WEBVTT 00:00:00.080 --> 00:00:02.797 Think about it. The the way I come at 00:00:02.880 --> 00:00:06.797 this is not that um this has always been 00:00:06.880 --> 00:00:11.437 the arc of computation, right? You can sort of take it in the last 30 years or 00:00:11.520 --> 00:00:13.597 the last 70 years. It's always been 00:00:13.680 --> 00:00:16.077 about can you digitize 00:00:16.160 --> 00:00:19.917 artifacts on about people, places, and 00:00:20.000 --> 00:00:24.157 things and then build analytical and 00:00:24.240 --> 00:00:25.517 predictive power. [clears throat] Right? 00:00:25.600 --> 00:00:30.237 That's what the mainframes did. That's what the mini computer did. That's what 00:00:30.320 --> 00:00:34.317 the client server error did. That's what the web error did. The mobile cloud 00:00:34.400 --> 00:00:36.557 error did. So it like it depend 00:00:36.640 --> 00:00:39.677 irrespective of which paradigm or 00:00:39.760 --> 00:00:43.677 platform. It has been one continuous arc 00:00:43.760 --> 00:00:46.957 of saying let's make better sense of 00:00:47.040 --> 00:00:48.877 this world 00:00:48.960 --> 00:00:53.597 um by reasoning about it in digital form 00:00:53.680 --> 00:00:58.477 because in some sense once you have these artifacts in digital form you can 00:00:58.560 --> 00:01:01.277 use a more malleable resource like software 00:01:01.360 --> 00:01:01.997 >> right 00:01:02.080 --> 00:01:05.917 >> um which doesn't have the same type of 00:01:06.000 --> 00:01:08.877 you know I'll call it u marginal cost 00:01:08.960 --> 00:01:11.437 economics associated ated with it that 00:01:11.520 --> 00:01:14.317 allows us to then build more insight and 00:01:14.400 --> 00:01:17.597 more uh more capability and in that 00:01:17.680 --> 00:01:20.157 context AI I would say is of the same 00:01:20.240 --> 00:01:22.717 class at least like the web or the 00:01:22.800 --> 00:01:26.477 internet um or mobile or PC or the cloud 00:01:26.560 --> 00:01:30.637 or and maybe even greater and so to me 00:01:30.720 --> 00:01:33.917 right now where we are is you know let's 00:01:34.000 --> 00:01:36.157 take just what's happened with software 00:01:36.240 --> 00:01:38.717 engineering right which is one you know 00:01:38.800 --> 00:01:41.517 is knowledge work um you know you could 00:01:41.600 --> 00:01:43.837 say it's elite knowledge work 00:01:43.920 --> 00:01:46.797 >> it started off uh you know in fact my 00:01:46.880 --> 00:01:51.597 own belief in this generation of AI and its capability 00:01:51.680 --> 00:01:55.917 uh really got built up when I first saw GitHub copilot do code completions right 00:01:56.000 --> 00:02:00.477 so for the longest time we had the dream that if you're a software developer can 00:02:00.560 --> 00:02:02.877 you predict the next sort of word or the 00:02:02.960 --> 00:02:06.557 next uh line of code uh and suddenly it 00:02:06.640 --> 00:02:09.197 started working with these models u then 00:02:09.280 --> 00:02:11.197 You said okay if I can do that then can 00:02:11.280 --> 00:02:14.397 I actually go and bring back you know 00:02:14.480 --> 00:02:18.717 the flow for a software developer by going to a chat session and asking any 00:02:18.800 --> 00:02:23.117 question and it comes back with answers that then uh you can use in your coding 00:02:23.200 --> 00:02:26.797 flow right so that was the next thing then you said well if that's working can 00:02:26.880 --> 00:02:31.917 I assign it small tasks that was the agent mode uh now you have complete 00:02:32.000 --> 00:02:36.477 autonomous agents where you can give it your entire project right it can work uh 00:02:36.560 --> 00:02:39.597 you know >> 24/7 >> it can work for 24/7 7. I mean it's 00:02:39.680 --> 00:02:43.597 still we've got some ways to go for these things to remain coherent long 00:02:43.680 --> 00:02:46.077 time but nevertheless it's getting 00:02:46.160 --> 00:02:48.717 better and better and interestingly 00:02:48.800 --> 00:02:51.517 enough you look at it uh the software 00:02:51.600 --> 00:02:55.997 developer still is got a lot of agency in it right so that's