WEBVTT 00:00:00.000 --> 00:00:03.837 I want to talk about AI and I would really want to because I think this is 00:00:03.920 --> 00:00:06.237 on everybody's mind more than almost any 00:00:06.320 --> 00:00:10.397 other subject today um related to 00:00:10.480 --> 00:00:11.037 intersection [clears throat] 00:00:11.120 --> 00:00:13.437 of business technology 00:00:13.520 --> 00:00:17.757 society um so Satia um 00:00:17.840 --> 00:00:21.517 you know we're we're moving AI from something that was experimental 00:00:21.600 --> 00:00:23.437 something that we always talked about in 00:00:23.520 --> 00:00:28.397 the future and now it's it's today um 00:00:28.480 --> 00:00:31.997 and it's now more foundational and it's 00:00:32.080 --> 00:00:36.237 not just foundational for companies but it it really is becoming now 00:00:36.320 --> 00:00:38.717 foundational 00:00:38.800 --> 00:00:42.557 for countries and throughout society and 00:00:42.640 --> 00:00:45.197 I think you know you have an advantage 00:00:45.280 --> 00:00:47.517 over so many other people you know being 00:00:47.600 --> 00:00:49.597 at the forefront of this technology 00:00:49.680 --> 00:00:53.837 transition. Um so um with that I wanted 00:00:53.920 --> 00:00:57.517 to ask a few questions related to that 00:00:57.600 --> 00:00:59.757 you have described that AI is a plat 00:00:59.840 --> 00:01:02.637 plat uh platform shift 00:01:02.720 --> 00:01:04.797 and what does what does that mean 00:01:04.880 --> 00:01:07.837 question one where do you see that shift 00:01:07.920 --> 00:01:12.077 going in the next few years and importantly the third part of my 00:01:12.160 --> 00:01:16.397 question would be fast forwarding a few years five years 00:01:16.480 --> 00:01:21.357 what's going to seem obvious in hindsight that feels less clear today. 00:01:21.440 --> 00:01:24.237 You >> know, first of all, um it's great uh to 00:01:24.320 --> 00:01:27.597 be back here, uh Larry, and it's um I 00:01:27.680 --> 00:01:31.277 had a chance, in fact, yesterday when you put out the letter [clears throat] 00:01:31.360 --> 00:01:34.557 uh to kick off the forum and read it and 00:01:34.640 --> 00:01:37.277 um and in there you sort of had this one 00:01:37.360 --> 00:01:41.437 line of uh really I think when it comes 00:01:41.520 --> 00:01:43.757 to AI, the real question in front of all 00:01:43.840 --> 00:01:48.477 of us is how do you ensure that the diffusion of AI happens and happens 00:01:48.560 --> 00:01:52.797 fast? I mean I think you had that line of how do the models, the data and the 00:01:52.880 --> 00:01:56.637 infrastructure spread more evenly to create surplus 00:01:56.720 --> 00:01:58.317 everywhere. If you sort of think about 00:01:58.400 --> 00:02:02.077 it, the the way I come at this is not 00:02:02.160 --> 00:02:05.837 that um this has always been the arc of 00:02:05.920 --> 00:02:10.317 computation, right? You can sort of take it in the last 30 years or the last 70 00:02:10.400 --> 00:02:12.557 years. It's always been about can you 00:02:12.640 --> 00:02:14.077 digitize 00:02:14.160 --> 00:02:17.997 artifacts on about people, places, and 00:02:18.080 --> 00:02:22.157 things and then build analytical and 00:02:22.240 --> 00:02:23.517 predictive [clears throat] power. Right? 00:02:23.600 --> 00:02:28.237 That's what the mainframes did. That's what the mini computer did. That's what 00:02:28.320 --> 00:02:32.397 the client server error did. That's what the web error did. The mobile cloud 00:02:32.480 --> 00:02:34.637 error did. So it like it depend 00:02:34.720 --> 00:02:37.757 irrespective of which paradigm or 00:02:37.840 --> 00:02:41.677 platform. It has been one continuous arc 00:02:41.760 --> 00:02:44.957 of saying let's make better sense of 00:02:45.040 --> 00:02:46.877 this world 00:02:46.960 --> 00:02:51.597 um by reasoning about it in digital form 00:02:51.680 --> 00:02:56.477 because in some sense once you have these artifacts in digital form you can 00:02:56.560 --> 00:02:59.357 use a more malleable resource like software 00:02:59.440 --> 00:03:05.287 >> right >> um which doesn't have the same type of you know I'll call it 00:03:05.370 --> 00:03:08.317 >> [clears throat] >> um marginal cost economics associated 00:03:08.400 --> 00:03:10.797 ated with it that allows us to then 00:03:10.880 --> 00:03:13.517 build more insight and more uh more 00:03:13.600 --> 00:03:17.037 capability and in that context AI I 00:03:17.120 --> 00:03:19.437 would say is of the same class at least 00:03:19.520 --> 00:03:22.797 like the web or the internet um or 00:03:22.880 --> 00:03:25.357 mobile or PC or the cloud or and maybe 00:03:25.440 --> 00:03:29.597 even greater and so to me right now 00:03:29.680 --> 00:03:32.797 where we are is you know let's take just 00:03:32.880 --> 00:03:36.797 what's happened with software engineering right which is one you know 00:03:36.880 --> 00:03:39.597 is knowledge work um you know you could 00:03:39.680 --> 00:03:41.917 say it's elite knowledge work 00:03:42.000 --> 00:03:44.877 >> it started off uh you know in fact my 00:03:44.960 --> 00:03:49.677 own belief in this generation of AI and its capability 00:03:49.760 --> 00:03:53.917 uh really got built up when I first saw GitHub copilot do code completions right 00:03:54.000 --> 00:03:58.477 so for the longest time we had the dream that if you're a software developer can 00:03:58.560 --> 00:04:00.877 you predict the next sort of word or the 00:04:00.960 --> 00:04:04.557 next uh line of code uh and suddenly it 00:04:04.640 --> 00:04:07.197 started working with these models u then 00:04:07.280 --> 00:04:09.197 You said okay if I can do that then can 00:04:09.280 --> 00:04:12.397 I actually go and bring back you know 00:04:12.480 --> 00:04:16.797 the flow for a software developer by going to a chat session and asking any 00:04:16.880 --> 00:04:21.197 question and it comes back with answers that then uh you can use in your coding 00:04:21.280 --> 00:04:24.797 flow right so that was the next thing then you said well if that's working can 00:04:24.880 --> 00:04:29.997 I assign it small tasks that was the agent mode uh now you have complete 00:04:30.080 --> 00:04:34.557 autonomous agents where you can give it your entire project right it can work uh 00:04:34.640 --> 00:04:37.997 you know >> 24/7 >> it can work for 24/7. I mean it's still 00:04:38.080 --> 00:04:42.237 we've got some ways to go for these things to remain coherent long time but 00:04:42.320 --> 00:04:44.557 nevertheless it's getting better and 00:04:44.640 --> 00:04:47.757 better and interestingly enough you look 00:04:47.840 --> 00:04:51.197 at it uh the software developer still is 00:04:51.280 --> 00:04:54.877 