1 00:00:02,480 --> 00:00:07,000 Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. 2 00:00:07,720 --> 00:00:10,280 Speaker 2: We'd like to welcome in video CEO Jensen Wang to 3 00:00:10,360 --> 00:00:14,160 Speaker 2: the program, and Jensen, it's been an astonishingly busy day 4 00:00:14,200 --> 00:00:17,560 Speaker 2: for you in Washington, DC. So I'm grateful for your time. 5 00:00:18,400 --> 00:00:22,400 Speaker 2: You're sold out of Blackwell, that's what you said, but 6 00:00:22,520 --> 00:00:25,840 Speaker 2: also that five hundred billion dollar forecast, which is Blackwell 7 00:00:25,960 --> 00:00:30,160 Speaker 2: Rubin has room to grow. How do those fit together? 8 00:00:34,040 --> 00:00:40,760 Speaker 1: I said, sales are after charts for Blackwell and in 9 00:00:40,880 --> 00:00:44,879 Speaker 1: video GPUs in the cloud are sold out. We got 10 00:00:44,880 --> 00:00:47,879 Speaker 1: plenty of Blackwells to sell you. We have lots of 11 00:00:47,920 --> 00:00:51,920 Speaker 1: Blackwells coming, We're making a lot of Blackwells, and we 12 00:00:51,960 --> 00:00:57,040 Speaker 1: have a bunch of Vera Rubens coming and so business 13 00:00:57,120 --> 00:01:01,000 Speaker 1: is very very strong. But we we've planned our supply 14 00:01:01,080 --> 00:01:03,640 Speaker 1: chain incredibly well. We have the largest supply chain in 15 00:01:03,640 --> 00:01:09,759 Speaker 1: the world. Our partners TSMC, our memory partners, s k Heinex, Micron, 16 00:01:09,840 --> 00:01:13,520 Speaker 1: Samsung are doing a fantastic job supporting us. And all 17 00:01:13,520 --> 00:01:16,680 Speaker 1: of our systems partners, fox Con and Quantum and Wistron 18 00:01:17,200 --> 00:01:20,600 Speaker 1: are packaging partners. Everybody's doing a fantastic job supporting us. 19 00:01:20,680 --> 00:01:23,520 Speaker 1: And we've done a good job planning for a very 20 00:01:23,680 --> 00:01:26,279 Speaker 1: very strong year, and we've done a good job planning 21 00:01:26,280 --> 00:01:30,760 Speaker 1: for Vera Rubin, so sales are off the charts and 22 00:01:30,880 --> 00:01:34,080 Speaker 1: video GPUs and the cloud is sold out, but we've 23 00:01:34,080 --> 00:01:35,600 Speaker 1: got a bunch of Blackwells to sell. 24 00:01:36,800 --> 00:01:39,480 Speaker 2: Jensen, what's the road ahead for Vera Rubin. It's one 25 00:01:39,520 --> 00:01:41,560 Speaker 2: of the most common questions we get for you of 26 00:01:41,640 --> 00:01:44,720 Speaker 2: how that ramp will go relative to what we saw 27 00:01:44,800 --> 00:01:46,880 Speaker 2: with the Blackwell generations. 28 00:01:49,600 --> 00:01:54,640 Speaker 1: Well, the silicon for Vera Rubin, seven different chips are 29 00:01:54,680 --> 00:01:57,320 Speaker 1: back in our labs and the bring up is happening 30 00:01:57,360 --> 00:02:01,480 Speaker 1: across engineering teams. Probably a couple of twenty thousand people 31 00:02:01,480 --> 00:02:05,760 Speaker 1: are working on bringing up Vera Rubin. From silicon to systems, 32 00:02:05,800 --> 00:02:09,880 Speaker 1: to software to algorithms. People are working around the clock 33 00:02:10,400 --> 00:02:14,360 Speaker 1: and this bring up is going beautifully. We're on track 34 00:02:14,480 --> 00:02:18,720 Speaker 1: to deliver Vera Rubin about Q three timeframe of next year, 35 00:02:19,960 --> 00:02:24,560 Speaker 1: continuing our once a year cycle. Vera Ruben is already 36 00:02:25,520 --> 00:02:30,280 Speaker 1: assured a huge success. Everybody's incredibly excited about it. Can't 37 00:02:30,280 --> 00:02:34,280 Speaker 1: wait to show everybody. And then one last thing is 38 00:02:34,320 --> 00:02:39,280 Speaker 1: that the Rack architecture, the Rack scale architecture, is completely revolutionary. 