why I kind of 00:02:56.080 --> 00:02:59.677 still think that you know going and thinking of these as somehow living 00:02:59.760 --> 00:03:03.597 outside of the realm of human agency is probably not the right way to think 00:03:03.680 --> 00:03:06.077 about it in fact the way to perhaps 00:03:06.160 --> 00:03:11.197 conceive it like it's let's say in early 80s If somebody had come to us and said 00:03:11.280 --> 00:03:15.757 what 4 billion people are going to wake up every morning and start typing you 00:03:15.840 --> 00:03:20.637 would have said why right you know we have a like we have a typist pool that's 00:03:20.720 --> 00:03:24.397 good enough we don't need 4 billion people but we that's what happened right 00:03:24.480 --> 00:03:27.277 we invented this entire class of thing 00:03:27.360 --> 00:03:29.357 called knowledge work where people 00:03:29.440 --> 00:03:33.037 started really using computers uh to go 00:03:33.120 --> 00:03:38.477 amplify what we were trying to achieve uh using software I think in the context 00:03:38.560 --> 00:03:40.877 of AI that same thing is going to happen. 00:03:40.960 --> 00:03:43.917 >> Um it's not like you know what is 00:03:44.000 --> 00:03:48.077 hardcore coding is going to remain hardcore coding forever. It's just that 00:03:48.160 --> 00:03:49.597 the levels of abstraction are going to 00:03:49.680 --> 00:03:52.637 change. Uh but we also are going to have 00:03:52.720 --> 00:03:55.117 code as output just like documents. In 00:03:55.200 --> 00:03:59.917 fact, one of Bill's things at Microsoft from the day I joined in '92 always was 00:04:00.000 --> 00:04:01.597 what's the real difference between a 00:04:01.680 --> 00:04:04.557 document, a website, and an application, 00:04:04.640 --> 00:04:07.277 right? It's the lack of sort of software 00:04:07.360 --> 00:04:09.917 that can transform itself. Interestingly 00:04:10.000 --> 00:04:11.997 enough, AI finally gives us that, right? 00:04:12.080 --> 00:04:15.837 Which is I can write a document. I can just say no, I don't want it as a 00:04:15.920 --> 00:04:19.837 document. I want it as a website. It'll just transform that document using code 00:04:19.920 --> 00:04:22.237 into a website. I say I don't like the 00:04:22.320 --> 00:04:23.997 website. I want an app. It'll write more 00:04:24.080 --> 00:04:27.197 code to transform it. So that reasoning 00:04:27.280 --> 00:04:29.757 and cap reasoning capabilities that 00:04:29.840 --> 00:04:32.077 prediction capabilities that ability to 00:04:32.160 --> 00:04:35.517 take action remain long-term coherent is 00:04:35.600 --> 00:04:40.477 all improving. Um and our job though is 00:04:40.560 --> 00:04:45.037 to parlay this like take even what you at BlackRock are doing right when you're 00:04:45.120 --> 00:04:49.197 bring taking something like say co-pilot plus Aladdin and bringing those things 00:04:49.280 --> 00:04:52.797 together [clears throat] >> to improve the productivity in the firm 00:04:52.880 --> 00:04:56.317 for the decisions you want to make right with your data 00:04:56.400 --> 00:04:58.237 >> I could just tell you from at our firm 00:04:58.320 --> 00:05:00.557 things that would take 12 hours to 00:05:00.640 --> 00:05:06.077 compute now takes minutes for us processing $14 trillion of other 00:05:06.160 --> 00:05:11.357 people's money with hundreds of thousands of different um mandates um we 00:05:11.440 --> 00:05:14.717 could do that instantaneous and we you know that to me if it wasn't for the 00:05:14.800 --> 00:05:18.877 technology and AI today we would not be able to function to the scale that we're 00:05:18.960 --> 00:05:22.717 operating >> that's right and so to me that one firm 00:05:22.800 --> 00:05:25.357 at a time one country at a time if we 00:05:25.440 --> 00:05:28.477 can really take these tokens and bend 00:05:28.560 --> 00:05:32.477 the curve of productivity then there is surplus everywhere and that's really the 00:05:32.560 --> 00:05:35.517 goal >> well surplus could be scary too does 00:05:35.600 --> 00:05:38.797 does surplus surplus mean fewer workers? 