1 00:00:02,520 --> 00:00:09,280 Speaker 1: Bloomberg Audio Studios, podcasts, radio news from the heart of 2 00:00:09,360 --> 00:00:15,080 Speaker 1: where innovation, money and power collide in Silicon Valley and beyond. 3 00:00:15,520 --> 00:00:39,720 Speaker 1: This is Bloomberg Technology with Caroline Hyde and Ed Ludlow. 4 00:00:34,720 --> 00:00:36,960 Speaker 2: Live from New York and Las Vegas. This is Bloomberg 5 00:00:37,000 --> 00:00:40,720 Speaker 2: Technology coming up. In Vidia rise to Samsung's rescue after 6 00:00:40,760 --> 00:00:44,920 Speaker 2: disappointing quarterly results. Shares actually bounced back to Jensen Wang 7 00:00:44,960 --> 00:00:47,519 Speaker 2: expresses optimism for the memory maker. Plus, we sit down 8 00:00:47,520 --> 00:00:50,880 Speaker 2: with mobili at CS to discuss the future of autonomous 9 00:00:50,920 --> 00:00:53,480 Speaker 2: driving in the US and our conversation with the CEO 10 00:00:53,479 --> 00:00:56,600 Speaker 2: of Sirius XM on the company's focus on growth and 11 00:00:56,680 --> 00:00:59,960 Speaker 2: leveraging AI. Meanwhile, Jenson Wang makes impact on all of 12 00:01:00,160 --> 00:01:02,880 Speaker 2: quantum names that have rallied so hard in twenty twenty four. 13 00:01:02,880 --> 00:01:04,560 Speaker 2: They're off to a bad start in twenty and twenty five, 14 00:01:04,560 --> 00:01:06,040 Speaker 2: off by thirty three percent. 15 00:01:05,800 --> 00:01:07,440 Speaker 3: Of iron Q for all the others. 16 00:01:07,480 --> 00:01:09,640 Speaker 2: On the downside, just one saying, look, it's going to 17 00:01:09,680 --> 00:01:12,640 Speaker 2: take fifteen to thirty years before we get some significantly 18 00:01:12,760 --> 00:01:15,000 Speaker 2: useful quantum computing outcomes. 19 00:01:15,319 --> 00:01:17,040 Speaker 3: So pouring cold water and some of that optimism. 20 00:01:17,080 --> 00:01:20,240 Speaker 2: But on the upside, Jensen rides to the rescue of 21 00:01:20,280 --> 00:01:22,840 Speaker 2: Samsung were currently up three point four percent, even though 22 00:01:22,880 --> 00:01:26,360 Speaker 2: the numbers of their last quarter were dismal. But it 23 00:01:26,440 --> 00:01:29,400 Speaker 2: looks as though the high bandwidth memory chips are so 24 00:01:29,440 --> 00:01:32,280 Speaker 2: important to integrate into AI accelerators of in video while 25 00:01:32,319 --> 00:01:33,679 Speaker 2: they're coming at a pace. 26 00:01:34,000 --> 00:01:35,679 Speaker 3: Peter Elstrom has more on all of this. 27 00:01:35,760 --> 00:01:38,639 Speaker 2: Peter, just give us the nuance because Samsung has lagged 28 00:01:38,680 --> 00:01:42,040 Speaker 2: behind s K, Heihinis and smaller competitors when it comes 29 00:01:42,080 --> 00:01:45,400 Speaker 2: to high bandwidth memory. But some optimism from Jensen Wang here. 30 00:01:46,440 --> 00:01:49,720 Speaker 4: Yeah, that's exactly right. So Samsung reported preliminary earning, so 31 00:01:49,720 --> 00:01:51,720 Speaker 4: we're going to get the final earnings later. But as 32 00:01:51,760 --> 00:01:55,440 Speaker 4: you said, they were pretty terrible. They reported operating profit 33 00:01:55,560 --> 00:01:59,240 Speaker 4: of six point five trillion Walt's about four point five 34 00:01:59,240 --> 00:02:02,120 Speaker 4: billion dollars and so third less than everybody had been expecting. 35 00:02:02,200 --> 00:02:04,520 Speaker 4: Revenue was also a bit late. But just a few 36 00:02:04,520 --> 00:02:07,160 Speaker 4: words from Jensen Wong and the stock went up. And 37 00:02:07,240 --> 00:02:09,960 Speaker 4: really the reason for this is what he said was 38 00:02:10,000 --> 00:02:12,919 Speaker 4: not even that positive. But he said that Samsung has 39 00:02:13,000 --> 00:02:15,440 Speaker 4: to make this leap to AI chips. They have to 40 00:02:15,480 --> 00:02:17,800 Speaker 4: make these breakthroughs, and he said that they're working, they 41 00:02:17,840 --> 00:02:19,679 Speaker 4: can do it, and they're doing and they're working very 42 00:02:19,720 --> 00:02:21,480 Speaker 4: fast to do it. They're trying to come out with 43 00:02:21,480 --> 00:02:24,560 Speaker 4: the next generation of high bandwidth memory chips that will 44 00:02:24,600 --> 00:02:27,400 Speaker 4: be paired with the Nvidia AI accelerators to be able 45 00:02:27,400 --> 00:02:29,880 Speaker 4: to train these AI models. So just a few words 46 00:02:29,880 --> 00:02:33,160 Speaker 4: from Jensen Wong were really enough to turn around Samsung's fate. 47 00:02:33,440 --> 00:02:36,720 Speaker 4: He expressed some optimism that they're making progress. They're coming 48 00:02:36,760 --> 00:02:39,720 Speaker 4: out with a new design for the HBM chips, and 49 00:02:39,840 --> 00:02:41,880 Speaker 4: Vidio is going to get to the point where at 50 00:02:41,919 --> 00:02:43,760 Speaker 4: some point they're going to give them approval for these 51 00:02:43,919 --> 00:02:46,400 Speaker 4: HBM chips, then they can start to buy from them. 52 00:02:46,480 --> 00:02:49,359 Speaker 4: In addition to ask k Heinix essentially as Kahnks has 53 00:02:49,360 --> 00:02:52,320 Speaker 4: had a monopoly on this market so far, so in 54 00:02:52,440 --> 00:02:55,080 Speaker 4: Vidio wants competition there. They want Samsung to get into the. 55 00:02:55,080 --> 00:02:57,360 Speaker 2: Market, and boy hasn't been displayed in the share prices 56 00:02:57,480 --> 00:02:59,920 Speaker 2: right we saw sk heinicks up about twenty percent LAS, 57 00:03:00,320 --> 00:03:02,840 Speaker 2: whereas I think is about a third of the market 58 00:03:02,919 --> 00:03:06,160 Speaker 2: capitalization of Samsung was ripped away because of their seeming 59 00:03:06,840 --> 00:03:09,160 Speaker 2: delay on getting in on high bandwidth memory. 60 00:03:09,360 --> 00:03:11,320 Speaker 3: Are they having though to spend a lot? Is that 61 00:03:11,360 --> 00:03:13,120 Speaker 3: why we saw the disappointment in the numbers. 62 00:03:14,160 --> 00:03:17,240 Speaker 4: Yeah, certainly they're investing very heavily, and Samsung is not 63 00:03:17,360 --> 00:03:19,880 Speaker 4: used to being in this position. Samsung has long led 64 00:03:19,880 --> 00:03:21,960 Speaker 4: the memory market. They've been the biggest, they invest the 65 00:03:21,960 --> 00:03:24,280 Speaker 4: most amount of money, they get the best engineers, and 66 00:03:24,360 --> 00:03:26,320 Speaker 4: what they're seeing is that es khin has kind of 67 00:03:26,360 --> 00:03:28,680 Speaker 4: like the little brother in this market, has been able 68 00:03:28,720 --> 00:03:31,880 Speaker 4: to surpass them. And partly that's because Skhinnicks had a 69 00:03:31,919 --> 00:03:35,880 Speaker 4: breakthrough design and how they organized their HBM chips that 70 00:03:35,920 --> 00:03:38,480 Speaker 4: really help with some of the heat dissipation issues that 71 00:03:38,520 --> 00:03:41,760 Speaker 4: are necessary as we move into this higher powered computing 72 00:03:42,080 --> 00:03:45,680 Speaker 4: with AI in AI memory in particular. So eske Hynicks 73 00:03:45,680 --> 00:03:48,160 Speaker 4: has gotten ahead of them. They got invidious approval to 74 00:03:48,200 --> 00:03:50,440 Speaker 4: be able to ship these chips. That's been a huge 75 00:03:50,480 --> 00:03:52,720 Speaker 4: boom to esk Heynicks in their share price so far. 76 00:03:53,080 --> 00:03:56,000 Speaker 4: But they have Samsung right behind them, very determined to 77 00:03:56,040 --> 00:03:58,200 Speaker 4: catch up, and as we heard from Jensen Wong, they 78 00:03:58,200 --> 00:03:59,200 Speaker 4: are making progress. 79 00:03:59,640 --> 00:04:03,000 Speaker 2: Alstro, we thank you so much. Now that's head out 80 00:04:03,040 --> 00:04:05,480 Speaker 2: to Las Vegas. We are our own ed Ludlow was 81 00:04:05,560 --> 00:04:07,760 Speaker 2: on the ground at CES with the laterst dead. 82 00:04:08,560 --> 00:04:11,160 Speaker 5: Yeah, it's so interesting to hear Peter talk about the 83 00:04:11,200 --> 00:04:14,920 Speaker 5: semiconductor and AI demand at Samsung, because if you look 84 00:04:14,920 --> 00:04:17,760 Speaker 5: at the numbers, it was everything not AI that was 85 00:04:17,800 --> 00:04:20,080 Speaker 5: the pain point, and a lot of the street going 86 00:04:20,120 --> 00:04:21,680 Speaker 5: into that print. 87 00:04:21,279 --> 00:04:23,000 Speaker 6: Were like, well, what does Samsung do? 88 00:04:23,120 --> 00:04:26,080 Speaker 5: They sell smartphones and they smell, they sell high end 89 00:04:26,120 --> 00:04:29,760 Speaker 5: TVs and everything here at CES is all the rest, right. 90 00:04:29,760 --> 00:04:33,320 Speaker 5: They're always the biggest exhibitor here, high end appliances that 91 00:04:33,440 --> 00:04:35,640 Speaker 5: AI integrated. I don't know if you have an AI 92 00:04:35,680 --> 00:04:38,760 Speaker 5: integrated fridge or washing machine, Caroline, I don't know if 93 00:04:38,800 --> 00:04:41,640 Speaker 5: I need one. But that's what Samsung was hoping would 94 00:04:41,680 --> 00:04:45,599 Speaker 5: be a boost to profit in particular, and it didn't materialize. 