1 00:00:00,240 --> 00:00:03,757 Yeah, I think this has really been an amazing partnership through every phase. 2 00:00:03,840 --> 00:00:05,917 Uh we had kind of no idea where it was 3 00:00:06,000 --> 00:00:11,117 all going to go when we started as Satia said. Uh but I I don't think I think 4 00:00:11,200 --> 00:00:15,037 this is one of the great tech partnerships uh ever and without 5 00:00:15,120 --> 00:00:16,317 certainly without Microsoft and 6 00:00:16,400 --> 00:00:22,520 particularly SA's early conviction uh we would not have been able to do this. 7 00:00:23,580 --> 00:00:25,600 [music] 8 00:00:32,160 --> 00:00:33,997 What a week. What a week. Great to see 9 00:00:34,080 --> 00:00:37,437 you both. Um Sam, how's the baby? 10 00:00:37,520 --> 00:00:41,677 >> Baby is great. That's the best thing ever, man. Every every cliche is true 11 00:00:41,760 --> 00:00:43,677 and it is the best thing ever. 12 00:00:43,760 --> 00:00:47,277 >> Uh hey Sacha, with all your time >> smile on Sam's face whenever he talks 13 00:00:47,360 --> 00:00:49,757 about uh it's just his his baby is just 14 00:00:49,840 --> 00:00:53,117 so different. It's dad that and compute 15 00:00:53,200 --> 00:00:57,597 I guess when he talks about compute and his baby. [laughter] 16 00:00:57,680 --> 00:01:01,277 >> U well Sachi have you given him any dad tips with all this time you guys have 17 00:01:01,360 --> 00:01:03,917 spent together? >> I said just enjoy it. I mean it's so 18 00:01:04,000 --> 00:01:06,317 awesome that uh you know I you know we 19 00:01:06,400 --> 00:01:08,637 had our babies or what our children so 20 00:01:08,720 --> 00:01:13,357 young and I wish I could redo it. So in some sense it's just the most precious 21 00:01:13,440 --> 00:01:18,477 time and as they grow it's just so wonderful. I'm so glad Sam is um 22 00:01:18,560 --> 00:01:21,757 >> I'm happy to be doing it older, but I do think sometimes, man, I wish I had the 23 00:01:21,840 --> 00:01:25,357 energy when I was like 25. Uh that part's harder. 24 00:01:25,440 --> 00:01:28,877 >> No doubt about it. What's the average age at Open AI, Sam? Any idea? It's 25 00:01:28,960 --> 00:01:32,477 young. >> It's not crazy young. Not Not like Not 26 00:01:32,560 --> 00:01:35,757 like most Silicon Valley startups. I don't know, maybe low 30s average. 27 00:01:35,840 --> 00:01:39,197 >> Are babies t is it are babies trending positively or negatively? 28 00:01:39,280 --> 00:01:40,397 >> Babies trending positively. 29 00:01:40,480 --> 00:01:41,997 >> Oh, that's good. That's good. Yeah. 30 00:01:42,080 --> 00:01:45,997 >> Well, you guys, such a big week. You know, I was thinking about I started at 31 00:01:46,080 --> 00:01:48,877 Nvidia's GTC, you know, just hit $5 32 00:01:48,960 --> 00:01:53,517 trillion. Google, Meta, Microsoft, Satcha, you had your earnings yesterday, 33 00:01:53,600 --> 00:01:57,197 you know, and we heard consistently not enough compute, not enough compute, not 34 00:01:57,280 --> 00:02:02,157 enough compute. We got rate cuts on Wednesday. The GDP's tracking near 4%. 35 00:02:02,240 --> 00:02:05,597 And then I was just saying to Sam, you know, the president's cut these massive 36 00:02:05,680 --> 00:02:08,317 deals in Malaysia, South Korea, Japan, 37 00:02:08,400 --> 00:02:12,797 sounds like with China. you know, deals that really incredibly provide the 38 00:02:12,880 --> 00:02:17,197 financial firepower to re-industrialize America. 80 billion for new nuclear 39 00:02:17,280 --> 00:02:21,117 fision, all the things that you guys need to build more compute, but 40 00:02:21,200 --> 00:02:24,877 certainly wasn't what wasn't lost in all of this was you guys had a big 41 00:02:24,960 --> 00:02:29,357 announcement on Tuesday that clarified your partnership. Congrats on that. And 42 00:02:29,440 --> 00:02:32,397 I thought we'd just start there. I really want to just break down the deal 43 00:02:32,480 --> 00:02:34,797 in really simple plain language to make 44 00:02:34,880 --> 00:02:37,517 sure I understand it and and and others 45 00:02:37,600 --> 00:02:39,517 but you know we'll just start with your 46 00:02:39,600 --> 00:02:42,317 investment Satcha you know Microsoft 47 00:02:42,400 --> 00:02:45,277 started investing in 2019 has invested 48 00:02:45,360 --> 00:02:48,077 in the ballpark at 134 billion into open 49 00:02:48,160 --> 00:02:51,997 AI and for that you get 27% of the 50 00:02:52,080 --> 00:02:55,757 business ownership in the business on a fully diluted basis I think it was about 51 00:02:55,840 --> 00:02:59,517 a third and you took some dilution over the course of last year with all the 52 00:02:59,600 --> 00:03:04,317 investment So, does that sound about right in terms of ownership? 53 00:03:04,400 --> 00:03:06,477 >> Yeah, it does. But I I would say before 54 00:03:06,560 --> 00:03:08,877 even our stake in it, Brad, I think 55 00:03:08,960 --> 00:03:12,237 what's pretty unique about OpenAI is the 56 00:03:12,320 --> 00:03:15,917 fact that as part of OpenAI's process of 57 00:03:16,000 --> 00:03:20,317 restructuring, one of the largest nonprofit gets created. I mean, let's 58 00:03:20,400 --> 00:03:24,397 not forget that, you know, in some sense I say at Microsoft, like I, you know, we 59 00:03:24,480 --> 00:03:27,277 are very proud of the fact that we were, we're associated with the two of the 60 00:03:27,360 --> 00:03:31,437 largest nonprofits, the Gates Foundation and now the OpenAI Foundation. So, 61 00:03:31,520 --> 00:03:35,997 that's I think the big news. Uh, we obviously were, you know, are thrilled. 62 00:03:36,080 --> 00:03:39,757 It's not what we thought. And as I said to somebody, it's not like when we first 63 00:03:39,840 --> 00:03:43,277 invested our billion dollars that, oh, this is going to be the 100 bagger that 64 00:03:43,360 --> 00:03:47,357 I'm going to be talking about to VCs about, but here we are. But we are very 65 00:03:47,440 --> 00:03:50,237 thrilled to be an investor and an early 66 00:03:50,320 --> 00:03:54,717 backer. Um and and it's a great and it's a really a testament to what Sam and 67 00:03:54,800 --> 00:03:58,477 team have done quite frankly. I mean they obviously had the vision early 68 00:03:58,560 --> 00:04:03,517 about what this technology could do and they ran with it and just executed you 69 00:04:03,600 --> 00:04:06,877 know in a masterful way. >> Yeah. I think this has really been an 70 00:04:06,960 --> 00:04:08,877 amazing partnership through every phase. 71 00:04:08,960 --> 00:04:11,037 Uh we had kind of no idea where it was 72 00:04:11,120 --> 00:04:16,237 all going to go when we started as Satia said. Uh but I I don't think I think 73 00:04:16,320 --> 00:04:20,157 this is one of the great tech partnerships uh ever and without 74 00:04:20,240 --> 00:04:23,357 certainly without Microsoft and particularly Sant's early conviction uh 75 00:04:23,440 --> 00:04:24,717 we would not have been able to do this. 76 00:04:24,800 --> 00:04:28,077 I don't think there were a lot of other people that would have uh been willing 77 00:04:28,160 --> 00:04:32,317 to take that kind of a bet given what the world looked like at the time. Um we 78 00:04:32,400 --> 00:04:36,157 didn't know exactly how the tech was going to go. Well, not exactly. We 79 00:04:36,240 --> 00:04:38,237 didn't know at all how the tech was going to go. We just had a lot of 80 00:04:38,320 --> 00:04:42,077 conviction in this this one idea of pushing on on deep learning and trusting 81 00:04:42,160 --> 00:04:45,597 that if we could do that, we'd figure out ways to make wonderful products and 82 00:04:45,680 --> 00:04:49,117 create a lot of value and also, as Satia said, create what we believe will be the 83 00:04:49,200 --> 00:04:52,397 largest nonprofit ever. And I think it's 84 00:04:52,480 --> 00:04:56,397 going to do amazingly great things. It it was I I really like the structure 85 00:04:56,480 --> 00:04:58,477 because it lets the nonprofit grow in 86 00:04:58,560 --> 00:05:04,077 value while the PBC is able to get the capital that it needs to keep scaling. I 87 00:05:04,160 --> 00:05:07,037 don't think the nonprofit would be able to be this valuable if we didn't come up 88 00:05:07,120 --> 00:05:09,757 with the structure and if we didn't have partners around the table that were 89 00:05:09,840 --> 00:05:13,917 excited for it to work this way. But, you know, I think it's been six more 90 00:05:14,000 --> 00:05:18,797 than six years since we first started this partnership and uh a pretty crazy 91 00:05:18,880 --> 00:05:22,077 amount of achievement for six years and I think much much more to come. I hope 92 00:05:22,160 --> 00:05:24,877 that Sasha makes a trillion dollars on the investment, not hundred billion, you 93 00:05:24,960 --> 00:05:27,837 know, whatever it is. >> Well, as part of the restructuring, you 94 00:05:27,920 --> 00:05:31,357 guys talked about it. You have this nonprofit on top and a public benefit 95 00:05:31,440 --> 00:05:33,517 corp below. It's pretty insane. The 96 00:05:33,600 --> 00:05:36,477 nonprofit is already capitalized with 97 00:05:36,560 --> 00:05:41,197 $130 billion. $130 billion of Open AI 98 00:05:41,280 --> 00:05:44,557 stock. It's one of the largest in the world out of the gates. It could end up 99 00:05:44,640 --> 00:05:48,157 being much much larger. The California Attorney General said they're not going 100 00:05:48,240 --> 00:05:50,317 to object to it. You already haveund 101 00:05:50,400 --> 00:05:55,197 this 130 billion dedicated to making sure that AGI benefits all of humanity. 102 00:05:55,280 --> 00:05:56,477 You announced that you're going to 103 00:05:56,560 --> 00:05:58,957 direct the first 25 billion to health 104 00:05:59,040 --> 00:06:04,157 and AI security and resilience. Sam, first let me just say, you know, as 105 00:06:04,240 --> 00:06:07,437 somebody who participates in the ecosystem, kudos to you both. It's 106 00:06:07,520 --> 00:06:09,357 incredible this contribution to the 107 00:06:09,440 --> 00:06:11,837 future of AI. But Sam, talk to us a bit 108 00:06:11,920 --> 00:06:14,717 about the importance of the the choice 109 00:06:14,800 --> 00:06:17,277 around health and and resilience. And 110 00:06:17,360 --> 00:06:21,837 then help us understand how do we make sure that you get maximal benefit 111 00:06:21,920 --> 00:06:24,077 without it getting weighted down as 112 00:06:24,160 --> 00:06:26,237 we've seen with so many nonprofits with 113 00:06:26,320 --> 00:06:29,037 its own political biases. 114 00:06:29,120 --> 00:06:34,077 >> Yeah. First of all, the the best way to create a bunch of value for the world is 115 00:06:34,160 --> 00:06:37,117 hopefully what we're we've already been doing, which is to make these amazing 116 00:06:37,200 --> 00:06:40,957 tools and just let people use them. And I think capitalism is great. I think 117 00:06:41,040 --> 00:06:45,037 companies are great. I think people are doing amazing work getting advanced AI 118 00:06:45,120 --> 00:06:46,557 into the hands of a lot of people and 119 00:06:46,640 --> 00:06:47,597 companies. They're doing incredible 120 00:06:47,680 --> 00:06:52,077 things. There are some areas where the I 121 00:06:52,160 --> 00:06:56,877 think market forces don't quite work for what's in the best interest of people 122 00:06:56,960 --> 00:07:00,877 and you do need to do things in a different way. Uh there are also some 123 00:07:00,960 --> 00:07:04,157 new things with this technology that just haven't existed before like the 124 00:07:04,240 --> 00:07:08,717 potential to use AI to do science at a rapid clip like really truly automated 125 00:07:08,800 --> 00:07:13,277 discovery. And when we thought about the areas we wanted to first focus on, 126 00:07:13,360 --> 00:07:17,277 clearly if we can cure a lot of disease and make the data and information for 127 00:07:17,360 --> 00:07:20,797 that broadly available, that would that'd be a wonderful thing to do for 128 00:07:20,880 --> 00:07:25,117 the world. And then on this point of AI resilience, I do think some things may 129 00:07:25,200 --> 00:07:29,837 get a little strange and they won't all be addressed by companies doing their 130 00:07:29,920 --> 00:07:34,317 thing. So as the world has to navigate through this transition, if we can fund 131 00:07:34,400 --> 00:07:37,837 some work to help with that, and that could be, you know, cyber defense, that 132 00:07:37,920 --> 00:07:40,797 could be AI safety research, that could be economic studies, all of these 133 00:07:40,880 --> 00:07:45,437 things, helping society get through this transition smoothly. We're very 134 00:07:45,520 --> 00:07:48,637 confident about how great it can be on the other side, but you know, I'm sure 135 00:07:48,720 --> 00:07:50,557 there will be some choppiness along the way. 136 00:07:50,640 --> 00:07:52,797 >> Let's keep busting through the the the 137 00:07:52,880 --> 00:07:55,677 um the deal. So models and exclusivity 138 00:07:55,760 --> 00:08:00,797 Sam OpenAI can distribute its models uh its leading models on Azure but I don't 139 00:08:00,880 --> 00:08:04,557 think you can distribute them on any other leading the big clouds for seven 140 00:08:04,640 --> 00:08:07,277 years until 2032 but that would end 141 00:08:07,360 --> 00:08:09,917 earlier if AGI is verified. We can come 142 00:08:10,000 --> 00:08:14,717 back to that but you can distribute your open source models Sora agents codecs 143 00:08:14,800 --> 00:08:16,477 wearables everything else on other 144 00:08:16,560 --> 00:08:19,517 platforms. So Sam, I assume this means 145 00:08:19,600 --> 00:08:23,837 no chat GPT or GPT6 on Amazon or Google. 146 00:08:23,920 --> 00:08:27,437 >> No. So, so we have a C. First of all, we want to do lots of things together to 147 00:08:27,520 --> 00:08:30,397 help, you know, create value for Microsoft. We want them to do lots of 148 00:08:30,480 --> 00:08:33,437 things for to create value for us. And there are many many things that'll 149 00:08:33,520 --> 00:08:37,037 happen in that category. Um, we are keeping what Satia termed once and I 150 00:08:37,120 --> 00:08:41,357 think it's a great phrase of stateless APIs on Azure exclusively through 2030. 151 00:08:41,440 --> 00:08:44,317 And everything else we're going to, you know, distribute elsewhere and that's 152 00:08:44,400 --> 00:08:46,317 obviously in Microsoft's interest, too. 153 00:08:46,400 --> 00:08:49,117 So, we'll put lots of products, lots of places, and then this thing we'll we'll 154 00:08:49,200 --> 00:08:52,957 do on Azure and people can get it there or or via us. And I think that's great. 155 00:08:53,040 --> 00:08:56,397 >> And then the rev share, there's still a rev share that gets paid by OpenAI to 156 00:08:56,480 --> 00:08:58,797 Microsoft on all your revenues that also 157 00:08:58,880 --> 00:09:03,917 runs until 2032 or until AGI is verified. So, let's just assume for the 158 00:09:04,000 --> 00:09:07,277 sake of argument, I know this is pedestrian, but it's important that the 159 00:09:07,360 --> 00:09:11,437 rev share is 15%. So that would mean if you had 20 billion in revenue that 160 00:09:11,520 --> 00:09:15,997 you're paying three billion to Microsoft and that counts as revenue to Azure. 