1 00:00:04,080 --> 00:00:08,440 Speaker 1: Bloomberg Tech is alive from coast to coast with Caroline 2 00:00:08,520 --> 00:00:13,919 Speaker 1: Hide in New York and Eva, though in San Francisco. 3 00:00:14,920 --> 00:00:16,720 Speaker 2: This is Bloomberg Tech coming up. 4 00:00:16,760 --> 00:00:20,080 Speaker 3: Alphabet hits a record high as Google dodges the sale 5 00:00:20,120 --> 00:00:22,119 Speaker 3: of Chrome in a key antitrust ruling. 6 00:00:22,320 --> 00:00:25,320 Speaker 1: Plus Apple benefits from Google's legal win but loses out 7 00:00:25,360 --> 00:00:28,160 Speaker 1: on the AI talent wars Again. We discussed the latest 8 00:00:28,200 --> 00:00:30,360 Speaker 1: key researcher jumping to rival Meta. 9 00:00:30,960 --> 00:00:31,600 Speaker 2: And the rolls. 10 00:00:31,680 --> 00:00:35,280 Speaker 3: Royce CFO joins US stateside as the British engineering giant 11 00:00:35,520 --> 00:00:39,320 Speaker 3: goes off to AI fuel's data center demand for power tech. 12 00:00:39,760 --> 00:00:41,800 Speaker 1: But first we check in on these markets. 13 00:00:42,120 --> 00:00:43,760 Speaker 4: The power higher on the day. 14 00:00:43,840 --> 00:00:47,400 Speaker 1: Ed reprieve from yesterday's sell off as we see boniols 15 00:00:47,440 --> 00:00:49,599 Speaker 1: come back a little bit, and we focus on well, 16 00:00:49,640 --> 00:00:51,760 Speaker 1: pretty woeful data when it comes to the jobs data. 17 00:00:51,800 --> 00:00:54,000 Speaker 1: But does that mean the Fed Canandian cut. We're up 18 00:00:54,040 --> 00:00:56,560 Speaker 1: more than a percentage point, But dig into the individual 19 00:00:56,600 --> 00:00:57,480 Speaker 1: movers because they're big. 20 00:00:58,240 --> 00:00:59,960 Speaker 2: Yeah, our top story is Google. 21 00:01:00,560 --> 00:01:02,400 Speaker 3: The key headline that you need to know is that 22 00:01:02,440 --> 00:01:06,240 Speaker 3: they will not have to divest or sell Chrome. They 23 00:01:06,319 --> 00:01:10,520 Speaker 3: will be allowed to continue paying in particular Apple twenty 24 00:01:10,640 --> 00:01:14,640 Speaker 3: billion dollars per year for placement of search, but there 25 00:01:14,720 --> 00:01:17,360 Speaker 3: is a lot that they're still required to do in 26 00:01:17,400 --> 00:01:19,600 Speaker 3: the remedy section of that key and trust ruling. The 27 00:01:19,680 --> 00:01:22,480 Speaker 3: stock for Alphabet pairent of Google on track for its 28 00:01:22,480 --> 00:01:26,679 Speaker 3: biggest jump since April record high Alphabet Apple. 29 00:01:26,720 --> 00:01:29,039 Speaker 2: Is also pushing a lot high. Later in the program, going. 30 00:01:28,920 --> 00:01:31,280 Speaker 3: Too detail, let's start with a Google piece and bring 31 00:01:31,319 --> 00:01:32,959 Speaker 3: in our guest character. 32 00:01:33,080 --> 00:01:34,960 Speaker 1: Yeah, let's bring in Sarah Forden because we want to 33 00:01:35,000 --> 00:01:38,119 Speaker 1: blow by blow account about what the legal win is here. 34 00:01:38,200 --> 00:01:41,720 Speaker 1: You're in DC, our legal team leader, Sarah, just walk 35 00:01:41,800 --> 00:01:44,120 Speaker 1: us through why there seems to be such a win 36 00:01:44,200 --> 00:01:45,199 Speaker 1: for Alphabet. 37 00:01:46,040 --> 00:01:46,240 Speaker 3: Ah. 38 00:01:46,319 --> 00:01:50,560 Speaker 5: Yeah, absolutely. I mean this was a huge win because primarily, 39 00:01:50,680 --> 00:01:53,639 Speaker 5: I mean the judge in the end didn't give Google 40 00:01:53,760 --> 00:01:56,240 Speaker 5: much more than a slap on the wrist, and there 41 00:01:56,320 --> 00:01:58,400 Speaker 5: was a lot of fear and concern that this was 42 00:01:58,440 --> 00:02:02,360 Speaker 5: going to completely reshape the tech market, the search market, 43 00:02:02,560 --> 00:02:06,200 Speaker 5: and instead it's almost status quo. I mean, they don't 44 00:02:06,200 --> 00:02:09,280 Speaker 5: have to break off Chrome. They can keep paying the 45 00:02:09,360 --> 00:02:14,080 Speaker 5: money to Apple to be a deferred default search engine. 46 00:02:14,440 --> 00:02:17,400 Speaker 5: But the only caveat there was that it can't be exclusive, 47 00:02:17,520 --> 00:02:20,400 Speaker 5: so that opens up things for Apple a little bit 48 00:02:20,440 --> 00:02:23,720 Speaker 5: more and they have to do some data sharing, but 49 00:02:23,840 --> 00:02:27,760 Speaker 5: it's very limited. It's a one time shot at sharing 50 00:02:27,800 --> 00:02:31,360 Speaker 5: the data, and it's just search data, not advertising data. 51 00:02:31,440 --> 00:02:34,720 Speaker 5: So they're still looking at how that's going to work technically, 52 00:02:34,760 --> 00:02:37,160 Speaker 5: and they'll have to report back to the judge. But 53 00:02:37,600 --> 00:02:39,920 Speaker 5: at the end of the day, it's not a huge 54 00:02:40,840 --> 00:02:42,720 Speaker 5: change or a huge blow for Google. 55 00:02:43,960 --> 00:02:44,200 Speaker 2: Sarah. 56 00:02:44,280 --> 00:02:48,000 Speaker 3: Google's response and it's statement with celebratory basically, and that 57 00:02:48,160 --> 00:02:49,560 Speaker 3: largely focuses on Chrome. 58 00:02:49,600 --> 00:02:51,600 Speaker 2: They do not in the data sharing part. 59 00:02:52,000 --> 00:02:54,560 Speaker 3: Their concern is privacy because they don't want to share 60 00:02:54,680 --> 00:03:00,640 Speaker 3: data with rivals like Perplexiopenai, dot Go, etc. There's still 61 00:03:00,639 --> 00:03:04,720 Speaker 3: some mechanics here. September tenth is a key date the 62 00:03:04,760 --> 00:03:08,600 Speaker 3: parties need to write down on paper something that appeases 63 00:03:08,680 --> 00:03:11,520 Speaker 3: this judge. But in the ruling, the judge also talks 64 00:03:11,520 --> 00:03:15,959 Speaker 3: about generative AI being key to the outcome of this case. 65 00:03:16,360 --> 00:03:16,959 Speaker 2: Explain that. 66 00:03:18,200 --> 00:03:21,200 Speaker 5: Yeah, So that was very interesting because the way the 67 00:03:21,280 --> 00:03:24,840 Speaker 5: judge handled the initial trial and even the remedy portion 68 00:03:24,919 --> 00:03:27,760 Speaker 5: of the trial made a lot of people think that 69 00:03:27,840 --> 00:03:29,560 Speaker 5: he was going to be much tougher, But at the 70 00:03:29,680 --> 00:03:33,440 Speaker 5: end of the day, his ruling was very conservative and 71 00:03:33,480 --> 00:03:35,520 Speaker 5: he said the main reason was that that he said 72 00:03:35,520 --> 00:03:38,640 Speaker 5: the generative AI was really changing the shape of the market, 73 00:03:38,680 --> 00:03:40,360 Speaker 5: and he didn't want to get out ahead of that, 74 00:03:41,320 --> 00:03:43,640 Speaker 5: and he didn't want to issue ruling that was going 75 00:03:43,680 --> 00:03:48,840 Speaker 5: to really disrupt the market, change the money flows, inhibit 76 00:03:48,880 --> 00:03:50,560 Speaker 5: innovation in any way. 77 00:03:51,960 --> 00:03:54,960 Speaker 3: Bloomberg, Sarah Forden, who leads the ns trust team out 78 00:03:55,000 --> 00:03:58,160 Speaker 3: of DC and all things legal, thank you very much. 79 00:03:58,240 --> 00:04:01,480 Speaker 3: Let's talk through the market reaction. Jeffrey's analyst Brent Hill 80 00:04:01,640 --> 00:04:04,440 Speaker 3: joins US. Now the stock's up eight point six percent 81 00:04:04,560 --> 00:04:07,080 Speaker 3: record high, but that's only the biggest jump since the first. 82 00:04:06,920 --> 00:04:07,960 Speaker 2: Week of April. 83 00:04:08,240 --> 00:04:11,280 Speaker 3: Your colleagues on the street, many of them have raised 84 00:04:11,320 --> 00:04:13,880 Speaker 3: price targets or calls on the stock. 85 00:04:14,440 --> 00:04:17,480 Speaker 2: You have not in response to this ruling. 86 00:04:17,920 --> 00:04:21,600 Speaker 3: Why and what is your main takeaway from it? 87 00:04:21,640 --> 00:04:24,800 Speaker 6: So for the last ten years in tech, we maintained 88 00:04:24,839 --> 00:04:31,200 Speaker 6: that any regulatory in insertion into these stocks are really 89 00:04:31,240 --> 00:04:35,680 Speaker 6: not founded. So watching what happened to Meta was Zuckerberg 90 00:04:35,800 --> 00:04:39,480 Speaker 6: watching what happened with Microsoft. There's been no breakup ever, 91 00:04:39,960 --> 00:04:42,680 Speaker 6: and so we've always said that an illegal case like this, 92 00:04:43,279 --> 00:04:45,960 Speaker 6: that there's always a remedy, and that the companies are 93 00:04:46,040 --> 00:04:50,040 Speaker 6: too big and that the regulators want one thing and 94 00:04:50,080 --> 00:04:52,000 Speaker 6: the tech companies want one thing, and they'll find a 95 00:04:52,000 --> 00:04:54,080 Speaker 6: way to meet in the middle. They have found a 96 00:04:54,120 --> 00:04:56,640 Speaker 6: way to meet in the middle. And so our view 97 00:04:56,800 --> 00:05:00,880 Speaker 6: is that again, in any situation, you buy these stocks 98 00:05:00,920 --> 00:05:04,000 Speaker 6: on the sphere, and that worked for Microsoft and at 99 00:05:04,000 --> 00:05:06,360 Speaker 6: work now for Google, we are a one hundred percent hit rate. 100 00:05:06,480 --> 00:05:09,400 Speaker 6: This isn't the game I'm creating. This is the game 101 00:05:09,720 --> 00:05:12,279 Speaker 6: we're playing in and that's been the rule book. So 102 00:05:13,080 --> 00:05:16,680 Speaker 6: our view is like it's there's been no change. This 103 00:05:16,760 --> 00:05:20,960 Speaker 6: company's growing their EBITDA at a mid to high team 104 00:05:21,680 --> 00:05:25,360 Speaker 6: multiple and the stock train at fourteen times and it 105 00:05:25,440 --> 00:05:28,400 Speaker 6: traded it twelve times just a few months ago. So 106 00:05:28,440 --> 00:05:31,320 Speaker 6: there's really no knee jerk reaction from us because the 107 00:05:31,400 --> 00:05:33,719 Speaker 6: reaction for the last ten years has been the same 108 00:05:33,800 --> 00:05:37,440 Speaker 6: reaction and any legal case that we've had when we 109 00:05:37,480 --> 00:05:40,039 Speaker 6: talk to our clients, which is they'll figure out a 110 00:05:40,080 --> 00:05:43,480 Speaker 6: way and the inherent value is higher for what they're 111 00:05:43,520 --> 00:05:45,840 Speaker 6: doing than what the street is embedding. 