1 00:00:00,000 --> 00:00:04,077 I'm here with Dr. Alex Karp, CEO and co-founder of Palantir. Thank you for 2 00:00:04,160 --> 00:00:06,997 taking the time to do this. >> By the way, I always say this, it's you 3 00:00:07,080 --> 00:00:10,757 know, you were you we we've been together since the beginning of our life 4 00:00:10,840 --> 00:00:13,717 in the public markets. Um 5 00:00:13,800 --> 00:00:17,677 when we first uh DPO'd, um which is why 6 00:00:17,760 --> 00:00:21,397 so many people in America and across the world got to participate. But, you know, 7 00:00:21,480 --> 00:00:25,677 without you, you know, sending out missives about how we were 8 00:00:25,760 --> 00:00:28,997 misunderstood, you know, probably millions and millions 9 00:00:29,080 --> 00:00:31,237 of people would not have participated. 10 00:00:31,320 --> 00:00:36,117 Um and yeah, it's Palantir's this kind of crazy walled poster child company 11 00:00:36,200 --> 00:00:39,237 where people can only understand the Palantir 12 00:00:39,320 --> 00:00:42,757 of 5 years ago, not the Palantir that were we have. 13 00:00:42,840 --> 00:00:47,197 And so, you know, there was a lot of work to do on the, you know, front line. 14 00:00:47,280 --> 00:00:48,877 I'm happy to have you with us. 15 00:00:48,960 --> 00:00:53,277 >> So, 6 years ago, you went on CNBC the day you guys did DPO, and I think a lot 16 00:00:53,360 --> 00:00:55,757 of people didn't really understand what you were saying. 17 00:00:55,840 --> 00:00:57,677 About 2 weeks ago, you also went on 18 00:00:57,760 --> 00:01:00,477 CNBC, and I think you changed in about 19 00:01:00,560 --> 00:01:05,117 20 minutes the entire valley's approach to thinking about front-end models 20 00:01:05,200 --> 00:01:09,677 versus open-source models. So, quite simply, why is open source so important 21 00:01:09,760 --> 00:01:12,397 for Palantir? >> Well, it 22 00:01:12,480 --> 00:01:14,077 what happened, by the way, that was like 23 00:01:14,160 --> 00:01:16,837 it was a revolution. It began with like 24 00:01:16,920 --> 00:01:19,677 work we were doing with Nvidia, and then 25 00:01:19,760 --> 00:01:23,277 going on um on on on television like 26 00:01:23,360 --> 00:01:27,077 that, it just exploded in a way no one could 27 00:01:27,160 --> 00:01:31,797 have really predicted. I think the explosion happened because 28 00:01:31,880 --> 00:01:35,997 you know, people are being sold this thing they know isn't quite true, like 29 00:01:36,080 --> 00:01:39,677 you know, and then then they paid a price. You're paying, you know, a lot of 30 00:01:39,760 --> 00:01:43,037 money if you're enterprise for for tokens that are 31 00:01:43,120 --> 00:01:45,077 really it's hard to see the value. And 32 00:01:45,160 --> 00:01:47,917 then you realize at the same time the 33 00:01:48,000 --> 00:01:50,317 alpha of your business is migrating to 34 00:01:50,400 --> 00:01:52,277 the person you're paying an absurd sum 35 00:01:52,360 --> 00:01:55,477 of money based on value. And then, last 36 00:01:55,560 --> 00:02:00,357 and least, they're just behaving in the public sphere in a way that is blowing 37 00:02:00,440 --> 00:02:04,637 up the politics of America, making people 38 00:02:04,720 --> 00:02:07,077 really afraid, leading to people just 39 00:02:07,160 --> 00:02:11,917 wanting to pillory wealthy people but not help poor people. And you're sitting 40 00:02:12,000 --> 00:02:15,397 there and saying you're basically like, "What is going on here?" 41 00:02:15,480 --> 00:02:18,477 >> Right. >> So, you have that backdrop. Then, you 42 00:02:18,560 --> 00:02:21,717 have And by the way, part of the reason for that backdrop, just to make this a 43 00:02:21,800 --> 00:02:24,317 little longer, is these models are 44 00:02:24,400 --> 00:02:26,717 excruciatingly effective 45 00:02:26,800 --> 00:02:29,397 when used with an application layer. 