got a lot of agency in it right so that's why I kind of still think that 00:04:54.960 --> 00:04:59.517 you know going and thinking of these as somehow living outside of the realm of 00:04:59.600 --> 00:05:03.597 human agency is probably not the right way to think about it in fact the way to 00:05:03.680 --> 00:05:06.717 perhaps conceive it like it's let's say in early8s 00:05:06.800 --> 00:05:10.717 If somebody had come to us and said whatever four billion people are going 00:05:10.800 --> 00:05:12.637 to wake up every morning and start 00:05:12.720 --> 00:05:15.437 typing you would have said why right you 00:05:15.520 --> 00:05:20.077 know we have a like we have a typist pool that's good enough we don't need 4 00:05:20.160 --> 00:05:24.157 billion people but we that's what happened right we invented this entire 00:05:24.240 --> 00:05:26.797 class of thing called knowledge work 00:05:26.880 --> 00:05:29.197 where people started really using 00:05:29.280 --> 00:05:32.637 computers uh to go amplify what we were 00:05:32.720 --> 00:05:37.437 trying to achieve uh using software I think in the context of AI that same 00:05:37.520 --> 00:05:41.917 thing is going to happen. >> Um it's not like you know what is 00:05:42.000 --> 00:05:46.077 hardcore coding is going to remain hardcore coding forever. It's just that 00:05:46.160 --> 00:05:47.677 the levels of abstraction are going to 00:05:47.760 --> 00:05:50.637 change. Uh but we also are going to have 00:05:50.720 --> 00:05:53.117 code as output just like documents. In 00:05:53.200 --> 00:05:57.997 fact, one of Bill's things at Microsoft from the day I joined in '92 always was 00:05:58.080 --> 00:05:59.677 what's the real difference between a 00:05:59.760 --> 00:06:02.637 document, a website and an application, 00:06:02.720 --> 00:06:05.277 right? It's the lack of sort of software 00:06:05.360 --> 00:06:07.917 that can transform itself. Interestingly 00:06:08.000 --> 00:06:09.997 enough, AI finally gives us that, right? 00:06:10.080 --> 00:06:13.837 Which is I can write a document. I can just say no, I don't want it as a 00:06:13.920 --> 00:06:17.837 document. I want it as a website. It'll just transform that document using code 00:06:17.920 --> 00:06:20.237 into a website. I say I don't like the 00:06:20.320 --> 00:06:22.077 website. I want an app. It'll write more 00:06:22.160 --> 00:06:25.197 code to transform it. So that reasoning 00:06:25.280 --> 00:06:27.837 and cap reasoning capabilities that 00:06:27.920 --> 00:06:30.077 prediction capabilities that ability to 00:06:30.160 --> 00:06:33.517 take action remain long-term coherent is 00:06:33.600 --> 00:06:38.477 all improving. Um and our job though is 00:06:38.560 --> 00:06:42.957 to parlay this like take even what you at Black Rockck are doing right when you 00:06:43.040 --> 00:06:46.877 are bring taking something like say co-pilot plus Aladdin and bringing those 00:06:46.960 --> 00:06:50.797 things together [clears throat] >> to improve the productivity in the firm 00:06:50.880 --> 00:06:54.317 for the decisions you want to make right with your data 00:06:54.400 --> 00:06:56.317 >> I could just tell you from in our firm 00:06:56.400 --> 00:06:58.637 things that would take 12 hours to 00:06:58.720 --> 00:07:04.077 compute now takes minutes for us processing 14 trillion dollars of other 00:07:04.160 --> 00:07:05.517 people's money with hundreds of 00:07:05.600 --> 00:07:09.357 thousands of different um mandates um we 00:07:09.440 --> 00:07:12.797 could do that instantaneous and we you know that to me if it wasn't for the 00:07:12.880 --> 00:07:16.877 technology and AI today we would not be able to function to the scale that we're 00:07:16.960 --> 00:07:20.797 operating >> that's right and so to me that one firm 00:07:20.880 --> 00:07:23.357 at a time one country at a time if we 00:07:23.440 --> 00:07:26.477 can really take these tokens and bend 00:07:26.560 --> 00:07:30.557 the curve of productivity then there is surplus everywhere and that's really the 00:07:30.640 --> 00:07:33.597 goal >> well surplus could be scary too does 00:07:33.680 --> 00:07:37.117 does surplus mean fewer workers? What do 00:07:37.200 --> 00:07:41.357 we mean by surplus? And so, you know, the I want to tie that into my second 00:07:41.440 --> 00:07:43.997 question about AI diffusion. >> Yeah. 00:07:44.080 --> 00:07:46.877 >> To me, the the whole realization of AI 00:07:46.960 --> 00:07:50.317 for any society and also for a more 00:07:50.400 --> 00:07:53.197 balanced world is making sure that it's 00:07:53.280 --> 00:07:55.837 diffused and accessible and available 00:07:55.920 --> 00:07:58.157 across the world. So what you know can 00:07:58.240 --> 00:08:00.877 you describe how this process of 00:08:00.960 --> 00:08:06.077 diffusion uh across economies across companies across people and countries 00:08:06.160 --> 00:08:09.997 how does that play out? >> Yeah I think 00:08:10.080 --> 00:08:14.397 that this is the real question right because one of the uh things right now 00:08:14.480 --> 00:08:16.957 the zeitgeist is a little bit about the 00:08:17.040 --> 00:08:20.477 admiration for AI in its abstract form 00:08:20.560 --> 00:08:24.157 or as as technology. 00:08:24.240 --> 00:08:25.837 uh [clears throat] but I think we as 00:08:25.920 --> 00:08:28.957 even a global community um have to get 00:08:29.040 --> 00:08:32.077 to a point where we're using this to do 00:08:32.160 --> 00:08:35.677 something useful uh that changes uh the 00:08:35.760 --> 00:08:39.997 outcomes of people and communities and countries and industries right otherwise 00:08:40.080 --> 00:08:42.397 I don't think uh this makes much sense 00:08:42.480 --> 00:08:44.397 right in fact I would say we will 00:08:44.480 --> 00:08:47.837 quickly lose even the social permission 00:08:47.920 --> 00:08:50.477 uh to actually take something like uh 00:08:50.560 --> 00:08:54.877 energy which is a scarce resource and use it to generate these tokens if these 00:08:54.960 --> 00:08:58.637 tokens are not improving health outcomes, education outcomes, public 00:08:58.720 --> 00:09:03.117 sector efficiency, private sector competitiveness across all sectors, 00:09:03.200 --> 00:09:05.597 small and large, right? And that to me 00:09:05.680 --> 00:09:08.637 is ultimately the goal. So therefore I 00:09:08.720 --> 00:09:11.677 think really diffusion is everything. 