00:05:38.880 --> 00:05:43.037 What do we mean by surplus? And so, you know, the I'm going to tie that into my 00:05:43.120 --> 00:05:45.277 second question about AI diffusion. 00:05:45.360 --> 00:05:45.997 >> Yeah. 00:05:46.080 --> 00:05:48.877 >> To me, the the whole realization of AI 00:05:48.960 --> 00:05:52.317 for any society and also for a more 00:05:52.400 --> 00:05:55.117 balanced world is making sure that it's 00:05:55.200 --> 00:05:57.837 diffused and accessible and available 00:05:57.920 --> 00:06:00.157 across the world. So what you know can 00:06:00.240 --> 00:06:02.797 you describe how this process of 00:06:02.880 --> 00:06:07.997 diffusion uh across economies across companies across people and countries 00:06:08.080 --> 00:06:11.997 how does that play out? >> Yeah I think 00:06:12.080 --> 00:06:16.317 that this is the real question right because one of the uh things right now 00:06:16.400 --> 00:06:18.957 the zeitgeist is a little bit about the 00:06:19.040 --> 00:06:22.397 admiration for AI in its abstract form 00:06:22.480 --> 00:06:26.397 or as as technology. [clears throat] uh 00:06:26.480 --> 00:06:28.637 but I think we as even a global 00:06:28.720 --> 00:06:31.517 community um have to get to a point 00:06:31.600 --> 00:06:34.477 where we are using this to do something 00:06:34.560 --> 00:06:38.157 useful uh that changes uh the outcomes 00:06:38.240 --> 00:06:42.397 of people and communities and countries and industries right otherwise I don't 00:06:42.480 --> 00:06:44.877 think uh this makes much sense right in 00:06:44.960 --> 00:06:47.197 fact I would say we will quickly lose 00:06:47.280 --> 00:06:49.837 even the social permission 00:06:49.920 --> 00:06:52.477 uh to actually take something like uh 00:06:52.560 --> 00:06:56.877 energy which is a scarce resource and use it to generate these tokens if these 00:06:56.960 --> 00:07:00.637 tokens are not improving health outcomes, education outcomes, public 00:07:00.720 --> 00:07:05.037 sector efficiency, private sector competitiveness across all sectors, 00:07:05.120 --> 00:07:07.597 small and large, right? And that to me 00:07:07.680 --> 00:07:10.637 is ultimately the goal. So therefore I 00:07:10.720 --> 00:07:13.677 think really diffusion is everything. 00:07:13.760 --> 00:07:16.237 And so the way it happens is let's sort 00:07:16.320 --> 00:07:19.997 of unpack this uh on the supply side 00:07:20.080 --> 00:07:22.157 what needs to happen in each country is 00:07:22.240 --> 00:07:26.077 the tokens per dollar per watt have to 00:07:26.160 --> 00:07:31.117 sort of monotonically get more efficient and better right so to some degree even 00:07:31.200 --> 00:07:34.717 what we're trying to do with the investments the two firms are doing uh 00:07:34.800 --> 00:07:39.117 around the world is to just say that like let's make sure that the supply is 00:07:39.200 --> 00:07:41.597 there which is uh everything from the 00:07:41.680 --> 00:07:46.797 chips on down ultimately to these token factories that get deployed everywhere. 00:07:46.880 --> 00:07:50.717 By the way, there's not one token factory. This token factory is the first 00:07:50.800 --> 00:07:54.157 thing that's going to be diffused all around the world. It's just like 00:07:54.240 --> 00:07:57.117 electricity, right? You just need a 00:07:57.200 --> 00:08:01.917 ubiquitous grid of uh energy and tokens 00:08:02.000 --> 00:08:04.477 that then will power the rest of the 00:08:04.560 --> 00:08:06.157 economy. Right? So that's I think one 00:08:06.240 --> 00:08:09.357 side of it. Then the demand side of this 00:08:09.440 --> 00:08:12.397 is a little bit like every firm has to 00:08:12.480 --> 00:08:15.677 start by using it. If I look back even 00:08:15.760 --> 00:08:18.717 you know when the PCs first came out or 00:08:18.800 --> 00:08:22.957 the personal computing era started I I loved you know I think Jobs had a nice 00:08:23.040 --> 00:08:27.837 metaphor he called it the bicycle for the mind. Uh Bill had a metaphor which I 00:08:27.920 --> 00:08:31.037 remember was like information at your fingertips, right? These