1 00:00:01,600 --> 00:00:05,280 Speaker 1: From Mahard where Innovation of Money and Power Collie in 2 00:00:05,360 --> 00:00:10,240 Speaker 1: Silicon Valley, Nbon. This is Bloomberg Technology with Caroline Hyde 3 00:00:10,320 --> 00:00:11,440 Speaker 1: and ed Luod love. 4 00:00:25,440 --> 00:00:27,960 Speaker 2: No from New York and San Francisco. This is Bluemberg Technology. 5 00:00:28,720 --> 00:00:28,880 Speaker 3: ARM. 6 00:00:29,200 --> 00:00:32,720 Speaker 2: It's interested in Intel's product division, but Intel turns down. 7 00:00:32,880 --> 00:00:34,680 Speaker 2: ARMS advances and. 8 00:00:34,720 --> 00:00:36,960 Speaker 4: China stocks in the US are set for their best 9 00:00:36,960 --> 00:00:40,360 Speaker 4: week since twenty twenty two, and money is green. 10 00:00:40,360 --> 00:00:43,160 Speaker 2: When it comes to database and nuclear build out. US 11 00:00:43,280 --> 00:00:47,800 Speaker 2: Energy Secretary Grandhome supports the USAI efforts to expand even 12 00:00:47,960 --> 00:00:51,479 Speaker 2: with foreign investment, and bring you her perspective. But first 13 00:00:51,960 --> 00:00:56,000 Speaker 2: we start with the latest chip story. ARM. We understand 14 00:00:56,000 --> 00:00:59,520 Speaker 2: approaching Intel about potentially buying the chip makers product division, 15 00:00:59,520 --> 00:01:01,480 Speaker 2: only to be told that the business isn't for sale, 16 00:01:01,520 --> 00:01:04,440 Speaker 2: according to a source who points out that ARM didn't 17 00:01:04,480 --> 00:01:09,600 Speaker 2: express interest in Intel's manufacturing operations. Now representatives representatives both 18 00:01:09,680 --> 00:01:12,520 Speaker 2: ARM and Intel declined comment. Let's break it all down, 19 00:01:12,560 --> 00:01:16,640 Speaker 2: Bloomberg Intelligence senior analyst Manley saying, the rationale here for 20 00:01:16,680 --> 00:01:19,760 Speaker 2: a company that designs chips is what Mandy. 21 00:01:21,319 --> 00:01:24,440 Speaker 5: Well. So when you think about you know, Armed, they 22 00:01:24,480 --> 00:01:28,720 Speaker 5: provide the IP blocks, they don't design or manufacture their chips, 23 00:01:28,840 --> 00:01:32,360 Speaker 5: and in this case, look, Intel has a lot of 24 00:01:32,440 --> 00:01:36,600 Speaker 5: IP within the company, it's tied to the X eighty 25 00:01:36,640 --> 00:01:39,600 Speaker 5: six architecture. Obviously ARM has a different architecture. 26 00:01:39,640 --> 00:01:40,679 Speaker 6: But when you think about you. 27 00:01:40,640 --> 00:01:46,319 Speaker 5: Know, alterra side or any other business that's adjacent, that's 28 00:01:46,360 --> 00:01:50,080 Speaker 5: where you know, ARM may be interested in acquiring some 29 00:01:50,160 --> 00:01:54,160 Speaker 5: of that instruction set or adjacent clients, whether it's FPBA 30 00:01:54,360 --> 00:01:55,639 Speaker 5: or something along those lines. 31 00:01:55,640 --> 00:01:58,560 Speaker 4: That will be my guest the mandate we resrate that 32 00:01:58,600 --> 00:02:02,960 Speaker 4: according to this Bloomberg ARMS approach to Intel was rebuffed. 33 00:02:03,240 --> 00:02:04,880 Speaker 7: But it's the same logic with Qualcomm. 34 00:02:05,000 --> 00:02:08,280 Speaker 4: Right, they've had success on ARM based processes, why go 35 00:02:08,360 --> 00:02:12,200 Speaker 4: to X eighty six. I note your colleagues had interesting 36 00:02:12,280 --> 00:02:16,280 Speaker 4: research overnight as well that let's say Intel gets even 37 00:02:16,440 --> 00:02:20,240 Speaker 4: deeper into distress and they start looking at options. How's 38 00:02:20,360 --> 00:02:21,760 Speaker 4: ARM going to finance such a thing? 39 00:02:23,440 --> 00:02:25,280 Speaker 6: Well, I mean, look at ARMS valuation. 40 00:02:25,440 --> 00:02:30,480 Speaker 5: It's creating almost fifty percent above Intel's marketcap. And look 41 00:02:30,520 --> 00:02:33,160 Speaker 5: when you do this some of the parts. Obviously, Intel 42 00:02:33,280 --> 00:02:36,880 Speaker 5: has got a lot more businesses that they could divest, 43 00:02:36,960 --> 00:02:40,119 Speaker 5: but in the case of ARMED, their stock is currently 44 00:02:40,240 --> 00:02:43,400 Speaker 5: at probably the best premium within the semi space. So 45 00:02:43,880 --> 00:02:47,080 Speaker 5: it could be stark. I would imagine, you know, it 46 00:02:47,120 --> 00:02:50,720 Speaker 5: will be a buyout of some of the portion of 47 00:02:50,800 --> 00:02:51,600 Speaker 5: Intel's business. 48 00:02:51,720 --> 00:02:53,400 Speaker 6: So clearly we're talking about a. 49 00:02:53,440 --> 00:02:57,760 Speaker 5: Much smaller pie within Intel that ARM is interested in. 50 00:02:57,760 --> 00:03:00,200 Speaker 5: In the case of Qualcom, I mean they were us 51 00:03:00,200 --> 00:03:03,799 Speaker 5: said at least based on the rumors in the bulk 52 00:03:03,840 --> 00:03:07,280 Speaker 5: of Intel's business. So I think it's a different transaction 53 00:03:07,400 --> 00:03:11,160 Speaker 5: if you are looking at ARM versus Pollcom here and. 54 00:03:11,120 --> 00:03:13,280 Speaker 2: All of this, as we say, thus far has just 55 00:03:13,360 --> 00:03:17,760 Speaker 2: been people familiar, particularly with the Qualcom as you called 56 00:03:17,800 --> 00:03:20,280 Speaker 2: it rumor, but we call reporting. I'm interested in Mandy 57 00:03:20,400 --> 00:03:26,160 Speaker 2: more broadly about how benefits in any scenario here or not, 58 00:03:26,360 --> 00:03:29,240 Speaker 2: as the case may be. What if Intel went with 59 00:03:29,280 --> 00:03:30,880 Speaker 2: a Qualcom, for example. 60 00:03:31,760 --> 00:03:33,800 Speaker 5: Well, in the case of ARM, I mean they are 61 00:03:34,320 --> 00:03:36,640 Speaker 5: at a four billion dollar run rate when you look 62 00:03:36,680 --> 00:03:39,400 Speaker 5: at in VideA, you know, over one hundred billion dollar 63 00:03:39,400 --> 00:03:42,720 Speaker 5: in data center revenue built on ARM designs. So clearly 64 00:03:43,040 --> 00:03:46,200 Speaker 5: ARMED has to find a way to expand into adjacent 65 00:03:46,280 --> 00:03:50,000 Speaker 5: categories without really competing with their customers, which in this 66 00:03:50,080 --> 00:03:53,360 Speaker 5: case are the likes of with Video and Apple. So 67 00:03:53,480 --> 00:03:57,120 Speaker 5: that's where I think the IP blocks are probably the 68 00:03:57,240 --> 00:04:00,120 Speaker 5: right way for them to expand into new categories. And 69 00:04:00,480 --> 00:04:03,640 Speaker 5: I don't think they are getting into design or chip manufacturing. 70 00:04:03,800 --> 00:04:06,840 Speaker 5: I mean that I won't be very well received in 71 00:04:06,880 --> 00:04:07,840 Speaker 5: the market. 72 00:04:08,560 --> 00:04:15,000 Speaker 4: Mandeep Intel seventy percent revenue product, about thirty percent manufacturing 73 00:04:15,360 --> 00:04:19,080 Speaker 4: away from approaches to takeover. There is a plan that 74 00:04:19,120 --> 00:04:23,200 Speaker 4: Gelsinger outlined. What does Bloomberg Intelligence make of that plan? 75 00:04:24,800 --> 00:04:27,960 Speaker 5: Well, not all pieces of the plan are viable, and 76 00:04:28,000 --> 00:04:32,600 Speaker 5: that's where you know, doing foundry manufacturing for chips that 77 00:04:32,680 --> 00:04:36,760 Speaker 5: are outside of Intel is so hard because they have 78 00:04:36,920 --> 00:04:39,800 Speaker 5: that like everyone has that perception that Intel will end 79 00:04:39,880 --> 00:04:41,440 Speaker 5: up competing with their customers. 80 00:04:41,680 --> 00:04:42,799 Speaker 7: That's why the likes. 81 00:04:42,640 --> 00:04:47,000 Speaker 5: Of you know, Nvidia or any server chip maker, it's 82 00:04:47,120 --> 00:04:50,120 Speaker 5: very hard to convince them to use Intel's fabs. So 83 00:04:50,160 --> 00:04:53,039 Speaker 5: that's where the foundry businesses where all the struggles are. 84 00:04:53,440 --> 00:04:56,040 Speaker 5: I do think the PC business will come back because 85 00:04:56,240 --> 00:04:58,880 Speaker 5: X eighty six still has a mode and when there 86 00:04:58,960 --> 00:05:01,520 Speaker 5: is a PC repairs se that's the one part of 87 00:05:01,560 --> 00:05:04,400 Speaker 5: the business that will recover nicely. So I'm betting on 88 00:05:04,440 --> 00:05:06,880 Speaker 5: the PC side. We just have to figure out how 89 00:05:06,880 --> 00:05:09,000 Speaker 5: to catch up on the server side, and obviously on 90 00:05:09,040 --> 00:05:12,960 Speaker 5: the foundary side, they really need to partner with hyperscalers 91 00:05:13,000 --> 00:05:15,400 Speaker 5: to improve the margin profile. 92 00:05:15,080 --> 00:05:16,280 Speaker 7: Of their business. 