161 00:09:16,080 --> 00:09:18,237 Satcha, is that does that sound about right? 162 00:09:18,320 --> 00:09:20,077 >> Yeah, we have a rev share and I think as 163 00:09:20,160 --> 00:09:22,317 you characterized it is either going to 164 00:09:22,400 --> 00:09:27,117 AGI or till the end of the term. Uh and I actually don't know exactly where we 165 00:09:27,200 --> 00:09:30,237 count it quite honestly whether it goes into Azure or somewhere else. That's a 166 00:09:30,320 --> 00:09:31,677 good question. It's a good question for 167 00:09:31,760 --> 00:09:34,557 Amy. Given that both exclusivity and the 168 00:09:34,640 --> 00:09:37,677 revshare end early in the case AGI is 169 00:09:37,760 --> 00:09:39,917 verified, it seems to make AGI a pretty 170 00:09:40,000 --> 00:09:44,877 big deal. And as I understand it, you know, if if OpenAI claimed AGI, it 171 00:09:44,960 --> 00:09:46,797 sounds like it goes to an expert panel. 172 00:09:46,880 --> 00:09:50,557 And you guys basically select a jury who's got to make a relatively quick 173 00:09:50,640 --> 00:09:54,077 decision whether or not AGI has been reached. Satcha, you said on yesterday's 174 00:09:54,160 --> 00:09:58,077 earning call that nobody's even close to getting to AGI and you don't expect it 175 00:09:58,160 --> 00:10:02,557 to happen anytime soon. You talked about this spiky and jagged intelligence. Sam, 176 00:10:02,640 --> 00:10:06,637 I've heard you perhaps sound a little bit more bullish on, you know, when we 177 00:10:06,720 --> 00:10:10,797 might get to AGI. So, I guess the question is to you both. Do you worry 178 00:10:10,880 --> 00:10:14,397 that over the next two or three years we're going to end up having to call in 179 00:10:14,480 --> 00:10:18,877 the jury to effectively make a uh a call on whether or not we've hit AGI? 180 00:10:18,960 --> 00:10:20,477 >> I I realize you got to try to make some 181 00:10:20,560 --> 00:10:24,557 drama between us here. I [laughter] 182 00:10:24,640 --> 00:10:26,797 >> you know, I think putting a process in 183 00:10:26,880 --> 00:10:30,077 place for this is a good thing to do. I 184 00:10:30,160 --> 00:10:34,877 expect that the technology will take several surprising twists and turns and 185 00:10:34,960 --> 00:10:37,677 we will continue to be good partners to each other and figure out what makes 186 00:10:37,760 --> 00:10:42,397 sense. >> That's well said. I think uh and that's one of the reasons why I think this 187 00:10:42,480 --> 00:10:46,317 process we put in place is a good one and at the end of the day I'm a big 188 00:10:46,400 --> 00:10:49,357 believer in the fact that intelligence 189 00:10:49,440 --> 00:10:53,517 uh capability wise is going to continue to improve and our real goal quite 190 00:10:53,600 --> 00:10:56,877 frankly is that which is how do you put that in the hands of people and 191 00:10:56,960 --> 00:11:00,717 organizations so that they can get the maximum benefits and that was the 192 00:11:00,800 --> 00:11:05,037 original mission of open AI that attracted me to open AAI and Sam and 193 00:11:05,120 --> 00:11:08,237 team and that's kind of what we plan to continue on 194 00:11:08,320 --> 00:11:11,597 >> Brad to say the obvious if we had super intelligence tomorrow, we would still 195 00:11:11,680 --> 00:11:15,357 want Microsoft's help getting this product out into people's hands and we 196 00:11:15,440 --> 00:11:19,917 want them like Yeah, >> of course. Of course. Yeah. No, it again 197 00:11:20,000 --> 00:11:21,917 I'm asking the questions I know that are 198 00:11:22,000 --> 00:11:26,957 on people's minds and that makes a ton of sense to me. Obviously s Microsoft is 199 00:11:27,040 --> 00:11:29,517 one of the largest distribution platforms in the world. You guys have 200 00:11:29,600 --> 00:11:32,557 been great partners for a long time. But I think it dispels some of the myths 201 00:11:32,640 --> 00:11:35,597 that are out there. But let's shift gears a little bit. You know, obviously 202 00:11:35,680 --> 00:11:37,277 OpenAI is one of the fastest growing 203 00:11:37,360 --> 00:11:39,517 companies in history. Satcha, you said 204 00:11:39,600 --> 00:11:42,637 on the pod a year ago, this pod, that 205 00:11:42,720 --> 00:11:47,037 every new phase shift creates a new Google and the Google of this phase 206 00:11:47,120 --> 00:11:49,517 shift is already known and it's open AI. 207 00:11:49,600 --> 00:11:52,397 And none of this would have been possible had you guys not made these 208 00:11:52,480 --> 00:11:55,597 these huge bets. With all that said, you 209 00:11:55,680 --> 00:11:57,597 know, OpenAI's revenues are still a 210 00:11:57,680 --> 00:12:01,197 reported 13 billion in 2025. And Sam, on 211 00:12:01,280 --> 00:12:03,277 your live stream this week, you talked 212 00:12:03,360 --> 00:12:05,197 about this massive commitment to 213 00:12:05,280 --> 00:12:08,477 compute, right? 1.4 4 trillion over the 214 00:12:08,560 --> 00:12:11,357 next four or five years with you know 215 00:12:11,440 --> 00:12:13,757 big commitments 500 million to Nvidia 216 00:12:13,840 --> 00:12:16,477 300 million to AMD and Oracle 250 217 00:12:16,560 --> 00:12:19,517 billion to Azure. So I think the single 218 00:12:19,600 --> 00:12:21,597 biggest question I've heard all week and 219 00:12:21,680 --> 00:12:24,637 and hanging over the market is how you 220 00:12:24,720 --> 00:12:26,637 know how can a company with 13 billion 221 00:12:26,720 --> 00:12:30,637 in revenues make 1.4 4 trillion of spend 222 00:12:30,720 --> 00:12:34,237 commitments, you know, and and and you've heard the criticism, Sam. 223 00:12:34,320 --> 00:12:37,677 >> First of all, we're doing well more revenue than that. Second of all, Brad, 224 00:12:37,760 --> 00:12:38,797 if you want to sell your shares, I'll 225 00:12:38,880 --> 00:12:41,357 find you a buyer. [laughter] 226 00:12:41,440 --> 00:12:46,317 >> I just enough like, you know, people are I I think there's a lot of people who 227 00:12:46,400 --> 00:12:48,957 would love to buy OpenAI shares. I don't I don't think you 228 00:12:49,040 --> 00:12:53,917 >> including myself, including myself, >> people who talk with a lot of like 229 00:12:54,000 --> 00:12:57,117 breathless concern about our comput stuff or whatever that would be thrilled 230 00:12:57,200 --> 00:13:00,557 to buy shares. So I think we we could sell you know your shares or anybody 231 00:13:00,640 --> 00:13:03,117 else's to some of the people who are making the most noise on Twitter 232 00:13:03,200 --> 00:13:07,277 whatever about this very quickly. We do plan for revenue to grow steeply. 233 00:13:07,360 --> 00:13:10,557 Revenue is growing steeply. We are taking a forward bet that it's going to 234 00:13:10,640 --> 00:13:13,357 continue to grow grow and that not only 235 00:13:13,440 --> 00:13:17,917 will Chhatabt keep growing but we will be able to become one of the important 236 00:13:18,000 --> 00:13:20,157 AI clouds that our consumer device 237 00:13:20,240 --> 00:13:23,117 business will be a significant and 238 00:13:23,200 --> 00:13:25,037 important thing that AI that can 239 00:13:25,120 --> 00:13:27,997 automate science will create huge value. 240 00:13:28,080 --> 00:13:31,197 So, you know, there are not many times 241 00:13:31,280 --> 00:13:35,437 that I want to be a public company, but one of the rare times it's appealing is 242 00:13:35,520 --> 00:13:38,477 when those people are writing these ridiculous OpenAI is about to go out of 243 00:13:38,560 --> 00:13:41,357 business and, you know, whatever. I would love to tell them they could just 244 00:13:41,440 --> 00:13:42,637 short the stock and I would love to see 245 00:13:42,720 --> 00:13:46,637 them get burned on that. Um, but 246 00:13:46,720 --> 00:13:49,437 you know, I we carefully plan, we 247 00:13:49,520 --> 00:13:54,477 understand where the technology, where the capability is going to grow, go and 248 00:13:54,560 --> 00:13:57,677 and how the products we can build around that and the revenue we can generate. we 249 00:13:57,760 --> 00:14:01,277 might screw it up like this is the bet that we're making and we're taking a 250 00:14:01,360 --> 00:14:05,277 risk along with that. A certain risk is if we don't have the compute, we will 251 00:14:05,360 --> 00:14:08,717 not be able to generate the revenue or make the models at these at this kind of 252 00:14:08,800 --> 00:14:10,317 scale. >> Exactly. And 253 00:14:10,400 --> 00:14:13,437 >> let me just say one thing uh Brad as 254 00:14:13,520 --> 00:14:17,197 both a partner and um an investor there 255 00:14:17,280 --> 00:14:20,077 is not been a single business plan that 256 00:14:20,160 --> 00:14:22,397 I've seen from OpenAI that they have put 257 00:14:22,480 --> 00:14:25,997 in and not beaten it. So in some sense 258 00:14:26,080 --> 00:14:30,877 this is the one place where you know in terms of their growth and just even the 259 00:14:30,960 --> 00:14:34,717 business it's been unbelievable execution quite frankly I mean obviously 260 00:14:34,800 --> 00:14:38,637 openai everyone talks about all the success in the usage and what have you 261 00:14:38,720 --> 00:14:41,117 but even um I would say all up uh the 262 00:14:41,200 --> 00:14:42,957 business execution has been just pretty 263 00:14:43,040 --> 00:14:45,757 unbelievable. I heard Greg Brockman say 264 00:14:45,840 --> 00:14:48,477 on C CBC a couple weeks ago, right? If 265 00:14:48,560 --> 00:14:50,717 we could 10x our compute, we might not 266 00:14:50,800 --> 00:14:52,957 have 10x more revenue, but we'd 267 00:14:53,040 --> 00:14:55,517 certainly have a lot more revenue 268 00:14:55,600 --> 00:14:57,997 >> simply because of lack of compute power. 269 00:14:58,080 --> 00:15:00,477 Things like, yeah, it's just it's really 270 00:15:00,560 --> 00:15:05,117 wild when I just look at how much we are held back. And in many ways, we have, 271 00:15:05,200 --> 00:15:08,317 you know, we've scaled our compute probably 10x over the past year, but if 272 00:15:08,400 --> 00:15:11,917 we had 10x more compute, I don't know if we'd have 10x more revenue, but I don't 273 00:15:12,000 --> 00:15:16,717 think it'd be that far. And we heard this from you as well last night Satcha 274 00:15:16,800 --> 00:15:19,917 that you were compute constrained and growth would have been higher even if if 275 00:15:20,000 --> 00:15:21,997 you had more compute. So help us 276 00:15:22,080 --> 00:15:27,517 contextualize Sam maybe like how compute constrained do you feel today and do you 277 00:15:27,600 --> 00:15:30,717 when you look at the buildout over the course of the next two to three years do 278 00:15:30,800 --> 00:15:34,877 you think you'll ever get to the point where you're not compute constrained? 279 00:15:34,960 --> 00:15:39,197 >> We talk about this question of is there ever enough compute a lot. I I think the 280 00:15:39,280 --> 00:15:41,277 answer is 281 00:15:41,360 --> 00:15:46,237 the only the best way to think about this is like a 282 00:15:46,320 --> 00:15:49,837 energy or something. You can talk about demand for energy at a certain price 283 00:15:49,920 --> 00:15:54,877 point, but you can't talk about demand for energy without talking about at 284 00:15:54,960 --> 00:15:58,237 different you know different demand at different 285 00:15:58,320 --> 00:16:03,277 price levels. If the price of compute per like unit of intelligence or 286 00:16:03,360 --> 00:16:06,157 whatever, however you want to think about it, fell by a factor of a 100 287 00:16:06,240 --> 00:16:10,877 tomorrow, you would see usage go up by much more than 100 and there'd be a lot 288 00:16:10,960 --> 00:16:13,437 of things that people would love to do with that compute that just make no 289 00:16:13,520 --> 00:16:17,357 economic sense at the current cost, but there would be new kind of demand. So I 290 00:16:17,440 --> 00:16:21,757 think the the now on the other hand as the models get 291 00:16:21,840 --> 00:16:25,837 even smarter and you can use these models to cure cancer or discover novel 292 00:16:25,920 --> 00:16:29,277 physics or drive a bunch of humanoid robots to construct a space station or 293 00:16:29,360 --> 00:16:32,157 whatever crazy thing you want then maybe 294 00:16:32,240 --> 00:16:36,717 there's huge willingness to pay a much higher rate cost per unit of 295 00:16:36,800 --> 00:16:39,997 intelligence for a much higher level of intelligence that we don't know yet but 296 00:16:40,080 --> 00:16:43,437 I would bet there will be. So I I think 297 00:16:43,520 --> 00:16:47,757 when you talk about capacity it's it's like a you know cost per unit and you 298 00:16:47,840 --> 00:16:49,917 know capability per unit and you have to 299 00:16:50,000 --> 00:16:55,597 kind of without those curves it's sort of a madeup it's not a super well 300 00:16:55,680 --> 00:16:58,397 specified problem. >> Yeah. I mean I think the one thing that 301 00:16:58,480 --> 00:17:01,357 you know Sam you've talked about which I think is the right way is to think about 302 00:17:01,440 --> 00:17:03,517 is that if intelligence is what a log of 303 00:17:03,600 --> 00:17:08,477 compute then you try and really make sure you keep getting efficient and so 304 00:17:08,560 --> 00:17:10,157 that means the tokens per dollar per 305 00:17:10,240 --> 00:17:13,517 watt uh and the economic value that the 306 00:17:13,600 --> 00:17:17,597 society gets out of it is what we should maximize and reduce the costs and so 307 00:17:17,680 --> 00:17:21,357 that's where if you sort of where like the Jevans paradox point is that right 308 00:17:21,440 --> 00:17:23,677 which is you keep reducing it 309 00:17:23,760 --> 00:17:26,557 commoditizing in some sense intelligence 310 00:17:26,640 --> 00:17:31,037 uh so that it becomes the real driver of GDP growth all around. 311 00:17:31,120 --> 00:17:34,717 >> Unfortunately, it's something closer to uh log of intelligence equals log of 312 00:17:34,800 --> 00:17:37,277 compute. But we may figure out better scaling laws and we may figure out how 313 00:17:37,360 --> 00:17:40,717 to beat this. Yeah, >> we heard from both Microsoft and Google 314 00:17:40,800 --> 00:17:43,277 yesterday. Both said their cloud businesses would have been growing 315 00:17:43,360 --> 00:17:47,837 faster if they have more GPUs. You know, I asked Jensen on this pod if there was 316 00:17:47,920 --> 00:17:52,717 any chance over the course of the next 5 years we would have a compute glut. and 317 00:17:52,800 --> 00:17:57,517 he said it's virtually non-existent chance in the next 2 to 3 years and I 318 00:17:57,600 --> 00:18:02,557 assume you guys would both agree with Jensen that while we can't see out 5 6 7 319 00:18:02,640 --> 00:18:06,157 years certainly over the course of the next 2 to three years for the for the 320 00:18:06,240 --> 00:18:09,917 reasons we just discussed that it's almost a non-existent chance that you 321 00:18:10,000 --> 00:18:13,037 have excess compute well I mean I think 322 00:18:13,120 --> 00:18:17,197 the the cycles of demand and supply in 323 00:18:17,280 --> 00:18:19,917 this particular case you can't really 324 00:18:20,000 --> 00:18:24,477 predict right I mean even the the point is What's the secular trend? The secular 325 00:18:24,560 --> 00:18:27,837 trend is what Sam said, which is at the end of the day, because quite frankly, 326 00:18:27,920 --> 00:18:31,757 the the biggest issue we are now having is not a compute glut, but it's a power 327 00:18:31,840 --> 00:18:34,157 and it's sort of the ability to get the 328 00:18:34,240 --> 00:18:37,517 builds done fast enough close to power. 