two metaphors 00:08:31.120 --> 00:08:34.957 were great like which allowed us to say that's what it is. It's a tool that I 00:08:35.040 --> 00:08:36.957 will use to get information at my 00:08:37.040 --> 00:08:38.957 fingertips. I'll use it as a cognitive 00:08:39.040 --> 00:08:42.797 amplifier. Now I think that's what we 00:08:42.880 --> 00:08:45.997 have. But you know 10x 100x right? So in 00:08:46.080 --> 00:08:48.877 some sense you as a as every knowledge 00:08:48.960 --> 00:08:52.077 worker you now have access to infinite 00:08:52.160 --> 00:08:54.077 minds. That's the way I think about it. 00:08:54.160 --> 00:08:58.077 Right? So there's a Turing award winner uh called Raj Ready who had this nice 00:08:58.160 --> 00:09:02.717 metaphor of AI and he had this long before uh even generative AI he said 00:09:02.800 --> 00:09:05.037 either either it's a cognitive amplifier 00:09:05.120 --> 00:09:07.757 or it's a guardian angel right so if you 00:09:07.840 --> 00:09:11.517 think of AI as that um then that in the 00:09:11.600 --> 00:09:15.677 global workforce right when a doctor can 00:09:15.760 --> 00:09:20.077 get to a patient spend more time with the patient because the AI is doing the 00:09:20.160 --> 00:09:22.317 transcription and entering the records 00:09:22.400 --> 00:09:25.197 in the EMR system entering the right 00:09:25.280 --> 00:09:27.917 billing code so that the health care uh 00:09:28.000 --> 00:09:30.077 you know industry is better served 00:09:30.160 --> 00:09:33.117 across the payer the provider and uh and 00:09:33.200 --> 00:09:35.997 the patient ultimately right that's an 00:09:36.080 --> 00:09:38.077 an outcome that I think all of us can 00:09:38.160 --> 00:09:41.037 benefit from so I feel ultimately it's 00:09:41.120 --> 00:09:43.597 going to require real leadership on the 00:09:43.680 --> 00:09:46.157 private sector and the public sector to 00:09:46.240 --> 00:09:48.957 ensure the diffusion happens and the one 00:09:49.040 --> 00:09:52.077 thing I'll mention Larry is skilling 00:09:52.160 --> 00:09:56.077 right so In some sense the thing that 00:09:56.160 --> 00:09:59.837 diffusion is very strongly correlated to 00:09:59.920 --> 00:10:02.797 one thing alone which is how broadly are 00:10:02.880 --> 00:10:07.037 people skilled in using this. Um and 00:10:07.120 --> 00:10:09.277 interestingly enough, I think if mobile 00:10:09.360 --> 00:10:12.637 has taught us one thing is it it's 00:10:12.720 --> 00:10:16.637 actually distinct from what happened in the PC, right? Uh I remember even 00:10:16.720 --> 00:10:18.957 growing up in the global south, uh there 00:10:19.040 --> 00:10:21.757 used to be a real relationship between 00:10:21.840 --> 00:10:25.117 learning Excel skills or word skills and 00:10:25.200 --> 00:10:28.717 getting a job. Um you know, right now, 00:10:28.800 --> 00:10:33.277 um what's the model in in mobile? It's kind of created the same opportunity, 00:10:33.360 --> 00:10:35.677 but it's been a lot more consumptionled. 00:10:35.760 --> 00:10:40.077 It's these creator economy and what have you, but it has not been about sort of, 00:10:40.160 --> 00:10:43.677 oh wow, here's how you get a healthcare job or here is how you get a finance job 00:10:43.760 --> 00:10:45.837 or here is how you get, you know, you 00:10:45.920 --> 00:10:48.477 get ahead professionally. 00:10:48.560 --> 00:10:51.597 Um, and that needs to come back, right? 00:10:51.680 --> 00:10:53.037 People need to say, oh, I pick up this 00:10:53.120 --> 00:10:56.077 AI skill and now I'm a better provider 00:10:56.160 --> 00:10:58.877 of some product or service in the real 00:10:58.960 --> 00:11:00.957 economy. So it's [cough] it's very easy 00:11:01.040 --> 00:11:03.757 to see how mobile and the diffusion of 00:11:03.840 --> 00:11:06.077 mobile how it transformed economies 00:11:06.160 --> 00:11:09.117 especially in the global south. How does 00:11:09.200 --> 00:11:11.597 how does this you know to me I I I just 00:11:11.680 --> 00:11:14.637 read a research report that said um the 00:11:14.720 --> 00:11:17.597 applications for AI so far are heavily 00:11:17.680 --> 00:11:21.837 weighted towards those who are educated or educated economies. 