00:09:11.760 --> 00:09:14.317 And so the way it happens is let's sort 00:09:14.400 --> 00:09:18.077 of unpack this uh on the supply side 00:09:18.160 --> 00:09:20.237 what needs to happen in each country is 00:09:20.320 --> 00:09:24.157 the tokens per dollar per watt have to 00:09:24.240 --> 00:09:29.197 sort of monotonically get more efficient and better right so to some degree even 00:09:29.280 --> 00:09:32.797 what we're trying to do with the investments the two firms are doing uh 00:09:32.880 --> 00:09:37.117 around the world is to just say that like let's make sure that the supply is 00:09:37.200 --> 00:09:39.677 there which is uh everything from the 00:09:39.760 --> 00:09:44.397 chips on down ultimately ely to these token factories that get deployed 00:09:44.480 --> 00:09:48.477 everywhere. By the way, there's not one token factory. This token factory is the 00:09:48.560 --> 00:09:52.157 first thing that's going to be diffused all around the world. It's just like 00:09:52.240 --> 00:09:55.117 electricity, right? You just need a 00:09:55.200 --> 00:09:59.917 ubiquitous grid of uh energy and tokens 00:10:00.000 --> 00:10:02.477 that then will power the rest of the 00:10:02.560 --> 00:10:04.237 economy, right? So, that's I think one 00:10:04.320 --> 00:10:07.437 side of it. Then the demand side of this 00:10:07.520 --> 00:10:10.477 is a little bit like every firm has to 00:10:10.560 --> 00:10:13.677 start by using it. If I look back even, 00:10:13.760 --> 00:10:16.797 you know, when the PCs first came out or 00:10:16.880 --> 00:10:20.957 the personal computing era started, I I loved, you know, I think Jobs had a nice 00:10:21.040 --> 00:10:25.917 metaphor. He called it the bicycle for the mind. Uh Bill had a metaphor which I 00:10:26.000 --> 00:10:29.117 remember was like information at your fingertips, right? These two metaphors 00:10:29.200 --> 00:10:33.037 were great like which allowed us to say that's what it is. It's a tool that I 00:10:33.120 --> 00:10:36.957 will use to get information at my fingertips. I'll use it as a cognitive 00:10:37.040 --> 00:10:38.477 amplifier. 00:10:38.560 --> 00:10:42.157 Now I think that's what we have. But you 00:10:42.240 --> 00:10:44.317 know 10x 100x right? So in some sense 00:10:44.400 --> 00:10:48.077 you as a as every knowledge worker you 00:10:48.160 --> 00:10:50.797 now have access to infinite minds. 00:10:50.880 --> 00:10:52.237 That's the way I think about it. Right. 00:10:52.320 --> 00:10:56.077 So there's a Turing award winner uh called Raj Ready who had this nice 00:10:56.160 --> 00:11:00.797 metaphor of AI and he had this long before uh even generative AI. He said 00:11:00.880 --> 00:11:03.037 either either it's a cognitive amplifier 00:11:03.120 --> 00:11:05.757 or it's a guardian angel right so if you 00:11:05.840 --> 00:11:09.597 think of AI as that um then that in the 00:11:09.680 --> 00:11:13.677 global workforce right when a doctor can 00:11:13.760 --> 00:11:18.077 get to a patient spend more time with the patient because the AI is doing the 00:11:18.160 --> 00:11:20.317 transcription and entering the records 00:11:20.400 --> 00:11:23.197 in the EMR system entering the right 00:11:23.280 --> 00:11:25.917 billing code so that the health care uh 00:11:26.000 --> 00:11:28.077 you know industry is better served 00:11:28.160 --> 00:11:31.117 across the payer the provider and uh and 00:11:31.200 --> 00:11:33.997 the patient ultimately right that's an 00:11:34.080 --> 00:11:36.077 an outcome that I think all of us can 00:11:36.160 --> 00:11:39.037 benefit from so I feel ultimately it's 00:11:39.120 --> 00:11:41.677 going to require real leadership on the 00:11:41.760 --> 00:11:44.237 private sector and the public sector to 00:11:44.320 --> 00:11:46.637 ensure that diffusion happens and the 00:11:46.720 --> 00:11:48.717 one thing other thing I'll mention Larry 00:11:48.800 --> 00:11:52.957 is skilling right so in some sense the 00:11:53.040 --> 00:11:56.557 thing that diffusion is very strongly 00:11:56.640 --> 00:11:59.597 correlated to one thing alone which is 00:11:59.680 --> 00:12:02.717 How broadly are people skilled in using 00:12:02.800 --> 00:12:06.317 this? Um, and interestingly enough, I 00:12:06.400 --> 00:12:09.437 think if mobile has taught us one thing 00:12:09.520 --> 00:12:14.157 is it it's actually distinct from what happened in the PC, right? Uh, I 00:12:14.240 --> 00:12:18.477 remember even growing up in the global south, uh, there used to be a real 00:12:18.560 --> 00:12:20.957 relationship between learning Excel 00:12:21.040 --> 00:12:24.877 skills or word skills and getting a job. 00:12:24.960 --> 00:12:27.917 um you know right now um what's the 00:12:28.000 --> 00:12:32.317 model in in mobile it's kind of created the same opportunity but it's been a lot 00:12:32.400 --> 00:12:37.037 more consumption-led it's these creator economy and what have you but it has not 00:12:37.120 --> 00:12:40.717 been about sort of oh wow here is how you get a healthare job or here is how 00:12:40.800 --> 00:12:45.037 you get a finance job or here is how you get you know you get ahead 00:12:45.120 --> 00:12:49.597 professionally um and that needs to come back right 00:12:49.680 --> 00:12:51.517 people need to say I pick up this AI 00:12:51.600 --> 00:12:56.877 skill and now I'm a better provider of some product or service in the real 00:12:56.960 --> 00:12:58.957 economy. >> So it's it's very [clears throat] easy 00:12:59.040 --> 00:13:01.837 to see how mobile and the diffusion of 00:13:01.920 --> 00:13:04.077 mobile how it transformed economies 00:13:04.160 --> 00:13:06.557 especially in the global south. 00:13:06.640 --> 00:13:10.797 How does how does this you know to me I I I just read a research report that 00:13:10.880 --> 00:13:15.197 said the applications for AI so far are 00:13:15.280 --> 00:13:19.837 heavily weighted towards those who are educated or educated economies. 00:13:19.920 --> 00:13:23.997 And so does that create that, you know, more of a bifurcation, a more 00:13:24.080 --> 00:13:29.357 polarization? How do we ensure that that that diffusion is spread evenly? How do 00:13:29.440 --> 00:13:30.957 we make sure that we're [clears throat] 00:13:31.040 --> 00:13:37.037 not leaving major portions of society or the world behind because I think that's 00:13:37.120 --> 00:13:39.677 that's [clears throat] going to be the big issue for us going forward. 00:13:39.760 --> 00:13:41.117 >> Yeah. So it's it's it's interesting, 00:13:41.200 --> 00:13:44.797 right? This is one of those times when 00:13:44.880 --> 00:13:48.397 uh by definition and because of the 00:13:48.480 --> 00:13:50.237 rails that have been established you 00:13:50.320 --> 00:13:53.037 know as you said right which is uh 00:13:53.120 --> 00:13:57.597 what's happened with mobile as well as what's happened with um 00:13:57.680 --> 00:14:00.317 >> uh you know essentially connectivity >> right 00:14:00.400 --> 00:14:04.877 >> you have the ability [clears throat] to sort of deliver the tokens pretty evenly 00:14:04.960 --> 00:14:09.917 around the world >> right >> a lot more so than let's say uh the PC 00:14:10.000 --> 00:14:13.357 era or even the beginning of the mobile era, right? Because it took a long time 00:14:13.440 --> 00:14:15.597 for even the mo smartphone in particular 00:14:15.680 --> 00:14:18.797 to penetrate um all of the world. 