1 00:00:02,520 --> 00:00:07,000 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:09,520 --> 00:00:11,840 Speaker 2: This is the Blueberg Day baq At podcast. Good morning, 3 00:00:11,840 --> 00:00:15,440 Speaker 2: It's Wednesday, the nineteenth of November. I'm Caroline Hepkeitt in London. 4 00:00:15,400 --> 00:00:19,240 Speaker 1: And I'm Stephen Caroline Brussels. Coming up today. Stocks stabilize 5 00:00:19,280 --> 00:00:23,280 Speaker 1: after a one point six trillion dollar global route as 6 00:00:23,320 --> 00:00:27,040 Speaker 1: former Barkley CEO Bob Diamond joins the list of financial 7 00:00:27,120 --> 00:00:30,080 Speaker 1: heavyweights framing the selloff as a positive. 8 00:00:30,800 --> 00:00:34,920 Speaker 2: The EU's top diplomat, Kaya Kallas tells Bloomberg the bloc's 9 00:00:35,000 --> 00:00:39,000 Speaker 2: economic ties to China limit its ability to pressure Beijing 10 00:00:39,159 --> 00:00:39,879 Speaker 2: over Russia. 11 00:00:40,520 --> 00:00:44,919 Speaker 1: Plus the four legged robodog called spot Why the use 12 00:00:44,920 --> 00:00:47,960 Speaker 1: of a one hundred thousand dollars police robot is raising 13 00:00:48,080 --> 00:00:50,440 Speaker 1: questions about ethics and oversight. 14 00:00:51,080 --> 00:00:53,040 Speaker 2: Let's start with the roundup of our top stories. 15 00:00:53,120 --> 00:00:55,320 Speaker 1: Global stocks have follow to their lowest level in a 16 00:00:55,440 --> 00:00:59,440 Speaker 1: month as traders question frothy valuations and toy they're billions 17 00:00:59,440 --> 00:01:03,680 Speaker 1: in AI spending or delivering meaningful returns. This helloffs already 18 00:01:03,680 --> 00:01:06,840 Speaker 1: wiped roughly one point six trillion dollars off equities, with 19 00:01:06,880 --> 00:01:10,360 Speaker 1: the SMP five hundred ten more than three percent in November, 20 00:01:10,680 --> 00:01:13,320 Speaker 1: but not everyone believes that's a bad thing. Here's the 21 00:01:13,360 --> 00:01:16,760 Speaker 1: view of Atlas Merchant Capital CEO and former Barclay's boss 22 00:01:16,800 --> 00:01:17,520 Speaker 1: Bob Diamond. 23 00:01:18,080 --> 00:01:22,080 Speaker 3: We seen risk assets be repriced. In my sense, this 24 00:01:22,160 --> 00:01:25,480 Speaker 3: is a healthy correction, not something that's turning into a 25 00:01:25,480 --> 00:01:26,160 Speaker 3: bear market. 26 00:01:26,840 --> 00:01:29,479 Speaker 1: Bob Diamond's comments were echoed by Grace Peters, co head 27 00:01:29,520 --> 00:01:33,240 Speaker 1: of Global Investment Strategy for JP Morgan Private Bank. She 28 00:01:33,319 --> 00:01:36,199 Speaker 1: told Bloomberg Radio that a correction of five to eight 29 00:01:36,280 --> 00:01:39,440 Speaker 1: percent is not unhealthy and could help pave the way 30 00:01:39,640 --> 00:01:42,600 Speaker 1: for a fourth year of double digit equity returns for 31 00:01:42,640 --> 00:01:45,080 Speaker 1: the SMP five hundred in twenty twenty six. 32 00:01:46,360 --> 00:01:49,400 Speaker 2: The big earnings event of the day comes after the 33 00:01:49,440 --> 00:01:52,840 Speaker 2: Wall Street close, when we'll hear from Nvidia. Traders will 34 00:01:52,880 --> 00:01:56,200 Speaker 2: be looking for reassurance about the sustainability of spending at 35 00:01:56,240 --> 00:01:59,880 Speaker 2: the four point four trillion dollar AI chip giant, as 36 00:02:00,000 --> 00:02:02,800 Speaker 2: one is evidence that it can continue to outrun is 37 00:02:02,880 --> 00:02:06,520 Speaker 2: competitors with more his Bloombag's Charlie pelletts. 38 00:02:06,080 --> 00:02:09,280 Speaker 3: The report could either rearshore Wall Street that the AI 39 00:02:09,400 --> 00:02:13,200 Speaker 3: computing boom is continuing or fuel fears that the tech 40 00:02:13,240 --> 00:02:17,120 Speaker 3: industry is in a bubble. Margie Patells, Senior portfolio manager 41 00:02:17,200 --> 00:02:18,880 Speaker 3: at all Spring Global Investors. 42 00:02:19,120 --> 00:02:22,880 Speaker 4: The PE is around forty times, and that's higher than 43 00:02:22,880 --> 00:02:25,600 Speaker 4: the average stock which is around twenty seven times. But 44 00:02:25,720 --> 00:02:27,960 Speaker 4: on the other hand, their leaders in their sector, they 45 00:02:28,000 --> 00:02:30,200 Speaker 4: should have an above average growth. As far as a 46 00:02:30,240 --> 00:02:30,920 Speaker 4: guy can see. 47 00:02:30,960 --> 00:02:35,040 Speaker 3: The Bloomberg consensus revenue estimate for Nvidia is fifty five 48 00:02:35,240 --> 00:02:39,200 Speaker 3: point one nine billion dollars in New York, Charlie Pellett, 49 00:02:39,240 --> 00:02:40,239 Speaker 3: Bloomberg Radio. 