46 00:02:29,480 --> 00:02:32,397 Now, they all know that. When you use it 47 00:02:32,480 --> 00:02:35,357 in application layer installed 48 00:02:35,440 --> 00:02:39,757 with what everyone's now copying from us called FDAs for X. So, 49 00:02:39,840 --> 00:02:43,117 then I think part of the reason this revolution actually happened is 50 00:02:43,200 --> 00:02:47,877 technical participants in the market know one thing. 51 00:02:47,960 --> 00:02:51,677 Palantir gets it right. You think they're crazy. You think 52 00:02:51,760 --> 00:02:54,757 they're insane. Carp is obnoxious. 53 00:02:54,840 --> 00:02:56,757 And then it turns out you have to copy him. 54 00:02:56,840 --> 00:03:01,077 Right? So, now, investors who are kind of just chillaxing in front of their 55 00:03:01,160 --> 00:03:05,437 screen producing AI slop on their computer and thinking I'm going to get 56 00:03:05,520 --> 00:03:09,037 rich and yeah, maybe core people, no one else is going to get rich. They're like, 57 00:03:09,120 --> 00:03:11,797 "Yeah, but that's just how the world works. You're good for me." They've been 58 00:03:11,880 --> 00:03:16,157 a little bit tone deaf to the technical thing. So, they're very happy to watch 59 00:03:16,240 --> 00:03:19,597 the the the like the frontier. By the way, I always feel like I have to say 60 00:03:19,680 --> 00:03:22,157 this. You know, >> Yeah, people think you hate the frontier 61 00:03:22,240 --> 00:03:23,677 laughs. I don't think that's your point. 62 00:03:23,760 --> 00:03:26,317 I think your argument is >> Well, people actually think I'm I'm 63 00:03:26,400 --> 00:03:30,477 going I'm like I'm kind of not being like I spend 64 00:03:30,560 --> 00:03:34,797 more time defending Dario and more effectively, honestly, cuz they don't 65 00:03:34,880 --> 00:03:38,877 even talk to like if you're telling them the truth about what you think, they 66 00:03:38,960 --> 00:03:43,077 don't talk to you, apparently. Because like the views there you know, and like 67 00:03:43,160 --> 00:03:46,797 I'm always trying to explain to you, you know, it's a worldview. This is a 68 00:03:46,880 --> 00:03:49,117 essentially a world historic figure. He 69 00:03:49,200 --> 00:03:53,397 He really did take the LM revolution, 70 00:03:53,480 --> 00:03:57,397 bring it to enterprise in a way where everyone found out something is going to 71 00:03:57,480 --> 00:04:01,917 be real. Now, of course, they don't talk very much about almost all the values 72 00:04:02,000 --> 00:04:05,837 being created in ontology with their models where they're doing good. 73 00:04:05,920 --> 00:04:09,957 >> Um so let's get into that discussion because 2 years ago you made it very 74 00:04:10,040 --> 00:04:13,637 clear to everybody that the models would be commoditized. The frontier labs have 75 00:04:13,720 --> 00:04:16,397 gotten better and better and better, but with the rise of open source, which I 76 00:04:16,480 --> 00:04:19,117 think is kind of in your point and video's point, the cost of tokens is 77 00:04:19,200 --> 00:04:22,677 coming down. Which means the application layer, something that processes, 78 00:04:22,760 --> 00:04:25,077 orchestrates, governs the tokens is becoming more powerful. 