112 00:05:46,000 --> 00:05:48,040 Speaker 2: Well, brands now will change. 113 00:05:48,279 --> 00:05:50,479 Speaker 1: Well, Google needs to find a way to continue to 114 00:05:50,520 --> 00:05:53,120 Speaker 1: compete even with a little bit of data sharing. What 115 00:05:53,160 --> 00:05:54,760 Speaker 1: do you make of that part of the agreement and 116 00:05:54,800 --> 00:05:57,200 Speaker 1: what it means versus rivals, particularly in general to AI. 117 00:05:59,040 --> 00:06:02,720 Speaker 6: Look, I mean we are starting our searches in perplexity 118 00:06:02,880 --> 00:06:06,000 Speaker 6: and open AI, and then we're going to Google. We're 119 00:06:06,040 --> 00:06:09,000 Speaker 6: not going away from Google. Google is still part of that. 120 00:06:09,600 --> 00:06:12,680 Speaker 6: But the way we as consumers are looking for information 121 00:06:12,760 --> 00:06:15,960 Speaker 6: I think is changing. And so I think this pressure 122 00:06:16,000 --> 00:06:18,440 Speaker 6: on Google is good. It's going to bring their game out. 123 00:06:18,560 --> 00:06:20,839 Speaker 6: You know, It's not like Scottie Shuffler likes to go 124 00:06:20,880 --> 00:06:23,960 Speaker 6: out and play golf against himself. He wants justin Thomas. 125 00:06:23,960 --> 00:06:27,640 Speaker 6: He wants the other players, whether it's Tommy Fleetwood competing 126 00:06:27,680 --> 00:06:30,479 Speaker 6: against him, that makes him better. So I think many 127 00:06:30,480 --> 00:06:33,279 Speaker 6: of these AI companies are making Google better. And we've 128 00:06:33,279 --> 00:06:36,440 Speaker 6: said this for a long time. There's more horsepower underneath 129 00:06:36,480 --> 00:06:39,839 Speaker 6: the hood. Google has done a terrible job of popping 130 00:06:39,880 --> 00:06:43,920 Speaker 6: the hood and showing us what's behind the hood, and 131 00:06:43,960 --> 00:06:45,880 Speaker 6: we think you're going to see that. So you know, 132 00:06:46,000 --> 00:06:49,880 Speaker 6: Gemini is doing a good job. We think ultimately that 133 00:06:50,360 --> 00:06:51,240 Speaker 6: many's AI. 134 00:06:51,080 --> 00:06:52,280 Speaker 2: Competitors are a good thing. 135 00:06:52,320 --> 00:06:54,520 Speaker 6: And I think this came into obviously the judge's ruling, 136 00:06:54,560 --> 00:06:57,040 Speaker 6: which is there's a lot more competition now than there 137 00:06:57,160 --> 00:06:57,960 Speaker 6: was a few years ago. 138 00:06:58,600 --> 00:07:00,320 Speaker 3: We're going to go very deep on the Apple portion 139 00:07:00,360 --> 00:07:02,120 Speaker 3: of this later in the hour, but the basics of 140 00:07:02,120 --> 00:07:04,320 Speaker 3: it are is that Google's still allowed to play pay 141 00:07:04,400 --> 00:07:08,440 Speaker 3: Apple twenty billion dollars a year and others to be 142 00:07:08,480 --> 00:07:09,760 Speaker 3: the default search basement. 143 00:07:09,800 --> 00:07:12,800 Speaker 2: How big is that for Google? That result? 144 00:07:14,280 --> 00:07:16,440 Speaker 6: I think it's I mean it's huge, it's it's it's 145 00:07:16,440 --> 00:07:19,040 Speaker 6: a big thing. And I think Apple has said that 146 00:07:19,080 --> 00:07:22,880 Speaker 6: they are also looking at evaluating Gemini, they are evaluing 147 00:07:23,040 --> 00:07:27,720 Speaker 6: other AI tools. But I think ultimately what happens is, look, 148 00:07:27,760 --> 00:07:29,880 Speaker 6: even if they had to divest the browser, they didn't 149 00:07:29,880 --> 00:07:32,880 Speaker 6: get this, Everyone's still going to go back to Google. Right, 150 00:07:32,960 --> 00:07:36,920 Speaker 6: We're going to go to opening perplexity to do different searches, 151 00:07:36,960 --> 00:07:39,920 Speaker 6: but we ultimately end back up in Google. You can't 152 00:07:40,000 --> 00:07:44,640 Speaker 6: complete the loop without Google, whether it's map information or 153 00:07:44,760 --> 00:07:48,720 Speaker 6: hours about a business you're trying to visit, or you're 154 00:07:48,720 --> 00:07:51,080 Speaker 6: trying to figure out, you know what time does the 155 00:07:51,160 --> 00:07:53,720 Speaker 6: vet close? You know, like, there's just things that you 156 00:07:53,840 --> 00:07:56,120 Speaker 6: need Google for and it's the best way. And so 157 00:07:56,680 --> 00:07:58,840 Speaker 6: it really didn't matter in our opinion if they had 158 00:07:58,840 --> 00:08:01,720 Speaker 6: to divest the browser or what's gonna happen. It's the 159 00:08:01,720 --> 00:08:04,680 Speaker 6: consumers are going to defect their behavior, and the behavior 160 00:08:04,800 --> 00:08:06,960 Speaker 6: is you go to where you get the best information, 161 00:08:07,080 --> 00:08:09,480 Speaker 6: and that's the best information today for a lot of 162 00:08:09,480 --> 00:08:14,920 Speaker 6: the consumers is in Google. So again, I think the 163 00:08:14,960 --> 00:08:17,680 Speaker 6: world is shifting. There's no question. I think this pressure 164 00:08:17,720 --> 00:08:20,600 Speaker 6: is going to be good. But I think again, if 165 00:08:20,640 --> 00:08:22,560 Speaker 6: you take a picture of a car in California, which 166 00:08:22,600 --> 00:08:24,760 Speaker 6: I did for my son, and you want to figure 167 00:08:24,760 --> 00:08:27,320 Speaker 6: out where a Toyota four Runner with different colors is at, 168 00:08:27,440 --> 00:08:30,040 Speaker 6: and Gemini will tell you the dealerships where that car 169 00:08:30,080 --> 00:08:34,400 Speaker 6: is available in perplexity or or check gvtal to tell 170 00:08:34,400 --> 00:08:36,640 Speaker 6: you the dealerships, it won't tell you where the exact 171 00:08:36,640 --> 00:08:39,200 Speaker 6: car can be found. So I think there's examples of 172 00:08:39,240 --> 00:08:44,920 Speaker 6: where Gemini is actually better than the other systems. And again, 173 00:08:45,520 --> 00:08:48,199 Speaker 6: we're gonna have multiple agents. We're gonna have multiple AI 174 00:08:48,360 --> 00:08:52,320 Speaker 6: systems that we all embrace that work in concert with 175 00:08:52,440 --> 00:08:55,480 Speaker 6: each other. And again I think that's what we're seeing 176 00:08:55,480 --> 00:08:58,320 Speaker 6: in our survey work. When you talk to your own usage, 177 00:08:58,320 --> 00:09:00,640 Speaker 6: when you look at you talk to your friends, we're 178 00:09:00,720 --> 00:09:03,600 Speaker 6: using multiple tools. This isn't going to reduce the need 179 00:09:03,640 --> 00:09:04,120 Speaker 6: for Google. 180 00:09:04,760 --> 00:09:08,600 Speaker 1: We're at your price target for alvabet I believe. So 181 00:09:09,320 --> 00:09:12,160 Speaker 1: do we see ongoing growth for alvabet. 182 00:09:12,200 --> 00:09:13,360 Speaker 4: You seem to be talking a. 183 00:09:13,360 --> 00:09:15,240 Speaker 1: Very bullish case for why it's going to win out 184 00:09:15,280 --> 00:09:16,000 Speaker 1: in this competition. 185 00:09:17,280 --> 00:09:17,439 Speaker 4: Yeah. 186 00:09:17,480 --> 00:09:19,520 Speaker 6: I mean Stock's up twenty two percent now and it's 187 00:09:19,559 --> 00:09:22,760 Speaker 6: outperforming Amazon and many of the other names. The sen 188 00:09:22,920 --> 00:09:25,680 Speaker 6: and AI was too negative, and on this court ruling 189 00:09:25,720 --> 00:09:27,880 Speaker 6: it was too It was too negative. So we've had 190 00:09:27,920 --> 00:09:30,920 Speaker 6: a nice snap back. And again, as we've seen in 191 00:09:30,920 --> 00:09:34,000 Speaker 6: many cases like Oracles up fifteen, Stock gave back fifteen 192 00:09:34,040 --> 00:09:37,000 Speaker 6: points recently. I mean I would say that I think 193 00:09:37,200 --> 00:09:40,480 Speaker 6: clearly Stock's reflecting a lot of the good news now 194 00:09:40,559 --> 00:09:43,640 Speaker 6: and that's honestly kind of again where our price target 195 00:09:43,679 --> 00:09:46,920 Speaker 6: was set. So we didn't predict this, but I certainly 196 00:09:46,920 --> 00:09:49,360 Speaker 6: think there Again, just go back to the playbook for 197 00:09:49,400 --> 00:09:52,400 Speaker 6: the last two decades in tech, the rule is every time, 198 00:09:52,440 --> 00:09:55,000 Speaker 6: going forward, in every conversation we have going forward with 199 00:09:55,040 --> 00:10:01,000 Speaker 6: you guys, the big tech investigations lead to basically nothing, 200 00:10:01,760 --> 00:10:04,840 Speaker 6: and they are great buying opportunities. It's been that case 201 00:10:04,880 --> 00:10:05,640 Speaker 6: for two decades. 202 00:10:05,840 --> 00:10:08,760 Speaker 7: So that's the That's what I think we've got to 203 00:10:08,760 --> 00:10:12,920 Speaker 7: continue to take away right big texts trying to help consumers, governments, 204 00:10:12,920 --> 00:10:15,520 Speaker 7: trying and protect and they ultimately find a way to 205 00:10:15,720 --> 00:10:18,840 Speaker 7: have peace and in this new AI world. 206 00:10:18,880 --> 00:10:20,560 Speaker 6: And I think that's exactly what we got. 207 00:10:20,720 --> 00:10:23,720 Speaker 1: Brenville Anst Jefferies. Great to have you on. 208 00:10:23,880 --> 00:10:24,280 Speaker 4: Thank you. 209 00:10:24,520 --> 00:10:28,400 Speaker 1: Coming up software companies, well, they're offering the government steep 210 00:10:28,480 --> 00:10:30,280 Speaker 1: discounts to line up contracts. 