95 00:04:45,960 --> 00:04:48,960 Speaker 2: It certainly didn't. But actually Jenson Wang right to the rescue, 96 00:04:49,040 --> 00:04:52,040 Speaker 2: and is Jensen's making moves whether it's on quantum stocks 97 00:04:52,040 --> 00:04:54,000 Speaker 2: as well. But just talk us through a little bit 98 00:04:54,040 --> 00:04:55,839 Speaker 2: more of what we're seeing unfolded when it comes to 99 00:04:55,880 --> 00:04:57,880 Speaker 2: actual consumer technology here. 100 00:04:58,920 --> 00:05:01,000 Speaker 5: Yeah, so if you and my in the ginormous hall 101 00:05:01,000 --> 00:05:03,000 Speaker 5: behind me, right at the center of it, out of shot, 102 00:05:03,080 --> 00:05:06,560 Speaker 5: is this like mini stadium, and that is Samsung's display. 103 00:05:06,600 --> 00:05:09,080 Speaker 5: It's always the biggest, and they are betting that the 104 00:05:09,120 --> 00:05:11,359 Speaker 5: consumer now is going to part with their cash to 105 00:05:11,400 --> 00:05:14,400 Speaker 5: build out their home in competition with Apple, in competition 106 00:05:14,440 --> 00:05:18,320 Speaker 5: with Amazon. I spoke to Jianjung, executive vice president, Samsung, 107 00:05:18,360 --> 00:05:22,240 Speaker 5: head of smart Things. It's all about efficiency, cost and energy. 108 00:05:22,240 --> 00:05:22,720 Speaker 6: Listen to this. 109 00:05:23,920 --> 00:05:28,120 Speaker 7: Twenty twenty four was the ten year anniversary since Samsung 110 00:05:28,200 --> 00:05:32,479 Speaker 7: acquired smart Things and started building this smart home experience 111 00:05:32,520 --> 00:05:37,479 Speaker 7: to our consumers. And with this smart Things platform, you know, 112 00:05:37,520 --> 00:05:40,839 Speaker 7: we are just so thrilled that each year we can 113 00:05:40,960 --> 00:05:45,560 Speaker 7: really deliver new, like innovative features to our customers and 114 00:05:45,800 --> 00:05:50,720 Speaker 7: like from like the kitchen to living room, bedroom and 115 00:05:50,880 --> 00:05:54,120 Speaker 7: all the appliances and TVs and you know watches and 116 00:05:54,240 --> 00:05:57,560 Speaker 7: rings and Galaxy devices that you know, with the smart 117 00:05:57,560 --> 00:06:01,000 Speaker 7: Things platform, we can really help you live in the 118 00:06:01,080 --> 00:06:04,520 Speaker 7: best way, like optimize, we can we can set the 119 00:06:05,000 --> 00:06:08,760 Speaker 7: optimized settings for you for your bedroom and kitchen and 120 00:06:09,240 --> 00:06:12,440 Speaker 7: living room. So so with the smart Things, you know, 121 00:06:12,480 --> 00:06:16,640 Speaker 7: the connectivity and then AI that we add to make 122 00:06:16,960 --> 00:06:21,240 Speaker 7: this appliances and device a small adaptable to your lifestyle. 123 00:06:21,680 --> 00:06:25,280 Speaker 7: I think that's the really great benefit of smart Things platform. 124 00:06:25,760 --> 00:06:27,000 Speaker 8: What can provide ideas? 125 00:06:27,120 --> 00:06:30,120 Speaker 5: Are you recognizing in the consumers, So for example, say 126 00:06:30,520 --> 00:06:35,320 Speaker 5: somebody watching this has never had a connected appliance to 127 00:06:35,400 --> 00:06:38,880 Speaker 5: device let alone and an. 128 00:06:38,760 --> 00:06:41,760 Speaker 9: AI capable washing machine or refrigerator. 129 00:06:41,839 --> 00:06:44,000 Speaker 7: Well, we think that you know, so you may want 130 00:06:44,040 --> 00:06:47,240 Speaker 7: to start with one like appliance at a time, right, 131 00:06:47,640 --> 00:06:52,760 Speaker 7: but once you once you experience that benefit, then I 132 00:06:53,160 --> 00:06:55,719 Speaker 7: like you may want to then change replace all the 133 00:06:55,760 --> 00:06:56,520 Speaker 7: other appliances. 134 00:06:56,600 --> 00:06:58,200 Speaker 3: I mean that's what I actually did. 135 00:06:58,680 --> 00:07:02,000 Speaker 7: So I recently moved to a new apartment and then 136 00:07:02,120 --> 00:07:04,040 Speaker 7: you know, I was like, okay, so maybe I can 137 00:07:04,200 --> 00:07:08,479 Speaker 7: sort of have a one new washing washer. And then 138 00:07:08,560 --> 00:07:11,000 Speaker 7: it's just the benefit is so great, right, so you 139 00:07:11,040 --> 00:07:14,440 Speaker 7: can remotely control it, you can see the energy use. 140 00:07:14,480 --> 00:07:16,720 Speaker 7: Then then why not you know, replace the dryer so 141 00:07:16,760 --> 00:07:19,920 Speaker 7: that I can have added benefit. And then you know, 142 00:07:20,080 --> 00:07:22,760 Speaker 7: once I see the value of okay, then with the 143 00:07:22,880 --> 00:07:25,720 Speaker 7: washer and dryer and then then cooked up and the hoods, 144 00:07:25,760 --> 00:07:29,240 Speaker 7: you know they all together, then you can say more energy, uh, 145 00:07:29,280 --> 00:07:33,200 Speaker 7: and then you can sort of have also coordinated control 146 00:07:33,280 --> 00:07:36,440 Speaker 7: that we can provide so kind of slowly, one at 147 00:07:36,440 --> 00:07:38,840 Speaker 7: a time, you can sort of build a smart home 148 00:07:38,920 --> 00:07:39,480 Speaker 7: that way. 149 00:07:39,840 --> 00:07:42,920 Speaker 5: This is the Consumer Electronics Show. But one of the 150 00:07:42,920 --> 00:07:46,640 Speaker 5: more interesting announcements I found was that you're taking small 151 00:07:46,720 --> 00:07:50,680 Speaker 5: things into a scenario that people might not expect with 152 00:07:51,040 --> 00:07:53,000 Speaker 5: some some heavy industries shipping. 153 00:07:53,440 --> 00:07:56,280 Speaker 9: It's talking big commercials right boats? 154 00:07:56,400 --> 00:07:56,600 Speaker 8: Right? 155 00:07:56,760 --> 00:07:57,440 Speaker 10: Why why? 156 00:07:57,560 --> 00:08:00,440 Speaker 9: Why? Why would a ship and a shipped crew need 157 00:08:00,560 --> 00:08:01,280 Speaker 9: small things? 158 00:08:01,640 --> 00:08:02,800 Speaker 8: Why not? Right? 159 00:08:02,920 --> 00:08:07,960 Speaker 7: So? Right, So we are So this year's CS you'll 160 00:08:08,000 --> 00:08:12,360 Speaker 7: see our offerings in the home and beyond the home. 161 00:08:12,800 --> 00:08:16,680 Speaker 7: So we have the smart Things pro solution that we 162 00:08:16,800 --> 00:08:20,640 Speaker 7: built on top of smart Things platform. So this smart 163 00:08:20,680 --> 00:08:25,320 Speaker 7: Things pro solution is for business and we are expanding 164 00:08:25,480 --> 00:08:31,640 Speaker 7: that functionality to car fleet of cars and ships. So 165 00:08:32,280 --> 00:08:37,360 Speaker 7: you know, you'll see our exhibition of our collaboration with 166 00:08:37,440 --> 00:08:39,720 Speaker 7: Samsung Heavy industry this year. 167 00:08:41,240 --> 00:08:44,400 Speaker 2: The executive EP and head of smart Things at Samsung 168 00:08:44,440 --> 00:08:46,680 Speaker 2: there with Ed coming up. We'll be joined by the 169 00:08:46,679 --> 00:08:50,439 Speaker 2: Panasonic North American chairwoman and CEO, Megan may One Lee 170 00:08:50,679 --> 00:08:52,000 Speaker 2: live from CS. 171 00:08:52,400 --> 00:09:00,320 Speaker 3: This a bring bad technology. 172 00:09:07,960 --> 00:09:10,679 Speaker 5: Okay, welcome back to Las Vegas and some special coverage 173 00:09:10,800 --> 00:09:13,920 Speaker 5: of CS twenty twenty five. One of the big focuses 174 00:09:13,960 --> 00:09:17,679 Speaker 5: in this place is always about the technology behind energy, 175 00:09:17,960 --> 00:09:20,880 Speaker 5: the supply chain for energy. One of the companies that 176 00:09:20,960 --> 00:09:24,720 Speaker 5: talk about that most is Panasonic, from energy supply chain 177 00:09:24,800 --> 00:09:26,960 Speaker 5: right through to consumer products as well. And I'm delighted 178 00:09:27,000 --> 00:09:30,080 Speaker 5: to say that Megham Young Wong Lee, Panasonic's North America 179 00:09:30,200 --> 00:09:33,400 Speaker 5: CEO is here. As every year we talk and every 180 00:09:33,520 --> 00:09:36,439 Speaker 5: year there's an update. So let's start with what I 181 00:09:36,520 --> 00:09:39,920 Speaker 5: think your focus was, which was energy supply chain. Yes, Why, 182 00:09:40,400 --> 00:09:43,920 Speaker 5: what's new and in particular, how are you using artificial 183 00:09:43,960 --> 00:09:46,360 Speaker 5: intelligence to get better? 184 00:09:46,760 --> 00:09:46,920 Speaker 10: Yes. 185 00:09:48,120 --> 00:09:52,000 Speaker 11: So we did the Kenot speech yesterday and our message 186 00:09:52,160 --> 00:09:55,079 Speaker 11: was all about well into the future as one hundred 187 00:09:55,080 --> 00:09:57,959 Speaker 11: and six years old old company, and we're making big 188 00:09:58,040 --> 00:10:01,559 Speaker 11: investment in North America in the area energy for evy batteries. 189 00:10:02,080 --> 00:10:04,679 Speaker 11: A supply chain is also a critical part of our 190 00:10:04,800 --> 00:10:07,480 Speaker 11: business and the area that we're trying to make a 191 00:10:07,520 --> 00:10:14,240 Speaker 11: contribution for a more efficient smart supply chain solutions. So 192 00:10:14,520 --> 00:10:18,000 Speaker 11: we about blu Yonder and blue Yonder is coming out 193 00:10:18,120 --> 00:10:23,360 Speaker 11: with an end to end visibility capability with AI agent. 194 00:10:23,640 --> 00:10:27,679 Speaker 11: They can customize for your problems and solutions and can 195 00:10:27,760 --> 00:10:30,679 Speaker 11: work with you. So we're really excited about that announcement. 