1 00:00:03,320 --> 00:00:05,560 Speaker 1: This is Bloomberg day Break Weekend, our global look at 2 00:00:05,600 --> 00:00:07,640 Speaker 1: the top stories in the coming week from our day 3 00:00:07,640 --> 00:00:10,360 Speaker 1: Break anchors all around the world. Straight ahead on the program, 4 00:00:10,360 --> 00:00:12,840 Speaker 1: and look ahead to the January jobs report here in 5 00:00:12,920 --> 00:00:16,200 Speaker 1: the US how that may impact FED policy moving forward. 6 00:00:16,560 --> 00:00:19,360 Speaker 2: I'm Caroline Hebcker here in London, where we're looking ahead 7 00:00:19,360 --> 00:00:21,759 Speaker 2: to the Bank of England great decision and what the 8 00:00:21,920 --> 00:00:25,000 Speaker 2: Chancellor's plans for growth might mean for them. 9 00:00:25,480 --> 00:00:28,440 Speaker 3: I'm Doug Chrisner looking at what lies ahead for China's 10 00:00:28,520 --> 00:00:29,120 Speaker 3: deep seek. 11 00:00:30,400 --> 00:00:34,400 Speaker 4: That's all straight ahead on Bloomberg Daybreak Weekend on Bloomberg 12 00:00:34,440 --> 00:00:38,160 Speaker 4: eleven three year on New York, Bloomberg ninety nine to one, Washington, DC, 13 00:00:38,640 --> 00:00:42,920 Speaker 4: Bloomberg ninety two to nine, Boston, DAB Digital Radio, London, 14 00:00:43,320 --> 00:00:46,479 Speaker 4: Sirius XM one twenty one, and around the world on 15 00:00:46,600 --> 00:00:49,720 Speaker 4: Bloomberg Radio, dot Com and the Bloomberg Business App. 16 00:00:54,760 --> 00:00:56,720 Speaker 1: Good day to you. We begin today's program with the 17 00:00:56,880 --> 00:01:00,320 Speaker 1: January jobs report. We get non farm pay year old 18 00:01:00,360 --> 00:01:03,200 Speaker 1: numbers this Friday, eight thirty am Wall Street Time, and 19 00:01:03,280 --> 00:01:07,560 Speaker 1: for more. We're joined by Michael McKee, Bloomberg International Economics 20 00:01:07,560 --> 00:01:11,720 Speaker 1: and Policy correspondent. Well Michael twenty twenty four ended with 21 00:01:11,800 --> 00:01:15,280 Speaker 1: a blowout December jobs report two hundred and fifty six 22 00:01:15,319 --> 00:01:19,000 Speaker 1: thousand added, ending the year four point one percent unemployment 23 00:01:19,000 --> 00:01:23,520 Speaker 1: of five decade low. Did the good times continue to January? 24 00:01:24,400 --> 00:01:27,640 Speaker 5: Well, that's the question, and we aren't exactly sure. There 25 00:01:27,640 --> 00:01:29,600 Speaker 5: seems to be a division on Wall Street about how 26 00:01:29,600 --> 00:01:32,399 Speaker 5: this is all going to work out. Reversion to the 27 00:01:32,440 --> 00:01:35,880 Speaker 5: mean is a sort of a well known phrase in economics, 28 00:01:35,880 --> 00:01:39,800 Speaker 5: and that's what economists surveyed by Bloomberg see for the 29 00:01:40,200 --> 00:01:45,400 Speaker 5: private payrolls number itself two hundred twenty three thousand last month, 30 00:01:45,560 --> 00:01:48,120 Speaker 5: but for January, they're only at the moment thinking about 31 00:01:48,120 --> 00:01:53,000 Speaker 5: one hundred and thirty thousand, which would fit the pattern 32 00:01:53,080 --> 00:01:58,720 Speaker 5: we saw before that big December number. So that would 33 00:01:58,760 --> 00:02:01,480 Speaker 5: suggest that the economy or the labor market at least, 34 00:02:01,520 --> 00:02:04,559 Speaker 5: is slowing down some. But that four point one percent 35 00:02:04,640 --> 00:02:09,240 Speaker 5: unemployment rate isn't expected to change. So what we have 36 00:02:09,480 --> 00:02:12,240 Speaker 5: seen sort of in all the ancillary data like jobless 37 00:02:12,240 --> 00:02:15,639 Speaker 5: claims and things, are that people aren't losing their jobs, 38 00:02:15,639 --> 00:02:18,600 Speaker 5: but they're not getting hired. It's taking longer to find 39 00:02:18,639 --> 00:02:22,760 Speaker 5: new jobs. Business seems to be putting new employment on hold, 40 00:02:23,320 --> 00:02:26,280 Speaker 5: but they're not getting rid of people yet, And the idea, 41 00:02:26,360 --> 00:02:29,120 Speaker 5: I guess, is that this report will ratify that. 42 00:02:29,880 --> 00:02:33,120 Speaker 1: Now seasonal holiday jobs, we always see it to a 43 00:02:33,200 --> 00:02:36,359 Speaker 1: decrease in January. Correct, Well, that's the way it used 44 00:02:36,360 --> 00:02:36,560 Speaker 1: to be. 45 00:02:36,960 --> 00:02:39,760 Speaker 5: It's a little bit less that way now, and it's 46 00:02:39,800 --> 00:02:42,040 Speaker 5: a little bit harder to figure out exactly what the 47 00:02:42,080 --> 00:02:44,720 Speaker 5: seasonal impact is going to be. We know that the 48 00:02:45,360 --> 00:02:48,360 Speaker 5: seasonal employees were hired later this year. They showed up 49 00:02:48,400 --> 00:02:51,799 Speaker 5: in December instead of November. Do they stay on a 50 00:02:51,880 --> 00:02:56,520 Speaker 5: little bit longer? Do they slowly go away? I think 51 00:02:56,760 --> 00:02:58,640 Speaker 5: one of the reasons we're looking at the one hundred 52 00:02:58,680 --> 00:03:03,680 Speaker 5: and thirty thousand is that economists are anticipating those people 53 00:03:04,160 --> 00:03:07,840 Speaker 5: will have left the jobs. But it's really hard to tell. 54 00:03:08,040 --> 00:03:10,200 Speaker 5: The other impact is going to be from the Los 55 00:03:10,200 --> 00:03:14,640 Speaker 5: Angeles fires because they took place during the survey week 56 00:03:14,800 --> 00:03:18,760 Speaker 5: for the January payrolls, and we don't know exactly how 57 00:03:18,800 --> 00:03:21,160 Speaker 5: many businesses were destroyed, but we know a lot from 58 00:03:21,200 --> 00:03:24,040 Speaker 5: looking at the video, and so there are probably going 59 00:03:24,080 --> 00:03:28,079 Speaker 5: to be a number of job losses. Some analysts have 60 00:03:28,120 --> 00:03:30,760 Speaker 5: said as many as twenty thousand that would show up 61 00:03:30,840 --> 00:03:31,840 Speaker 5: in the report. 62 00:03:32,120 --> 00:03:36,160 Speaker 1: And for the economy, we saw Hollywood suddenly stopped some 63 00:03:36,240 --> 00:03:40,040 Speaker 1: production of TV shows, movies, so it really had an impact, 64 00:03:40,360 --> 00:03:42,600 Speaker 1: which will lessen over time. Of course, I think things 65 00:03:43,000 --> 00:03:46,920 Speaker 1: are now weeks later getting back to normal. Well, let's 66 00:03:46,920 --> 00:03:50,160 Speaker 1: talk about the Federal Reserve. The labor market pretty solid. 67 00:03:50,200 --> 00:03:52,160 Speaker 1: As you said, we were looking at no change at 68 00:03:52,160 --> 00:03:56,040 Speaker 1: a four point one unemployment rate. Economic growth we just 69 00:03:56,080 --> 00:03:59,880 Speaker 1: saw this past week GDP growth fourth quarter a little 70 00:03:59,880 --> 00:04:01,040 Speaker 1: stronger than expected. 71 00:04:01,240 --> 00:04:05,720 Speaker 5: But inflation, that's always the kind of the butt out there. 72 00:04:05,760 --> 00:04:09,240 Speaker 5: You don't even have to say anything beyond that inflation 73 00:04:09,680 --> 00:04:12,800 Speaker 5: has sort of stalled out. The PCE numbers that the 74 00:04:12,880 --> 00:04:17,039 Speaker 5: Fed released on Friday basically show that in December inflation 75 00:04:17,279 --> 00:04:22,400 Speaker 5: was unchanged on a year year basis, and that's not 76 00:04:22,440 --> 00:04:26,919 Speaker 5: what they want to see. What it does suggest that 77 00:04:27,000 --> 00:04:29,359 Speaker 5: as long as that continues, the Fed's going to remain 78 00:04:29,400 --> 00:04:32,480 Speaker 5: on hold. There is the reason that Jay Powell cited 79 00:04:32,560 --> 00:04:36,880 Speaker 5: for not moving at last week's meeting. So I think 80 00:04:36,920 --> 00:04:40,400 Speaker 5: at this point we're watching to see any indications of 81 00:04:40,440 --> 00:04:44,039 Speaker 5: whether inflation comes down, and all of a sudden we'll 82 00:04:44,040 --> 00:04:46,920 Speaker 5: be looking at things like home prices and rents even 83 00:04:47,040 --> 00:04:51,039 Speaker 5: more closely, because that's really where the stickiness is. The 84 00:04:51,080 --> 00:04:54,360 Speaker 5: Fed needs that to happen. But also we're looking at 85 00:04:54,360 --> 00:04:57,760 Speaker 5: our average early earnings in the employment report because the 86 00:04:57,760 --> 00:05:01,000 Speaker 5: FED says right now the labor market is not inflationary, 87 00:05:01,120 --> 00:05:03,720 Speaker 5: so they don't want to see any changes there either. 