have to 129 00:06:14,640 --> 00:06:19,000 Speaker 8: understand where what timeframe they're using, and where their expectations are, 130 00:06:19,000 --> 00:06:21,880 Speaker 8: because you know, we've looked at a lot of these 131 00:06:21,920 --> 00:06:25,520 Speaker 8: companies and you've got very active. When you step back 132 00:06:25,520 --> 00:06:27,600 Speaker 8: from it, you look at the margins on these companies 133 00:06:27,680 --> 00:06:29,520 Speaker 8: relative to most of the rest of the S and 134 00:06:29,600 --> 00:06:33,320 Speaker 8: P those margins are great margins are cash flowing businesses, 135 00:06:33,760 --> 00:06:36,480 Speaker 8: and as we all know, once you put a software 136 00:06:36,640 --> 00:06:40,039 Speaker 8: system into a company, it's really hard to make a 137 00:06:40,080 --> 00:06:42,800 Speaker 8: decision to change that or move that. And so from 138 00:06:42,839 --> 00:06:46,560 Speaker 8: that perspective, I think investors have to ask themselves on 139 00:06:46,640 --> 00:06:49,599 Speaker 8: an absolute basis, are these companies generating the kinds of 140 00:06:49,640 --> 00:06:52,920 Speaker 8: revenues that I want? Even if they didn't be what 141 00:06:53,120 --> 00:06:57,039 Speaker 8: the wildest expectations that I was hoping for. Because the 142 00:06:57,080 --> 00:07:00,240 Speaker 8: industry tends to run or investors tend to run ahead 143 00:07:00,240 --> 00:07:03,000 Speaker 8: of themselves, and the whisper numbers always a little bit 144 00:07:03,080 --> 00:07:06,880 Speaker 8: higher than where they're at, and yet the companies, the 145 00:07:06,960 --> 00:07:11,120 Speaker 8: industry in general are generating amazing returns. 146 00:07:12,000 --> 00:07:14,680 Speaker 2: Carol, this week we talked at about concentration risk, and 147 00:07:14,720 --> 00:07:17,680 Speaker 2: the more sanguine of your peers in the market would say, well, 148 00:07:18,040 --> 00:07:21,520 Speaker 2: we look at profit estimates for the MAG seven in particular, 149 00:07:21,600 --> 00:07:24,200 Speaker 2: but tech generally so much better than the S and 150 00:07:24,200 --> 00:07:27,440 Speaker 2: P five hundred aggregate. But you have concentration risk. How 151 00:07:27,480 --> 00:07:29,080 Speaker 2: are you thinking about that at the moment. 152 00:07:30,120 --> 00:07:33,120 Speaker 8: I think one of the ways that we deal with 153 00:07:33,160 --> 00:07:37,000 Speaker 8: it is barbelling portfolios and really leaning into that diversification 154 00:07:37,080 --> 00:07:42,280 Speaker 8: because there is concentration risk. You've also got higher valuations overall, 155 00:07:42,560 --> 00:07:46,240 Speaker 8: and you've got markets that are primed for perfection if 156 00:07:46,240 --> 00:07:48,720 Speaker 8: you will, so they don't, they don't leave. That doesn't 157 00:07:48,800 --> 00:07:51,560 Speaker 8: leave much wiggle room other than when you get big 158 00:07:51,600 --> 00:07:53,680 Speaker 8: pullbacks like we had in April. It's one of the 159 00:07:53,680 --> 00:07:56,400 Speaker 8: reasons why I think the pullback was so short lived 160 00:07:56,480 --> 00:07:59,040 Speaker 8: back then and the reset was quick is people who 161 00:07:59,040 --> 00:08:01,720 Speaker 8: have been sitting on the sidelines looking for an opportunity 162 00:08:01,760 --> 00:08:03,880 Speaker 8: to get in dead. So one of the ways that 163 00:08:03,920 --> 00:08:08,240 Speaker 8: you deal with that is you school yourself to expect 164 00:08:08,320 --> 00:08:12,080 Speaker 8: some level of volatility, don't freak out when it first happens, 165 00:08:12,360 --> 00:08:15,600 Speaker 8: and maybe own some other industries, some other segments, some 166 00:08:15,720 --> 00:08:18,880 Speaker 8: other parts of the globe, and maybe some fixed incomers 167 00:08:19,200 --> 00:08:22,720 Speaker 8: to balance the portfolio and to allow it to be 168 00:08:22,760 --> 00:08:24,560 Speaker 8: able to ride through those storms. 169 00:08:25,200 --> 00:08:26,360 Speaker 4: Diversification key. 170 00:08:26,480 --> 00:08:29,360 Speaker 5: But just going back to the concentration risk and the 171 00:08:29,440 --> 00:08:31,480 Speaker 5: area of hardware having been the most loved. 172 00:08:31,520 --> 00:08:33,160 Speaker 4: Salesforce is down thirty. 173 00:08:32,920 --> 00:08:37,320 Speaker 5: Percent basically year to date with looking at Broadcom up 174 00:08:37,440 --> 00:08:39,600 Speaker 5: thirty percent year to date, and we got their earnings 175 00:08:39,600 --> 00:08:42,280 Speaker 5: after the ball is hardware and picks and shovels still 176 00:08:42,280 --> 00:08:44,880 Speaker 5: where it's at Carol, Well, I think. 177 00:08:44,760 --> 00:08:46,839 Speaker 8: A piece of it. We're not through with that build 178 00:08:46,920 --> 00:08:49,440 Speaker 8: ut segment yet, but you know, a piece of the 179 00:08:49,520 --> 00:08:52,240 Speaker 8: questions you're starting to ask yourself is particularly as it 180 00:08:52,280 --> 00:08:54,880 Speaker 8: relates to data centers and some of the other things 181 00:08:54,880 --> 00:08:56,880 Speaker 8: that are going on. It's great if you can put 182 00:08:56,880 --> 00:08:59,240 Speaker 8: them up, if you can put a side, then not 183 00:08:59,360 --> 00:09:01,600 Speaker 8: in my backyard, and sorts of pushback you're getting in 184 00:09:01,679 --> 00:09:03,839 Speaker 8: some of those, but then when you're getting told it's 185 00:09:03,840 --> 00:09:05,440 Speaker 8: going to take five or six years to hook it 186 00:09:05,480 --> 00:09:07,800 Speaker 8: to the grid. So there's lots of different ways to 187 00:09:07,880 --> 00:09:11,600 Speaker 8: play the hardware and the buildout and who's got capacity 188 00:09:11,600 --> 00:09:13,600 Speaker 8: and able to do it. But there's a whole other 189 00:09:13,679 --> 00:09:18,000 Speaker 8: segment of bringing in some of the reshoring activities that 190 00:09:18,040 --> 00:09:19,959 Speaker 8: are going on as well. 191 00:09:20,040 --> 00:09:22,040 Speaker 2: Carol, it's got to that time of the show where 192 00:09:22,040 --> 00:09:25,680 Speaker 2: I ask you the impossible question, what happens next in 193 00:09:25,720 --> 00:09:28,640 Speaker 2: the balance of twenty twenty five for the technology sector? 194 00:09:28,679 --> 00:09:30,920 Speaker 2: Your big predictions, please, We. 195 00:09:31,440 --> 00:09:34,040 Speaker 8: Do think that you'll see continued grind higher. I mean, 196 00:09:34,160 --> 00:09:37,240 Speaker 8: markets have been climbing a wall of worry technology as 197 00:09:37,280 --> 00:09:40,280 Speaker 8: well all year, and we think you'll see a continued 198 00:09:40,320 --> 00:09:44,119 Speaker 8: sort of grudging climb higher. You know, many company managements 199 00:09:44,120 --> 00:09:47,880 Speaker 8: have told us they're nauseously optimistic for this final quarter, 200 00:09:47,920 --> 00:09:49,640 Speaker 8: and I would think we're in that camp too. 201 00:09:51,360 --> 00:09:53,720 Speaker 2: Carol's life a bemo private wealth. It's great to have 202 00:09:53,760 --> 00:09:56,280 Speaker 2: you back on the show and we always appreciate a prediction. 203 00:09:56,400 --> 00:09:58,839 Speaker 2: Thank you very much. Now we have some breaking news 204 00:09:58,880 --> 00:10:01,800 Speaker 2: crossing the Bloomberg time or. Rhode Island and Connecticut have 205 00:10:01,920 --> 00:10:06,360 Speaker 2: sued the Trump administration over the administration order blocking further 206 00:10:06,440 --> 00:10:09,880 Speaker 2: construction of a nearly completed offshore wind palm, which was 207 00:10:09,920 --> 00:10:12,680 Speaker 2: meant to provide power to the two New England states. 208 00:10:12,720 --> 00:10:16,000 Speaker 2: You'll remember, Carra, August twenty second, the administration issued that 209 00:10:16,160 --> 00:10:19,520 Speaker 2: stop work order. We also had the companies involved have 210 00:10:19,600 --> 00:10:22,720 Speaker 2: a parallel suit against the US in order that the 211 00:10:22,760 --> 00:10:25,320 Speaker 2: wind farm work can continue. But the breaking news right 212 00:10:25,320 --> 00:10:27,360 Speaker 2: now is that Rhode Island and Connecticut, two of the 213 00:10:27,400 --> 00:10:30,880 Speaker 2: New England states, participating in a suit against the administration, 214 00:10:31,320 --> 00:10:33,200 Speaker 2: trying to get the judge to allow that work to 215 00:10:33,280 --> 00:10:33,840 Speaker 2: move forward. 