196 00:10:31,480 --> 00:10:33,319 Speaker 6: What kind of a deal was that? How difficult was 197 00:10:33,400 --> 00:10:34,200 Speaker 6: it gets to be done? 198 00:10:34,240 --> 00:10:37,640 Speaker 5: You know, like the story of twenty twenty four was companies, 199 00:10:37,760 --> 00:10:41,679 Speaker 5: industrial companies particularly going out and saying we're either going 200 00:10:41,720 --> 00:10:43,839 Speaker 5: to have to acquire capabilities, we're going to have to 201 00:10:43,920 --> 00:10:44,720 Speaker 5: grow them internally. 202 00:10:45,280 --> 00:10:49,600 Speaker 11: You went one way, yes, yes, So we started working 203 00:10:49,640 --> 00:10:51,760 Speaker 11: with them a couple of years ago, and we're really 204 00:10:51,800 --> 00:10:57,120 Speaker 11: excited about their our ability and investment that we made 205 00:10:57,160 --> 00:11:00,760 Speaker 11: with blue Yonder and their capability to really the problem 206 00:11:00,960 --> 00:11:04,559 Speaker 11: of the supply chain resilience and safety and will be 207 00:11:04,679 --> 00:11:07,800 Speaker 11: the forthcoming with the newer technology, and we're really excited 208 00:11:07,840 --> 00:11:12,160 Speaker 11: about that. So it's a bully under subsidiary subsidiary of Panasonic, 209 00:11:12,640 --> 00:11:16,600 Speaker 11: and they're in North America based and it's a great 210 00:11:16,640 --> 00:11:19,040 Speaker 11: announcement for US and newer capability for us. 211 00:11:19,360 --> 00:11:23,320 Speaker 5: You said two things, supply chain resilience and investing in America. 212 00:11:23,880 --> 00:11:25,959 Speaker 5: And I post on social media every year that I'm 213 00:11:26,000 --> 00:11:27,880 Speaker 5: going to be speaking to you, and every year I 214 00:11:27,960 --> 00:11:29,360 Speaker 5: get dozens of questions. 215 00:11:29,640 --> 00:11:32,160 Speaker 6: Hundreds actually in this case, I would say. 216 00:11:32,040 --> 00:11:36,040 Speaker 5: The vast majority are about the upcoming Trump administration and 217 00:11:36,559 --> 00:11:41,920 Speaker 5: potential tariffs and policy around China. And that's so interesting 218 00:11:42,080 --> 00:11:45,360 Speaker 5: to you because of the Evy battery supply chain in 219 00:11:45,360 --> 00:11:46,440 Speaker 5: particular in this country. 220 00:11:46,880 --> 00:11:48,160 Speaker 6: What's your message around that? 221 00:11:49,160 --> 00:11:53,000 Speaker 11: So even before the Trump administration, the supply chain, I mean, 222 00:11:53,080 --> 00:11:55,920 Speaker 11: we all know that China controls a lot of row material. 223 00:11:56,520 --> 00:11:58,240 Speaker 6: We head out material being. 224 00:11:59,200 --> 00:12:02,720 Speaker 11: Yes, yes, the Eavy batteries yes, yes, So we've been 225 00:12:02,800 --> 00:12:06,200 Speaker 11: working hard even before I mean during COVID, everyone had 226 00:12:06,240 --> 00:12:09,800 Speaker 11: the challenge of managing supply chain. So we had that 227 00:12:10,040 --> 00:12:12,520 Speaker 11: issue of trying to make sure that the supply chain 228 00:12:12,640 --> 00:12:17,319 Speaker 11: is smooth and predictable and under control. So we have 229 00:12:17,559 --> 00:12:20,520 Speaker 11: vested interest to make sure that it's closer to the production. 230 00:12:21,280 --> 00:12:24,560 Speaker 11: The production being Reno and a newer factory in Kansas 231 00:12:24,679 --> 00:12:26,240 Speaker 11: which is opening up this spring. 232 00:12:26,440 --> 00:12:27,360 Speaker 8: We're really excited about. 233 00:12:27,360 --> 00:12:28,559 Speaker 6: Okay, give me more updates. 234 00:12:28,600 --> 00:12:31,319 Speaker 5: I have the next question from the audience, partip those 235 00:12:31,400 --> 00:12:34,920 Speaker 5: that follow names like Tesla right, ask give me a 236 00:12:35,040 --> 00:12:36,000 Speaker 5: factory update please. 237 00:12:36,160 --> 00:12:36,319 Speaker 6: Yes. 238 00:12:36,640 --> 00:12:40,400 Speaker 11: So our Reno operation has been really successful and it's 239 00:12:40,520 --> 00:12:43,400 Speaker 11: up and running for now ten years, and we're opening 240 00:12:43,480 --> 00:12:46,319 Speaker 11: up new operation in Kansas, and we've been building the 241 00:12:46,400 --> 00:12:48,800 Speaker 11: factory for now two years. It's going to open up 242 00:12:49,360 --> 00:12:53,440 Speaker 11: in April and well we'll be in full operation from 243 00:12:54,120 --> 00:12:58,120 Speaker 11: spring and summer this year. And we're working with partners 244 00:12:58,200 --> 00:13:01,600 Speaker 11: like Mazda Subaru which is a very announced and Lucid 245 00:13:01,679 --> 00:13:02,000 Speaker 11: as well. 246 00:13:02,120 --> 00:13:05,000 Speaker 6: That's right with the gravity projects exactly. Okay, that's interesting. 247 00:13:05,040 --> 00:13:07,400 Speaker 5: So I got a question for you about Lucid, and 248 00:13:07,760 --> 00:13:09,120 Speaker 5: when I read it from me, it was from an 249 00:13:09,120 --> 00:13:09,839 Speaker 5: audience member. 250 00:13:10,440 --> 00:13:12,920 Speaker 6: I was trying to think, like, what's what's the core 251 00:13:13,000 --> 00:13:13,520 Speaker 6: of this question? 252 00:13:13,679 --> 00:13:16,040 Speaker 5: But I think people were surprised that you partnered with 253 00:13:16,160 --> 00:13:18,880 Speaker 5: Lucid on the gravity it might not necessarily be a 254 00:13:19,000 --> 00:13:22,520 Speaker 5: high volume ev initially, what was your thinking there? 255 00:13:23,080 --> 00:13:26,120 Speaker 11: So Panasonic being a one hundred and six years old company, 256 00:13:26,240 --> 00:13:28,439 Speaker 11: and it's great to work with the partners. 257 00:13:28,040 --> 00:13:30,880 Speaker 3: Like Sabaru and Mazda, but we're very also. 258 00:13:30,760 --> 00:13:33,559 Speaker 11: Keen on working with up and coming, newer companies so 259 00:13:33,679 --> 00:13:36,360 Speaker 11: that they challenge us and we learn from them and 260 00:13:36,480 --> 00:13:39,679 Speaker 11: make sure that we're partnering and capable of partnering with 261 00:13:39,760 --> 00:13:40,840 Speaker 11: the companies like Lucid. 262 00:13:40,920 --> 00:13:42,079 Speaker 8: And we're really excited about that. 263 00:13:42,200 --> 00:13:43,079 Speaker 3: It's going really well. 264 00:13:43,440 --> 00:13:47,800 Speaker 5: I've covered that company a few years and interesting vehicles. 265 00:13:47,920 --> 00:13:50,560 Speaker 5: They're not very good at building them, you know, from 266 00:13:50,600 --> 00:13:53,120 Speaker 5: a volume perspective. When you make a decision like that, 267 00:13:53,280 --> 00:13:55,480 Speaker 5: how do you weigh that up in your head? You know, 268 00:13:55,679 --> 00:13:57,920 Speaker 5: because you want to be able to provide supply. It 269 00:13:58,040 --> 00:13:59,440 Speaker 5: helps you in supply chain planning. 270 00:14:00,200 --> 00:14:03,439 Speaker 11: I do think we as a company want to take 271 00:14:03,480 --> 00:14:06,680 Speaker 11: a chance and partner with the companies that operate different 272 00:14:06,720 --> 00:14:09,480 Speaker 11: ways than US. Bluyander is an example why it's a 273 00:14:09,520 --> 00:14:14,120 Speaker 11: software company US based, and Lucid is also a newer 274 00:14:14,200 --> 00:14:19,080 Speaker 11: partner too. But we have a success cases with Tesla 275 00:14:19,240 --> 00:14:22,160 Speaker 11: ten years ago and we're doing it again with Lucid, 276 00:14:22,240 --> 00:14:23,760 Speaker 11: and we're very bullish about that. 277 00:14:24,000 --> 00:14:26,640 Speaker 6: What is the latest on the Tesla relationship? Where are 278 00:14:26,680 --> 00:14:29,040 Speaker 6: you innovating and where do you see it progressing? 279 00:14:30,640 --> 00:14:34,080 Speaker 11: We are Panasonic as a Panasonic and really excited about 280 00:14:34,200 --> 00:14:35,800 Speaker 11: the forty six eighty capability. 281 00:14:36,200 --> 00:14:37,840 Speaker 6: Which where are we at with forty six eighty? 282 00:14:38,160 --> 00:14:40,160 Speaker 11: So that product is. 283 00:14:42,040 --> 00:14:43,680 Speaker 8: The capability and quality is great. 284 00:14:44,440 --> 00:14:48,920 Speaker 11: It's been tested and production in our mother company factory 285 00:14:49,000 --> 00:14:51,720 Speaker 11: in Japan, and we're planning on bringing it to our 286 00:14:51,800 --> 00:14:52,800 Speaker 11: cancas in the future. 287 00:14:53,320 --> 00:14:56,480 Speaker 5: You with respect, R a CS veteran. You've been to 288 00:14:56,640 --> 00:14:59,640 Speaker 5: many what's it been like this year? Many of the 289 00:15:00,480 --> 00:15:03,480 Speaker 5: and automakers are here just walking around. I feel like 290 00:15:03,960 --> 00:15:07,560 Speaker 5: even on the consumer electronics side, genuine consumer electronics, things 291 00:15:08,280 --> 00:15:11,200 Speaker 5: are positive. Yes, what have you been talking with your 292 00:15:11,240 --> 00:15:14,640 Speaker 5: customers your suppliers with what are they thinking about? 293 00:15:15,320 --> 00:15:19,200 Speaker 11: So we started working with CTA and CS since nineteen 294 00:15:19,280 --> 00:15:20,360 Speaker 11: sixty seven. 295 00:15:20,640 --> 00:15:23,680 Speaker 8: Okay, so we're one of the longer, so we feel. 296 00:15:23,480 --> 00:15:26,200 Speaker 3: Like we've grown up with the CTA. 297 00:15:26,480 --> 00:15:30,200 Speaker 11: CES is not necessarily so much about newer gadgets and products. 