211 00:10:30,360 --> 00:10:32,160 Speaker 4: We'll discuss next. That's pretty bad tech. 212 00:10:42,080 --> 00:10:44,640 Speaker 3: Service Now is aiming to boost its contracts with the 213 00:10:44,720 --> 00:10:48,600 Speaker 3: US government by offering federal agencies discounts, but as much 214 00:10:48,600 --> 00:10:52,240 Speaker 3: as seventy percent on its software. Bloombo's Brody Ford breaks 215 00:10:52,240 --> 00:10:55,520 Speaker 3: the story and joins US now. Service now wants adoption 216 00:10:55,559 --> 00:10:58,720 Speaker 3: of its AI tools, right, but just explain the mechanism. 217 00:10:58,760 --> 00:11:02,080 Speaker 3: What does a federal government agency need to do to 218 00:11:02,160 --> 00:11:04,200 Speaker 3: get that seventy percent discount? 219 00:11:04,520 --> 00:11:08,400 Speaker 8: Yeah, so service now makes effectively it helped desk software. 220 00:11:08,480 --> 00:11:10,760 Speaker 8: You say, oh, dang, I lost my laptop. I need 221 00:11:10,800 --> 00:11:13,839 Speaker 8: a new one. Instead of going and finding somebody, you know, 222 00:11:13,920 --> 00:11:17,280 Speaker 8: you just put in a ticket with service now over simplification. 223 00:11:17,440 --> 00:11:20,920 Speaker 8: But it makes these kinds of things simple in the workplace. Essentially, 224 00:11:20,920 --> 00:11:23,920 Speaker 8: the federal government has been saying, for these software tools 225 00:11:23,960 --> 00:11:27,920 Speaker 8: we use, why don't we centralize our negotiations and try 226 00:11:27,960 --> 00:11:31,000 Speaker 8: to get the best discount we can from these software vendors. 227 00:11:31,040 --> 00:11:33,360 Speaker 8: And so Service Now is just the latest of these 228 00:11:33,400 --> 00:11:37,240 Speaker 8: steep discounts. They say, if you upgrade, if you expand 229 00:11:37,280 --> 00:11:40,160 Speaker 8: your business, we'll give you a discount. Government gets a 230 00:11:40,160 --> 00:11:44,240 Speaker 8: discount and Service now gets effectively new business because in 231 00:11:44,280 --> 00:11:47,040 Speaker 8: a couple of years that pricing might go back to normal. 232 00:11:47,520 --> 00:11:50,760 Speaker 1: And is that the positive here because Service now is 233 00:11:50,760 --> 00:11:54,480 Speaker 1: in what seventy five percent of government agencies, So they 234 00:11:54,480 --> 00:11:56,480 Speaker 1: take this hit to margin in the short term for 235 00:11:56,559 --> 00:11:57,440 Speaker 1: long term reward. 236 00:11:58,120 --> 00:12:00,560 Speaker 8: Yeah, I'm sure that is the bet there. May right, 237 00:12:00,600 --> 00:12:03,440 Speaker 8: they're saying that we can land some new business, get 238 00:12:03,440 --> 00:12:06,880 Speaker 8: them to upgrade to our better systems, We'll take the 239 00:12:07,000 --> 00:12:09,200 Speaker 8: margin hit for a little while. Then in two or 240 00:12:09,200 --> 00:12:11,280 Speaker 8: three years, you know what are we going to charge them. 241 00:12:11,320 --> 00:12:16,520 Speaker 8: Then it's unclear how these discounts will stick. 242 00:12:16,760 --> 00:12:18,880 Speaker 2: Will they stick, But. 243 00:12:18,800 --> 00:12:21,240 Speaker 8: For now, the government and these vendors are saying it's 244 00:12:21,240 --> 00:12:23,800 Speaker 8: a bit of a win win situation. I mean, government 245 00:12:23,840 --> 00:12:27,880 Speaker 8: buying of software is a famously fragmented and chaotic process, 246 00:12:27,920 --> 00:12:29,520 Speaker 8: and they're trying to improve that a bit. 247 00:12:30,240 --> 00:12:32,920 Speaker 1: Bloomberg's Brodie Ford, it's a great read. Thanks so much 248 00:12:32,920 --> 00:12:36,319 Speaker 1: for explaining it. Look for more on software expertise here, 249 00:12:36,400 --> 00:12:38,400 Speaker 1: let's bring in Hillary fresh Year is the senior research 250 00:12:38,400 --> 00:12:41,000 Speaker 1: analysts for software and IT services at clear Bridge Investments, 251 00:12:41,040 --> 00:12:44,760 Speaker 1: and Hillary, Look, it's not just Service Now. Microsoft has 252 00:12:44,800 --> 00:12:48,199 Speaker 1: also been discounting. We've seen slacks have two pass a 253 00:12:48,280 --> 00:12:52,040 Speaker 1: salesforce and indeed some of the providers of cloud. Is 254 00:12:52,080 --> 00:12:54,040 Speaker 1: this something you build into the models at the moment 255 00:12:54,080 --> 00:12:55,840 Speaker 1: that for the time being they're going to have to 256 00:12:55,880 --> 00:12:56,880 Speaker 1: offer more for less. 257 00:12:57,160 --> 00:13:00,200 Speaker 9: Sure, well, I think yes, it's part and parcel of 258 00:13:00,240 --> 00:13:03,360 Speaker 9: actually doing business in the current era with the government. 259 00:13:03,720 --> 00:13:06,680 Speaker 9: But the government has such antiquated systems, they have so 260 00:13:06,760 --> 00:13:10,280 Speaker 9: much to do with respect to digitizing their environments that, 261 00:13:10,360 --> 00:13:12,560 Speaker 9: as Brodie said, I think it's a big opportunity for 262 00:13:12,600 --> 00:13:16,320 Speaker 9: the vendors. And recall that the margin on incremental software 263 00:13:16,360 --> 00:13:19,800 Speaker 9: is incredibly high, so they can afford to give more 264 00:13:19,880 --> 00:13:23,880 Speaker 9: for the same amount initially to get more in the end. So, 265 00:13:24,120 --> 00:13:26,200 Speaker 9: in fact, I think it's been a source of upside 266 00:13:26,240 --> 00:13:28,000 Speaker 9: for some of these models. We actually saw that in 267 00:13:28,040 --> 00:13:29,640 Speaker 9: Service Now few quarters ago. 268 00:13:30,640 --> 00:13:33,160 Speaker 3: Oh, Hillary, you said in this current environment in Carolina, 269 00:13:33,160 --> 00:13:34,439 Speaker 3: and I was discussing this morning at. 270 00:13:34,400 --> 00:13:36,719 Speaker 2: The desk about how that last. 271 00:13:36,520 --> 00:13:40,000 Speaker 3: Earnings period, there were a number of names where government 272 00:13:40,040 --> 00:13:44,160 Speaker 3: contracts were track so closely. How crucial is it that 273 00:13:44,320 --> 00:13:46,880 Speaker 3: a software name is on good terms with this administration 274 00:13:47,160 --> 00:13:49,440 Speaker 3: and able to get through that procurement process. 275 00:13:50,080 --> 00:13:54,280 Speaker 9: I think it's very important and beneficial. Most of the 276 00:13:54,360 --> 00:13:56,839 Speaker 9: vendors we track are doing a pretty good job of it, 277 00:13:57,280 --> 00:14:01,000 Speaker 9: and I actually I think most investors haven't imputed much 278 00:14:01,040 --> 00:14:03,720 Speaker 9: benefit from government near term in their models to so 279 00:14:03,800 --> 00:14:05,960 Speaker 9: to the extent that comes through, I think that could 280 00:14:05,960 --> 00:14:07,520 Speaker 9: be a source of upside for some of them. 281 00:14:08,280 --> 00:14:11,560 Speaker 3: So then how should investors adjust maybe how they model 282 00:14:11,640 --> 00:14:13,560 Speaker 3: some of these names. Is there a lot more upside 283 00:14:13,600 --> 00:14:17,040 Speaker 3: in some of these shares that come directly from top 284 00:14:17,080 --> 00:14:19,520 Speaker 3: line growth from government sales that you're not yet seeing 285 00:14:19,560 --> 00:14:21,680 Speaker 3: baked in overtime? 286 00:14:21,760 --> 00:14:24,840 Speaker 9: Yes, over time, potentially next quarter. I don't think that's 287 00:14:24,880 --> 00:14:28,160 Speaker 9: an immediate term phenomenon for many, But we saw Salesforce 288 00:14:28,200 --> 00:14:31,400 Speaker 9: had booked one hundred million dollar government contract recently to 289 00:14:31,520 --> 00:14:33,200 Speaker 9: the end of the quarter. That's actually a very small 290 00:14:33,240 --> 00:14:36,120 Speaker 9: relative to the total, but it's indicative of a thign. 291 00:14:36,200 --> 00:14:39,560 Speaker 9: It's an indicative of the government starting to purchase following 292 00:14:39,600 --> 00:14:43,680 Speaker 9: DOGE cuts, where the vendors saw some immediate term pain 293 00:14:43,800 --> 00:14:45,240 Speaker 9: in the prayer a few quarters, and. 294 00:14:45,200 --> 00:14:47,760 Speaker 1: That's important considering we've got Salesforce numbers coming out after 295 00:14:47,800 --> 00:14:50,440 Speaker 1: the battle on September the third, and I'm interested well, 296 00:14:50,520 --> 00:14:54,200 Speaker 1: so today I'm interested in the growth or the winners 297 00:14:54,240 --> 00:14:57,040 Speaker 1: and losers here because in many ways, Salesforce has been 298 00:14:57,040 --> 00:14:59,680 Speaker 1: beaten up this year, unlike many other tech names, because 299 00:14:59,680 --> 00:15:03,120 Speaker 1: we're that it's losing out to Genai competitors. 300 00:15:03,240 --> 00:15:04,240 Speaker 4: Is not something you're seeing. 301 00:15:04,760 --> 00:15:07,960 Speaker 9: Yes, the entire SaaS complex has been really beaten up 302 00:15:07,960 --> 00:15:10,200 Speaker 9: on investor concerns of our disintermediation. 303 00:15:10,280 --> 00:15:11,080 Speaker 4: And it's funny. 304 00:15:11,120 --> 00:15:14,960 Speaker 9: We've seen rolling recognition of GENI beneficiaries, starting with semis 305 00:15:15,000 --> 00:15:19,040 Speaker 9: and hardware, data center, power, hyperscalers, etc. Most recently the 306 00:15:19,120 --> 00:15:23,040 Speaker 9: data platform names, but SAS has been left behind, and 307 00:15:23,080 --> 00:15:26,760 Speaker 9: I believe in that ving investors are assuming that SaaS 308 00:15:27,200 --> 00:15:29,800 Speaker 9: is very much a zero sum game, meaning for any 309 00:15:30,080 --> 00:15:33,520 Speaker 9: GENI winner, there are going to be multiple incumbent losers. 