216 00:10:34,080 --> 00:10:35,559 Speaker 4: What we got next future. 217 00:10:35,240 --> 00:10:37,160 Speaker 5: Of energy is important to AI. We go back to 218 00:10:37,240 --> 00:10:40,520 Speaker 5: aied coming up, Apple looking to go toe to toe 219 00:10:41,040 --> 00:10:43,400 Speaker 5: with Open AI. Of course company it has a partnership with, 220 00:10:43,559 --> 00:10:46,520 Speaker 5: but it's launching its own AI web search, integrating it 221 00:10:46,520 --> 00:10:46,920 Speaker 5: in SyRI. 222 00:10:47,000 --> 00:10:49,360 Speaker 4: We'll dig into that next. This is Bloomberg Tech. 223 00:11:16,320 --> 00:11:19,480 Speaker 5: Apple said to be launching its own AI web search 224 00:11:19,559 --> 00:11:23,240 Speaker 5: tool integrated into Siri, basically rivaling the likes of Open AI. 225 00:11:23,360 --> 00:11:26,560 Speaker 5: Of Perplexity megs Mark German joins us, Now, it is 226 00:11:26,679 --> 00:11:29,480 Speaker 5: such a thoroughly reported piece you put out yesterday and 227 00:11:29,520 --> 00:11:32,320 Speaker 5: moved the stock. What's interesting is who's going to be 228 00:11:32,320 --> 00:11:36,600 Speaker 5: helping build the underlying LLM and generator of AI within it. 229 00:11:36,679 --> 00:11:40,160 Speaker 5: And it's not Perplexity, and it's seemingly not anthropic either. 230 00:11:41,360 --> 00:11:43,559 Speaker 6: Yeah, that's right. We've known for some time that Apple's 231 00:11:43,600 --> 00:11:46,960 Speaker 6: launching an overhauled version of Siri around March. This is 232 00:11:47,000 --> 00:11:49,960 Speaker 6: going to include delayed features like the ability to tap 233 00:11:50,000 --> 00:11:53,960 Speaker 6: into your personal data to fulfill queries. Obviously it's surprising 234 00:11:54,000 --> 00:11:57,040 Speaker 6: it couldn't do that till now after launching fifteen years ago. 235 00:11:57,440 --> 00:12:00,280 Speaker 6: But the feature that we didn't know was coming until 236 00:12:00,320 --> 00:12:04,800 Speaker 6: yesterday is an AI web search tool, sort of an 237 00:12:04,840 --> 00:12:09,599 Speaker 6: answer engine. Siri right now is able to answer questions, 238 00:12:09,760 --> 00:12:13,240 Speaker 6: broad strokes of information it can provide, can control your phone, 239 00:12:13,640 --> 00:12:16,200 Speaker 6: send messages, and what have you. What it doesn't do 240 00:12:16,280 --> 00:12:18,920 Speaker 6: well is tap into the open web to get information 241 00:12:19,160 --> 00:12:21,120 Speaker 6: and to still it down for you in the way 242 00:12:21,160 --> 00:12:24,760 Speaker 6: that AI search engines today can do things like perplexity, 243 00:12:24,800 --> 00:12:27,840 Speaker 6: things like CHATCHGPT. So now Apple will be launching their 244 00:12:27,840 --> 00:12:30,679 Speaker 6: own answer engine that's going to come in March as 245 00:12:30,720 --> 00:12:33,280 Speaker 6: part of an update called iOS twenty six point four, 246 00:12:33,679 --> 00:12:36,719 Speaker 6: and over time I anticipate them to integrate it into Safari, 247 00:12:36,800 --> 00:12:40,440 Speaker 6: into Spotlight and other parts of its operating systems. You know, 248 00:12:40,559 --> 00:12:43,000 Speaker 6: Google Search is very important to Apple. It makes them 249 00:12:43,160 --> 00:12:47,080 Speaker 6: roughly twenty billion plus per year. But the industry is shifting. 250 00:12:47,360 --> 00:12:49,559 Speaker 6: You know, how many times are you going to Google 251 00:12:49,600 --> 00:12:52,319 Speaker 6: Search right now? Probably fewer than you used to a 252 00:12:52,400 --> 00:12:55,600 Speaker 6: lot of people are doing their searches from CHATCHGPT or perplexity. 253 00:12:55,840 --> 00:12:58,720 Speaker 6: It's an increasing number of people. So this is important 254 00:12:58,720 --> 00:12:59,720 Speaker 6: for Apple for its long term. 255 00:12:59,760 --> 00:13:03,640 Speaker 2: Few world knowledge answers is just one part. You know, 256 00:13:03,679 --> 00:13:06,360 Speaker 2: you're reporting shows us what the market has actually been 257 00:13:06,400 --> 00:13:09,679 Speaker 2: asking for, which is when this revamp SERI comes as 258 00:13:09,679 --> 00:13:14,400 Speaker 2: a package, so spring next year. I see basically three parts, right, 259 00:13:14,440 --> 00:13:18,240 Speaker 2: a Siri redesign, a health AI subscription service, and then 260 00:13:18,280 --> 00:13:21,079 Speaker 2: some conversational features on the home devices which we've discussed 261 00:13:21,080 --> 00:13:23,400 Speaker 2: on the show What are we waiting for? That's coming 262 00:13:23,480 --> 00:13:23,920 Speaker 2: in March? 263 00:13:23,960 --> 00:13:28,040 Speaker 6: Mark in total, So what's coming in March is this 264 00:13:28,120 --> 00:13:31,240 Speaker 6: AI search product I mentioned. The ability to tap into 265 00:13:31,280 --> 00:13:34,440 Speaker 6: personal data to fulfill queries, things like who did I 266 00:13:34,480 --> 00:13:37,280 Speaker 6: meet with a month ago? What song did ED text 267 00:13:37,320 --> 00:13:41,000 Speaker 6: me last week? The ability to fulfill queries based on 268 00:13:41,000 --> 00:13:43,240 Speaker 6: on screen content. You're looking at a picture of someone, 269 00:13:43,280 --> 00:13:46,240 Speaker 6: tell me more. And then you have voice based navigation, 270 00:13:46,360 --> 00:13:48,840 Speaker 6: so using your voice to control your phone, move around 271 00:13:48,880 --> 00:13:53,040 Speaker 6: your operating system, telling Siri to like something on Instagram. 272 00:13:53,200 --> 00:13:56,680 Speaker 6: Later in the year, you'll see the Health Plus subscription service, 273 00:13:56,920 --> 00:14:00,280 Speaker 6: which is basically an AI agent for health. And you're 274 00:14:00,280 --> 00:14:03,040 Speaker 6: also going to see a visual redesign for Siri later 275 00:14:03,120 --> 00:14:05,719 Speaker 6: next year, and then the year after is likely when 276 00:14:05,720 --> 00:14:08,800 Speaker 6: you're going to see the conversational Siri tied to that 277 00:14:08,920 --> 00:14:13,160 Speaker 6: new robotic home device, the tabletop Robot, which is essentially 278 00:14:13,559 --> 00:14:16,600 Speaker 6: a virtual person to have in your workspace to help 279 00:14:16,640 --> 00:14:18,040 Speaker 6: you get things done throughout your day. 280 00:14:18,880 --> 00:14:23,320 Speaker 5: So my question is, first, ed, what song did you 281 00:14:23,800 --> 00:14:25,000 Speaker 5: message Mark German? 282 00:14:25,760 --> 00:14:26,000 Speaker 10: Was it? 283 00:14:26,040 --> 00:14:28,160 Speaker 2: I believe it was, Yeah, it was Pink Pony Club. 284 00:14:28,200 --> 00:14:31,680 Speaker 2: That's no surprise any regular followers on social media. But 285 00:14:31,720 --> 00:14:33,760 Speaker 2: I'm interested, Like you know, when I look at how 286 00:14:33,840 --> 00:14:37,080 Speaker 2: Siri works right now, or Apple Intelligence, it summarizes what's 287 00:14:37,080 --> 00:14:39,160 Speaker 2: in my email. It often will be like, here's your 288 00:14:39,160 --> 00:14:42,000 Speaker 2: Spotify playlist of the day. Spotify sends updates as well. 289 00:14:42,160 --> 00:14:43,440 Speaker 2: What would you have sent, Mark Carrot? 290 00:14:44,600 --> 00:14:47,200 Speaker 5: What would I have sent? I? Did you see Oasis? 291 00:14:47,440 --> 00:14:50,520 Speaker 5: So probably an Oasis song? But Mark Brawley, the question 292 00:14:50,560 --> 00:14:52,640 Speaker 5: that I'm also going to ask you is, therefore I 293 00:14:52,720 --> 00:14:56,280 Speaker 5: go back to the underlying technology here, the relationship between 294 00:14:56,320 --> 00:14:58,680 Speaker 5: Google and Apple. We've just had such an update on 295 00:14:58,720 --> 00:14:59,560 Speaker 5: it from Judge. 296 00:14:59,280 --> 00:14:59,960 Speaker 4: Meta this week. 297 00:15:00,240 --> 00:15:02,120 Speaker 5: That's going to be integral for what's going to be 298 00:15:02,120 --> 00:15:04,400 Speaker 5: building the underlying technology for this product. 299 00:15:04,480 --> 00:15:07,000 Speaker 6: Right Ah, Yes, you asked me that earlier. 