00:14:18.880 --> 00:14:21.277 Whereas now it's not the case, right? 00:14:21.360 --> 00:14:24.637 These models and their outputs are 00:14:24.720 --> 00:14:26.557 pretty much available everywhere. And so 00:14:26.640 --> 00:14:29.837 the question to me is 00:14:29.920 --> 00:14:34.077 what's the use cases that make sense, right? One, in fact, one of the demos I 00:14:34.160 --> 00:14:35.997 always go back to, I think this was even 00:14:36.080 --> 00:14:38.557 in the beginning of 23 was a rural 00:14:38.640 --> 00:14:41.517 Indian farmer was able to use a bot 00:14:41.600 --> 00:14:45.197 built on I think a very early GPT3 or 25 00:14:45.280 --> 00:14:48.637 even uh essentially to reason over some 00:14:48.720 --> 00:14:50.717 farm subsidies that he had heard about 00:14:50.800 --> 00:14:53.757 in a local language and had it even in 00:14:53.840 --> 00:14:56.877 that very early days uh have it even 00:14:56.960 --> 00:14:59.037 show some agentic behavior right like go 00:14:59.120 --> 00:15:00.797 complete a form for me. So in some sense 00:15:00.880 --> 00:15:03.917 it took uh you know it brought back 00:15:04.000 --> 00:15:07.917 agency to someone uh who perhaps didn't 00:15:08.000 --> 00:15:12.397 have that because the technology was so much more accessible. So I I do think 00:15:12.480 --> 00:15:14.717 it's in our hands even in the global 00:15:14.800 --> 00:15:18.957 south to use it uh to create I would say 00:15:19.040 --> 00:15:21.277 more of that opportunity where there 00:15:21.360 --> 00:15:24.787 isn't one. Um but I think what the 00:15:24.870 --> 00:15:25.997 [clears throat] necessary conditions 00:15:26.080 --> 00:15:29.037 still are do you have uh the capital 00:15:29.120 --> 00:15:33.517 investment being put in uh do you even have an environment for capital because 00:15:33.600 --> 00:15:37.917 in an interesting way we are for example as hyperscalers investing all over right 00:15:38.000 --> 00:15:42.237 including the global south uh so as long as there's an environment which attracts 00:15:42.320 --> 00:15:44.557 the capital investment >> and you see the demand 00:15:44.640 --> 00:15:47.437 >> and you see and then yeah the demand is there 00:15:47.520 --> 00:15:51.757 >> um and so the question is how do you have a set of policies that allow for 00:15:51.840 --> 00:15:56.077 both the capital to come in for it to find nexus where there are certain 00:15:56.160 --> 00:15:58.317 things by the way private capital can do 00:15:58.400 --> 00:16:00.157 certain things that public capital only 00:16:00.240 --> 00:16:03.197 can do for example the grid right it's 00:16:03.280 --> 00:16:08.317 not I mean grid in most countries is sort of fundamentally driven by governments 00:16:08.400 --> 00:16:10.317 >> public >> and public and so if [clears throat] you 00:16:10.400 --> 00:16:12.637 don't have a sophisticated sort or 00:16:12.720 --> 00:16:17.597 rather if you don't have a a real approach to modernizing the grid uh that 00:16:17.680 --> 00:16:21.037 will hold things back I mean there's a lot of talk about behind the meter and 00:16:21.120 --> 00:16:23.677 so on and Yes, there's some amount of that we can do ourselves. 00:16:23.760 --> 00:16:25.917 >> We can do that in the US. Many countries can't. 00:16:26.000 --> 00:16:29.357 >> Exactly. And it's not long-term scalable, right? I mean, like to me, a 00:16:29.440 --> 00:16:32.877 long-term scalable solution is to have 00:16:32.960 --> 00:16:37.677 uh you know, all of these token factories, part of the real economy, 00:16:37.760 --> 00:16:42.397 connected to the grid, connected to the telco network, delivering uh just like 00:16:42.480 --> 00:16:44.397 we delivered bits, you have to deliver 00:16:44.480 --> 00:16:47.357 tokens plus bits. Um and that's kind of 00:16:47.440 --> 00:16:51.757 what's going to drive an at scale whether it's in the global south or in 00:16:51.840 --> 00:16:55.037 uh on the developed world. >> So so many people talk about there may 00:16:55.120 --> 00:16:57.037 be an AI bubble. I mean the most 00:16:57.120 --> 00:16:58.477 important thing that we see as an 00:16:58.560 --> 00:17:02.637 investor is the the democratization of 00:17:02.720 --> 00:17:05.517 technology is and the diffusion of that 00:17:05.600 --> 00:17:08.077 technology really does then transform 00:17:08.160 --> 00:17:13.117 the demand and the the companies or the countries that diffuse it fastest are 00:17:13.200 --> 00:17:14.637 going to be the ultimate winners. not 00:17:14.720 --> 00:17:16.477 the technology creator. 00:17:16.560 --> 00:17:20.797 >> That's that's you know it's it's it's 00:17:20.880 --> 00:17:23.117 for this not to be a bubble 00:17:23.200 --> 00:17:23.757 >> y 00:17:23.840 --> 00:17:27.917 >> by definition it requires that the 00:17:28.000 --> 00:17:30.157 benefits of this are much more evenly 00:17:30.240 --> 00:17:33.357 spread. I mean I think a tellt tell sign 00:17:33.440 --> 00:17:36.797 of if it's a bubble would be if all 00:17:36.880 --> 00:17:39.997 we're talking about are the tech firms. 00:17:40.080 --> 00:17:43.117 Uh right? If uh all we talk about is 00:17:43.200 --> 00:17:47.277 what's happening to the technology side that then that's by you know it's just 00:17:47.360 --> 00:17:51.437 purely supply side >> right >> uh ultimately if we are not talking 00:17:51.520 --> 00:17:55.677 about wow here is a drug comp you know drug that was sort of uh brought into 00:17:55.760 --> 00:17:59.757 the market that's super successful because it was uh AI accelerated the 00:17:59.840 --> 00:18:01.837 clinical trial it's not even the magical 00:18:01.920 --> 00:18:03.757 molecule right it's kind of even the 00:18:03.840 --> 00:18:06.877 rest of what is uh needed in order to 00:18:06.960 --> 00:18:09.517 make something much more relevant right 00:18:09.600 --> 00:18:14.797 um and So the more [clears throat] we have uh and by the way it's happening 00:18:14.880 --> 00:18:19.277 right. So I'm not sort of saying that that's why I'm much more confident that 00:18:19.360 --> 00:18:21.757 this is a technology that will in fact 00:18:21.840 --> 00:18:25.197 build on the rails of cloud and mobile 00:18:25.280 --> 00:18:27.037 diffuse faster 00:18:27.120 --> 00:18:30.557 >> and bend the productivity curve and 00:18:30.640 --> 00:18:33.437 bring local surplus and economic growth 00:18:33.520 --> 00:18:36.317 all around the world. Not just economic 00:18:36.400 --> 00:18:39.357 growth driven by capital expenses. 