93 00:05:16,680 --> 00:05:20,119 Speaker 4: Bloomberg Intelligence analyst man Deep Singh, thank you very much. 94 00:05:20,200 --> 00:05:24,080 Speaker 4: Now sticking with semiconductors, Tokyo Electron seeks to build a 95 00:05:24,080 --> 00:05:27,760 Speaker 4: team of chip engineers in India to better ride the 96 00:05:27,800 --> 00:05:32,159 Speaker 4: Modi government's push for more semiconductor manufacturing. In an exclusive 97 00:05:32,200 --> 00:05:35,960 Speaker 4: interview with Bloomberg, Tokyo Electron CEO said the company plans 98 00:05:36,000 --> 00:05:39,000 Speaker 4: to hire and train local engineers in or around twenty 99 00:05:39,040 --> 00:05:43,080 Speaker 4: twenty six, with their first task to provide technical services 100 00:05:43,200 --> 00:05:46,360 Speaker 4: to Tata Electronics. He also spoke about where he sees 101 00:05:46,440 --> 00:05:48,640 Speaker 4: AI demand going in the years to come. 102 00:05:48,680 --> 00:05:49,360 Speaker 7: Listen to this. 103 00:05:51,200 --> 00:05:51,680 Speaker 8: Demo. A. 104 00:05:52,440 --> 00:05:54,640 Speaker 9: I think the market has just crossed the threshold of 105 00:05:54,720 --> 00:05:57,960 Speaker 9: the second phase of AI. Our projection is that overall 106 00:05:58,040 --> 00:06:00,320 Speaker 9: chip demand will double in the next five year is 107 00:06:00,600 --> 00:06:04,240 Speaker 9: to a trillion dollars in twenty thirty, boosted by artificial 108 00:06:04,240 --> 00:06:09,440 Speaker 9: intelligence as well as augmented reality, virtual reality and autonomous driving. 109 00:06:10,839 --> 00:06:14,400 Speaker 2: Meanwhile, Chinese equities kept their biggest weekly rally since two 110 00:06:14,440 --> 00:06:17,200 Speaker 2: thousand and eight. Well they burst of trading that overwhelmed 111 00:06:17,240 --> 00:06:20,599 Speaker 2: the Shanghai Stock Exchange, underscoring a shift in investor sentiment 112 00:06:20,920 --> 00:06:23,800 Speaker 2: of course, after Beijing ramped up its economic stimulus, and 113 00:06:23,960 --> 00:06:26,159 Speaker 2: the shift has been felt in Chinese stocks in the 114 00:06:26,240 --> 00:06:28,720 Speaker 2: US as well, where they're set for their best week 115 00:06:28,760 --> 00:06:33,920 Speaker 2: since twenty twenty two. Bloomberg's Emini Grafeo joins US for more. 116 00:06:34,720 --> 00:06:37,719 Speaker 2: Now we're seeing some real risk on Is there a 117 00:06:37,760 --> 00:06:41,200 Speaker 2: fomo trade going on here? As David Tepp has been outlining. 118 00:06:40,680 --> 00:06:42,720 Speaker 8: I think there absolutely is, But we have to remember 119 00:06:42,800 --> 00:06:45,279 Speaker 8: that when you kind of zoom out here, a lot 120 00:06:45,320 --> 00:06:48,120 Speaker 8: of these US listed Chinese stocks are still in negative 121 00:06:48,200 --> 00:06:52,000 Speaker 8: territory on a one to three and five year basis, 122 00:06:52,040 --> 00:06:55,360 Speaker 8: something like you know, Black Rocks, China, ETF. It's still 123 00:06:55,400 --> 00:06:58,880 Speaker 8: a negative territory. But at least for this week, it's 124 00:06:58,880 --> 00:07:01,560 Speaker 8: been an incredible week. And you do have David Tepper 125 00:07:01,600 --> 00:07:04,680 Speaker 8: coming in saying he's going longer on China stocks after 126 00:07:05,040 --> 00:07:08,080 Speaker 8: the both monetary and fiscal stimulus. He said he's snapping 127 00:07:08,160 --> 00:07:11,360 Speaker 8: up shares of Ali Baba and by Do on valuation 128 00:07:11,560 --> 00:07:15,360 Speaker 8: still being low even after these weeks like double digit 129 00:07:15,440 --> 00:07:18,680 Speaker 8: gains in these stocks, and we're also one of the 130 00:07:18,680 --> 00:07:21,680 Speaker 8: most read stories quant hedge funds in China have shorted 131 00:07:21,760 --> 00:07:24,720 Speaker 8: that have shorted Index futures have seen heavy losses this week. 132 00:07:24,720 --> 00:07:27,280 Speaker 8: If you look at a chart of the CSI three 133 00:07:27,400 --> 00:07:30,680 Speaker 8: hundred index and what it's done this week literally a 134 00:07:30,840 --> 00:07:35,440 Speaker 8: horizontal line or a vertical line up, and that has 135 00:07:35,480 --> 00:07:39,000 Speaker 8: really kind of hammered these quant hedge funds that have 136 00:07:39,080 --> 00:07:40,440 Speaker 8: been going short these funds. 137 00:07:40,480 --> 00:07:44,560 Speaker 7: But it's been an incredible week. Yeah, that is vertical 138 00:07:44,600 --> 00:07:46,640 Speaker 7: life crazy, look at that. 139 00:07:46,760 --> 00:07:52,320 Speaker 4: Indeed, Bloomberg Technology loves charts, Emily Graffeo loves charts. 140 00:07:52,720 --> 00:07:54,320 Speaker 7: But why is it so crazy? 141 00:07:54,440 --> 00:07:58,080 Speaker 4: I mean, what is the factors behind the volatility? 142 00:07:58,160 --> 00:08:00,480 Speaker 7: I guess you know to the upside in the case. 143 00:08:00,880 --> 00:08:04,200 Speaker 8: Well, so earlier this week, we had kind of the 144 00:08:04,280 --> 00:08:07,720 Speaker 8: Chinese government coming in finally after kind of refusing to 145 00:08:07,800 --> 00:08:10,840 Speaker 8: bring in stimulus, and they brought in stimulus not just 146 00:08:10,920 --> 00:08:13,560 Speaker 8: on the fiscal side, but also on the monetary side, 147 00:08:13,560 --> 00:08:17,080 Speaker 8: and it continued all week. Just earlier in the week, 148 00:08:17,120 --> 00:08:21,160 Speaker 8: we had seen that the Chinese central banks kind of 149 00:08:21,200 --> 00:08:24,760 Speaker 8: pull back the reserve requirements for banks, so on both 150 00:08:24,760 --> 00:08:27,400 Speaker 8: the monetary and the fiscal side. It was a stimulus 151 00:08:27,440 --> 00:08:31,160 Speaker 8: that investors had been not seeing all year, and that's 152 00:08:31,160 --> 00:08:34,120 Speaker 8: why you had seen those stock market losses all year 153 00:08:34,400 --> 00:08:36,400 Speaker 8: and now when you look at the CSI three hundred, 154 00:08:36,840 --> 00:08:41,040 Speaker 8: the mainland shares, they've erased all the losses for the year. 155 00:08:41,120 --> 00:08:43,840 Speaker 8: So it's all around been kind of investors reacting to 156 00:08:43,880 --> 00:08:46,000 Speaker 8: the macro news. And now it seems like there's kind 157 00:08:46,000 --> 00:08:48,720 Speaker 8: of this momentum trade as the quant hedge funds that 158 00:08:48,720 --> 00:08:50,840 Speaker 8: were short get kicked out, we're seeing a little bit 159 00:08:50,840 --> 00:08:52,920 Speaker 8: of a short squeeze. I mean, I think that chart 160 00:08:53,080 --> 00:08:55,120 Speaker 8: just speaks for itself. 161 00:08:55,040 --> 00:08:55,880 Speaker 2: About the momentum. 162 00:08:55,920 --> 00:08:57,800 Speaker 8: We'll have to see if it continues, because there have 163 00:08:57,920 --> 00:09:02,080 Speaker 8: been some kind of like surprise rallies that don't always 164 00:09:02,080 --> 00:09:04,360 Speaker 8: hold up. And the markets are off next week for 165 00:09:04,400 --> 00:09:05,959 Speaker 8: the holiday, so good point. 166 00:09:06,000 --> 00:09:10,080 Speaker 2: Great context. Also context is reten investors are interesting in 167 00:09:10,080 --> 00:09:10,800 Speaker 2: the Chinese space. 168 00:09:10,920 --> 00:09:13,160 Speaker 8: Yeah, and they've been crushed at least just looking at 169 00:09:13,240 --> 00:09:17,080 Speaker 8: the ETF flows. I go back to MCCHI. That's the 170 00:09:17,120 --> 00:09:22,839 Speaker 8: ticker of the Blackrock China ETF, which we've seen flows into, 171 00:09:22,880 --> 00:09:26,559 Speaker 8: and oftentimes in ETF world, the flows follow the performance, 172 00:09:26,760 --> 00:09:29,640 Speaker 8: so people see these big rallies and then they flow 173 00:09:29,679 --> 00:09:32,080 Speaker 8: in and they kind of miss the top of that trade. 174 00:09:32,120 --> 00:09:34,720 Speaker 8: So we've seen that happen in this particular ETF just 175 00:09:34,800 --> 00:09:37,440 Speaker 8: over the years and again it's still down on the year, 176 00:09:37,520 --> 00:09:37,960 Speaker 8: two year. 177 00:09:37,920 --> 00:09:38,720 Speaker 2: Five year basis. 178 00:09:38,720 --> 00:09:40,880 Speaker 8: So even though there's a big rally today, I think 179 00:09:40,920 --> 00:09:42,720 Speaker 8: a lot of investors have been in the trade for 180 00:09:42,760 --> 00:09:46,440 Speaker 8: a while are still feeling like this is not good enough. 181 00:09:47,800 --> 00:09:52,360 Speaker 7: Bloomberg's Emily Graffair bringing us crazy charts. Thank you, Happy Friday. 182 00:09:52,400 --> 00:09:54,280 Speaker 4: I want to keep the discussion going with City Index 183 00:09:54,320 --> 00:09:58,840 Speaker 4: senior analysts Fionas and Kota, And it's kind of simple story, right, 184 00:09:59,040 --> 00:10:04,199 Speaker 4: Chinese governments, stimulus and those kind of more downtrodden consumer 185 00:10:04,280 --> 00:10:09,920 Speaker 4: facing Chinese technology companies react, particularly the ADRs. How many 186 00:10:09,920 --> 00:10:11,960 Speaker 4: phone calls have you had across your desk this week 187 00:10:12,000 --> 00:10:14,920 Speaker 4: about China and that corner of the market. 188 00:10:15,920 --> 00:10:18,960 Speaker 10: Ah, huge. I mean that's been the main story this week. 189 00:10:19,040 --> 00:10:22,560 Speaker 1: It's followed on as well, obviously from the Federal Reserve 190 00:10:22,679 --> 00:10:26,920 Speaker 1: the previous week, so we've quickly swung attention over to 191 00:10:27,080 --> 00:10:29,160 Speaker 1: China and as you said, those ADRs. 192 00:10:29,160 --> 00:10:31,000 Speaker 10: I mean, we've seen some phenomenal moods. 193 00:10:31,400 --> 00:10:33,640 Speaker 1: Just take for example JD dot Com that's up thirty 194 00:10:33,679 --> 00:10:36,839 Speaker 1: four percent this week, up nine percent today. I mean, 195 00:10:36,880 --> 00:10:39,679 Speaker 1: we've seen some really strong moods and the market's been 196 00:10:39,800 --> 00:10:42,319 Speaker 1: when investors have been keen to pick up on those, 197 00:10:42,559 --> 00:10:46,959 Speaker 1: especially given the sort of downbeat mood that they had been. 198 00:10:46,840 --> 00:10:49,360 Speaker 10: Towards China prior to this week. 199 00:10:49,400 --> 00:10:52,720 Speaker 1: You know, there's really had been that sense that Beijing 200 00:10:53,040 --> 00:10:55,280 Speaker 1: wasn't going to get its act together to really. 