300 00:15:07,000 --> 00:15:12,240 Speaker 5: I did not answer the question, So. 301 00:15:10,640 --> 00:15:11,080 Speaker 11: Go for it. 302 00:15:11,200 --> 00:15:11,520 Speaker 10: Yes. 303 00:15:12,000 --> 00:15:15,640 Speaker 6: So Apple has talked to open Ai and Thropic and 304 00:15:15,800 --> 00:15:19,600 Speaker 6: Google most recently to partner with them to rebuild Siri 305 00:15:19,880 --> 00:15:22,800 Speaker 6: as one of the components underlying the new Serie engine, 306 00:15:23,240 --> 00:15:25,240 Speaker 6: and a lot of signs right now are pointing to 307 00:15:25,320 --> 00:15:28,520 Speaker 6: them working with Gemini. Google has built a model for them. 308 00:15:28,960 --> 00:15:31,560 Speaker 6: The two companies signed an agreement earlier this week a 309 00:15:31,640 --> 00:15:34,720 Speaker 6: formal evaluation agreement. This doesn't mean they have a commercial agreement. 310 00:15:34,920 --> 00:15:37,960 Speaker 6: That means they've agreed for Apple to evaluate a model. 311 00:15:38,600 --> 00:15:41,960 Speaker 6: They're fine tuning it, and they're heavily considering it. They've 312 00:15:42,040 --> 00:15:46,080 Speaker 6: also considered Anthropic very heavily, and they still are for 313 00:15:46,160 --> 00:15:49,640 Speaker 6: different parts of Siri. The problem is is that Anthropic 314 00:15:49,720 --> 00:15:51,880 Speaker 6: wants north of one point five billion a year and 315 00:15:51,880 --> 00:15:54,600 Speaker 6: then revenue number that's going to escalate annually for the 316 00:15:54,640 --> 00:15:58,480 Speaker 6: next three years, and that is a pretty a very 317 00:15:58,520 --> 00:16:01,560 Speaker 6: big dollar amount to pay for technology like this. In 318 00:16:01,600 --> 00:16:04,760 Speaker 6: Apple's mind, they feel they have little leverage here, and 319 00:16:04,880 --> 00:16:07,400 Speaker 6: Google's a longtime partner and obviously that partnership is going 320 00:16:07,440 --> 00:16:09,960 Speaker 6: to continue, so it all seems to fit. So we'll 321 00:16:09,960 --> 00:16:12,400 Speaker 6: see what ends up happening, but I'm thinking Google. 322 00:16:12,120 --> 00:16:12,600 Speaker 10: As of now. 323 00:16:13,600 --> 00:16:16,800 Speaker 2: Bloomberg's Mark German, who, as Cary said, very detailed report 324 00:16:16,840 --> 00:16:19,960 Speaker 2: on what happens next with Siri, Thank you very much. Meanwhile, 325 00:16:20,000 --> 00:16:23,120 Speaker 2: open AI rival deep Seek's said to be developing an 326 00:16:23,160 --> 00:16:26,280 Speaker 2: AI model with more advanced AI agent features. I want 327 00:16:26,280 --> 00:16:28,840 Speaker 2: to get out to our AI editor Bloomberg Seth Figureman. 328 00:16:29,400 --> 00:16:32,480 Speaker 2: Very interesting story that Bloomberg broke because like deep Seek, 329 00:16:32,720 --> 00:16:35,760 Speaker 2: actually despite the sort of volatility of April, which deep 330 00:16:35,800 --> 00:16:39,000 Speaker 2: Seat calls in markets. It moves slower than some of 331 00:16:39,000 --> 00:16:41,760 Speaker 2: the other Chinese names working on models, but the whole 332 00:16:41,800 --> 00:16:44,120 Speaker 2: point is that this is a gentic AI. They want 333 00:16:44,120 --> 00:16:45,640 Speaker 2: something that goes beyond the chatbot. 334 00:16:46,080 --> 00:16:47,720 Speaker 12: Yeah, that's right. I think we've all been a little 335 00:16:47,760 --> 00:16:50,400 Speaker 12: bit surprised at how little we've heard from deep Seek 336 00:16:50,400 --> 00:16:53,280 Speaker 12: in the last eight months since up ended the markets. 337 00:16:53,320 --> 00:16:56,200 Speaker 12: We've seen a lot of products from Chinese and US rivals, 338 00:16:56,480 --> 00:16:57,960 Speaker 12: and there's a lot of speculation mat what's going on 339 00:16:58,000 --> 00:17:00,080 Speaker 12: behind the scenes. There are other challenges that might be facing, 340 00:17:00,120 --> 00:17:02,640 Speaker 12: but what we've hurt and reported today is that its 341 00:17:02,640 --> 00:17:04,840 Speaker 12: focus is really trying to make a splash in the 342 00:17:04,880 --> 00:17:06,919 Speaker 12: agent market. And you know, for viewers here, this has 343 00:17:06,960 --> 00:17:09,679 Speaker 12: really been where the tech industry has shifted to in 344 00:17:09,720 --> 00:17:12,439 Speaker 12: the last six months or so. Open the eye, Anthropic, 345 00:17:12,560 --> 00:17:15,679 Speaker 12: Google and others are all pushing out AI agent products. 346 00:17:15,720 --> 00:17:17,720 Speaker 12: I think what Deepseeek is trying to do is basically 347 00:17:18,119 --> 00:17:21,359 Speaker 12: build a new model that has agentic capabilities you know, 348 00:17:21,440 --> 00:17:24,280 Speaker 12: embeded within it so that it can field more complex, 349 00:17:24,760 --> 00:17:28,560 Speaker 12: multi step tasks on your behalf with minimal intervention. Again, 350 00:17:28,640 --> 00:17:30,119 Speaker 12: a lot of companies are trying to do this, and 351 00:17:30,160 --> 00:17:33,560 Speaker 12: we are seeing very mixed range of execution here, and 352 00:17:33,640 --> 00:17:35,800 Speaker 12: it seems like deep Sea probably wants to make sure 353 00:17:35,800 --> 00:17:38,359 Speaker 12: they put out something that will move the needle in 354 00:17:38,440 --> 00:17:39,880 Speaker 12: this potentially crowded market. 355 00:17:40,440 --> 00:17:44,520 Speaker 5: But the crowding really for deep Seek is its popularity 356 00:17:44,520 --> 00:17:46,960 Speaker 5: in China. At the moment, is still the most popular 357 00:17:47,080 --> 00:17:50,440 Speaker 5: chatbot tool. But as we say, Ali Baba Tencent, they've 358 00:17:50,480 --> 00:17:53,119 Speaker 5: just had a rapid rate of innovations in their models. 359 00:17:53,119 --> 00:17:55,040 Speaker 4: When do we anticipate R two will come out? 360 00:17:55,240 --> 00:17:56,919 Speaker 12: Yeah, so again we gotta know if this one is 361 00:17:57,040 --> 00:17:58,640 Speaker 12: R two, but this model is supposed to come out 362 00:17:58,640 --> 00:18:00,840 Speaker 12: before the end of the Year's interesting though, is that 363 00:18:00,880 --> 00:18:03,600 Speaker 12: Ali Baba tends up the ones you mentioned haven't been 364 00:18:03,720 --> 00:18:06,199 Speaker 12: as active I think in the agent marketplace. I mean, 365 00:18:06,240 --> 00:18:08,640 Speaker 12: they're doing a lot of image and digo generation technology, 366 00:18:08,680 --> 00:18:12,000 Speaker 12: a lot of more sophisticated chatbots manners which we and 367 00:18:12,040 --> 00:18:15,800 Speaker 12: others have covered, which is originally from Chinese origin, but 368 00:18:15,840 --> 00:18:17,720 Speaker 12: now trying to move into Singapore. They have made a 369 00:18:17,720 --> 00:18:19,760 Speaker 12: bigger splash with agent products, So there might be a 370 00:18:19,800 --> 00:18:22,879 Speaker 12: bigger market within China and globally if deep Sea can 371 00:18:22,920 --> 00:18:24,920 Speaker 12: do something competitive on the agent front. But it's hard 372 00:18:24,960 --> 00:18:27,199 Speaker 12: to say right now how much it'll be different from 373 00:18:27,240 --> 00:18:27,879 Speaker 12: what's out there. 374 00:18:28,200 --> 00:18:30,440 Speaker 4: Seth Fiegerman breaking it down on Deep Seat. We so 375 00:18:30,600 --> 00:18:37,199 Speaker 4: appreciate it. 376 00:18:37,200 --> 00:18:39,240 Speaker 5: It is time now for talking tech and first up. 377 00:18:39,240 --> 00:18:40,400 Speaker 4: Red Note so its. 378 00:18:40,320 --> 00:18:43,240 Speaker 5: Valuation served nineteen percent in just three months. 379 00:18:43,320 --> 00:18:45,359 Speaker 4: I think thirty one billion dollars now. The social media 380 00:18:45,400 --> 00:18:47,320 Speaker 4: firm emerged the year this year. 381 00:18:47,280 --> 00:18:50,639 Speaker 5: As a real viable competitor to TikTok, which faces threats 382 00:18:50,640 --> 00:18:52,679 Speaker 5: of a ban in the United States. Remember some Red 383 00:18:52,760 --> 00:18:56,280 Speaker 5: Note investors anticipate in an imminent IPO plus s k 384 00:18:56,440 --> 00:18:58,919 Speaker 5: Heinex is set to pay two week seven billion dollars 385 00:18:58,920 --> 00:19:02,200 Speaker 5: in bonuses to twelve labour tensions. Now, the company's labor 386 00:19:02,240 --> 00:19:05,520 Speaker 5: union has improven landmark agreement allocating ten percent of the 387 00:19:05,520 --> 00:19:09,000 Speaker 5: company's annual profitence to a bonus pool of its thirty 388 00:19:09,000 --> 00:19:12,240 Speaker 5: three thousand, six and twenty five employees. For twenty twenty 389 00:19:12,320 --> 00:19:15,880 Speaker 5: five alone, employees could receive only eighty thousand. 