00:11:21.920 --> 00:11:26.957 And so does that create that you know more of a bifurcation more polarization? 00:11:27.040 --> 00:11:31.517 How do we ensure that that that diffusion is spread evenly? How do we 00:11:31.600 --> 00:11:33.117 make sure that we're not [clears throat] 00:11:33.200 --> 00:11:39.037 leaving major portions of society or the world behind because I think that's 00:11:39.120 --> 00:11:42.077 that's going to [clears throat] be the big issue for us going forward. Yeah. So 00:11:42.160 --> 00:11:43.677 it's it's it's interesting right this is 00:11:43.760 --> 00:11:46.797 one of those times when 00:11:46.880 --> 00:11:50.317 uh by definition and because of the 00:11:50.400 --> 00:11:54.317 rails that have been established you know as you said right which is 00:11:54.400 --> 00:11:57.197 >> uh what's happened with mobile as well 00:11:57.280 --> 00:12:01.677 as what's happened with um uh you know essentially connectivity 00:12:01.760 --> 00:12:05.277 >> right >> you have the ability to sort of deliver 00:12:05.360 --> 00:12:08.637 the tokens pretty evenly around the world >> right 00:12:08.720 --> 00:12:13.597 >> a lot more so than let's say uh the PC C era or even the beginning of the mobile 00:12:13.680 --> 00:12:15.277 era, right? Because it took a long time 00:12:15.360 --> 00:12:17.597 for even the mo smartphone in particular 00:12:17.680 --> 00:12:21.197 to penetrate um all of the world whereas 00:12:21.280 --> 00:12:23.597 now it's not the case, right? These 00:12:23.680 --> 00:12:27.037 models and their outputs are pretty much 00:12:27.120 --> 00:12:28.797 available everywhere. And so the 00:12:28.880 --> 00:12:34.237 question to me is what's the use cases that make sense, 00:12:34.320 --> 00:12:37.677 right? It's one, in fact, one of the demos I always go back to. I think this 00:12:37.760 --> 00:12:40.157 was even in the beginning of 23 was a 00:12:40.240 --> 00:12:43.037 rural Indian farmer was able to use a 00:12:43.120 --> 00:12:46.317 bot built on I think a very early GPT3 00:12:46.400 --> 00:12:50.317 or 25 even uh essentially to reason over 00:12:50.400 --> 00:12:52.477 some farm subsidies that he had heard 00:12:52.560 --> 00:12:54.957 about in a local language and had it 00:12:55.040 --> 00:12:58.557 even in that very early days uh have it 00:12:58.640 --> 00:13:00.557 even show some agentic behavior, right? 00:13:00.640 --> 00:13:02.477 Like go complete a form for me. So in 00:13:02.560 --> 00:13:04.477 some sense it took uh you know it 00:13:04.560 --> 00:13:09.037 brought back agency to someone uh who 00:13:09.120 --> 00:13:13.197 perhaps didn't have that because the technology was so much more accessible. 00:13:13.280 --> 00:13:15.997 So I I do think it's in our hands even 00:13:16.080 --> 00:13:19.197 in the global south to use it uh to 00:13:19.280 --> 00:13:21.757 create I would say more of that 00:13:21.840 --> 00:13:26.887 opportunity where there isn't one. Um but I think what the necessary 00:13:26.970 --> 00:13:30.637 [clears throat] conditions still are do you have uh the 00:13:30.720 --> 00:13:35.277 capital investment being put in uh do you even have an environment for capital 00:13:35.360 --> 00:13:39.277 because in an interesting way we are for example as hyperscalers investing all 00:13:39.360 --> 00:13:43.517 over right including the global south uh so as long as there's an environment 00:13:43.600 --> 00:13:46.477 which attracts the capital investment >> and you see the demand 00:13:46.560 --> 00:13:49.437 >> and you see and then yeah the demand is there yeah 00:13:49.520 --> 00:13:53.677 >> um and so the question is how do you have a set of policies that allow for 00:13:53.760 --> 00:13:57.997 both the capital to come in for it to find nexus where there are certain 00:13:58.080 --> 00:14:00.237 things by the way private capital can do 00:14:00.320 --> 00:14:02.157 certain things that public capital only 00:14:02.240 --> 00:14:05.197 can do for example the grid right it's 00:14:05.280 --> 00:14:10.317 not I mean grid in most countries is sort of fundamentally driven by governments 00:14:10.400 --> 00:14:12.317 >> public >> and public and so if you [clears throat] 00:14:12.400 --> 00:14:14.637 don't have a sophisticated sort or 00:14:14.720 --> 00:14:19.517 rather if you don't have a a real approach to modernizing the grid uh that 00:14:19.600 --> 00:14:22.957 will hold things back I mean there's a lot of talk about behind the meter and 00:14:23.040 --> 00:14:25.677 so on and Yes, there's some amount of that we can do ourselves. 