201 00:10:55,040 --> 00:10:57,679 Speaker 10: Pull out that that bazooka type. 202 00:10:59,040 --> 00:11:02,800 Speaker 1: Sized a stimulus that the market was actually looking for. 203 00:11:03,080 --> 00:11:05,280 Speaker 1: And this week we actually got a sense that perhaps 204 00:11:05,360 --> 00:11:07,360 Speaker 1: that's actually going to be happening. 205 00:11:07,440 --> 00:11:08,440 Speaker 10: That's what we've seen. 206 00:11:08,840 --> 00:11:11,080 Speaker 1: I mean, the big question here, I think now is 207 00:11:11,080 --> 00:11:14,199 Speaker 1: is this a stabilization move or is this something that 208 00:11:14,240 --> 00:11:18,360 Speaker 1: we're going to see you know, the Chinese authorities really 209 00:11:18,400 --> 00:11:20,280 Speaker 1: support going through the rest of the year. 210 00:11:21,559 --> 00:11:24,040 Speaker 4: If you're just joining us here on Bloomberg Technology, our 211 00:11:24,040 --> 00:11:28,720 Speaker 4: top tech story today is a Bloomberg report that arm 212 00:11:28,760 --> 00:11:31,960 Speaker 4: made an approach to Intel that Intel rebuffed, all according 213 00:11:32,000 --> 00:11:35,040 Speaker 4: to a single source. When you woke up to that 214 00:11:35,080 --> 00:11:39,120 Speaker 4: news this morning, Fiona, what was your reaction, Well. 215 00:11:38,840 --> 00:11:41,679 Speaker 1: I mean Intel's definitely been in the news, hasn't it 216 00:11:41,800 --> 00:11:44,200 Speaker 1: this week? I mean, you know what, this is a 217 00:11:43,840 --> 00:11:48,480 Speaker 1: stock that's really down in the doldrums. It's really been struggling. 218 00:11:49,280 --> 00:11:53,400 Speaker 1: It's obviously been approached by several suitors and. 219 00:11:53,280 --> 00:11:54,680 Speaker 10: This is just the latest now. 220 00:11:54,800 --> 00:11:56,720 Speaker 1: I mean, it all seems a little bit murky and 221 00:11:57,400 --> 00:12:00,560 Speaker 1: unknown where this might be going as far as we 222 00:12:00,679 --> 00:12:04,839 Speaker 1: know that there, it's not moving forward yet. But I think, 223 00:12:04,880 --> 00:12:07,280 Speaker 1: you know, if we consider what's happened to the valuation 224 00:12:07,920 --> 00:12:11,200 Speaker 1: of Intel, obviously down in the dumps right now, and 225 00:12:11,240 --> 00:12:14,520 Speaker 1: it doesn't really look like the turnaround plan is really 226 00:12:14,520 --> 00:12:16,000 Speaker 1: going to do the job that it needs to. 227 00:12:16,120 --> 00:12:18,920 Speaker 10: So that does mean that Intel remains vulnerable. 228 00:12:19,480 --> 00:12:21,960 Speaker 2: We're showing a long term year to day hhart down 229 00:12:22,040 --> 00:12:24,880 Speaker 2: fifty two percent. I want to take that step back, Fiona, 230 00:12:24,920 --> 00:12:29,200 Speaker 2: because it is extraordinary that the icon, one of the 231 00:12:29,520 --> 00:12:32,559 Speaker 2: icons of chip making, would ever be being discussed as 232 00:12:32,600 --> 00:12:38,280 Speaker 2: an acquisition or merger target, Intel, of all names. Fiona, 233 00:12:38,320 --> 00:12:42,079 Speaker 2: how much does that sharpen your investors' minds that this 234 00:12:42,160 --> 00:12:44,920 Speaker 2: current move of AI is so swift you've got to 235 00:12:44,920 --> 00:12:45,600 Speaker 2: be on top of it. 236 00:12:46,640 --> 00:12:48,640 Speaker 10: Yeah, that's a really good point. And I mean, you know, 237 00:12:48,679 --> 00:12:49,680 Speaker 10: if we just think. 238 00:12:49,480 --> 00:12:54,520 Speaker 1: About where Intel was compared to for example, it's appears, 239 00:12:55,320 --> 00:12:59,520 Speaker 1: you know, it was always the riding high, the strong horsemen, 240 00:12:59,840 --> 00:13:01,400 Speaker 1: and that's no longer the case. 241 00:13:01,400 --> 00:13:05,079 Speaker 10: And it has been a relatively rapid decline. 242 00:13:04,559 --> 00:13:07,280 Speaker 1: This year as you pointed out, you know, fifty percent 243 00:13:07,360 --> 00:13:09,800 Speaker 1: of its value lost, and at the same time we've 244 00:13:09,840 --> 00:13:14,440 Speaker 1: seen a huge rally in the valuations of those more 245 00:13:14,480 --> 00:13:17,719 Speaker 1: AI focused stocks, and so that just really highlights that 246 00:13:17,800 --> 00:13:21,120 Speaker 1: point that, you know, this AI trade, it's a rapid 247 00:13:21,200 --> 00:13:23,040 Speaker 1: moving one and you have to be on the ball 248 00:13:23,080 --> 00:13:25,439 Speaker 1: with it. And you know what I think as Intel's 249 00:13:25,559 --> 00:13:28,680 Speaker 1: just lost the edge as far as its tech edge 250 00:13:28,720 --> 00:13:31,160 Speaker 1: is concerned. It's just losing the ball there, and that 251 00:13:31,240 --> 00:13:33,480 Speaker 1: really obviously hasn't helped the share price at all. 252 00:13:33,960 --> 00:13:38,440 Speaker 2: Therefore, your clients, do they want single name exposure, do 253 00:13:38,480 --> 00:13:41,040 Speaker 2: they want to be stop players in this market? Stop pickers, 254 00:13:41,160 --> 00:13:42,880 Speaker 2: or do they want to go broader? They don't want 255 00:13:42,880 --> 00:13:46,360 Speaker 2: to have index exposure so they don't get caught out 256 00:13:46,480 --> 00:13:47,280 Speaker 2: if the wind turns. 257 00:13:48,320 --> 00:13:50,679 Speaker 1: Yeah, do you know we have seen a lot of 258 00:13:51,600 --> 00:13:57,439 Speaker 1: preferential preference towards index stocks just for exactly inducey is sorry, 259 00:13:57,559 --> 00:14:00,240 Speaker 1: just for that reason, in order to be able to 260 00:14:00,320 --> 00:14:04,200 Speaker 1: mitigate risk. There is always that concern of being caught out. Now, 261 00:14:04,200 --> 00:14:08,480 Speaker 1: obviously there are some favorites where our traders and our 262 00:14:08,559 --> 00:14:10,800 Speaker 1: investors are sort of, you know, happy to go into 263 00:14:10,800 --> 00:14:14,760 Speaker 1: the single stocks, but more broadly speaking, we have seen. 264 00:14:14,559 --> 00:14:16,040 Speaker 10: More of a focus on. 265 00:14:17,720 --> 00:14:20,040 Speaker 1: Indices and that also allows for when we sort of 266 00:14:20,080 --> 00:14:23,440 Speaker 1: move towards rotations. You know, I think, particularly with what's 267 00:14:23,480 --> 00:14:25,920 Speaker 1: going on with China this week and what we've seen 268 00:14:26,600 --> 00:14:29,520 Speaker 1: of those concerns in the US previously about sort of 269 00:14:29,560 --> 00:14:32,960 Speaker 1: you know, moving towards the potential hard landing in some 270 00:14:33,040 --> 00:14:35,960 Speaker 1: cases with the weaker than expected job later at the 271 00:14:35,960 --> 00:14:36,800 Speaker 1: start of the summer. 272 00:14:37,000 --> 00:14:39,720 Speaker 10: You know that idea that we might see rotation. 273 00:14:39,520 --> 00:14:42,200 Speaker 1: If you're in an index, that does allow you to 274 00:14:42,280 --> 00:14:45,920 Speaker 1: benefit from those rotations potentially out of tech into EM's 275 00:14:46,200 --> 00:14:50,080 Speaker 1: assets or out of tech into for example, more defensive stocks. 276 00:14:50,120 --> 00:14:53,520 Speaker 10: If we find that the data goes the wrong way, well. 277 00:14:53,480 --> 00:14:56,160 Speaker 2: Data going the right way. On CPI today, City Index 278 00:14:56,240 --> 00:14:59,680 Speaker 2: Senior Analyst Fiona Sincotta, thank you for joining us. Coming up, 279 00:15:00,080 --> 00:15:03,240 Speaker 2: Morale at Germany's largest company is plunging as it goes 280 00:15:03,240 --> 00:15:06,680 Speaker 2: through a major restructuring plan. Details on SAPNX. This is 281 00:15:06,720 --> 00:15:20,600 Speaker 2: Blue Meg Technology. An internal survey shows how morale has 282 00:15:20,720 --> 00:15:25,000 Speaker 2: plunged at Germany's most valuable company, SAP. Only thirty eight 283 00:15:25,040 --> 00:15:28,400 Speaker 2: percent of employees have full trust in the software firm, 284 00:15:28,720 --> 00:15:30,800 Speaker 2: but you never know it as a shareholder look. The 285 00:15:30,840 --> 00:15:33,840 Speaker 2: stock a surge to a record high this year. Bloomberg's 286 00:15:33,880 --> 00:15:36,880 Speaker 2: Jake Ridinski joins us for more. So, what is grinding 287 00:15:36,880 --> 00:15:37,600 Speaker 2: on the employees? 288 00:15:37,680 --> 00:15:39,960 Speaker 7: Jake Well, I think. 289 00:15:39,880 --> 00:15:43,320 Speaker 3: Part of what since shares soaring is the fact that 290 00:15:43,320 --> 00:15:46,800 Speaker 3: they've dot this massive restructuring plan going on at SAP 291 00:15:47,320 --> 00:15:50,320 Speaker 3: that's going to affect about one in ten of workers. 292 00:15:50,840 --> 00:15:53,680 Speaker 3: So you can imagine if you're being forced to be 293 00:15:53,680 --> 00:15:59,760 Speaker 3: either retrained or potentially laid off, you'd not be a. 294 00:15:59,760 --> 00:16:04,600 Speaker 11: Pick that the management's doing doing a great job. This 295 00:16:04,680 --> 00:16:07,080 Speaker 11: is this is the lowest we've We've been tracking this 296 00:16:07,160 --> 00:16:09,200 Speaker 11: number for about three years, and this is the lowest 297 00:16:09,200 --> 00:16:14,440 Speaker 11: since twenty twenty one, So it's it's clear that, you know, 298 00:16:16,120 --> 00:16:18,560 Speaker 11: employees are quite worried about their future at I say, 299 00:16:18,840 --> 00:16:20,960 Speaker 11: despite the really high share price. 