298 00:15:30,280 --> 00:15:31,960 Speaker 3: It's about our message. 299 00:15:32,360 --> 00:15:35,840 Speaker 11: Our keynote speech was about storytelling how we grew up 300 00:15:36,040 --> 00:15:40,320 Speaker 11: with the CTA for past sixty years, so we feel 301 00:15:40,400 --> 00:15:40,840 Speaker 11: really good. 302 00:15:41,000 --> 00:15:42,280 Speaker 8: AI was big last year. 303 00:15:43,200 --> 00:15:45,400 Speaker 3: This year it's all about application. 304 00:15:45,120 --> 00:15:49,040 Speaker 11: Even including us. We made an announcement about a product 305 00:15:49,080 --> 00:15:53,920 Speaker 11: called Umi. It's an AI wellness coach that's on the floor, 306 00:15:54,200 --> 00:15:58,040 Speaker 11: and you know, it's a newer capability that we're demonstrating 307 00:15:58,160 --> 00:16:01,200 Speaker 11: on this platform, which is a little different from our 308 00:16:01,400 --> 00:16:04,640 Speaker 11: past capability, but we are coming up with a newer 309 00:16:04,720 --> 00:16:06,560 Speaker 11: solution and AI product. 310 00:16:06,640 --> 00:16:09,160 Speaker 6: We just had fifteen seconds. Are you ready for the 311 00:16:09,160 --> 00:16:11,920 Speaker 6: Trump administration? Yes, we are, and. 312 00:16:12,000 --> 00:16:15,200 Speaker 11: We've been prepared for this and we will work with 313 00:16:15,280 --> 00:16:17,680 Speaker 11: the government to make sure that our investment in this 314 00:16:17,880 --> 00:16:21,280 Speaker 11: market is meaningful for our company as well as as 315 00:16:21,360 --> 00:16:22,320 Speaker 11: well as for the market. 316 00:16:22,600 --> 00:16:25,800 Speaker 5: Megan Young onely, I always appreciate catching up here in 317 00:16:25,880 --> 00:16:29,640 Speaker 5: Las Vegas, Panasonic North America CEO Caroline back to. 318 00:16:29,640 --> 00:16:30,200 Speaker 6: You in New York. 319 00:16:30,480 --> 00:16:33,200 Speaker 2: Great conversation and another story ed that we're watching and 320 00:16:33,280 --> 00:16:36,320 Speaker 2: it's going back to Anthropic, the open AI rival, is 321 00:16:36,360 --> 00:16:38,440 Speaker 2: in advanced talks to raise two billion dollars and a 322 00:16:38,480 --> 00:16:40,880 Speaker 2: funning round that would value the startup at sixty billion, 323 00:16:41,600 --> 00:16:45,280 Speaker 2: sources saying this Lightspeed Venture Partners is leading around. Anthropic 324 00:16:45,400 --> 00:16:47,800 Speaker 2: was recently on pace to generate around eight hundred and 325 00:16:47,840 --> 00:16:48,840 Speaker 2: seventy five million. 326 00:16:48,600 --> 00:16:50,120 Speaker 3: Dollars in annual revenue. 327 00:16:57,800 --> 00:17:01,040 Speaker 2: Serious XM, the online radio service, so is it's focused 328 00:17:01,080 --> 00:17:04,640 Speaker 2: on growth after it's twenty twenty five full costs missed expectations. 329 00:17:04,680 --> 00:17:05,600 Speaker 3: That was back in December. 330 00:17:05,880 --> 00:17:07,760 Speaker 2: Now, Belie Meg's Ed Ludlow just caught up with the 331 00:17:07,840 --> 00:17:11,000 Speaker 2: CEO Jennifer Witz at CES and began with a discussion 332 00:17:11,040 --> 00:17:12,200 Speaker 2: on AI implementation. 333 00:17:13,520 --> 00:17:14,400 Speaker 8: In some ways, I think. 334 00:17:14,320 --> 00:17:17,959 Speaker 12: We're the ANTIAI in terms of in terms of content 335 00:17:18,080 --> 00:17:22,720 Speaker 12: creation and curation, right, So, you know, we pride ourselves 336 00:17:22,840 --> 00:17:25,480 Speaker 12: on the hosts and the programmers that we have, the 337 00:17:25,640 --> 00:17:29,000 Speaker 12: people that actually put together the channels and the shows. 338 00:17:29,280 --> 00:17:32,320 Speaker 12: It's the voices you hear every day on your commute, 339 00:17:32,560 --> 00:17:36,600 Speaker 12: but really drive that intimacy that audio offers in the connection. 340 00:17:37,600 --> 00:17:40,720 Speaker 12: Where we will leverage AI is in some respects where 341 00:17:40,760 --> 00:17:43,640 Speaker 12: others have used it as well to provide better discovery 342 00:17:43,720 --> 00:17:47,199 Speaker 12: and personalization, right, So we hope that our programmers can 343 00:17:47,280 --> 00:17:50,600 Speaker 12: really curate an experience to help you find what you love. 344 00:17:51,000 --> 00:17:54,679 Speaker 12: But also the technology of AI could create more personalization 345 00:17:54,960 --> 00:17:57,480 Speaker 12: in our marketing, in the product itself in terms of 346 00:17:57,520 --> 00:18:01,240 Speaker 12: recommendations to enhance that and more. And of course there's 347 00:18:01,280 --> 00:18:04,680 Speaker 12: lots of other benefits for AI in terms of cost 348 00:18:04,760 --> 00:18:06,720 Speaker 12: reduction and more efficiencies in the business. 349 00:18:06,760 --> 00:18:08,480 Speaker 8: Overall, this is Bloomberg. 350 00:18:08,680 --> 00:18:09,879 Speaker 6: So let's talk some business. 351 00:18:10,080 --> 00:18:13,080 Speaker 5: Last month, you basically said this is our revenue outlook 352 00:18:13,119 --> 00:18:16,880 Speaker 5: for twenty twenty five, and investors, for whatever reason, we're disappointed. 353 00:18:17,480 --> 00:18:19,760 Speaker 5: You also said that you're going to cut costs run 354 00:18:19,840 --> 00:18:23,520 Speaker 5: your business. How is the cost costing going and what 355 00:18:23,640 --> 00:18:26,800 Speaker 5: were the factors that I guess if you accept that 356 00:18:26,960 --> 00:18:30,160 Speaker 5: the revenue outlut is not what your investors want to see, 357 00:18:30,440 --> 00:18:32,920 Speaker 5: what were the factors behind it being what it was. 358 00:18:33,680 --> 00:18:37,160 Speaker 12: Yeah, So we're very focused on supporting the top line 359 00:18:37,200 --> 00:18:39,320 Speaker 12: and the two aspects of our business that we've talked about, 360 00:18:39,560 --> 00:18:43,440 Speaker 12: subscription and advertising, and we have opportunities to continue to 361 00:18:43,560 --> 00:18:45,760 Speaker 12: grow there and drive improvements to that part. 362 00:18:45,680 --> 00:18:47,880 Speaker 8: Of our business. But we're really focused on the subscription 363 00:18:48,040 --> 00:18:50,080 Speaker 8: side on what we do best. 364 00:18:50,320 --> 00:18:53,080 Speaker 12: Audio first, and in the car, because that's where we've 365 00:18:53,240 --> 00:18:56,040 Speaker 12: proven that we can really be successful, and that's where 366 00:18:56,160 --> 00:18:59,200 Speaker 12: radio is very successful in our ads business. We talked 367 00:18:59,200 --> 00:19:01,479 Speaker 12: about where we're at in terms of podcasts and other 368 00:19:01,560 --> 00:19:05,159 Speaker 12: content to build out that portfolio, and yes, cost reduction 369 00:19:05,280 --> 00:19:07,359 Speaker 12: will be increasingly. 370 00:19:06,880 --> 00:19:08,160 Speaker 8: Important as we move forwards. 371 00:19:08,200 --> 00:19:11,040 Speaker 12: We want to sustain our industry leading margins, and on 372 00:19:11,160 --> 00:19:14,640 Speaker 12: top of that, we also have significant free cash flow 373 00:19:14,720 --> 00:19:18,160 Speaker 12: generation right and as we get to our target leverage ratio, 374 00:19:18,520 --> 00:19:22,840 Speaker 12: we'll be able to increasingly return capital and shareholders, whether 375 00:19:22,880 --> 00:19:26,800 Speaker 12: it's through our dividend or through show repurchases as well. 376 00:19:26,960 --> 00:19:28,800 Speaker 5: I think I'm right in saying this is your first 377 00:19:28,880 --> 00:19:33,560 Speaker 5: CES in about five years. That's right, It's packed. There 378 00:19:33,640 --> 00:19:36,640 Speaker 5: is an intense focus on the exhibitors AI. I would 379 00:19:36,680 --> 00:19:39,120 Speaker 5: also say there are lots of questions about what twenty 380 00:19:39,200 --> 00:19:41,720 Speaker 5: twenty five is going to be like, in particular because 381 00:19:41,760 --> 00:19:43,960 Speaker 5: we have a new administration that will come into office 382 00:19:44,359 --> 00:19:47,720 Speaker 5: this month. How a serious extent preparing for that? Do 383 00:19:47,840 --> 00:19:50,600 Speaker 5: you see if being a factor to. 384 00:19:50,680 --> 00:19:53,680 Speaker 9: People that listen to audio in America this year? 385 00:19:54,760 --> 00:19:57,040 Speaker 12: We have a really diverse set of content, and I 386 00:19:57,080 --> 00:19:59,240 Speaker 12: think one of the things we saw during the election 387 00:19:59,560 --> 00:20:05,240 Speaker 12: is an increase in news and politics content consumption, which 388 00:20:05,320 --> 00:20:07,560 Speaker 12: is probably not surprising, but it just speaks to the 389 00:20:07,640 --> 00:20:10,520 Speaker 12: overall bundle and that we have something for everyone at 390 00:20:10,560 --> 00:20:13,160 Speaker 12: any given time depending on what's going on, and also 391 00:20:13,320 --> 00:20:16,280 Speaker 12: the value of live linear when something important is going on. 392 00:20:17,200 --> 00:20:18,960 Speaker 12: So I think, you know that's going to continue to 393 00:20:19,000 --> 00:20:20,719 Speaker 12: be a focus for us. And then you know there 394 00:20:20,760 --> 00:20:23,080 Speaker 12: are things like you know, people are focused on tariffs 395 00:20:23,119 --> 00:20:25,200 Speaker 12: and taxes and what happens with the auto business. 