50 00:02:41,280 --> 00:02:44,040 Speaker 1: The United States Congress has voted to force the Justice 51 00:02:44,040 --> 00:02:47,680 Speaker 1: Department to release files on sex trafficker Jeffrey Epstein. The 52 00:02:47,760 --> 00:02:51,080 Speaker 1: legislation overwhelmingly passed the House at a four hundred and 53 00:02:51,120 --> 00:02:54,919 Speaker 1: twenty seven to one vote. Hours later, the Senate passed 54 00:02:54,919 --> 00:02:58,040 Speaker 1: the measure with unanimous consent. The maneuver allows the Senate 55 00:02:58,080 --> 00:03:00,160 Speaker 1: to approve the bill without a vote, as long as 56 00:03:00,160 --> 00:03:05,240 Speaker 1: no senator objects to Democratic Minority Leader Chuck Schumer introduced 57 00:03:05,240 --> 00:03:08,240 Speaker 1: the request for unanimous consent and called on the House 58 00:03:08,240 --> 00:03:10,680 Speaker 1: Speaker Mike Johnson to send the bill to the White 59 00:03:10,720 --> 00:03:11,639 Speaker 1: House right away. 60 00:03:12,320 --> 00:03:14,880 Speaker 4: There's no reason it can't be on the President's desk 61 00:03:14,960 --> 00:03:16,840 Speaker 4: in an hour second. 62 00:03:16,880 --> 00:03:18,200 Speaker 1: The President has to sign it. 63 00:03:18,760 --> 00:03:20,800 Speaker 2: You never know with him say he would. 64 00:03:21,080 --> 00:03:22,120 Speaker 3: Let's wait and see. 65 00:03:22,320 --> 00:03:25,040 Speaker 5: But third, we have to make sure that the whole 66 00:03:25,120 --> 00:03:26,919 Speaker 5: all of the documents are. 67 00:03:26,800 --> 00:03:31,600 Speaker 1: Released, Chuck Schumer speaking, there are Senate Republicans ignored coals 68 00:03:31,639 --> 00:03:34,760 Speaker 1: by the House Speaker to give the Justice Department additional 69 00:03:34,840 --> 00:03:37,040 Speaker 1: leeweight to withhold documents. 70 00:03:38,280 --> 00:03:41,240 Speaker 2: The European Union's top diplomat has said that the bloc's 71 00:03:41,400 --> 00:03:44,680 Speaker 2: deep economic ties to China are limiting its ability to 72 00:03:44,720 --> 00:03:48,480 Speaker 2: pressure Beijing over Russia's war in Ukraine. At a Bluebig 73 00:03:48,480 --> 00:03:51,880 Speaker 2: event in Bustles, the EU's High Representative for Foreign Affairs, 74 00:03:51,960 --> 00:03:55,560 Speaker 2: Kayak Kallas, said that without China support, the war would 75 00:03:55,560 --> 00:03:59,040 Speaker 2: be over. She added the EU should strengthen its language 76 00:03:59,080 --> 00:04:02,720 Speaker 2: or Moscow's recent aggression against the blog, referring to a 77 00:04:02,880 --> 00:04:06,000 Speaker 2: railway explosion that took place in Poland over the weekend. 78 00:04:06,720 --> 00:04:10,960 Speaker 6: These sabotage acts that they are organizing on our territories 79 00:04:11,080 --> 00:04:15,760 Speaker 6: in different countries, these are extremely, extremely serious, and I 80 00:04:15,800 --> 00:04:21,080 Speaker 6: would quote a good friend, Secretary General of Fernato Mark Ruto, 81 00:04:21,120 --> 00:04:23,480 Speaker 6: who said that why are we saying, you know, hybrid 82 00:04:23,520 --> 00:04:26,880 Speaker 6: attexts which she seems like you know, something soft, when 83 00:04:27,080 --> 00:04:30,000 Speaker 6: we should call them by its name, which is state 84 00:04:30,279 --> 00:04:31,960 Speaker 6: sponsored terrorism. 85 00:04:32,440 --> 00:04:36,000 Speaker 2: That was Kaya Kalas that use high representative for foreign affairs, 86 00:04:36,040 --> 00:04:39,400 Speaker 2: adding that Russia is really trying to test how far 87 00:04:39,480 --> 00:04:42,520 Speaker 2: they can go on Europe's honed her as she called 88 00:04:42,520 --> 00:04:46,960 Speaker 2: it following an optic in incidents of sabotage, cybertexts and 89 00:04:47,120 --> 00:04:52,440 Speaker 2: drone incursions. Kremlin spokesman Dmiti Peskov rejected the accusation, saying 90 00:04:52,560 --> 00:04:54,720 Speaker 2: russiaphobia is flourishing. 91 00:04:55,279 --> 00:04:58,520 Speaker 1: The UK's domestic security service. As warrened lawmakers about a 92 00:04:58,560 --> 00:05:02,000 Speaker 1: new Chinese ESPIONA threat, m I five says there have 93 00:05:02,000 --> 00:05:05,279 Speaker 1: been efforts backed by the country to target MPs online, 94 00:05:05,360 --> 00:05:10,520 Speaker 1: reigniting concerns associated with parliament. Security Minister Dan Jarvis set 95 00:05:10,560 --> 00:05:13,080 Speaker 1: out the government's response in the House of Commons yesterday. 96 00:05:13,720 --> 00:05:16,920 Speaker 5: I'm setting out a comprehensive package of measures we are 97 00:05:17,000 --> 00:05:21,640 Speaker 5: taking to disrupt and deter the threats post by China 98 00:05:21,800 --> 00:05:25,919 Speaker 5: as well as by wide estate actors. Supported by ministers 99 00:05:25,960 --> 00:05:29,919 Speaker 5: from across government and coordinated by myself, we are launching 100 00:05:30,040 --> 00:05:34,360 Speaker 5: a counter political interference an espionage action. 