300 00:16:22,040 --> 00:16:24,760 Speaker 4: The restructuring was announced in January, and like all software 301 00:16:24,800 --> 00:16:26,800 Speaker 4: companies around the world, it's a pivot to AI. 302 00:16:27,440 --> 00:16:28,440 Speaker 7: I guess there might be. 303 00:16:28,360 --> 00:16:31,600 Speaker 4: A cultural difference between where I am in Silicon Valley 304 00:16:31,600 --> 00:16:34,000 Speaker 4: and where you are in Germany and Europe. And is 305 00:16:34,000 --> 00:16:37,160 Speaker 4: it stock comp like if the stock is doing what 306 00:16:37,160 --> 00:16:40,400 Speaker 4: we're showing on the screen, are don't the employees happy? 307 00:16:40,480 --> 00:16:42,320 Speaker 4: Because they're going along for the ride. 308 00:16:43,960 --> 00:16:45,840 Speaker 11: Well, this is a survey of kind of the rank 309 00:16:45,880 --> 00:16:48,680 Speaker 11: and file employees. So I think a lot of these 310 00:16:48,680 --> 00:16:52,360 Speaker 11: guys are not not really getting getting much in the 311 00:16:52,400 --> 00:16:56,960 Speaker 11: way of conversation from from the strange spit share prices, 312 00:16:58,160 --> 00:17:02,240 Speaker 11: so that also, I imagine would influence how they feel 313 00:17:02,280 --> 00:17:05,480 Speaker 11: about the company. Maybe maybe you see the company's share 314 00:17:05,520 --> 00:17:07,960 Speaker 11: pace storing and piguing. Why am I not getting a raise? 315 00:17:09,600 --> 00:17:12,080 Speaker 4: Invokes Jake Ridinsky. Great to have you on from Germany, 316 00:17:12,119 --> 00:17:13,080 Speaker 4: Thank you very much. 317 00:17:20,680 --> 00:17:23,920 Speaker 2: On Thursday, I caught up with Energy Secretory Jennifer Grahholm 318 00:17:24,119 --> 00:17:27,000 Speaker 2: in Washington at a conference hosted by the Special Competitive 319 00:17:27,040 --> 00:17:30,480 Speaker 2: Studies Project. I asked her about well Open AI CEO 320 00:17:30,560 --> 00:17:33,439 Speaker 2: Sam Altman's efforts to raise a lot of money overseas 321 00:17:33,840 --> 00:17:37,199 Speaker 2: for costly AI infrastructure projects in the United States and 322 00:17:37,240 --> 00:17:39,600 Speaker 2: if there should be any concerns. Here's what she had 323 00:17:39,600 --> 00:17:39,920 Speaker 2: to say. 324 00:17:40,600 --> 00:17:43,720 Speaker 12: Money is green, but I do think it's important to 325 00:17:45,440 --> 00:17:49,440 Speaker 12: have you know, what's the access I guess for those 326 00:17:49,480 --> 00:17:55,200 Speaker 12: who are funding two very sensitive IP right, I mean 327 00:17:55,240 --> 00:18:00,800 Speaker 12: these advanced chips are you know, the g pus for 328 00:18:01,280 --> 00:18:05,480 Speaker 12: AI can be used for a variety of things, and 329 00:18:05,520 --> 00:18:07,680 Speaker 12: we want them to be used in the right way, 330 00:18:07,720 --> 00:18:10,119 Speaker 12: and so does the funder Does that mean you get 331 00:18:10,200 --> 00:18:13,479 Speaker 12: access to the IP that's a question. But but we 332 00:18:13,520 --> 00:18:15,760 Speaker 12: want these data centers built in the US, as I mentioned, 333 00:18:15,800 --> 00:18:19,840 Speaker 12: So however they get funded, as long as that there's 334 00:18:19,880 --> 00:18:22,800 Speaker 12: some boundaries on it, I think it's perfectly fine. 335 00:18:23,359 --> 00:18:26,520 Speaker 2: Money is green. However, I followed up by asking if 336 00:18:26,520 --> 00:18:29,600 Speaker 2: there's any more regulation of AI in general needed his 337 00:18:29,680 --> 00:18:30,600 Speaker 2: her response. 338 00:18:30,880 --> 00:18:34,800 Speaker 12: It's about national security, but it's also about competition, right. 339 00:18:34,880 --> 00:18:38,640 Speaker 12: We want to we want to lead the world in 340 00:18:38,640 --> 00:18:41,800 Speaker 12: in AI, and we are and we want it to 341 00:18:41,800 --> 00:18:45,520 Speaker 12: stay that way, and so we don't want to, you know, 342 00:18:45,640 --> 00:18:49,800 Speaker 12: we don't want to create constraints on that. However, we 343 00:18:49,840 --> 00:18:54,760 Speaker 12: recognize that un constrained AI could also be used in 344 00:18:54,800 --> 00:18:57,000 Speaker 12: a very negative way, and so we want to we 345 00:18:57,040 --> 00:18:58,560 Speaker 12: want to channel that in the right direction. 346 00:19:00,359 --> 00:19:03,680 Speaker 4: Sticking in the realm of hardware and AI, Meta unveiled 347 00:19:03,760 --> 00:19:07,280 Speaker 4: new models of its Quest headset and Meta Connect on Wednesday, 348 00:19:07,280 --> 00:19:11,080 Speaker 4: but also it's augmented reality glass is called Ohryan. 349 00:19:11,200 --> 00:19:13,399 Speaker 7: I sat down with metas CTO. 350 00:19:13,080 --> 00:19:17,080 Speaker 4: Andrew Bosworth to discuss the technology behind those glasses and 351 00:19:17,119 --> 00:19:18,959 Speaker 4: how the company plans to expand on it. 352 00:19:19,040 --> 00:19:19,560 Speaker 7: Listen to this. 353 00:19:20,320 --> 00:19:23,280 Speaker 13: We already have the next two products in development based 354 00:19:23,320 --> 00:19:27,040 Speaker 13: on the technology we developed for Oryan, and we think 355 00:19:27,080 --> 00:19:29,560 Speaker 13: this is just a proof of how exciting the future 356 00:19:29,640 --> 00:19:32,080 Speaker 13: is going to be as these technologies become consumer ready. 357 00:19:32,640 --> 00:19:34,760 Speaker 4: You may or may not guess, so you know, speak 358 00:19:34,840 --> 00:19:37,199 Speaker 4: some of the team and know that that's part of 359 00:19:37,200 --> 00:19:40,879 Speaker 4: the origin story. My understanding is that this is a 360 00:19:41,040 --> 00:19:44,520 Speaker 4: future behavioral change that humans have to make right right now. 361 00:19:44,560 --> 00:19:47,080 Speaker 4: I have a smartphone, I have a laptop, and that's 362 00:19:47,080 --> 00:19:49,400 Speaker 4: the price point you want to come in at. One 363 00:19:49,480 --> 00:19:53,439 Speaker 4: day a Ryan or its next generation sibling will be 364 00:19:53,560 --> 00:19:55,320 Speaker 4: priced to the high end laptop PC. 365 00:19:56,440 --> 00:19:57,960 Speaker 7: What is that price point? 366 00:19:58,000 --> 00:20:00,800 Speaker 4: And is you know, give me something here, you know, 367 00:20:00,880 --> 00:20:02,879 Speaker 4: will I be coming back to Menlo in ten years 368 00:20:02,880 --> 00:20:06,280 Speaker 4: and finally looking at it in a consumer form or 369 00:20:06,359 --> 00:20:08,080 Speaker 4: is it something more real than. 370 00:20:07,960 --> 00:20:11,120 Speaker 13: That long before ten years. Yeah, I think we're more 371 00:20:11,160 --> 00:20:13,919 Speaker 13: than one year away, less than ten years away. But 372 00:20:14,000 --> 00:20:16,359 Speaker 13: we have a very clear line of sight to a 373 00:20:16,359 --> 00:20:17,159 Speaker 13: consumer product. 374 00:20:17,320 --> 00:20:18,560 Speaker 7: The price isn't clear to us yet. 375 00:20:18,600 --> 00:20:20,280 Speaker 13: One of the big things going from a prototype like 376 00:20:20,320 --> 00:20:23,080 Speaker 13: this is understanding what can we learn that allows us 377 00:20:23,119 --> 00:20:25,440 Speaker 13: to simplify or what do we need to keep in 378 00:20:25,600 --> 00:20:28,399 Speaker 13: future designs and that's going to control where the price lands. 379 00:20:28,640 --> 00:20:30,680 Speaker 13: But we really want to get this into a price 380 00:20:30,720 --> 00:20:32,679 Speaker 13: point of form factor that not just consumers use it, 381 00:20:32,720 --> 00:20:34,240 Speaker 13: but developers want to build for it. 382 00:20:34,359 --> 00:20:37,800 Speaker 4: The breakthrough in technology is actually in a material silicon 383 00:20:37,880 --> 00:20:40,920 Speaker 4: carbide that allows for all of this in the lenses. 384 00:20:41,280 --> 00:20:43,760 Speaker 7: How does the supply chain look like a silicon carbide 385 00:20:43,800 --> 00:20:45,440 Speaker 7: for somebody that wants to do consume attach. 386 00:20:45,600 --> 00:20:47,840 Speaker 13: Yeah, silicon carbide was you know, the first place we 387 00:20:47,920 --> 00:20:52,520 Speaker 13: looked for super high indexed glass that's refractive and that's 388 00:20:52,520 --> 00:20:55,000 Speaker 13: really important for what we do for these lenses. I 389 00:20:55,040 --> 00:20:57,439 Speaker 13: will say it's an incredibly difficult material to produce and 390 00:20:57,520 --> 00:20:59,479 Speaker 13: to work with, and so we are also looking at 391 00:20:59,560 --> 00:21:02,440 Speaker 13: multiple materials that we could use to replicate this functionality 392 00:21:02,720 --> 00:21:04,879 Speaker 13: and again at a hopefully more competitive price point. 393 00:21:06,240 --> 00:21:09,359 Speaker 7: That was meta CTO Andrew Bosworth. 394 00:21:16,280 --> 00:21:18,720 Speaker 2: Welcome back to Bluebog Technology and Caroline Hyde in. 395 00:21:18,600 --> 00:21:21,280 Speaker 7: New York in San Francisco. 