310 00:15:34,160 --> 00:15:35,920 Speaker 9: But there are a few things I think about when 311 00:15:36,160 --> 00:15:39,320 Speaker 9: thinking through that which I'd be happy to discuss. One 312 00:15:39,320 --> 00:15:41,040 Speaker 9: of them is that over the next five years we're 313 00:15:41,040 --> 00:15:44,440 Speaker 9: going to see so much more opportunity in software and 314 00:15:44,480 --> 00:15:47,160 Speaker 9: even in SaaS than we've been seen, there's going to 315 00:15:47,160 --> 00:15:50,080 Speaker 9: be far more workloads to address farmer software written, and 316 00:15:50,160 --> 00:15:53,400 Speaker 9: the incumbents who are moving quickly and executing will be 317 00:15:53,440 --> 00:15:56,600 Speaker 9: a big part of that. Second, these vendors are probably 318 00:15:56,640 --> 00:16:01,000 Speaker 9: going to generate more revenue from GENNI before we see 319 00:16:01,000 --> 00:16:04,920 Speaker 9: any actual real distancetermuniation from their businesses and their variances 320 00:16:05,040 --> 00:16:08,160 Speaker 9: depending on the sub segment. But that's something to think about. 321 00:16:08,200 --> 00:16:10,240 Speaker 9: And then finally, the valuations have been crushed, as you 322 00:16:10,280 --> 00:16:13,880 Speaker 9: pointed out, so it's an interesting stetup. There's still a 323 00:16:13,920 --> 00:16:16,120 Speaker 9: fair amount of mutum uncertainty, but as we moved through 324 00:16:16,160 --> 00:16:19,840 Speaker 9: the year, that narrative could shift similar to but not 325 00:16:19,960 --> 00:16:22,200 Speaker 9: exactly to the extent that we saw in a in 326 00:16:22,240 --> 00:16:24,760 Speaker 9: a Snowflake a year ago or a Mango DV more recently, 327 00:16:24,840 --> 00:16:25,560 Speaker 9: but to a less. 328 00:16:25,680 --> 00:16:27,400 Speaker 2: Find that so fascinating. 329 00:16:27,480 --> 00:16:29,520 Speaker 3: I was in Europe for the UK for much of 330 00:16:29,560 --> 00:16:31,320 Speaker 3: the last thirty days and a lot of the software 331 00:16:31,400 --> 00:16:34,080 Speaker 3: names had a rough period. There's a lot of empsystem 332 00:16:34,120 --> 00:16:38,800 Speaker 3: like how the no Code Low Code player survives right, 333 00:16:38,880 --> 00:16:42,880 Speaker 3: And I'm interested in salesforce earnings right because there's the hype. 334 00:16:42,680 --> 00:16:43,960 Speaker 2: Of the AI headline. 335 00:16:44,640 --> 00:16:47,560 Speaker 3: Do you see that materially like growing these businesses? 336 00:16:47,600 --> 00:16:47,720 Speaker 10: Now? 337 00:16:47,840 --> 00:16:49,880 Speaker 2: Are they good at AI or are they just good 338 00:16:49,920 --> 00:16:50,600 Speaker 2: at marketing? 339 00:16:51,920 --> 00:16:53,840 Speaker 9: They'll some of them will be good at both. I 340 00:16:53,880 --> 00:16:56,040 Speaker 9: think salesforce will be good at both. Cogin is a 341 00:16:56,160 --> 00:16:59,480 Speaker 9: very different discipline. Co gen doesn't have to be right 342 00:16:59,560 --> 00:17:02,200 Speaker 9: out of the You have a world of developers who 343 00:17:02,240 --> 00:17:04,640 Speaker 9: can spend all the time they save actually generating code 344 00:17:04,720 --> 00:17:07,520 Speaker 9: or remediating the code after it's been written. When something 345 00:17:07,560 --> 00:17:10,960 Speaker 9: is customer facing or even broadly employee facing, it has 346 00:17:11,000 --> 00:17:14,240 Speaker 9: to be accurate, secure, compliant, trust it. It can't run 347 00:17:14,240 --> 00:17:17,600 Speaker 9: off the rails. It can't expose proprietary data or expose 348 00:17:17,640 --> 00:17:21,439 Speaker 9: the organization to liability or security vulnerabilities. So that just 349 00:17:21,480 --> 00:17:25,080 Speaker 9: translates to slower adoption in the enterprise in particular and 350 00:17:25,080 --> 00:17:32,200 Speaker 9: commercial organizations. But the incumbents have incomacy advantages, They delivering 351 00:17:32,200 --> 00:17:36,000 Speaker 9: distribution advantages. They have a lot of hooks into every system. 352 00:17:36,040 --> 00:17:38,879 Speaker 9: They can make things work together. They own the workflows, 353 00:17:39,119 --> 00:17:42,600 Speaker 9: the data fabric, the business logic. There's a lot there 354 00:17:42,640 --> 00:17:45,439 Speaker 9: that they can work with and IMPUTYI on top of it. 355 00:17:45,520 --> 00:17:47,600 Speaker 9: So it just means they have a fighting chance and 356 00:17:47,640 --> 00:17:50,159 Speaker 9: they're moving a whole lot faster this time around than 357 00:17:50,200 --> 00:17:52,040 Speaker 9: they did in cloud. But it's going to take time. 358 00:17:52,080 --> 00:17:54,040 Speaker 9: We're not going to see it immediately. It'll take time. 359 00:17:54,200 --> 00:17:55,959 Speaker 4: Henry Fresh Deep Insight. 360 00:17:56,040 --> 00:17:58,560 Speaker 1: We thank as senior research analysts for software and IT 361 00:17:58,800 --> 00:18:00,000 Speaker 1: services at Clearbridge Investment. 362 00:18:06,920 --> 00:18:10,800 Speaker 3: Cato Networks is announcing its first ever acquisition, buying Israeli 363 00:18:10,880 --> 00:18:14,879 Speaker 3: startup aim Security, which specialized is in enterprise AI security tools, 364 00:18:15,119 --> 00:18:17,199 Speaker 3: going to bring in Cato CEO Sho Kramer. 365 00:18:17,240 --> 00:18:18,439 Speaker 2: And you know this is interesting. 366 00:18:18,440 --> 00:18:20,680 Speaker 3: You've been on the show regularly throughout the year, We've 367 00:18:20,680 --> 00:18:22,399 Speaker 3: talked about M and A and now you've done some 368 00:18:22,960 --> 00:18:24,200 Speaker 3: what's the rationale here? 369 00:18:26,119 --> 00:18:31,320 Speaker 10: Well, the nationalist that AI transformation is going to dominate 370 00:18:32,760 --> 00:18:36,119 Speaker 10: enterprise investment in the next decade. It's going to be 371 00:18:36,240 --> 00:18:42,159 Speaker 10: bigger and faster and more impactful from a business perspective 372 00:18:42,240 --> 00:18:44,440 Speaker 10: than even digital transformation. 373 00:18:45,440 --> 00:18:51,960 Speaker 11: And it creates a huge security challenge because it's a 374 00:18:52,040 --> 00:18:57,160 Speaker 11: completely new security sect that needs to listen to all 375 00:18:57,240 --> 00:19:01,239 Speaker 11: these tens of thousands of conversations in plain language and 376 00:19:01,320 --> 00:19:04,000 Speaker 11: decide what is. 377 00:19:03,920 --> 00:19:08,159 Speaker 10: Appopulate for the enterprise according to some policy. So this 378 00:19:08,480 --> 00:19:11,520 Speaker 10: is a whole new category in security is going to 379 00:19:11,520 --> 00:19:15,600 Speaker 10: be huge, and SASE is the best place to put it. 380 00:19:16,200 --> 00:19:21,000 Speaker 10: SASE is the network. Security is a cloud service that 381 00:19:21,080 --> 00:19:25,160 Speaker 10: sits and listen to all these conversations. So we've obviously 382 00:19:25,920 --> 00:19:31,840 Speaker 10: jumped in early into this and bought a security that 383 00:19:32,000 --> 00:19:37,960 Speaker 10: specializes for the last three years in building these security sets. 384 00:19:38,520 --> 00:19:41,240 Speaker 1: Is it about the talent that you need to bring 385 00:19:41,280 --> 00:19:44,560 Speaker 1: in when you've already got an annual recurring revenue run 386 00:19:44,640 --> 00:19:47,400 Speaker 1: rate of three hundred million dollars. You're building fast too. 387 00:19:47,400 --> 00:19:48,840 Speaker 1: Why can't you do it organically? 388 00:19:50,480 --> 00:19:56,160 Speaker 10: Because the market is happening at late that is unprecedented. 389 00:19:56,480 --> 00:20:00,240 Speaker 10: There's a huge pressure both from the board that's is 390 00:20:00,280 --> 00:20:06,160 Speaker 10: AI as most important business initiative as well as from 391 00:20:06,240 --> 00:20:11,359 Speaker 10: employees that the AI is the most important productivity initiative 392 00:20:11,400 --> 00:20:15,359 Speaker 10: And the SISO that, as we talked last time, is 393 00:20:15,440 --> 00:20:18,560 Speaker 10: in its predicament as it is from a budget and 394 00:20:18,840 --> 00:20:23,320 Speaker 10: from a polational from a gunity perspective, now has to 395 00:20:23,359 --> 00:20:27,880 Speaker 10: face AI and needs to deliver a secure journey and 396 00:20:27,920 --> 00:20:30,560 Speaker 10: it needs to and they need to do it now. 397 00:20:30,760 --> 00:20:34,879 Speaker 10: So developing three years now, what AIM has developed in 398 00:20:34,880 --> 00:20:37,080 Speaker 10: the last three years is not going to cut it. 399 00:20:37,680 --> 00:20:42,520 Speaker 10: Enterprises need it now and need a broad solution and 400 00:20:42,600 --> 00:20:45,040 Speaker 10: a deep solution and that's what we bring them. 401 00:20:45,280 --> 00:20:45,760 Speaker 2: Schlima. 402 00:20:46,520 --> 00:20:48,320 Speaker 3: We only have a minute left, but a crew has 403 00:20:48,400 --> 00:20:50,760 Speaker 3: come in and giving you an additional fifty million on 404 00:20:50,800 --> 00:20:53,520 Speaker 3: top of the three point fifty you did in June. 405 00:20:53,880 --> 00:20:55,680 Speaker 3: Did you need the money for this piece of M 406 00:20:55,720 --> 00:20:58,480 Speaker 3: and A or why are you taking that extra capital. 407 00:21:00,040 --> 00:21:05,760 Speaker 10: Because we can. Because I think that with this acquisition, 408 00:21:06,000 --> 00:21:11,240 Speaker 10: Kato is becoming even more exciting to investors. And you know, 409 00:21:11,320 --> 00:21:16,960 Speaker 10: we always have a second closing plan and and we 410 00:21:17,080 --> 00:21:20,440 Speaker 10: have we have we have enough cash in the bank 411 00:21:20,560 --> 00:21:26,720 Speaker 10: to get to profitability without compromising our aggressive golf targets, 412 00:21:26,800 --> 00:21:32,679 Speaker 10: with or without this fifteen million, but showing a stronger balance. 413 00:21:32,760 --> 00:21:33,760 Speaker 10: It is always a good thing. 