390 00:19:15,600 --> 00:19:16,960 Speaker 4: Dollars in bonus. 391 00:19:17,200 --> 00:19:19,720 Speaker 5: And in Vidia's venture capital arm is set to invest 392 00:19:19,920 --> 00:19:22,280 Speaker 5: in Honeywell's Quantinum for. 393 00:19:22,280 --> 00:19:22,920 Speaker 4: The first time. 394 00:19:23,200 --> 00:19:25,359 Speaker 5: In Vidier is the latest big name backer behind the 395 00:19:25,440 --> 00:19:28,800 Speaker 5: quantum computing company with the latest investment set to value 396 00:19:28,880 --> 00:19:31,680 Speaker 5: quantinum at ten million dollars ed. 397 00:19:32,640 --> 00:19:35,119 Speaker 2: All right, this week British finance app Revelue offered a 398 00:19:35,200 --> 00:19:37,840 Speaker 2: secondary share sale with a seventy five billion dollar valuation. 399 00:19:37,880 --> 00:19:40,520 Speaker 2: We covered it on the show Bloomberg's learned that Revolute 400 00:19:40,520 --> 00:19:44,400 Speaker 2: is putting in extra work to remain private while retaining 401 00:19:44,440 --> 00:19:47,120 Speaker 2: talent and appease some of its VC backers. Let's get 402 00:19:47,119 --> 00:19:49,840 Speaker 2: out to bloombost Tom Metcalfe, who's been following the company. 403 00:19:50,240 --> 00:19:53,600 Speaker 2: So this is like some financial engineering, like different valuations 404 00:19:53,600 --> 00:19:56,560 Speaker 2: on different transactions. But there is one big point here, 405 00:19:56,560 --> 00:19:58,560 Speaker 2: which is that Revolute wants to stay private. 406 00:19:58,720 --> 00:20:03,880 Speaker 11: Why yeah, exactly exactly that it's the age old story 407 00:20:03,960 --> 00:20:05,520 Speaker 11: of you know, get you get a little bit more 408 00:20:05,560 --> 00:20:08,560 Speaker 11: flexibility as a private company, and if you can put 409 00:20:08,560 --> 00:20:10,960 Speaker 11: off quite a tricky task of keeping those investors happy 410 00:20:11,040 --> 00:20:14,320 Speaker 11: your employees happy as well, then you're able to I think, 411 00:20:14,359 --> 00:20:16,880 Speaker 11: do you get a competitive of entries against any public peers. 412 00:20:17,920 --> 00:20:19,879 Speaker 11: You know, it's very few sort of startups that can 413 00:20:19,960 --> 00:20:22,040 Speaker 11: do this. They always grab the attention. But you know, 414 00:20:22,080 --> 00:20:24,560 Speaker 11: it's that blend valuation that's really interesting. There is a 415 00:20:24,560 --> 00:20:26,959 Speaker 11: little bit of kind of give and take here, like 416 00:20:27,119 --> 00:20:29,400 Speaker 11: on the primary they again given out a lower evaluation, 417 00:20:29,880 --> 00:20:32,720 Speaker 11: employees get a pretty decent one, and then they actually 418 00:20:32,720 --> 00:20:35,399 Speaker 11: are buying back some shares from a very select class 419 00:20:35,400 --> 00:20:37,720 Speaker 11: of investors at a different valuation as well, and. 420 00:20:37,720 --> 00:20:39,400 Speaker 4: A forty five billion dollar valuation. 421 00:20:39,560 --> 00:20:41,719 Speaker 5: But that's probably a lot of upside if you've been 422 00:20:41,760 --> 00:20:45,320 Speaker 5: a very early investor. But more broadly, I mean you 423 00:20:45,440 --> 00:20:49,640 Speaker 5: cover the billionaires here, right, the CEO really does seem 424 00:20:49,640 --> 00:20:51,920 Speaker 5: to be up there in terms of his own valuation 425 00:20:52,040 --> 00:20:52,800 Speaker 5: as a billionaire. 426 00:20:52,800 --> 00:20:55,040 Speaker 4: Now, yeah, exactly. 427 00:20:55,080 --> 00:20:57,679 Speaker 11: I mean I remember, gosh's been years now since been 428 00:20:57,680 --> 00:21:00,480 Speaker 11: tracking these folks, and you know, when Stronsky came out, 429 00:21:00,520 --> 00:21:03,200 Speaker 11: you've seen Revolute go through a whole range of valuations. 430 00:21:03,240 --> 00:21:05,520 Speaker 11: But unlike Klana, which is sort of the earlier of 431 00:21:05,520 --> 00:21:07,920 Speaker 11: hearing startup, I always kind of compare it with those 432 00:21:07,920 --> 00:21:10,320 Speaker 11: paper valuations. It should be clear they're on paper, so 433 00:21:10,760 --> 00:21:13,040 Speaker 11: you know, until that crystallizes, it's a long way off, 434 00:21:13,080 --> 00:21:15,240 Speaker 11: like kind of money in the bank, I suppose. But 435 00:21:15,280 --> 00:21:17,920 Speaker 11: whereas Clara had a very much roller coaster riders now 436 00:21:17,960 --> 00:21:20,600 Speaker 11: just about to IPO, Revolute always seem to be in 437 00:21:20,640 --> 00:21:22,679 Speaker 11: a position where it could pick and choose when it 438 00:21:22,680 --> 00:21:24,639 Speaker 11: could go out for new money. So its valuation has 439 00:21:24,720 --> 00:21:27,880 Speaker 11: very much been steady or in recent years or even 440 00:21:27,920 --> 00:21:30,640 Speaker 11: months as jump. So it was thirty three billion, then 441 00:21:30,680 --> 00:21:33,640 Speaker 11: forty five, that's hits sixty five and now seventy five. 442 00:21:33,680 --> 00:21:35,280 Speaker 11: But that's on a second evaluation. 443 00:21:35,320 --> 00:21:38,800 Speaker 5: Of course, next Toron Sky two hundred and first richest person. 444 00:21:38,920 --> 00:21:41,520 Speaker 5: If you're basing it on that seventy five billion dollar valuation, 445 00:21:41,880 --> 00:21:50,480 Speaker 5: Bloomberg's Tom Metcalf brilliant to have you, Thank you, Welcome. 446 00:21:50,119 --> 00:21:51,000 Speaker 4: Back to Bloomberg Tech. 447 00:21:51,080 --> 00:21:53,520 Speaker 5: Let's get straight to earnings now, because shares of HPE 448 00:21:53,640 --> 00:21:56,920 Speaker 5: they are training higher throughout this morning. The company reporting 449 00:21:57,040 --> 00:22:00,440 Speaker 5: fiscal third quarter earnings that did show operating margin and 450 00:22:00,520 --> 00:22:02,920 Speaker 5: the serving unit had narrowed, but the CEO Antonio and 451 00:22:03,000 --> 00:22:05,119 Speaker 5: Arry on the call telling investors, look, it's going to 452 00:22:05,119 --> 00:22:07,280 Speaker 5: return to roughly ten percent by the end of the 453 00:22:07,320 --> 00:22:09,680 Speaker 5: current period. Well, now we've got him here to explain 454 00:22:09,720 --> 00:22:12,600 Speaker 5: a little bit more. HPE CEO Antonio n Airy. We 455 00:22:12,840 --> 00:22:15,000 Speaker 5: get into how you're building out this business, how Juniper 456 00:22:15,040 --> 00:22:18,000 Speaker 5: adds to the networking side, but for now, the AI systems, 457 00:22:18,080 --> 00:22:21,360 Speaker 5: the server unit, how is profitability to improve? 458 00:22:22,800 --> 00:22:25,639 Speaker 13: Well, good morning, Caareran thanks for having me. We are 459 00:22:25,720 --> 00:22:28,960 Speaker 13: very pleased with our quarter. It turned out to be 460 00:22:29,160 --> 00:22:33,119 Speaker 13: very solid with record breaking performance on revenue and we 461 00:22:33,200 --> 00:22:37,280 Speaker 13: expand the profitability sequentially. And to your question around the 462 00:22:37,320 --> 00:22:40,480 Speaker 13: server segment, we deliver what we say we will do. 463 00:22:40,960 --> 00:22:44,320 Speaker 13: But most importantly, our traditional server business return it to 464 00:22:44,320 --> 00:22:47,960 Speaker 13: a historical level. And so when I think about you four, 465 00:22:48,600 --> 00:22:52,040 Speaker 13: we're going to see a return to approximately ten percent 466 00:22:52,119 --> 00:22:55,320 Speaker 13: for the quarter because of the momentum in traditional servers, 467 00:22:55,560 --> 00:22:57,760 Speaker 13: which by the way, group double digits here over here, 468 00:22:58,119 --> 00:23:01,639 Speaker 13: and the balance of AI mix between sovere and an 469 00:23:01,720 --> 00:23:05,200 Speaker 13: enterprise which now represents more than fifty percent of our 470 00:23:05,359 --> 00:23:07,600 Speaker 13: orders compared to the service providers. 471 00:23:08,440 --> 00:23:11,439 Speaker 4: So the AI serve a bit is that to improve? 