396 00:21:21,480 --> 00:21:24,840 Speaker 2: Quick check on these markets, because well, we have had 397 00:21:24,920 --> 00:21:27,760 Speaker 2: a strong week not only for the NASDAK and the 398 00:21:27,800 --> 00:21:30,600 Speaker 2: text talks, but also for some other risk assets. Bitcoin 399 00:21:30,680 --> 00:21:33,240 Speaker 2: on Fire are up another five percent for the week, 400 00:21:33,359 --> 00:21:36,000 Speaker 2: and we're seeing basically the highest since July of this year, 401 00:21:36,000 --> 00:21:38,320 Speaker 2: but we're also seeing the highest of July this year 402 00:21:38,400 --> 00:21:40,920 Speaker 2: for the NASDAK two three straight weeks of gains. Move 403 00:21:40,960 --> 00:21:42,840 Speaker 2: on and have a look at what ultimately the risk 404 00:21:42,880 --> 00:21:45,679 Speaker 2: on action means for individual names. Looking at micro strategy 405 00:21:45,760 --> 00:21:48,399 Speaker 2: to the higher side. Add surprisingly with Crypto moving and 406 00:21:48,440 --> 00:21:51,119 Speaker 2: managing to have a really good month of September in general, 407 00:21:51,440 --> 00:21:56,440 Speaker 2: PDD extraordinary week, biggest move on record for these ADRs 408 00:21:56,520 --> 00:21:58,639 Speaker 2: those names that are traded here in the United States. 409 00:21:58,640 --> 00:22:01,479 Speaker 2: Of course, why well, all of that money being pumped 410 00:22:01,480 --> 00:22:04,680 Speaker 2: into Chinese economy means good news for the Chinese stocks 411 00:22:04,720 --> 00:22:08,040 Speaker 2: I signal one out here. Meanwhile, Intel on the downside 412 00:22:08,040 --> 00:22:10,000 Speaker 2: now off by four tens percent, following the rest of 413 00:22:10,000 --> 00:22:12,359 Speaker 2: the socks and the chip industry more broadly well, once 414 00:22:12,400 --> 00:22:16,240 Speaker 2: again being sniffed around by various competitors or frenemies in 415 00:22:16,240 --> 00:22:19,400 Speaker 2: the space. This time aren't potentially analyzing and being rebuffed 416 00:22:19,440 --> 00:22:22,200 Speaker 2: according to sources, but Intel currently to the lower side. 417 00:22:22,320 --> 00:22:24,040 Speaker 2: Ed what if you've got Let's. 418 00:22:23,880 --> 00:22:25,520 Speaker 7: Go to another top story out of Europe. 419 00:22:25,560 --> 00:22:30,160 Speaker 4: Amazon's four billion dollar investment pack with Aifirmanthropic was cleared 420 00:22:30,200 --> 00:22:33,639 Speaker 4: by the UK's competition and Markets Authority, which has been 421 00:22:33,680 --> 00:22:36,679 Speaker 4: increasingly hawkish on big tech. Let's go out to our 422 00:22:36,680 --> 00:22:41,000 Speaker 4: tech editor in London, Amy Thompson, and the CMA explained 423 00:22:41,000 --> 00:22:43,560 Speaker 4: their reasoning for letting this pass. 424 00:22:43,840 --> 00:22:47,200 Speaker 7: What was that reasoning, Amy, Yeah, it. 425 00:22:47,200 --> 00:22:50,920 Speaker 14: Was basically, the anthropic doesn't have enough of a market. 426 00:22:50,960 --> 00:22:53,560 Speaker 2: In the UK for them to have jurisdiction. 427 00:22:53,880 --> 00:22:56,199 Speaker 14: And we've kind of seen this with a few of 428 00:22:56,240 --> 00:22:59,360 Speaker 14: the cases that they've taken on were I think they 429 00:22:59,400 --> 00:23:02,560 Speaker 14: looked at UH Microsoft Inflection for example, and they came 430 00:23:02,600 --> 00:23:05,760 Speaker 14: to a similar conclusion. So they're having a lot of 431 00:23:05,760 --> 00:23:09,240 Speaker 14: look at these UH, these big tech slash AI deals, 432 00:23:09,800 --> 00:23:13,119 Speaker 14: but there's not a whole lot of UH regulation happening. 433 00:23:13,160 --> 00:23:17,560 Speaker 2: I guess that's a theme across here too. Amazon's investment 434 00:23:17,600 --> 00:23:21,640 Speaker 2: is also being considered by the US FTC. How much 435 00:23:21,720 --> 00:23:25,920 Speaker 2: is it giving these big tech companies polls? 436 00:23:26,400 --> 00:23:28,720 Speaker 14: I mean, it's it's part of the same concern that 437 00:23:28,720 --> 00:23:32,160 Speaker 14: we've seen from regulators UH not just in the UK, 438 00:23:32,720 --> 00:23:35,919 Speaker 14: UH but in the US and Europe about the dominance 439 00:23:35,960 --> 00:23:39,639 Speaker 14: that these UH big tech platforms have. And the latest 440 00:23:39,640 --> 00:23:42,880 Speaker 14: iteration is a concern about I think what the CMA 441 00:23:43,000 --> 00:23:46,520 Speaker 14: called UH web of connections UH with some of these 442 00:23:46,560 --> 00:23:52,440 Speaker 14: buzzy AI startups and whether all of these connections we're seeing, uh, 443 00:23:52,480 --> 00:23:56,639 Speaker 14: you know, Microsoft up and AI, uh Amazon anthropic, Google 444 00:23:56,680 --> 00:24:01,719 Speaker 14: anthropic Microsoft inflection is uh hurting the market. But I 445 00:24:01,720 --> 00:24:04,800 Speaker 14: don't think we've really seen anybody land a blow on 446 00:24:04,880 --> 00:24:05,800 Speaker 14: big tech so far. 447 00:24:06,240 --> 00:24:07,600 Speaker 2: The FDC hasn't. 448 00:24:07,280 --> 00:24:13,280 Speaker 14: Really given an update since January. The UK's investigation into 449 00:24:13,359 --> 00:24:19,480 Speaker 14: the Google anthropic relationship, you know, would appear to be 450 00:24:19,520 --> 00:24:23,679 Speaker 14: based on the same premises as the Amazon one. The 451 00:24:23,840 --> 00:24:29,200 Speaker 14: EU had to let the Open Ai Microsoft's deal go 452 00:24:29,280 --> 00:24:32,560 Speaker 14: as well because I didn't qualify as a merger, you know. 453 00:24:32,720 --> 00:24:36,840 Speaker 14: So you know, I don't think they've really landed a blow. 454 00:24:38,520 --> 00:24:41,439 Speaker 4: It begs the question then, about the pipeline for deals, 455 00:24:41,480 --> 00:24:43,480 Speaker 4: either where you are in the UK and Europe or 456 00:24:43,480 --> 00:24:44,840 Speaker 4: where I am in the States. 457 00:24:44,920 --> 00:24:46,200 Speaker 7: What is in the pipeline? 458 00:24:46,200 --> 00:24:50,680 Speaker 14: Amy, Oh, what is in the pipeline for deals? I mean, 459 00:24:51,840 --> 00:24:57,800 Speaker 14: I think I think if you're a startup in Europe, 460 00:24:57,840 --> 00:25:01,040 Speaker 14: for example, you're not sad to see results like this. 461 00:25:01,359 --> 00:25:04,320 Speaker 14: You're you're happy to see big tech companies being able 462 00:25:04,320 --> 00:25:07,440 Speaker 14: to come in and throw their weight around and give 463 00:25:07,480 --> 00:25:10,679 Speaker 14: you billions of investment and give you some compute and 464 00:25:10,800 --> 00:25:15,440 Speaker 14: give you access to chips, you know, but it does 465 00:25:15,520 --> 00:25:17,840 Speaker 14: leave us with the same problem out in the UK 466 00:25:17,880 --> 00:25:19,800 Speaker 14: and Europe that we've had for a while, which is, 467 00:25:19,960 --> 00:25:22,720 Speaker 14: you know, our tech scene is still dominated by big 468 00:25:22,800 --> 00:25:23,520 Speaker 14: US players. 469 00:25:24,600 --> 00:25:28,720 Speaker 2: Amy Thompson really on top of the European tech side. 470 00:25:28,720 --> 00:25:31,879 Speaker 2: We thank you. Meanwhile, five Tran, a data movement company 471 00:25:31,880 --> 00:25:34,520 Speaker 2: which helps power open AIS products, is announcing it just 472 00:25:34,520 --> 00:25:37,040 Speaker 2: to past three hundred million dollars in annual recurring revenue, 473 00:25:37,080 --> 00:25:39,760 Speaker 2: up from two hundred million in twenty twenty three, but 474 00:25:39,880 --> 00:25:43,119 Speaker 2: also striking new deals and relationships with some KEYAI players. 475 00:25:43,200 --> 00:25:45,720 Speaker 2: CEO five trans George Fraser, joins us. Now let's just 476 00:25:45,800 --> 00:25:48,160 Speaker 2: dwell on the numbers. Thus far six and a half 477 00:25:48,200 --> 00:25:51,760 Speaker 2: thousand businesses around the world you now serve doing exactly 478 00:25:51,800 --> 00:25:53,280 Speaker 2: what George. 479 00:25:53,560 --> 00:25:55,800 Speaker 15: Yeah, very nice to be with you. So what via 480 00:25:55,920 --> 00:25:58,879 Speaker 15: trend does is simple. On the outside, our customers are 481 00:25:58,920 --> 00:26:03,440 Speaker 15: businesses that use tools like Salesforce, like Azure, like Oracle, 482 00:26:03,680 --> 00:26:07,240 Speaker 15: like Workday like SAP, lots of tools to run their businesses. 483 00:26:07,280 --> 00:26:09,720 Speaker 15: And what five Trend does is we gather all that 484 00:26:09,800 --> 00:26:12,199 Speaker 15: data together in one place and they're able to use 485 00:26:12,240 --> 00:26:14,879 Speaker 15: it to understand what's happening in their business, how their 486 00:26:14,880 --> 00:26:18,040 Speaker 15: customers are using their product, optimize supply chains, all kinds 487 00:26:18,040 --> 00:26:20,840 Speaker 15: of things. But the crux of what fivetrend does is 488 00:26:20,880 --> 00:26:22,800 Speaker 15: it gets all your data in one place. 489 00:26:23,359 --> 00:26:26,719 Speaker 2: And that is pretty helpful for large language models. I'm 490 00:26:26,760 --> 00:26:28,680 Speaker 2: assuming how does it benefit open Ai? 491 00:26:29,400 --> 00:26:31,919 Speaker 15: Yeah, so open ai is a great five trend customer. 492 00:26:31,960 --> 00:26:36,320 Speaker 15: They're a very comprehensive use case. We centralize data about 493 00:26:36,359 --> 00:26:39,359 Speaker 15: all aspects of open AI's business from all kinds of 494 00:26:39,440 --> 00:26:42,240 Speaker 15: data sources, and the primary thing they do with it 495 00:26:41,960 --> 00:26:44,600 Speaker 15: is use it to understand how people are using their 496 00:26:44,640 --> 00:26:48,280 Speaker 15: products and guide the next generation product development. 