88 00:05:04,200 --> 00:05:06,320 Speaker 1: Well, let's talk about the rate. Two point eight percent? 89 00:05:06,360 --> 00:05:08,159 Speaker 1: Is this almost a new normal? 90 00:05:08,600 --> 00:05:08,720 Speaker 6: This? 91 00:05:09,080 --> 00:05:11,120 Speaker 1: It really hasn't changed much in months. 92 00:05:10,880 --> 00:05:14,800 Speaker 5: Right, That's the key question is can the FED get 93 00:05:14,839 --> 00:05:16,280 Speaker 5: it down to the two percent target? 94 00:05:17,080 --> 00:05:18,160 Speaker 1: Or is the. 95 00:05:18,080 --> 00:05:22,640 Speaker 5: Economy growing at a faster pace than it had been. 96 00:05:22,920 --> 00:05:27,080 Speaker 5: Is potential growth higher, which would mean inflation would be higher. 97 00:05:26,800 --> 00:05:28,560 Speaker 1: It could support a two point Does. 98 00:05:28,440 --> 00:05:31,400 Speaker 5: That mean that we need higher interest rates on a 99 00:05:31,440 --> 00:05:34,560 Speaker 5: regular basis? Not necessarily raise them from here, but don't 100 00:05:34,600 --> 00:05:37,880 Speaker 5: cut them. That's the debate within the FED, and that's 101 00:05:38,000 --> 00:05:40,640 Speaker 5: the thing that they have to figure out between now 102 00:05:40,640 --> 00:05:44,080 Speaker 5: and their next meeting on March nineteenth. And that should 103 00:05:44,120 --> 00:05:48,040 Speaker 5: be relatively easy except for Donald Trump and his tariffs 104 00:05:48,120 --> 00:05:51,120 Speaker 5: and everything else that's going to happen between now and then. 105 00:05:51,400 --> 00:05:53,919 Speaker 1: Well, speaking of those tariffs, how do you think the 106 00:05:53,920 --> 00:05:56,560 Speaker 1: FED has prepared for the threat of those twenty five 107 00:05:56,600 --> 00:06:00,360 Speaker 1: percent tariffs? I mean, Canada, Mexico buy more American products 108 00:06:00,400 --> 00:06:03,280 Speaker 1: and anybody else, So we know this is you know, 109 00:06:03,800 --> 00:06:06,279 Speaker 1: it could be challenging. 110 00:06:07,480 --> 00:06:09,920 Speaker 5: Indeed, well I know a lot of FED officials around 111 00:06:09,960 --> 00:06:13,040 Speaker 5: the country at the various FED banks and then down 112 00:06:13,040 --> 00:06:16,640 Speaker 5: in Washington at the Board of Governors have tasked their 113 00:06:16,680 --> 00:06:22,120 Speaker 5: researchers to come up with what if scenarios. The problem 114 00:06:22,279 --> 00:06:25,680 Speaker 5: is is without a lot of detail, it's been hard 115 00:06:25,680 --> 00:06:29,080 Speaker 5: for them to come up with what if scenarios, and 116 00:06:29,560 --> 00:06:32,280 Speaker 5: so now if they get some details, it takes them 117 00:06:32,600 --> 00:06:35,839 Speaker 5: time to put to work through it all because there's 118 00:06:35,880 --> 00:06:37,839 Speaker 5: a lot that goes into it. It's not just what 119 00:06:37,920 --> 00:06:40,720 Speaker 5: the tariff level is, it's how long it's imposed for 120 00:06:41,720 --> 00:06:48,160 Speaker 5: and how it's imposed over time or immediately, and then 121 00:06:48,200 --> 00:06:51,320 Speaker 5: what are the tariff countries do? Do they put teriffs 122 00:06:51,360 --> 00:06:53,599 Speaker 5: back on the US. So all of that has to 123 00:06:53,600 --> 00:06:55,800 Speaker 5: be accounted for. So it'll be a little while before 124 00:06:55,839 --> 00:06:58,760 Speaker 5: the PET has a clear idea of what it would mean. 125 00:06:58,920 --> 00:07:01,799 Speaker 1: The January jobs are out This Friday morning, eight thirty 126 00:07:01,839 --> 00:07:04,720 Speaker 1: am Wall Street Time our thanks to Michael McKee, Bloomberg 127 00:07:04,800 --> 00:07:08,680 Speaker 1: International Economics and Policy correspondent, we turned out to earnings 128 00:07:08,720 --> 00:07:11,200 Speaker 1: with two more members of the tech sector, so called 129 00:07:11,200 --> 00:07:15,280 Speaker 1: Magnificent seven, posting fourth quarter results this coming week Alphabet 130 00:07:15,280 --> 00:07:18,360 Speaker 1: on Tuesday and on Thursday, Amazon, and we want to 131 00:07:18,400 --> 00:07:21,200 Speaker 1: focus on Amazon to see about sales over the holidays 132 00:07:21,520 --> 00:07:24,800 Speaker 1: and it's cash cow cloud computing, an AI services unit, 133 00:07:25,080 --> 00:07:28,480 Speaker 1: and any impact at all from China's deep seek chat 134 00:07:28,480 --> 00:07:30,840 Speaker 1: pot Now for more where all of that were joined 135 00:07:30,840 --> 00:07:36,520 Speaker 1: by anirag Rana, Bloomberg Intelligence technology analyst anarag We'll start 136 00:07:36,560 --> 00:07:39,120 Speaker 1: with the earnings. What are you expecting to see in 137 00:07:39,200 --> 00:07:41,280 Speaker 1: Thursday's earnings report from Amazon? 138 00:07:42,920 --> 00:07:45,440 Speaker 7: You know, my colleague Punum and I we re published 139 00:07:45,440 --> 00:07:48,840 Speaker 7: a preview for Amazon, and we think that the four 140 00:07:48,880 --> 00:07:50,720 Speaker 7: Q sales could be at the high end of their 141 00:07:50,720 --> 00:07:55,280 Speaker 7: guidance of seven to eleven percent, driven by AWS advertising 142 00:07:55,360 --> 00:07:58,160 Speaker 7: retail sales over the holiday quarter, which were very strong. 143 00:07:58,480 --> 00:08:02,080 Speaker 6: Frankly, so those are the areas. We also think advertising 144 00:08:02,120 --> 00:08:05,320 Speaker 6: revenue could be in the high teens given the addition 145 00:08:05,400 --> 00:08:06,760 Speaker 6: of Prime Video ads. 146 00:08:07,720 --> 00:08:11,800 Speaker 1: So sales good, the ons, signature site ad sales. What 147 00:08:11,920 --> 00:08:15,960 Speaker 1: about its cash cow Amazon web services and what is 148 00:08:16,000 --> 00:08:19,120 Speaker 1: Amazon investing now in AI and infrastructure? 149 00:08:19,240 --> 00:08:22,520 Speaker 6: And that's you know, you're right, that's probably the most 150 00:08:22,560 --> 00:08:26,400 Speaker 6: important question right now. We're looking at Amazon, you know, 151 00:08:26,480 --> 00:08:30,880 Speaker 6: sales growth of somewhere around nineteen percent excluding ethics impact. 152 00:08:32,000 --> 00:08:34,960 Speaker 6: That's slight better than I would say what would have 153 00:08:35,240 --> 00:08:38,120 Speaker 6: anticipated just a year ago, and a lot of that 154 00:08:38,240 --> 00:08:43,240 Speaker 6: is driven by the improvement in workload consumption or people 155 00:08:43,320 --> 00:08:48,559 Speaker 6: running more things on the platform. AI will contribute as well, 156 00:08:48,760 --> 00:08:53,880 Speaker 6: although they don't disclose contribution from AI sales similar to Microsoft, 157 00:08:54,240 --> 00:08:56,760 Speaker 6: but that's because they do not have you know, you 158 00:08:56,800 --> 00:09:01,640 Speaker 6: could say the workloads coming from conserhum apps like chat, GPT. 159 00:09:01,960 --> 00:09:06,000 Speaker 6: Most of their businesses, enterprise and enterprise and corporate clients 160 00:09:06,040 --> 00:09:10,959 Speaker 6: are just starting the implementation of AI related products, so 161 00:09:11,000 --> 00:09:13,280 Speaker 6: it's not as you know, you could say, that is 162 00:09:13,280 --> 00:09:16,080 Speaker 6: not a mature market as some of the consumer apps 163 00:09:16,080 --> 00:09:16,439 Speaker 6: have been. 164 00:09:16,800 --> 00:09:18,719 Speaker 1: So a lot of room to grow for Amazon in. 165 00:09:18,720 --> 00:09:21,680 Speaker 6: AI, absolutely, and a lot of room for everybody to grow, 166 00:09:21,720 --> 00:09:25,079 Speaker 6: including you know, Microsoft and Google. In this case, what 167 00:09:25,360 --> 00:09:29,400 Speaker 6: Amazon has done is they have a strong relationship. They've 168 00:09:29,440 --> 00:09:31,760 Speaker 6: invested in a company called Anthropic, which is one of 169 00:09:31,800 --> 00:09:35,880 Speaker 6: their you could say, preferred large language model providers. They 170 00:09:35,880 --> 00:09:38,840 Speaker 6: also have their own model. They also let people use 171 00:09:39,240 --> 00:09:43,400 Speaker 6: models from Mecca called Lama, So it's it's up to 172 00:09:43,440 --> 00:09:45,840 Speaker 6: the client what kind of model they want to use. 173 00:09:47,040 --> 00:09:49,920 Speaker 6: Amazon Web Services is just going to provide the platform 174 00:09:50,320 --> 00:09:53,120 Speaker 6: and and you know, the basically the infrastructure to run 175 00:09:53,160 --> 00:09:54,960 Speaker 6: those products. 