329 00:18:37,600 --> 00:18:41,037 So, if you can't do that, you may actually have a bunch of chips sitting 330 00:18:41,120 --> 00:18:45,037 in inventory that I can't plug in. In fact, that is my problem today, right? 331 00:18:45,120 --> 00:18:47,917 It's not a supply issue of chips. It's 332 00:18:48,000 --> 00:18:49,917 actually uh the fact that I don't have 333 00:18:50,000 --> 00:18:52,957 warm shells to plug into. And so how 334 00:18:53,040 --> 00:18:57,757 some supply chain constraints emerge tough to predict uh because the demand 335 00:18:57,840 --> 00:19:01,597 is just going you know is tough to predict right I mean I wouldn't you it's 336 00:19:01,680 --> 00:19:05,117 not like Sam and I would want to be sitting here saying oh my god we're less 337 00:19:05,200 --> 00:19:09,037 short on compute it's because we just were not that good at being able to 338 00:19:09,120 --> 00:19:13,357 project out what the demand would really look like. So I think that that's and by 339 00:19:13,440 --> 00:19:17,277 the way the worldwide side right one it's one thing to sort of talk about one 340 00:19:17,360 --> 00:19:20,717 segment in one country but it's about you know really getting it out to 341 00:19:20,800 --> 00:19:23,997 everywhere in the world and so there will be constraints and how we work 342 00:19:24,080 --> 00:19:27,117 through them is going to be the most important thing it won't be a linear 343 00:19:27,200 --> 00:19:31,517 path for sure there there will come a glut for sure and whether that's like in 344 00:19:31,600 --> 00:19:35,837 two to three years or five to six I can't tell you but uh like it's going to 345 00:19:35,920 --> 00:19:39,277 happen at some point probably several points along the way like this is 346 00:19:39,360 --> 00:19:41,517 there's something deep about human 347 00:19:41,600 --> 00:19:45,357 psychology here and bubbles and also as 348 00:19:45,440 --> 00:19:49,837 Satia said like there's it's such a complex supply chain weird stuff gets 349 00:19:49,920 --> 00:19:52,077 built the technological landscape shifts 350 00:19:52,160 --> 00:19:57,597 in big ways so you know if a very cheap form of energy comes online 351 00:19:57,680 --> 00:20:00,477 soon at mass scale then a lot of people are going to be extremely burned with 352 00:20:00,560 --> 00:20:03,677 existing contracts they've signed it I 353 00:20:03,760 --> 00:20:08,397 if if we can continue this unbelievable reduction in cost per unit of 354 00:20:08,480 --> 00:20:12,237 intelligence let's say it's been averaging like 40x X for a given level 355 00:20:12,320 --> 00:20:17,117 per year. You know, that's like a very scary exponent 356 00:20:17,200 --> 00:20:20,557 from an infrastructure buildout standpoint. Now, again, we're taking the 357 00:20:20,640 --> 00:20:25,117 bet that there will be a lot more demand as that gets cheaper, but I have some 358 00:20:25,200 --> 00:20:28,397 fear that it's just like, man, we keep going with these breakthroughs and 359 00:20:28,480 --> 00:20:31,757 everybody can run like a personal AGI on their laptop and we just did an insane 360 00:20:31,840 --> 00:20:35,277 thing here. Some people are going to get 361 00:20:35,360 --> 00:20:39,517 really burned like has happened in every other tech infrastructure cycle at some 362 00:20:39,600 --> 00:20:42,637 points along the way. >> I think that's really well said and you 363 00:20:42,720 --> 00:20:44,237 have to hold those two simultaneous 364 00:20:44,320 --> 00:20:47,357 truths. We had that happen in 20201 and 365 00:20:47,440 --> 00:20:51,597 yet the internet became much bigger and produced much greater outcomes for 366 00:20:51,680 --> 00:20:54,477 society than anybody estimated in that period of time. 367 00:20:54,560 --> 00:20:58,077 >> Yeah. But I think that the one thing that Sam said is not talked about enough 368 00:20:58,160 --> 00:21:00,397 which is the current for example the 369 00:21:00,480 --> 00:21:05,197 optimizations that OpenAI has done on the inference stack for a given GPU. I 370 00:21:05,280 --> 00:21:08,957 mean I it's kind of like it's you know we talk about the MOS law improvement on 371 00:21:09,040 --> 00:21:11,197 one end but the software improvements 372 00:21:11,280 --> 00:21:14,797 are much more exponential than that. 373 00:21:14,880 --> 00:21:17,037 Someday we will make a incredible 374 00:21:17,120 --> 00:21:20,237 consumer device that can run a GPT5 or 375 00:21:20,320 --> 00:21:23,757 GPD6 capable model completely locally at 376 00:21:23,840 --> 00:21:27,837 a low power draw. And this is like so hard to wrap my head around. 377 00:21:27,920 --> 00:21:30,957 >> That will be incredible. And you know that's the type of thing I think that 378 00:21:31,040 --> 00:21:34,317 scares some of the people who are building obviously these large 379 00:21:34,400 --> 00:21:38,557 centralized compute uh stacks. And Satcha you've talked a lot about the 380 00:21:38,640 --> 00:21:42,797 distribution both to the edge as well as having inference capability distributed 381 00:21:42,880 --> 00:21:46,477 around the world. Yeah, I mean the way at least I've thought about it is more 382 00:21:46,560 --> 00:21:49,517 about really building a fungeable fleet. 383 00:21:49,600 --> 00:21:52,957 I mean when I look at sort of in the cloud infrastructure business, one of 384 00:21:53,040 --> 00:21:57,757 the key things you have to do is have two things. One is an effic like in this 385 00:21:57,840 --> 00:22:02,237 context in a very efficient token factory and then high utilization. 386 00:22:02,320 --> 00:22:05,917 That's that's it. There are two simple things that you need to achieve and in 387 00:22:06,000 --> 00:22:09,197 order to have high utilization you have to have multiple workloads that can be 388 00:22:09,280 --> 00:22:12,557 scheduled even on the training. I mean, if you look at the AI pipelines, there's 389 00:22:12,640 --> 00:22:15,517 pre-training, there's mid-training, there's post- training, there's RL. You 390 00:22:15,600 --> 00:22:19,037 want to be able to do all of those things. So, thinking about fungeibility 391 00:22:19,120 --> 00:22:22,877 of the fleet is everything for a cloud provider. 392 00:22:22,960 --> 00:22:24,717 >> Okay. So, Sam, you referenced, you know, 393 00:22:24,800 --> 00:22:29,357 and and Reuters was reporting yesterday that OpenAI may be planning to go public 394 00:22:29,440 --> 00:22:32,317 late 26 or in 27. >> No, no, no. We we don't we don't have 395 00:22:32,400 --> 00:22:34,077 anything that specific. I I'm a realist. 396 00:22:34,160 --> 00:22:38,877 I assume it will happen someday, but that was uh I don't know why people 397 00:22:38,960 --> 00:22:42,877 write these reports. We don't have like date in mind decision to do this or 398 00:22:42,960 --> 00:22:45,597 anything like that. I just assume it's where things will eventually go. 399 00:22:45,680 --> 00:22:48,877 >> But it does seem to me if you guys were, 400 00:22:48,960 --> 00:22:50,717 you know, are are doing in excess of 401 00:22:50,800 --> 00:22:56,477 hundred billion dollars of revenue in 28 or 29 that you at least would be in pos 402 00:22:56,560 --> 00:22:58,237 >> what? >> How about 27? 403 00:22:58,320 --> 00:23:00,877 >> Yeah, 27 even better. You are in 404 00:23:00,960 --> 00:23:05,117 position to do an IPO and the rumored 405 00:23:05,200 --> 00:23:06,557 trillion dollars. Again, just to 406 00:23:06,640 --> 00:23:09,117 contextualize for listeners, if you guys 407 00:23:09,200 --> 00:23:12,237 went public at 10 times 100 billion in 408 00:23:12,320 --> 00:23:16,477 revenue, right, which would be, I think, a lower multiple than Facebook went 409 00:23:16,560 --> 00:23:18,957 public at, a lower multiple than a lot 410 00:23:19,040 --> 00:23:23,837 of other uh big consumer companies went public at, that would put you at a 411 00:23:23,920 --> 00:23:25,917 trillion dollars. If you floated 10 to 412 00:23:26,000 --> 00:23:28,077 20% of the company, that raises a 413 00:23:28,160 --> 00:23:31,677 hundred to$200 billion, which seems like 414 00:23:31,760 --> 00:23:35,597 that would be a good path to fund a lot of the growth and a lot of the stuff 415 00:23:35,680 --> 00:23:39,757 that we just talked about. So, you're you're you're not opposed to it. You're 416 00:23:39,840 --> 00:23:43,677 not But you guys are making fund the company with revenue growth, which is 417 00:23:43,760 --> 00:23:47,037 what I would like us to do. >> But no doubt about it. 418 00:23:47,120 --> 00:23:51,437 Well, I've also said I think that this is such an important company and you 419 00:23:51,520 --> 00:23:53,277 know there are so many people including 420 00:23:53,360 --> 00:23:56,237 my kids who like to trade their little 421 00:23:56,320 --> 00:24:01,037 accounts and they use chat GPT and I think having retail investors have an 422 00:24:01,120 --> 00:24:04,237 opportunity to buy one of the most important and largest 423 00:24:04,320 --> 00:24:06,637 >> honestly that that is probably the 424 00:24:06,720 --> 00:24:11,437 single most appealing thing about it to me. Um that would be really nice. 425 00:24:11,520 --> 00:24:15,677 One of the things I've talked to you both about um shifting gears again is 426 00:24:15,760 --> 00:24:17,917 part of the big beautiful bill, you 427 00:24:18,000 --> 00:24:20,637 know, Senator Cruz had included federal 428 00:24:20,720 --> 00:24:23,517 preeemption so that we wouldn't have 429 00:24:23,600 --> 00:24:26,717 this state patchwork 50 different laws 430 00:24:26,800 --> 00:24:31,517 that mireers the industry down in kind of needless compliance and regulation. 431 00:24:31,600 --> 00:24:35,437 unfortunately got killed at the last second by Senator Blackburn because 432 00:24:35,520 --> 00:24:39,357 frankly I think AI is pretty poorly understood in Washington and there's a 433 00:24:39,440 --> 00:24:41,597 lot of dumerism I think that has gained 434 00:24:41,680 --> 00:24:46,637 traction in Washington. So now we have state laws like the Colorado AI act that 435 00:24:46,720 --> 00:24:50,237 goes into full effect in February I believe that creates this whole new 436 00:24:50,320 --> 00:24:54,717 class of litigants anybody who claims any unfair impact from an algorithmic 437 00:24:54,800 --> 00:24:56,957 discrimination in a chatbot. So somebody 438 00:24:57,040 --> 00:24:59,917 could claim harm for countless reasons. 439 00:25:00,000 --> 00:25:03,117 Sam, how worried are you that, you know, 440 00:25:03,200 --> 00:25:08,317 having this state patchwork of AI, you know, poses real challenges to, you 441 00:25:08,400 --> 00:25:12,157 know, our ability to continue to accelerate and compete around the world. 442 00:25:12,240 --> 00:25:15,517 >> I don't know how we're supposed to comply with that California, sorry, 443 00:25:15,600 --> 00:25:19,357 Colorado law. I would love them to tell us uh and, you know, we'd like to be 444 00:25:19,440 --> 00:25:23,677 able to do it, but that's just from what I've read of that. That's like a I 445 00:25:23,760 --> 00:25:27,277 literally don't know what we're supposed to do. I'm very worried about a 50-state 446 00:25:27,360 --> 00:25:30,717 patchwork. I think it's a big mistake. I think it's there's a reason we don't 447 00:25:30,800 --> 00:25:33,997 usually do that for these sorts of things. I think it'd be bad. 448 00:25:34,080 --> 00:25:37,757 >> Yeah. I mean, I think the the fundamental problem of um you know, this 449 00:25:37,840 --> 00:25:42,317 patchwork approach is quite frankly, I mean, between OpenAI and Microsoft, 450 00:25:42,400 --> 00:25:46,237 we'll figure out a way to navigate this, right? I mean, uh we can figure this 451 00:25:46,320 --> 00:25:48,397 out. The problem is anyone starting a 452 00:25:48,480 --> 00:25:53,517 startup and trying to kind this it's sort of it just goes to the exact 453 00:25:53,600 --> 00:25:58,157 opposite of I think what the intent here is which obviously safety is very 454 00:25:58,240 --> 00:26:02,397 important making sure that the fundamental um you know concerns people 455 00:26:02,480 --> 00:26:05,677 have are addressed but there's a way to do that at the federal level so I think 456 00:26:05,760 --> 00:26:09,037 the U if we don't do this again you know 457 00:26:09,120 --> 00:26:11,437 EU will do it and then that'll cause its 458 00:26:11,520 --> 00:26:17,357 own issues so I think if US leads it's better uh as you as one regulatory 459 00:26:17,440 --> 00:26:21,757 framework >> for sure. >> And to be clear, it's not that one is 460 00:26:21,840 --> 00:26:25,357 advocating for no regulation. It's simply saying let's have, you know, 461 00:26:25,440 --> 00:26:26,957 agreed upon regulation at the federal 462 00:26:27,040 --> 00:26:29,277 level as opposed to 50 competing state 463 00:26:29,360 --> 00:26:32,637 laws which certainly uh firebombs the 464 00:26:32,720 --> 00:26:36,717 the AI startup industry and I think it makes it makes it super challenging even 465 00:26:36,800 --> 00:26:39,677 for companies like yours who can afford to defend all these cases. 466 00:26:39,760 --> 00:26:41,517 >> Yeah. And I would just say quite frankly 467 00:26:41,600 --> 00:26:45,997 my hope is that this time around even across EU and the United States like 468 00:26:46,080 --> 00:26:49,757 that'll be the dream right quite frankly for any European startup. 469 00:26:49,840 --> 00:26:51,597 >> I don't think that's going to happen. 