497 00:26:49,400 --> 00:26:52,280 Speaker 7: George Witch, executive or leader at open Ai, did you 498 00:26:52,359 --> 00:26:55,240 Speaker 7: negotiate the partnership with We. 499 00:26:55,280 --> 00:26:57,560 Speaker 15: Work with a lot of people at open Ai. We 500 00:26:57,600 --> 00:27:00,800 Speaker 15: have a Slack channel with them where there's and activities. 501 00:27:00,840 --> 00:27:04,040 Speaker 15: Sometimes it's a little hard to tell, you know, who 502 00:27:04,119 --> 00:27:06,320 Speaker 15: is whose counterparty. I joke that I am the chief 503 00:27:06,480 --> 00:27:09,440 Speaker 15: customer support agent of the open ai account. I'm in 504 00:27:09,560 --> 00:27:14,199 Speaker 15: there every week. But there's a lot there's a lot 505 00:27:14,200 --> 00:27:15,159 Speaker 15: of people at opening that. 506 00:27:15,160 --> 00:27:15,679 Speaker 7: We work with. 507 00:27:15,720 --> 00:27:17,240 Speaker 15: I don't know who would be the one that I 508 00:27:17,240 --> 00:27:17,680 Speaker 15: would name. 509 00:27:18,560 --> 00:27:21,359 Speaker 4: So the reason I ask is you explained how the 510 00:27:21,720 --> 00:27:25,119 Speaker 4: sort of contract relationship works and how the data works. 511 00:27:25,160 --> 00:27:27,359 Speaker 4: But as you will have seen the reporting, you know 512 00:27:27,440 --> 00:27:31,640 Speaker 4: Mira Marati has decided to leave and there's consideration about 513 00:27:31,840 --> 00:27:35,240 Speaker 4: a transfer for a nonprofit with a for profit subsidiary 514 00:27:35,600 --> 00:27:39,000 Speaker 4: to a B corp. As a company doing business with 515 00:27:39,080 --> 00:27:41,240 Speaker 4: open Ai, what does that make you think? 516 00:27:43,640 --> 00:27:46,119 Speaker 15: I think we're going to continue to have a great relationship. 517 00:27:46,160 --> 00:27:48,600 Speaker 15: I think open Ai is a great company. I think 518 00:27:48,640 --> 00:27:54,720 Speaker 15: they've had a complicated history because the their their product 519 00:27:54,880 --> 00:27:59,639 Speaker 15: took off so explosively, unlike anything that's ever happened before. 520 00:28:00,080 --> 00:28:02,959 Speaker 15: We saw it because we were replicating data for them 521 00:28:03,040 --> 00:28:05,919 Speaker 15: back then. We saw their account go to the go 522 00:28:06,000 --> 00:28:08,560 Speaker 15: to the moon in data volumes. So I think it's 523 00:28:08,720 --> 00:28:11,600 Speaker 15: it's very exciting everything that's happening in open Ai. There's 524 00:28:11,600 --> 00:28:14,000 Speaker 15: some drama that has come with it, but I think 525 00:28:14,040 --> 00:28:16,680 Speaker 15: from where I said, the people I interact with they're 526 00:28:16,920 --> 00:28:17,960 Speaker 15: navigating it very well. 527 00:28:18,280 --> 00:28:19,920 Speaker 2: What are their accounts are going to the moon? 528 00:28:20,640 --> 00:28:26,000 Speaker 15: George, some big some big customers that have been growing 529 00:28:26,000 --> 00:28:29,040 Speaker 15: with us a lot recently. For example, LVMH. We were 530 00:28:29,080 --> 00:28:31,440 Speaker 15: just talking about what's going on in Europe a moment 531 00:28:31,440 --> 00:28:34,920 Speaker 15: ago on the previous segment. So LVMH is a big customer. 532 00:28:34,920 --> 00:28:38,360 Speaker 15: There a different kind of use case. They're mostly centralizing 533 00:28:38,440 --> 00:28:44,000 Speaker 15: data from earps from SAP in order to do supply 534 00:28:44,080 --> 00:28:47,400 Speaker 15: chain optimization and things like that. But that's another great 535 00:28:47,440 --> 00:28:49,600 Speaker 15: example of a big customer right now. 536 00:28:51,320 --> 00:28:54,200 Speaker 4: Yes, we've been covering that company during the show today. 537 00:28:54,520 --> 00:28:58,440 Speaker 4: On your ar R growth, it's really interesting companies like yours, 538 00:28:58,480 --> 00:29:01,640 Speaker 4: it's year on year quite to jump. What did you 539 00:29:01,720 --> 00:29:03,880 Speaker 4: have to do to get there? A big sort of 540 00:29:03,920 --> 00:29:06,720 Speaker 4: hiring effort on the sales team. What is the kind 541 00:29:06,720 --> 00:29:08,320 Speaker 4: of cost of that revenue growth? 542 00:29:09,400 --> 00:29:11,080 Speaker 15: You know, in the last year, Like a lot of 543 00:29:11,600 --> 00:29:14,920 Speaker 15: technology companies, the last couple of years, we have discovered 544 00:29:15,000 --> 00:29:18,800 Speaker 15: rediscovered efficient growth and so the headcount of five Tran 545 00:29:18,840 --> 00:29:21,280 Speaker 15: has not grown a ton in the last couple of years. 546 00:29:21,880 --> 00:29:25,920 Speaker 15: We've been able to grow the revenue and grow the 547 00:29:25,960 --> 00:29:29,600 Speaker 15: number of customers and do more with more or less 548 00:29:29,880 --> 00:29:32,400 Speaker 15: the same amount of people at the company. I think 549 00:29:32,440 --> 00:29:35,680 Speaker 15: it's just it's a lot of hard work by the team. 550 00:29:35,720 --> 00:29:37,000 Speaker 15: It's a lot of word of mouth out there in 551 00:29:37,040 --> 00:29:40,440 Speaker 15: the market that five Tran works. Five Tran solves what 552 00:29:40,520 --> 00:29:43,000 Speaker 15: can be a very ugly problem for companies of getting 553 00:29:43,040 --> 00:29:46,480 Speaker 15: their data from all these systems wrangled together, and I 554 00:29:46,480 --> 00:29:47,800 Speaker 15: think that's what's driving our growth. 555 00:29:47,960 --> 00:29:50,080 Speaker 2: I mean speaking to of vcs George, and a lot 556 00:29:50,080 --> 00:29:52,600 Speaker 2: of them will say. The hard thing is to understand 557 00:29:52,880 --> 00:29:55,840 Speaker 2: how long these customers are locked in for, how repeatable 558 00:29:55,880 --> 00:29:58,800 Speaker 2: this sort of growth is, to decide really where the 559 00:29:58,840 --> 00:30:02,200 Speaker 2: return on aim vestment is coming, George, of this run rate, 560 00:30:02,280 --> 00:30:05,240 Speaker 2: do you think it will increase a similar sort of level. 561 00:30:07,680 --> 00:30:10,840 Speaker 15: The market for what we do is enormous. Most data 562 00:30:10,880 --> 00:30:15,120 Speaker 15: centralization is do it yourself. It's not mostly other companies 563 00:30:15,120 --> 00:30:19,080 Speaker 15: that we compete with, its internal pipelines that people build 564 00:30:19,080 --> 00:30:22,680 Speaker 15: themselves and convincing them that they don't have to do 565 00:30:22,800 --> 00:30:26,520 Speaker 15: that anymore. So the total market for centralizing data in 566 00:30:26,600 --> 00:30:28,680 Speaker 15: the way that we do is tens of billions of dollars. 567 00:30:28,760 --> 00:30:33,640 Speaker 15: So in principle we have the ability to grow at 568 00:30:33,680 --> 00:30:37,920 Speaker 15: a high rate for decades. There are challenges, there are 569 00:30:37,960 --> 00:30:40,000 Speaker 15: things we need to make better about our products, there 570 00:30:40,000 --> 00:30:43,240 Speaker 15: are things we need to execute better on, but we 571 00:30:43,720 --> 00:30:46,560 Speaker 15: believe that the ceiling for us is very high. 572 00:30:47,040 --> 00:30:50,200 Speaker 4: George Fraser, CEO of five trand really appreciate you being 573 00:30:50,200 --> 00:30:53,640 Speaker 4: here on bloomber Technology doing business with some very interesting 574 00:30:53,720 --> 00:30:56,000 Speaker 4: names in the world's tech Now coming up our conversation 575 00:30:56,160 --> 00:31:00,120 Speaker 4: with tech entrepreneur Alexis Ohanian of seven seven six and 576 00:31:00,240 --> 00:31:03,280 Speaker 4: his latest investment is in the field of sports. Really 577 00:31:03,320 --> 00:31:19,200 Speaker 4: interesting one that's next. This is Bloomberg Technology. Alexis o'hanian. 578 00:31:19,320 --> 00:31:23,080 Speaker 4: You know him as an entrepreneur, a tech titan, an investor, 579 00:31:23,440 --> 00:31:27,520 Speaker 4: and now more than ever a heavyweight in supporting female athletes, 580 00:31:27,560 --> 00:31:31,719 Speaker 4: once invested in Angel City Football Club and now betting 581 00:31:31,760 --> 00:31:36,080 Speaker 4: big on professional track and field with his company AFLOSS. 582 00:31:36,560 --> 00:31:40,600 Speaker 4: Here's Alexis on how Athlos seems to be lucrative for athletes. 583 00:31:41,480 --> 00:31:44,040 Speaker 16: Ten percent of all the revenue spent four AFLOS. So 584 00:31:44,040 --> 00:31:47,560 Speaker 16: that's broadcast, that's tickets, that's merchant, it's hot dogs, goes 585 00:31:47,640 --> 00:31:50,280 Speaker 16: indoor pool and is divided evenly among every one of 586 00:31:50,320 --> 00:31:52,320 Speaker 16: the thirty six women who lines up to compete tonight. 587 00:31:52,480 --> 00:31:54,920 Speaker 16: And that's in addition to the record breaking person. And 588 00:31:54,960 --> 00:31:57,360 Speaker 16: it's just the start. And so how long will it take? 589 00:31:58,240 --> 00:32:01,120 Speaker 16: I don't know, but I believe this sport, it's the 590 00:32:01,160 --> 00:32:05,680 Speaker 16: original professional sport. This sport can and should be as 591 00:32:05,800 --> 00:32:08,640 Speaker 16: big outside of the Olympics as it is during. And 592 00:32:08,680 --> 00:32:10,680 Speaker 16: if we can do that, then there's no reason why 593 00:32:10,720 --> 00:32:12,920 Speaker 16: we can't have purses and prizes that well. 594 00:32:12,760 --> 00:32:17,760 Speaker 4: As Alexis, and yet track and Field stars are underpaid. 