176 00:09:55,679 --> 00:09:58,440 Speaker 1: Now, Wall Street got a real wake up call last 177 00:09:58,520 --> 00:10:01,160 Speaker 1: week with that low cost chat from the Chinese startup 178 00:10:01,280 --> 00:10:04,880 Speaker 1: Deep Seek. Boy did it rattle the markets and rattle 179 00:10:04,920 --> 00:10:11,120 Speaker 1: a lot of AI companies. How did Amazon react well in. 180 00:10:10,960 --> 00:10:13,680 Speaker 6: The long run? So, first and foremost, we are not 181 00:10:13,800 --> 00:10:19,360 Speaker 6: even sure whether we should see that as in a way, 182 00:10:19,360 --> 00:10:22,800 Speaker 6: there are two scenarios whether we can continue to see 183 00:10:23,080 --> 00:10:26,640 Speaker 6: large amount of improvements in these models without the use 184 00:10:26,679 --> 00:10:29,920 Speaker 6: of expensive chips. And that's where the argument is right now. 185 00:10:30,280 --> 00:10:34,480 Speaker 6: If we were to take that aside, if in reality 186 00:10:34,640 --> 00:10:38,240 Speaker 6: we can come up with models at a much cheaper cost, 187 00:10:38,559 --> 00:10:41,400 Speaker 6: that's really good for somebody like an Amazon because they 188 00:10:41,400 --> 00:10:44,720 Speaker 6: don't have to spend that much in capital expenditures and 189 00:10:44,800 --> 00:10:47,760 Speaker 6: the growth curve or the adoption curve off AI goes up. 190 00:10:48,040 --> 00:10:51,000 Speaker 6: These guys benefit from that because they're providing the infrastructure. 191 00:10:51,240 --> 00:10:53,360 Speaker 6: So I think in the long run it's good for 192 00:10:53,400 --> 00:10:56,640 Speaker 6: the cloud providers like Amazon. But again I think we 193 00:10:56,679 --> 00:10:59,280 Speaker 6: still have to see whether that really is the case 194 00:10:59,280 --> 00:11:01,199 Speaker 6: that you can build models that. 195 00:11:01,280 --> 00:11:03,600 Speaker 1: Cheaply consumer spending. I want to go back to that 196 00:11:03,640 --> 00:11:05,640 Speaker 1: in the in the final quarter of last year up 197 00:11:06,040 --> 00:11:08,560 Speaker 1: better than expected about four percent. A lot of that 198 00:11:08,960 --> 00:11:13,040 Speaker 1: from Amazon dot Com. Obviously, it's like most consumers can't 199 00:11:13,040 --> 00:11:15,320 Speaker 1: live without it. But something I want to bring up 200 00:11:15,480 --> 00:11:19,079 Speaker 1: ups in its earnings just said that they're going to 201 00:11:19,160 --> 00:11:23,040 Speaker 1: slash deliveries they do for Amazon in half by next year. 202 00:11:23,520 --> 00:11:26,199 Speaker 1: That's because of the home deliveries just too costly. FedEx 203 00:11:26,280 --> 00:11:29,000 Speaker 1: made the same decision five years ago. FedEx doesn't even 204 00:11:29,040 --> 00:11:31,560 Speaker 1: deliver for Amazon. What do you think it could mean 205 00:11:31,920 --> 00:11:33,160 Speaker 1: for their e commerce unit? 206 00:11:33,360 --> 00:11:35,880 Speaker 6: Yeah, I think you know, one of the most important 207 00:11:35,920 --> 00:11:38,480 Speaker 6: part of their e commerce business is really their logistics 208 00:11:38,520 --> 00:11:41,680 Speaker 6: at this point. Frankly speaking, you know, when you think 209 00:11:41,720 --> 00:11:45,000 Speaker 6: about it, what they did in COVID, they've really invested 210 00:11:45,080 --> 00:11:48,280 Speaker 6: so much to improve their logistics network. So frankly speaking, 211 00:11:48,360 --> 00:11:51,080 Speaker 6: I think, you know, you could argue that these guys 212 00:11:51,240 --> 00:11:53,440 Speaker 6: really don't need anybody else. Now that's not true. They 213 00:11:53,440 --> 00:11:56,800 Speaker 6: will outsource when they need extra capacity, but you know, 214 00:11:56,840 --> 00:11:59,679 Speaker 6: their logistics are pretty impressive at this point, and in fact, 215 00:12:00,080 --> 00:12:03,280 Speaker 6: this whole promise of delivering products within a few hours 216 00:12:03,720 --> 00:12:07,520 Speaker 6: is really changing the way people buy. What used to happen, 217 00:12:07,640 --> 00:12:10,000 Speaker 6: Tom was I used to go to Amazon because it 218 00:12:10,080 --> 00:12:13,120 Speaker 6: was the low cost provider. That's no longer the case. 219 00:12:13,240 --> 00:12:16,880 Speaker 6: You can find goods outside and other websites that are cheaper, 220 00:12:17,240 --> 00:12:20,840 Speaker 6: but the reason you go to Amazon dot Com is 221 00:12:20,920 --> 00:12:23,640 Speaker 6: because as a Prime member, you can get those products 222 00:12:23,640 --> 00:12:27,160 Speaker 6: pretty quickly. It's happened to me several times that you 223 00:12:27,240 --> 00:12:29,720 Speaker 6: need something right away and they will deliver it in 224 00:12:29,760 --> 00:12:33,080 Speaker 6: four to five hours. So that level of service is 225 00:12:33,120 --> 00:12:36,480 Speaker 6: what I think is the biggest differentiator for Amazon, and 226 00:12:36,520 --> 00:12:37,200 Speaker 6: it's not price. 227 00:12:37,400 --> 00:12:40,840 Speaker 1: Amazon Q four earnings out this coming Thursday are thanks 228 00:12:40,880 --> 00:12:44,800 Speaker 1: to anirog Rana, Bloomberg Intelligence technology analyst and coming up 229 00:12:44,840 --> 00:12:47,240 Speaker 1: on Bloomberg day Break weekend, a rate decision this week 230 00:12:47,280 --> 00:12:50,000 Speaker 1: from the Bank of England. I'm Tom Busby and this 231 00:12:50,240 --> 00:13:03,079 Speaker 1: is Bloomberger. This is Bloomberg Daybreak Weekend, our global look 232 00:13:03,080 --> 00:13:05,600 Speaker 1: ahead at the top stories for investors in the coming week. 233 00:13:05,880 --> 00:13:08,520 Speaker 1: I'm Tom Busby in New York. Up later in our 234 00:13:08,559 --> 00:13:12,320 Speaker 1: program Deep Seek Move Markets. This past week we see 235 00:13:12,320 --> 00:13:16,280 Speaker 1: what's next for China's Ai startup. But first, policymakers at 236 00:13:16,280 --> 00:13:18,400 Speaker 1: the Bank of England are preparing to make their first 237 00:13:18,600 --> 00:13:22,000 Speaker 1: interest rate decision of the year. A slumping currency and 238 00:13:22,120 --> 00:13:24,480 Speaker 1: stagnant growth will be on the minds of officials as 239 00:13:24,520 --> 00:13:26,960 Speaker 1: they make their choice. Now for more, let's go to 240 00:13:27,000 --> 00:13:30,600 Speaker 1: London and bring in Bloomberg Daybreak Europe Banker Caroline. 241 00:13:30,040 --> 00:13:34,160 Speaker 2: Hepgar Tom week Sterling is just the latest factor that 242 00:13:34,320 --> 00:13:36,840 Speaker 2: Bank of England officials will have to think about when 243 00:13:36,880 --> 00:13:40,559 Speaker 2: plotting the path for interest rates in twenty twenty five. 244 00:13:40,920 --> 00:13:44,760 Speaker 2: Investors are still expecting a quarter point cut, one of 245 00:13:45,000 --> 00:13:48,760 Speaker 2: just two fully priced in for this year, but stagnant 246 00:13:48,800 --> 00:13:52,120 Speaker 2: economic growth, alongside the threat of a global trade war, 247 00:13:52,480 --> 00:13:56,280 Speaker 2: has loomed large over the Central Bank's forecasts and could 248 00:13:56,360 --> 00:14:01,680 Speaker 2: dampen the Bank of England's inflation projections in years this 249 00:14:02,000 --> 00:14:05,560 Speaker 2: as moves in guilt yields and rate expectations since the 250 00:14:05,640 --> 00:14:10,360 Speaker 2: budget in October have tightened fiscal conditions, a real headwind 251 00:14:10,559 --> 00:14:15,560 Speaker 2: for the British economy. Enter Chancellor Rachel Reeves she's on 252 00:14:15,600 --> 00:14:20,280 Speaker 2: a mission to revitalize the nation's economic health by going 253 00:14:20,360 --> 00:14:24,400 Speaker 2: further and faster, she puts it for growth and potentially 254 00:14:24,520 --> 00:14:29,040 Speaker 2: lifting some of the pressure on Andrew Bailey's Monetary Policy Committee. 255 00:14:29,280 --> 00:14:32,280 Speaker 2: She has been speaking to Bloomberg about her proposals. 