472 00:23:11,480 --> 00:23:15,480 Speaker 5: How well broadly is the AI system's profitability improving as 473 00:23:15,480 --> 00:23:18,480 Speaker 5: we see this monumental buildout of infrastructure. 474 00:23:20,000 --> 00:23:22,400 Speaker 13: Well, as I think about the AI servers, I think 475 00:23:22,400 --> 00:23:26,200 Speaker 13: it's important character to think about different customer types and 476 00:23:26,240 --> 00:23:29,840 Speaker 13: how we participate in each of the segments. So we 477 00:23:29,840 --> 00:23:32,720 Speaker 13: think about the service providers and the hyper scales and 478 00:23:32,720 --> 00:23:35,680 Speaker 13: the mother buildings where a lot of the capital expenses 479 00:23:35,960 --> 00:23:39,000 Speaker 13: are taking place. To your point, we are now going 480 00:23:39,040 --> 00:23:42,479 Speaker 13: to lead. We're networking for AI. We are extremely pleased 481 00:23:42,520 --> 00:23:46,520 Speaker 13: we close the Juniper transaction. Junior is already a reference 482 00:23:46,600 --> 00:23:49,600 Speaker 13: in many of those buildouts, and that's where how we're 483 00:23:49,600 --> 00:23:52,120 Speaker 13: going to lead in that particular segment of the market. 484 00:23:52,359 --> 00:23:55,960 Speaker 13: And we're going to sell the server compute platforms whether 485 00:23:55,960 --> 00:23:59,000 Speaker 13: our partner where it makes sense from a profitability perspective. 486 00:23:59,240 --> 00:24:01,919 Speaker 13: But what we saw in the last couple of quarters 487 00:24:01,920 --> 00:24:06,400 Speaker 13: in particular discorder, sovereign and neoclouds and enterprise now represent 488 00:24:06,480 --> 00:24:09,880 Speaker 13: more than sixty percent of the market. There, we participate 489 00:24:09,960 --> 00:24:13,600 Speaker 13: in a slightly different approach which the market profile is different. 490 00:24:13,920 --> 00:24:16,520 Speaker 13: We lead with a rack scale integrated architecture for the 491 00:24:16,560 --> 00:24:20,080 Speaker 13: sovereign space, and we lead with an integrated solution for 492 00:24:20,280 --> 00:24:26,000 Speaker 13: enterprise Enterprise group for the seventh Conservative quarder and we 493 00:24:26,119 --> 00:24:28,679 Speaker 13: double the number of logos. And then in sovereign we 494 00:24:28,760 --> 00:24:30,959 Speaker 13: grew more than two hundred and fifty percent. And we 495 00:24:31,000 --> 00:24:32,960 Speaker 13: want some marquee deals in the Middle. 496 00:24:32,680 --> 00:24:36,479 Speaker 2: East, Antonio, that might be the answer. Actually, I've studied 497 00:24:36,480 --> 00:24:40,120 Speaker 2: the traditional server business and the storage business, and you're 498 00:24:40,119 --> 00:24:44,760 Speaker 2: doing better than your peers Dell net app. But why 499 00:24:44,800 --> 00:24:47,960 Speaker 2: are the dynamics better for you when you have these 500 00:24:48,000 --> 00:24:51,520 Speaker 2: analogous businesses with those other names I mentioned. 501 00:24:52,920 --> 00:24:59,320 Speaker 13: Is multiple things. First, in the enterprise traditional server, we 502 00:24:59,440 --> 00:25:04,439 Speaker 13: see a refreshed cycle taking place or age infrastructure with 503 00:25:04,560 --> 00:25:08,840 Speaker 13: more richly configured servers. And we have two phenomenal platforms 504 00:25:09,080 --> 00:25:12,000 Speaker 13: which is HP pro I and Jene eleven and Gene twelve. 505 00:25:12,520 --> 00:25:16,440 Speaker 13: We did a fantastic job in really hitting the sweet 506 00:25:16,480 --> 00:25:20,560 Speaker 13: spot to the market with better performance per core, lower 507 00:25:20,760 --> 00:25:25,240 Speaker 13: energy consumption, better security, quantum proof for the maother and 508 00:25:25,640 --> 00:25:29,439 Speaker 13: two worldad optimization. And so now as we go to 509 00:25:29,480 --> 00:25:33,159 Speaker 13: the June twelve that AUP continues to growth and the 510 00:25:33,200 --> 00:25:38,240 Speaker 13: ability to attach services is much higher. As I go 511 00:25:38,400 --> 00:25:42,520 Speaker 13: to the storage business, we really transform the entire industry 512 00:25:42,520 --> 00:25:46,560 Speaker 13: in my mind by deploying a consistent architecture, whether it 513 00:25:46,640 --> 00:25:50,280 Speaker 13: is structural data block storage, or whether it is obstructural 514 00:25:50,359 --> 00:25:54,159 Speaker 13: data which you need for AI. And that's what we 515 00:25:54,240 --> 00:25:57,480 Speaker 13: call the object data with file ingestion, so the customer 516 00:25:57,520 --> 00:26:01,200 Speaker 13: can do one one investment with a peace of mind 517 00:26:01,359 --> 00:26:04,879 Speaker 13: as they grow their data needs for AI. So I 518 00:26:04,920 --> 00:26:08,159 Speaker 13: think that's what's resonating in the market. But often we 519 00:26:08,200 --> 00:26:10,840 Speaker 13: have a fantastic go to market. We play in one 520 00:26:10,920 --> 00:26:13,400 Speaker 13: hundred and seventy two countries and that reach together whether 521 00:26:13,480 --> 00:26:16,440 Speaker 13: partner is a major differentiation. In addition to the fact 522 00:26:16,440 --> 00:26:19,720 Speaker 13: that Green Lake provides through AI dream and life cycle 523 00:26:19,800 --> 00:26:21,920 Speaker 13: management serpability. 524 00:26:22,320 --> 00:26:25,359 Speaker 2: Those are the things specific to you, Antony, Would you 525 00:26:25,359 --> 00:26:31,200 Speaker 2: give me an outlook for enterprise IT spending and because 526 00:26:31,240 --> 00:26:33,399 Speaker 2: we have a lot of macro uncertainty right now, and 527 00:26:33,440 --> 00:26:37,640 Speaker 2: you must see in the pipeline that how that uncertainty 528 00:26:37,800 --> 00:26:39,160 Speaker 2: is really manifesting. 529 00:26:40,960 --> 00:26:44,600 Speaker 13: I was based on our pipeline. First of all, is 530 00:26:44,680 --> 00:26:48,720 Speaker 13: solid across the three segments we participate in networking, server, 531 00:26:48,920 --> 00:26:53,360 Speaker 13: and hybrid cloud. It is uniform across the three geos. 532 00:26:54,520 --> 00:26:57,359 Speaker 13: There was another question in another interview, did how North 533 00:26:57,359 --> 00:27:01,040 Speaker 13: America versus oldiers are doing North America very very well 534 00:27:01,080 --> 00:27:05,040 Speaker 13: for us this quarter? And so I think the demand 535 00:27:05,160 --> 00:27:09,040 Speaker 13: will continue to be there. Every enterprise have to modernize 536 00:27:09,400 --> 00:27:12,440 Speaker 13: and deploy AI. We as a company are deploy AI 537 00:27:12,840 --> 00:27:17,160 Speaker 13: very extensively. We see the productivity improvements across many functions 538 00:27:17,160 --> 00:27:20,600 Speaker 13: and many businesses, so that will continue. But at the 539 00:27:20,600 --> 00:27:23,840 Speaker 13: same time, there is a way to modernize the legacy 540 00:27:24,119 --> 00:27:26,639 Speaker 13: by freeing up space, power and cooling so you can 541 00:27:26,680 --> 00:27:30,520 Speaker 13: deploy this new technology. So we are very confident about 542 00:27:30,560 --> 00:27:34,600 Speaker 13: the outlook, and with Juniper, that outlook becomes even stronger 543 00:27:35,000 --> 00:27:38,840 Speaker 13: because now we have a complete portfolio networking that makes 544 00:27:38,960 --> 00:27:41,440 Speaker 13: us unique as we want to build the best networking 545 00:27:41,480 --> 00:27:45,960 Speaker 13: business in a modern, secure, cloud, native and AI driven portfolio. 546 00:27:46,160 --> 00:27:48,120 Speaker 4: And you're expecting to cut costs. 547 00:27:48,240 --> 00:27:50,400 Speaker 5: I think we're seeing six hundred million dollars in cost 548 00:27:50,400 --> 00:27:53,639 Speaker 5: savings are expected by that combination, Antonio. Cost savings are 549 00:27:53,640 --> 00:27:56,000 Speaker 5: necessary for many businesses right now as you think about 550 00:27:56,040 --> 00:27:59,240 Speaker 5: some of the pressure from tariffs, your bird's eye perspective 551 00:27:59,280 --> 00:28:03,200 Speaker 5: on how much that's implicating your business right now. 552 00:28:04,119 --> 00:28:07,400 Speaker 13: You have to have a mindset of continuously transform the company. 