00:18:39.440 --> 00:18:44.557 uh right because that's it's a narrow point in time uh calculation. right now 00:18:44.640 --> 00:18:46.797 that's what we're seeing more >> that's what we're seeing you know you 00:18:46.880 --> 00:18:48.397 know in in the developed world in 00:18:48.480 --> 00:18:51.917 particular uh but remember my capital 00:18:52.000 --> 00:18:55.517 like that the one thing that you know is definitely we're spending a lot of it in 00:18:55.600 --> 00:18:58.797 the United States but 50% of it is also all over the world 00:18:58.880 --> 00:19:02.637 >> right >> um and so interesting enough it depends 00:19:02.720 --> 00:19:07.037 on uh demand all over the world and the demand all over the world will only be 00:19:07.120 --> 00:19:11.357 there if there is local surplus all over the world and so that's sort of the way 00:19:11.440 --> 00:19:15.357 I see the equation >> so let's drill down a little more. As AI 00:19:15.440 --> 00:19:19.437 diffuses, obviously organizations, companies, 00:19:19.520 --> 00:19:21.677 governments are going to have to evolve. 00:19:21.760 --> 00:19:24.717 I'm now getting to the demand side. So, 00:19:24.800 --> 00:19:26.477 how do you think the structure of 00:19:26.560 --> 00:19:30.477 organizations is changing in an AI world 00:19:30.560 --> 00:19:33.837 across roles, across teams, management? 00:19:33.920 --> 00:19:37.357 I'm I'm sure um Microsoft has evolved 00:19:37.440 --> 00:19:40.317 itself. So it probably be good to tell 00:19:40.400 --> 00:19:42.557 the audience how do you see this 00:19:42.640 --> 00:19:47.437 diffusion occur in the utilization at the corporate level or at a government 00:19:47.520 --> 00:19:51.437 level that which ultimately then creates that demand which eliminates any fears 00:19:51.520 --> 00:19:53.837 and bubbles. >> Yeah. No, I think it's probably one of 00:19:53.920 --> 00:19:56.237 the the the big challenges with all of 00:19:56.320 --> 00:20:00.717 these new technologies is when uh work 00:20:00.800 --> 00:20:04.717 work artifact and work flow changes 00:20:04.800 --> 00:20:08.637 uh the means we as firms have to change 00:20:08.720 --> 00:20:13.197 how we work. In [clears throat] fact, I remember meeting um uh the CEO of 00:20:13.280 --> 00:20:15.277 General Ali, you know, a few years back 00:20:15.360 --> 00:20:18.157 and he was describing he had joined um 00:20:18.240 --> 00:20:23.197 uh the firm, you know, prec [clears throat] era and uh uh and he was 00:20:23.280 --> 00:20:25.117 describing how for example they worked 00:20:25.200 --> 00:20:27.837 with their agents in the field uh with 00:20:27.920 --> 00:20:31.757 faxes inter office memos and um and and 00:20:31.840 --> 00:20:35.757 suddenly the PC showed up and people would then put a spreadsheet in an email 00:20:35.840 --> 00:20:39.597 and send it around and the entire workflow and the work process has 00:20:39.680 --> 00:20:42.397 changed right so similarly I think with 00:20:42.480 --> 00:20:46.237 AI uh you are going to start seeing uh 00:20:46.320 --> 00:20:50.397 actual change in how workflow happens right I mean even [clears throat] 00:20:50.480 --> 00:20:52.317 in fact for me coming to Davos you know 00:20:52.400 --> 00:20:55.117 whatever 50 bilateral meetings I have 00:20:55.200 --> 00:20:58.077 preparing for those uh had a particular 00:20:58.160 --> 00:21:02.957 workflow right which is uh there is to be my field team would prepare notes and 00:21:03.040 --> 00:21:07.037 that would come to my HQ and that would get further refined and nothing had 00:21:07.120 --> 00:21:09.597 really changed right since I joined in 00:21:09.680 --> 00:21:14.717 '92 to essentially even a few years back. Whereas now I just go to co-pilot 00:21:14.800 --> 00:21:18.957 and say hey I'm meeting Larry. Please give me a brief and it comes back and 00:21:19.040 --> 00:21:23.037 gives me by the way the one nice thing is it gives me a 360 right? It knows 00:21:23.120 --> 00:21:27.437 what we're doing with you as a client what we're doing as a client of yours 00:21:27.520 --> 00:21:30.157 and everything in [clears throat] between as an investment. It's so it 00:21:30.240 --> 00:21:32.957 captures even information unlike 00:21:33.040 --> 00:21:37.277 anything else. In fact, what I do is I take that and immediately share that 00:21:37.360 --> 00:21:40.957 back with all my colleagues across all the functions. Right? Think about it. 00:21:41.040 --> 00:21:43.757 It's a complete inversion of how 00:21:43.840 --> 00:21:48.077 information is flowing in the organization. It's not like this classic 00:21:48.160 --> 00:21:51.437 we have an organization, we have departments, we have these 00:21:51.520 --> 00:21:53.437 specializations and the information 00:21:53.520 --> 00:21:56.637 trickles up. No, no, no. It actually it 00:21:56.720 --> 00:22:00.317 flattens the entire information flow. So 00:22:00.400 --> 00:22:02.957 once you start having that you have to 00:22:03.040 --> 00:22:06.317 redesign structurally uh so the current 00:22:06.400 --> 00:22:10.317 structure may not make sense um because 00:22:10.400 --> 00:22:14.077 you want people to be able to work in a 00:22:14.160 --> 00:22:16.637 way that allows them to have this 00:22:16.720 --> 00:22:19.517 information flow freely. So what all 00:22:19.600 --> 00:22:23.677 this leads me to if I had to sort of say what's the formula the formula I think 00:22:23.760 --> 00:22:25.677 it starts with the mindset. So the 00:22:25.760 --> 00:22:29.917 mindset we as leaders should have is we 00:22:30.000 --> 00:22:32.957 need to think about changing the work 00:22:33.040 --> 00:22:36.157 the workflow with the technology then 00:22:36.240 --> 00:22:40.317 that needs skill set. So you can't sort of talk about this in the abstract. You 00:22:40.400 --> 00:22:43.837 got to use it like so if I'm not using the >> you have to trust it. 00:22:43.920 --> 00:22:47.997 >> You have to trust it. You have to use it. You have to learn even how to put 00:22:48.080 --> 00:22:51.997 the guard rails to trust it. Right? So you can't again you can't just be afraid 00:22:52.080 --> 00:22:54.877 of it. uh it's going to it's going to be 00:22:54.960 --> 00:22:57.677 diffused. So the question is as a firm 00:22:57.760 --> 00:23:00.877 you have to use it to learn how to even 00:23:00.960 --> 00:23:03.037 uh put the guardrails that allow you to 00:23:03.120 --> 00:23:06.317 be able to trust it. So skills uh so 00:23:06.400 --> 00:23:08.557 mindsets skills the other big 00:23:08.640 --> 