256 00:14:32,520 --> 00:14:35,240 Speaker 8: Well, look at the reaction from business to the speech 257 00:14:35,280 --> 00:14:38,720 Speaker 8: I gave two thirds of businesses and the instant reaction 258 00:14:39,040 --> 00:14:42,119 Speaker 8: has said they now feel more confident about the government's 259 00:14:42,480 --> 00:14:46,200 Speaker 8: growth plans. I make no apologies for putting our country 260 00:14:46,200 --> 00:14:49,640 Speaker 8: bag on the right's path, and because of the planning 261 00:14:49,680 --> 00:14:54,480 Speaker 8: reforms that we're making alongside the big announcements yesterday, it 262 00:14:54,560 --> 00:14:57,240 Speaker 8: means what we can crack on and get these projects 263 00:14:57,280 --> 00:15:00,440 Speaker 8: delivered quicker because they won't get clogged up in courts 264 00:15:00,520 --> 00:15:03,600 Speaker 8: because we're reforming the way that you build stuff in Britain. 265 00:15:05,080 --> 00:15:06,840 Speaker 9: Do not feel, though, Chancellor, that you need to deliver 266 00:15:06,920 --> 00:15:09,800 Speaker 9: something that will deliver now that will give an uptick 267 00:15:09,880 --> 00:15:12,360 Speaker 9: to growth. Now we're looking at the labor market, data, 268 00:15:12,720 --> 00:15:16,600 Speaker 9: messages from recruiters, the purchasing managers' surveys, all of those 269 00:15:17,000 --> 00:15:19,720 Speaker 9: telling us quite negative things about the labor market, saying 270 00:15:19,720 --> 00:15:22,080 Speaker 9: that businesses are shedding jobs at the rate we haven't 271 00:15:22,080 --> 00:15:23,600 Speaker 9: seen since the financial crisis. 272 00:15:24,880 --> 00:15:25,480 Speaker 10: Well, if you. 273 00:15:25,480 --> 00:15:29,120 Speaker 8: Look at the IMF forecast for the UK, they've revised 274 00:15:29,200 --> 00:15:32,800 Speaker 8: up the UK's growth prospects for this year. The PwC 275 00:15:32,960 --> 00:15:35,720 Speaker 8: survey released at the beginning of last week of global 276 00:15:35,760 --> 00:15:38,640 Speaker 8: CEOs who see Britain as the second best place in 277 00:15:38,680 --> 00:15:41,520 Speaker 8: the world to invest outside of the United States. The 278 00:15:41,560 --> 00:15:43,760 Speaker 8: first time in twenty eight years have been at that 279 00:15:43,800 --> 00:15:47,800 Speaker 8: position in the League table, and yesterday business is coming 280 00:15:47,800 --> 00:15:51,040 Speaker 8: out and backing Labour's plans to grow the economy and 281 00:15:51,080 --> 00:15:53,400 Speaker 8: making them feel more confident about the future. 282 00:15:53,520 --> 00:15:54,960 Speaker 10: Can you give me a growth number by the end 283 00:15:55,000 --> 00:15:57,280 Speaker 10: of the year, then, if you are more positive about 284 00:15:57,320 --> 00:15:59,160 Speaker 10: what growth is going to deliver in the UK, what 285 00:15:59,200 --> 00:16:01,680 Speaker 10: growth numbers we can expect. Do you have a number 286 00:16:01,720 --> 00:16:04,840 Speaker 10: in mind, do you have a target for this year 287 00:16:05,200 --> 00:16:06,440 Speaker 10: and can you share it with us. 288 00:16:06,880 --> 00:16:09,480 Speaker 8: I'm not going to do growth forecasts. That's up to 289 00:16:10,160 --> 00:16:13,800 Speaker 8: the Independent Office, the Budget Responsibility, the IMF and others 290 00:16:13,840 --> 00:16:17,680 Speaker 8: to forecast the UK's growth prospects. But what I did 291 00:16:17,800 --> 00:16:20,760 Speaker 8: was to set out some ambitious plans and to get 292 00:16:20,760 --> 00:16:23,840 Speaker 8: our economy growing, to get spades in the ground, to 293 00:16:23,960 --> 00:16:28,040 Speaker 8: deliver these infrastructure projects that in many cases have been 294 00:16:29,000 --> 00:16:33,040 Speaker 8: available for years now but the previous government balked at. 295 00:16:33,240 --> 00:16:37,000 Speaker 8: So whether it's the Oxcam Growth Corridor to create Europe's 296 00:16:37,120 --> 00:16:40,760 Speaker 8: Silicon Valley here in the UK, or the third Runway 297 00:16:40,800 --> 00:16:44,960 Speaker 8: at Heathrow, a new stadium at Old Trafford, the TransPennine routes, 298 00:16:45,080 --> 00:16:49,280 Speaker 8: upgrade a new airport at Doncaster. All of these things 299 00:16:49,400 --> 00:16:53,320 Speaker 8: are about a confidence in Britain, saying to investors, look 300 00:16:53,360 --> 00:16:56,280 Speaker 8: again at Britain. This is a great place to invest, 301 00:16:56,320 --> 00:16:59,240 Speaker 8: to start and grow a business, and this government has 302 00:16:59,280 --> 00:16:59,800 Speaker 8: your back. 303 00:17:01,240 --> 00:17:03,760 Speaker 10: When does the first spade go in the ground and 304 00:17:03,880 --> 00:17:09,040 Speaker 10: any of those projects, Well, let's. 305 00:17:08,800 --> 00:17:11,480 Speaker 8: Take Heathrow with our key throw to come forward with 306 00:17:11,560 --> 00:17:14,640 Speaker 8: plans by this summer and we hope to be able 307 00:17:14,640 --> 00:17:17,960 Speaker 8: to grant a development consent order in this parliament. So 308 00:17:18,080 --> 00:17:21,280 Speaker 8: spades in the ground in this parliament. But other projects 309 00:17:21,320 --> 00:17:24,480 Speaker 8: can get going sooner. We've committed to build one and 310 00:17:24,480 --> 00:17:27,880 Speaker 8: a half million homes in this Parliament and we've made 311 00:17:27,880 --> 00:17:32,119 Speaker 8: it easier to build, for example, around commuter railway stations, 312 00:17:32,400 --> 00:17:36,280 Speaker 8: with the default answer for planning applications now being yes. 313 00:17:36,800 --> 00:17:40,240 Speaker 8: So spades in the ground this parliament. One and a 314 00:17:40,280 --> 00:17:43,520 Speaker 8: half million homes in this parliament, because we want to 315 00:17:43,560 --> 00:17:47,240 Speaker 8: go further and faster to kickstart economic growth and to 316 00:17:47,320 --> 00:17:50,720 Speaker 8: make our economy more competitive, to be a more attractive 317 00:17:50,760 --> 00:17:54,520 Speaker 8: place for businesses to invest, and ultimately to make working 318 00:17:54,520 --> 00:17:55,440 Speaker 8: people better off. 319 00:17:57,760 --> 00:18:00,720 Speaker 9: Chancellor, we've heard a lot about growth over reseas and 320 00:18:00,720 --> 00:18:02,560 Speaker 9: that do you think to be still some divisions amongst 321 00:18:02,600 --> 00:18:04,720 Speaker 9: your team around what all of these will mean for 322 00:18:04,760 --> 00:18:07,600 Speaker 9: the environment. Of course, businesses might be a little bit 323 00:18:07,640 --> 00:18:10,359 Speaker 9: confused about what kind of reaction function we can expect 324 00:18:10,400 --> 00:18:13,400 Speaker 9: you to have around green issues. Do you think that 325 00:18:13,680 --> 00:18:16,800 Speaker 9: the green policies of this government, or the push towards 326 00:18:17,640 --> 00:18:20,159 Speaker 9: electrification for example, all of these things are they a 327 00:18:20,200 --> 00:18:22,960 Speaker 9: little harder to predict for business now than they were? 328 00:18:26,760 --> 00:18:29,439 Speaker 8: Well, look at the record of this government. We've ended 329 00:18:29,480 --> 00:18:33,200 Speaker 8: the moratorium on onshore wind and indeed have signed off 330 00:18:33,240 --> 00:18:37,480 Speaker 8: planning applications in just six months for new onshore wind farms, 331 00:18:37,680 --> 00:18:41,600 Speaker 8: has signed off planning applications for solar farms that the 332 00:18:41,640 --> 00:18:46,000 Speaker 8: previous governments blocked. But we've invested alongside with BP and 333 00:18:46,160 --> 00:18:51,000 Speaker 8: Equanal in carbon capture and storage in te Side and Merseyside, 334 00:18:51,359 --> 00:18:55,480 Speaker 8: so we know that there are huge industrial and investment 335 00:18:55,520 --> 00:18:59,639 Speaker 8: opportunities for the private sector in these jobs and industries 336 00:18:59,680 --> 00:19:03,720 Speaker 8: of the and has unique strengths in this area because 337 00:19:03,720 --> 00:19:07,040 Speaker 8: of our industrial heritage and because of our geography to 338 00:19:07,119 --> 00:19:08,840 Speaker 8: reap the benefits of that investment. 339 00:19:10,800 --> 00:19:13,520 Speaker 9: Okay, Chancellor, can I ask you just about the US 340 00:19:13,600 --> 00:19:16,800 Speaker 9: Treasury Secretary Besant, who is now going to be your 341 00:19:16,800 --> 00:19:19,440 Speaker 9: counterparty in the United States. I wonder what you plan 342 00:19:19,560 --> 00:19:21,720 Speaker 9: to discuss with him, and do you have plans for 343 00:19:21,760 --> 00:19:22,720 Speaker 9: a conversation soon. 344 00:19:23,160 --> 00:19:26,399 Speaker 8: I'm really pleased that Scott Bessont was confirmed earlier this 345 00:19:26,440 --> 00:19:30,520 Speaker 8: week as the next to the US Treasury's Secretary. I 346 00:19:30,680 --> 00:19:34,639 Speaker 8: have written to him and I look forward to talking 347 00:19:34,680 --> 00:19:38,359 Speaker 8: to him soon about how our two countries can work 348 00:19:38,400 --> 00:19:42,160 Speaker 8: together and to grow our respective economies. And I look 349 00:19:42,200 --> 00:19:45,480 Speaker 8: forward to having a close relationship with Scott Bessant and 350 00:19:45,560 --> 00:19:46,920 Speaker 8: his team at the US Treasury. 