414 00:21:34,359 --> 00:21:37,440 Speaker 1: Saline's Shomo Kramer. So it's great to catch up with you. 415 00:21:37,520 --> 00:21:40,400 Speaker 1: Co found the CEO Cato Networks as it makes its 416 00:21:40,400 --> 00:21:41,240 Speaker 1: first ever M and a. 417 00:21:47,280 --> 00:21:48,800 Speaker 4: Welcome back to Bloomberg Tech. 418 00:21:48,920 --> 00:21:52,639 Speaker 1: The data center power demand is growing exponentially thanks to 419 00:21:52,680 --> 00:21:56,679 Speaker 1: AI and the UK's biggest engineering company, Rolls Royce is 420 00:21:56,720 --> 00:21:59,600 Speaker 1: seizing that opportunity. Best known for its jet engine business, 421 00:21:59,760 --> 00:22:02,600 Speaker 1: We'll Royce is also one of the pioneers of small 422 00:22:02,840 --> 00:22:05,840 Speaker 1: nuclear reactor technology. Was recently chosen to build three units 423 00:22:05,880 --> 00:22:07,800 Speaker 1: in the United Kingdom. HIT to talk through the power 424 00:22:07,840 --> 00:22:10,680 Speaker 1: systems growth along with civil, aerospace and defense is a 425 00:22:10,720 --> 00:22:12,480 Speaker 1: company's CFO, Helen McKay. 426 00:22:12,560 --> 00:22:14,520 Speaker 4: It is wonderful to have you here, Helen, while you're 427 00:22:14,680 --> 00:22:16,280 Speaker 4: in the US talking to investors. 428 00:22:16,320 --> 00:22:18,560 Speaker 1: But I'm interested in what you tell them at the moment, 429 00:22:18,600 --> 00:22:22,080 Speaker 1: particularly about SMR technology. What is the opportunity here for 430 00:22:22,160 --> 00:22:23,000 Speaker 1: you as a business. 431 00:22:23,440 --> 00:22:27,760 Speaker 12: Huge opportunities you see in SMR, the size of that market. 432 00:22:27,800 --> 00:22:32,480 Speaker 12: We think the addressable market is about four hundred equivalents 433 00:22:32,480 --> 00:22:37,600 Speaker 12: of their SMRs. Huge opportunity coming forward. As you think 434 00:22:37,600 --> 00:22:41,000 Speaker 12: about how we're going to support energy resilience going forward, 435 00:22:41,160 --> 00:22:43,919 Speaker 12: it has to figure we have a leading position in 436 00:22:43,920 --> 00:22:47,119 Speaker 12: that market. As you said, we won the contract with 437 00:22:47,160 --> 00:22:50,600 Speaker 12: the UK government for the first three small modular reactors. 438 00:22:51,080 --> 00:22:53,879 Speaker 12: We've actually won a contract with the Czech Republic for 439 00:22:54,000 --> 00:22:58,800 Speaker 12: up to six. We're in final stages with Sweden for 440 00:22:58,960 --> 00:23:02,680 Speaker 12: their small module reactors, and we're actually looking at entry 441 00:23:02,720 --> 00:23:05,800 Speaker 12: positions in the US. I mean the US market. You 442 00:23:05,840 --> 00:23:09,160 Speaker 12: have a nuclear ambition to go from I think it's 443 00:23:09,240 --> 00:23:13,680 Speaker 12: one hundred gigawatts to four hundred gigawatts by twenty fifty 444 00:23:14,160 --> 00:23:20,120 Speaker 12: massive opportunity. And we've been building nuclear reactors for submarines, 445 00:23:20,160 --> 00:23:23,520 Speaker 12: for nuclear submarines for more than sixty years, and our 446 00:23:23,680 --> 00:23:26,440 Speaker 12: small modular reactors are the largest on the market as well. 447 00:23:26,480 --> 00:23:29,000 Speaker 1: You've really been selling into government and it's interesting at 448 00:23:29,000 --> 00:23:31,520 Speaker 1: the moment that for us, it's all about the hyperscalar 449 00:23:31,560 --> 00:23:34,399 Speaker 1: demand as well. And we have seen this nuclear renaissance 450 00:23:34,640 --> 00:23:37,080 Speaker 1: bear fruit. When you've got Amazon with x Energy, when 451 00:23:37,080 --> 00:23:40,480 Speaker 1: you've got Alphabet going with Chairostpower, do you talk to 452 00:23:40,480 --> 00:23:42,600 Speaker 1: the hyperscalers or is it more about the US government 453 00:23:42,600 --> 00:23:44,280 Speaker 1: giving your defense leaning No soo. 454 00:23:44,480 --> 00:23:47,280 Speaker 12: Absolutely we're talking to the hyperscalers right now. Where the 455 00:23:47,320 --> 00:23:51,280 Speaker 12: initial focus is on governments and utility companies, but the 456 00:23:51,320 --> 00:23:55,159 Speaker 12: hyperscalers are absolutely talking to us and interested in this. 457 00:23:55,520 --> 00:23:58,200 Speaker 12: If you think about, as you said earlier, the growth 458 00:23:58,240 --> 00:24:02,440 Speaker 12: and AI the that's going to be required to provide 459 00:24:02,480 --> 00:24:06,840 Speaker 12: that continuity and resilience, SMR will absolutely figure in that. 460 00:24:06,920 --> 00:24:10,320 Speaker 12: So those conversations are underway across the globe, not just 461 00:24:10,359 --> 00:24:12,560 Speaker 12: in the US. 462 00:24:12,600 --> 00:24:14,560 Speaker 3: Helen we spent a lot of time in the last 463 00:24:14,600 --> 00:24:16,760 Speaker 3: year speaking to Oklow and x Energy, the kind of 464 00:24:16,760 --> 00:24:20,680 Speaker 3: the more small nimble startups in SMR on this program. 465 00:24:20,800 --> 00:24:22,560 Speaker 2: What's the Rolls Royce advantage? 466 00:24:22,800 --> 00:24:27,159 Speaker 3: What makes your technology better than the newcomers to the field. 467 00:24:27,960 --> 00:24:31,280 Speaker 12: Fantastic, So thanks for the question. So we've been in 468 00:24:31,320 --> 00:24:33,399 Speaker 12: this area for more than sixty years. 469 00:24:33,560 --> 00:24:34,760 Speaker 4: Yeah, we have built. 470 00:24:34,560 --> 00:24:38,560 Speaker 12: Nuclear submarines with nuclear reactors, which is consistent technology with 471 00:24:38,800 --> 00:24:43,720 Speaker 12: SMRs for the U for the UK Navy, So we've 472 00:24:43,720 --> 00:24:48,320 Speaker 12: got leading technology, proven technology. It's based on proven fuel 473 00:24:48,520 --> 00:24:52,879 Speaker 12: supplies as well. In addition to that, SMR is the 474 00:24:52,960 --> 00:24:56,680 Speaker 12: largest on the market at four hundred and seventeen megawatts. 475 00:24:56,880 --> 00:24:59,600 Speaker 12: That means from a cost and efficiency perspective, it's one 476 00:24:59,600 --> 00:25:05,439 Speaker 12: of the more efficient, actually more comparable with energy and wind, 477 00:25:05,800 --> 00:25:10,760 Speaker 12: but importantly more consistent, so it doesn't have latency issues. 478 00:25:11,320 --> 00:25:16,080 Speaker 12: And very importantly ere SMR construct eighty percent of it 479 00:25:16,119 --> 00:25:18,800 Speaker 12: can be modular built, so you can construct it in 480 00:25:18,840 --> 00:25:20,760 Speaker 12: the factory and if you think about almost like a 481 00:25:20,880 --> 00:25:23,560 Speaker 12: Lego block and then you take it to build it 482 00:25:23,720 --> 00:25:27,399 Speaker 12: on site. So it means the construction is much shorter 483 00:25:27,760 --> 00:25:30,760 Speaker 12: and it means the risk factor faster, yeah, is much 484 00:25:30,800 --> 00:25:33,240 Speaker 12: lower as well. So we do have that leading position 485 00:25:33,560 --> 00:25:35,080 Speaker 12: with that distinctive technology. 486 00:25:35,880 --> 00:25:36,200 Speaker 2: Helen. 487 00:25:36,280 --> 00:25:39,960 Speaker 3: In the defense tech context, the political and strategic environments 488 00:25:40,040 --> 00:25:43,119 Speaker 3: like really changed, not just the United States, but like 489 00:25:43,160 --> 00:25:45,600 Speaker 3: Western allies overall. Could you just kind of give me 490 00:25:45,640 --> 00:25:50,400 Speaker 3: your outlook for your next gen military turbo fans combined 491 00:25:50,400 --> 00:25:52,480 Speaker 3: psyco engines and what's changing for you. 492 00:25:53,119 --> 00:25:55,760 Speaker 12: So, as you say, lots of activity in relation to 493 00:25:56,280 --> 00:25:59,119 Speaker 12: investment and defense at the minute, both in the US 494 00:25:59,320 --> 00:26:04,200 Speaker 12: and in Europe. And we've got a very strong position 495 00:26:04,560 --> 00:26:09,720 Speaker 12: in the defense business, not just in what we provide 496 00:26:09,840 --> 00:26:13,439 Speaker 12: for military operations, but actually how that shows up in 497 00:26:13,480 --> 00:26:16,320 Speaker 12: our energy business within power systems. We have a very 498 00:26:16,359 --> 00:26:21,320 Speaker 12: strong governmental position there. We have got leading positions in 499 00:26:21,400 --> 00:26:25,359 Speaker 12: Germany and Europe. We have got leading positions in land 500 00:26:25,560 --> 00:26:29,200 Speaker 12: and naval, and with the spending particularly that's happening in 501 00:26:29,200 --> 00:26:34,160 Speaker 12: Europe when people are talking about increasing natal commitments, where 502 00:26:34,200 --> 00:26:36,920 Speaker 12: we expect to see that show up in the short 503 00:26:37,080 --> 00:26:42,760 Speaker 12: term is actually in land and then naval. You know, 504 00:26:42,960 --> 00:26:46,399 Speaker 12: in our power systems business that governmental business is twenty 505 00:26:46,400 --> 00:26:49,680 Speaker 12: five percent of our revenues. So we're very well positioned 506 00:26:49,920 --> 00:26:53,240 Speaker 12: YEP to support that growth and to capture those opportunities 507 00:26:53,280 --> 00:26:56,240 Speaker 12: going forward. So short term that's where we see it 508 00:26:56,320 --> 00:26:58,720 Speaker 12: will show up. In longer term, we expect to see 509 00:26:58,760 --> 00:27:02,240 Speaker 12: it show up in our defense business, but very exciting. 510 00:27:02,400 --> 00:27:04,399 Speaker 1: I mean, talk to us about the positioning for the 511 00:27:04,440 --> 00:27:07,480 Speaker 1: long term opportunity here. Because you're the CFO, you're thinking 512 00:27:07,480 --> 00:27:09,239 Speaker 1: about how to finance all of this that has been 513 00:27:09,280 --> 00:27:10,760 Speaker 1: some reporting around the. 514 00:27:10,800 --> 00:27:11,920 Speaker 4: SMR part of the business. 