396 00:20:25,280 --> 00:20:27,040 Speaker 8: But you know, we feel really good. 397 00:20:26,920 --> 00:20:30,440 Speaker 12: About our position in terms of our availability across the 398 00:20:30,480 --> 00:20:33,359 Speaker 12: spectrum of auto manufacturers, being a lot of meetings with 399 00:20:33,440 --> 00:20:36,320 Speaker 12: the OEMs while we're here, in addition to advertisers, and 400 00:20:37,280 --> 00:20:39,480 Speaker 12: I think we feel good. December was a great month 401 00:20:39,560 --> 00:20:42,120 Speaker 12: for auto sales, so hopefully that's an indication of what's 402 00:20:42,160 --> 00:20:45,280 Speaker 12: going to come in twenty twenty five. Strong auto market 403 00:20:45,359 --> 00:20:46,200 Speaker 12: is great for our business. 404 00:20:47,240 --> 00:20:58,280 Speaker 2: Serious XM CEO Jennifer Witz There, welcome back to New 405 00:20:58,280 --> 00:21:00,800 Speaker 2: Meg Technology. I'm Caroline heid and new I'm looking at 406 00:21:00,880 --> 00:21:02,960 Speaker 2: d Wave Quantum as one of the key quantum stocks 407 00:21:03,000 --> 00:21:05,600 Speaker 2: we are keeping an eye on. Jensen Wang takes a 408 00:21:05,720 --> 00:21:08,400 Speaker 2: sledgehammer to some of these market capitalizations by saying, look, 409 00:21:08,480 --> 00:21:11,360 Speaker 2: quantum from a really useful perspective, I'll gonna be there 410 00:21:11,680 --> 00:21:14,280 Speaker 2: for about fifteen years. Many got very excited post the 411 00:21:14,320 --> 00:21:18,080 Speaker 2: Google Willow AI chip and Quantum chip at that. But 412 00:21:18,240 --> 00:21:19,800 Speaker 2: let's just talk a little bit more about what Video 413 00:21:19,880 --> 00:21:22,159 Speaker 2: CEO Jensen Woe has been saying. He actually joined us 414 00:21:22,200 --> 00:21:24,680 Speaker 2: yesterday at CES and had this to say about the 415 00:21:24,720 --> 00:21:26,119 Speaker 2: outlook for autonomous driving. 416 00:21:26,240 --> 00:21:26,800 Speaker 3: Just take a listen. 417 00:21:27,520 --> 00:21:30,880 Speaker 13: The automics vehicle industry and the robotics industry is reillly 418 00:21:30,880 --> 00:21:32,399 Speaker 13: im point to us, and we offer three. 419 00:21:32,320 --> 00:21:33,200 Speaker 10: Computers for them. 420 00:21:33,600 --> 00:21:37,320 Speaker 14: We offered, of course the training computer three DGX through DGX, 421 00:21:37,680 --> 00:21:40,080 Speaker 14: the robotics computer that's inside the car or inside of 422 00:21:40,160 --> 00:21:43,240 Speaker 14: robot and now we have this new computer called Omniverse 423 00:21:44,440 --> 00:21:48,720 Speaker 14: with Cosmos that is the digital twin or the playground 424 00:21:48,800 --> 00:21:50,120 Speaker 14: where these robots. 425 00:21:49,800 --> 00:21:50,960 Speaker 6: Can learn how to be robots. 426 00:21:51,359 --> 00:21:54,080 Speaker 13: And so if we could accelerate the development of an 427 00:21:54,200 --> 00:21:58,280 Speaker 13: artificial intelligence for avs and for robotics, it brings. 428 00:21:58,080 --> 00:21:59,119 Speaker 10: In a lot of business for us. 429 00:22:01,160 --> 00:22:04,280 Speaker 5: So interesting to see in video move in more aggressively 430 00:22:04,400 --> 00:22:07,879 Speaker 5: to autonomous driving. Part of that Cosmos Foundation model play 431 00:22:08,600 --> 00:22:12,480 Speaker 5: is the generation of synthetic data text input generate images 432 00:22:12,520 --> 00:22:16,120 Speaker 5: of video train models on that video rather than real 433 00:22:16,160 --> 00:22:18,639 Speaker 5: world data. A lot happening in this space. One of 434 00:22:18,680 --> 00:22:21,720 Speaker 5: the key players mobilize and the CEO I'm not Sashu 435 00:22:22,160 --> 00:22:24,000 Speaker 5: joins us once again in Las Vegas. 436 00:22:24,280 --> 00:22:25,639 Speaker 6: That is an academic debate. 437 00:22:26,240 --> 00:22:29,840 Speaker 5: I've always understood mobilized advantage to be that you have 438 00:22:30,560 --> 00:22:33,720 Speaker 5: scs or chips in vehicles already on real roads around 439 00:22:33,760 --> 00:22:38,080 Speaker 5: the world. Real world data, Jensen says, synthetic data. 440 00:22:38,560 --> 00:22:41,560 Speaker 15: What do you say, Well, synthetic data is a big 441 00:22:41,680 --> 00:22:46,960 Speaker 15: thing in humanoid robotics. Why for humanoid robotics because each 442 00:22:47,119 --> 00:22:51,760 Speaker 15: robot has different actuator types, different placement of actuators. So 443 00:22:51,840 --> 00:22:55,600 Speaker 15: if you build a foundation model using some architecture of 444 00:22:55,680 --> 00:22:59,000 Speaker 15: your robot, it will not generalize to other architectures. If 445 00:22:59,040 --> 00:23:02,000 Speaker 15: you build a foundation model from synthetic data, you can 446 00:23:02,080 --> 00:23:06,720 Speaker 15: have something that generalizes to all robots. For example, you know, 447 00:23:06,800 --> 00:23:10,160 Speaker 15: I co founded a company in humanoid robotics, manter Robotics, 448 00:23:10,200 --> 00:23:14,400 Speaker 15: three years ago. So they rely heavily on Nvidia's physics 449 00:23:14,680 --> 00:23:18,960 Speaker 15: simulators and build foundational robots from synthetic data, and you 450 00:23:19,080 --> 00:23:23,240 Speaker 15: can then train dexterity. You can pick in place of 451 00:23:23,640 --> 00:23:28,240 Speaker 15: objects grasping and so forth, just from synthetic data. With cars, 452 00:23:28,560 --> 00:23:32,120 Speaker 15: it's different with cars. All cars look alike in terms 453 00:23:32,119 --> 00:23:32,880 Speaker 15: of factuations. 454 00:23:33,119 --> 00:23:33,239 Speaker 11: Right. 455 00:23:34,119 --> 00:23:37,600 Speaker 15: What you want to minimize is distribution drift. You don't 456 00:23:37,680 --> 00:23:42,280 Speaker 15: want to train a model on some artifact that could 457 00:23:42,359 --> 00:23:45,560 Speaker 15: come from from synthetic data. Well, if you don't have 458 00:23:45,680 --> 00:23:47,840 Speaker 15: real data, that's all what you can do. But if 459 00:23:47,880 --> 00:23:50,800 Speaker 15: you have real data, then you can be more precise. 460 00:23:51,160 --> 00:23:53,479 Speaker 5: Well, I think the Jensen's argument was that these syndetic 461 00:23:53,600 --> 00:23:55,840 Speaker 5: data augments the real world data. 462 00:23:57,520 --> 00:23:59,919 Speaker 15: No, but what we do at Mobilize, say, for example, 463 00:24:00,000 --> 00:24:03,240 Speaker 15: we find an edge case, Okay, then we go to 464 00:24:03,440 --> 00:24:06,720 Speaker 15: a simulator. We have simulators, We go to a simulator 465 00:24:06,760 --> 00:24:09,200 Speaker 15: and we generate many, many examples. 466 00:24:08,720 --> 00:24:09,640 Speaker 6: Of that edge case. 467 00:24:09,960 --> 00:24:13,200 Speaker 15: Right, But it's this is a multiverse, multiverse, So this 468 00:24:13,359 --> 00:24:15,560 Speaker 15: is really really for edge cases, but not for the 469 00:24:15,960 --> 00:24:17,639 Speaker 15: kind of you know, main. 470 00:24:19,000 --> 00:24:23,480 Speaker 5: Saying multiverse like, this isn't spider Man, this is autonomous driving. 471 00:24:23,800 --> 00:24:25,680 Speaker 5: Let me just make an observation and at the team 472 00:24:25,720 --> 00:24:27,359 Speaker 5: in New York, let's bring up Mobilized shares. 473 00:24:27,840 --> 00:24:29,359 Speaker 6: The stocks down significantly. 474 00:24:30,440 --> 00:24:32,960 Speaker 5: Is that because video is coming out strong and saying 475 00:24:34,119 --> 00:24:36,360 Speaker 5: we want some of this autonomous driving market as well. 476 00:24:37,680 --> 00:24:38,280 Speaker 6: I don't think so. 477 00:24:38,640 --> 00:24:42,760 Speaker 15: I think investors were expecting announcements and we're not ready 478 00:24:42,800 --> 00:24:46,520 Speaker 15: yet with announcements. I think we'll have major announcements throughout 479 00:24:46,560 --> 00:24:47,840 Speaker 15: the year, but we're not ready yet. 480 00:24:48,600 --> 00:24:50,800 Speaker 6: And this is a natural response for that. 481 00:24:51,200 --> 00:24:53,440 Speaker 5: You have something to show, and that is the Volkswagen 482 00:24:53,560 --> 00:24:57,840 Speaker 5: ID Buzz, the Caampa van battery electric. You are working 483 00:24:57,960 --> 00:25:02,960 Speaker 5: with them on a higher level of autonomy for that product. 484 00:25:03,280 --> 00:25:07,000 Speaker 5: My understanding is like it's in the prototype phase. However, 485 00:25:08,000 --> 00:25:10,240 Speaker 5: a lot of the pieces are there to go to production, 486 00:25:10,800 --> 00:25:14,000 Speaker 5: but there is no plan as it stands to firm 487 00:25:14,760 --> 00:25:17,360 Speaker 5: drying go to production update US. 488 00:25:17,720 --> 00:25:19,840 Speaker 15: Well, no, there's a firm plan to go to production. 489 00:25:19,960 --> 00:25:21,520 Speaker 15: It's end of twenty twenty six. 490 00:25:22,160 --> 00:25:22,560 Speaker 10: Right now. 491 00:25:22,640 --> 00:25:25,719 Speaker 15: There are about one hundred and fifty vehicles not driving 492 00:25:25,840 --> 00:25:29,080 Speaker 15: in Hamburg and Munich in Austin, Texas. 493 00:25:29,720 --> 00:25:30,080 Speaker 5: Testing. 