39 00:02:39,919 --> 00:02:43,600 Speaker 1: It includes a scale up switch called the mvy link 40 00:02:44,280 --> 00:02:47,480 Speaker 1: mvy Link seventy two. Our fifth generation is the only 41 00:02:47,560 --> 00:02:50,919 Speaker 1: one of its kind in the world. This rack architecture, 42 00:02:51,360 --> 00:02:55,480 Speaker 1: which is incredibly complex, started with Grace Blackwell, then Grace 43 00:02:55,480 --> 00:03:00,280 Speaker 1: Blackwell Ultra. It is transitioned to Grace Blackwell Ultra is 44 00:03:00,320 --> 00:03:06,400 Speaker 1: incredibly seamless. The same rascale architecture is going to be 45 00:03:06,520 --> 00:03:09,600 Speaker 1: used for Vera Rubin, and so the supply chains are 46 00:03:09,680 --> 00:03:13,760 Speaker 1: used to it this complexity that we enjoyed with Grace 47 00:03:13,840 --> 00:03:18,040 Speaker 1: Blackwell transition. We're now incredibly smooth running and so I 48 00:03:18,040 --> 00:03:20,600 Speaker 1: think Vera Rubin is going to be just really smooth 49 00:03:20,600 --> 00:03:21,960 Speaker 1: and we're gonna rt it really hard. 50 00:03:22,919 --> 00:03:26,120 Speaker 2: Jensen. I tried to go through what the CFO Collect 51 00:03:26,080 --> 00:03:29,720 Speaker 2: Crest said about China in the quarter gone It seemed 52 00:03:29,720 --> 00:03:33,120 Speaker 2: like there was not meaning for h twenty sales because 53 00:03:33,160 --> 00:03:35,880 Speaker 2: the demand wasn't there even if you were permitted to 54 00:03:35,920 --> 00:03:38,520 Speaker 2: sell each twenty. And then in the current period and 55 00:03:38,560 --> 00:03:41,720 Speaker 2: going forward in video seems committed to working with both 56 00:03:41,760 --> 00:03:47,120 Speaker 2: the United States and China to sell what Collect called 57 00:03:47,320 --> 00:03:50,960 Speaker 2: more competitive compute. Where do we stand with that and 58 00:03:51,320 --> 00:03:54,600 Speaker 2: could you just clarify what Collect was talking about in 59 00:03:54,640 --> 00:03:56,160 Speaker 2: the current state of play for China. 60 00:03:59,520 --> 00:04:03,200 Speaker 1: The most important thing she said is that we've said 61 00:04:03,280 --> 00:04:07,240 Speaker 1: for some time now our forecast for China is zero. 62 00:04:08,280 --> 00:04:12,360 Speaker 1: All of our forecast guidance that we showed zero, we 63 00:04:12,400 --> 00:04:15,080 Speaker 1: should start. That's the most important thing that she said. 64 00:04:15,360 --> 00:04:18,479 Speaker 1: She also said that effectively, China is a very important 65 00:04:18,480 --> 00:04:21,360 Speaker 1: market to us. It's very important to the United States, 66 00:04:21,600 --> 00:04:25,240 Speaker 1: it's very important to China. We would love the opportunity 67 00:04:25,600 --> 00:04:29,040 Speaker 1: to be able to re engage the Chinese market with 68 00:04:29,160 --> 00:04:32,159 Speaker 1: excellent products that we deliver and to be able to 69 00:04:32,160 --> 00:04:37,320 Speaker 1: compete globally. The Chinese market is very large this year. 70 00:04:37,600 --> 00:04:41,320 Speaker 1: My guess is probably about fifty billion dollars. It's great 71 00:04:41,360 --> 00:04:44,279 Speaker 1: for the American people that we're able to compete in 72 00:04:44,320 --> 00:04:47,240 Speaker 1: the Chinese market. It's great for the China market that 73 00:04:47,320 --> 00:04:51,080 Speaker 1: we're able to provide Nvidia's technology to them. It's great 74 00:04:51,080 --> 00:04:54,920 Speaker 1: for the rest of the world as Chinese software companies 75 00:04:54,960 --> 00:04:58,840 Speaker 1: and Chinese open source models leave China and are used 76 00:04:58,880 --> 00:05:01,720 Speaker 1: all over the world. And so I think it's fantastic 77 00:05:01,760 --> 00:05:04,200 Speaker 1: that we're able. It would be fantastic if we're able 78 00:05:04,240 --> 00:05:07,159 Speaker 1: to participate in the China market, but for now, we 79 00:05:07,160 --> 00:05:13,040 Speaker 1: should just assume our nvidious forecast for China market is zero. 80 00:05:13,360 --> 00:05:16,320 Speaker 1: We're going to continue to engage the US government, continue 81 00:05:16,360 --> 00:05:19,880 Speaker 1: to engage the China government to advise them and to 82 00:05:20,160 --> 00:05:22,080 Speaker 1: encourage them to allow us to go back and compete 83 00:05:22,120 --> 00:05:24,840 Speaker 1: in the open market. And so until then we should 84 00:05:24,839 --> 00:05:27,080 Speaker 1: assume zero Jensen. 