101 00:05:34,279 --> 00:05:38,039 Speaker 1: Plan, Mister dan Jarvis, speaking thereafter, an alert was raised 102 00:05:38,040 --> 00:05:41,880 Speaker 1: over two online accounts claiming to represent head hunting groups 103 00:05:42,040 --> 00:05:45,240 Speaker 1: that my five says are run by Chinese intelligence agencies. 104 00:05:45,600 --> 00:05:48,360 Speaker 1: The Chinese Embassy in London dismissed the British claims as 105 00:05:48,480 --> 00:05:52,560 Speaker 1: malicious slander, saying it had lodged stern representations with the 106 00:05:52,680 --> 00:05:55,480 Speaker 1: UK for undermining China UK relations. 107 00:05:56,640 --> 00:05:59,800 Speaker 2: US President Donald chomp has said that he would formerly 108 00:06:00,080 --> 00:06:03,640 Speaker 2: signates Saudi Arabia as a non NATO ally following a 109 00:06:03,720 --> 00:06:07,160 Speaker 2: visit from Crown Prince Mohammed bin Salman. The announcement capped 110 00:06:07,160 --> 00:06:10,040 Speaker 2: to day of deal making between the two leaders and 111 00:06:10,240 --> 00:06:13,800 Speaker 2: will include the provision of financing and priority access to 112 00:06:13,920 --> 00:06:18,320 Speaker 2: purchasing military equipment from the US A Defense Corporation packed 113 00:06:18,360 --> 00:06:21,120 Speaker 2: including the future sale of F thirty five advanced fighter 114 00:06:21,200 --> 00:06:24,400 Speaker 2: jets the Kingdom was also agreed. Speaking about the arrangement, 115 00:06:24,440 --> 00:06:26,440 Speaker 2: President Trump explained its significance. 116 00:06:27,600 --> 00:06:31,320 Speaker 7: A stronger and more capable alliance will advance the interests 117 00:06:31,320 --> 00:06:34,600 Speaker 7: of both countries, and it will serve the highest interest 118 00:06:34,720 --> 00:06:37,560 Speaker 7: of peace. And we all share in peace. And we've 119 00:06:37,600 --> 00:06:41,640 Speaker 7: never had and been so close to truly everlasting peace 120 00:06:41,640 --> 00:06:44,120 Speaker 7: in the Middle East. All my life. I've heard, oh, 121 00:06:44,240 --> 00:06:46,120 Speaker 7: peace in the Middle East, but it will never happen. 122 00:06:46,160 --> 00:06:48,240 Speaker 7: We did it now we have to make sure it 123 00:06:48,360 --> 00:06:51,000 Speaker 7: matures properly and as really as strong as we think 124 00:06:51,000 --> 00:06:53,320 Speaker 7: it can be. But we've gotten all good signals. 125 00:06:54,240 --> 00:06:57,719 Speaker 2: President Trump speaking there, Saudi Arabia will become the twentieth 126 00:06:57,839 --> 00:07:01,680 Speaker 2: US ally designated onto that stage, joining other countries in 127 00:07:01,720 --> 00:07:05,400 Speaker 2: the Middle East, including Egypt, Israel, and Cutter. Crown Prince 128 00:07:05,760 --> 00:07:09,400 Speaker 2: Muhammad bin Salman was also joined by prominent figures including 129 00:07:09,400 --> 00:07:13,920 Speaker 2: Tessa's Elon Mask, investor Bill Ackman, and Invidious Jensen Wong 130 00:07:14,520 --> 00:07:17,520 Speaker 2: at an evening event on Tuesday. 131 00:07:18,280 --> 00:07:21,200 Speaker 1: New analysis by Bloomberg shows at the pay premium for 132 00:07:21,320 --> 00:07:25,080 Speaker 1: graduates over minimum wage salaries in England has had since 133 00:07:25,160 --> 00:07:28,600 Speaker 1: two thousand and seven. Boombrooks Ewen Parts has the details 134 00:07:29,080 --> 00:07:29,520 Speaker 1: for years. 135 00:07:29,560 --> 00:07:32,560 Speaker 8: The advice to teenagers considering their options was clear, if 136 00:07:32,560 --> 00:07:35,480 Speaker 8: you want to well paid job, head to university, but 137 00:07:35,600 --> 00:07:38,400 Speaker 8: new analysis by Bloomberg suggest the picture of these days 138 00:07:38,480 --> 00:07:41,360 Speaker 8: is not so simple. Back in two thousand and seven, 139 00:07:41,440 --> 00:07:44,600 Speaker 8: average graduates in their twenties earned twice as much as 140 00:07:44,600 --> 00:07:47,320 Speaker 8: the typical minimum wage worker on a forty hour week. 141 00:07:47,720 --> 00:07:50,440 Speaker 8: By twenty twenty four, the rising value of the minium 142 00:07:50,440 --> 00:07:53,720 Speaker 8: wage has shrunk that premium to forty three percent, and 143 00:07:53,760 --> 00:07:56,520 Speaker 8: accounting for student debt, repayments, the gap comes down to 144 00:07:56,720 --> 00:07:59,920 Speaker 8: just thirty two percent. A separate ranking by the OEC. 145 00:08:00,080 --> 00:08:02,280 Speaker 8: He says that UGA graduates get some of the worst 146 00:08:02,280 --> 00:08:06,240 Speaker 8: financial returns for their university education anywhere in the developed world. 