351 00:19:47,600 --> 00:19:50,760 Speaker 2: That was the Chancellor Rachel Reeves speaking to Bloomberg's Anna Edwards, 352 00:19:50,840 --> 00:19:54,520 Speaker 2: Christy Gupta and Guy Johnson. So the government is going 353 00:19:54,600 --> 00:19:58,280 Speaker 2: for growth, but our businesses coming along for the ride. 354 00:19:58,400 --> 00:20:00,879 Speaker 2: We've been getting reaction from the back to General of 355 00:20:00,880 --> 00:20:04,560 Speaker 2: the British Chambers of Commerce, Chevron Haviland, who was one 356 00:20:04,560 --> 00:20:07,159 Speaker 2: of the first to turn critical in the wake of 357 00:20:07,200 --> 00:20:10,760 Speaker 2: the budget last year as growth flatlined and we saw 358 00:20:10,800 --> 00:20:14,639 Speaker 2: a dip in both consumer and business confidence. We spoke 359 00:20:14,720 --> 00:20:18,480 Speaker 2: to her just after Rachel Reeves's big announcement. 360 00:20:18,880 --> 00:20:21,359 Speaker 11: It will deliver it in the short term and lots 361 00:20:21,359 --> 00:20:25,760 Speaker 11: of different places. Remember this is a really difficult time 362 00:20:26,000 --> 00:20:30,560 Speaker 11: for business. Natal insurance increases are going, you know, coming 363 00:20:30,560 --> 00:20:33,600 Speaker 11: in place in just a few weeks, so tax rises 364 00:20:33,960 --> 00:20:37,600 Speaker 11: for all businesses. So it was really good to see 365 00:20:37,640 --> 00:20:44,600 Speaker 11: the Chancellor focus on economic growth, Airport expansion, Heathrow, Doncaster, Sheffield, 366 00:20:45,240 --> 00:20:48,560 Speaker 11: new road, rail low attempts crossing East West rail and 367 00:20:48,640 --> 00:20:52,080 Speaker 11: rebalancing the planning system as you were outlined. So those 368 00:20:52,160 --> 00:20:55,960 Speaker 11: things will have not just a there are a great 369 00:20:57,880 --> 00:21:01,960 Speaker 11: signifier global signify far of confidence and the direction we're 370 00:21:02,000 --> 00:21:04,760 Speaker 11: traveling in. You know, big infrastructure projects, as you say, 371 00:21:04,840 --> 00:21:06,800 Speaker 11: take a long time, so you need to start now. 372 00:21:07,359 --> 00:21:10,399 Speaker 11: But remember that indicator for the small and medium sized 373 00:21:10,400 --> 00:21:14,639 Speaker 11: businesses in those supply chains will already give them confidence 374 00:21:14,720 --> 00:21:17,720 Speaker 11: to think about investing now and growing their businesses now 375 00:21:18,440 --> 00:21:21,560 Speaker 11: so they can supply those into those infrastructure projects. 376 00:21:21,960 --> 00:21:23,800 Speaker 1: But Trevon, is it going to be enough. 377 00:21:23,920 --> 00:21:26,280 Speaker 12: Those businesses are worried about how they're going to pay 378 00:21:26,320 --> 00:21:29,239 Speaker 12: for the national insurance rise coming in a couple of 379 00:21:29,280 --> 00:21:32,000 Speaker 12: months time. The budget has been very difficult and we've 380 00:21:32,040 --> 00:21:35,200 Speaker 12: seen that reflected in both business and consumer confidence figures. 381 00:21:36,560 --> 00:21:39,920 Speaker 11: The budget has been very difficult. It has, and especially 382 00:21:39,920 --> 00:21:43,600 Speaker 11: if you have a business with a large employee base. 383 00:21:43,760 --> 00:21:46,680 Speaker 11: It is going to be very hard. Our businesses are 384 00:21:46,720 --> 00:21:49,000 Speaker 11: telling us they're going to have to put up prices 385 00:21:49,040 --> 00:21:51,000 Speaker 11: if they can. A lot of them have already put 386 00:21:51,080 --> 00:21:53,239 Speaker 11: up their prices. That's going to be tricky. They're going 387 00:21:53,280 --> 00:21:56,359 Speaker 11: to take it in their margin, which means lower investment, 388 00:21:57,080 --> 00:21:59,919 Speaker 11: or they're going to slow down recruitment. And all of 389 00:22:00,080 --> 00:22:02,200 Speaker 11: that is good. But you remember, at the same time 390 00:22:02,400 --> 00:22:06,320 Speaker 11: in the budget, the Chancellor also said to mitigate against 391 00:22:07,080 --> 00:22:10,720 Speaker 11: those issues, we need more opportunity for business, and she 392 00:22:10,840 --> 00:22:16,200 Speaker 11: talked about getting britten back to building homes, hospitals, energy, infrastructure, 393 00:22:16,640 --> 00:22:19,920 Speaker 11: and so you know, the announcements yesterday are a really 394 00:22:19,920 --> 00:22:22,800 Speaker 11: good step in that direction. They're a really good indicator 395 00:22:22,880 --> 00:22:26,879 Speaker 11: for that. Okay, things that infrastructure projects. It's not just 396 00:22:27,000 --> 00:22:30,760 Speaker 11: local supply chains and local economic development. Often supply chains 397 00:22:30,840 --> 00:22:37,280 Speaker 11: run all over the country. Connectivity, airport expansion. That's fantastic 398 00:22:37,359 --> 00:22:39,840 Speaker 11: for trade, you know, moving our goods around the world, 399 00:22:40,520 --> 00:22:42,240 Speaker 11: and it also global competitiveness. 400 00:22:42,600 --> 00:22:45,199 Speaker 2: Okay, but she did not reverse the tax increases on 401 00:22:45,320 --> 00:22:48,119 Speaker 2: business from the October budget. I mean, okay, you can 402 00:22:48,240 --> 00:22:51,040 Speaker 2: understand why she might not do that, but she will 403 00:22:51,080 --> 00:22:53,920 Speaker 2: be under pressure to do something in the spring statement. Potentially, 404 00:22:53,960 --> 00:22:56,639 Speaker 2: if her fiscal head doom disappears, that's either going to 405 00:22:56,640 --> 00:22:58,520 Speaker 2: be cuts to government or it's going to be more 406 00:22:58,560 --> 00:23:02,400 Speaker 2: tax increases. Are you expecting more tax increases to come? 407 00:23:02,520 --> 00:23:04,720 Speaker 2: Do you want her to do, let's say something that 408 00:23:04,760 --> 00:23:08,640 Speaker 2: would be much more business positive, lower corporation tax in Britain. 409 00:23:09,760 --> 00:23:13,040 Speaker 11: We well, I don't know what she's going to do 410 00:23:13,080 --> 00:23:16,320 Speaker 11: in the spring, and we're definitely not expecting any tax 411 00:23:16,680 --> 00:23:20,199 Speaker 11: increases for business. She's been pretty clear that that was 412 00:23:20,240 --> 00:23:21,520 Speaker 11: a what did you call it yesterday? 413 00:23:21,680 --> 00:23:22,240 Speaker 6: Once in a. 414 00:23:22,240 --> 00:23:29,040 Speaker 11: Generation tax increase. However, there are other places where she 415 00:23:29,119 --> 00:23:33,360 Speaker 11: can help business, so we've asked her to accelerate her 416 00:23:33,720 --> 00:23:36,800 Speaker 11: review of business rates. Business rates are the tax that 417 00:23:36,840 --> 00:23:40,399 Speaker 11: you pay on property, so really hard if you're on 418 00:23:40,440 --> 00:23:44,080 Speaker 11: the high Street, you know, before you've even sold a 419 00:23:44,119 --> 00:23:47,520 Speaker 11: single product, you're paying tens of thousands in tax. So 420 00:23:48,000 --> 00:23:50,560 Speaker 11: how she can review business rates and change those more 421 00:23:50,640 --> 00:23:54,160 Speaker 11: quickly to help our high streets? And actually, you know 422 00:23:54,320 --> 00:23:56,720 Speaker 11: the other thing is the quickest way to grow our 423 00:23:56,720 --> 00:24:01,199 Speaker 11: economy is through trade. Our biggest training partner, the EU, 424 00:24:01,520 --> 00:24:04,600 Speaker 11: is still really hard to move goods over the border. 425 00:24:04,680 --> 00:24:04,880 Speaker 6: There. 426 00:24:05,400 --> 00:24:09,120 Speaker 11: What is the government doing more quickly to help businesses 427 00:24:09,160 --> 00:24:10,359 Speaker 11: who are trading around the world. 428 00:24:10,800 --> 00:24:14,320 Speaker 2: That was chevallne Havilan from the British Chambers of Commerce. 