553 00:28:07,680 --> 00:28:10,879 Speaker 13: That's a fact, and you know the future belongs to 554 00:28:10,920 --> 00:28:14,920 Speaker 13: the fastest said all the time. But the at least 555 00:28:14,960 --> 00:28:18,520 Speaker 13: six hundred million dollars in synergies is related just to 556 00:28:18,560 --> 00:28:24,280 Speaker 13: the Juniper transaction, and are re iterated that yesterday and 557 00:28:24,320 --> 00:28:26,879 Speaker 13: then there is an incremental three hundred and fifty million 558 00:28:26,920 --> 00:28:31,760 Speaker 13: dollars through three key strategic levers. Continue to optimize our portfolio, 559 00:28:32,400 --> 00:28:36,600 Speaker 13: continue to optimize the workforce, and aggressively deploy this set 560 00:28:36,640 --> 00:28:40,040 Speaker 13: of technologies and other core is not just a cost 561 00:28:40,080 --> 00:28:43,280 Speaker 13: take out, is a way to improve the experiences and 562 00:28:43,360 --> 00:28:47,160 Speaker 13: become more efficient and agile in this market which you 563 00:28:47,240 --> 00:28:50,120 Speaker 13: have to react and in the moment. So we are 564 00:28:50,200 --> 00:28:52,760 Speaker 13: very encouraged about what we're seeing and Juniper actually give 565 00:28:52,800 --> 00:28:55,640 Speaker 13: us the opportunity to rethink some of the processes we 566 00:28:55,720 --> 00:28:56,880 Speaker 13: have had for a long time. 567 00:28:56,920 --> 00:29:01,440 Speaker 2: Here, Antonio, I ask you this every Coquo house the 568 00:29:01,480 --> 00:29:05,160 Speaker 2: relationship in partnership within video, but is Jensen one would 569 00:29:05,200 --> 00:29:08,760 Speaker 2: see it right for the supply chain and the partners 570 00:29:09,240 --> 00:29:13,479 Speaker 2: they give great visibility to future iterations product right. They 571 00:29:13,520 --> 00:29:17,040 Speaker 2: commit to the annual cadence of new GPU. They're increasingly 572 00:29:17,080 --> 00:29:21,760 Speaker 2: involved in the networking through mv link. Is anything changing 573 00:29:22,040 --> 00:29:25,600 Speaker 2: for you because of the way that video operates generationally 574 00:29:25,720 --> 00:29:28,040 Speaker 2: technology to technology every year. 575 00:29:30,240 --> 00:29:34,520 Speaker 13: We have a fantastic strong partnership at the company level 576 00:29:34,600 --> 00:29:39,680 Speaker 13: and at the personal level. Jensen is available in the moment. 577 00:29:39,920 --> 00:29:42,160 Speaker 13: If I need something, he picks the phone and we 578 00:29:42,360 --> 00:29:45,200 Speaker 13: chat that we solve it. But I will say the following. 579 00:29:45,360 --> 00:29:51,120 Speaker 13: I think from a collaboration perspective, from a core engineering perspective. 580 00:29:51,600 --> 00:29:54,360 Speaker 13: The proof of that is our AI factor for enterprise 581 00:29:54,440 --> 00:29:57,800 Speaker 13: with our private CLOUDI we actually took a very different 582 00:29:57,840 --> 00:30:02,560 Speaker 13: approach together with a video we integrated entire Nvidia AI 583 00:30:02,720 --> 00:30:06,320 Speaker 13: suite of software inside our green lay cloud. We took 584 00:30:06,360 --> 00:30:10,400 Speaker 13: a software down into infrastructure and together we provide an 585 00:30:10,400 --> 00:30:15,440 Speaker 13: integrated solution for our enterprise customers. That's a testament how 586 00:30:15,480 --> 00:30:18,120 Speaker 13: you co engineer despite the fact a lot of the 587 00:30:18,200 --> 00:30:21,800 Speaker 13: value is on the GPU, but reality is the software 588 00:30:21,880 --> 00:30:24,560 Speaker 13: and the experience that you deliver. On the other hand, 589 00:30:24,600 --> 00:30:28,840 Speaker 13: now with networking, we have another set of opportunities because 590 00:30:29,040 --> 00:30:32,400 Speaker 13: above the MVY link and the spectrum as you refer to, 591 00:30:32,920 --> 00:30:36,760 Speaker 13: you need a full data center architecture. Nvidia does not 592 00:30:36,880 --> 00:30:41,440 Speaker 13: participate into that. Our major competitors obviously our Cisco and Arista, 593 00:30:41,600 --> 00:30:44,240 Speaker 13: but Juriper has become the reference for many of these 594 00:30:44,320 --> 00:30:47,440 Speaker 13: large AI deployments. But I do believe together with the 595 00:30:47,480 --> 00:30:49,440 Speaker 13: Nvidia we can do a better job in a way. 596 00:30:49,480 --> 00:30:53,240 Speaker 13: We deploy that copex and we run that infrastructure from 597 00:30:53,280 --> 00:30:57,520 Speaker 13: an opex perspective using AI technologies for that matter, in 598 00:30:57,600 --> 00:31:01,080 Speaker 13: full manage the network. So we are very excited about that. 599 00:31:01,560 --> 00:31:03,600 Speaker 13: And look, you know in the last ward that we 600 00:31:03,600 --> 00:31:07,480 Speaker 13: announced new innovation together with Nvidia, the RTX six thousand pro, 601 00:31:07,680 --> 00:31:12,000 Speaker 13: the latest Ultra you know Blackwell, we are committed to 602 00:31:12,000 --> 00:31:14,720 Speaker 13: be time to market with Jensen and team. 603 00:31:15,600 --> 00:31:18,640 Speaker 5: I'm interested by the adoption and generative AI by the 604 00:31:18,680 --> 00:31:21,280 Speaker 5: companies that are helping them become a reality. Of course, 605 00:31:21,440 --> 00:31:24,600 Speaker 5: benefits your share price, which is near a record high, Antonio, 606 00:31:24,640 --> 00:31:27,280 Speaker 5: But how is it benefiting your employees or indeed, how 607 00:31:27,280 --> 00:31:28,800 Speaker 5: are the pilot's runn because there's been a lot of 608 00:31:28,880 --> 00:31:32,360 Speaker 5: questions about whether there's been efficacy there since the MIT report. 609 00:31:33,760 --> 00:31:36,480 Speaker 13: Yeah, I think it's fair to say, Carol, we went 610 00:31:36,520 --> 00:31:40,120 Speaker 13: from generative AI to agentic AI, and I think about, 611 00:31:40,880 --> 00:31:43,560 Speaker 13: you know, agentic KI as the next evolution for what 612 00:31:43,760 --> 00:31:47,800 Speaker 13: really enterprise needed. And my view is that AGENTAKI will 613 00:31:47,840 --> 00:31:52,520 Speaker 13: transform business processes by simplifying them, automating them and then 614 00:31:52,600 --> 00:31:56,320 Speaker 13: bring intelligence to it. In our company, we are using 615 00:31:56,360 --> 00:32:00,000 Speaker 13: agentic ai aggressively in our offers. So Green Lake Intelligence, 616 00:32:00,480 --> 00:32:03,880 Speaker 13: which we announce it June, is one of the most 617 00:32:03,880 --> 00:32:08,400 Speaker 13: comprehensive clouds that includes a gent ki no reserveability in 618 00:32:08,400 --> 00:32:12,239 Speaker 13: the way deploy and manage infrastructure and so forth. On 619 00:32:12,280 --> 00:32:15,120 Speaker 13: the other hand, as a company, we have deploying agentki 620 00:32:15,240 --> 00:32:19,640 Speaker 13: across finance. Our CFO is incredibly aggressive on this, so 621 00:32:19,680 --> 00:32:23,040 Speaker 13: she is on the leading edge on this. Our marketing 622 00:32:23,080 --> 00:32:27,520 Speaker 13: team uses for demand generation and the brand capaigns and 623 00:32:27,640 --> 00:32:31,440 Speaker 13: targeting segments where it makes sense, and our services team 624 00:32:31,640 --> 00:32:35,800 Speaker 13: is used to provide better support experiences in our supply chain. 625 00:32:35,840 --> 00:32:38,680 Speaker 13: We use it for forecasting and planning, and there is 626 00:32:38,760 --> 00:32:42,120 Speaker 13: many other examples of that, and so I think this 627 00:32:42,400 --> 00:32:46,160 Speaker 13: generative I now became agent KI. In the future, of 628 00:32:46,160 --> 00:32:50,200 Speaker 13: course will be the robotics part, but the productivity level 629 00:32:50,240 --> 00:32:52,160 Speaker 13: we see in is pretty significant and we are not 630 00:32:52,480 --> 00:32:54,920 Speaker 13: put of a concept. We have deployed more than sixty 631 00:32:55,320 --> 00:32:57,840 Speaker 13: use cases across the company and we have more than 632 00:32:57,880 --> 00:33:01,720 Speaker 13: two hundred in testing as we speak. Some will fail, 633 00:33:01,760 --> 00:33:04,560 Speaker 13: Carol run, and that's fine, and the mentality there needs 634 00:33:04,600 --> 00:33:07,200 Speaker 13: to be fell fast and improved and focus on our 635 00:33:07,240 --> 00:33:08,520 Speaker 13: return and investor capital. 