00:23:12.077 consideration u really is how do you 00:23:12.160 --> 00:23:15.277 make sure you have the data set that 00:23:15.360 --> 00:23:18.397 you're feeding like context like it's 00:23:18.480 --> 00:23:20.877 kind of like you have a new intelligence 00:23:20.960 --> 00:23:23.437 layer but the intelligence layer is only 00:23:23.520 --> 00:23:27.197 as good as the context you give it. So 00:23:27.280 --> 00:23:31.917 people describe it even as context engineering but that is what firms do 00:23:32.000 --> 00:23:35.997 right if you think about what do firms do it's all about the tacit knowledge we 00:23:36.080 --> 00:23:41.437 have by working as people in various departments and moving paper and 00:23:41.520 --> 00:23:44.957 information so the question is how do you really have this AI also have that 00:23:45.040 --> 00:23:47.437 context so these are sort of some of the 00:23:47.520 --> 00:23:50.157 new things that have to percolate 00:23:50.240 --> 00:23:54.477 throughout an organization uh to take advantage in fact that's why I think you 00:23:54.560 --> 00:23:57.117 you're going to see that challenge of 00:23:57.200 --> 00:24:01.757 why am I not seeing immediate results in productivity? Because you have to do the 00:24:01.840 --> 00:24:04.877 hard work. In fact, that's why it's not going to be some, you know, it's going 00:24:04.960 --> 00:24:08.157 to there going to be firmwide differences. They're going to there 00:24:08.240 --> 00:24:12.557 could be sectorwide differences, but it's going to fundamentally be because 00:24:12.640 --> 00:24:15.997 of the leadership will in an organization. 00:24:16.080 --> 00:24:20.957 >> Do you see the applications being used across large companies and medium and 00:24:21.040 --> 00:24:24.477 small companies or is it still the domain of mostly the large companies at 00:24:24.560 --> 00:24:26.717 this moment? I I think that what you're 00:24:26.800 --> 00:24:30.157 seeing is it's easier the because if you 00:24:30.240 --> 00:24:34.237 have a green sort of um uh you know if 00:24:34.320 --> 00:24:37.037 you start fresh it's easier to adopt 00:24:37.120 --> 00:24:41.997 these tools and you construct your organization knowing that these tools 00:24:42.080 --> 00:24:43.917 exist. So >> is it a barbell then? 00:24:44.000 --> 00:24:48.237 >> It is a barbell. So small companies that are just starting use that platform 00:24:48.320 --> 00:24:51.377 >> 100% and I think in fact I would say even for large organization there's 00:24:51.460 --> 00:24:54.717 [clears throat] a fundamental challenge right because unless and until your rate 00:24:54.800 --> 00:24:57.677 of change keeps up with >> right 00:24:57.760 --> 00:25:00.397 >> uh with with what is possible uh you're 00:25:00.480 --> 00:25:03.197 going to get schooled by someone small 00:25:03.280 --> 00:25:08.397 being able to achieve scale because of these tools. So but I think scale large 00:25:08.480 --> 00:25:10.077 organizations have an inherent strength. 00:25:10.160 --> 00:25:11.757 You have the relationships, you have the 00:25:11.840 --> 00:25:15.517 data, you have um you have knowhow. But 00:25:15.600 --> 00:25:19.677 the bottom line is if you don't translate that with a new production 00:25:19.760 --> 00:25:24.157 function, uh then you really will be stuck. And so therefore the change 00:25:24.240 --> 00:25:28.397 management challenge for large organizations is going to be bigger. The 00:25:28.480 --> 00:25:31.837 structural challenge for small organizations of how to overcome scale 00:25:31.920 --> 00:25:35.037 issues is going to be harder. So it's sort of the two sides. in an interesting 00:25:35.120 --> 00:25:36.317 way. It's going to be a very 00:25:36.400 --> 00:25:39.997 competitively intense world uh where 00:25:40.080 --> 00:25:44.557 neither side like whether you're a new entrant or an incumbent can't take it as 00:25:44.640 --> 00:25:46.957 like I I can just coast. 00:25:47.040 --> 00:25:49.917 >> What about country to country? Are you 00:25:50.000 --> 00:25:54.477 seeing big differences in how the applications are being used? Is it is AI 00:25:54.560 --> 00:25:59.117 still the domain of developed countries or is it becoming rapidly a domain of 00:25:59.200 --> 00:26:02.237 all countries? I I I'm seeing there [clears throat] are two things I would 00:26:02.320 --> 00:26:04.797 say Larry as I travel around the world 00:26:04.880 --> 00:26:09.197 the quality of um whether it's the 00:26:09.280 --> 00:26:11.677 knowhow the software developers the 00:26:11.760 --> 00:26:13.277 startups 00:26:13.360 --> 00:26:17.037 um or even large or large organizations 00:26:17.120 --> 00:26:20.557 it's not that different it's fascinating you can show up in Jakarta you can show 00:26:20.640 --> 00:26:22.797 up in Istanbul you can show up in Mexico 00:26:22.880 --> 00:26:27.837 City it's not that different than showing up even in say Seattle or San 00:26:27.920 --> 00:26:29.517 Francisco right it's 00:26:29.600 --> 00:26:31.997 uh for the first time just because 00:26:32.080 --> 00:26:35.757 access to what's happening uh is there 00:26:35.840 --> 00:26:39.597 that said at [clears throat] scale the 00:26:39.680 --> 00:26:43.357 commitment to using this the risk 00:26:43.440 --> 00:26:45.997 capital being there the large companies 00:26:46.080 --> 00:26:49.037 pushing it hard I mean I you know again 00:26:49.120 --> 00:26:52.637 the US you know is in fact if I compare 00:26:52.720 --> 00:26:56.477 it uh take financial sector 00:26:56.560 --> 00:26:59.117 financial sector's adoption of the cloud 00:26:59.200 --> 00:27:02.077 versus AI night and day, right? Because 00:27:02.160 --> 00:27:05.437 in an interesting way, it's much faster 00:27:05.520 --> 00:27:08.077 uh when it comes to AI versus it was 00:27:08.160 --> 00:27:09.837 with the cloud and cloud because for a 00:27:09.920 --> 00:27:12.717 variety of reasons regulatory issues too 00:27:12.800 --> 00:27:18.477 until the regulators allowed banks to bring their data off out of campus that 00:27:18.560 --> 00:27:20.707 was a big issue. >> Yeah. So I would say I think 00:27:20.790 --> 00:27:22.877 [clears throat] wherever you know so in 00:27:22.960 --> 00:27:25.917 the west in particular in the US uh 00:27:26.000 --> 00:27:29.357 there is clearly a real I would say more 00:27:29.440 --> 00:27:31.997 of an energy around it in terms of going 00:27:32.080 --> 00:27:34.957 and using it uh but it's sort of a lot 00:27:35.040 --> 00:27:40.157 more uniformly spreading around the world than any technology at least I've 00:27:40.240 --> 00:27:45.037 seen but are you [clears throat] are you mentioned about the power the grid is 00:27:45.120 --> 00:27:46.637 