85 00:05:27,160 --> 00:05:30,760 Speaker 2: During the call, the US Commerce Department issued a statement 86 00:05:30,920 --> 00:05:34,479 Speaker 2: saying that you are now permitted to export up to 87 00:05:34,560 --> 00:05:38,800 Speaker 2: thirty five thousand Blackwell chips each to both Saudiast humane 88 00:05:39,160 --> 00:05:41,920 Speaker 2: and to the UAE through G forty two. But there 89 00:05:41,960 --> 00:05:45,200 Speaker 2: are some requirements that the US has a view, in 90 00:05:45,240 --> 00:05:51,120 Speaker 2: particular around controls of preventing tech transfer to China through 91 00:05:51,120 --> 00:05:53,000 Speaker 2: the Middle East. What can you tell us about your 92 00:05:53,080 --> 00:05:55,480 Speaker 2: understanding of what the US government's asking of you. 93 00:05:55,520 --> 00:06:05,600 Speaker 1: There That that UH that that that element UH is 94 00:06:05,720 --> 00:06:08,880 Speaker 1: has been around for a long time is to prevent diversion. 95 00:06:09,640 --> 00:06:13,480 Speaker 1: Of course, over the years, people have speculated about diversion. 96 00:06:14,200 --> 00:06:19,720 Speaker 1: We've chased down every single concern and UH we've repeatedly 97 00:06:20,400 --> 00:06:24,320 Speaker 1: UH tested and sampled data centers around the world and 98 00:06:24,680 --> 00:06:28,520 Speaker 1: found no diversion. And so this is a this is 99 00:06:28,560 --> 00:06:31,320 Speaker 1: an area that that will continue to be rigorous on 100 00:06:31,920 --> 00:06:36,080 Speaker 1: and UH there's a lot of different ways to uh, comply. 101 00:06:36,560 --> 00:06:39,000 Speaker 1: And one of them, of course, is to have it 102 00:06:39,080 --> 00:06:43,000 Speaker 1: be run by American Cloud. Another way is just to 103 00:06:43,000 --> 00:06:46,040 Speaker 1: make sure that we have measures put in place, whether 104 00:06:46,120 --> 00:06:49,560 Speaker 1: technology or processes, to ensure that no diversion happens. 105 00:06:50,920 --> 00:06:53,320 Speaker 2: Jensen, the number one question I get for you is 106 00:06:53,400 --> 00:06:58,680 Speaker 2: always about energy. How severe is the energy shortage in 107 00:06:58,720 --> 00:07:01,520 Speaker 2: the context of AI expects and would you talk a 108 00:07:01,520 --> 00:07:05,600 Speaker 2: bit about power and whether power is a bigger constraint 109 00:07:06,120 --> 00:07:08,440 Speaker 2: for this buildout than the chips themselves. 110 00:07:12,240 --> 00:07:16,720 Speaker 1: When you're growing at the rate and scale of Nvidia, 111 00:07:17,600 --> 00:07:21,120 Speaker 1: Remember we're growing some sixty percent a year. Just quarter 112 00:07:21,200 --> 00:07:25,040 Speaker 1: to quarter growth of our company is ten billion dollars. 