494 00:25:30,359 --> 00:25:32,800 Speaker 15: Yeah, testing, but there's a firm plan to go to 495 00:25:32,960 --> 00:25:34,119 Speaker 15: start off production. 496 00:25:34,240 --> 00:25:35,920 Speaker 6: That must be a really big deal for you guys. 497 00:25:36,520 --> 00:25:39,960 Speaker 15: Yes, but you know, robotaxis is a spectrum. We build 498 00:25:40,080 --> 00:25:43,320 Speaker 15: robotaxes with id bus and we'll also with the Scheffler 499 00:25:43,480 --> 00:25:48,280 Speaker 15: and the Vernia. We build with aud a consumer level 500 00:25:48,359 --> 00:25:52,880 Speaker 15: autonomous car, a level three level four on highways, which 501 00:25:52,880 --> 00:25:55,399 Speaker 15: will come out in twenty twenty seven. And by the way, 502 00:25:55,440 --> 00:25:58,920 Speaker 15: there's lots of commonality in hardware between those two. It 503 00:25:59,119 --> 00:26:03,960 Speaker 15: is the same q, the same boards. We are developing 504 00:26:04,880 --> 00:26:08,440 Speaker 15: imaging radars both for the consumer car and for the 505 00:26:08,600 --> 00:26:13,040 Speaker 15: and for the robotaxi, so that commonality would reduce costs considerably. 506 00:26:13,240 --> 00:26:16,639 Speaker 15: And we have also FSD like systems which we call 507 00:26:16,760 --> 00:26:18,520 Speaker 15: Supervision three hundred. 508 00:26:18,320 --> 00:26:20,880 Speaker 5: Thousand like in the sense they are camera vision based 509 00:26:20,920 --> 00:26:23,680 Speaker 5: system so purely camera based. 510 00:26:23,800 --> 00:26:26,560 Speaker 15: There is an optional front facing radar, but it's purely 511 00:26:27,240 --> 00:26:31,359 Speaker 15: camera based and it's it's eyes on. It means the 512 00:26:31,480 --> 00:26:33,639 Speaker 15: driver is still responsible. You cannot you cannot let go 513 00:26:33,760 --> 00:26:34,880 Speaker 15: of driving. 514 00:26:35,000 --> 00:26:36,080 Speaker 6: Very quick on this one. 515 00:26:37,760 --> 00:26:40,760 Speaker 5: Mobili has a broad offering in the theater of autonomous 516 00:26:40,840 --> 00:26:41,920 Speaker 5: driving robotaxi. 517 00:26:42,640 --> 00:26:46,560 Speaker 6: Which specific deployment do we see first. 518 00:26:47,400 --> 00:26:50,480 Speaker 15: Well, we see the Supervision we're already deployed in China. 519 00:26:50,520 --> 00:26:53,159 Speaker 15: But our next generation, which it's ninety five percent of 520 00:26:53,240 --> 00:26:55,200 Speaker 15: the focus of the company, is this next generation on 521 00:26:55,240 --> 00:26:57,760 Speaker 15: the I six coming out next year. It will be 522 00:26:57,880 --> 00:27:01,720 Speaker 15: on all Volkswagen Group eighteen models of the folks I 523 00:27:01,760 --> 00:27:05,320 Speaker 15: can go up, including Portion and Audi that's coming out 524 00:27:05,359 --> 00:27:09,040 Speaker 15: next year at twenty twenty six, and then Chauffeur, which 525 00:27:09,119 --> 00:27:11,840 Speaker 15: is the level three autonomous driving on highways, will come 526 00:27:11,880 --> 00:27:14,400 Speaker 15: twenty twenty seven, early twenty twenty seven. 527 00:27:14,480 --> 00:27:15,359 Speaker 10: I have to ask you this. 528 00:27:15,640 --> 00:27:18,080 Speaker 6: You are a key automotive supplier. 529 00:27:18,640 --> 00:27:21,280 Speaker 5: You must be speaking with your customers and partners this 530 00:27:21,440 --> 00:27:25,160 Speaker 5: week about the coming Trump administration. How do you think 531 00:27:25,280 --> 00:27:28,200 Speaker 5: that's going to impact twenty twenty five in the auto market, 532 00:27:28,280 --> 00:27:29,520 Speaker 5: particularly here in North America? 533 00:27:30,400 --> 00:27:32,919 Speaker 15: Now, putting politics aside, I think it's. 534 00:27:32,800 --> 00:27:34,520 Speaker 6: Going to take society but not policy. 535 00:27:34,640 --> 00:27:36,760 Speaker 15: Yeah, but I think from a policy point of view, 536 00:27:36,800 --> 00:27:39,520 Speaker 15: it's going to be very positive. The problem with the 537 00:27:39,680 --> 00:27:44,080 Speaker 15: US is that there's a patchwork of regulations state wise 538 00:27:44,160 --> 00:27:48,520 Speaker 15: and federal wise. If the President comes in and puts 539 00:27:48,880 --> 00:27:52,480 Speaker 15: and you know, puts things in order at the federal level, 540 00:27:52,960 --> 00:27:55,640 Speaker 15: it could promote autonomous driving, consider. 541 00:27:55,400 --> 00:27:58,600 Speaker 5: Which Elon must mentioned exactly. So I see that very positive. 542 00:27:58,920 --> 00:28:01,680 Speaker 5: I'm not just sure. Great catch up, Thank you for 543 00:28:01,720 --> 00:28:05,320 Speaker 5: your time. I will go and check out id Buzz Caroline. 544 00:28:05,560 --> 00:28:07,560 Speaker 5: We keep guying CSS Vegas. 545 00:28:07,320 --> 00:28:07,600 Speaker 10: Back to you. 546 00:28:08,119 --> 00:28:11,280 Speaker 2: Certainly do let's stick with autos because Scout Motors in 547 00:28:11,359 --> 00:28:14,120 Speaker 2: the US, its revival, is betting big on range. 548 00:28:13,920 --> 00:28:15,680 Speaker 3: Extenders on evs today. 549 00:28:15,680 --> 00:28:18,240 Speaker 2: It's come back by twenty twenty seven, that's as Volkswagen 550 00:28:18,240 --> 00:28:21,880 Speaker 2: relaunches the legendary name pipe. Ed sat down with the CEO, 551 00:28:22,000 --> 00:28:25,280 Speaker 2: Scott Keo, and began by asking him about the demand 552 00:28:25,440 --> 00:28:27,080 Speaker 2: the company has seen since its announcement. 553 00:28:28,359 --> 00:28:29,840 Speaker 10: Yeah, look, the reactions spend huge. 554 00:28:29,840 --> 00:28:31,720 Speaker 16: We're not giving the mixes, but I would say, you 555 00:28:31,800 --> 00:28:34,119 Speaker 16: know direction it will probably over fifty percent would be 556 00:28:34,480 --> 00:28:35,720 Speaker 16: in the range extended version. 557 00:28:35,840 --> 00:28:39,480 Speaker 6: Really, and I think in my why I think the motives, 558 00:28:39,840 --> 00:28:40,720 Speaker 6: I think there's two reasons. 559 00:28:40,840 --> 00:28:42,959 Speaker 10: I think one a portion of the America. 560 00:28:43,120 --> 00:28:45,880 Speaker 16: This gives us a fifty state vehicle, which I think 561 00:28:45,960 --> 00:28:48,920 Speaker 16: is exactly what Scout always wants it to be. I think, look, 562 00:28:49,000 --> 00:28:53,480 Speaker 16: what are the two challenges we see with electrication, charging infrastructure, 563 00:28:53,800 --> 00:28:56,200 Speaker 16: and of course this takes that all off the table, 564 00:28:56,280 --> 00:28:58,400 Speaker 16: and plus this convenience. So I think those two things 565 00:28:58,920 --> 00:29:00,000 Speaker 16: Ranger Center makes a lot of sense. 566 00:29:00,520 --> 00:29:02,520 Speaker 5: Let's find some common ground and give some context of 567 00:29:02,560 --> 00:29:05,320 Speaker 5: the audience about Scout. You know, one might frame it 568 00:29:05,520 --> 00:29:09,640 Speaker 5: is Volkswagen's play to take a foothold long term in 569 00:29:09,720 --> 00:29:10,960 Speaker 5: the US market. 570 00:29:12,320 --> 00:29:12,960 Speaker 10: Giving your CD. 571 00:29:13,120 --> 00:29:16,480 Speaker 5: You understand that, but we're waiting until twenty twenty seven, 572 00:29:18,080 --> 00:29:18,760 Speaker 5: it's a long way. 573 00:29:19,720 --> 00:29:23,239 Speaker 16: Look, I think what we're doing is we're storing an 574 00:29:23,240 --> 00:29:26,880 Speaker 16: American icon. I think Scout was an iconic American brand, 575 00:29:27,400 --> 00:29:29,560 Speaker 16: and now we're bringing it back to life. So if 576 00:29:29,600 --> 00:29:32,480 Speaker 16: you're waiting for just a product, well, yeah, twenty seven 577 00:29:32,600 --> 00:29:34,600 Speaker 16: might seem like a long time. But if we're stating 578 00:29:34,640 --> 00:29:37,720 Speaker 16: to restore an American igon, bring back four thousand jobs 579 00:29:37,760 --> 00:29:41,000 Speaker 16: into South Carolina, start an entirely new company. 580 00:29:41,480 --> 00:29:43,240 Speaker 10: I think it's the perfect time. So what the reaction 581 00:29:43,360 --> 00:29:44,400 Speaker 10: to the customers. 582 00:29:44,040 --> 00:29:46,160 Speaker 16: Has been, we want to go along for this journey, 583 00:29:46,200 --> 00:29:48,280 Speaker 16: and I think twenty seven is manageable. 584 00:29:48,680 --> 00:29:51,680 Speaker 5: What's interesting in some sense is that Scout is kind 585 00:29:51,720 --> 00:29:54,480 Speaker 5: of leading the way in the concept of extended range. 586 00:29:54,640 --> 00:29:57,080 Speaker 5: So you look at some of the legacy OEMs they 587 00:29:57,200 --> 00:30:01,160 Speaker 5: have put on pause, pure battery electric offerings, variant pickup 588 00:30:01,360 --> 00:30:03,920 Speaker 5: or otherwise, and they may now look at the plug 589 00:30:03,960 --> 00:30:05,680 Speaker 5: in hybrid or the extended range. 590 00:30:06,800 --> 00:30:09,640 Speaker 16: You see how this following See yeah, I do, and 591 00:30:09,720 --> 00:30:12,240 Speaker 16: I'll tell you why it's perfect technology. I think, first 592 00:30:12,280 --> 00:30:15,240 Speaker 16: and foremost, the two platforms are exactly the same. 593 00:30:15,400 --> 00:30:16,160 Speaker 10: This is critical. 