470 00:26:51,680 --> 00:26:53,357 >> What is that? >> That would be great. I don't I wouldn't 471 00:26:53,440 --> 00:26:57,117 hold your breath for that one. That would be great. No, but I I I really 472 00:26:57,200 --> 00:27:00,717 think that if you think about it right, if you sort of if anyone in Europe is 473 00:27:00,800 --> 00:27:02,557 thinking about their you know what how 474 00:27:02,640 --> 00:27:05,677 can they participate in this AI uh 475 00:27:05,760 --> 00:27:10,157 economy with their companies uh this should be the main concern there as 476 00:27:10,240 --> 00:27:14,397 well. So therefore uh that's I hope there is some enlightened approach to it 477 00:27:14,480 --> 00:27:17,917 but I agree with you that you know today I wouldn't bet on that. 478 00:27:18,000 --> 00:27:20,877 I do think that with Sachs as the AIS 479 00:27:20,960 --> 00:27:23,037 are, you at least have a president that 480 00:27:23,120 --> 00:27:25,597 I think might fight for that in terms of 481 00:27:25,680 --> 00:27:30,877 coordination of of AI policy, using trade as a lever to make sure that, you 482 00:27:30,960 --> 00:27:33,917 know, we don't end up with overly restricted European policy. But we shall 483 00:27:34,000 --> 00:27:37,277 see. I think first things first, federal preeemption in the United States is 484 00:27:37,360 --> 00:27:40,237 pretty critical. You know, we've been down in the weeds a little bit here, 485 00:27:40,320 --> 00:27:42,157 Sam. So, I want to telescope out a 486 00:27:42,240 --> 00:27:45,117 little bit. You know, I've heard people 487 00:27:45,200 --> 00:27:47,917 on your team talk about all the great 488 00:27:48,000 --> 00:27:50,717 things coming up and and as you start 489 00:27:50,800 --> 00:27:52,557 thinking about much more unlimited 490 00:27:52,640 --> 00:27:56,877 compute chat GPT6 and beyond robotics, 491 00:27:56,960 --> 00:27:58,877 physical devices, 492 00:27:58,960 --> 00:28:04,077 scientific research as you as you look forward to 2026, what do you think 493 00:28:04,160 --> 00:28:08,477 surprises us the most? What what what what are you most excited about in terms 494 00:28:08,560 --> 00:28:12,717 of what's on the drawing board? you I mean you just hit on a lot of the key 495 00:28:12,800 --> 00:28:17,517 points there. I I think codeex has been a very cool thing to 496 00:28:17,600 --> 00:28:21,437 watch this year and as these go from multi-our tasks to multi-day tasks which 497 00:28:21,520 --> 00:28:23,837 I expect to happen next year what people 498 00:28:23,920 --> 00:28:29,197 be able to do to create software at an unprecedented rate and 499 00:28:29,280 --> 00:28:30,637 and really in fundamentally new ways. 500 00:28:30,720 --> 00:28:33,117 I'm very excited for that. I think we'll see that in other industries too. I have 501 00:28:33,200 --> 00:28:36,877 like a bias towards coding. I understand that one better. I think we'll see that 502 00:28:36,960 --> 00:28:39,117 really start to transform what people 503 00:28:39,200 --> 00:28:44,317 are capable of. I I I hope for very small scientific discoveries in 2026, 504 00:28:44,400 --> 00:28:47,517 but if we can get those very small ones, we'll get bigger ones in future years. 505 00:28:47,600 --> 00:28:50,477 That's a really crazy thing to say is that like AI is going to make a novel 506 00:28:50,560 --> 00:28:52,637 scientific discovery in 2026. Even a 507 00:28:52,720 --> 00:28:57,677 very small one. This is like this is a wildly important thing to be talking 508 00:28:57,760 --> 00:28:59,517 about. So, I'm excited for that. 509 00:28:59,600 --> 00:29:03,597 Certainly, robotics and computer and new kind of computers in future years. 510 00:29:03,680 --> 00:29:06,397 That'll be that'll be uh very important. 511 00:29:06,480 --> 00:29:10,797 But yeah, my personal bias is if we can 512 00:29:10,880 --> 00:29:15,437 really get AI to do science here, that is I mean that is super intelligence in 513 00:29:15,520 --> 00:29:19,357 some sense. Like if if this is expanding the total sum of human knowledge that is 514 00:29:19,440 --> 00:29:22,397 a crazy big deal. >> Yeah. I mean I think one of the things 515 00:29:22,480 --> 00:29:25,757 to use your codeex example I think the 516 00:29:25,840 --> 00:29:29,517 combination of the model capability I mean if you think about the magical 517 00:29:29,600 --> 00:29:31,997 moment that happened with chat GPT was 518 00:29:32,080 --> 00:29:35,197 the UI that met intelligence that just 519 00:29:35,280 --> 00:29:39,837 took off right there it's just you know unbelievable right form fact and some of 520 00:29:39,920 --> 00:29:41,677 it was also the instruction following 521 00:29:41,760 --> 00:29:44,717 piece of model capability was ready for 522 00:29:44,800 --> 00:29:47,597 chat I think that that's what the codeex 523 00:29:47,680 --> 00:29:49,997 and the you know these coding agents are 524 00:29:50,080 --> 00:29:52,877 about to uh help us which is what's that 525 00:29:52,960 --> 00:29:54,637 you know coding agent goes off for a 526 00:29:54,720 --> 00:29:57,277 long period of time comes back and then 527 00:29:57,360 --> 00:30:01,837 I'm then dropped into what I should steer like one of the metaphors I think 528 00:30:01,920 --> 00:30:04,157 we're all sort of working towards is I 529 00:30:04,240 --> 00:30:07,437 do this macro delegation and micro 530 00:30:07,520 --> 00:30:11,117 steering what is that UI meets this new 531 00:30:11,200 --> 00:30:15,597 intelligence capability and you can see the beginnings of that with codeex right 532 00:30:15,680 --> 00:30:19,917 the way at least I use it inside a GitHub copilot is I you know it's Now, 533 00:30:20,000 --> 00:30:22,317 it's just a it's a just a different way 534 00:30:22,400 --> 00:30:26,957 than the chat interface. And I think that that I think would be a new way for 535 00:30:27,040 --> 00:30:30,557 the human computer interface. Quite frankly, it's probably bigger than 536 00:30:30,640 --> 00:30:33,037 >> uh that that might be the departure. 537 00:30:33,120 --> 00:30:36,397 >> That's one reason I'm very excited that we're doing new form factors of 538 00:30:36,480 --> 00:30:39,677 computing devices cuz computers were not built for that kind of workflow very 539 00:30:39,760 --> 00:30:42,477 well. Certainly, a UI like Chacht is 540 00:30:42,560 --> 00:30:47,277 wrong for it. But this idea that you can have a device that is sort of always 541 00:30:47,360 --> 00:30:50,557 with you but able to go off and do things and get micro steer from you when 542 00:30:50,640 --> 00:30:53,997 it needs and have like really good contextual awareness of your whole life 543 00:30:54,080 --> 00:30:55,757 and flow. And I think that'll be cool. 544 00:30:55,840 --> 00:30:59,437 >> And what neither of you have talked about is the consumer use case. I think 545 00:30:59,520 --> 00:31:02,797 a lot about, you know, again, we go under this device and we have to hunt 546 00:31:02,880 --> 00:31:05,837 and peck through a hundred different applications and fill out little web 547 00:31:05,920 --> 00:31:09,917 forms, things that really haven't changed in 20 years. But to just have, 548 00:31:10,000 --> 00:31:12,877 you know, a personal assistant that we take for granted perhaps that we 549 00:31:12,960 --> 00:31:16,637 actually have a personal assistant, but to give a personal assistant for 550 00:31:16,720 --> 00:31:21,437 virtually free to billions of people around the world to improve their lives, 551 00:31:21,520 --> 00:31:25,117 whether it's, you know, ordering diapers for their kid or whether it's, you know, 552 00:31:25,200 --> 00:31:29,277 booking their hotel or or or making changes in their calendar. I think 553 00:31:29,360 --> 00:31:31,357 sometimes it's the pedestrian that's 554 00:31:31,440 --> 00:31:36,477 that's the most impactful. And as we move from answers to memory and actions 555 00:31:36,560 --> 00:31:39,917 and then the ability to interface with that through an earbud or some other 556 00:31:40,000 --> 00:31:43,517 device that doesn't require me to constantly be st staring at this 557 00:31:43,600 --> 00:31:46,877 rectangular piece of glass. I think it's pretty extraordinary. 558 00:31:46,960 --> 00:31:49,357 >> I think that that's what Sam was teasing. 559 00:31:49,440 --> 00:31:53,197 >> Yeah. Yeah. >> Hope we get it right. I got to drop off unfortunately. 560 00:31:53,280 --> 00:31:56,957 >> Sam, it was great to see you. Thanks for joining us. Congrats again on this big 561 00:31:57,040 --> 00:31:58,077 step forward and we'll talk soon. 562 00:31:58,160 --> 00:31:59,757 >> Thanks for letting me crash. 563 00:31:59,840 --> 00:32:02,397 >> See you Sam. Take care. See you. 564 00:32:02,480 --> 00:32:07,437 >> As Samwell knows, we're certainly a buyer, not a seller. Um, but but but 565 00:32:07,520 --> 00:32:11,997 sometimes, you know, I think it's important because the world, you know, 566 00:32:12,080 --> 00:32:16,237 we're a pretty small, we spend all day long thinking about this stuff, right? 567 00:32:16,320 --> 00:32:18,957 And so conviction, it comes from the 568 00:32:19,040 --> 00:32:23,837 10,000 hours we've spent thinking about it. But the reality is we have to bring 569 00:32:23,920 --> 00:32:27,757 along the rest of the world. And the rest of the world doesn't spend 10,000 570 00:32:27,840 --> 00:32:31,437 hours thinking about this. Um, and frankly they look at some things that 571 00:32:31,520 --> 00:32:34,317 appear overly ambitious, right, and get 572 00:32:34,400 --> 00:32:36,077 worried about whether or not we can pull 573 00:32:36,160 --> 00:32:38,717 those things off. You took this idea to 574 00:32:38,800 --> 00:32:41,917 the board in 2019 to invest a billion 575 00:32:42,000 --> 00:32:46,077 dollars into open AI. Was it a no-brainer in the boardroom? You know, 576 00:32:46,160 --> 00:32:50,477 did you have to expend any political capital to get it done? dish dish for me 577 00:32:50,560 --> 00:32:54,557 a little bit like what that moment was was like because I think it was such a 578 00:32:54,640 --> 00:32:58,477 pivotal moment not just for Microsoft not just for the country but I really do 579 00:32:58,560 --> 00:33:02,317 think for the world. Yeah, I mean it's it's interesting when you look back the 580 00:33:02,400 --> 00:33:04,157 the journey when I look at it it's been 581 00:33:04,240 --> 00:33:07,597 a you know we were involved even in 2016 582 00:33:07,680 --> 00:33:10,557 uh when initially open AI uh started in 583 00:33:10,640 --> 00:33:14,717 fact Azure was even the first sponsor I think and then they were doing a lot 584 00:33:14,800 --> 00:33:18,957 more reinforcement learning at that time I remember the Dota 2 competition I 585 00:33:19,040 --> 00:33:23,597 think happened on Azure and then uh they moved on to other things and you know I 586 00:33:23,680 --> 00:33:27,517 was interested in RL but quite frankly you know it speaks a little bit to your 587 00:33:27,600 --> 00:33:30,477 10,000 hours or the prepared had mind. 588 00:33:30,560 --> 00:33:35,597 Uh Microsoft since 1995 was obsessed. I mean, Bill's obsession for the company 589 00:33:35,680 --> 00:33:37,277 was natural language. Natural language. 590 00:33:37,360 --> 00:33:41,197 I mean, after all, we're a coding company. We're information work company. 591 00:33:41,280 --> 00:33:43,597 >> So, it's when Sam in 2019 started 592 00:33:43,680 --> 00:33:45,997 talking about text and natural language 593 00:33:46,080 --> 00:33:48,877 and transformers and scaling laws. 594 00:33:48,960 --> 00:33:53,197 >> Uh that's when I said, "Wow, like this is an interesting I mean he, you know, 595 00:33:53,280 --> 00:33:57,277 this is a team that was going in the direction or the direction of travel was 596 00:33:57,360 --> 00:34:00,157 now clear. it had a lot more overlap 597 00:34:00,240 --> 00:34:02,957 with our interest. So in that sense it 598 00:34:03,040 --> 00:34:07,997 was a no-brainer. Obviously you go to the board and say hey I have an idea of 599 00:34:08,080 --> 00:34:12,237 taking a billion dollars and giving it to this crazy structure which we don't 600 00:34:12,320 --> 00:34:14,157 even kind of understand what is it. It's 601 00:34:14,240 --> 00:34:16,877 a nonprofit blah blah blah and and 602 00:34:16,960 --> 00:34:19,677 saying go for it. Uh there was a debate. 603 00:34:19,760 --> 00:34:22,157 Uh Bill was kind of rightfully so 604 00:34:22,240 --> 00:34:27,117 skeptical because and then he became like once he saw the GPD4 demo like that 605 00:34:27,200 --> 00:34:31,037 was like the thing that Bill's talked about publicly where uh when he saw it 606 00:34:31,120 --> 00:34:33,357 he said it's the best demo he saw after 607 00:34:33,440 --> 00:34:35,037 you know what Charles Simony showed him 608 00:34:35,120 --> 00:34:38,317 at Xerox Park and but you know quite 609 00:34:38,400 --> 00:34:40,637 honestly none of us could uh so the 610 00:34:40,720 --> 00:34:43,037 moment for me was that you know let's go 611 00:34:43,120 --> 00:34:46,157 give it a shot then seeing the early 612 00:34:46,240 --> 00:34:50,157 codeex inside of uh copilot inside of uh 613 00:34:50,240 --> 00:34:52,717 GitHub copilot and seeing just the code 614 00:34:52,800 --> 00:34:55,357 completions and seeing it work. That's 615 00:34:55,440 --> 00:35:00,317 when I would say we I I felt like I can go from 1 to 10 because that was the big 616 00:35:00,400 --> 00:35:03,277 call quite frankly. One was controversial. 617 00:35:03,360 --> 00:35:06,877 >> Uh but the 1 to 10 was what really made 618 00:35:06,960 --> 00:35:09,517 this entire era possible and then 619 00:35:09,600 --> 00:35:14,237 obviously uh the great execution by the team and the productization on their 620 00:35:14,320 --> 00:35:15,997 part, our part. I mean if I think about 621 00:35:16,080 --> 00:35:18,797 it right the collective monetization 622 00:35:18,880 --> 00:35:22,237 reach of GitHub copilot chat GPT 623 00:35:22,320 --> 00:35:26,477 Microsoft 365 copilot and co-pilot you add those four things that is it right 624 00:35:26,560 --> 00:35:28,717 that's the biggest sort of AI set of 625 00:35:28,800 --> 00:35:33,517 products uh out there on the planet and that's um you know what obviously has 626 00:35:33,600 --> 00:35:37,917 let us sustain all of this and I think not many people know that your CTO Kevin 627 00:35:38,000 --> 00:35:42,077 Scott you know an ex googler lives down here in Silicon Valley and to 628 00:35:42,160 --> 00:35:44,077 contextualize it right Microsoft had 629 00:35:44,160 --> 00:35:46,397 missed out on search had missed out on 630 00:35:46,480 --> 00:35:49,197 mobile. You become CEO, almost had 631 00:35:49,280 --> 00:35:51,677 missed out on the cloud, right? You 632 00:35:51,760 --> 00:35:53,837 you've described it, caught the last 633 00:35:53,920 --> 00:35:56,957 train out of town to capture the cloud. 634 00:35:57,040 --> 00:36:00,717 And I think you were pretty determined to have eyes and ears down here so you 635 00:36:00,800 --> 00:36:05,277 didn't miss the next big thing. So I assume that Kevin played a good role for 636 00:36:05,360 --> 00:36:08,797 you as well. >> Absolutely. >> Deep Seek and Open AI. 637 00:36:08,880 --> 00:36:11,437 >> Yeah. I mean I mean if uh it's in fact I 638 00:36:11,520 --> 00:36:14,237 would say Kevin's conviction uh and 639 00:36:14,320 --> 00:36:16,157 Kevin was also skeptical like that was 640 00:36:16,240 --> 00:36:18,797 the thing I I I always watch for people 641 00:36:18,880 --> 00:36:22,077 who are skeptical who change uh their 642 00:36:22,160 --> 00:36:26,797 opinion because to me that's a signal so I'm always looking for someone who's a 643 00:36:26,880 --> 00:36:30,397 non-believer in something and then suddenly changes and then they get 644 00:36:30,480 --> 00:36:32,397 excited about it that I have all the 645 00:36:32,480 --> 00:36:37,597 time for that because I'm then curious why what and so Kevin started with all 646 00:36:37,680 --> 00:36:41,997 of us were kind of skeptical Right. No, I mean in some sense it defies the the 647 00:36:42,080 --> 00:36:45,837 you know we're all having gone to school and said god you know there must be an 648 00:36:45,920 --> 00:36:50,317 algorithm to crack this versus just let's scaling laws and throw compute. 