that going to be one of the determinants 00:27:46.720 --> 00:27:49.997 of of the accessibility ility if you do 00:27:50.080 --> 00:27:53.517 not have cheap power it the demand is 00:27:53.600 --> 00:27:57.597 costly >> 100%. So if you sort of look at the 00:27:57.680 --> 00:28:00.077 tokens per dollar per watt right which I 00:28:00.160 --> 00:28:01.517 think in [clears throat] some sense I 00:28:01.600 --> 00:28:05.197 would claim that GDP growth in any place 00:28:05.280 --> 00:28:09.197 will be directly correlated like you if you sort of buy my entire argument that 00:28:09.280 --> 00:28:13.037 look we've got a new commodity its tokens >> right 00:28:13.120 --> 00:28:17.677 >> and the job of every economy uh and every firm in the economy is to 00:28:17.760 --> 00:28:19.757 translate these tokens into economic 00:28:19.840 --> 00:28:22.317 growth then if you have a cheaper 00:28:22.400 --> 00:28:27.597 commodity it's better uh And so that's sort of what why there's tokens per 00:28:27.680 --> 00:28:31.357 dollar per watt. And by the way, there are many many elements to this, right? 00:28:31.440 --> 00:28:35.517 Which is uh it's not just um the production side. That's why I think even 00:28:35.600 --> 00:28:38.317 having the grid is important. Um uh 00:28:38.400 --> 00:28:40.317 construction costs, right? So if you 00:28:40.400 --> 00:28:43.517 like if you think about the total TCO uh 00:28:43.600 --> 00:28:47.757 everything it's like the how are you a cheap producer of energy? Can you build 00:28:47.840 --> 00:28:50.317 the data centers? Uh then what's the 00:28:50.400 --> 00:28:53.037 cost curve uh of the silicon and the 00:28:53.120 --> 00:28:55.837 systems? uh the and by the way look at 00:28:55.920 --> 00:28:58.797 the token pricing right token pricing 00:28:58.880 --> 00:29:02.637 basically drops by you know a half uh 00:29:02.720 --> 00:29:05.757 every three months uh I mean this is a 00:29:05.840 --> 00:29:08.397 so how so that that's why I think you 00:29:08.480 --> 00:29:12.237 can sort of really plot how you use the 00:29:12.320 --> 00:29:16.717 tokens to create surplus knowing that you have a commodity that's whose prices 00:29:16.800 --> 00:29:19.917 are just going to monotonically come down in a pretty fast curve 00:29:20.000 --> 00:29:22.957 >> we're sitting in Europe uh and there is 00:29:23.040 --> 00:29:25.197 a real fear 00:29:25.280 --> 00:29:27.277 because of the co Europe does not have 00:29:27.360 --> 00:29:30.317 its own power and has to import mostly 00:29:30.400 --> 00:29:35.837 of its power. Um do you have any messages for Europe 00:29:35.920 --> 00:29:38.637 related to this? >> Yeah, I mean I think so there are two 00:29:38.720 --> 00:29:40.557 sets of things right. is you know here 00:29:40.640 --> 00:29:43.437 we are in in Switzerland and I look at 00:29:43.520 --> 00:29:45.917 uh the the pharma or the financial 00:29:46.000 --> 00:29:51.277 sector you know obviously Switz they're uh they they do do a big job in in in 00:29:51.360 --> 00:29:54.237 this country as in in Europe but they're also international brands and 00:29:54.320 --> 00:29:58.797 international operations. So one thing that uh whenever I think about Europe is 00:29:58.880 --> 00:30:02.957 the Europeans are producing products and services that actually are going 00:30:03.040 --> 00:30:05.437 everywhere in the world and so therefore 00:30:05.520 --> 00:30:08.077 uh European competitiveness is about the 00:30:08.160 --> 00:30:12.477 competitiveness of their output globally not just in Europe. I think sometimes 00:30:12.560 --> 00:30:14.077 when you come to Europe there's a lot of 00:30:14.160 --> 00:30:16.717 conversation about just Europe. Uh but 00:30:16.800 --> 00:30:20.637 European economy is thrives and has you 00:30:20.720 --> 00:30:24.317 know thrived in the last whatever 200 years 300 years. the miracle of the west 00:30:24.400 --> 00:30:28.157 is fundamentally because of what has happened in Europe uh is because they 00:30:28.240 --> 00:30:31.597 were able to produce things that the world needed and so I would say that's 00:30:31.680 --> 00:30:33.757 number one and in order to do that you 00:30:33.840 --> 00:30:35.997 again I go back to the human capital 00:30:36.080 --> 00:30:38.797 here is just fantastic and world class 00:30:38.880 --> 00:30:41.757 uh you have to absolutely invest in uh 00:30:41.840 --> 00:30:46.477 producing uh you know having the energy and the tokens here which again you're 00:30:46.560 --> 00:30:50.317 attracting like as I said we're investing and others are investing uh 00:30:50.400 --> 00:30:54.317 the the data centers here so the question is what's that next generation 00:30:54.400 --> 00:30:58.637 of output that comes from here. Right? I always think about the German middle. 00:30:58.720 --> 00:31:03.117 Whenever I go to a jeweler or a dentist in the United States, I'm surrounded by 00:31:03.200 --> 00:31:05.197 German middle. Right. Totally. 00:31:05.280 --> 00:31:07.757 >> Um it's just unbelievable engineering 00:31:07.840 --> 00:31:11.197 provice of that country. uh and now the 00:31:11.280 --> 00:31:12.957 question and by the way that's the point 00:31:13.040 --> 00:31:15.517 that they are producing industrial 00:31:15.600 --> 00:31:19.277 products which today are built in into 00:31:19.360 --> 00:31:22.157 it all the intelligence as well that 00:31:22.240 --> 00:31:24.557 data right so I know whenever we come to 00:31:24.640 --> 00:31:26.637 Europe everyone's like talking about 00:31:26.720 --> 00:31:29.277 sovereignty and data this data that 00:31:29.360 --> 00:31:32.157 guess what Europe actually should be 00:31:32.240 --> 00:31:36.077 much more concerned about access to 00:31:36.160 --> 00:31:38.397 their industrial companies their 00:31:38.480 --> 00:31:41.197 financial services companies of data 00:31:41.280 --> 00:31:44.077 from you, US and the rest of the world. 00:31:44.160 --> 00:31:47.757 Uh as opposed to just thinking that somehow by protecting Europe, you're 00:31:47.840 --> 00:31:51.597 going to be competitive. You are only going to be competitive if the products 00:31:51.680 --> 00:31:54.237 coming out of Europe are globally 00:31:54.320 --> 00:31:58.637 competitive, right? >> Um and so that's I think what needs to 00:31:58.720 --> 00:32:00.717 change. Uh you know, Europe has led in 00:32:00.800 --> 00:32:03.357 privacy, that's fantastic, has led in 00:32:03.440 --> 00:32:08.157 many aspects of even safety around AI and what have you. And that's a feature 00:32:08.240 --> 00:32:12.477 uh that's great but you also have to complement it with by building locally 00:32:12.560 --> 00:32:14.877 and then also thinking globally what's 00:32:14.960 --> 00:32:17.437 the contribution this continent will 00:32:17.520 --> 00:32:19.757 make uh to the rest of the world which 00:32:19.840 --> 00:32:22.077 it has historically been a leader 00:32:22.160 --> 00:32:27.277 >> a leader so do you think the whole idea around sovereignty of data is that being 00:32:27.360 --> 00:32:31.197 misunderstood >> I I think that that when people talk 00:32:31.280 --> 00:32:33.437 about sovereignty 00:32:33.520 --> 00:32:38.557 first of all it's very important clearly And who owns and in a week like this 00:32:38.640 --> 00:32:40.157 it's more important. 