79 00:04:25,160 --> 00:04:29,517 >> You know, you would need compute so that Nvidia primarily 80 00:04:29,600 --> 00:04:32,957 um and we're very strongly partnered with them. You you would need an 81 00:04:33,040 --> 00:04:36,797 application layer because that while the and you need a way of installing them. 82 00:04:36,880 --> 00:04:40,637 So, you need FTEs, you need an application layer, people generally call 83 00:04:40,720 --> 00:04:43,557 that an ontology now after maligning it everywhere 84 00:04:43,640 --> 00:04:47,837 uh because they you need to do it's and there's two points. Simply put, there's 85 00:04:47,920 --> 00:04:51,357 safety. So, you know, we've now we're now helping 86 00:04:51,440 --> 00:04:54,597 people and I think people are aware of the dangers of just, you know, like 87 00:04:54,680 --> 00:04:58,317 look, they you know, a lot of our clients are running around saying no no 88 00:04:58,400 --> 00:05:02,877 ontology, no love meaning no glove, no love. So, like it's probably not exactly 89 00:05:02,960 --> 00:05:05,397 what I can say on TV, but >> It's a famous last word. 90 00:05:05,480 --> 00:05:08,917 >> It's like they're like, yeah, they're like, "Hey, look, no ontology, no love." 91 00:05:09,000 --> 00:05:12,637 It's like it's like it's like gone it's gone viral in corporate America. It's 92 00:05:12,720 --> 00:05:16,397 like it's crazy. It's like it's so there's like but there's a safety 93 00:05:16,480 --> 00:05:20,037 function like if you're meeting someone you don't know 94 00:05:20,120 --> 00:05:24,997 and who may have a history of doing things and leaving certain products 95 00:05:25,080 --> 00:05:29,637 behind that you know, you can't get rid of, you probably be insane not to have 96 00:05:29,720 --> 00:05:33,517 ontology protecting you. So, that is the safety function 97 00:05:33,600 --> 00:05:36,877 and that's that so that that's crazy important. By the way, with models 98 00:05:36,960 --> 00:05:39,477 coming from the whole world, that safety function is going to be even more 99 00:05:39,560 --> 00:05:42,397 important. But in the end of the day, 100 00:05:42,480 --> 00:05:46,917 businesses need to expand their tribal knowledge, their alpha while protecting 101 00:05:47,000 --> 00:05:50,557 it. And so, then there's another term which is now being adopted essentially 102 00:05:50,640 --> 00:05:54,717 the orchestration. How do you actually deploy the models so that they can do 103 00:05:54,800 --> 00:05:59,437 exactly what they're capable of doing while not not providing like chillaxing 104 00:05:59,520 --> 00:06:03,717 swap? Uh so, you get >> Why is open source plus the ontology so 105 00:06:03,800 --> 00:06:07,237 important for orchestration? >> Okay. Well, within the Well, first of all, it's 106 00:06:07,320 --> 00:06:11,997 because that's where you get the maximum convergence between pro safety because 107 00:06:12,080 --> 00:06:16,917 you the open source model is is is not aspiring in any way, obviously, to 108 00:06:17,000 --> 00:06:20,237 export although you do have our, you know, whatever protective layer 109 00:06:20,320 --> 00:06:24,357 probably. So, um >> That data is not going back to Frontier Labs. 110 00:06:24,440 --> 00:06:28,837 >> So, it's essentially but then you also the it allows you to fine-tune the 111 00:06:28,920 --> 00:06:33,437 model. The fine-tuning is very hard to do without dealing with the Frontier 112 00:06:33,520 --> 00:06:37,237 Lab. And when you're fine-tuning, you're basically exploiting what is the alpha 113 00:06:37,320 --> 00:06:39,997 you're trying to create on top of the alpha that's deep in your business. What 114 00:06:40,080 --> 00:06:42,597 is the context of your enter >> What is the context of your enterprise? 