595 00:32:17,920 --> 00:32:21,320 Speaker 4: You know, that is kind of commonly held belief. And 596 00:32:21,360 --> 00:32:23,520 Speaker 4: then I think about a lot of what you just 597 00:32:23,560 --> 00:32:26,320 Speaker 4: touched on. So take Angel City FC. My relationship with 598 00:32:26,360 --> 00:32:28,920 Speaker 4: Angel City is I have a friend that plays in 599 00:32:28,920 --> 00:32:29,960 Speaker 4: the squad, Megan Reid. 600 00:32:30,080 --> 00:32:32,000 Speaker 7: Right, That's how I was exposed to them. 601 00:32:32,040 --> 00:32:35,800 Speaker 4: But I also was exposed through Apple TV. I don't 602 00:32:35,880 --> 00:32:38,320 Speaker 4: see the same level with track and Field on the 603 00:32:38,360 --> 00:32:39,400 Speaker 4: streaming platforms. 604 00:32:39,560 --> 00:32:40,200 Speaker 7: What does a. 605 00:32:40,160 --> 00:32:43,080 Speaker 4: Media deal not yet? But what does a media deal 606 00:32:43,120 --> 00:32:44,200 Speaker 4: for track and field look like? 607 00:32:44,360 --> 00:32:47,480 Speaker 16: Well, I think we got phase one from our friends 608 00:32:47,520 --> 00:32:50,520 Speaker 16: at Box to Box, who produced a show called Sprints 609 00:32:50,600 --> 00:32:54,960 Speaker 16: that captivated us on Netflix. And when we looked at 610 00:32:55,000 --> 00:32:58,000 Speaker 16: partners for Athletis, remember this is today, it's just one 611 00:32:58,040 --> 00:33:01,880 Speaker 16: event happening yearly. We want it to be the biggest 612 00:33:01,920 --> 00:33:05,080 Speaker 16: spectacle of the sport of entertainment. We got DJD Nice, 613 00:33:05,080 --> 00:33:07,680 Speaker 16: We've got Megnae Stallion performing. This is going to be 614 00:33:07,720 --> 00:33:09,880 Speaker 16: one of the best events any New York sports fan 615 00:33:09,920 --> 00:33:12,040 Speaker 16: will have been to. That that was our goal, and 616 00:33:12,080 --> 00:33:14,200 Speaker 16: when we looked at streaming partners, we said, Okay, this 617 00:33:14,280 --> 00:33:17,160 Speaker 16: is a global sport. The fan base is everywhere. They 618 00:33:17,280 --> 00:33:19,840 Speaker 16: want access, so we need to make it accessible. So 619 00:33:20,000 --> 00:33:22,120 Speaker 16: we wheeled and deal with different partners who understood that 620 00:33:22,240 --> 00:33:23,520 Speaker 16: was our goal, and we were able to get to 621 00:33:23,520 --> 00:33:25,280 Speaker 16: a place where, yeah, you can watch on an ESPN 622 00:33:25,320 --> 00:33:28,320 Speaker 16: plus awesome. You can also watch it on x you 623 00:33:28,320 --> 00:33:30,240 Speaker 16: can watch it on YouTube, you can watch it on 624 00:33:30,320 --> 00:33:33,680 Speaker 16: his own and so access, especially globally was so important. 625 00:33:34,080 --> 00:33:36,000 Speaker 16: But again this is still phase one. I'm going to 626 00:33:36,040 --> 00:33:39,400 Speaker 16: tell you a much different story come Monday morning, because 627 00:33:39,400 --> 00:33:41,560 Speaker 16: we have a re air on ESPN two on Sunday. 628 00:33:42,200 --> 00:33:44,560 Speaker 16: Exactly the number of people who watched, who tuned in, 629 00:33:44,680 --> 00:33:47,640 Speaker 16: who tweeted, who posted, who talked about it, and those 630 00:33:47,680 --> 00:33:50,000 Speaker 16: are the numbers. That's the first step is to say, look, 631 00:33:50,080 --> 00:33:53,120 Speaker 16: here is the thing. What if we invested real money 632 00:33:53,120 --> 00:33:56,120 Speaker 16: outside of the Olympics into one of these track events? 633 00:33:56,400 --> 00:33:57,320 Speaker 6: Will people show up? 634 00:33:57,360 --> 00:33:59,680 Speaker 16: Will people tune in? I think they will because these 635 00:33:59,680 --> 00:34:02,560 Speaker 16: women are no less excellent when the Olympics end, right 636 00:34:02,600 --> 00:34:04,320 Speaker 16: and so putting them on the stage, giving them this 637 00:34:04,400 --> 00:34:06,880 Speaker 16: high profile attention, I think they'll deliver. 638 00:34:07,520 --> 00:34:11,400 Speaker 2: An exos Hanian of seven seven six. Now, DirectTV and 639 00:34:11,520 --> 00:34:14,360 Speaker 2: Dish are said to be in advanced talks to merge 640 00:34:14,440 --> 00:34:17,560 Speaker 2: in a move that will create the largest US PayTV provider. 641 00:34:17,840 --> 00:34:20,400 Speaker 2: According to sources, the agreement could be announced as soon 642 00:34:20,440 --> 00:34:23,960 Speaker 2: as the coming days. For more by Michelle Davis joins US. Now, 643 00:34:24,400 --> 00:34:28,080 Speaker 2: why combine eleven million subscribers on one side eight million 644 00:34:28,120 --> 00:34:28,520 Speaker 2: on the other. 645 00:34:29,160 --> 00:34:31,439 Speaker 17: So this is a deal that's been a really long 646 00:34:31,480 --> 00:34:34,760 Speaker 17: time coming. The two of these companies attempted this merger 647 00:34:34,840 --> 00:34:38,279 Speaker 17: more than twenty years ago, regulators blocked it, and it 648 00:34:38,320 --> 00:34:41,080 Speaker 17: seems like now the stars or the planets are aligning 649 00:34:41,120 --> 00:34:43,759 Speaker 17: for them because the world has changed so much in 650 00:34:43,800 --> 00:34:45,880 Speaker 17: the past twenty years. The way that you and me 651 00:34:46,239 --> 00:34:49,560 Speaker 17: view content has changed completely. It used to be twenty 652 00:34:49,640 --> 00:34:52,760 Speaker 17: years ago that PayTV was the thing, you know, cable 653 00:34:52,880 --> 00:34:56,839 Speaker 17: satellite Now streaming as we all know, has really taken over, 654 00:34:56,920 --> 00:34:59,280 Speaker 17: and so a deal like this is really about survival 655 00:34:59,320 --> 00:35:00,319 Speaker 17: for these two comppanies. 656 00:35:01,440 --> 00:35:03,960 Speaker 4: Michelle, reading your story, it sounds like this is close, 657 00:35:04,080 --> 00:35:06,640 Speaker 4: right close to getting over the line, at least from 658 00:35:06,640 --> 00:35:07,840 Speaker 4: a sort of deal perspective. 659 00:35:07,840 --> 00:35:09,520 Speaker 7: What are you hearing about how it came together? 660 00:35:10,600 --> 00:35:13,759 Speaker 17: So you know, it's been an off and on situation 661 00:35:13,920 --> 00:35:17,279 Speaker 17: for more than two decades, but there are a couple 662 00:35:17,320 --> 00:35:19,360 Speaker 17: of things that had to happen recently for it to 663 00:35:19,440 --> 00:35:22,200 Speaker 17: be the perfect time for it to be coming soon. 664 00:35:22,360 --> 00:35:24,200 Speaker 17: We're hearing that the deal could get announced as soon 665 00:35:24,239 --> 00:35:27,400 Speaker 17: as Monday. Some of those things include, you know, TPG 666 00:35:27,520 --> 00:35:29,840 Speaker 17: and AT and T both own Direct TV through a 667 00:35:29,920 --> 00:35:32,200 Speaker 17: JV and as part of the deal that they struck 668 00:35:32,239 --> 00:35:34,360 Speaker 17: a few years ago, there was a provision that said 669 00:35:34,640 --> 00:35:37,680 Speaker 17: AT and T could not exit it's seventy percent stake 670 00:35:37,880 --> 00:35:41,880 Speaker 17: until this past summer. And now that that has passed, 671 00:35:41,920 --> 00:35:45,440 Speaker 17: it gives direct TV, you know, the corporate governance ability 672 00:35:45,480 --> 00:35:48,240 Speaker 17: to do something like this. And on the dish side, 673 00:35:48,400 --> 00:35:52,040 Speaker 17: Charlie Ergan, the billionaire who controls Dish Echo Star, he 674 00:35:52,120 --> 00:35:54,720 Speaker 17: has been dealing with some issues on the dead side. 675 00:35:54,760 --> 00:35:58,719 Speaker 17: He's spent a ton of money trying to buy Spectrum 676 00:35:58,719 --> 00:36:00,520 Speaker 17: to build out the wireless business, and he has some 677 00:36:00,560 --> 00:36:03,239 Speaker 17: big debt maturities coming due. And so the view is 678 00:36:03,239 --> 00:36:05,000 Speaker 17: that all of this coming together at the same time 679 00:36:05,080 --> 00:36:07,919 Speaker 17: could help solve both of these problems at once. 680 00:36:08,360 --> 00:36:12,640 Speaker 2: EchoStar, TPG, AT and T the names behind some big 681 00:36:12,680 --> 00:36:15,400 Speaker 2: stakes here. Do they remain committed to investing in the 682 00:36:15,400 --> 00:36:16,160 Speaker 2: future business. 683 00:36:16,440 --> 00:36:19,759 Speaker 17: So everything is still in flux, but Our understanding is 684 00:36:19,800 --> 00:36:23,239 Speaker 17: that at this point it does sound like the stakeholders 685 00:36:23,280 --> 00:36:25,920 Speaker 17: will remain stakeholders. There might be a way for some 686 00:36:25,960 --> 00:36:29,400 Speaker 17: folks to take money off the table. DirecTV does generate 687 00:36:29,440 --> 00:36:32,400 Speaker 17: a lot of cash flow for AT and T and TPG, 688 00:36:32,920 --> 00:36:35,120 Speaker 17: so the assumption would be they would want to keep 689 00:36:35,120 --> 00:36:37,239 Speaker 17: some of that, but you know, something like this would 690 00:36:37,320 --> 00:36:40,120 Speaker 17: help them exit a bit if they wanted to sow. 691 00:36:40,239 --> 00:36:42,920 Speaker 2: Thanks for breaking it down and what you're looking at. 692 00:36:43,680 --> 00:36:46,840 Speaker 4: More news in today's Talking Tech and First Up. Ireland 693 00:36:47,200 --> 00:36:50,440 Speaker 4: has fined Meta nearly one hundred and two million dollars 694 00:36:50,520 --> 00:36:54,440 Speaker 4: this after Meta notified the country's Data Protection Commission that 695 00:36:54,840 --> 00:36:59,640 Speaker 4: quote inadvertently stored passwords of some users in its internal 696 00:36:59,719 --> 00:37:05,040 Speaker 4: system without encryption or protection. Plus, game developer Virtuous is 697 00:37:05,040 --> 00:37:08,080 Speaker 4: set to acquire a Japanese studio in the coming months 698 00:37:08,160 --> 00:37:10,960 Speaker 4: as it plans to expand its presence in the country. 