636 00:33:09,880 --> 00:33:13,800 Speaker 2: Antonio, you've been CEO since the start of twenty eighteen. 637 00:33:14,760 --> 00:33:19,200 Speaker 2: Where does HPE sit today relative to your big vision 638 00:33:19,280 --> 00:33:24,240 Speaker 2: for what HPE is can or should be against your peers. 639 00:33:25,880 --> 00:33:28,520 Speaker 13: When I became CEO, I had a vision to be 640 00:33:28,800 --> 00:33:32,880 Speaker 13: an edge centric, cloud level and data driven company. We 641 00:33:32,920 --> 00:33:36,880 Speaker 13: invested at the edge was the Ruba acquisition, and we 642 00:33:36,960 --> 00:33:39,800 Speaker 13: delivered tremendous value for our shoholders from seven hundred and 643 00:33:39,800 --> 00:33:42,880 Speaker 13: fifty million dollar revenue all the way to over five billion, 644 00:33:43,280 --> 00:33:45,600 Speaker 13: and obviously now the next move was the acquisition of 645 00:33:45,720 --> 00:33:50,640 Speaker 13: Juniper to make this company a networking centric company because 646 00:33:50,720 --> 00:33:53,760 Speaker 13: I believe the next AI era here is the convergence 647 00:33:53,800 --> 00:33:59,320 Speaker 13: of networking cloud and then obviously the business process that 648 00:33:59,360 --> 00:34:02,720 Speaker 13: we will run as an enterprise, and that to me 649 00:34:02,880 --> 00:34:05,920 Speaker 13: is the core foundation that have been envisioned for our 650 00:34:06,000 --> 00:34:09,200 Speaker 13: company going forward, and on that core foundation we deliver 651 00:34:09,320 --> 00:34:13,279 Speaker 13: the best cloud and AI experiences. So is continue to 652 00:34:13,280 --> 00:34:16,280 Speaker 13: be shaped. I'm very pleased with the progress, but let's 653 00:34:16,280 --> 00:34:19,520 Speaker 13: not forget it's not just the division itself. It's how 654 00:34:19,600 --> 00:34:22,480 Speaker 13: you execute with the culture and a set of values 655 00:34:22,520 --> 00:34:25,719 Speaker 13: that makes us unique. And HP has been recognized also 656 00:34:25,719 --> 00:34:27,759 Speaker 13: along the way as one of the best places to 657 00:34:27,880 --> 00:34:34,520 Speaker 13: come and work by many surveys and magazines and institutions. 658 00:34:34,560 --> 00:34:37,760 Speaker 13: So my view is that we are shaping the future, 659 00:34:37,840 --> 00:34:41,239 Speaker 13: but ultimately is about delivering Shopholder value and we are 660 00:34:41,320 --> 00:34:43,239 Speaker 13: going to be positioned for the next three year to 661 00:34:43,320 --> 00:34:46,399 Speaker 13: accelerate that value as you see today because our stock 662 00:34:46,480 --> 00:34:50,680 Speaker 13: price still undervalue in terms of multiples. Our goal is 663 00:34:50,719 --> 00:34:54,719 Speaker 13: to deliver that value accelerator for our shareholders and be 664 00:34:54,920 --> 00:34:58,320 Speaker 13: relevant to our customers in this new environment we live. 665 00:34:58,200 --> 00:35:00,919 Speaker 2: In, I should have disasked you if your stock price 666 00:35:00,960 --> 00:35:04,960 Speaker 2: was undervalued. Antonio Anderi, President and CEO of HP. Will 667 00:35:05,040 --> 00:35:07,360 Speaker 2: leave it there, but a really robust conversation, thank you 668 00:35:07,440 --> 00:35:10,520 Speaker 2: very much. Coming up, tech leaders are set to gather 669 00:35:10,800 --> 00:35:15,400 Speaker 2: a President Trump's brand new Rose Garden for a discussion 670 00:35:15,440 --> 00:35:17,400 Speaker 2: about AI. We're gonna have more on that next. This 671 00:35:17,440 --> 00:35:31,080 Speaker 2: is Bloomberg Tech, President. 672 00:35:30,640 --> 00:35:32,680 Speaker 5: Trump and the First Lady. Well, they're set to host 673 00:35:32,680 --> 00:35:34,280 Speaker 5: a group of tech leaders. 674 00:35:34,080 --> 00:35:35,960 Speaker 4: And the newly renovated Rose Garden. 675 00:35:36,160 --> 00:35:39,840 Speaker 5: Those joining include Mark Zuckerberg, Tim Cook, Satia Nadella for 676 00:35:39,880 --> 00:35:44,000 Speaker 5: an event on AI education Bloemos Katherine Lucy joins us. 677 00:35:44,040 --> 00:35:47,720 Speaker 5: Now this really is a powerful Rose Garden meeting. 678 00:35:49,520 --> 00:35:52,160 Speaker 10: Yeah, it's quite a lineup, right. A lot of bald 679 00:35:52,160 --> 00:35:56,200 Speaker 10: faced names are expected, both for a event with the 680 00:35:56,360 --> 00:35:58,799 Speaker 10: as you said, with the First Lady around AI and 681 00:35:59,440 --> 00:36:04,120 Speaker 10: AI and children, but also for a reception the President 682 00:36:04,239 --> 00:36:08,960 Speaker 10: is hosting on the newly repaved Rose Garden, which he 683 00:36:09,000 --> 00:36:11,160 Speaker 10: has made clear he wants to use more as a 684 00:36:11,200 --> 00:36:13,280 Speaker 10: space to host gatherings at the White House. 685 00:36:14,520 --> 00:36:16,840 Speaker 2: Catherine, I went to d C for the Winning the 686 00:36:16,920 --> 00:36:20,200 Speaker 2: AI Race speech. The President made. So while this is, 687 00:36:20,280 --> 00:36:22,279 Speaker 2: you know, it's a nice thing with the CEOs, go 688 00:36:22,840 --> 00:36:26,080 Speaker 2: at the heart of it, what is this administration's attitude 689 00:36:26,080 --> 00:36:28,000 Speaker 2: to AI. I feel like there has been a lot 690 00:36:28,000 --> 00:36:31,319 Speaker 2: of traffic of leaders from California Silicon Valley going to 691 00:36:31,360 --> 00:36:33,840 Speaker 2: the White House to discuss that issue. 692 00:36:35,160 --> 00:36:37,520 Speaker 10: Yeah, the President and his ministers have been very clear 693 00:36:37,560 --> 00:36:40,440 Speaker 10: they are intered investing in AI. They have put a 694 00:36:40,480 --> 00:36:44,440 Speaker 10: big action plan around AI. They have had a lot 695 00:36:44,480 --> 00:36:47,200 Speaker 10: of tech CEOs in not US today obviously, but throughout 696 00:36:48,239 --> 00:36:53,200 Speaker 10: this year as they look for ways to invest in manufacturing, 697 00:36:53,360 --> 00:36:57,839 Speaker 10: to invest in domestic production, to support tech centers. They've 698 00:36:57,840 --> 00:37:02,120 Speaker 10: also been closely aligned with chip manufacturers. So there's been 699 00:37:02,280 --> 00:37:04,719 Speaker 10: a lot of activity in this space throughout the year. 700 00:37:05,800 --> 00:37:08,879 Speaker 2: Bloomberg's Caafine Lucy with the reporting. Thank you very much. 701 00:37:08,960 --> 00:37:11,080 Speaker 2: Let's stick with recent news from the Trump administration. The 702 00:37:11,120 --> 00:37:15,040 Speaker 2: president has torn up a Biden era compromise that allowed 703 00:37:15,040 --> 00:37:18,560 Speaker 2: some of the world's biggest chip makers to maintain operations 704 00:37:18,560 --> 00:37:21,320 Speaker 2: in China. I want to get out to Bloomberg's senior editor, 705 00:37:21,719 --> 00:37:26,879 Speaker 2: Mike Shephard. We're talking about validated end user authorizations or VEUS, 706 00:37:27,040 --> 00:37:31,839 Speaker 2: and there's been this pipeline of breaking news announcements around it. 707 00:37:32,239 --> 00:37:34,200 Speaker 2: There's a little bit of pressure on the chip stocks. 708 00:37:34,239 --> 00:37:36,640 Speaker 2: Why are we focused on what the president's doing in 709 00:37:36,680 --> 00:37:37,200 Speaker 2: this domain? 710 00:37:38,600 --> 00:37:42,160 Speaker 9: Well, this ends this so called blanket waiver that had 711 00:37:42,160 --> 00:37:47,560 Speaker 9: allowed the company's Samsung sk Heinex in TSMC to avoid 712 00:37:47,640 --> 00:37:52,240 Speaker 9: becoming collateral damage ed in the US effort to reign 713 00:37:52,360 --> 00:37:57,640 Speaker 9: in China's artificial intelligence ambitions, and that efforts included imposing 714 00:37:57,680 --> 00:38:01,200 Speaker 9: export restrictions not only in US com companies, but also 715 00:38:01,480 --> 00:38:05,200 Speaker 9: on businesses in Europe and elsewhere that supplied those makers 716 00:38:05,239 --> 00:38:10,439 Speaker 9: with facilities in China. Samsung and sk Heinex are South 717 00:38:10,480 --> 00:38:14,640 Speaker 9: Korean companies and they do have facilities in China, and 718 00:38:14,840 --> 00:38:19,200 Speaker 9: even though they are not Chinese flagged, they were nonetheless 719 00:38:19,520 --> 00:38:23,960 Speaker 9: targeted by potentially these export restrictions. So the waivers were 720 00:38:24,000 --> 00:38:27,759 Speaker 9: designed to spare them from feeling the brunt of it, 721 00:38:27,840 --> 00:38:34,040 Speaker 9: and it would allow them to ship in semiconductor manufacturing equipment, materials, chemicals, 722 00:38:34,040 --> 00:38:36,640 Speaker 9: and things needed to keep those plants running. And it 723 00:38:36,680 --> 00:38:40,480 Speaker 9: was really critical for Samsung and Skhinis to have that 724 00:38:40,600 --> 00:38:44,320 Speaker 9: ability to not have to go to the US government 725 00:38:44,400 --> 00:38:47,560 Speaker 9: for permission every single time they needed to make a shipment. 