115 00:06:42,680 --> 00:06:44,917 What is a specialized problem 116 00:06:45,000 --> 00:06:47,117 >> sets embedded in your data that you have 117 00:06:47,200 --> 00:06:51,757 a unique lever and insight into way of solving. So, if you're building, I don't 118 00:06:51,840 --> 00:06:55,757 know, you're building a drug to reduce the chance of cancer, like you are 119 00:06:55,840 --> 00:06:59,597 actually building it on proprietary data and proprietary insights on how the 120 00:06:59,680 --> 00:07:03,757 human body works. >> Right. >> Right. And that like so, or you know, in 121 00:07:03,840 --> 00:07:09,077 Battlefield's obvious, but every single enterprise that is actually valuable. 122 00:07:09,160 --> 00:07:10,477 Like how do you define an enterprise 123 00:07:10,560 --> 00:07:13,397 that's valued? It has a specialized way 124 00:07:13,480 --> 00:07:17,157 of doing something a consumer wants or 125 00:07:17,240 --> 00:07:21,397 in the government context has a specialized way of doing something that 126 00:07:21,480 --> 00:07:25,517 the end user does not want that protects your people from the end user. 127 00:07:25,600 --> 00:07:27,757 Like this so, that's like this is so, 128 00:07:27,840 --> 00:07:30,997 that that to do that most efficiently, 129 00:07:31,080 --> 00:07:34,717 you would need compute uh ontology both 130 00:07:34,800 --> 00:07:39,637 protective and alpha augmenting and creating. And you need to make sure it 131 00:07:39,720 --> 00:07:43,597 doesn't transfer you that own those weights yourself. So, this by the way, 132 00:07:43,680 --> 00:07:47,717 this is not speculative. We we've seen this already in the US government 133 00:07:47,800 --> 00:07:52,597 context where in context that is very very hard to use frontier labs or where 134 00:07:52,680 --> 00:07:54,437 there are other quite firm. I don't 135 00:07:54,520 --> 00:07:56,677 understand this. I'm willing to go like 136 00:07:56,760 --> 00:08:00,437 By the way, in what world does the 137 00:08:00,520 --> 00:08:04,717 Department of War, the only institution in America that is extremely high 138 00:08:04,800 --> 00:08:07,997 credibility, the institution that integrated before anyone else, that 139 00:08:08,080 --> 00:08:11,317 protects us every day, that protects, that allows us it to export our 140 00:08:11,400 --> 00:08:16,117 technology, in what world are we outsourcing the moral veracity of that 141 00:08:16,200 --> 00:08:19,917 to a bunch of people sitting very far away who do and they're even met a man 142 00:08:20,000 --> 00:08:23,477 or woman in uniform and it's presumably don't care if they come home alive at 143 00:08:23,560 --> 00:08:26,437 least in practice. So, there's also like 144 00:08:26,520 --> 00:08:30,997 who makes these decisions? By the way, Palantir we've always been part of the 145 00:08:31,080 --> 00:08:32,277 reason the sovereignty thing actually 146 00:08:32,360 --> 00:08:34,997 works is technical users know for 147 00:08:35,080 --> 00:08:39,357 whether it was PG, Foundry, Ontology, Maven, 148 00:08:39,440 --> 00:08:41,637 uh now sovereign AI, we've always been 149 00:08:41,720 --> 00:08:43,997 on the side of protecting individual 150 00:08:44,080 --> 00:08:46,437 rights, protecting data, and protecting 151 00:08:46,520 --> 00:08:49,117 by logical extension your sovereignty. 152 00:08:49,200 --> 00:08:51,717 So, that like we that that's actually 153 00:08:51,800 --> 00:08:56,597 where we should all be as a country and as a tech community. And then 154 00:08:56,680 --> 00:08:59,597 there's the reason though that this ended up being 155 00:08:59,680 --> 00:09:04,717 you know, now I should say I'm wildly happy you have a lot of people entering 156 00:09:04,800 --> 00:09:08,237 and taking, you know, cuz this is actually where it should be and we don't 157 00:09:08,320 --> 00:09:11,997 like just cuz we basically are have been at the forefront of launching many of 158 00:09:12,080 --> 00:09:13,477 these revolutions and it's commonly 159 00:09:13,560 --> 00:09:16,077 known in tech in technical circles that 160 00:09:16,160 --> 00:09:19,077 we do this well. Um you know, building a 161 00:09:19,160 --> 00:09:21,077 broad The reason you see this broad 162 00:09:21,160 --> 00:09:24,877 phalanx of a coalition is the customers 163 00:09:24,960 --> 00:09:28,837 this is what they want and need. They are livid at the option that was 164 00:09:28,920 --> 00:09:33,437 provided and this this way of doing things. In fact, currently the biggest 165 00:09:33,520 --> 00:09:36,357 problem at Palantir is just how do we scale this? 166 00:09:36,440 --> 00:09:39,477 >> So, so what is but there's a lot of customers here. By the way, the 167 00:09:39,560 --> 00:09:43,597 backstory here because of this is you get the backstory. 168 00:09:43,680 --> 00:09:47,877 >> Like usually it two three years ago playing AIP like >> Oh, I remember. 169 00:09:47,960 --> 00:09:50,357 >> Like playing AIP >> This was like, "Hey, we're doing 170 00:09:50,440 --> 00:09:53,797 something really cool. Let's just invite people." And 171 00:09:53,880 --> 00:09:56,237 I mean like but but and look at the people out there. 172 00:09:56,320 --> 00:09:58,197 >> Yeah. >> It's like they care. They they care. 173 00:09:58,280 --> 00:10:01,997 It's like they want to learn. We are actually partnering with them. They're 174 00:10:02,080 --> 00:10:05,917 from every part of industry. They're the among the most important industries in 175 00:10:06,000 --> 00:10:08,277 the world. >> So, so what has the customer respond? 176 00:10:08,360 --> 00:10:11,557 You're on the front lines with customers every day. What is their response been? 177 00:10:11,640 --> 00:10:14,517 >> I say Well, it's it's um it's it the 178 00:10:14,600 --> 00:10:16,437 response to I would say the open source 179 00:10:16,520 --> 00:10:19,837 as a part of the sovereign narrative is 180 00:10:19,920 --> 00:10:23,037 a colossal It is what It's not only what 181 00:10:23,120 --> 00:10:25,917 they want and need. It's like Imagine 182 00:10:26,000 --> 00:10:30,357 again if someone is you're using this thing you just have a bad feeling. 183 00:10:30,440 --> 00:10:34,837 And then And now like now you understand why you have this deep bad feeling and 184 00:10:34,920 --> 00:10:36,797 and honestly in many cases that's where 185 00:10:36,880 --> 00:10:40,517 I end up defending uh there's anger. So 186 00:10:40,600 --> 00:10:43,877 now it's like there's like a valve release. The problem we have as a 187 00:10:43,960 --> 00:10:48,797 company is how do we stay very focused like we're going to We just have to I 188 00:10:48,880 --> 00:10:51,157 get calls from all over the world. I'm like 189 00:10:51,240 --> 00:10:53,517 "Can you come to my office?" Like we 190 00:10:53,600 --> 00:10:55,837 We're just like we we're we're 191 00:10:55,920 --> 00:10:58,917 rebuilding internal dynamics a lot here. 192 00:10:59,000 --> 00:11:03,517 Uh rebuilding infrastructure, you know, this sovereign AIP like requires us to 193 00:11:03,600 --> 00:11:07,397 build out certain parts of mythology, to build out our ability to fine-tune 194 00:11:07,480 --> 00:11:10,477 models, to service a demand both in the 195 00:11:10,560 --> 00:11:15,557 US government and in US commercial uh that we can't really fulfill. We're also 196 00:11:15,640 --> 00:11:16,997 doing a lot of educational stuff. 