699 00:37:11,000 --> 00:37:15,400 Speaker 4: According to its CEO, Virtuous is inactive talks with multiple studios, 700 00:37:15,560 --> 00:37:18,640 Speaker 4: focusing on targets that have one hundred or fewer staff 701 00:37:18,800 --> 00:37:22,160 Speaker 4: but a track record of reliability and TikTok owner Bike 702 00:37:22,280 --> 00:37:25,480 Speaker 4: Dance is set to sign a ten point eight billion 703 00:37:25,520 --> 00:37:29,960 Speaker 4: dollar loan. That's according to sources, About twenty lenders comprised 704 00:37:30,000 --> 00:37:33,680 Speaker 4: of international and Chinese banks are said to be funding 705 00:37:33,760 --> 00:37:36,359 Speaker 4: the deal, and it would mark the largest loan in 706 00:37:36,480 --> 00:37:38,160 Speaker 4: Asia on record. 707 00:37:45,560 --> 00:37:48,399 Speaker 2: Apple shares on the month continuing to outperform and from 708 00:37:48,440 --> 00:37:53,560 Speaker 2: avoiding volatility despite growing concern around iPhone sales growth. Now 709 00:37:53,560 --> 00:37:56,520 Speaker 2: a Bloomberg Intelligence survey has found that the iPhone sixteen 710 00:37:56,640 --> 00:38:00,400 Speaker 2: did not excite consumers enough to warrant a smartphone super cycle, 711 00:38:00,680 --> 00:38:03,120 Speaker 2: and sales growth will be just three percent year over 712 00:38:03,239 --> 00:38:07,200 Speaker 2: year instead of previously projected five percent. Yesterday, analysts Morgan 713 00:38:07,200 --> 00:38:10,040 Speaker 2: Stanley in UBS both noted that iPhone sixteen lead times 714 00:38:10,080 --> 00:38:13,280 Speaker 2: are tracking lower than previous years discussed at all BLOMG 715 00:38:13,320 --> 00:38:16,520 Speaker 2: Intelligence senior analyst Anna Ragrana, did these numbers catch you 716 00:38:16,520 --> 00:38:17,080 Speaker 2: by surprise? 717 00:38:18,320 --> 00:38:18,520 Speaker 6: Yeah. 718 00:38:18,560 --> 00:38:21,080 Speaker 18: I think the surprising factor was we thought it will 719 00:38:21,120 --> 00:38:24,880 Speaker 18: at least match last year's refresh rate, but it's declined slightly. 720 00:38:25,200 --> 00:38:27,080 Speaker 18: So when you look at it and you ask people, like, 721 00:38:27,160 --> 00:38:30,040 Speaker 18: you know, how in the next twelve months, how many 722 00:38:30,080 --> 00:38:31,760 Speaker 18: people are going to upgrade their phones? 723 00:38:31,920 --> 00:38:34,160 Speaker 6: And that number was somewhere around fifty five percent. 724 00:38:34,360 --> 00:38:36,799 Speaker 18: Last year, it was around sixty the year before it 725 00:38:36,840 --> 00:38:39,520 Speaker 18: was sixty four so every year we are seeing a 726 00:38:39,600 --> 00:38:42,080 Speaker 18: decline in that number, which means people are keeping their 727 00:38:42,120 --> 00:38:44,480 Speaker 18: phone for a longer period of time. Now, whether that's 728 00:38:44,520 --> 00:38:47,400 Speaker 18: driven by cost or whether that's driven by the phone 729 00:38:47,440 --> 00:38:52,000 Speaker 18: being much better than previous years, but you know, one 730 00:38:52,000 --> 00:38:54,160 Speaker 18: would have thought with AI features you could have seen 731 00:38:54,160 --> 00:38:55,120 Speaker 18: a slight bump in that. 732 00:38:56,520 --> 00:38:59,360 Speaker 4: ANARAG survey data has been a big focus for Apple 733 00:38:59,400 --> 00:39:04,040 Speaker 4: investors recently. Could you kindly explain the methodology of the 734 00:39:04,080 --> 00:39:08,120 Speaker 4: Bloomberg Intelligence survey for the iPhone sixteen and also kind 735 00:39:08,120 --> 00:39:10,440 Speaker 4: of the breadth and depth of the data that you obtained. 736 00:39:11,480 --> 00:39:13,239 Speaker 18: Yeah, in this case, we go out and look at 737 00:39:13,320 --> 00:39:15,960 Speaker 18: US consumers and see what kind of phone are they 738 00:39:15,960 --> 00:39:18,960 Speaker 18: looking to buy, whether they are looking to buy the 739 00:39:19,080 --> 00:39:22,080 Speaker 18: Promax phone or the prophone, what are the reasons they 740 00:39:22,080 --> 00:39:24,640 Speaker 18: want to upgrade, how many of them want to upgrade, 741 00:39:24,719 --> 00:39:27,239 Speaker 18: how many of them want to switch over? And one 742 00:39:27,239 --> 00:39:30,520 Speaker 18: thing was clear, whether it was Android users or Apple users, 743 00:39:30,800 --> 00:39:32,960 Speaker 18: both said that they're going to keep the phone for 744 00:39:33,000 --> 00:39:37,000 Speaker 18: a longer period of time. Apple intelligence actually fell really 745 00:39:37,080 --> 00:39:39,640 Speaker 18: low in the ranking of the reasons they want to upgrade. 746 00:39:39,760 --> 00:39:42,479 Speaker 18: The reason still remains the same that the last few years, 747 00:39:42,480 --> 00:39:46,200 Speaker 18: whether it's storage, processing, power or camera, which was in 748 00:39:46,239 --> 00:39:48,960 Speaker 18: line with what we were expecting. Now, one reason for 749 00:39:49,000 --> 00:39:52,319 Speaker 18: this could be that we haven't really seen the soft 750 00:39:52,400 --> 00:39:56,000 Speaker 18: gare upgrade in terms of any UAI features that consumers 751 00:39:56,040 --> 00:39:58,560 Speaker 18: are using. These phones are capable of doing it, but 752 00:39:58,600 --> 00:40:01,320 Speaker 18: we don't have those features, and that will be launched 753 00:40:01,360 --> 00:40:04,160 Speaker 18: over the next twelve months. So I think that sentiment 754 00:40:04,239 --> 00:40:07,640 Speaker 18: could change as we see these features launch over the 755 00:40:07,680 --> 00:40:09,399 Speaker 18: next year or so, and that. 756 00:40:09,880 --> 00:40:13,880 Speaker 2: Is where the tension lies investors looking towards the longer 757 00:40:13,960 --> 00:40:18,160 Speaker 2: term adoption here, perhaps not this particular moment of frenzy 758 00:40:18,360 --> 00:40:19,280 Speaker 2: outside the stores. 759 00:40:20,480 --> 00:40:22,759 Speaker 18: I agree with you, and in fact, we think next 760 00:40:22,840 --> 00:40:25,120 Speaker 18: year's model is going to be a bigger upgrade or 761 00:40:25,160 --> 00:40:27,440 Speaker 18: the reason for if people to upgrade, because. 762 00:40:27,239 --> 00:40:28,759 Speaker 6: It's going to look different the hard ware. 763 00:40:28,840 --> 00:40:30,720 Speaker 18: Mark Goverman has done a very good job of telling 764 00:40:30,719 --> 00:40:33,319 Speaker 18: people that iPhone seventeen is where you should see some 765 00:40:33,360 --> 00:40:36,320 Speaker 18: improvement in that and hopefully by that time. 766 00:40:36,440 --> 00:40:38,720 Speaker 6: We will see all the AI features launched. 767 00:40:38,760 --> 00:40:41,719 Speaker 18: So those two factors I think would be compelling enough 768 00:40:41,719 --> 00:40:44,480 Speaker 18: for Apple iPhone sales to go up dramatically. 769 00:40:46,320 --> 00:40:49,840 Speaker 4: Blueberg intelligence scene around there, Santa Agvrana with an important 770 00:40:49,840 --> 00:40:51,560 Speaker 4: piece of survey data in Carra. I'm just going to 771 00:40:51,560 --> 00:40:54,160 Speaker 4: reflect on sign real quick, which is word of mouth. 772 00:40:54,520 --> 00:40:57,160 Speaker 4: Think back to metaconnect and Ryan and the small number 773 00:40:57,160 --> 00:40:59,719 Speaker 4: of people that got to see it. It might never 774 00:40:59,719 --> 00:41:02,560 Speaker 4: see that light of day. But with Apple Intelligence that's 775 00:41:02,600 --> 00:41:05,400 Speaker 4: not out yet. Maybe seeing is believing. So when it 776 00:41:05,440 --> 00:41:08,319 Speaker 4: does come out, people say, oh, I'd quite like to 777 00:41:08,320 --> 00:41:10,040 Speaker 4: try that out, maybe they go buy a new iPhone. 778 00:41:10,080 --> 00:41:12,160 Speaker 4: I just always think about that in the context of tech. 779 00:41:12,320 --> 00:41:15,040 Speaker 2: I'm always questioning the demographics of who's actually playing with 780 00:41:15,160 --> 00:41:17,920 Speaker 2: it is as well. Is it everyone that's based in 781 00:41:17,920 --> 00:41:20,319 Speaker 2: Silicon Valley versus the rest of the world. Is it 782 00:41:20,440 --> 00:41:23,520 Speaker 2: men versus women? Is it young versus old? Who is 783 00:41:23,560 --> 00:41:27,880 Speaker 2: actually playing with the meta AI or chatchpt and wanting 784 00:41:27,920 --> 00:41:30,279 Speaker 2: to do it? On Apple Intelligence as well? So much 785 00:41:30,320 --> 00:41:32,279 Speaker 2: to debate. It's been a big week. Boy, that does 786 00:41:32,280 --> 00:41:33,920 Speaker 2: it for this sedition of Bloomberg Technology. 787 00:41:34,400 --> 00:41:36,560 Speaker 4: You know where to recap on the podcast and exactly 788 00:41:36,560 --> 00:41:38,680 Speaker 4: where to find it from New York and SF. This 789 00:41:38,880 --> 00:41:43,920 Speaker 4: is Bloomberg Technology.