113 00:07:25,600 --> 00:07:28,280 Speaker 1: We grew an entire size of a company just in 114 00:07:28,320 --> 00:07:32,600 Speaker 1: one quarter. And so the scale and the rate at 115 00:07:32,640 --> 00:07:35,720 Speaker 1: which we're growing, everything's a challenge, which is the reason 116 00:07:35,720 --> 00:07:39,160 Speaker 1: why Nvidia has to be world class at our supply chain, 117 00:07:39,560 --> 00:07:43,720 Speaker 1: working with incredible providers and suppliers like TSMC and the 118 00:07:43,760 --> 00:07:47,040 Speaker 1: memory partners and all of our systems partners, but also 119 00:07:47,120 --> 00:07:53,360 Speaker 1: working downstream to work with energy providers, power generator companies, 120 00:07:54,200 --> 00:07:57,760 Speaker 1: all of the land power and shell providers, so that 121 00:07:57,800 --> 00:08:01,480 Speaker 1: we could make sure that as we launch into the marketplace, 122 00:08:01,520 --> 00:08:04,560 Speaker 1: as we deploy into the marketplace, land Power and Shell 123 00:08:04,800 --> 00:08:08,360 Speaker 1: will be ready for us. One of our great advantages 124 00:08:08,800 --> 00:08:11,840 Speaker 1: is that we have such a large network of go 125 00:08:11,880 --> 00:08:15,640 Speaker 1: to market. We're in every single cloud. Every single cloud 126 00:08:15,680 --> 00:08:18,200 Speaker 1: service provider is a customer of ours. We're in every 127 00:08:18,400 --> 00:08:22,440 Speaker 1: single GPU cloud, and so we have a large network 128 00:08:22,440 --> 00:08:25,040 Speaker 1: and not to mention OEMs, not to mention, all around 129 00:08:25,040 --> 00:08:29,280 Speaker 1: the world. Our customer base, our network of partners is 130 00:08:29,320 --> 00:08:32,520 Speaker 1: so large that we will find nooks and crannies of 131 00:08:32,559 --> 00:08:36,840 Speaker 1: power and large scale, medium scale, small scale in different 132 00:08:36,840 --> 00:08:39,400 Speaker 1: parts of the world. And so this is a huge 133 00:08:39,440 --> 00:08:42,160 Speaker 1: advantage of ours, and it stems from the fact ed 134 00:08:42,600 --> 00:08:48,600 Speaker 1: that Nvidia's architecture literally runs every model and today, yesterday 135 00:08:48,600 --> 00:08:51,800 Speaker 1: we announced a big news with Anthropic and so now 136 00:08:52,400 --> 00:09:01,720 Speaker 1: the premiere frontier models, open AI, Anthropic, XAI, Gemini, all 137 00:09:01,720 --> 00:09:07,280 Speaker 1: the open sources, biological models, physical AI models, everything in 138 00:09:07,320 --> 00:09:10,240 Speaker 1: the world runs on Nvidia. And as a result of that, 139 00:09:11,080 --> 00:09:16,680 Speaker 1: irrespective of which cloud provider you are, it is fantastic 140 00:09:16,720 --> 00:09:18,800 Speaker 1: that we can deploy in your cloud because the off 141 00:09:18,880 --> 00:09:19,880 Speaker 1: take will be incredible. 142 00:09:20,760 --> 00:09:23,640 Speaker 2: Jensen. We can see where the hyperscalers are getting the money, 143 00:09:23,679 --> 00:09:26,400 Speaker 2: where they have the money to deploy and build. But 144 00:09:26,640 --> 00:09:30,040 Speaker 2: you mentioned anthropic. With Anthropic or indeed open ai, they 145 00:09:30,040 --> 00:09:35,040 Speaker 2: have tens of billions of dollars of commitments around the world. 146 00:09:35,600 --> 00:09:37,640 Speaker 2: Very simple like, how do you know the open ai 147 00:09:37,760 --> 00:09:39,440 Speaker 2: is good for it that it will be able to 148 00:09:39,480 --> 00:09:42,920 Speaker 2: find the money. 149 00:09:43,840 --> 00:09:50,079 Speaker 1: Well, we're thoughtful along with open ai, thoughtful in aligning 150 00:09:50,160 --> 00:09:56,320 Speaker 1: on and taking into consideration visibility of demand and their 151 00:09:56,360 --> 00:10:00,000 Speaker 1: financing capabilities. All of that has to be in accordance, 152 00:10:00,559 --> 00:10:03,840 Speaker 1: has to be aligned, has to be coherent before we 153 00:10:03,880 --> 00:10:08,920 Speaker 1: start to build out. And so I think the ambitions large, 154 00:10:09,240 --> 00:10:13,199 Speaker 1: but the execution is disciplined, and that's really really important 155 00:10:13,200 --> 00:10:17,040 Speaker 1: to recognize. We're very disciplined with our investment. We're disciplined 156 00:10:17,040 --> 00:10:21,320 Speaker 1: with our buildout. These are very large scale investments, and 157 00:10:21,400 --> 00:10:24,920 Speaker 1: so the two teams are quite disciplined, very disciplined in 158 00:10:25,000 --> 00:10:28,559 Speaker 1: thinking through the investment levels. Now, it's also important to 159 00:10:28,600 --> 00:10:32,199 Speaker 1: take a step back and realize that open Ai, Anthropic, 160 00:10:32,760 --> 00:10:36,920 Speaker 1: these are the fastest growing company in the history of humanity. 