515 00:27:11,960 --> 00:27:14,679 Speaker 1: Maybe you think for outside funding even talk of an 516 00:27:14,680 --> 00:27:15,639 Speaker 1: IPO of that unit. 517 00:27:15,840 --> 00:27:18,080 Speaker 4: What are you thinking about longer term to finance all 518 00:27:18,080 --> 00:27:18,280 Speaker 4: of this? 519 00:27:18,800 --> 00:27:22,359 Speaker 12: So SMR, we're not ipo ing that, just to be clear. 520 00:27:23,000 --> 00:27:26,080 Speaker 12: So we're investing right now to support growth across all 521 00:27:26,119 --> 00:27:30,000 Speaker 12: of our businesses. But if I maybe focus on the 522 00:27:30,560 --> 00:27:34,679 Speaker 12: governmental business, just within the last six weeks, we've actually 523 00:27:34,680 --> 00:27:37,639 Speaker 12: invested more than one hundred million pounds in the US 524 00:27:37,720 --> 00:27:43,320 Speaker 12: alone to support the growth of expanded production, be that 525 00:27:43,400 --> 00:27:45,560 Speaker 12: in defense or data centers. 526 00:27:45,680 --> 00:27:48,159 Speaker 1: Do you have to because of the administration investment on 527 00:27:48,240 --> 00:27:51,239 Speaker 1: the No, Yeah, the US is an important market for 528 00:27:51,320 --> 00:27:54,280 Speaker 1: It is very important that we continue to grow our 529 00:27:54,320 --> 00:27:55,200 Speaker 1: position here. 530 00:27:55,400 --> 00:27:57,880 Speaker 12: It's one of our home markets. So it's the right 531 00:27:57,920 --> 00:28:00,880 Speaker 12: thing for us to do. But across our business, since 532 00:28:00,920 --> 00:28:06,960 Speaker 12: we put our transformation together, we've actually increased investment each year. Yeah, 533 00:28:07,119 --> 00:28:11,320 Speaker 12: while we've delivered this results and we're investing now for 534 00:28:11,720 --> 00:28:14,040 Speaker 12: the longer term, some of the investments that we're doing 535 00:28:14,080 --> 00:28:18,320 Speaker 12: in our investment defense business, the platforms and the programs 536 00:28:18,359 --> 00:28:21,439 Speaker 12: won't come into operation until the twenty thirties. So the 537 00:28:21,480 --> 00:28:23,280 Speaker 12: long term growth is happening right now. 538 00:28:24,960 --> 00:28:28,080 Speaker 2: Helen ros Royce is so aligned with Airbus. 539 00:28:28,760 --> 00:28:31,800 Speaker 3: But the strategy of this president administration is to use 540 00:28:32,160 --> 00:28:37,119 Speaker 3: Boeings like a negotiating tool, you know in international markets. 541 00:28:37,920 --> 00:28:39,120 Speaker 2: How do you see that playing out? 542 00:28:39,360 --> 00:28:43,880 Speaker 3: Do you participate in a US administration that's focused on 543 00:28:43,920 --> 00:28:46,200 Speaker 3: Boeing if you're so close to Airbus? By the way, 544 00:28:46,280 --> 00:28:49,840 Speaker 3: massive aviation like a care about the propulsion as well 545 00:28:49,840 --> 00:28:52,040 Speaker 3: as the fuselage which aircraft cone on. 546 00:28:53,200 --> 00:28:53,440 Speaker 4: I mean. 547 00:28:53,440 --> 00:28:55,040 Speaker 12: So what I'd say is we have got a very 548 00:28:55,080 --> 00:28:59,440 Speaker 12: good and strong relationship with the US administration and we've 549 00:28:59,440 --> 00:29:03,280 Speaker 12: got a very good relationship with Boeing and Airbus. So 550 00:29:03,280 --> 00:29:05,440 Speaker 12: that's how we lead into that. We've had a presence 551 00:29:05,520 --> 00:29:09,240 Speaker 12: in America for more than one hundred years. We have 552 00:29:09,280 --> 00:29:12,880 Speaker 12: got five thos people across twenty six states that work 553 00:29:12,960 --> 00:29:16,000 Speaker 12: for rules Royce. It is one of your whole markets. 554 00:29:16,200 --> 00:29:17,320 Speaker 2: So that is how we. 555 00:29:17,200 --> 00:29:21,120 Speaker 12: Approach those relationships with the administration in the US, and 556 00:29:21,200 --> 00:29:24,160 Speaker 12: it has worked incredibly well. And it will remain a 557 00:29:24,240 --> 00:29:27,040 Speaker 12: very important market for us going forward. 558 00:29:28,120 --> 00:29:31,080 Speaker 3: Helen McKay, CFO Rolls Royce, thank you so much for 559 00:29:31,160 --> 00:29:33,920 Speaker 3: joining us on Bloomberg Tech. Let's get back to our 560 00:29:33,960 --> 00:29:36,400 Speaker 3: top story, and that is Google it does not have 561 00:29:36,520 --> 00:29:39,320 Speaker 3: to divest Chrome. The shares are up almost nine percent, 562 00:29:39,360 --> 00:29:43,320 Speaker 3: biggest jumpson's April record high. There's the second part to 563 00:29:43,400 --> 00:29:46,680 Speaker 3: the story, which is that Google's able to continue paying 564 00:29:46,760 --> 00:29:50,240 Speaker 3: partners for placement of search. Apple is the main part 565 00:29:50,320 --> 00:29:52,880 Speaker 3: of that story. Its shares are also higher and in 566 00:29:52,920 --> 00:29:54,160 Speaker 3: the balance and remainder. 567 00:29:53,840 --> 00:29:54,080 Speaker 2: Of the show. 568 00:29:54,120 --> 00:29:55,640 Speaker 3: We're going to go out to bloombergs Mark German and 569 00:29:55,760 --> 00:29:58,280 Speaker 3: understand the Apple piece of this story. 570 00:29:58,480 --> 00:29:59,280 Speaker 2: What else is coming up? 571 00:29:59,320 --> 00:30:02,440 Speaker 1: Karen plenty more, particularly when it comes to funding and 572 00:30:02,480 --> 00:30:04,600 Speaker 1: in the world of general to AI. The CEO of 573 00:30:04,680 --> 00:30:07,080 Speaker 1: you dot Com joining us to discuss the company's latest 574 00:30:07,080 --> 00:30:08,680 Speaker 1: one hundred million dollar funding round. 575 00:30:09,240 --> 00:30:10,280 Speaker 4: This is Bloomberg Tech. 576 00:30:19,720 --> 00:30:22,560 Speaker 3: AI search company u dot Com has closed a one 577 00:30:22,640 --> 00:30:26,200 Speaker 3: hundred million dollar Series C funding round that values it 578 00:30:26,360 --> 00:30:29,280 Speaker 3: at one point five billion dollars, fueled by the AI boom, 579 00:30:29,320 --> 00:30:32,800 Speaker 3: and it shift in focus to enterprise customers. Use dot 580 00:30:32,840 --> 00:30:35,800 Speaker 3: Com co founder and CEO Richard Socials with us in 581 00:30:35,840 --> 00:30:39,800 Speaker 3: San Francisco. The environment has changed, The landscape has changed. 582 00:30:39,840 --> 00:30:42,960 Speaker 3: Every time you come on, it's changed. But did that 583 00:30:43,040 --> 00:30:45,240 Speaker 3: sort of make this round necessary? What do you need 584 00:30:45,240 --> 00:30:46,000 Speaker 3: the funds for? 585 00:30:46,640 --> 00:30:52,200 Speaker 13: We're scaling, Our customers are scaling. The LM infrastructure that 586 00:30:52,360 --> 00:30:56,720 Speaker 13: we need to keep these AI and agents up to 587 00:30:56,800 --> 00:31:00,200 Speaker 13: date is increasing. The needs for it are increasing, so 588 00:31:00,360 --> 00:31:03,240 Speaker 13: that's why we raise it to support our customers like Harvey, 589 00:31:03,560 --> 00:31:08,920 Speaker 13: the Nih abduct, Dot Go, windsurf Telegraph, the German Press 590 00:31:08,920 --> 00:31:11,840 Speaker 13: Agency DPA. There's so many customers now that want this 591 00:31:11,920 --> 00:31:14,360 Speaker 13: technology and need to get the LMS to. 592 00:31:14,280 --> 00:31:14,880 Speaker 11: Be up to date. 593 00:31:15,440 --> 00:31:19,040 Speaker 3: Many founder CEOs from the show saying we're scaling, I 594 00:31:19,040 --> 00:31:21,120 Speaker 3: think that there's like a lot of value in explaining 595 00:31:21,120 --> 00:31:23,960 Speaker 3: what that reads in material real terms, like you're hiring 596 00:31:23,960 --> 00:31:25,680 Speaker 3: better talent, you need more compute. 597 00:31:25,840 --> 00:31:26,880 Speaker 2: What is it? Yeah? 598 00:31:26,880 --> 00:31:29,600 Speaker 13: For us, it's definitely more compute, but also the talent. 599 00:31:29,640 --> 00:31:33,600 Speaker 13: Those are basically the two biggest factors. The more mbdigpus 600 00:31:33,880 --> 00:31:38,480 Speaker 13: but also more scraping infrastructure to really build out the 601 00:31:38,520 --> 00:31:43,000 Speaker 13: best search index for lms. You know, Google build an 602 00:31:43,000 --> 00:31:45,600 Speaker 13: amazing search index for people to decide, oh, which link 603 00:31:45,600 --> 00:31:46,320 Speaker 13: should I click on. 604 00:31:46,680 --> 00:31:48,240 Speaker 2: But LMS search differently. 605 00:31:48,320 --> 00:31:50,920 Speaker 13: They can search through hundreds of different websites, right, they 606 00:31:50,960 --> 00:31:54,440 Speaker 13: can read the whole text or certain lurbs of each 607 00:31:54,440 --> 00:31:57,200 Speaker 13: website to then give you a summary of those answers. 608 00:31:57,240 --> 00:31:59,520 Speaker 13: So all of that is different and needs investment. 609 00:32:00,200 --> 00:32:02,440 Speaker 1: Richard, I mean you are one of the heroes in 610 00:32:02,520 --> 00:32:05,920 Speaker 1: natural language processing. You're like the fourth most cited researcher 611 00:32:05,960 --> 00:32:09,400 Speaker 1: in it. You've been studying it for years. I must 612 00:32:09,840 --> 00:32:13,880 Speaker 1: envisage that you've had some calls for your talent IU 613 00:32:14,240 --> 00:32:16,560 Speaker 1: and wanting to purchase your company. Have you been fending 614 00:32:16,600 --> 00:32:18,920 Speaker 1: off Meta and the like so left, right and center. 