429 00:24:14,600 --> 00:24:17,800 Speaker 2: She was sharing her reaction to chants of Rachel Reeves's 430 00:24:17,800 --> 00:24:21,240 Speaker 2: proposals that came out in the past few days. Speaking 431 00:24:21,280 --> 00:24:25,320 Speaker 2: to me and to Bloomberg's Stephen Carroll. Judging by her 432 00:24:25,400 --> 00:24:28,640 Speaker 2: media blitz over the past couple of days, Reeves has 433 00:24:28,680 --> 00:24:31,080 Speaker 2: a plan and she wants us to know about it. 434 00:24:31,440 --> 00:24:33,800 Speaker 2: But just how long will it take for the results 435 00:24:33,840 --> 00:24:37,600 Speaker 2: to materialize? And when can institutions like the Bank of 436 00:24:37,640 --> 00:24:41,560 Speaker 2: England expect to see those improvements in real life. These 437 00:24:41,600 --> 00:24:45,000 Speaker 2: are all questions that remain up in the air, some 438 00:24:45,119 --> 00:24:48,040 Speaker 2: of which will likely be put to Bank of England 439 00:24:48,080 --> 00:24:52,159 Speaker 2: Governor Andrew Bailey during his post Monetary Policy Committee press 440 00:24:52,200 --> 00:24:55,280 Speaker 2: conference in the next few days, and of course we 441 00:24:55,480 --> 00:24:58,320 Speaker 2: will have full coverage of the press conference and the 442 00:24:58,400 --> 00:25:03,280 Speaker 2: interest rate decision on Bloomberg. I'm Caroline HEPCUN London. You 443 00:25:03,320 --> 00:25:05,959 Speaker 2: can catch us every week day morning for Bloomberg Daybreak 444 00:25:06,000 --> 00:25:08,480 Speaker 2: here at beginning at six am in London, that's one 445 00:25:08,520 --> 00:25:09,480 Speaker 2: am on Wall Street. 446 00:25:09,560 --> 00:25:09,879 Speaker 4: Tom. 447 00:25:10,080 --> 00:25:13,199 Speaker 1: Thank you Caroline, and coming up on Bloomberg day Break weekend, 448 00:25:13,200 --> 00:25:15,800 Speaker 1: we head to China to see how AI startup Deep 449 00:25:15,840 --> 00:25:20,360 Speaker 1: seek as plans to take on US artificial intelligence giants. 450 00:25:20,800 --> 00:25:33,960 Speaker 1: I'm Tom Busby and this is Bloomberg. This is Bloomberg 451 00:25:34,040 --> 00:25:36,000 Speaker 1: day Break weekend, our global look ahead at the top 452 00:25:36,040 --> 00:25:39,040 Speaker 1: stories for investors in the coming week. I'm Tom Busby 453 00:25:39,080 --> 00:25:41,760 Speaker 1: in New York. It was a story that sent shock 454 00:25:41,800 --> 00:25:45,200 Speaker 1: waves through global markets last week, a Chinese startup releasing 455 00:25:45,200 --> 00:25:48,360 Speaker 1: an AI model set to rival open ais chat GPT 456 00:25:48,800 --> 00:25:52,159 Speaker 1: and allegedly at just a fraction of the cost. For 457 00:25:52,320 --> 00:25:55,200 Speaker 1: more on what's ahead for China's Deep Seek, let's get 458 00:25:55,200 --> 00:25:58,440 Speaker 1: to the host of the Daybreak Asia podcast, Doug Krisner. 459 00:25:59,040 --> 00:26:01,640 Speaker 3: Tom. The model is now own as R one, and 460 00:26:01,760 --> 00:26:04,440 Speaker 3: the claim made by deep Seek was that R one 461 00:26:04,600 --> 00:26:09,280 Speaker 3: rivaled or even outperformed leading Western chatbots on a range 462 00:26:09,320 --> 00:26:13,119 Speaker 3: of AI industry benchmarks. I think the most shocking claim 463 00:26:13,320 --> 00:26:16,240 Speaker 3: was R one was built for just a small fraction 464 00:26:16,320 --> 00:26:19,720 Speaker 3: of the cost of its Western rivals. Well, this immediately 465 00:26:19,760 --> 00:26:23,520 Speaker 3: sparked skepticism on the high valuation of US and Europe 466 00:26:23,640 --> 00:26:26,199 Speaker 3: and AI related companies, but I think the eye of 467 00:26:26,240 --> 00:26:29,119 Speaker 3: the storm was clearly in Nvidia. In the Monday session, 468 00:26:29,480 --> 00:26:34,320 Speaker 3: it shares tumbled seventeen percent, and that drop erased five 469 00:26:34,400 --> 00:26:37,399 Speaker 3: hundred eighty nine billion dollars from Nvidia's market cap in 470 00:26:37,520 --> 00:26:41,159 Speaker 3: one single trading day. For more on the deep Seek story, 471 00:26:41,200 --> 00:26:44,160 Speaker 3: I'm joined by Robert Lee He a senior software analyst 472 00:26:44,440 --> 00:26:47,639 Speaker 3: for Bloomberg Intelligence. Robert joining us from our studios in 473 00:26:47,680 --> 00:26:50,160 Speaker 3: Hong Kong. Robert, thank you for making time to chat 474 00:26:50,240 --> 00:26:53,560 Speaker 3: with me about what's happening at the deep Seek. This 475 00:26:53,840 --> 00:26:58,040 Speaker 3: Chinese artificial intelligence startup and the AI model that the 476 00:26:58,040 --> 00:27:01,320 Speaker 3: company has apparently been working on for a while are one. 477 00:27:01,840 --> 00:27:04,440 Speaker 3: What do we know about it exactly? Can you fill 478 00:27:04,480 --> 00:27:05,480 Speaker 3: me in sure? 479 00:27:05,560 --> 00:27:07,440 Speaker 13: Thanks very much for having me on. First of all, 480 00:27:07,880 --> 00:27:10,960 Speaker 13: as you would expect, Bluemberg Intelligence likes to lead the way, 481 00:27:11,000 --> 00:27:13,359 Speaker 13: this is actually Deep Seeker is a company we've been 482 00:27:13,400 --> 00:27:15,920 Speaker 13: writing on for the best part of seven or eight months. 483 00:27:16,160 --> 00:27:19,280 Speaker 13: I would say it's relatively well known to Asian investors 484 00:27:19,960 --> 00:27:22,760 Speaker 13: at this point, or has been for some time, but 485 00:27:22,760 --> 00:27:27,760 Speaker 13: obviously it's only its international profile has only risen more recently. 486 00:27:28,320 --> 00:27:32,080 Speaker 13: So the main reason why, or which helps you understand 487 00:27:32,160 --> 00:27:34,359 Speaker 13: why deep Seek is doing so well at the moment, 488 00:27:34,480 --> 00:27:38,119 Speaker 13: really goes back to the earlier export controls on the 489 00:27:38,160 --> 00:27:41,119 Speaker 13: semiconductor or chip side that we're put in place via 490 00:27:41,200 --> 00:27:45,119 Speaker 13: the US. And one point I've consistently made over the 491 00:27:45,200 --> 00:27:48,280 Speaker 13: last year or so is that, again not to trivialize 492 00:27:48,280 --> 00:27:51,480 Speaker 13: software development, but the technological barriers to entry on software 493 00:27:51,840 --> 00:27:54,840 Speaker 13: are significantly lower than on the chip side. It's far 494 00:27:54,960 --> 00:27:57,600 Speaker 13: easier to develop these algorithms than it is to design 495 00:27:57,640 --> 00:28:00,639 Speaker 13: a cutting edge tip at the atomic scale. So with 496 00:28:00,760 --> 00:28:03,840 Speaker 13: these export controls put in place by the US, obviously 497 00:28:03,840 --> 00:28:06,040 Speaker 13: any good engineer is going to try and work their 498 00:28:06,080 --> 00:28:08,600 Speaker 13: way around the problem. Go round it, go under it, 499 00:28:08,680 --> 00:28:09,199 Speaker 13: go over it. 500 00:28:09,280 --> 00:28:09,639 Speaker 1: Whatever. 501 00:28:10,280 --> 00:28:13,080 Speaker 13: So what the Chinese companies as a whole have done, 502 00:28:13,160 --> 00:28:16,679 Speaker 13: with deep Seek being the leading one, is moved to 503 00:28:17,280 --> 00:28:22,600 Speaker 13: more computationally efficient, smaller models that are more adept at 504 00:28:22,680 --> 00:28:25,960 Speaker 13: utilizing and running on locally developed chips from the likes 505 00:28:25,960 --> 00:28:31,000 Speaker 13: of Huawei, and that ultimately leads to models which are 506 00:28:31,160 --> 00:28:34,680 Speaker 13: faster to develop and more importantly, lower cost to both 507 00:28:34,720 --> 00:28:38,680 Speaker 13: develop and to train or inference, and that gives companies 508 00:28:38,720 --> 00:28:43,120 Speaker 13: like deep Seek a significant cost and efficiency advantage over 509 00:28:43,120 --> 00:28:46,440 Speaker 13: their domestic competitors in China. And also, as we've seen 510 00:28:46,480 --> 00:28:49,720 Speaker 13: in recent headlines, some of the big US tech platforms, 511 00:28:49,760 --> 00:28:52,360 Speaker 13: So it's really been a wake up call to the 512 00:28:52,520 --> 00:28:53,400 Speaker 13: entire industry. 