726 00:38:47,800 --> 00:38:50,319 Speaker 9: It allowed them to keep those facilities running, and it 727 00:38:50,320 --> 00:38:53,680 Speaker 9: has become a complication for them and for their suppliers too. 728 00:38:53,760 --> 00:38:57,359 Speaker 5: Kara, I mean what a labor impact is going to have. 729 00:38:57,640 --> 00:39:00,000 Speaker 5: I mean, we see the US government trying to brush 730 00:39:00,040 --> 00:39:01,719 Speaker 5: it off. It's going to be easy to facilitate. 731 00:39:02,239 --> 00:39:05,120 Speaker 4: But remind us of why the current. 732 00:39:04,920 --> 00:39:07,799 Speaker 5: Administration was so worried about this particular loophole as they 733 00:39:07,800 --> 00:39:08,160 Speaker 5: call it. 734 00:39:09,480 --> 00:39:11,799 Speaker 9: Well, you know, Caro, I mentioned data leakage, and that, 735 00:39:11,880 --> 00:39:15,600 Speaker 9: of course, you know, the idea that tech from these 736 00:39:15,640 --> 00:39:19,360 Speaker 9: factories could somehow leak into the Chinese market, and that 737 00:39:19,480 --> 00:39:23,080 Speaker 9: China would be able to somehow copy or mimic or 738 00:39:23,280 --> 00:39:27,040 Speaker 9: use this technology in some fashion, or these materials in 739 00:39:27,040 --> 00:39:29,800 Speaker 9: some fashion learning they know how. But there is also 740 00:39:29,920 --> 00:39:33,480 Speaker 9: another factor. We're seeing more than just South Korea and 741 00:39:33,520 --> 00:39:36,240 Speaker 9: Taiwan getting caught up in the tug of war between 742 00:39:36,280 --> 00:39:38,680 Speaker 9: the US and China, this is also a tug of 743 00:39:38,719 --> 00:39:43,400 Speaker 9: war with allies with South Korea and Taiwan and the 744 00:39:43,560 --> 00:39:48,360 Speaker 9: US over competition over trade. The Commerce Department made clear 745 00:39:48,400 --> 00:39:51,320 Speaker 9: that look, they see this as a question of leveling 746 00:39:51,360 --> 00:39:54,360 Speaker 9: the playing field not just with China, but with companies 747 00:39:54,520 --> 00:39:57,160 Speaker 9: from South Korea. And Taiwan. They want to make sure 748 00:39:57,200 --> 00:40:03,000 Speaker 9: that advantages given through these way are also not unfairly 749 00:40:04,680 --> 00:40:08,759 Speaker 9: putting US companies in an unfair position themselves. So this 750 00:40:08,800 --> 00:40:10,920 Speaker 9: is why the waivers have ended, and it's going to 751 00:40:10,960 --> 00:40:14,440 Speaker 9: set up four months of intense negotiations for these companies 752 00:40:14,480 --> 00:40:15,800 Speaker 9: to figure out how to proceed. 753 00:40:16,040 --> 00:40:18,839 Speaker 5: In most my Shepherd, we thank you from Washington. Now 754 00:40:18,880 --> 00:40:22,480 Speaker 5: coming up French AI firm Mistral. It's solidifying its position 755 00:40:22,520 --> 00:40:24,560 Speaker 5: as one of Europe's most valuable tech startups. 756 00:40:24,560 --> 00:40:26,400 Speaker 4: We talk about the funding that's going on now. 757 00:40:26,440 --> 00:40:40,200 Speaker 3: Discipling their tech. French AI start up Mistral is. 758 00:40:40,160 --> 00:40:42,560 Speaker 5: In talks to raise a new investment that will value 759 00:40:42,560 --> 00:40:45,560 Speaker 5: the company at fourteen billion dollars in most. Cake Clark 760 00:40:45,640 --> 00:40:48,200 Speaker 5: joins us now with the story, it's a high evaluation. 761 00:40:48,520 --> 00:40:51,840 Speaker 4: This is really the French startup, the European version of 762 00:40:51,880 --> 00:40:52,319 Speaker 4: open ai. 763 00:40:52,600 --> 00:40:53,040 Speaker 14: Exactly. 764 00:40:53,160 --> 00:40:54,879 Speaker 4: Has it got any niche a tool to compete against 765 00:40:54,920 --> 00:40:55,239 Speaker 4: the rest. 766 00:40:55,400 --> 00:40:58,000 Speaker 14: It's developing open source models, so that's one of its 767 00:40:58,040 --> 00:41:00,120 Speaker 14: that's its niece. But it's also a European company me 768 00:41:00,200 --> 00:41:03,000 Speaker 14: as you said, so perhaps people in Europe would prefer 769 00:41:03,080 --> 00:41:06,239 Speaker 14: to use a European homegrown AI company as opposed to 770 00:41:06,760 --> 00:41:07,560 Speaker 14: chat to BT. 771 00:41:07,600 --> 00:41:12,480 Speaker 2: Or Entthropics Claude, It's interesting where the capitules coming from. 772 00:41:12,760 --> 00:41:15,000 Speaker 2: It's also based on the news flow of this week. 773 00:41:15,040 --> 00:41:20,000 Speaker 2: Forteen billion dollars is modest, right, Kate, relative to Anthropic. 774 00:41:20,360 --> 00:41:22,920 Speaker 14: That's exactly right. I was thinking, Wow, this seems cheap 775 00:41:23,480 --> 00:41:26,120 Speaker 14: compared to anthropics one hundred and eighty three billion dollar 776 00:41:26,200 --> 00:41:29,319 Speaker 14: valuation and open AI's five hundred dollars billion dollar, five 777 00:41:29,400 --> 00:41:31,360 Speaker 14: hundred billion dollar valuation, and so. 778 00:41:31,360 --> 00:41:33,640 Speaker 5: Many cross over in some of them where the capital 779 00:41:33,719 --> 00:41:35,760 Speaker 5: is coming from at the moment, because we all focused 780 00:41:35,800 --> 00:41:37,840 Speaker 5: on the fat that Anthropic kind of went to the 781 00:41:37,880 --> 00:41:39,040 Speaker 5: Middle East when many thought they. 782 00:41:38,960 --> 00:41:42,480 Speaker 14: Wouldn't exactly, and we don't know who's leading this Mistral around. 783 00:41:43,160 --> 00:41:45,040 Speaker 14: I have been told it is not likely to be 784 00:41:45,080 --> 00:41:47,319 Speaker 14: a Middle East investor, but we'll see, and we're we're 785 00:41:47,360 --> 00:41:49,480 Speaker 14: doing that reporting to find out. But it does have 786 00:41:49,520 --> 00:41:52,520 Speaker 14: several US venture capital firms that are backers of Mistral, 787 00:41:52,560 --> 00:41:54,839 Speaker 14: Andries and Horowitz is one of the major investors, which 788 00:41:54,880 --> 00:41:57,920 Speaker 14: is also a firm that is invested in other US lms. 789 00:41:59,280 --> 00:42:02,040 Speaker 2: Very quick, Kate, just summarize demand. I'm seeing a lot 790 00:42:02,080 --> 00:42:06,799 Speaker 2: of newsflow, deal flow, primary secondaries, the appetite is still 791 00:42:06,840 --> 00:42:08,239 Speaker 2: there for these AI startups. 792 00:42:08,560 --> 00:42:11,680 Speaker 14: There is an incredible amount of appetite for these AI startups. 793 00:42:11,719 --> 00:42:15,319 Speaker 14: There's words cannot really even describe how much appetite there 794 00:42:15,400 --> 00:42:18,480 Speaker 14: is for an open AI and anthropic even if a stroll, 795 00:42:18,960 --> 00:42:23,440 Speaker 14: investors are extremely excited to put their money into these 796 00:42:23,520 --> 00:42:26,520 Speaker 14: large language models and into the application layer AI companies. 797 00:42:27,400 --> 00:42:30,359 Speaker 2: Bloomberg's k Clark great reporting as always, and yeah, there's 798 00:42:30,360 --> 00:42:31,560 Speaker 2: a lot going on, Carrot. 799 00:42:32,280 --> 00:42:34,719 Speaker 5: That does it for this edition of Bloomberg Tech, where 800 00:42:34,719 --> 00:42:38,799 Speaker 5: there is insatiable demand for content, whether it be on 801 00:42:38,960 --> 00:42:41,160 Speaker 5: Open ai or Mistrial and many others. 802 00:42:41,719 --> 00:42:44,160 Speaker 2: Yeah, hardware or software, we got it all. So check 803 00:42:44,200 --> 00:42:46,080 Speaker 2: out the podcast. You know where to find it on 804 00:42:46,120 --> 00:42:50,160 Speaker 2: the Bloomberg terminal as well as online on Apple, Spotify, Nihart. 805 00:42:50,640 --> 00:42:55,000 Speaker 2: From San Francisco, New York City, This is Bloomberg