147 00:08:06,760 --> 00:08:09,800 Speaker 3: In London, I'm Une Pots Bloomberg Radio, and. 148 00:08:09,720 --> 00:08:12,040 Speaker 2: Those are our top stories for you this morning. Just 149 00:08:12,080 --> 00:08:15,400 Speaker 2: looking at the market. So the tone very much still 150 00:08:15,520 --> 00:08:19,680 Speaker 2: risk off this morning. The Your Country World Index is flat. 151 00:08:19,720 --> 00:08:22,360 Speaker 2: The msciged Pacific Index is down by a quarter of 152 00:08:22,400 --> 00:08:25,640 Speaker 2: one percent. Stop futures in the red for the US 153 00:08:25,800 --> 00:08:27,760 Speaker 2: now is that future is dropping two tents. Your stocks 154 00:08:27,760 --> 00:08:32,240 Speaker 2: fifty futures flat right now. Tenure treasury yields this morning 155 00:08:32,679 --> 00:08:35,840 Speaker 2: trading at four point one one percent, so again flat. 156 00:08:35,880 --> 00:08:39,120 Speaker 2: Bloomberg Dollar Spot Index is slightly weaker. Gold is up 157 00:08:39,120 --> 00:08:42,640 Speaker 2: by seven tenths of one percent. Bitcoin still struggling well 158 00:08:42,679 --> 00:08:44,360 Speaker 2: below ninety one thousand dollars. 159 00:08:44,360 --> 00:08:46,920 Speaker 1: Those are the markets in a moment. What two expect 160 00:08:46,920 --> 00:08:50,160 Speaker 1: from in videos results later that following that global stock rouse, 161 00:08:50,240 --> 00:08:54,480 Speaker 1: plus the promise and perils of robot police dogs, there's 162 00:08:54,480 --> 00:08:58,120 Speaker 1: another story we've been reading this morning about a restauranteur 163 00:08:58,640 --> 00:09:01,360 Speaker 1: in Dubai are guyla party has been writing about this 164 00:09:01,760 --> 00:09:05,200 Speaker 1: who used Chatt GBT for menu inspiration, and that led 165 00:09:05,240 --> 00:09:11,400 Speaker 1: to an entire AI concept restaurant called Woohoo. The I 166 00:09:11,520 --> 00:09:13,920 Speaker 1: necessarily came up with that name either, but it's a 167 00:09:14,000 --> 00:09:18,080 Speaker 1: futuristic experiences immersive audio and video as part of as well. 168 00:09:18,559 --> 00:09:23,800 Speaker 1: Some of the dishes sound interesting. Dinosaur Heart which is 169 00:09:23,800 --> 00:09:26,040 Speaker 1: one of them, which is served in a rubber plate, 170 00:09:26,120 --> 00:09:27,880 Speaker 1: so it sort of vibrates. 171 00:09:28,800 --> 00:09:34,120 Speaker 2: I love that's very Jurassic Park, isn't it? Molecular barata? 172 00:09:34,280 --> 00:09:37,440 Speaker 2: I do you know what molecular barata is? Yeah, but 173 00:09:37,880 --> 00:09:40,600 Speaker 2: I think we have been hunting around, haven't we for 174 00:09:41,120 --> 00:09:43,520 Speaker 2: what the real world impact of AI is going to be, 175 00:09:44,720 --> 00:09:47,600 Speaker 2: And it could be wiseperad but including on dining, which yeah, 176 00:09:47,640 --> 00:09:50,439 Speaker 2: I think is kind of interesting, although still quite a 177 00:09:50,480 --> 00:09:54,200 Speaker 2: lot of the menu items which for this restaurant, which 178 00:09:54,200 --> 00:09:56,840 Speaker 2: apparently is going to be replicated because they spent one 179 00:09:56,840 --> 00:10:01,600 Speaker 2: point one million dollars, you know, creating this particular model 180 00:10:01,800 --> 00:10:05,000 Speaker 2: for restaurant restaurantings, so they obviously want to expand it. 181 00:10:06,160 --> 00:10:07,439 Speaker 2: But yeah, this is just the start. 182 00:10:08,480 --> 00:10:09,360 Speaker 3: Well yeah, and I mean the. 183 00:10:11,000 --> 00:10:14,280 Speaker 1: Effectivists it looks look reads pretty dramatically for reading guys 184 00:10:14,280 --> 00:10:17,080 Speaker 1: who are reporting as well. So it's a totally an 185 00:10:17,080 --> 00:10:20,280 Speaker 1: interesting idea. I don't know how inspired I am biased, 186 00:10:20,280 --> 00:10:23,280 Speaker 1: but we shall wait and see. Perhaps all restaurants will 187 00:10:23,320 --> 00:10:24,880 Speaker 1: be AI in no time at all. 188 00:10:26,320 --> 00:10:29,320 Speaker 2: Now, let's think about other stories for you this morning. 189 00:10:29,440 --> 00:10:33,160 Speaker 2: Bring you more on the major event for global markets today, 190 00:10:33,480 --> 00:10:35,480 Speaker 2: the results from the chip maker and videoed you out 191 00:10:35,480 --> 00:10:37,800 Speaker 2: after the close on Wall Street. The four point four 192 00:10:37,880 --> 00:10:43,000 Speaker 2: trillion dollar company's earnings are going to you know, they 193 00:10:43,080 --> 00:10:45,600 Speaker 2: come of course, as we have seen this major pullback 194 00:10:45,640 --> 00:10:49,280 Speaker 2: in risk assets and there's this concern about a bubble 195 00:10:49,360 --> 00:10:53,720 Speaker 2: potentially in AI. Our Asia tech correspondent and an Annabel 196 00:10:53,800 --> 00:10:56,560 Speaker 2: Drulis joins us now from Hong Kong and about good morning. 