161 00:10:37,440 --> 00:10:42,600 Speaker 1: They're off take their end market demand is absolutely real 162 00:10:42,880 --> 00:10:46,439 Speaker 1: and absolutely incredible, and you could see that they're really 163 00:10:46,480 --> 00:10:49,120 Speaker 1: struggling to keep up with the demand that they have. 164 00:10:49,679 --> 00:10:52,320 Speaker 1: The engineering teams. We work incredibly hard to make sure 165 00:10:52,360 --> 00:10:56,120 Speaker 1: that we bring them on more capacity, but also optimizing 166 00:10:56,160 --> 00:10:59,360 Speaker 1: their stack so that the usage of whatever capacity is 167 00:10:59,360 --> 00:11:03,320 Speaker 1: as sufficient as possible. And meanwhile, there's so many new 168 00:11:03,400 --> 00:11:05,679 Speaker 1: use cases that they want to put back put out 169 00:11:05,720 --> 00:11:09,040 Speaker 1: into the world, and it's currently limited by the capacity 170 00:11:09,120 --> 00:11:11,880 Speaker 1: they have, and so this is a really important time. 171 00:11:12,200 --> 00:11:15,439 Speaker 1: You're seeing an exponential growth in the amount of compute 172 00:11:15,520 --> 00:11:20,120 Speaker 1: demand necessary for AI, You're seeing an exponential growth of 173 00:11:20,400 --> 00:11:25,439 Speaker 1: adoption and use of AI, and the number of applications 174 00:11:25,480 --> 00:11:28,000 Speaker 1: that are going to be using these AI is also growing. 175 00:11:28,200 --> 00:11:30,400 Speaker 1: And so we've got to do our best to support 176 00:11:30,440 --> 00:11:33,560 Speaker 1: the scaling out of two of the most consequential companies 177 00:11:33,559 --> 00:11:37,320 Speaker 1: in history, and we're delied to be partnered with them. 178 00:11:37,840 --> 00:11:44,079 Speaker 2: Jensen investors have been worrying about depreciation. Software can actually 179 00:11:44,160 --> 00:11:46,880 Speaker 2: extend life, like there are a one hundreds out there 180 00:11:47,080 --> 00:11:51,720 Speaker 2: in the real world still at full utilization. Are people 181 00:11:51,800 --> 00:11:55,880 Speaker 2: underestimating how long your chips stay useful or are they 182 00:11:55,960 --> 00:12:00,080 Speaker 2: kind of misunderstanding in the context of depreciation, how oh 183 00:12:00,120 --> 00:12:03,400 Speaker 2: you're handling generation to generation updates of GPU. 184 00:12:06,920 --> 00:12:15,440 Speaker 1: Nvidia's architect Nvidia is unlike any other accelerator and The 185 00:12:15,559 --> 00:12:21,160 Speaker 1: reason for that is because of Kuda's diversity of capability 186 00:12:21,400 --> 00:12:25,320 Speaker 1: and versatility. Remember I said two things earlier. I said 187 00:12:25,320 --> 00:12:30,360 Speaker 1: the fact that Nvidia participates and could accelerate every phase 188 00:12:30,400 --> 00:12:34,240 Speaker 1: of AI, pre training, post training, and inference. Were the 189 00:12:34,280 --> 00:12:37,360 Speaker 1: only architecture in the world that does that fantastically. The 190 00:12:37,440 --> 00:12:41,720 Speaker 1: second thing we do, we run every single model, and 191 00:12:41,800 --> 00:12:45,840 Speaker 1: so most agentic systems, most clouds are running so many 192 00:12:45,880 --> 00:12:50,319 Speaker 1: different diverse type of models language models, vision models, biological models, 193 00:12:50,400 --> 00:12:54,000 Speaker 1: chemical models, for all the different fields of science. Nvidia 194 00:12:54,320 --> 00:12:59,640 Speaker 1: could be used across the entire lifespan of the technology. 