615 00:32:20,000 --> 00:32:23,040 Speaker 13: There's definitely been interest in you dot com and our 616 00:32:23,120 --> 00:32:26,760 Speaker 13: team for the last like five years. But we're here 617 00:32:26,800 --> 00:32:30,400 Speaker 13: to really build an enduring company where people can get answers, 618 00:32:30,600 --> 00:32:34,320 Speaker 13: build their own agents, transform their companies, and so we're 619 00:32:34,360 --> 00:32:35,240 Speaker 13: not that interested in that. 620 00:32:35,840 --> 00:32:38,560 Speaker 1: It is such a fair space though. Everyone's in on 621 00:32:38,600 --> 00:32:41,120 Speaker 1: the enterprise. The large language model developers that you use 622 00:32:41,200 --> 00:32:43,640 Speaker 1: open AI, they're trying to get into enterprise, and just 623 00:32:43,920 --> 00:32:48,480 Speaker 1: recently the judge Meta ruling on alphabet for example, and 624 00:32:48,480 --> 00:32:50,280 Speaker 1: the fact that they're going to have to share data. 625 00:32:50,360 --> 00:32:52,959 Speaker 1: How does that benefit you? Because you started your journey 626 00:32:53,000 --> 00:32:54,240 Speaker 1: in AI search. 627 00:32:55,400 --> 00:32:59,000 Speaker 13: Yeah. I think in consumer there will be a few 628 00:32:59,120 --> 00:33:03,520 Speaker 13: usually monopoly or throw our polies, right, But an enterprise 629 00:33:03,560 --> 00:33:06,000 Speaker 13: there's so much open space, right. There are so many 630 00:33:06,080 --> 00:33:09,080 Speaker 13: different companies that need up to date information to make 631 00:33:09,120 --> 00:33:12,600 Speaker 13: their lms more productive over both web data but also 632 00:33:12,800 --> 00:33:16,479 Speaker 13: internal search, internal data, and you need to have all 633 00:33:16,520 --> 00:33:19,000 Speaker 13: of that be composable as an API infrastructure. And so 634 00:33:19,760 --> 00:33:23,400 Speaker 13: that's kind of what we're focused on and where we 635 00:33:23,520 --> 00:33:26,720 Speaker 13: think that is. Indeed, the killer app for lms is 636 00:33:26,760 --> 00:33:28,520 Speaker 13: their productivity in enterprise. 637 00:33:28,920 --> 00:33:31,520 Speaker 3: Our executive producer Jackie Lopez was talking about how it's 638 00:33:31,560 --> 00:33:33,560 Speaker 3: just beautiful timing having you on the show today. Let's 639 00:33:33,600 --> 00:33:36,000 Speaker 3: be honest about it. You know, with the Google decision 640 00:33:36,080 --> 00:33:39,000 Speaker 3: last night, it's coincidence. I was trying to think what 641 00:33:39,160 --> 00:33:42,840 Speaker 3: is richards socialst thing and you've always been basically talking 642 00:33:42,880 --> 00:33:46,040 Speaker 3: about Google in the context that people are building different 643 00:33:46,120 --> 00:33:49,760 Speaker 3: and better stuff and both consumers and enterprises are more 644 00:33:49,800 --> 00:33:52,480 Speaker 3: open to using a different technology. I think that's a 645 00:33:52,480 --> 00:33:55,760 Speaker 3: fair summary of your position. But how has the ruling 646 00:33:55,880 --> 00:34:00,160 Speaker 3: changed things? You know against your the ideology of recent years. 647 00:34:00,120 --> 00:34:04,080 Speaker 13: Is so in many ways it's a good ruling now 648 00:34:04,120 --> 00:34:06,640 Speaker 13: of course, as a startup, when this ruling will really 649 00:34:06,720 --> 00:34:12,640 Speaker 13: come into effect is important. They might appeal the ruling. 650 00:34:13,280 --> 00:34:16,799 Speaker 13: It'll take years probably for it to really materialize. That's 651 00:34:16,920 --> 00:34:21,239 Speaker 13: infinity in AI and startup time. So we're still just 652 00:34:21,280 --> 00:34:23,960 Speaker 13: focused on building the best APIs and also enter in 653 00:34:24,040 --> 00:34:28,319 Speaker 13: solutions for our customers, and we don't really think this 654 00:34:28,360 --> 00:34:31,480 Speaker 13: will materially affect us over next two or three years. 655 00:34:31,600 --> 00:34:31,759 Speaker 2: Now. 656 00:34:31,760 --> 00:34:35,480 Speaker 13: Of course it will affect other consumer companies, but again, 657 00:34:35,680 --> 00:34:37,960 Speaker 13: in many ways, this is an index that was built 658 00:34:38,000 --> 00:34:40,439 Speaker 13: for people to decide which flew a link to click 659 00:34:40,480 --> 00:34:44,160 Speaker 13: on AIS, and people through their AIS and through their 660 00:34:44,200 --> 00:34:46,479 Speaker 13: agents will search very differently into the three years. 661 00:34:47,040 --> 00:34:48,920 Speaker 1: Well, what's interesting is one of your clients that we 662 00:34:49,040 --> 00:34:51,200 Speaker 1: just showed is dut dot Go and it's all about search. 663 00:34:51,640 --> 00:34:54,520 Speaker 1: So how does its end exposure affect you and how 664 00:34:54,520 --> 00:34:57,080 Speaker 1: do you think about continuing to serve are the AI 665 00:34:57,200 --> 00:35:00,120 Speaker 1: winners or broadening out to more of the blue chips. 666 00:35:00,120 --> 00:35:05,360 Speaker 13: Well, yeah, I think the values of privacy are actually 667 00:35:05,440 --> 00:35:09,120 Speaker 13: very useful for both consumers and for enterprise, and so 668 00:35:09,200 --> 00:35:12,399 Speaker 13: we're really excited to keep partnering with companies like that 669 00:35:12,400 --> 00:35:15,600 Speaker 13: that both want to get search results but also feed 670 00:35:15,600 --> 00:35:17,680 Speaker 13: those search results into lms, and we're doing that over 671 00:35:17,760 --> 00:35:21,400 Speaker 13: a billion times a month. There's actually no other AI 672 00:35:21,480 --> 00:35:24,239 Speaker 13: startup I know of that is at that scale a 673 00:35:24,320 --> 00:35:28,080 Speaker 13: billion times where our answers either are shown directly to 674 00:35:28,120 --> 00:35:30,719 Speaker 13: a user or are given to an LM to then 675 00:35:30,800 --> 00:35:33,680 Speaker 13: majorly effect what that LM says. In fact, it would 676 00:35:33,719 --> 00:35:37,520 Speaker 13: say that many people underestimate that whole search infrastructure layer. 677 00:35:38,239 --> 00:35:41,000 Speaker 13: Whereas the lms themselves are going to get commoditized more 678 00:35:41,000 --> 00:35:45,080 Speaker 13: and morts open source pressure for them, but the search 679 00:35:45,160 --> 00:35:46,840 Speaker 13: you can't open source search index. 680 00:35:48,880 --> 00:35:51,160 Speaker 1: We want to thank you, Richard Shosha, wish we had 681 00:35:51,200 --> 00:35:54,560 Speaker 1: more time, CEO and co founder Review dot Com. Fascinating fundraise, 682 00:35:54,600 --> 00:35:55,680 Speaker 1: fascinating business model. 683 00:35:55,719 --> 00:36:01,080 Speaker 4: Come back soon. We hope. 684 00:36:02,400 --> 00:36:04,040 Speaker 1: You've got to get back to the key story of 685 00:36:04,040 --> 00:36:05,160 Speaker 1: the day, and one of the move is on the 686 00:36:05,160 --> 00:36:08,239 Speaker 1: back of it, Apple up almost three percent. That's as 687 00:36:08,280 --> 00:36:11,360 Speaker 1: it rises alongside Alphabet the Court of Course ruling that 688 00:36:11,440 --> 00:36:16,040 Speaker 1: Google can continue to pay partners for keeping Google's Search 689 00:36:16,480 --> 00:36:19,319 Speaker 1: on their operating system. So more on Alphabet's impact on Apple. 690 00:36:19,400 --> 00:36:21,920 Speaker 1: Let's get to Mark German. It is a big lift 691 00:36:22,400 --> 00:36:25,920 Speaker 1: and it's a relief because it helps Apple's bottom line. 692 00:36:26,080 --> 00:36:28,000 Speaker 14: It's a relief for Apple, it's a relief for Google, 693 00:36:28,040 --> 00:36:30,640 Speaker 14: but it's also relief for the whole technology industry. Right 694 00:36:30,680 --> 00:36:35,520 Speaker 14: the US government is scrutinizing all of them, meta. 695 00:36:34,640 --> 00:36:35,720 Speaker 2: Google, Apple. 696 00:36:35,760 --> 00:36:39,160 Speaker 14: Of course you have the European Union involved, obviously that's separate. 697 00:36:39,200 --> 00:36:42,040 Speaker 14: But this ruling yesterday sets some pretty nice precedent. Don't 698 00:36:42,040 --> 00:36:44,680 Speaker 14: forget Apple. They're going to try on a couple of 699 00:36:44,719 --> 00:36:47,560 Speaker 14: years now for what they've done to consumers according to 700 00:36:47,560 --> 00:36:50,120 Speaker 14: the US government. Right, So if Google's getting off scot 701 00:36:50,160 --> 00:36:52,600 Speaker 14: free for things that probably are much worse than what 702 00:36:52,640 --> 00:36:55,560 Speaker 14: Apple has done according I mean, in my viewpoint, I 703 00:36:55,600 --> 00:36:57,000 Speaker 14: think Apple is going to be okay in a couple 704 00:36:57,000 --> 00:36:59,799 Speaker 14: of years too. So that long term headwind that's been 705 00:37:00,560 --> 00:37:03,399 Speaker 14: but also the short term headwind of losing potentially twenty 706 00:37:03,440 --> 00:37:06,040 Speaker 14: billion a year from this Google deal that's also been mitigated. 707 00:37:06,640 --> 00:37:08,200 Speaker 3: Well, Mark, just really quick, because I also want to 708 00:37:08,200 --> 00:37:10,719 Speaker 3: get to a story you broke yesterday. It's the services 709 00:37:10,760 --> 00:37:13,160 Speaker 3: part of Apple's business that the streets focused on this 710 00:37:13,239 --> 00:37:15,440 Speaker 3: morning in the context of the Google ruling. 711 00:37:16,880 --> 00:37:19,160 Speaker 14: Yeah, that's exactly right. I mean, like I said, the 712 00:37:19,520 --> 00:37:21,880 Speaker 14: Google deal right now brings in over twenty billion dollars 713 00:37:21,880 --> 00:37:24,359 Speaker 14: a year for Apple, and that's just one of two 714 00:37:24,440 --> 00:37:26,920 Speaker 14: twenty billion dollar per year potential headwinds. The other is 715 00:37:26,920 --> 00:37:29,040 Speaker 14: the app store. Obviously, the EU is trying to rip 716 00:37:29,160 --> 00:37:31,000 Speaker 14: up the business model there. You have a judge in 717 00:37:31,000 --> 00:37:34,799 Speaker 14: California who ruled that developers can spin users towards the 718 00:37:34,800 --> 00:37:38,120 Speaker 14: web to complete transactions, which obviously means Apple loses it's 719 00:37:38,160 --> 00:37:41,520 Speaker 14: fifteen to thirty percent. So the services business, nearly half 720 00:37:41,560 --> 00:37:44,080 Speaker 14: of it was potentially under fire over the over the 721 00:37:44,080 --> 00:37:46,960 Speaker 14: next twelve months. Now the Google one's resolved, we'll see 722 00:37:46,960 --> 00:37:48,040 Speaker 14: what happens with the app store. 