197 00:10:56,600 --> 00:10:58,720 Speaker 2: What are the key numbers then that we're watching for here? 198 00:10:59,679 --> 00:11:01,280 Speaker 9: Yeah, so I think there's going to be a number 199 00:11:01,480 --> 00:11:03,679 Speaker 9: of different ones to watch. But I think in terms 200 00:11:03,679 --> 00:11:05,559 Speaker 9: of the third quarter, what you're going to be looking at, 201 00:11:05,559 --> 00:11:08,040 Speaker 9: of course is the net income and the revenue, and 202 00:11:08,080 --> 00:11:10,320 Speaker 9: both of these are expected to show more than fifty 203 00:11:10,360 --> 00:11:13,240 Speaker 9: percent growth. Now the reason for that, I mean it's 204 00:11:13,240 --> 00:11:18,000 Speaker 9: pretty straightforward. You've had Microsoft, Amazon, Alphabet Meta, which together, 205 00:11:18,080 --> 00:11:20,199 Speaker 9: when you put them together, they represent around forty percent 206 00:11:20,200 --> 00:11:23,640 Speaker 9: of Video's sales. They're actually projecting an increase of their 207 00:11:23,679 --> 00:11:26,440 Speaker 9: combined AI spending over the next twelve months by around 208 00:11:26,480 --> 00:11:29,160 Speaker 9: thirty four percent. That's according to the data here at Bloomberg. 209 00:11:29,160 --> 00:11:31,760 Speaker 9: So I mean that sort of speaks to the general Yes, 210 00:11:31,800 --> 00:11:35,040 Speaker 9: another strong number of Ord's, another strong quarter of sales 211 00:11:35,080 --> 00:11:38,480 Speaker 9: is what we're expecting exactly what we're watching for. You've 212 00:11:38,480 --> 00:11:40,840 Speaker 9: got the details on shipments of the Blackwell and new 213 00:11:40,880 --> 00:11:44,080 Speaker 9: Ruben GPUs. How's that role out going, What does the 214 00:11:44,120 --> 00:11:49,760 Speaker 9: cadence on delivery look like specifically rather into twenty twenty six, 215 00:11:49,840 --> 00:11:51,920 Speaker 9: and also taking a look at the gross margins and 216 00:11:52,720 --> 00:11:55,319 Speaker 9: are they having any sort of big impact because you 217 00:11:55,400 --> 00:11:57,400 Speaker 9: have seen high component costs. I mean, just a few 218 00:11:57,440 --> 00:12:00,520 Speaker 9: days ago, for instance, Roytist was reporting that Sam's raise 219 00:12:00,559 --> 00:12:02,760 Speaker 9: their memory chip prices or it's looking to do so 220 00:12:03,160 --> 00:12:06,080 Speaker 9: by sixty percent. Given you've got so much demand, So 221 00:12:06,280 --> 00:12:08,199 Speaker 9: is that having a bearing on names like Nvideo. 222 00:12:09,679 --> 00:12:12,160 Speaker 1: Well, this is coming at a time when Wall Street's 223 00:12:12,200 --> 00:12:14,480 Speaker 1: looking for reassurance about how sustainable a lot of this 224 00:12:14,679 --> 00:12:18,120 Speaker 1: massive spending on AI is. I mean, how important to 225 00:12:18,160 --> 00:12:20,199 Speaker 1: will and Vidia be is a piece of that puzzle. 226 00:12:21,160 --> 00:12:22,800 Speaker 9: I think it's going to be really I mean it's 227 00:12:22,840 --> 00:12:25,079 Speaker 9: going to be really pivotal, and we know that this 228 00:12:25,160 --> 00:12:29,679 Speaker 9: is a really key market or event for investors this week. 229 00:12:29,880 --> 00:12:35,360 Speaker 9: It really becomes a macro one. How Nvidia can can deliver. 230 00:12:35,480 --> 00:12:37,400 Speaker 9: I think it's going to be the big question because 231 00:12:37,520 --> 00:12:40,280 Speaker 9: even though you've seen nvidea beating on its numbers or 232 00:12:40,320 --> 00:12:43,920 Speaker 9: expectations in successive quarters, actually, if you were to look 233 00:12:43,960 --> 00:12:46,920 Speaker 9: back on average over the past several the stock does 234 00:12:46,960 --> 00:12:50,360 Speaker 9: decline in the coming months, So you know, it doesn't 235 00:12:50,400 --> 00:12:51,960 Speaker 9: even if they do well, it doesn't mean that we're 236 00:12:51,960 --> 00:12:55,000 Speaker 9: going to get a positive reaction. But two trends that 237 00:12:55,040 --> 00:12:57,920 Speaker 9: we've seen recently that I think Jensen Wang might need 238 00:12:57,920 --> 00:13:00,600 Speaker 9: to address in the earnings care So the first is 239 00:13:00,600 --> 00:13:02,600 Speaker 9: what we're seeing from rivals in this space. You've got 240 00:13:02,800 --> 00:13:05,320 Speaker 9: likes of AMD. You've also got broadcom that are trying 241 00:13:05,360 --> 00:13:07,640 Speaker 9: to bring in and having some success also and bringing 242 00:13:07,640 --> 00:13:11,439 Speaker 9: in large customers, trying to crack that dominance of Nvidia 243 00:13:11,520 --> 00:13:14,560 Speaker 9: and AI chips. But I think more significantly probably is 244 00:13:14,600 --> 00:13:19,439 Speaker 9: also these circular deals and the concern that the and 245 00:13:19,600 --> 00:13:22,880 Speaker 9: video is essentially structuring its deals with customers and partners 246 00:13:23,920 --> 00:13:26,720 Speaker 9: that benefits itself. So you saw this overnight. For instance, 247 00:13:26,760 --> 00:13:30,680 Speaker 9: there was the deal between Microsoft and Video investing into 248 00:13:30,720 --> 00:13:36,120 Speaker 9: Anthropic Andthropic then buys back on Microsoft Cloud Services AWS 249 00:13:36,200 --> 00:13:38,320 Speaker 9: that then benefits and Video. So it just sort of 250 00:13:38,320 --> 00:13:41,760 Speaker 9: becomes this question, where is the genuine demand? Exactly? 