649 00:36:50,400 --> 00:36:52,717 But quite frankly uh Kevin's conviction 650 00:36:52,800 --> 00:36:55,757 that this is worth going after is one of 651 00:36:55,840 --> 00:36:59,917 the big things that drove this. Well, we talk about, you know, that that 652 00:37:00,000 --> 00:37:03,997 investment that that's now worth 130 billion, I suppose, could be worth a 653 00:37:04,080 --> 00:37:06,397 trillion someday, as Sam says, but it 654 00:37:06,480 --> 00:37:08,077 really in many ways understates the 655 00:37:08,160 --> 00:37:11,517 value of the partnership, right? So, you 656 00:37:11,600 --> 00:37:13,677 have the value in the revshare, billions 657 00:37:13,760 --> 00:37:16,797 per year going to Microsoft. You have 658 00:37:16,880 --> 00:37:19,997 the profit you make off the $250 billion 659 00:37:20,080 --> 00:37:22,317 of the Azure compute commitment from 660 00:37:22,400 --> 00:37:25,837 OpenAI. And of course you get huge sales 661 00:37:25,920 --> 00:37:28,637 from the exclusive distribution of the 662 00:37:28,720 --> 00:37:31,277 API. So talk to us how you think about 663 00:37:31,360 --> 00:37:36,637 the value across those domains especially how this exclusivity has 664 00:37:36,720 --> 00:37:40,317 brought a lot of customers who may have been on AWS to Azure. 665 00:37:40,400 --> 00:37:43,117 >> Yeah. No absolutely. I mean so to us um 666 00:37:43,200 --> 00:37:45,917 if I look at it um you know aside from 667 00:37:46,000 --> 00:37:48,477 all the uh the equity parts the real 668 00:37:48,560 --> 00:37:51,117 strategic thing that comes together and 669 00:37:51,200 --> 00:37:53,917 that remains going forward uh is that 670 00:37:54,000 --> 00:37:56,877 stateless API exclusivity on Azure that 671 00:37:56,960 --> 00:37:59,437 helps quite frankly both open AAI and us 672 00:37:59,520 --> 00:38:01,677 and our customers uh because when 673 00:38:01,760 --> 00:38:03,997 somebody in the enterprise uh is trying 674 00:38:04,080 --> 00:38:06,637 to build an application they want an API 675 00:38:06,720 --> 00:38:09,357 that's stateless they want to mix it up 676 00:38:09,440 --> 00:38:12,477 with uh compute in storage, put a 677 00:38:12,560 --> 00:38:14,717 database underneath it to capture state 678 00:38:14,800 --> 00:38:16,797 and build a full workload and that's 679 00:38:16,880 --> 00:38:19,917 where uh you know Azure coming together 680 00:38:20,000 --> 00:38:24,877 with this API and so what we're doing with even uh Azure foundry right because 681 00:38:24,960 --> 00:38:28,317 in some sense you let's say you want to build an AI application but the key 682 00:38:28,400 --> 00:38:31,117 thing is uh how do you make sure that 683 00:38:31,200 --> 00:38:33,677 the eval 684 00:38:33,760 --> 00:38:35,677 are great so that's where you need even 685 00:38:35,760 --> 00:38:39,117 a full app server in Foundry that's what 686 00:38:39,200 --> 00:38:41,597 we've done and so therefore I feel that 687 00:38:41,680 --> 00:38:43,757 that is the way we will go to market in 688 00:38:43,840 --> 00:38:46,397 our infrastructure business. The other 689 00:38:46,480 --> 00:38:48,637 side of the value capture for us is 690 00:38:48,720 --> 00:38:51,277 going to be incorporating all this IP. 691 00:38:51,360 --> 00:38:53,917 Not only we have the exclusivity of the 692 00:38:54,000 --> 00:38:58,877 model in uh Azure but we have access to the IP. I mean having a royaltyfree 693 00:38:58,960 --> 00:39:03,037 let's even forgetting all the the knowhow and the knowledge side of it but 694 00:39:03,120 --> 00:39:07,677 having royalty-free access all the way till seven more years gives us a lot of 695 00:39:07,760 --> 00:39:11,837 flexibility business model wise. It's kind of like having a frontier model for 696 00:39:11,920 --> 00:39:15,997 free uh in some sense if you're an MSFT shareholder. That's kind of where you 697 00:39:16,080 --> 00:39:20,077 should start from is to think about we have a frontier model that we can then 698 00:39:20,160 --> 00:39:23,677 deploy whether it's in GitHub, whether it's in M365, whether it's in our 699 00:39:23,760 --> 00:39:26,877 consumer copilot, then add to it our own 700 00:39:26,960 --> 00:39:31,837 data, post train it. Uh so that means we can have it embedded in the weights 701 00:39:31,920 --> 00:39:33,597 there. And so therefore we're excited 702 00:39:33,680 --> 00:39:36,237 about the value creation on both the 703 00:39:36,320 --> 00:39:38,877 Azure and the infrastructure side as 704 00:39:38,960 --> 00:39:43,437 well as in our high value domains uh whether it is in health whether it's in 705 00:39:43,520 --> 00:39:46,077 knowledge work whether it's in coding or security 706 00:39:46,160 --> 00:39:49,997 >> you've been consolidating the losses from open AI you know I think you you 707 00:39:50,080 --> 00:39:54,077 just reported earnings yesterday I think you consolidated 4 billion of losses in 708 00:39:54,160 --> 00:39:58,957 the quarter do you think that investors are I mean they may even be attributing 709 00:39:59,040 --> 00:40:02,397 negative value right because of the losses you know as they apply their 710 00:40:02,480 --> 00:40:06,877 multiple of earnings. Satcha, whereas I hear this and I think about all of those 711 00:40:06,960 --> 00:40:11,437 benefits we just described, not to mention the look through equity value 712 00:40:11,520 --> 00:40:15,757 that you own in a company that could be worth a trillion unto itself. You know, 713 00:40:15,840 --> 00:40:17,917 do you think that the market is is is 714 00:40:18,000 --> 00:40:22,957 kind of misunderstanding the value of open AI as a component of Microsoft? 715 00:40:23,040 --> 00:40:26,797 >> Yeah, that's a good one. So, I think the the approach that Amy is going to take 716 00:40:26,880 --> 00:40:31,597 is full transparency because at some level I'm no accounting expert. So 717 00:40:31,680 --> 00:40:36,397 therefore the best thing to do is to give uh all of the transparency I think 718 00:40:36,480 --> 00:40:40,077 this time around as well. I think that's why the non-GAAP gap so that at least 719 00:40:40,160 --> 00:40:44,877 people can see the EPS numbers because the the the common sense way I look at 720 00:40:44,960 --> 00:40:46,797 it Brad is simple. If you've invested 721 00:40:46,880 --> 00:40:49,517 let's call it 13.5 billion. You can of 722 00:40:49,600 --> 00:40:52,397 course lose 13.5 billion but you can't 723 00:40:52,480 --> 00:40:56,797 lose more than 13.5 billion. At least the last time I checked that's what you 724 00:40:56,880 --> 00:40:58,957 have at risk. You could also say hey the 725 00:40:59,040 --> 00:41:02,397 $135 billion that has you know today our 726 00:41:02,480 --> 00:41:05,357 equity stake you know is sort of illquid 727 00:41:05,440 --> 00:41:09,837 what have you we don't plan to sell it so therefore it's got risk associated 728 00:41:09,920 --> 00:41:14,717 with it but the real story I think you were pulling is all the other things uh 729 00:41:14,800 --> 00:41:18,317 that are happening what's happening with Azure growth right would Azure be 730 00:41:18,400 --> 00:41:22,637 growing if we had not sort of had the openi partnership to your point the 731 00:41:22,720 --> 00:41:25,837 number of customers who came from other clouds 732 00:41:25,920 --> 00:41:29,997 for the first time right this is the thing that really we benefited from 733 00:41:30,080 --> 00:41:33,757 what's happening with Microsoft 365. In fact, one of the things about Microsoft 734 00:41:33,840 --> 00:41:35,837 365 was what was the next big thing 735 00:41:35,920 --> 00:41:38,637 after E5? Guess what? We found it in 736 00:41:38,720 --> 00:41:41,997 copilot. It's bigger than any suite. 737 00:41:42,080 --> 00:41:44,637 Like you know, we talk about penetration 738 00:41:44,720 --> 00:41:49,837 and usage uh and the pace. It's bigger than anything we've done in our 739 00:41:49,920 --> 00:41:53,997 information work which we've been added for decades. And so so we pretty feel 740 00:41:54,080 --> 00:41:58,317 very very good about the opportunity to create value for our shareholders. Uh 741 00:41:58,400 --> 00:42:01,757 and then at the same time be fully transparent so that people can look 742 00:42:01,840 --> 00:42:05,197 through the what are the losses. I mean who knows what the accounting rules are 743 00:42:05,280 --> 00:42:09,037 but we will do whatever is needed and people will then be able to see what's 744 00:42:09,120 --> 00:42:13,357 happening. But a year ago, Satcha, there were a bunch of headlines that Microsoft 745 00:42:13,440 --> 00:42:17,517 was pulling back on AI infrastructure, right? Fair or unfair, they're they were 746 00:42:17,600 --> 00:42:20,797 out there, you know, and and and perhaps you guys were a little more 747 00:42:20,880 --> 00:42:25,837 conservative, a little more skeptical of what was going on. Amy said on the call 748 00:42:25,920 --> 00:42:29,277 last night, though, that you've been short power and infrastructure for many 749 00:42:29,360 --> 00:42:33,277 quarters, and she thought that you would catch up, but you haven't c caught up 750 00:42:33,360 --> 00:42:36,957 because demand keeps increasing. So I guess the question is were you too 751 00:42:37,040 --> 00:42:40,957 conservative you know knowing what you know now and and and what's the road map 752 00:42:41,040 --> 00:42:43,437 from here? >> Yeah it's a great question because see 753 00:42:43,520 --> 00:42:46,877 the the thing that we realized and I'm 754 00:42:46,960 --> 00:42:50,477 glad we did uh is that the concept of 755 00:42:50,560 --> 00:42:54,237 building a fleet that truly was funible 756 00:42:54,320 --> 00:42:56,317 fungeible for all the parts of the life 757 00:42:56,400 --> 00:42:59,997 cycle of AI funible across geographies 758 00:43:00,080 --> 00:43:03,037 and fungeible across generations. Right? 759 00:43:03,120 --> 00:43:07,117 So because one of the key things is when you have let's take even uh what Jensen 760 00:43:07,200 --> 00:43:10,877 and team are doing right I mean they're at a pace in fact one of the things I 761 00:43:10,960 --> 00:43:14,797 like is the speed of light right we now have GB300's bringing you know that 762 00:43:14,880 --> 00:43:16,477 we're bringing up so you don't want to 763 00:43:16,560 --> 00:43:20,077 have ordered a bunch of GB200's that are 764 00:43:20,160 --> 00:43:22,397 getting plugged in only to find that 765 00:43:22,480 --> 00:43:25,197 GB2300s are in full production. So you 766 00:43:25,280 --> 00:43:27,197 kind of have to make sure you're 767 00:43:27,280 --> 00:43:29,757 continuously modernizing, you're 768 00:43:29,840 --> 00:43:32,397 spreading the fleet all over, you are 769 00:43:32,480 --> 00:43:35,357 really truly funible by workload uh and 770 00:43:35,440 --> 00:43:39,917 you're adding to that the software optimizations we talked about. So to me 771 00:43:40,000 --> 00:43:44,957 that is the decision we made and we said look sometimes you may have to say no to 772 00:43:45,040 --> 00:43:48,717 some of the demand including some of the open AI demand right because sometimes 773 00:43:48,800 --> 00:43:50,717 you know Sam may say hey we build me a 774 00:43:50,800 --> 00:43:53,437 dedicated you know big you know whatever 775 00:43:53,520 --> 00:43:55,997 multi- gigawatt data center in one 776 00:43:56,080 --> 00:43:58,637 location for training makes sense from 777 00:43:58,720 --> 00:44:03,757 an open AI perspective doesn't make sense from a long-term infrastructure 778 00:44:03,840 --> 00:44:07,277 buildout for Azure and that's where I thought they did the right thing to give 779 00:44:07,360 --> 00:44:09,677 them flexibility to go procure that from 780 00:44:09,760 --> 00:44:14,477 others while m maintaining uh again a significant book of business from open 781 00:44:14,560 --> 00:44:16,077 AAI but more importantly giving 782 00:44:16,160 --> 00:44:21,677 ourselves the flexibility with other customers our own one P remember like 783 00:44:21,760 --> 00:44:25,837 one of the things that we don't want to do is be short on uh is you know we talk 784 00:44:25,920 --> 00:44:29,517 about Azure in fact some of times our investors are overly fixated on the 785 00:44:29,600 --> 00:44:34,397 Azure number but remember for me the high margin business for me is co-pilot 786 00:44:34,480 --> 00:44:36,317 it is security co-pilot it's GitHub 787 00:44:36,400 --> 00:44:39,197 co-pilot it's the healthcare co-pilot So 788 00:44:39,280 --> 00:44:43,597 we want to make sure we have a balanced way to approach the returns that the 789 00:44:43,680 --> 00:44:47,837 investors have. And so that's kind of one of the other misunderstood perhaps 790 00:44:47,920 --> 00:44:50,957 in our investor base in particular, which I find pretty strange and funny 791 00:44:51,040 --> 00:44:55,437 because I think they they want to hold Microsoft because of the portfolio we 792 00:44:55,520 --> 00:44:57,837 have. But man are they fixated on the 793 00:44:57,920 --> 00:44:59,517 growth number of one little thing called 794 00:44:59,600 --> 00:45:04,477 Azure. On that point, Azure grew 39% in 795 00:45:04,560 --> 00:45:07,837 the quarter on a staggering $93 billion 796 00:45:07,920 --> 00:45:09,677 run rate. And you know, I think that 797 00:45:09,760 --> 00:45:13,597 compares to GCP that grew at 32% and AWS 798 00:45:13,680 --> 00:45:17,197 closer to 20%. But could Azure because 799 00:45:17,280 --> 00:45:20,477 you did give compute to 1P and because 800 00:45:20,560 --> 00:45:23,037 you did give compute to research, it 801 00:45:23,120 --> 00:45:25,277 sounds like Azure could have grown 41 802 00:45:25,360 --> 00:45:28,157 42% had you had more compute to offer. 803 00:45:28,240 --> 00:45:31,277 >> Absolutely. Absolutely. There's no question. There is no question. So 804 00:45:31,360 --> 00:45:35,837 that's why I think the internal thing is to balance out what we think again is in 805 00:45:35,920 --> 00:45:39,597 the long-term interests of our shareholders and uh and also to serve 806 00:45:39,680 --> 00:45:43,677 our customers well and also not to kind of you know one of the other things was 807 00:45:43,760 --> 00:45:47,437 you know people talk about concentration risk right we obviously want a lot of 808 00:45:47,520 --> 00:45:52,717 open AI but we also want other customer and so we're shaping the demand here you 809 00:45:52,800 --> 00:45:56,077 know we are in a supply you know you know we're not demand constraint we're 810 00:45:56,160 --> 00:46:01,197 supply constraint so we are shaping the demand such that it matches is the 811 00:46:01,280 --> 00:46:04,637 supply in the optimal way with the long-term uh view. 812 00:46:04,720 --> 00:46:08,957 >> To that point, Satcha, you you talked about 400 billion. It's incredible 813 00:46:09,040 --> 00:46:13,997 number of remaining performance obligations. Last night, you said that, 814 00:46:14,080 --> 00:46:17,997 you know, that's your booked business today. It'll surely go up tomorrow as 815 00:46:18,080 --> 00:46:21,997 sales continue to come in. And you said you're going to, you know, your need to 816 00:46:22,080 --> 00:46:24,237 build out capacity just to serve that 817 00:46:24,320 --> 00:46:26,877 backlog is very high. You know, how 818 00:46:26,960 --> 00:46:29,357 diversified is that backlog to your to 819 00:46:29,440 --> 00:46:34,157 your point? And how confident are you that that 400 billion does turn into 820 00:46:34,240 --> 00:46:37,037 revenue over the course of the next couple years? 