197 00:11:17,080 --> 00:11:19,397 >> Yeah. >> It's Speaking of education, one thing 198 00:11:19,480 --> 00:11:22,157 that is I've heard a lot is a lot of these open source models are coming from 199 00:11:22,240 --> 00:11:25,877 China. And somehow they're like, "How is Palantir endorsing China?" Can you give 200 00:11:25,960 --> 00:11:29,157 a response? >> endorsing we're endorsing what what 201 00:11:29,240 --> 00:11:33,717 Well, first of all, we obviously are I mean very pro-American. You see we're 202 00:11:33,800 --> 00:11:38,477 partnered with Nvidia, a great American company. Um, the way Look, there's a 203 00:11:38,560 --> 00:11:41,197 there's a template of how not to do this. 204 00:11:41,280 --> 00:11:43,437 >> Yeah. >> It's called Europe. 205 00:11:43,520 --> 00:11:47,517 Europe basically tries to close its borders. I mean, there are all sorts of 206 00:11:47,600 --> 00:11:51,797 reasons how they It doesn't now put this way, but de facto, they're closing their 207 00:11:51,880 --> 00:11:55,877 board trying to close their borders to US tech, right? That The problem with 208 00:11:55,960 --> 00:11:59,517 that, leaving everything else aside, is they're screwing European tech. 209 00:11:59,600 --> 00:11:59,957 >> Mhm. 210 00:12:00,040 --> 00:12:03,597 >> You must be able to compete. Like, we I 211 00:12:03,680 --> 00:12:06,597 believe that we will we can deliver. 212 00:12:06,680 --> 00:12:10,557 I've seen this I in practice frontier 213 00:12:10,640 --> 00:12:14,317 surpassing uh alpha creation. 214 00:12:14,400 --> 00:12:17,717 Where we're honest about what models do and don't do safely. 215 00:12:17,800 --> 00:12:21,077 >> Correct. >> Right? And that's being done with a completely American stack. 216 00:12:21,160 --> 00:12:23,877 >> Which means you can download the open-source models, no matter where they 217 00:12:23,960 --> 00:12:27,477 were created, but run them locally, which fundamentally changes the game. 218 00:12:27,560 --> 00:12:32,877 >> I Yes, but I mainly we have a strong preference for American models. Some of 219 00:12:32,960 --> 00:12:36,517 our clients use models from all over the world, including China. 220 00:12:36,600 --> 00:12:40,957 I do believe if you're using any of these models, you know, I mean, I I I 221 00:12:41,040 --> 00:12:45,517 this the I can't go and disseminate, you know, no no Palantir, no no ontology, no 222 00:12:45,600 --> 00:12:49,397 love, because it may be not be right for the TV audiences, although who knows 223 00:12:49,480 --> 00:12:53,877 what I'll do. But um but yeah, it's going to put obviously it creates great 224 00:12:53,960 --> 00:12:56,957 demand for our products. So, since I don't want to be out there like I I'm 225 00:12:57,040 --> 00:13:01,437 cognizant of how this like is going to help us, obviously. But But But But But 226 00:13:01,520 --> 00:13:03,837 again, you you have to be very careful. 227 00:13:03,920 --> 00:13:07,477 Like, you can we should obviously scrutinize all models. There needs to be 228 00:13:07,560 --> 00:13:12,117 better oversight, no doubt. All models. But you do not want to do, 229 00:13:12,200 --> 00:13:16,237 if you do this, what Europe is trying to do, what you get are weak companies that 230 00:13:16,320 --> 00:13:17,837 nobody actually believes can compete. 231 00:13:17,920 --> 00:13:20,797 And that's So, you're screwing the people you're trying to help. You know, 232 00:13:20,880 --> 00:13:22,837 business is a weird thing. You can you 233 00:13:22,920 --> 00:13:25,557 can nudge, you can have preferences. If 234 00:13:25,640 --> 00:13:30,597 you do overt like that level without without being able to show something, 235 00:13:30,680 --> 00:13:34,397 you end up with industry that is and America is the dominant player in the 236 00:13:34,480 --> 00:13:38,517 world. Um, and so I think this will force a lot of honesty 237 00:13:38,600 --> 00:13:41,277 because if you are doing compute 238 