251 00:13:42,440 --> 00:13:45,559 Speaker 2: Yeah, absolutely, And you mentioned and Vedia's CEO, Jensen Wong. 252 00:13:45,720 --> 00:13:50,240 Speaker 2: I just note that he's in so many conversations according 253 00:13:50,440 --> 00:13:54,160 Speaker 2: to Voyce's. Apparently he's also taking part in the US 254 00:13:54,160 --> 00:13:58,960 Speaker 2: Saudi Arabia Investment Forum in Washington around you know, NBS 255 00:13:59,000 --> 00:14:02,959 Speaker 2: being in washing to DC, which is interesting. There's also 256 00:14:03,120 --> 00:14:06,000 Speaker 2: one other story that I wanted to add. An analyst 257 00:14:06,080 --> 00:14:11,319 Speaker 2: yesterday downgraded Microsoft an Amazon to neutral from buy. This 258 00:14:11,400 --> 00:14:17,360 Speaker 2: is a Rothschild Redburns, Alexander Hassel, Why break from Piers 259 00:14:17,640 --> 00:14:20,000 Speaker 2: and why is that story significance? 260 00:14:20,960 --> 00:14:23,840 Speaker 9: Yeah, it's such an interesting call from redburn on this. 261 00:14:24,240 --> 00:14:26,640 Speaker 9: I don't think. I mean, he's certainly going against the 262 00:14:26,640 --> 00:14:28,400 Speaker 9: grain of analysts in the market. I think if you 263 00:14:28,480 --> 00:14:30,640 Speaker 9: were to look at at the percentage of analysts that 264 00:14:30,680 --> 00:14:34,360 Speaker 9: are tracking both of these companies, so Microsoft Amazon both 265 00:14:34,360 --> 00:14:37,360 Speaker 9: are in the high nineties for analysts that are holding 266 00:14:37,400 --> 00:14:39,920 Speaker 9: in the equivalent of a buy rating. So he's certainly 267 00:14:39,960 --> 00:14:43,720 Speaker 9: breaking trend, but I think what he's highlighting as his 268 00:14:43,840 --> 00:14:46,280 Speaker 9: reasons for this as sort of speaking to the broader 269 00:14:46,280 --> 00:14:49,000 Speaker 9: concerns that you have in the market. So he's looking at, 270 00:14:49,000 --> 00:14:51,760 Speaker 9: for instance, that that sort of narrative and the underlying 271 00:14:51,800 --> 00:14:54,680 Speaker 9: economics around generative AI, and he's saying that that looks 272 00:14:54,680 --> 00:14:58,160 Speaker 9: a lot weaker than probably is assumed. The narrative as well, 273 00:14:58,200 --> 00:15:03,360 Speaker 9: looking broadly misplaced or increasingly are misplaced. He's worried about 274 00:15:03,360 --> 00:15:06,160 Speaker 9: the depreciation schedules as well. That's the exact same thing 275 00:15:06,200 --> 00:15:08,360 Speaker 9: we heard from Michael Barrow just a few days ago. 276 00:15:08,640 --> 00:15:11,440 Speaker 9: But it certainly did have a bearing on the session 277 00:15:11,520 --> 00:15:13,840 Speaker 9: because we saw Amazon, for instance, really one of the 278 00:15:13,840 --> 00:15:16,280 Speaker 9: weaker ones, but down more than four percent. And it 279 00:15:16,280 --> 00:15:19,240 Speaker 9: does just feed into that general narrative and that general 280 00:15:19,240 --> 00:15:22,000 Speaker 9: concern we have around the sustainability of spending in AI, 281 00:15:22,320 --> 00:15:24,760 Speaker 9: the concerns around the bubble, what would lead it to pop? 282 00:15:24,840 --> 00:15:27,080 Speaker 9: Would it be a slow deflation. I mean, there's still 283 00:15:27,080 --> 00:15:28,640 Speaker 9: a lot we don't know, but I think it's just 284 00:15:28,640 --> 00:15:30,760 Speaker 9: sort of speaks to the mood of the moment essentially. 285 00:15:31,440 --> 00:15:33,800 Speaker 1: Yeah, very interesting one to watch as well. Annabel, thanks 286 00:15:33,800 --> 00:15:36,320 Speaker 1: so much for joining us there our Asia Tech correspondent 287 00:15:36,360 --> 00:15:39,040 Speaker 1: and anchor of Bloomberg Tech Asia with the latest on 288 00:15:39,120 --> 00:15:39,680 Speaker 1: those stories. 