821 00:46:37,120 --> 00:46:39,917 >> Yeah, that that 400 billion uh has a 822 00:46:40,000 --> 00:46:41,997 very short duration as Amy explained. 823 00:46:42,080 --> 00:46:45,197 It's the 2-year uh duration on average. 824 00:46:45,280 --> 00:46:47,117 So that's definitely uh our intent. 825 00:46:47,200 --> 00:46:51,117 That's one of the reasons why uh we're spending the capital outcllay with high 826 00:46:51,200 --> 00:46:54,797 certainty that we just need to clear this backlog. And to your point, it's 827 00:46:54,880 --> 00:46:57,117 pretty diversified both on the 1 P and 828 00:46:57,200 --> 00:46:59,677 the 3P. our own demand is quite frankly 829 00:46:59,760 --> 00:47:02,157 pretty high for our one first party uh 830 00:47:02,240 --> 00:47:04,157 and even amongst third party one of the 831 00:47:04,240 --> 00:47:07,677 things we now are seeing is the the rise 832 00:47:07,760 --> 00:47:12,557 of all the other companies building real workloads uh that are scaling uh and so 833 00:47:12,640 --> 00:47:16,797 given that I think we feel very good I mean obviously it's uh that's one of the 834 00:47:16,880 --> 00:47:20,717 best things about RPO is you can be planful quite frankly and so therefore 835 00:47:20,800 --> 00:47:24,077 we feel very very good about building and then this doesn't include obviously 836 00:47:24,160 --> 00:47:29,037 the additional demand that we're already going to start seeing including the 250 837 00:47:29,120 --> 00:47:32,877 uh you know which will have a longer duration and we'll build accordingly 838 00:47:32,960 --> 00:47:35,837 >> right so there are a lot of new entrance 839 00:47:35,920 --> 00:47:38,237 right uh in this race to build out 840 00:47:38,320 --> 00:47:41,757 compute Oracle coreweave cruso etc and 841 00:47:41,840 --> 00:47:46,237 normally we think that will compete away margins but you've somehow managed to 842 00:47:46,320 --> 00:47:48,317 build all this out while maintaining 843 00:47:48,400 --> 00:47:50,717 healthy operating margins at Azure so I 844 00:47:50,800 --> 00:47:53,437 guess the question is for Microsoft how 845 00:47:53,520 --> 00:47:56,797 do you compete in this world that is uh 846 00:47:56,880 --> 00:48:01,277 where people are levering up, taking lower margins while balancing that 847 00:48:01,360 --> 00:48:05,997 profit and and and risk. And do you see any of those competitors doing deals 848 00:48:06,080 --> 00:48:09,357 that cause you to scratch your head and say, "Oh, we're just setting ourselves 849 00:48:09,440 --> 00:48:11,757 up for another boom and bust cycle." 850 00:48:11,840 --> 00:48:13,757 >> I mean, I'd say at some level the the 851 00:48:13,840 --> 00:48:19,037 good news for us has been competing even as a hyperscaler every day. You know, 852 00:48:19,120 --> 00:48:23,197 there's a lot of competition, right, between us and Amazon and Google on all 853 00:48:23,280 --> 00:48:26,477 of these, right? I mean it's sort of one of those interesting things which is 854 00:48:26,560 --> 00:48:30,397 everything is a commodity right compute storage I remember everybody saying wow 855 00:48:30,480 --> 00:48:32,957 how can there be a margin except at 856 00:48:33,040 --> 00:48:37,837 scale nothing is a commodity um and so therefore yes so we have to have our 857 00:48:37,920 --> 00:48:39,597 cost structure our supply chain 858 00:48:39,680 --> 00:48:43,037 efficiency our software efficiencies all 859 00:48:43,120 --> 00:48:46,077 have to kind of continue to compound in 860 00:48:46,160 --> 00:48:50,717 order to make sure that there's margins uh but scale and to your point one of 861 00:48:50,800 --> 00:48:52,957 the things that I really love about the 862 00:48:53,040 --> 00:48:55,277 OpenAI partnership is it's gotten us to 863 00:48:55,360 --> 00:48:58,157 scale, right? This is a scale game. When 864 00:48:58,240 --> 00:49:00,877 you have uh the biggest workload there 865 00:49:00,960 --> 00:49:05,357 is running on your cloud, that means not only are we going to learn faster on 866 00:49:05,440 --> 00:49:08,397 what it means to operate with scale, that means your cost structure is going 867 00:49:08,480 --> 00:49:10,477 to come down faster than anything else. 868 00:49:10,560 --> 00:49:14,237 And guess what? That'll make us price competitive. And so I feel pretty 869 00:49:14,320 --> 00:49:18,957 confident about our ability to, you know, have margins. And and that this is 870 00:49:19,040 --> 00:49:21,677 where the portfolio helps. I've always said 871 00:49:21,760 --> 00:49:26,317 >> you know you know I've been forced into giving the Azure numbers right because 872 00:49:26,400 --> 00:49:28,157 at some level I never thought of 873 00:49:28,240 --> 00:49:30,797 allocating I mean my capital allocation 874 00:49:30,880 --> 00:49:34,237 is for the cloud from whether it is Xbox 875 00:49:34,320 --> 00:49:38,317 cloud gaming or Microsoft 365 or for 876 00:49:38,400 --> 00:49:41,117 Azure it's one capital outlay uh and 877 00:49:41,200 --> 00:49:45,917 then everything is a meter as far as I'm concerned from an MSF perspective it's a 878 00:49:46,000 --> 00:49:48,077 question of hey the blended average of 879 00:49:48,160 --> 00:49:50,877 that should match the operating margins 880 00:49:50,960 --> 00:49:55,197 we need as a company because after all otherwise why we're not a conglomerate 881 00:49:55,280 --> 00:49:59,357 we're one company with one platform logic it's not running five six 882 00:49:59,440 --> 00:50:03,197 different businesses we're in these five six different businesses only to 883 00:50:03,280 --> 00:50:05,997 compound the returns on the cloud and AI 884 00:50:06,080 --> 00:50:10,317 investment >> yeah I I love that line uh nothing is a 885 00:50:10,400 --> 00:50:14,957 commodity at scale you know there's been a lot of ink and time spent even on this 886 00:50:15,040 --> 00:50:19,037 podcast with my partner Bill Gurley talking about circular revenues 887 00:50:19,120 --> 00:50:23,117 including including Microsoft Stasher credits right to OpenAI that were booked 888 00:50:23,200 --> 00:50:25,997 as revenue. Do you see anything going on 889 00:50:26,080 --> 00:50:28,317 like the AMD deal, you know, where they 890 00:50:28,400 --> 00:50:30,477 traded 10% of their equity and, you 891 00:50:30,560 --> 00:50:33,437 know, for a deal or the Nvidia deal? 892 00:50:33,520 --> 00:50:37,277 Again, I don't want to be overly fixated on concern, but I do want to address 893 00:50:37,360 --> 00:50:41,917 headon what is uh being talked about every day on CNBC and Bloomberg and 894 00:50:42,000 --> 00:50:45,997 there are a lot of these overlapping deals that are going on out there. Do 895 00:50:46,080 --> 00:50:50,157 you do you when you think about that in the context of Microsoft does any of 896 00:50:50,240 --> 00:50:52,477 that worry you again as to the 897 00:50:52,560 --> 00:50:56,157 sustainability or durability of uh the 898 00:50:56,240 --> 00:50:58,157 AI revenues that we see in the world? 899 00:50:58,240 --> 00:51:00,717 >> Yeah. I mean first of all our investment 900 00:51:00,800 --> 00:51:05,597 of uh let's say that 13 and a half which was all the training investment that was 901 00:51:05,680 --> 00:51:10,077 not booked as revenue. That is the that is the reason why we have the equity 902 00:51:10,160 --> 00:51:12,557 percentage. That's the reason why we 903 00:51:12,640 --> 00:51:15,517 have the 27% or 135 billion. So that was 904 00:51:15,600 --> 00:51:19,757 not something some that somehow that made it into Azure revenue. In fact, if 905 00:51:19,840 --> 00:51:21,997 anything, the Azure revenue was purely 906 00:51:22,080 --> 00:51:25,757 the consumption revenue of chat GPT and 907 00:51:25,840 --> 00:51:28,157 anything else and the APIs they put out 908 00:51:28,240 --> 00:51:30,637 that they monetized and we monetized 909 00:51:30,720 --> 00:51:33,677 >> to your aspect of others. You know, to 910 00:51:33,760 --> 00:51:37,837 some degree, it's always been there in terms of vendor financing, right? So 911 00:51:37,920 --> 00:51:42,077 it's not like a new concept that when someone's building something and they 912 00:51:42,160 --> 00:51:44,637 have a customer who is also building 913 00:51:44,720 --> 00:51:49,357 something but they need financing you know for whether it is in you know it's 914 00:51:49,440 --> 00:51:53,517 it's sort of some they're taking some exotic forms uh which obviously need to 915 00:51:53,600 --> 00:51:55,277 be scrutinized by the investment 916 00:51:55,360 --> 00:51:57,997 community but that said you know vendor 917 00:51:58,080 --> 00:52:02,477 financing is not a new concept interestingly enough we have not had to 918 00:52:02,560 --> 00:52:04,557 do any of that right I mean we may have 919 00:52:04,640 --> 00:52:07,357 you know really uh either invested in 920 00:52:07,440 --> 00:52:10,477 OpenAI and essentially got an equity uh 921 00:52:10,560 --> 00:52:13,357 stake in it for return for compute or 922 00:52:13,440 --> 00:52:17,997 essentially sold them great pricing of compute in order to be able to sort of 923 00:52:18,080 --> 00:52:22,397 bootstrap them. But you know others choose to do so differently and uh and I 924 00:52:22,480 --> 00:52:24,557 think circularity ultimately will be 925 00:52:24,640 --> 00:52:27,037 tested by demand because all this will 926 00:52:27,120 --> 00:52:29,917 work uh as long as there is demand for 927 00:52:30,000 --> 00:52:33,117 the final out output of it and up to now 928 00:52:33,200 --> 00:52:37,117 that has been the case. Certainly, certainly. Well, I want to shift uh you 929 00:52:37,200 --> 00:52:41,117 know, as you said, over half your business is software uh applications. 930 00:52:41,200 --> 00:52:44,477 You know, I want to think about software and agents. You know, last year on this 931 00:52:44,560 --> 00:52:49,437 pod, you made a bit of a stir by saying that much of application software, you 932 00:52:49,520 --> 00:52:51,277 know, was this thin layer that sat sat 933 00:52:51,360 --> 00:52:54,877 on top of a CRUD database. The notion 934 00:52:54,960 --> 00:52:59,757 that business applications exist, 935 00:52:59,840 --> 00:53:03,437 that's probably where they'll all collapse, right, in the agent era. 936 00:53:03,520 --> 00:53:04,797 Because if you think about it right, 937 00:53:04,880 --> 00:53:07,277 they are essentially 938 00:53:07,360 --> 00:53:10,717 crowd databases with a bunch of business 939 00:53:10,800 --> 00:53:12,237 logic. 940 00:53:12,320 --> 00:53:15,997 The business logic is all going to these 941 00:53:16,080 --> 00:53:18,637 agents. Public software companies are 942 00:53:18,720 --> 00:53:21,677 now trading at about 5.2 times forward 943 00:53:21,760 --> 00:53:25,917 revenue. So that's below their 10-year average of seven times despite the 944 00:53:26,000 --> 00:53:29,757 markets being at all-time highs. And there's lots of concern that SAS 945 00:53:29,840 --> 00:53:32,157 subscriptions and margins may be put at 946 00:53:32,240 --> 00:53:37,357 risk by AI. So how today is AI affecting 947 00:53:37,440 --> 00:53:41,517 the growth rates of your software products of you know those core products 948 00:53:41,600 --> 00:53:43,277 and specifically as you think about 949 00:53:43,360 --> 00:53:47,357 database fabric security office 360 and 950 00:53:47,440 --> 00:53:52,237 then second question I guess is what are you doing to make sure that software is 951 00:53:52,320 --> 00:53:56,957 not disrupted but is instead superpowered by AI? Yeah, I think that's 952 00:53:57,040 --> 00:54:01,437 a Yeah, that's right. So, the last time we talked about this, my my point really 953 00:54:01,520 --> 00:54:03,757 there was the architecture of SAS 954 00:54:03,840 --> 00:54:08,717 applications is changing because this agent tier is replacing the old business 955 00:54:08,800 --> 00:54:11,917 logic tier. And so, because if you think about it, the way we built SAS 956 00:54:12,000 --> 00:54:15,997 applications in the past was you had the data, the logic tier, and the UI all 957 00:54:16,080 --> 00:54:20,557 tightly coupled. Uh, and AI quite frankly doesn't respect that coupling 958 00:54:20,640 --> 00:54:25,437 because it requires you to be able to decouple. And yet the context 959 00:54:25,520 --> 00:54:28,237 engineering is going to be very important. I mean take you know 960 00:54:28,320 --> 00:54:30,477 something like uh office 365. One of the 961 00:54:30,560 --> 00:54:33,277 things I love about uh our Microsoft 365 962 00:54:33,360 --> 00:54:36,717 offering is it's low arpoo 963 00:54:36,800 --> 00:54:40,957 uh high usage right I mean if you think about it right outlook or teams or 964 00:54:41,040 --> 00:54:45,517 sharepoint you pick word or excel like people are using it all the time 965 00:54:45,600 --> 00:54:47,437 creating lots and lots of data which is 966 00:54:47,520 --> 00:54:50,077 going into the graph and our arpoo is 967 00:54:50,160 --> 00:54:52,717 low. So that's sort of what gives me 968 00:54:52,800 --> 00:54:56,237 real confidence that this AI tier with I 969 00:54:56,320 --> 00:54:59,597 can meet it by exposing all my data. In 970 00:54:59,680 --> 00:55:01,037 fact, one of the fascinating things 971 00:55:01,120 --> 00:55:03,917 that's happened uh Brad with both GitHub 972 00:55:04,000 --> 00:55:07,597 and Microsoft 365 is thanks to AI, we 973 00:55:07,680 --> 00:55:12,397 are seeing alltime highs in terms of data that's going into the graph or the 974 00:55:12,480 --> 00:55:14,797 repo. >> I mean think about it. The more code 975 00:55:14,880 --> 00:55:16,477 that gets generated, whether it is 976 00:55:16,560 --> 00:55:19,437 codeex or cloud or wherever, where is it 977 00:55:19,520 --> 00:55:24,477 going? GitHub, more PowerPoints that get created, Excel models that get created, 978 00:55:24,560 --> 00:55:26,317 all these artifacts and chat 979 00:55:26,400 --> 00:55:28,237 conversations. Chat conversations are 980 00:55:28,320 --> 00:55:31,597 new docs, they're all going in to the 981 00:55:31,680 --> 00:55:34,557 graph and and all that is needed again 982 00:55:34,640 --> 00:55:37,357 >> for grounding. Uh so that's what you 983 00:55:37,440 --> 00:55:39,517 know you turn it