513 00:28:53,920 --> 00:28:57,560 Speaker 3: How long have software programmers in China been working on this? 514 00:28:57,760 --> 00:28:59,800 Speaker 13: So give you a metric to work with. I guess 515 00:28:59,800 --> 00:29:01,760 Speaker 13: you know how many of us had heard of large 516 00:29:01,840 --> 00:29:05,560 Speaker 13: language models in China when Chat GPT first launched, and 517 00:29:05,600 --> 00:29:07,760 Speaker 13: they were next to none, So to quite a stat 518 00:29:07,800 --> 00:29:11,200 Speaker 13: at you. In October twenty twenty three, so you know, 519 00:29:11,320 --> 00:29:15,840 Speaker 13: roughly eighteen months ago or so, there were fourteen sanctioned 520 00:29:15,880 --> 00:29:20,680 Speaker 13: officially sanctioned models available in China from the regulator, and 521 00:29:20,680 --> 00:29:22,640 Speaker 13: then rolling forward to where we were at the end 522 00:29:22,680 --> 00:29:25,480 Speaker 13: of last year, they were close to three hundred. So 523 00:29:25,560 --> 00:29:30,160 Speaker 13: that highlights the very rapid progress that Chinese companies have made, 524 00:29:30,520 --> 00:29:34,680 Speaker 13: and as I said, with increasing focus on smaller, more 525 00:29:34,680 --> 00:29:38,560 Speaker 13: computationally efficient models in order to work their wear around 526 00:29:38,560 --> 00:29:42,239 Speaker 13: this problem caused by the US chip controls. Consequence of 527 00:29:42,280 --> 00:29:47,680 Speaker 13: that is their developments have remained on track and relatively unhindered, 528 00:29:48,000 --> 00:29:51,920 Speaker 13: but that has given them some potential cost advantage versus 529 00:29:52,040 --> 00:29:55,640 Speaker 13: the let me call it a more brute force approach 530 00:29:56,040 --> 00:29:58,920 Speaker 13: taken by companies in other parts of the world, not 531 00:29:59,080 --> 00:30:01,760 Speaker 13: just by the US. But again this is going back 532 00:30:01,800 --> 00:30:05,360 Speaker 13: to basic principles and engineering. You know, you may have 533 00:30:05,440 --> 00:30:08,760 Speaker 13: seen headlines at the end of last year given the 534 00:30:08,920 --> 00:30:11,680 Speaker 13: very high energy costs of these very large models. There 535 00:30:11,760 --> 00:30:16,160 Speaker 13: was even talk about restarting nuclear reactors, etc. I think, 536 00:30:16,240 --> 00:30:19,760 Speaker 13: you know, just Gutville, It just doesn't make sense. There 537 00:30:19,760 --> 00:30:22,680 Speaker 13: has to be an easier way to go about things. 538 00:30:22,760 --> 00:30:26,760 Speaker 13: And I think, you know, prompted by these external restrictions 539 00:30:26,800 --> 00:30:30,280 Speaker 13: placed on them, Like any good engineer, you know, the 540 00:30:30,400 --> 00:30:33,800 Speaker 13: Chinese have focused gone back to their code and try 541 00:30:33,840 --> 00:30:35,920 Speaker 13: to work around the problem, and that has developed them 542 00:30:36,080 --> 00:30:38,720 Speaker 13: some you know, highly competitive models as a result. 543 00:30:38,840 --> 00:30:41,720 Speaker 3: So it creates a big question mark over the bleeding 544 00:30:41,800 --> 00:30:45,600 Speaker 3: edge market for that hardware that you're talking about, obviously 545 00:30:45,680 --> 00:30:48,960 Speaker 3: on the GPU side, on the memory side as well, 546 00:30:49,040 --> 00:30:51,120 Speaker 3: right with those high bandwidth memory chips. 547 00:30:51,320 --> 00:30:53,640 Speaker 13: That remains in question. And in no way am I 548 00:30:53,720 --> 00:30:57,480 Speaker 13: trying to evade that question, because if the cost of 549 00:30:57,520 --> 00:31:02,640 Speaker 13: developing these models is decreasing, and on one hand, would 550 00:31:02,640 --> 00:31:05,320 Speaker 13: that lead to a proliferation in the number of models, 551 00:31:05,520 --> 00:31:08,760 Speaker 13: a proliferation more importantly in the number of applications out there, 552 00:31:10,000 --> 00:31:13,920 Speaker 13: and in some way, you know, actually accelerate the uptake 553 00:31:14,480 --> 00:31:18,280 Speaker 13: of these products within the wider market because of their 554 00:31:18,280 --> 00:31:21,520 Speaker 13: increased availability. That's one way that things could get and 555 00:31:21,560 --> 00:31:23,520 Speaker 13: I guess that would be a more positive way, you know. 556 00:31:23,560 --> 00:31:25,960 Speaker 13: On the negative side, and again I think it really 557 00:31:26,040 --> 00:31:29,080 Speaker 13: is up the debate and remains to be seen, you know, 558 00:31:29,240 --> 00:31:32,320 Speaker 13: is a potential negative for the hardware suppliers and the 559 00:31:32,440 --> 00:31:35,800 Speaker 13: likes of Nvideo, etc. Because again, this brute force approach 560 00:31:35,840 --> 00:31:38,560 Speaker 13: that's been taken so far. You know, I don't think 561 00:31:38,560 --> 00:31:41,200 Speaker 13: it's sustainable in the long run, both from a capital 562 00:31:41,240 --> 00:31:43,720 Speaker 13: point of view and you know, an environmental point of 563 00:31:43,800 --> 00:31:46,760 Speaker 13: view and an energy point of view. So I think 564 00:31:46,800 --> 00:31:49,880 Speaker 13: that it genuinely is uncertain at the moment, but should 565 00:31:49,920 --> 00:31:51,720 Speaker 13: become clearer in the coming months. 566 00:31:51,800 --> 00:31:54,440 Speaker 3: So what do you expect the impact to be of 567 00:31:54,480 --> 00:31:59,720 Speaker 3: the fact that are one, this AI model from deep 568 00:31:59,760 --> 00:32:02,920 Speaker 3: Ceas is open source. How is that going to impact 569 00:32:02,920 --> 00:32:03,480 Speaker 3: the industry? 570 00:32:03,720 --> 00:32:05,840 Speaker 13: Well, again, you know, my job is to take a 571 00:32:05,840 --> 00:32:10,640 Speaker 13: critical eye to thinks. But I think potentially there could 572 00:32:10,680 --> 00:32:13,800 Speaker 13: be a positive from that because in open source and 573 00:32:13,840 --> 00:32:19,080 Speaker 13: allowing external developers to really understand the nuts and bolts 574 00:32:19,080 --> 00:32:22,280 Speaker 13: of how they've put this model together. It's potentially a 575 00:32:22,320 --> 00:32:25,560 Speaker 13: positive for the industry and will help the industry as 576 00:32:25,600 --> 00:32:29,960 Speaker 13: a whole move towards you know, more efficient, lower cost 577 00:32:30,000 --> 00:32:34,240 Speaker 13: models overall. So again that is one potential direction of 578 00:32:34,280 --> 00:32:36,760 Speaker 13: travel that the industry could go in as a result 579 00:32:36,800 --> 00:32:39,400 Speaker 13: of this. Because, and again this may surprise some people 580 00:32:39,440 --> 00:32:43,680 Speaker 13: out there, this innovative Chinese company has been pretty transparent 581 00:32:44,320 --> 00:32:47,400 Speaker 13: about what it's done, so I think, you know, ultimately 582 00:32:47,480 --> 00:32:50,400 Speaker 13: that could be to the benefit of the entire industry. 583 00:32:50,680 --> 00:32:53,720 Speaker 13: But again its early days. It remains to be seen. 584 00:32:53,840 --> 00:32:55,400 Speaker 3: What do we know about the way in which this 585 00:32:55,640 --> 00:32:59,000 Speaker 3: R one model has been trained. When you hear stories 586 00:32:59,040 --> 00:33:02,560 Speaker 3: of how US AI chat parts have been trained, I 587 00:33:02,560 --> 00:33:06,520 Speaker 3: mean they're accumulating vast sums of data from the intranet 588 00:33:06,680 --> 00:33:09,920 Speaker 3: and that is helping to train these models. It's a 589 00:33:10,040 --> 00:33:12,720 Speaker 3: very different story in China though, where data is concerned, 590 00:33:12,760 --> 00:33:15,920 Speaker 3: is it not and is there anything to read into 591 00:33:16,720 --> 00:33:20,240 Speaker 3: kind of the context of a Chinese AI app being 592 00:33:20,360 --> 00:33:22,080 Speaker 3: developed on the mainland. 593 00:33:22,680 --> 00:33:25,440 Speaker 13: That's a very important point. And again when we've raised 594 00:33:25,440 --> 00:33:29,120 Speaker 13: in our research one issue that the Chinese companies do have. 595 00:33:29,400 --> 00:33:32,200 Speaker 13: First of all, there's the censorship rules, the Great Firewall, 596 00:33:32,280 --> 00:33:37,680 Speaker 13: et cetera. So obviously their availability to data in Chinese 597 00:33:37,760 --> 00:33:41,720 Speaker 13: language is relatively unrestricted within the confines of these censorship rules, 598 00:33:42,120 --> 00:33:47,160 Speaker 13: so as being commented widely. Yeah, sure, if you're asking 599 00:33:47,280 --> 00:33:51,160 Speaker 13: more sensitive, politically sensitive questions, for example, the model sort 600 00:33:51,160 --> 00:33:55,240 Speaker 13: of clam up and unwilling to answer that. But I 601 00:33:55,280 --> 00:33:58,760 Speaker 13: think the reality is the World Wide Web is dominated 602 00:33:58,800 --> 00:34:02,400 Speaker 13: by the English language. Forget the exact stat off the 603 00:34:02,400 --> 00:34:04,400 Speaker 13: top of my head, but you know it's like eighty 604 00:34:04,440 --> 00:34:06,720 Speaker 13: to ninety percent of all information on the world Wide 605 00:34:06,720 --> 00:34:11,800 Speaker 13: where globally is in English. And again, the Chinese aility 606 00:34:11,880 --> 00:34:14,040 Speaker 13: or the ability of Chinese companies to access that training 607 00:34:14,120 --> 00:34:17,560 Speaker 13: data is more limited versus companies in the US or Europe. 