289 00:15:41,240 --> 00:15:41,920 Speaker 3: Stay with us. 290 00:15:42,000 --> 00:15:44,880 Speaker 1: More from Bloomberg Daybreak Europe coming up after this. 291 00:15:46,720 --> 00:15:49,840 Speaker 2: Now two something different this morning. Police forces in North 292 00:15:49,840 --> 00:15:53,280 Speaker 2: America are increasingly adopting robot dogs as part of the 293 00:15:53,520 --> 00:15:56,880 Speaker 2: law enforcement work. More than sixty bomb squads and swat 294 00:15:56,880 --> 00:15:59,800 Speaker 2: teams in the US and encounters that are now using 295 00:16:00,120 --> 00:16:03,960 Speaker 2: one model. It's called Spot. But the use of the 296 00:16:04,120 --> 00:16:07,840 Speaker 2: technology in policing is raising questions about ethics, oversight and 297 00:16:07,880 --> 00:16:10,640 Speaker 2: more are reported to a Adebio joins this now with 298 00:16:10,840 --> 00:16:15,080 Speaker 2: more on this. I think the most significant thing is 299 00:16:15,120 --> 00:16:17,240 Speaker 2: that it's such an eye catching design. I mean, if 300 00:16:17,240 --> 00:16:20,720 Speaker 2: you've seen the pictures of it, this four legged robot, 301 00:16:20,800 --> 00:16:25,440 Speaker 2: you'll know it. What does Spot actually do? Tia, Yeah, 302 00:16:25,480 --> 00:16:26,240 Speaker 2: that's right, Carolyn. 303 00:16:26,320 --> 00:16:30,760 Speaker 10: The four legged design of Spot actually is really important 304 00:16:30,800 --> 00:16:34,520 Speaker 10: because it sort of gives it more agility and dexterity 305 00:16:34,560 --> 00:16:38,320 Speaker 10: than traditional robots that move on tracks or wheels. But 306 00:16:38,400 --> 00:16:41,240 Speaker 10: Spot's really got quite a varied mix of skills. I mean, 307 00:16:41,320 --> 00:16:45,560 Speaker 10: it's being used to handle situations like arms standoffs and 308 00:16:45,920 --> 00:16:50,080 Speaker 10: hazardous materials incidents, but also it might be best known 309 00:16:50,240 --> 00:16:52,520 Speaker 10: for the viral dance routines. I don't know if you've 310 00:16:52,520 --> 00:16:55,800 Speaker 10: seen them online to songs like Uptown Funk. So SPOT 311 00:16:55,840 --> 00:16:59,520 Speaker 10: does have a pretty extensive CV, but it can also 312 00:16:59,760 --> 00:17:03,240 Speaker 10: do things like climbing stairs and opening doors, and that's 313 00:17:03,280 --> 00:17:07,720 Speaker 10: why it's proving really so useful to law enforcement workers 314 00:17:07,760 --> 00:17:11,840 Speaker 10: around the world. So really SPOT is specialized in situations 315 00:17:11,840 --> 00:17:14,680 Speaker 10: where sending in a human or a real dog would 316 00:17:14,720 --> 00:17:18,440 Speaker 10: be life threatening. It can offer different forms of support 317 00:17:18,520 --> 00:17:21,440 Speaker 10: on cases. So, for example, it approached a man who 318 00:17:21,440 --> 00:17:24,359 Speaker 10: had crashed a car trying to kidnap his son, and 319 00:17:24,400 --> 00:17:26,359 Speaker 10: it sort of just kept an eye on the situation 320 00:17:26,480 --> 00:17:29,240 Speaker 10: to see if that man was armed. Last year, and 321 00:17:29,480 --> 00:17:33,119 Speaker 10: two different occasions, it helped assess a chemical waste accident. 322 00:17:33,800 --> 00:17:36,560 Speaker 10: But also SPOT can end up taking a really active 323 00:17:36,680 --> 00:17:40,600 Speaker 10: role in these situations. So it even intervened recently when 324 00:17:40,600 --> 00:17:43,919 Speaker 10: a suspect took his mother hostage at knife point and 325 00:17:43,960 --> 00:17:47,159 Speaker 10: fired at officers, and SPOT was deployed to corner the 326 00:17:47,160 --> 00:17:51,000 Speaker 10: suspect and then police eventually followed with tear guess tear 327 00:17:51,000 --> 00:17:55,560 Speaker 10: gas to apprehend him. So it's a very varied use 328 00:17:55,600 --> 00:17:59,760 Speaker 10: of technology that we're seeing increasingly being deployed by law 329 00:17:59,800 --> 00:18:01,080 Speaker 10: and fament professionals. 330 00:18:01,440 --> 00:18:03,840 Speaker 1: Yeah, indeed, how widespread is the use of this kind 331 00:18:03,880 --> 00:18:05,360 Speaker 1: of technology in policing. 332 00:18:05,920 --> 00:18:09,200 Speaker 10: So it's primarily being used in the US and Canada. 333 00:18:09,359 --> 00:18:13,360 Speaker 10: More than sixty bomb squads and swat teams over there 334 00:18:13,400 --> 00:18:17,000 Speaker 10: are now using SPOT, that's according to the company that 335 00:18:17,119 --> 00:18:20,480 Speaker 10: makes it. But it is really growing in terms of 336 00:18:20,560 --> 00:18:24,760 Speaker 10: policing use, and that's because we've seen the funding for 337 00:18:24,840 --> 00:18:28,440 Speaker 10: this sort of technology soaring in the past few years. 