00:13:41,360 --> 00:13:44,797 ontology, uh, actual product-based and 239 00:13:44,880 --> 00:13:48,797 technical orchestration of and FTEs 240 00:13:48,880 --> 00:13:50,877 with open model models, open way models, 241 00:13:50,960 --> 00:13:55,957 that's that is by far the best thing on the market. And yeah, the other things 242 00:13:56,040 --> 00:13:59,597 are, you know, so yeah, it's it's it's going to be very good for America and I 243 00:13:59,680 --> 00:14:02,077 don't think it's going to be I think it might actually be pretty good for 244 00:14:02,160 --> 00:14:04,517 Palantir, too. >> Last question for you, Dr. Karp. Again, 245 00:14:04,600 --> 00:14:08,637 thank you for taking time. Uh, a lot of people are wondering, is there actually 246 00:14:08,720 --> 00:14:11,517 going to be a light at the end of the tunnel when it comes to this entire AI 247 00:14:11,600 --> 00:14:16,557 revolution? Put broadly, what does it mean to be a 248 00:14:16,640 --> 00:14:21,117 enterprise software company that actually delivers value in the age of AI? 249 00:14:21,200 --> 00:14:23,757 >> Oh, you mean what does it mean to be Palantir? 250 00:14:23,840 --> 00:14:26,677 Uh, look, >> Well, we're we're It's a better way to put it. 251 00:14:26,760 --> 00:14:30,557 >> we're we're we're we're Palantir is at the way 252 00:14:30,640 --> 00:14:34,717 beginning of a revolution. Like I was I was just uh, two two years ago we're 253 00:14:34,800 --> 00:14:38,357 sitting here, we have an offsite, people are like, "Tell me something you believe 254 00:14:38,440 --> 00:14:40,557 and no one else believes." And like, we're obviously going to be a 255 00:14:40,640 --> 00:14:44,157 trillion-dollar company. Now, I think 256 00:14:44,240 --> 00:14:49,757 we're at the way beginning of a massive massive opportunity and there is no, 257 00:14:49,840 --> 00:14:53,117 like, it's very hard to know what the end point is, but I can tell you 258 00:14:53,200 --> 00:14:58,157 I can see American industry just accelerating forward and I think 259 00:14:58,240 --> 00:15:00,997 Palantir is going to play a disproportionate role in that simply 260 00:15:01,080 --> 00:15:04,837 because you can kind of fake like you've done 261 00:15:04,920 --> 00:15:08,957 these things before FDA application layer. 262 00:15:09,040 --> 00:15:11,637 >> Uh, terms that everyone start using now. 263 00:15:11,720 --> 00:15:15,277 >> It's like, but it it is yeah, but it First of all, it's it's it's the 264 00:15:15,360 --> 00:15:17,637 orchestration of all these things at the same time. 265 00:15:17,720 --> 00:15:19,677 >> Which is art. >> It's art It's much more art than 266 00:15:19,760 --> 00:15:22,637 science. You also you need deep access 267 00:15:22,720 --> 00:15:27,197 to these data sets and it working you need a knowledge of how to work within 268 00:15:27,280 --> 00:15:30,917 these institutions to expand them. They have to have seen your products actually 269 00:15:31,000 --> 00:15:33,757 work. Also, the software concept concept 270 00:15:33,840 --> 00:15:36,717 is very broad like it includes AI slop. 271 00:15:36,800 --> 00:15:39,837 It includes things that are obviously going to be replaced and then it 272 00:15:39,920 --> 00:15:43,797 includes things that like most of what Palantir does which are like essentially 273 00:15:43,880 --> 00:15:45,437 like primitive they're more like 274 00:15:45,520 --> 00:15:48,197 infrastructure you need to do to enhance 275 00:15:48,280 --> 00:15:51,117 what these things do and again, you 276 00:15:51,200 --> 00:15:54,117 know, the the demand for what we we do 277 00:15:54,200 --> 00:16:00,040 is beyond what we can supply. >> Thank you. Thank you. Thank you.