594 00:30:16,360 --> 00:30:18,800 Speaker 16: So the platform for an EV and the platform an 595 00:30:18,840 --> 00:30:21,600 Speaker 16: extended range or exactly the same. The second thing, it 596 00:30:21,680 --> 00:30:25,120 Speaker 16: has zero impact on manufacturing and the plant, so you 597 00:30:25,160 --> 00:30:27,720 Speaker 16: don't need to retool the entire plant. It's two relatively 598 00:30:27,800 --> 00:30:30,040 Speaker 16: simple JIT operations, one for the tank and one for 599 00:30:30,120 --> 00:30:33,040 Speaker 16: the engine. So this gives you ultimate flexibility. You could 600 00:30:33,040 --> 00:30:34,800 Speaker 16: go from zero to one hundred percent, or fifty to 601 00:30:34,840 --> 00:30:38,080 Speaker 16: fifty whatever it is. So regardless of the way America goes, 602 00:30:38,240 --> 00:30:40,280 Speaker 16: we are put in a position for the next twenty 603 00:30:40,400 --> 00:30:43,000 Speaker 16: thirty years to have a tech platform right that can 604 00:30:43,080 --> 00:30:43,520 Speaker 16: navigate it. 605 00:30:43,760 --> 00:30:46,800 Speaker 2: Scout Motors CEO Scot Kio there coming up when we 606 00:30:46,960 --> 00:30:50,040 Speaker 2: joined by the Zeeman's US president and CEO, Barbara Hunton. 607 00:30:50,400 --> 00:31:09,120 Speaker 3: Again it's live from CES. This is bloting big technology Semens. 608 00:31:09,600 --> 00:31:13,080 Speaker 3: It's showcasing its vision for the future here and over 609 00:31:13,160 --> 00:31:14,040 Speaker 3: in Las Vegas as well. 610 00:31:14,120 --> 00:31:16,960 Speaker 2: Let's see, yes, a future where data, AI and automation 611 00:31:17,080 --> 00:31:20,920 Speaker 2: can provide more flexibility and optimization across the world's industries 612 00:31:21,000 --> 00:31:23,760 Speaker 2: big and small. And pleased to say Ed Ludlow is 613 00:31:23,840 --> 00:31:25,440 Speaker 2: now sitting down the key executive. 614 00:31:26,120 --> 00:31:28,719 Speaker 5: Yeah, what's so interesting about this is that we started 615 00:31:28,720 --> 00:31:31,920 Speaker 5: with video and in Vidia talked about in particular Omniverse. 616 00:31:32,000 --> 00:31:35,680 Speaker 5: It's simulation and three d graphics platform. Basically customers can 617 00:31:35,760 --> 00:31:38,520 Speaker 5: go in and work within it, but the customers are 618 00:31:38,520 --> 00:31:40,920 Speaker 5: also here, and that's what's so interesting about Zemons and 619 00:31:41,280 --> 00:31:46,240 Speaker 5: North America. Barbara Hunton, I find Omniverse hard to understand. 620 00:31:46,720 --> 00:31:48,560 Speaker 5: I would say it's at the center of what you've 621 00:31:48,600 --> 00:31:51,360 Speaker 5: been talking about as an Nvidia customer this week. 622 00:31:51,560 --> 00:31:55,320 Speaker 8: Explain yeah, in video is a treasured a partner of ours. 623 00:31:55,520 --> 00:31:58,640 Speaker 8: You know, Siemens as the maker of industrial software. 624 00:31:58,920 --> 00:32:02,360 Speaker 17: We've got the tools that help designers and engineers visualize 625 00:32:02,440 --> 00:32:07,400 Speaker 17: and actually work with the most comprehensive physics based digital twin. 626 00:32:07,880 --> 00:32:10,040 Speaker 17: But when you would look at the drawings that we'd produce, 627 00:32:10,080 --> 00:32:12,880 Speaker 17: they looked a lot like engineering drawings. Right now, layer 628 00:32:12,960 --> 00:32:16,800 Speaker 17: on the omniverse and bring that photorealistic rendering, and suddenly 629 00:32:17,320 --> 00:32:22,280 Speaker 17: engineers anywhere can connect look at this object that looks. 630 00:32:22,240 --> 00:32:24,440 Speaker 8: Like it will look in the real world. That's the 631 00:32:24,560 --> 00:32:25,480 Speaker 8: power of Omniverse. 632 00:32:25,560 --> 00:32:29,040 Speaker 5: I think something that will street. But generally people the 633 00:32:29,080 --> 00:32:32,239 Speaker 5: interest in technology are trying to understand. Is that all 634 00:32:32,280 --> 00:32:35,760 Speaker 5: sounds great. If you are a business, Does it help 635 00:32:35,800 --> 00:32:38,040 Speaker 5: you make more money? Does it make the running of 636 00:32:38,120 --> 00:32:40,240 Speaker 5: your facilities instantly better? 637 00:32:40,480 --> 00:32:40,640 Speaker 7: Oh? 638 00:32:40,760 --> 00:32:42,720 Speaker 8: My heavens yes, and let me tell you how. 639 00:32:43,440 --> 00:32:46,120 Speaker 17: Right here in our booth, we're featuring customers of ours 640 00:32:46,160 --> 00:32:50,520 Speaker 17: who've chosen to use our Siemens Accelerator platform, and what 641 00:32:50,600 --> 00:32:52,880 Speaker 17: they're doing is using these tools to help them in 642 00:32:52,960 --> 00:32:55,520 Speaker 17: the design phase in the manufacturing phase. Why would you 643 00:32:55,640 --> 00:32:58,600 Speaker 17: want to go digital first so that you can try 644 00:32:58,680 --> 00:33:02,600 Speaker 17: all kinds of permutations in the virtual world before actually 645 00:33:02,720 --> 00:33:06,200 Speaker 17: vending metal and making things for real. Think about Jet zero, 646 00:33:07,080 --> 00:33:10,160 Speaker 17: This is a blended wing aircraft that'll be brought to market. 647 00:33:10,600 --> 00:33:13,680 Speaker 17: And there Tom Leary, their CEO, said the other night 648 00:33:13,760 --> 00:33:14,000 Speaker 17: to me. 649 00:33:14,280 --> 00:33:16,520 Speaker 8: He said, we chose Semens because it's the best. 650 00:33:16,680 --> 00:33:19,800 Speaker 17: We wanted to start in the early phases with the 651 00:33:19,920 --> 00:33:23,520 Speaker 17: virtual designs that would allow us to flow through into 652 00:33:23,600 --> 00:33:24,800 Speaker 17: the manufacturing phase. 653 00:33:24,960 --> 00:33:27,320 Speaker 5: I guess, in really simple terms, if you build your 654 00:33:27,360 --> 00:33:30,960 Speaker 5: own product like that platform, do you then just basically 655 00:33:31,080 --> 00:33:33,280 Speaker 5: sell it as a high margin service? 656 00:33:33,640 --> 00:33:35,760 Speaker 6: How does it translate to the business model for Semens. 657 00:33:35,920 --> 00:33:38,280 Speaker 17: Yeah, we're engaging with customers in a lot of different ways. 658 00:33:38,360 --> 00:33:41,080 Speaker 17: In the olden days, we would have enterprise agreements. You know, 659 00:33:41,200 --> 00:33:45,440 Speaker 17: think about all the aerospace, automotive today, battery manufacturers. We 660 00:33:45,760 --> 00:33:49,520 Speaker 17: serve all of those markets, helping the designers, the manufacturers, 661 00:33:49,560 --> 00:33:52,640 Speaker 17: the operators, but we know that there's a need to 662 00:33:52,880 --> 00:33:55,080 Speaker 17: put all that in the cloud, make it accessible on 663 00:33:55,160 --> 00:33:56,840 Speaker 17: a per user basis. 664 00:33:56,800 --> 00:33:58,560 Speaker 8: So that even startups can get going. 665 00:33:58,680 --> 00:34:01,880 Speaker 17: And here with team centers offered up in our Semens 666 00:34:02,000 --> 00:34:05,520 Speaker 17: Accelerated Accelerated marketplace, if you went to Eureka Park, you'd 667 00:34:05,560 --> 00:34:08,200 Speaker 17: see a bunch of startups who are being onboarded, and 668 00:34:08,320 --> 00:34:12,440 Speaker 17: we're giving deep discounts for that license suite so that 669 00:34:12,520 --> 00:34:16,399 Speaker 17: people can get their entryway into this new economy that's 670 00:34:16,480 --> 00:34:16,960 Speaker 17: being built. 671 00:34:17,840 --> 00:34:20,480 Speaker 6: You are an experienced CS GOA yes. 672 00:34:21,000 --> 00:34:24,520 Speaker 5: This week in particular, how many conversations have you had 673 00:34:24,560 --> 00:34:29,640 Speaker 5: with customers partners about the upcoming administration tariffs and are 674 00:34:29,680 --> 00:34:30,279 Speaker 5: you ready for that? 675 00:34:30,360 --> 00:34:32,239 Speaker 8: At Semens, we're absolutely ready. 676 00:34:32,320 --> 00:34:35,600 Speaker 17: And here's what I keep telling our customers and certainly 677 00:34:35,760 --> 00:34:36,759 Speaker 17: our own organization. 678 00:34:37,320 --> 00:34:38,960 Speaker 8: We've been in the United States for one hundred and 679 00:34:38,960 --> 00:34:39,440 Speaker 8: sixty years. 680 00:34:39,480 --> 00:34:42,399 Speaker 17: We've worked with all of the administrations along the way, 681 00:34:42,880 --> 00:34:47,680 Speaker 17: and Siemens' capabilities are aligned with national priorities. So whether 682 00:34:47,760 --> 00:34:50,680 Speaker 17: we're talking about increasing the amount of electricity that's available 683 00:34:50,719 --> 00:34:53,560 Speaker 17: for data centers and using the switch gear that Semens make, 684 00:34:53,600 --> 00:34:56,320 Speaker 17: so whether we're talking about the resurgence of manufacturing and 685 00:34:56,440 --> 00:34:59,560 Speaker 17: these tools we're featuring. This is a moment when Semens 686 00:34:59,600 --> 00:35:00,520 Speaker 17: can have true impact. 687 00:35:00,719 --> 00:35:03,640 Speaker 5: You might benefit from some policy that's coming. Have you 688 00:35:03,719 --> 00:35:06,640 Speaker 5: had to adjust supply chain make it more onshore, more 689 00:35:06,680 --> 00:35:07,919 Speaker 5: focused In America. 690 00:35:07,719 --> 00:35:09,120 Speaker 8: This has been a trend for Semens. 