into a forward index 984 00:55:39,600 --> 00:55:42,077 into an embedding and basically that 985 00:55:42,160 --> 00:55:45,277 semantics is what you really go ground 986 00:55:45,360 --> 00:55:48,397 any agent request. And so I think the 987 00:55:48,480 --> 00:55:50,637 next generation of SAS applications will 988 00:55:50,720 --> 00:55:53,517 have to sort of if you are high RPO low 989 00:55:53,600 --> 00:55:55,837 usage then you have a little bit of a 990 00:55:55,920 --> 00:55:58,237 problem. But if you are we are the exact 991 00:55:58,320 --> 00:56:01,197 opposite. we are low RPO, high usage and 992 00:56:01,280 --> 00:56:05,917 I think that anyone who can structure that and then use this AI as in fact an 993 00:56:06,000 --> 00:56:10,637 accelerant because I mean like if you look at the M365 copilot price I mean 994 00:56:10,720 --> 00:56:12,637 it's higher than any other thing that we 995 00:56:12,720 --> 00:56:14,717 sell and yet it's getting deployed 996 00:56:14,800 --> 00:56:17,917 faster and with more usage and so I feel 997 00:56:18,000 --> 00:56:20,157 very good oh or coding right who would 998 00:56:20,240 --> 00:56:25,277 have thought in fact take GitHub right what GitHub did in first I don't know 15 999 00:56:25,360 --> 00:56:29,197 years of its existence or 10 years of its existence it was basically done in 1000 00:56:29,280 --> 00:56:31,277 the last year just because coding is no 1001 00:56:31,360 --> 00:56:34,717 longer a tool. It's more a substitute 1002 00:56:34,800 --> 00:56:39,517 for wages and so it's a very different type of business model even kind of 1003 00:56:39,600 --> 00:56:43,277 thinking about the stack and where value gets distributed. So until very 1004 00:56:43,360 --> 00:56:48,317 recently, right, clouds largely ran pre-ompiled software. You didn't need a 1005 00:56:48,400 --> 00:56:51,677 lot of GPUs and most of the value acrewed to the software layer to the 1006 00:56:51,760 --> 00:56:56,077 database to the applications like CRM and Excel. But it does seem in the 1007 00:56:56,160 --> 00:57:00,557 future that these interfaces will only be valuable, right? If they're if 1008 00:57:00,640 --> 00:57:03,837 they're uh intelligent, right? If they're pre-ompiled, they're kind of 1009 00:57:03,920 --> 00:57:05,917 dumb. The software's got to be able to 1010 00:57:06,000 --> 00:57:09,117 think and to act and to advise. And that 1011 00:57:09,200 --> 00:57:13,277 requires you know the production of these tokens you know dealing with the 1012 00:57:13,360 --> 00:57:17,677 everchanging context. And so in that world it does seem like much more of the 1013 00:57:17,760 --> 00:57:20,237 value will acrue to the AI factory if 1014 00:57:20,320 --> 00:57:23,917 you will to you know Jensen producing 1015 00:57:24,000 --> 00:57:25,837 you know uh helping to produce these 1016 00:57:25,920 --> 00:57:29,037 tokens at uh uh the lowest cost and to 1017 00:57:29,120 --> 00:57:33,197 the models and maybe that the agents or the software will acrue a little bit 1018 00:57:33,280 --> 00:57:36,957 less of the value in the future than they've accured in the in the past. 1019 00:57:37,040 --> 00:57:39,677 Well, steelman for me. Why that's wrong? 1020 00:57:39,760 --> 00:57:45,037 >> Yeah. So, I think there are two things that are necessary to try and to drive 1021 00:57:45,120 --> 00:57:48,077 the value of AI. One is what you described first, which is the token 1022 00:57:48,160 --> 00:57:51,917 factory. And even [clears throat] if you unpack the token factory, uh it's the 1023 00:57:52,000 --> 00:57:54,877 hardware silicon system, but then it is 1024 00:57:54,960 --> 00:57:57,837 about running it most efficiently with 1025 00:57:57,920 --> 00:57:59,837 the system software with all the 1026 00:57:59,920 --> 00:58:03,277 fungibility, max utilization. That's 1027 00:58:03,360 --> 00:58:05,277 where the hyperscaler's role is, right? 1028 00:58:05,360 --> 00:58:09,357 What is a hyperscaler? Is hyperscaler like everybody says if you sort of said 1029 00:58:09,440 --> 00:58:12,957 hey I want to run a hyperscaler. Yeah you could say oh it's simple. I'll buy a 1030 00:58:13,040 --> 00:58:16,237 bunch of servers and wire them up and run it. It's not that right. I mean it 1031 00:58:16,320 --> 00:58:19,197 was that simple then there would have been more than three hyperscalers by 1032 00:58:19,280 --> 00:58:22,397 now. So the hyperscaler is the knowhow 1033 00:58:22,480 --> 00:58:27,357 of running that max util and the token factories. And it's not and by the way 1034 00:58:27,440 --> 00:58:28,477 it's going to be heterogeneous. 1035 00:58:28,560 --> 00:58:30,397 Obviously Jensen's super competitive. 1036 00:58:30,480 --> 00:58:34,637 Lisa is going to come, you know, Hawk's going to produce things uh from 1037 00:58:34,720 --> 00:58:38,557 Broadcom. We will all do our own. So there's going to be a combination. So 1038 00:58:38,640 --> 00:58:40,237 you want to run ultimately a 1039 00:58:40,320 --> 00:58:43,357 heterogeneous fleet that is maximized 1040 00:58:43,440 --> 00:58:47,837 for token throughput and efficiency and so on. So that's kind of one job. The 1041 00:58:47,920 --> 00:58:49,997 next thing is what I call the agent 1042 00:58:50,080 --> 00:58:52,717 factory. Remember that a SAS application 1043 00:58:52,800 --> 00:58:54,877 in the modern world is driving a 1044 00:58:54,960 --> 00:58:58,077 business outcome. it knows how to most 1045 00:58:58,160 --> 00:59:01,517 efficiently use the tokens to create 1046 00:59:01,600 --> 00:59:06,077 some business value. Uh in fact, GitHub copilot is a great example of it, right? 1047 00:59:06,160 --> 00:59:10,317 Which is, you know, if you think about it, it the auto mode of GitHub copilot 1048 00:59:10,400 --> 00:59:12,157 is the smartest thing we've done, right? 1049 00:59:12,240 --> 00:59:15,197 So, it chooses based on the prompt which 1050 00:59:15,280 --> 00:59:18,317 model to use for a code completion or a 1051 00:59:18,400 --> 00:59:23,037 task handoff, right? That's what you and you do that not just by, you know, 1052 00:59:23,120 --> 00:59:27,117 choosing in some roundrobin fashion. You do it because of the feedback cycle. You 1053 00:59:27,200 --> 00:59:29,597 have you have the eval, the data loops 1054 00:59:29,680 --> 00:59:34,237 and so on. So the new SAS applications as you rightfully said are intelligent 1055 00:59:34,320 --> 00:59:36,477 applications that are optimized for a 1056 00:59:36,560 --> 00:59:39,357 set of evals and a set of outcomes that 1057 00:59:39,440 --> 00:59:41,837 then know how to use the token facto's 1058 00:59:41,920 --> 00:59:44,797 output most efficiently. Sometimes 1059 00:59:44,880 --> 00:59:47,437 latency matters, sometimes uh 1060 00:59:47,520 --> 00:59:49,437 performance matters and knowing how to 1061 00:59:49,520 --> 00:59:52,557 do that trade uh in a smart way is where 1062 00:59:52,640 --> 00:59:57,037 the SAS application value is. But overall it is going to be true that 1063 00:59:57,120 --> 01:00:01,197 there is a real marginal cost to software this time around. It was there 1064 01:00:01,280 --> 01:00:03,277 in the cloud era too when we were doing 1065 01:00:03,360 --> 01:00:08,397 you know CDROMs there wasn't much of a marginal cost you know with the cloud 1066 01:00:08,480 --> 01:00:11,757 there was and this time around it's a lot more and so therefore the business 1067 01:00:11,840 --> 01:00:16,077 models have to adjust and you have to do these optimizations for the agent 1068 01:00:16,160 --> 01:00:19,517 factory and the token factory separately. you have a big search 1069 01:00:19,600 --> 01:00:23,357 business that most people don't know about, you know, but it turns out that 1070 01:00:23,440 --> 01:00:26,237 that's probably one of the most profitable businesses in the history of 1071 01:00:26,320 --> 01:00:28,637 the world because people are running 1072 01:00:28,720 --> 01:00:30,477 lots of searches, billions of searches, 1073 01:00:30,560 --> 01:00:33,277 and the cost of completing a search if 1074 01:00:33,360 --> 01:00:37,837 you're Microsoft is many fractions of a penny, right? Doesn't cost very much to 1075 01:00:37,920 --> 01:00:40,237 complete a search, but the comparable 1076 01:00:40,320 --> 01:00:43,277 query or prompt stack today when when 1077 01:00:43,360 --> 01:00:45,597 you use a chatbot looks different, 1078 01:00:45,680 --> 01:00:49,037 right? So I guess the question is 1079 01:00:49,120 --> 01:00:51,357 assume similar levels of revenue in the 1080 01:00:51,440 --> 01:00:53,997 future for those two businesses, right? 1081 01:00:54,080 --> 01:00:56,077 Do you ever get to a point where kind of 1082 01:00:56,160 --> 01:00:59,117 that chat interaction has unit economics 1083 01:00:59,200 --> 01:01:01,917 that are as profitable as search? I 1084 01:01:02,000 --> 01:01:03,837 think that's a great point because see 1085 01:01:03,920 --> 01:01:07,837 search was pretty magical uh in terms of 1086 01:01:07,920 --> 01:01:11,437 its ad unit uh and its cost economics 1087 01:01:11,520 --> 01:01:13,997 because there was the index which was a 1088 01:01:14,080 --> 01:01:16,477 fixed cost that you could then amortize 1089 01:01:16,560 --> 01:01:19,037 in a much more efficient way 1090 01:01:19,120 --> 01:01:21,517 >> uh whereas this one you know each chat 1091 01:01:21,600 --> 01:01:26,157 uh to your point you have to burn a lot more GPU cycles uh both with the intent 1092 01:01:26,240 --> 01:01:30,157 and the retrieval so the economics are different so I think you do that's why I 1093 01:01:30,240 --> 01:01:34,077 think a lot of the early sort of economics of chat have been the premium 1094 01:01:34,160 --> 01:01:38,397 model and subscription on the even on the consumer side. So we are yet to 1095 01:01:38,480 --> 01:01:42,957 discover whether it's agentic commerce or whatever is the ad unit how it's 1096 01:01:43,040 --> 01:01:45,117 going to be litigated but at the same 1097 01:01:45,200 --> 01:01:47,837 time the fact that at this point you 1098 01:01:47,920 --> 01:01:51,357 know I kind of know in fact I use search 1099 01:01:51,440 --> 01:01:53,757 uh for very very specific navigational 1100 01:01:53,840 --> 01:01:56,477 queries I used to say I use it a lot for 1101 01:01:56,560 --> 01:01:59,197 commerce but that's also shifting to my 1102 01:01:59,280 --> 01:02:01,277 you know co-pilot like I look at the 1103 01:02:01,360 --> 01:02:05,757 co-pilot mode in edge and bing uh or 1104 01:02:05,840 --> 01:02:09,597 copilot now they're blend ending in. So I think that yes, I think there is going 1105 01:02:09,680 --> 01:02:13,837 to be a relitigation just like that we talked about the SAS disruption. We're 1106 01:02:13,920 --> 01:02:18,557 in the beginning of the cheese being a little moved in consumer economics of 1107 01:02:18,640 --> 01:02:22,077 that category, >> right? I I mean and given that it's the 1108 01:02:22,160 --> 01:02:25,757 multi-trillion dollar this this is the thing that's driven all the economics of 1109 01:02:25,840 --> 01:02:27,997 the internet, right? when you move the 1110 01:02:28,080 --> 01:02:30,877 economics of search for both you and 1111 01:02:30,960 --> 01:02:32,797 Google and it converges on something 1112 01:02:32,880 --> 01:02:35,037 that looks more like a personal agent, a 1113 01:02:35,120 --> 01:02:39,917 personal assistant chat. Um, you know, that could end up being much much bigger 1114 01:02:40,000 --> 01:02:43,757 in terms of the total value delivered to humanity, but the unit economics, you're 1115 01:02:43,840 --> 01:02:46,877 not just advertising this one time fixed index. 1116 01:02:46,960 --> 01:02:49,517 >> That's right. >> And so, that's right. I think that the 1117 01:02:49,600 --> 01:02:52,477 consumer could be worse. Yeah. the consumer category because you are 1118 01:02:52,560 --> 01:02:55,517 pulling a thread on something that I think a lot about right which is what 1119 01:02:55,600 --> 01:02:57,757 during these disruptions 1120 01:02:57,840 --> 01:02:59,757 you you kind of have to have a real 1121 01:02:59,840 --> 01:03:02,637 sense of where is is the what is the 1122 01:03:02,720 --> 01:03:05,517 category economics uh is it winner take 1123 01:03:05,600 --> 01:03:09,677 all um uh and both matter uh right the 1124 01:03:09,760 --> 01:03:13,277 the problem on consumer space always is 1125 01:03:13,360 --> 01:03:16,717 that there's finite amount of time uh 1126 01:03:16,800 --> 01:03:20,557 and so if I'm not doing one thing uh I'm 1127 01:03:20,640 --> 01:03:24,877 doing something else and if your monetization is predicated on some human 1128 01:03:24,960 --> 01:03:28,717 interaction in particular if there was truly agentic stuff even on consumer 1129 01:03:28,800 --> 01:03:32,637 that could be different. Uh whereas in the enterprise one is it's not winner 1130 01:03:32,720 --> 01:03:35,357 take all and two it is going to be a lot 1131 01:03:35,440 --> 01:03:38,157 more friendly for agentic interaction. 1132 01:03:38,240 --> 01:03:42,477 So it's not like for example the per seat versus consumption. The reality is 1133 01:03:42,560 --> 01:03:44,957 agents are the new seats. 1134 01:03:45,040 --> 01:03:47,437 >> And so you can think of it as uh the 1135 01:03:47,520 --> 01:03:50,157 enterprise monetization is much clearer. 1136 01:03:50,240 --> 01:03:53,997 The consumer monetization I think is a little more murky. You know, we've seen 1137 01:03:54,080 --> 01:03:58,157 a spade of layoffs recently with Amazon announcing some big big layoffs this 1138 01:03:58,240 --> 01:04:02,317 week. You know, the Mag 7 has had little job growth over the last three years 1139 01:04:02,400 --> 01:04:06,317 despite really robust top lines. You know, you didn't grow your headcount 1140 01:04:06,400 --> 01:04:10,557 really from 24 to 25. It's around 225,000. 1141 01:04:10,640 --> 01:04:14,317 You know, many attribute this to normal getting fit, you know, just getting more 1142 01:04:14,400 --> 01:04:17,997 efficient coming out of co and I think there's a lot of truth to that. But do 1143 01:04:18,080 --> 01:04:20,717 you think part of this is due to AI? Do 1144 01:04:20,800 --> 01:04:25,757 you think that AI is going to be a net job creator? And do you see this being a 1145 01:04:25,840 --> 01:04:27,517 long-term positive for Microsoft 1146 01:04:27,600 --> 01:04:30,077 productivity? Like it feels to me like 1147 01:04:30,160 --> 01:04:32,957 the pie grows, but you can do all these 1148 01:04:33,040 --> 01:04:35,117 things much more efficiently, which 1149 01:04:35,200 --> 01:04:38,477 either means you your margins expand or 1150 01:04:38,560 --> 01:04:42,557 it means you reinvest those margin dollars and you grow faster for longer. 1151 01:04:42,640 --> 01:04:44,157 I call it the golden age of margin 1152 01:04:44,240 --> 01:04:49,117 expansion. I'm a firm believer that the 1153 01:04:49,200 --> 01:04:52,637 the productivity curve does uh and will 1154 01:04:52,720 --> 01:04:55,677 bend in the sense that we will start 1155 01:04:55,760 --> 01:04:59,357 seeing some of what is the work and the 1156 01:04:59,440 --> 01:05:01,997 workflow in particular change, right? 