723 00:37:48,520 --> 00:37:51,560 Speaker 1: What's interesting is Judge Meta basically said genera to AI 724 00:37:51,680 --> 00:37:52,799 Speaker 1: has changed the game here. 725 00:37:53,080 --> 00:37:54,680 Speaker 4: Jeneraiti AI is changing the game when. 726 00:37:54,600 --> 00:37:56,800 Speaker 1: It comes to talent, and just talk to us about 727 00:37:56,840 --> 00:38:00,440 Speaker 1: how we really are seeing Apple lose out in that respect. 728 00:38:00,480 --> 00:38:02,480 Speaker 14: It feels like, well, there's a talent war right now 729 00:38:02,520 --> 00:38:04,600 Speaker 14: and Meta is leading the pack. You have Open AI 730 00:38:04,640 --> 00:38:06,560 Speaker 14: and Anthropic in there. They're all trying to hire each 731 00:38:06,560 --> 00:38:10,000 Speaker 14: other's top academics and researchers in the AI space. A 732 00:38:10,000 --> 00:38:12,120 Speaker 14: little edge can do a lot. The big question for 733 00:38:12,160 --> 00:38:14,640 Speaker 14: me is how quickly does this stuff all become commoditized 734 00:38:14,960 --> 00:38:17,960 Speaker 14: and Apple's bed is well pretty soon because they are 735 00:38:18,000 --> 00:38:20,799 Speaker 14: working on some extensive AI partnerships right now, and they've 736 00:38:20,800 --> 00:38:23,040 Speaker 14: been looking at a number of companies to acquire, so 737 00:38:23,080 --> 00:38:24,759 Speaker 14: they believe they're going to play in here too. But 738 00:38:24,880 --> 00:38:27,520 Speaker 14: for now, they're bleeding talent on an almost weekly basis. 739 00:38:27,680 --> 00:38:30,080 Speaker 14: Every two weeks, I have a story coming out between 740 00:38:30,120 --> 00:38:33,240 Speaker 14: two and five different major AI players at Apple leaving 741 00:38:33,239 --> 00:38:36,400 Speaker 14: for Meta. Yesterday, I had a story about four departures 742 00:38:36,440 --> 00:38:38,520 Speaker 14: over the last week or so, including the head of 743 00:38:38,560 --> 00:38:42,320 Speaker 14: AI Robotics research going to Meta to their new robotics department. 744 00:38:42,640 --> 00:38:44,719 Speaker 14: You also have two people going to Open Ai and 745 00:38:44,800 --> 00:38:47,680 Speaker 14: another person going to Anthropic, and a lot of the 746 00:38:47,680 --> 00:38:50,680 Speaker 14: people on Apple's LM team they're interviewing out. So you're 747 00:38:50,680 --> 00:38:52,960 Speaker 14: going to see more departures in the near future, but 748 00:38:53,000 --> 00:38:55,440 Speaker 14: for now, Apples looking at ways to replenish that talent 749 00:38:55,520 --> 00:38:59,319 Speaker 14: pool by buying or partnering mes Monk. 750 00:39:00,040 --> 00:39:03,200 Speaker 3: What is a notable move for Apple of almost three 751 00:39:03,200 --> 00:39:05,440 Speaker 3: percent of Google ruling, But also check out his reporting 752 00:39:05,480 --> 00:39:09,040 Speaker 3: on the talent departures. Another AI story, Open Ai is 753 00:39:09,040 --> 00:39:13,080 Speaker 3: agreed to buy product testing startup Statsig for one point 754 00:39:13,080 --> 00:39:15,279 Speaker 3: one billion dollars in an all stock deal want to 755 00:39:15,280 --> 00:39:18,520 Speaker 3: bring in Bloomberg's AI reporter Rachel Metz. It's not the 756 00:39:18,560 --> 00:39:20,480 Speaker 3: biggest deal that open AI's done. 757 00:39:21,160 --> 00:39:22,400 Speaker 2: It's not small either. 758 00:39:22,560 --> 00:39:25,600 Speaker 3: Why does open ai need statsig? 759 00:39:26,000 --> 00:39:30,520 Speaker 15: Open ai is working to build out its products. It's 760 00:39:30,560 --> 00:39:34,000 Speaker 15: consumer products also, it's B to B products, and this is, 761 00:39:34,440 --> 00:39:36,959 Speaker 15: in the company's view, a really good way to do that. 762 00:39:37,320 --> 00:39:40,640 Speaker 15: They bought this company that helps companies test products that 763 00:39:40,680 --> 00:39:43,080 Speaker 15: could do things like ab testing, so you can have 764 00:39:43,320 --> 00:39:46,759 Speaker 15: people trying out different things with features that you might 765 00:39:46,800 --> 00:39:49,399 Speaker 15: want to launch, and this is something that they see 766 00:39:49,520 --> 00:39:52,320 Speaker 15: as really valuable to the future of products like chat GPT. 767 00:39:52,880 --> 00:39:58,200 Speaker 1: The CEO moves over become CTO of Applications reports into Fijisimo. Rachel, 768 00:39:58,320 --> 00:40:00,440 Speaker 1: What did the deal look like from a talent perspective, 769 00:40:00,520 --> 00:40:03,200 Speaker 1: because they've been getting more and more extraordinary as times 770 00:40:03,239 --> 00:40:04,520 Speaker 1: gone on between AI companies. 771 00:40:05,560 --> 00:40:08,919 Speaker 15: Yeah, so as far as talent, as you mentioned, the 772 00:40:08,960 --> 00:40:12,239 Speaker 15: CEO of statsig is going to take on this new 773 00:40:12,320 --> 00:40:17,080 Speaker 15: role underneath Fijisimo. Figisimo is in charge of opening Eyes 774 00:40:17,719 --> 00:40:22,080 Speaker 15: Applications at this point, and they also it also led 775 00:40:22,120 --> 00:40:24,320 Speaker 15: to a whole bunch of other changes that you see 776 00:40:24,880 --> 00:40:27,200 Speaker 15: that were announced at the same time. Open the eyes 777 00:40:27,560 --> 00:40:30,320 Speaker 15: sort of shuffling around a number of people in management. 778 00:40:30,360 --> 00:40:33,560 Speaker 15: So now the company's going to have two chief technology officers. 779 00:40:33,800 --> 00:40:37,160 Speaker 15: Previously it had one, mirror Marati. She's been gone for 780 00:40:37,160 --> 00:40:39,279 Speaker 15: a while and started her own company. Now they will 781 00:40:39,320 --> 00:40:42,839 Speaker 15: have two, one on the consumer side and one on 782 00:40:42,920 --> 00:40:44,160 Speaker 15: the B to B side. So it's going to be 783 00:40:44,239 --> 00:40:47,200 Speaker 15: interesting to see how those two people are in charge 784 00:40:47,200 --> 00:40:50,520 Speaker 15: of different things, how they all work together, and what 785 00:40:50,560 --> 00:40:52,280 Speaker 15: it means as far as growth in their business. 786 00:40:53,239 --> 00:40:56,400 Speaker 3: Rachel and lots happened in the last month, Like GPT five, 787 00:40:56,840 --> 00:40:58,240 Speaker 3: we have more m and a news. 788 00:40:58,600 --> 00:40:59,879 Speaker 2: We have a lot of talent news. 789 00:41:00,200 --> 00:41:03,040 Speaker 3: Could you just update the audience where open ai currently 790 00:41:03,120 --> 00:41:06,680 Speaker 3: kind of stands in all the chaos of reorgs and newsflow. 791 00:41:08,719 --> 00:41:10,480 Speaker 15: I mean a lot has been a lot has been 792 00:41:10,520 --> 00:41:13,439 Speaker 15: going on, and I suspect we will we will see more. 793 00:41:13,520 --> 00:41:15,360 Speaker 15: I mean we have to remember that this is a 794 00:41:15,400 --> 00:41:18,919 Speaker 15: company that's undergoing a lot of change. It's not a 795 00:41:19,000 --> 00:41:21,360 Speaker 15: young company at this point. I mean it's been around 796 00:41:21,560 --> 00:41:24,960 Speaker 15: for about ten years. However, things have been chanting very 797 00:41:25,040 --> 00:41:29,160 Speaker 15: rapidly over the past few years, and chagbt is continuing 798 00:41:29,200 --> 00:41:31,080 Speaker 15: to grow and grow and grow. It's got over seven 799 00:41:31,160 --> 00:41:34,400 Speaker 15: hundred million users weekly users at this point, so I 800 00:41:34,400 --> 00:41:36,960 Speaker 15: would expect to keep seeing things move around as a 801 00:41:37,040 --> 00:41:39,160 Speaker 15: company continues to try to figure out what's going on, 802 00:41:39,239 --> 00:41:43,240 Speaker 15: and as the industry continues to shift with other companies 803 00:41:43,280 --> 00:41:46,200 Speaker 15: such as Meta, I'm trying to poach people on paying 804 00:41:46,239 --> 00:41:49,560 Speaker 15: extremely large amounts of money for employees. It's going to 805 00:41:49,560 --> 00:41:51,279 Speaker 15: be an interesting ride. 806 00:41:51,160 --> 00:41:53,680 Speaker 1: And we're here for it as a you Rachel Metz, 807 00:41:53,880 --> 00:41:55,799 Speaker 1: so good to have you on on the latest bit 808 00:41:55,840 --> 00:41:57,640 Speaker 1: of M and A and Open AI. I meanwhile, that 809 00:41:57,640 --> 00:42:00,200 Speaker 1: does it for this edition Opening by Tech, But we've 810 00:42:00,200 --> 00:42:01,719 Speaker 1: got to look in at what the market's been up to. 811 00:42:01,880 --> 00:42:03,480 Speaker 4: It has been a bounce back since yesterday. 812 00:42:04,480 --> 00:42:07,560 Speaker 3: Yeah, now's that one hundred bounce back. Whether it's short 813 00:42:07,560 --> 00:42:11,480 Speaker 3: lived or not. Apple and Alphabet the main stories. Apple, 814 00:42:11,680 --> 00:42:13,479 Speaker 3: I think is kind of big, like it's a strong 815 00:42:13,520 --> 00:42:16,600 Speaker 3: reaction on a stop where a standard deviation Okay, forgive 816 00:42:16,640 --> 00:42:19,160 Speaker 3: me that one one sigma move is two percent. We'll 817 00:42:19,239 --> 00:42:21,520 Speaker 3: keep tracking the top story recap on the podcast. We've 818 00:42:21,520 --> 00:42:24,360 Speaker 3: had some absolutely terrific conversations today on what has been 819 00:42:24,640 --> 00:42:28,040 Speaker 3: a massive story from San Francisco and New York. 820 00:42:28,520 --> 00:42:30,239 Speaker 2: This is Bloomberg Tech