691 00:35:09,200 --> 00:35:11,160 Speaker 17: Actually, you'd see if you looked at our global mega 692 00:35:11,200 --> 00:35:14,520 Speaker 17: trends we follow, glocalization is one of them. We truly 693 00:35:14,640 --> 00:35:18,279 Speaker 17: believe that bringing a manufacturing supply chains closer to the 694 00:35:18,320 --> 00:35:21,840 Speaker 17: point of use is going to be a trend going forward. 695 00:35:22,080 --> 00:35:25,920 Speaker 17: So we've been making in America for decades now, and no, 696 00:35:26,280 --> 00:35:28,680 Speaker 17: I don't see tremendous change coming for us. 697 00:35:28,719 --> 00:35:30,600 Speaker 8: But we truly want to be responsive. 698 00:35:31,320 --> 00:35:34,320 Speaker 17: In particular, we think that the kind of technology we 699 00:35:34,480 --> 00:35:38,640 Speaker 17: bring can make even government customers more efficient and effective. 700 00:35:38,800 --> 00:35:41,399 Speaker 5: So Elon Musk would like to hear that to talk 701 00:35:41,400 --> 00:35:43,520 Speaker 5: about it. You are someone that meets with so many 702 00:35:43,640 --> 00:35:45,640 Speaker 5: CEOs during the week. I always am grateful for your 703 00:35:45,680 --> 00:35:50,160 Speaker 5: time here at CES. Barbara Humpton, Siemens North America CEO, Caroline, that's. 704 00:35:50,000 --> 00:35:52,719 Speaker 3: You in New York and it's time now for talking tech. 705 00:35:52,840 --> 00:35:56,080 Speaker 2: First up, Tencent has announced its biggest buyback since two 706 00:35:56,120 --> 00:35:58,360 Speaker 2: thousand and six, we're purchasing three point. 707 00:35:58,280 --> 00:36:00,879 Speaker 3: Nine three million Hong Kong listed chef. The move comes 708 00:36:00,920 --> 00:36:01,319 Speaker 3: amid a. 709 00:36:01,400 --> 00:36:03,040 Speaker 2: Sell off in the stock after the tech film was 710 00:36:03,040 --> 00:36:05,840 Speaker 2: added to a US blacklist for alleged links to the 711 00:36:05,920 --> 00:36:09,200 Speaker 2: Chinese military. Plus, Indonesia keeps its Apple. 712 00:36:09,000 --> 00:36:10,480 Speaker 3: iPhone sixteen ban. 713 00:36:11,040 --> 00:36:13,960 Speaker 2: The country says the tech giants one billion dollar investment plan, 714 00:36:14,040 --> 00:36:17,239 Speaker 2: which includes building an air tag factory, is insufficient to 715 00:36:17,320 --> 00:36:20,960 Speaker 2: meet local investment requirements. Indonesia says it's willing to negotiate 716 00:36:21,040 --> 00:36:23,800 Speaker 2: with Apple, but may impose sanctions if the company continues 717 00:36:23,880 --> 00:36:27,919 Speaker 2: to not comply with the investment rules. And TikTok shop 718 00:36:28,200 --> 00:36:31,120 Speaker 2: rival whatnot has raised two hundred and sixty five million 719 00:36:31,160 --> 00:36:34,000 Speaker 2: dollars worth evaluation of four point ninety seven billion. The 720 00:36:34,200 --> 00:36:37,040 Speaker 2: LA based livestream shopping platform says it plans to use 721 00:36:37,080 --> 00:36:40,120 Speaker 2: those funds to hire engineers, improve customer service, and expand 722 00:36:40,280 --> 00:36:43,640 Speaker 2: into new countries. Whatnot's funding around coincides with a looming 723 00:36:43,800 --> 00:36:45,920 Speaker 2: US ban, potentially on TikTok. 724 00:36:46,000 --> 00:36:48,880 Speaker 3: Sending some of its live sellers maybe to competitors. 725 00:37:00,160 --> 00:37:02,720 Speaker 5: This ces in Las Vegas feels a little bit different. 726 00:37:02,880 --> 00:37:06,120 Speaker 5: Twenty twenty five. Yes, the inauguration of a new administration 727 00:37:06,239 --> 00:37:08,560 Speaker 5: is around the corner, but there's just been more news. 728 00:37:08,640 --> 00:37:09,440 Speaker 6: Nvidia kind of. 729 00:37:09,440 --> 00:37:11,200 Speaker 5: Kicked it all off in the week and here a 730 00:37:11,200 --> 00:37:14,239 Speaker 5: Bloomberg Technology. We're ramping up as well our coverage of 731 00:37:14,280 --> 00:37:17,680 Speaker 5: consumer technology. There's more to cover. AI is playing a 732 00:37:17,680 --> 00:37:20,160 Speaker 5: big part. I'm on my best behavior because the big 733 00:37:20,239 --> 00:37:23,480 Speaker 5: boss is in town, Senior Executive editor Tom Giles, and 734 00:37:23,560 --> 00:37:25,640 Speaker 5: we have a big team here and we are going 735 00:37:25,719 --> 00:37:29,080 Speaker 5: to go deeper and broader on consumer technology, how and why. 736 00:37:29,920 --> 00:37:34,279 Speaker 18: Right now is an incredibly exciting time in consumer electronics. 737 00:37:34,400 --> 00:37:38,720 Speaker 18: As you mentioned, AI is changing everything. It's getting woven 738 00:37:38,840 --> 00:37:42,520 Speaker 18: into every gadget we use, every robot that's infiltrating our 739 00:37:42,560 --> 00:37:47,200 Speaker 18: homes and our warehouses, our cars, the list goes on 740 00:37:47,400 --> 00:37:50,399 Speaker 18: and on, and it's changing things in a very dramatic way. 741 00:37:50,920 --> 00:37:53,759 Speaker 18: Right now is I think the time is right to 742 00:37:53,840 --> 00:37:56,120 Speaker 18: double down on our consumer electronics coverage. 743 00:37:56,239 --> 00:37:57,480 Speaker 10: We've always cared about the. 744 00:37:57,560 --> 00:38:01,239 Speaker 18: Business of CE. Right now it's time to do a 745 00:38:01,320 --> 00:38:04,279 Speaker 18: better job of telling the world where they can find 746 00:38:04,320 --> 00:38:05,000 Speaker 18: all this information. 747 00:38:05,080 --> 00:38:06,719 Speaker 10: There's a section on Bloomberg Doctor. 748 00:38:06,920 --> 00:38:08,759 Speaker 6: Right now, a place that we're going to show our 749 00:38:08,840 --> 00:38:09,239 Speaker 6: best work. 750 00:38:09,400 --> 00:38:11,600 Speaker 18: We're going to start we're going to We've been doing 751 00:38:11,719 --> 00:38:14,000 Speaker 18: product reviews, but we're going to be much more systematic 752 00:38:14,080 --> 00:38:17,680 Speaker 18: about it, much more consistent, much more comprehensive about it, 753 00:38:17,920 --> 00:38:21,080 Speaker 18: and we're going to talk about products in the context 754 00:38:21,160 --> 00:38:24,120 Speaker 18: of the business and the strategy of these corporations that 755 00:38:24,200 --> 00:38:26,759 Speaker 18: are trying to make money from these gadgets that are 756 00:38:26,840 --> 00:38:29,440 Speaker 18: changing the way we live and work and do our 757 00:38:29,480 --> 00:38:31,839 Speaker 18: everyday lives. We're going to talk about it in an 758 00:38:31,920 --> 00:38:34,960 Speaker 18: unbiased way, and we're also going to draw on this 759 00:38:36,800 --> 00:38:40,120 Speaker 18: group of journalists who have so much experience in writing 760 00:38:40,440 --> 00:38:44,840 Speaker 18: and thinking about consumer electronics. Everybody like vlad Savov, Mark German, 761 00:38:45,160 --> 00:38:48,440 Speaker 18: Dana Wolman, who we just hired from n Gadget in 762 00:38:48,520 --> 00:38:52,040 Speaker 18: the last year. Long list, Sharen Gafari, who writes about 763 00:38:52,160 --> 00:38:55,040 Speaker 18: artificial intelligence. The list goes on and on, and we've 764 00:38:55,080 --> 00:38:57,520 Speaker 18: got dozens of reporters around the world and they're going 765 00:38:57,560 --> 00:39:00,919 Speaker 18: to be bringing you the latest consumer electron so real quick. 766 00:39:01,000 --> 00:39:03,319 Speaker 5: CS is the first week of the year. It puts 767 00:39:03,360 --> 00:39:06,280 Speaker 5: everyone in one place, be dating with very important people. 768 00:39:06,640 --> 00:39:08,200 Speaker 5: What's it been like for you, Oh my. 769 00:39:08,239 --> 00:39:12,520 Speaker 18: Gosh, yesterday a lot of conversations with Nvidia, really interesting. 770 00:39:12,560 --> 00:39:15,480 Speaker 18: You talk to Jensen one on yourself. He wants to 771 00:39:15,600 --> 00:39:19,200 Speaker 18: map the physical world. He's creating this new world foundational 772 00:39:19,320 --> 00:39:22,960 Speaker 18: model that is going to help us understand how robots interact, 773 00:39:23,000 --> 00:39:26,040 Speaker 18: how cars interact. If you want to weave AI into 774 00:39:26,239 --> 00:39:30,160 Speaker 18: these physical devices, you need to understand how these objects 775 00:39:30,760 --> 00:39:33,840 Speaker 18: interact in the real world. That's just the beginning of 776 00:39:33,920 --> 00:39:36,359 Speaker 18: the really interesting, exciting things that we're seeing here. 777 00:39:36,560 --> 00:39:39,120 Speaker 5: It's hard to find somebody more excitable than me, carrab, 778 00:39:39,120 --> 00:39:41,160 Speaker 5: but I think we've done it with Bloomberg Senior Executive 779 00:39:41,280 --> 00:39:42,400 Speaker 5: edits Tom Giles. 780 00:39:42,200 --> 00:39:42,520 Speaker 6: Back to you. 781 00:39:42,719 --> 00:39:45,560 Speaker 2: He's giving a run for your money, almost on par 782 00:39:45,719 --> 00:39:49,240 Speaker 2: with the energy levels and what a joy all things CS. 783 00:39:49,400 --> 00:39:52,080 Speaker 2: Thank you for today's reporting. Meanwhile, that does it for 784 00:39:52,120 --> 00:39:54,320 Speaker 2: this edition of bloom Big Technology. And don't forget to 785 00:39:54,400 --> 00:39:56,960 Speaker 2: check out our podcast. Find it on the terminal as 786 00:39:57,000 --> 00:40:00,960 Speaker 2: well as online on Apple Spotify. And iHeart from New 787 00:40:01,040 --> 00:40:04,640 Speaker 2: York from a very busy Las Vegas. This is Lumbag Technology.