608 00:34:17,640 --> 00:34:19,759 Speaker 13: So again I think that's another issue they need to 609 00:34:19,800 --> 00:34:24,880 Speaker 13: work around in the long run. But you know, their models, 610 00:34:24,920 --> 00:34:29,239 Speaker 13: as have said, are highly efficient, highly cost competitive. The 611 00:34:29,239 --> 00:34:31,960 Speaker 13: fact that they're open sourcing this technology and making it 612 00:34:32,040 --> 00:34:37,960 Speaker 13: effectively available to everybody should ultimately help the developments and models, 613 00:34:38,000 --> 00:34:38,920 Speaker 13: you know, globally. 614 00:34:39,080 --> 00:34:42,279 Speaker 3: So if the efficiency of the technology, which seems to 615 00:34:42,320 --> 00:34:45,840 Speaker 3: have been demonstrated, is there, that will likely then I 616 00:34:45,840 --> 00:34:49,759 Speaker 3: would imagine, lead to increased demand for the resource. Is 617 00:34:49,800 --> 00:34:53,240 Speaker 3: this a pivotal moment for the adoption of chat bards 618 00:34:53,239 --> 00:34:55,560 Speaker 3: because of what this company is doing? 619 00:34:56,160 --> 00:35:00,040 Speaker 13: Right, One thing I have done repeatedly when I I 620 00:35:00,120 --> 00:35:02,520 Speaker 13: meet new people, when I talk to my friends and 621 00:35:02,600 --> 00:35:06,719 Speaker 13: family and colleagues, I normally will drop into conversation a 622 00:35:06,840 --> 00:35:10,800 Speaker 13: question just asking about their AI usage to see whether 623 00:35:10,840 --> 00:35:14,600 Speaker 13: they're using these spots, whether they're paying for bots. More importantly, 624 00:35:14,880 --> 00:35:18,280 Speaker 13: and although this is completely anecdotal, I think the reality 625 00:35:18,360 --> 00:35:20,680 Speaker 13: is the vast majority of us at the moment are 626 00:35:20,719 --> 00:35:21,880 Speaker 13: not paying for these things. 627 00:35:22,320 --> 00:35:23,160 Speaker 1: So why is that? 628 00:35:23,360 --> 00:35:25,799 Speaker 13: Particularly in this part of the world. In China, many 629 00:35:25,800 --> 00:35:28,200 Speaker 13: of these apps are free to use, and that's the 630 00:35:28,239 --> 00:35:31,280 Speaker 13: culture of Chinese apps in general. They tend to monetize 631 00:35:31,320 --> 00:35:35,120 Speaker 13: through advertising, But I think it reflects the level of 632 00:35:35,200 --> 00:35:39,400 Speaker 13: value add that the average consumer currently sees in the 633 00:35:39,440 --> 00:35:43,080 Speaker 13: current generation of bots and other AI tools. Whilst they're 634 00:35:43,120 --> 00:35:46,359 Speaker 13: interesting to play around with and maybe there are applications 635 00:35:46,360 --> 00:35:49,560 Speaker 13: in some areas, the vast majority of consumers are not 636 00:35:49,600 --> 00:35:51,760 Speaker 13: putting their hands in the pocket and paying for these things. 637 00:35:52,000 --> 00:35:54,600 Speaker 13: So the biggest challenge this industry faces at the moment 638 00:35:54,680 --> 00:35:58,040 Speaker 13: is monetization and tying back to the US tech platform. 639 00:35:58,160 --> 00:36:03,040 Speaker 13: Spending ten billion dollars plus per quarter in CAPEX, I 640 00:36:03,040 --> 00:36:06,640 Speaker 13: would say largely driven by fear of missing out, you know, 641 00:36:06,840 --> 00:36:09,319 Speaker 13: at some point we are going to hit a day 642 00:36:09,360 --> 00:36:14,080 Speaker 13: of reckoning if these companies are not monetizing fast enough 643 00:36:14,200 --> 00:36:17,080 Speaker 13: or in a in a more meaningful way. So whilst 644 00:36:17,280 --> 00:36:19,080 Speaker 13: Deepseeker is a bit of a wake up call to 645 00:36:19,120 --> 00:36:21,200 Speaker 13: show that, you know, Chinese obviously narrowing the gap and 646 00:36:21,200 --> 00:36:24,040 Speaker 13: the technology front, the big challenge for all these companies, 647 00:36:24,440 --> 00:36:27,959 Speaker 13: whatever region they operate in is monetization. In our view, 648 00:36:28,040 --> 00:36:31,960 Speaker 13: and we've published as repeatedly this is not happening fast enough, 649 00:36:32,480 --> 00:36:35,680 Speaker 13: and I think that is the major challenge this industry 650 00:36:35,760 --> 00:36:36,640 Speaker 13: still faces. 651 00:36:37,080 --> 00:36:39,080 Speaker 3: So what is the risk there? When I hear that, 652 00:36:39,239 --> 00:36:41,840 Speaker 3: it seems to suggest a lot of caution. 653 00:36:42,320 --> 00:36:46,520 Speaker 13: Well, there been so many bubbles and hype cycles in tech, 654 00:36:46,760 --> 00:36:49,840 Speaker 13: not just in recent years, whether it's crypto or metaverse, 655 00:36:49,920 --> 00:36:52,200 Speaker 13: and you know, going back to the year two thousand 656 00:36:52,440 --> 00:36:55,279 Speaker 13: and the Internet bubble, and I think there are some 657 00:36:55,360 --> 00:36:59,279 Speaker 13: parallels in all honesty with the Internet bubble. Ultimately, you know, 658 00:36:59,440 --> 00:37:02,759 Speaker 13: we internet is an essential part of everybody's life these days. 659 00:37:02,760 --> 00:37:04,920 Speaker 13: So I'm not in any way suggesting AI won't be 660 00:37:05,360 --> 00:37:08,399 Speaker 13: or isn't a useful tool, but I you know, whether 661 00:37:08,400 --> 00:37:12,279 Speaker 13: it goes back to the human psychology, human nature, there 662 00:37:12,320 --> 00:37:15,240 Speaker 13: tends to be an overreaction either way. So, whilst AI 663 00:37:15,520 --> 00:37:22,120 Speaker 13: is a very interesting and innovative technique that can drive 664 00:37:22,320 --> 00:37:26,840 Speaker 13: efficiency and cost savings across many applications, I think the reality, 665 00:37:26,840 --> 00:37:29,920 Speaker 13: as I've said, is the technology still at relatively immature phase, 666 00:37:30,440 --> 00:37:35,600 Speaker 13: and therefore the companies are struggling to monetize at anywhere 667 00:37:35,760 --> 00:37:40,080 Speaker 13: fast enough rate given the huge amounts, humongous amounts they're 668 00:37:40,120 --> 00:37:43,680 Speaker 13: spending on CAPEX at the moment. So I think obviously 669 00:37:43,920 --> 00:37:46,400 Speaker 13: it isn't such an issue for the very large tech platforms, 670 00:37:46,400 --> 00:37:49,719 Speaker 13: given their very healthy balance sheets in free cash flow generations. 671 00:37:49,760 --> 00:37:52,440 Speaker 13: But I think the more marginal players out there, you know, 672 00:37:52,480 --> 00:37:54,400 Speaker 13: at some point we'll have to make a decision. Can 673 00:37:54,440 --> 00:37:58,439 Speaker 13: they continue plowering such high amounts into CAPEX when there's 674 00:37:58,480 --> 00:38:01,560 Speaker 13: no or very limited chance of making a near term 675 00:38:01,600 --> 00:38:02,160 Speaker 13: return on this. 676 00:38:02,440 --> 00:38:05,240 Speaker 3: Robert, great stuff, Thank you so much. Robert Lee, Senior 677 00:38:05,280 --> 00:38:08,960 Speaker 3: analyst for Bloomberg Intelligence, joining us from Hong Kong. I'm 678 00:38:08,960 --> 00:38:11,840 Speaker 3: Doug Prisner. You can catch us weekdays for the Daybreak 679 00:38:11,880 --> 00:38:16,480 Speaker 3: Asia podcast. It's available wherever you get your podcast, Tom. 680 00:38:16,200 --> 00:38:18,160 Speaker 1: And that does it for this edition of Bloomberg day 681 00:38:18,160 --> 00:38:20,759 Speaker 1: Break Weekend. Join us again Monday morning at five am 682 00:38:20,840 --> 00:38:23,200 Speaker 1: Wall Street Time for the latest on markets overseas, in 683 00:38:23,239 --> 00:38:26,240 Speaker 1: the news you need to start your day. I'm Tom Buzzby. 684 00:38:26,440 --> 00:38:29,359 Speaker 1: Stay with us. Top stories and global business headlines are 685 00:38:29,400 --> 00:38:30,920 Speaker 1: coming up right now.