00:32:40.240 --> 00:32:45.837 >> Uh but that said uh it is 00:32:45.920 --> 00:32:48.237 you have to kind of think about how what 00:32:48.320 --> 00:32:52.877 is sovereignty mean like for example in the AI era the topic that's least talked 00:32:52.960 --> 00:32:55.197 about but I feel will be most talked 00:32:55.280 --> 00:32:58.477 about in in this uh this calendar year 00:32:58.560 --> 00:33:01.117 will be the sovereignty of a firm. Just 00:33:01.200 --> 00:33:04.717 imagine if your firm you're not able to 00:33:04.800 --> 00:33:08.637 embed the tacit knowledge of the firm in 00:33:08.720 --> 00:33:12.317 a set of weights in a model that you 00:33:12.400 --> 00:33:15.037 control. By definition, you have no 00:33:15.120 --> 00:33:17.357 sovereignty. That means you're leaking 00:33:17.440 --> 00:33:22.237 enterprise value through some model company somewhere. In fact, that it's 00:33:22.320 --> 00:33:25.197 sort of fascinating that nobody's talking about that, right? It's like 00:33:25.280 --> 00:33:26.637 everybody's talking about everything 00:33:26.720 --> 00:33:29.757 else that is sort of you know outside of 00:33:29.840 --> 00:33:32.637 that whereas the most important thing is 00:33:32.720 --> 00:33:36.957 it really doesn't matter if you in fact the data center where it runs is the 00:33:37.040 --> 00:33:40.557 least important thing quite honestly but like even there first of all the data 00:33:40.640 --> 00:33:44.957 centers all are all over just because speed of light is a real constraint uh 00:33:45.040 --> 00:33:49.197 and so therefore the data centers will be spread yes uh you will have digital 00:33:49.280 --> 00:33:52.797 you'll be able to encrypt everything you'll be able to have the keys with you 00:33:52.880 --> 00:33:54.397 all of these are much more techn 00:33:54.480 --> 00:33:56.957 technically solve problems but the one 00:33:57.040 --> 00:34:00.237 problem that will only be solved is by 00:34:00.320 --> 00:34:05.357 you having much more sovereignty over the you know tacid knowledge uh and 00:34:05.440 --> 00:34:07.197 control over the models and it's not a 00:34:07.280 --> 00:34:10.237 one-way enterprise value transfer um and 00:34:10.320 --> 00:34:12.717 so to me I think sovereignty requires 00:34:12.800 --> 00:34:16.077 real thought on what is it um you know 00:34:16.160 --> 00:34:19.277 control of destiny means that your your 00:34:19.360 --> 00:34:21.517 ability to produce something that is 00:34:21.600 --> 00:34:24.637 unique is preserved uh David Ricardo was 00:34:24.720 --> 00:34:26.797 not wrong. There's comparative advantage 00:34:26.880 --> 00:34:29.277 in countries. Uh there is comparative 00:34:29.360 --> 00:34:32.397 advantage in firms that needs to be 00:34:32.480 --> 00:34:36.637 preserved even in the AI era. That's what'll give you real sovereignty. 00:34:36.720 --> 00:34:40.077 >> One last question. I know we're running out of time. 00:34:40.160 --> 00:34:44.077 Um in 5 years or 10 years, is there going to be one dominant model that 00:34:44.160 --> 00:34:48.637 we're all going to be using or are and how is Microsoft preparing for this? Are 00:34:48.720 --> 00:34:50.397 you going to be are we going to be using 00:34:50.480 --> 00:34:53.357 one model for for enterprise, one model 00:34:53.440 --> 00:34:55.997 for other other traits? 00:34:56.080 --> 00:34:58.237 >> You know, even in the last whatever 3 00:34:58.320 --> 00:35:00.397 years, four years that we've been at it, 00:35:00.480 --> 00:35:04.557 um the the reality at this point is it's 00:35:04.640 --> 00:35:08.157 a multimodel world, right? I mean the in 00:35:08.240 --> 00:35:12.477 fact if you think about it the in both 00:35:12.560 --> 00:35:16.397 there are going to be multiple models 00:35:16.480 --> 00:35:19.597 and the trick is really how do you take 00:35:19.680 --> 00:35:22.557 advantage of these multiple models and 00:35:22.640 --> 00:35:25.037 in fact build your own model by 00:35:25.120 --> 00:35:27.837 distilling these right uh so think of 00:35:27.920 --> 00:35:31.117 these models uh that you orchestrate to 00:35:31.200 --> 00:35:35.997 build your own model and more importantly you do what is described as 00:35:36.080 --> 00:35:37.517 orch orchestration or harness 00:35:37.600 --> 00:35:40.317 engineering. So the IP of any 00:35:40.400 --> 00:35:43.517 application or any firm is how do you 00:35:43.600 --> 00:35:48.317 use all these models with context engineering or your data? Yes. 00:35:48.400 --> 00:35:52.477 >> Right. So it's that three part. So can I bring in all the models by the way uh 00:35:52.560 --> 00:35:55.117 which is close source, open source, 00:35:55.200 --> 00:35:58.877 build my own model, orchestrate them and 00:35:58.960 --> 00:36:02.477 feed it my data to change the trajectory 00:36:02.560 --> 00:36:05.117 of some outcome that I care about. 00:36:05.200 --> 00:36:07.677 That's it. That's the entire picture. So 00:36:07.760 --> 00:36:09.837 you can do it in like oh I produce a 00:36:09.920 --> 00:36:12.237 particular product or service. Uh first 00:36:12.320 --> 00:36:17.037 I got to do better better job in sales or better job in R&D or better job in 00:36:17.120 --> 00:36:20.957 finance or what have you. And you take that outcome and then you say can I use 00:36:21.040 --> 00:36:23.517 all the models orchestrate them and feed 00:36:23.600 --> 00:36:26.077 it my context and then in as a result of 00:36:26.160 --> 00:36:29.037 it the reasoning traces are really 00:36:29.120 --> 00:36:31.917 leading to some capability and models 00:36:32.000 --> 00:36:34.877 that I control as my IP. As long as 00:36:34.960 --> 00:36:39.197 firms can answer that question, they're going to be getting ahead. 00:36:39.280 --> 00:36:41.677 >> Ladies and gentlemen, let's uh thank 00:36:41.760 --> 00:36:48.440 Satia, my friend. Thank you [applause] for 00:36:49.200 --> 00:36:53.037 and hopefully this is the beginning of many great dialogue and conversations 00:36:53.120 --> 00:36:56.157 here at the World Academic Forum. Thank you everyone. 00:36:56.240 --> 00:36:59.400 >> Thank you.