195 00:13:00,120 --> 00:13:02,720 Speaker 1: And so if you look at products that we shipped, 196 00:13:02,920 --> 00:13:06,720 Speaker 1: Ampier A one hundred we shipped six years ago. But 197 00:13:06,800 --> 00:13:09,640 Speaker 1: because we're continuing, our installed bas is so large, our 198 00:13:09,679 --> 00:13:14,400 Speaker 1: diversity is so great, we could continuously update our software 199 00:13:14,920 --> 00:13:17,480 Speaker 1: bring value to our customers on the one hand, but 200 00:13:17,559 --> 00:13:22,240 Speaker 1: because our versatility is so great based on the capability 201 00:13:22,240 --> 00:13:24,640 Speaker 1: they need, they could use our GPUs for a very 202 00:13:24,760 --> 00:13:27,560 Speaker 1: very long time. Now, remember A one hundred and six 203 00:13:27,640 --> 00:13:31,160 Speaker 1: years old. However, it is still an order of a 204 00:13:31,200 --> 00:13:34,760 Speaker 1: magnitude faster than any CPU could put the bear. So 205 00:13:34,840 --> 00:13:37,240 Speaker 1: it is still the best computer. It is still the 206 00:13:37,280 --> 00:13:40,400 Speaker 1: best processor for much of the workload in the cloud, 207 00:13:41,000 --> 00:13:46,920 Speaker 1: and most people misunderstand that because unlike US, most accelerators 208 00:13:47,520 --> 00:13:51,239 Speaker 1: are kind of singular use, because they don't have diversity, 209 00:13:51,480 --> 00:13:54,320 Speaker 1: because they don't have versatility, because they're not great at 210 00:13:54,360 --> 00:13:58,200 Speaker 1: every phase of AI, once they're used for whatever they 211 00:13:58,240 --> 00:14:01,520 Speaker 1: were designed to do of value fast off a cliff. 212 00:14:01,800 --> 00:14:04,680 Speaker 1: That is not true with n video Jensen. 213 00:14:04,679 --> 00:14:08,040 Speaker 2: My final question is a point of clarification, if I may. 214 00:14:08,080 --> 00:14:11,319 Speaker 2: You were asked on the call about content and in 215 00:14:11,440 --> 00:14:15,040 Speaker 2: video's contribution to any given piece of AI infrastructure, and 216 00:14:15,080 --> 00:14:17,839 Speaker 2: what you said was Hopper around twenty to twenty five 217 00:14:18,320 --> 00:14:23,240 Speaker 2: Blackwell about thirty with those figures billions of dollars in 218 00:14:23,360 --> 00:14:26,760 Speaker 2: dollar terms on a one gig of what data center? 219 00:14:26,840 --> 00:14:29,320 Speaker 2: Or are you talking about percentages of total cost? 220 00:14:32,800 --> 00:14:38,160 Speaker 1: Oh, thank you, billions of dollars billions of dollars. Yeah, 221 00:14:38,200 --> 00:14:42,560 Speaker 1: And so for our ver Rubens system, a one gig 222 00:14:42,560 --> 00:14:45,400 Speaker 1: of what data center is probably something along the lines 223 00:14:45,400 --> 00:14:49,080 Speaker 1: of fifty to fifty five, and video's contribution is probably 224 00:14:49,080 --> 00:14:50,000 Speaker 1: about thirty five of. 225 00:14:50,000 --> 00:14:57,960 Speaker 2: That video CE one billion noted. I was asked to 226 00:14:58,000 --> 00:15:01,680 Speaker 2: ask you, the question has been asked answered astonishingly. Busy 227 00:15:01,800 --> 00:15:03,720 Speaker 2: day for you in the nation's Captain. 228 00:15:03,880 --> 00:15:07,680 Speaker 1: That's a great question. The difference between percentages and billion 229 00:15:07,800 --> 00:15:09,840 Speaker 1: is a big deal. Yeah, it's a brilliance. 230 00:15:10,560 --> 00:15:12,920 Speaker 2: The stakes are high, but we're always grateful for your time. 231 00:15:13,200 --> 00:15:15,000 Speaker 2: I know it's been a busy day. Thank you for 232 00:15:15,080 --> 00:15:18,360 Speaker 2: joining us on Bloomberg Television. That's Nvideo CEO Jens Wang