1157 01:05:02,080 --> 01:05:05,917 there's going to be more agency for you 1158 01:05:06,000 --> 01:05:09,357 at a task level to get to job complete 1159 01:05:09,440 --> 01:05:12,157 because of the power of these tools uh 1160 01:05:12,240 --> 01:05:16,477 in your hand and that I think is going to be the case. So that's why I think we 1161 01:05:16,560 --> 01:05:20,557 are even internally for example when you talked about even our allocation of 1162 01:05:20,640 --> 01:05:22,717 tokens we want to make sure that 1163 01:05:22,800 --> 01:05:24,797 everybody at Microsoft standard issue 1164 01:05:24,880 --> 01:05:27,757 right all of them have Microsoft 365 to 1165 01:05:27,840 --> 01:05:30,397 the tilt in the sort of most un uh 1166 01:05:30,480 --> 01:05:35,037 limited way and have GitHub copilot so that they can really be more productive 1167 01:05:35,120 --> 01:05:36,637 but here is the other interesting thing 1168 01:05:36,720 --> 01:05:39,197 Brad we're learning is there is a new 1169 01:05:39,280 --> 01:05:42,157 way to even learn right which is you 1170 01:05:42,240 --> 01:05:46,637 know how to work with agents Right? So that's kind of like when the first when 1171 01:05:46,720 --> 01:05:48,557 word, excel, powerpoint all showed up in 1172 01:05:48,640 --> 01:05:54,077 office, you kind of we learned how to rethink let's say how we did a forecast, 1173 01:05:54,160 --> 01:05:57,277 right? Right? I mean, think about it, right? In the 80s, the forecasts were 1174 01:05:57,360 --> 01:06:01,677 inter office memos and faxes and what have you. And then suddenly somebody 1175 01:06:01,760 --> 01:06:03,277 said, "Oh, here's an Excel spreadsheet. 1176 01:06:03,360 --> 01:06:04,877 Let's put it an email. Send it around. 1177 01:06:04,960 --> 01:06:07,357 People enter numbers and there was a forecast." 1178 01:06:07,440 --> 01:06:10,237 >> Similarly, right now, any planning, any 1179 01:06:10,320 --> 01:06:13,117 execution starts with AI. You research 1180 01:06:13,200 --> 01:06:17,437 with AI. You think with AI, you share with your colleagues and what have you. 1181 01:06:17,520 --> 01:06:19,437 So, there's a new artifact being created 1182 01:06:19,520 --> 01:06:22,157 and a new workflow being created. And 1183 01:06:22,240 --> 01:06:25,437 that is the rate of the pace of change 1184 01:06:25,520 --> 01:06:29,757 of the business process that matches the 1185 01:06:29,840 --> 01:06:32,077 capability of AI. That's where the 1186 01:06:32,160 --> 01:06:37,357 productivity efficiencies come. And so organizations that can master that are 1187 01:06:37,440 --> 01:06:40,717 going to be the biggest beneficiaries whether it's in our industry or quite 1188 01:06:40,800 --> 01:06:44,877 frankly in the real world. >> And so is Microsoft benefiting from 1189 01:06:44,960 --> 01:06:48,397 that? You know, so let's let's think about a couple years from now. Five 1190 01:06:48,480 --> 01:06:52,237 years from now at the current growth rate will be sooner, but let's call it 1191 01:06:52,320 --> 01:06:56,077 five years from now, your top line is twice as big as what it is today. 1192 01:06:56,160 --> 01:06:59,677 Satcha, how many more employees will you have if you're if you're if you grow 1193 01:06:59,760 --> 01:07:02,717 revenue by >> like one of the best things right now is 1194 01:07:02,800 --> 01:07:06,557 these examples that I'm hit with every day from the employees of Microsoft. 1195 01:07:06,640 --> 01:07:10,317 There was this person who leads our network operations, right? I mean if you 1196 01:07:10,400 --> 01:07:12,637 think about the amount of uh fiber we 1197 01:07:12,720 --> 01:07:15,597 have had to put uh for like this you 1198 01:07:15,680 --> 01:07:17,677 know this 2 gawatt data center we just 1199 01:07:17,760 --> 01:07:20,717 built out uh in fair water right and the 1200 01:07:20,800 --> 01:07:25,517 amount of fiber there the AI and what have you it's just crazy right so 1201 01:07:25,600 --> 01:07:29,677 >> and it turns out this is a real world asset there are I think 400 different 1202 01:07:29,760 --> 01:07:33,277 fiber operators we're dealing with worldwide every time something happens 1203 01:07:33,360 --> 01:07:37,277 we are literally going and dealing with all these DevOps pipelines the person 1204 01:07:37,360 --> 01:07:41,357 who leads it she basically said to me you what I there's no way I'll ever get 1205 01:07:41,440 --> 01:07:44,957 the headcount to go do all this. Not forget even if I even approve the 1206 01:07:45,040 --> 01:07:49,117 budget. I can't hire all these folks. So she she did the next best thing. She 1207 01:07:49,200 --> 01:07:53,037 just built herself a whole bunch of agents to automate the DevOps pipeline 1208 01:07:53,120 --> 01:07:55,597 of how to deal with the maintenance. 1209 01:07:55,680 --> 01:07:59,357 That is an example of you to your point a team 1210 01:07:59,440 --> 01:08:02,397 >> with AI tools being able to get more 1211 01:08:02,480 --> 01:08:06,957 productivity. So in if you are question I will say we will grow a headcount but 1212 01:08:07,040 --> 01:08:11,277 the way I look at it is that headcount we grow will grow with a lot more 1213 01:08:11,360 --> 01:08:14,717 leverage than the headcount we had pre AI 1214 01:08:14,800 --> 01:08:18,317 >> and that's the adjustment I think structurally you're seeing first right 1215 01:08:18,400 --> 01:08:21,277 which is one you called it getting fit I 1216 01:08:21,360 --> 01:08:24,077 think of it as more getting to a place 1217 01:08:24,160 --> 01:08:27,757 where everybody is really not learning 1218 01:08:27,840 --> 01:08:30,317 how to rethink how they work and it's 1219 01:08:30,400 --> 01:08:33,037 the how not even the what even If the 1220 01:08:33,120 --> 01:08:35,437 what remains the constant, how you go 1221 01:08:35,520 --> 01:08:37,757 about it has to be relearned. And it's 1222 01:08:37,840 --> 01:08:40,077 the unlearning and learning process that 1223 01:08:40,160 --> 01:08:44,877 I think will take the next year or so, then the headcount growth will come with 1224 01:08:44,960 --> 01:08:49,357 max leverage. Yeah. No, it's a I think we're on the 1225 01:08:49,440 --> 01:08:53,597 verge of incredible economic productivity growth. It does feel like 1226 01:08:53,680 --> 01:08:57,837 when I talk to you or Michael Dell that most companies aren't even really in the 1227 01:08:57,920 --> 01:09:02,317 first inning, maybe the the first batter in the first inning in reworking those 1228 01:09:02,400 --> 01:09:06,397 workflows to get maximum leverage from these agents. But it sure feels like 1229 01:09:06,480 --> 01:09:09,357 over the course of the next two to three years, that's where a lot of gains are 1230 01:09:09,440 --> 01:09:13,757 going to start coming from. And again, I you know, I I certainly am an optimist. 1231 01:09:13,840 --> 01:09:17,677 I think we're going to have net job gains from all of this. But I think for 1232 01:09:17,760 --> 01:09:21,437 those companies, they'll just be able to grow their bottom line, their number of 1233 01:09:21,520 --> 01:09:23,517 employees slower than their top line. 1234 01:09:23,600 --> 01:09:27,357 That is the productivity gain to the company. Aggregate all that up. That's 1235 01:09:27,440 --> 01:09:29,517 the productivity gain to the economy. 1236 01:09:29,600 --> 01:09:33,277 And then we'll just take that consumer surplus and invest it in creating a lot 1237 01:09:33,360 --> 01:09:35,197 of things that didn't exist before. 1238 01:09:35,280 --> 01:09:39,037 >> 100%. 100%. Even in software development, right? One of the things I 1239 01:09:39,120 --> 01:09:42,157 look at it is no one would say we're 1240 01:09:42,240 --> 01:09:46,877 going to have a challenge in having, you know, more software engineers contribute 1241 01:09:46,960 --> 01:09:51,117 to our sort of society because the reality is you look at the IT backlog in 1242 01:09:51,200 --> 01:09:53,677 any organization. And so the question is 1243 01:09:53,760 --> 01:09:56,477 all these software agents are hopefully 1244 01:09:56,560 --> 01:09:59,357 going to help us go and take a whack at 1245 01:09:59,440 --> 01:10:02,557 all of the IT backlog we have and think 1246 01:10:02,640 --> 01:10:05,277 of that dream of evergreen software. 1247 01:10:05,360 --> 01:10:08,637 That's going to be true. and then think about the demand for software. So I 1248 01:10:08,720 --> 01:10:12,637 think that to your point it's the levels of abstraction at which knowledge work 1249 01:10:12,720 --> 01:10:14,717 happens will change. We will adjust to 1250 01:10:14,800 --> 01:10:19,757 that the work and the workflow that will then adjust itself even in terms of the 1251 01:10:19,840 --> 01:10:22,237 demand for the products of this industry. 1252 01:10:22,320 --> 01:10:26,237 >> I'm going to end on this which is really around the reindustrialization of 1253 01:10:26,320 --> 01:10:28,477 America. I've said if you add up the $4 1254 01:10:28,560 --> 01:10:31,837 trillion of capex that you and these and 1255 01:10:31,920 --> 01:10:36,157 and so many of of the big large US tech companies are investing over the course 1256 01:10:36,240 --> 01:10:39,837 of the next four or five years, it's about 10 times the size of the Manhattan 1257 01:10:39,920 --> 01:10:42,397 project on an inflation adjusted or GD 1258 01:10:42,480 --> 01:10:47,117 GDP adjusted basis. So it's a massive undertaking for America. The president 1259 01:10:47,200 --> 01:10:51,997 has made it a real priority of his administration to recut the trade deals 1260 01:10:52,080 --> 01:10:56,477 and it looks like we now have trillions of dollars. South Koreans committed $350 1261 01:10:56,560 --> 01:10:58,717 billion dollars of investments uh just 1262 01:10:58,800 --> 01:11:02,237 today into the United States. And when 1263 01:11:02,320 --> 01:11:04,717 you think about, you know, what you see 1264 01:11:04,800 --> 01:11:09,517 going on in power in the United States, both production, the grid, etc., what 1265 01:11:09,600 --> 01:11:13,357 you see going on in terms of this re-industrialization, 1266 01:11:13,440 --> 01:11:16,317 how how do you think this is all going? 1267 01:11:16,400 --> 01:11:20,957 and uh you you know maybe just reflect on where we're landing the plane here 1268 01:11:21,040 --> 01:11:24,717 and your level of optimism for the the the few years ahead. 1269 01:11:24,800 --> 01:11:28,077 >> Yeah. No, I I I feel very very optimistic because in some sense, you 1270 01:11:28,160 --> 01:11:30,157 know, Brad Smith was telling me about 1271 01:11:30,240 --> 01:11:35,197 sort of the economy around a Wisconsin data center. It's fascinating. Most 1272 01:11:35,280 --> 01:11:39,117 people think, oh, data center that is sort of like, yeah, uh it's going to be 1273 01:11:39,200 --> 01:11:41,117 one big warehouse and there's, you know, 1274 01:11:41,200 --> 01:11:43,837 fully automated. Uh a lot of it is true. 1275 01:11:43,920 --> 01:11:46,477 uh but first of all what went into the 1276 01:11:46,560 --> 01:11:49,517 construction uh of that data center and 1277 01:11:49,600 --> 01:11:54,477 the local supply chain of the data center uh that is in some sense the 1278 01:11:54,560 --> 01:11:59,117 reindustrialization of the United States as well uh even before you get to what 1279 01:11:59,200 --> 01:12:01,357 is happening in Arizona with the TSMC 1280 01:12:01,440 --> 01:12:03,997 plants or what was happening with Micron 1281 01:12:04,080 --> 01:12:06,877 and their investments in memory or Intel 1282 01:12:06,960 --> 01:12:08,797 and their fabs and what have you right 1283 01:12:08,880 --> 01:12:11,597 there's a lot of stuff that we will want 1284 01:12:11,680 --> 01:12:16,317 to start building doesn't mean we won't have trade deals that make sense for the 1285 01:12:16,400 --> 01:12:20,397 United States with other countries. But to your point, the reindustrialization 1286 01:12:20,480 --> 01:12:22,957 for the new economy and take making sure 1287 01:12:23,040 --> 01:12:25,437 that all the skills and all that 1288 01:12:25,520 --> 01:12:29,517 capacity from power on down, I think is 1289 01:12:29,600 --> 01:12:33,197 sort of very important right for us. And in and the other thing that I also say, 1290 01:12:33,280 --> 01:12:37,277 Brad, it's important and this is something that I've had a chance to talk 1291 01:12:37,360 --> 01:12:41,597 to President Trump as well as uh Secretary Lutnik and others is it's 1292 01:12:41,680 --> 01:12:45,517 important to recognize that we as hyperscalers of the United States are 1293 01:12:45,600 --> 01:12:48,477 also investing around the world. So in 1294 01:12:48,560 --> 01:12:51,037 other words, the United States is the 1295 01:12:51,120 --> 01:12:54,477 biggest investor of compute factories or 1296 01:12:54,560 --> 01:12:57,677 token factories uh around the world. But 1297 01:12:57,760 --> 01:13:01,597 not only are we attracting foreign capital to invest in our country so that 1298 01:13:01,680 --> 01:13:04,157 we can re-industrialize, we are helping 1299 01:13:04,240 --> 01:13:06,397 whether it's in Europe or in Asia or 1300 01:13:06,480 --> 01:13:09,197 elsewhere in Latin America and in Africa 1301 01:13:09,280 --> 01:13:11,997 with our capital investments, bringing 1302 01:13:12,080 --> 01:13:14,877 the best American tech uh to the world 1303 01:13:14,960 --> 01:13:19,437 that they can then innovate on and trust. And so both of those I think are 1304 01:13:19,520 --> 01:13:22,957 really bode well for the United States long term. 1305 01:13:23,040 --> 01:13:25,517 >> I'm grateful for your leadership Sam is 1306 01:13:25,600 --> 01:13:30,237 is is really helping lead the charge at open AI for America. I think this is a 1307 01:13:30,320 --> 01:13:34,637 moment where I look ahead, you know, you can see 4% GDP growth on the horizon. 1308 01:13:34,720 --> 01:13:37,437 We'll have our challenges. We'll have our ups and downs. These tend to be 1309 01:13:37,520 --> 01:13:41,677 stairs, you know, stairs up rather than a line straight up and to the right. But 1310 01:13:41,760 --> 01:13:46,317 I for one see a level of coordination going on between Washington and Silicon 1311 01:13:46,400 --> 01:13:50,237 Valley between big tech and the re-industrialization of America that 1312 01:13:50,320 --> 01:13:51,917 gives me cause for incredible hope. 1313 01:13:52,000 --> 01:13:54,317 Watching what happened this week in Asia 1314 01:13:54,400 --> 01:13:58,957 uh led by the president and his team and then watching what's happening here uh 1315 01:13:59,040 --> 01:14:03,677 is is super exciting. So thanks for making the time. We're big fans. Thanks. 1316 01:14:03,760 --> 01:14:05,277 Thanks Satcha. 1317 01:14:05,360 --> 01:14:09,387 >> Thanks so much Brad. Thank you. 1318 01:14:09,470 --> 01:14:11,490 [music] 1319 01:14:16,640 --> 01:14:22,320 As a reminder to everybody, just our opinions, not investment advice.