338 00:18:28,440 --> 00:18:32,200 Speaker 10: It's past twenty eight billion this year. That's up two 339 00:18:32,280 --> 00:18:37,080 Speaker 10: hundred percent year on year, and so these forces have 340 00:18:37,280 --> 00:18:41,200 Speaker 10: a lot more spending power to access this sort of technology, 341 00:18:41,240 --> 00:18:45,480 Speaker 10: and that's meant that robots in general have been finding 342 00:18:45,560 --> 00:18:49,480 Speaker 10: homes in law enforcement agencies like ICE, that's the US 343 00:18:49,680 --> 00:18:53,680 Speaker 10: Immigration and Customs Enforcement. They've recently spent seventy eight thousand 344 00:18:53,720 --> 00:18:57,840 Speaker 10: dollars on a robot from a Canadian tech manufacturer that's 345 00:18:57,920 --> 00:19:02,520 Speaker 10: quite similar to SPOT, but also deploys things like smoke bombs, 346 00:19:03,040 --> 00:19:06,040 Speaker 10: according to records. But this isn't new. We've seen the 347 00:19:06,160 --> 00:19:09,680 Speaker 10: use of robots in emergency situations for a while now. 348 00:19:09,960 --> 00:19:13,560 Speaker 10: There's a fascinating Bloomberg longread on this story on the 349 00:19:13,640 --> 00:19:17,600 Speaker 10: terminal and it details how police and bomb squads have 350 00:19:17,760 --> 00:19:20,960 Speaker 10: relied on robots really since the nineteen eighties, but their 351 00:19:21,000 --> 00:19:25,680 Speaker 10: deployment has definitely become more widespread since the early two thousands, 352 00:19:25,680 --> 00:19:28,399 Speaker 10: and we're seeing the use of this technology catch on 353 00:19:28,760 --> 00:19:31,880 Speaker 10: around the world as well. So there's roughly two thousand 354 00:19:32,000 --> 00:19:36,240 Speaker 10: SPOT units now in operation globally according to Boston Dynamics, 355 00:19:36,640 --> 00:19:40,920 Speaker 10: and those deployments include organizations such as the Dutch Ministry 356 00:19:40,920 --> 00:19:43,200 Speaker 10: of Defense and also Italy's National Police. 357 00:19:43,960 --> 00:19:46,639 Speaker 2: What are the concerns around the technology. 358 00:19:46,760 --> 00:19:50,119 Speaker 10: Well, it's mainly around the ethics, so the use of 359 00:19:50,160 --> 00:19:53,760 Speaker 10: the technology really raises quite a few questions. There's things 360 00:19:53,760 --> 00:19:57,399 Speaker 10: like oversight and also more broadly, the risk of using 361 00:19:57,480 --> 00:20:02,280 Speaker 10: military grade tools in civilian settings. There is the question 362 00:20:02,480 --> 00:20:06,840 Speaker 10: of autonomy here, so this robot can operate autonomously in 363 00:20:06,920 --> 00:20:11,959 Speaker 10: many cases, so that does raise concerns over control and 364 00:20:12,200 --> 00:20:15,400 Speaker 10: you know the use of it in emergency situations, high 365 00:20:15,480 --> 00:20:20,760 Speaker 10: pressure situations. The technology is also continuing to evolve, and 366 00:20:20,800 --> 00:20:26,080 Speaker 10: there have been some questions recently about if all departments 367 00:20:26,200 --> 00:20:29,840 Speaker 10: are really advanced enough to use these tools. The cost 368 00:20:30,040 --> 00:20:33,439 Speaker 10: is it can be astronomical and so there are some 369 00:20:33,560 --> 00:20:38,239 Speaker 10: experts really questioning whether that cost can be justified and 370 00:20:38,280 --> 00:20:42,359 Speaker 10: whether the complexity of the robots are actually really worth 371 00:20:42,560 --> 00:20:46,280 Speaker 10: the extra services they can provide. But really the main 372 00:20:47,280 --> 00:20:50,440 Speaker 10: point of contention is this question of ethics. We've seen 373 00:20:50,480 --> 00:20:54,320 Speaker 10: this technology be used by enforcement agencies like ICE, whose 374 00:20:54,359 --> 00:20:57,680 Speaker 10: activities have already been controversial in the US this year, 375 00:20:57,920 --> 00:21:01,480 Speaker 10: so there is growing anxiety to you about the deployment 376 00:21:01,520 --> 00:21:04,080 Speaker 10: of this technology as it continues to grow and evolve. 377 00:21:05,600 --> 00:21:08,320 Speaker 1: This is Bloomberg Daybreak Europe, your morning brief on the 378 00:21:08,400 --> 00:21:11,440 Speaker 1: stories making news from London to Wall Street and beyond. 379 00:21:11,760 --> 00:21:14,960 Speaker 2: Look for us on your podcast feed every morning, on Apple, 380 00:21:15,080 --> 00:21:17,880 Speaker 2: Spotify and anywhere else you get your podcasts. 381 00:21:17,960 --> 00:21:21,000 Speaker 1: You can also listen live each morning on London DAB Radio, 382 00:21:21,040 --> 00:21:24,480 Speaker 1: the Bloomberg Business app, and Bloomberg dot Com. 383 00:21:24,640 --> 00:21:28,119 Speaker 2: York Station is also available on your Amazon Alexa devices. 384 00:21:28,480 --> 00:21:32,760 Speaker 2: Just say Alexa play Bloomberg eleven thirty. I'm Caroline Hipka and. 385 00:21:32,760 --> 00:21:33,560 Speaker 3: I'm Stephen Carol. 386 00:21:33,640 --> 00:21:36,000 Speaker 1: Join us again tomorrow morning for all the news you 387 00:21:36,040 --> 00:21:41,120 Speaker 1: need to start your day right here on Bloomberg Daybreak Europe.