00:14:25.760 --> 00:14:27.837 >> We can do that in the US. Many countries can't. 00:14:27.920 --> 00:14:29.437 >> Exactly. And it's not long-term 00:14:29.520 --> 00:14:31.357 scalable, right? I mean, like to me, a 00:14:31.440 --> 00:14:34.877 long-term scalable solution is to have 00:14:34.960 --> 00:14:39.677 uh you know, all of these token factories, part of the real economy, 00:14:39.760 --> 00:14:44.317 connected to the grid, connected to the telco network, delivering uh just like 00:14:44.400 --> 00:14:46.317 we delivered bits, you have to deliver 00:14:46.400 --> 00:14:49.357 tokens plus bits. Um and that's kind of 00:14:49.440 --> 00:14:53.757 what's going to drive an app scale whether it's in the global south or in 00:14:53.840 --> 00:14:57.037 uh on the developed world. >> So so many people talk about there may 00:14:57.120 --> 00:14:59.037 be an AI bubble. I mean the most 00:14:59.120 --> 00:15:00.397 important thing that we see as an 00:15:00.480 --> 00:15:04.637 investor is the the democratization of 00:15:04.720 --> 00:15:07.437 technology is and the diffusion of that 00:15:07.520 --> 00:15:09.997 technology really does then transform 00:15:10.080 --> 00:15:15.117 the demand and the the companies or the countries that diffuse it fastest are 00:15:15.200 --> 00:15:16.637 going to be the ultimate winners. about 00:15:16.720 --> 00:15:18.477 the technology creator. 00:15:18.560 --> 00:15:22.717 >> That's that's you know it's it's it's 00:15:22.800 --> 00:15:25.117 for this not to be a bubble 00:15:25.200 --> 00:15:25.677 >> y 00:15:25.760 --> 00:15:29.917 >> by definition it requires that the 00:15:30.000 --> 00:15:32.157 benefits of this are much more evenly 00:15:32.240 --> 00:15:35.357 spread. I mean I think a tellt tell sign 00:15:35.440 --> 00:15:38.717 of if it's a bubble would be if all 00:15:38.800 --> 00:15:41.917 we're talking about are the tech firms. 00:15:42.000 --> 00:15:45.037 Uh right? If uh all we talk about is 00:15:45.120 --> 00:15:49.037 what's happening to the technology side that then that's by day you know it's 00:15:49.120 --> 00:15:53.437 just purely supply side >> right >> uh ultimately if we are not talking 00:15:53.520 --> 00:15:57.597 about wow here is a drug comp you know drug that was sort of uh brought into 00:15:57.680 --> 00:16:01.757 the market that's super successful because it was uh AI accelerated the 00:16:01.840 --> 00:16:03.757 clinical trial it's not even the magical 00:16:03.840 --> 00:16:05.757 molecule right it's kind of even the 00:16:05.840 --> 00:16:08.877 rest of what is uh needed in order to 00:16:08.960 --> 00:16:11.517 make something much more relevant right 00:16:11.600 --> 00:16:16.717 um and So the more [clears throat] we have uh and by the way it's happening 00:16:16.800 --> 00:16:18.397 right. So I'm not sort of saying that 00:16:18.480 --> 00:16:21.277 that's why I'm much more confident that 00:16:21.360 --> 00:16:23.757 this is a technology that will in fact 00:16:23.840 --> 00:16:27.117 build on the rails of cloud and mobile 00:16:27.200 --> 00:16:30.287 diffuse faster and bend the productivity 00:16:30.370 --> 00:16:34.397 [clears throat] curve and bring local surplus and 00:16:34.480 --> 00:16:36.957 economic growth all around the world. 00:16:37.040 --> 00:16:41.277 Not just economic growth driven by capital expenses. 00:16:41.360 --> 00:16:46.557 uh right because that's it's a narrow point in time uh calculation. right now 00:16:46.640 --> 00:16:48.797 that's what we're seeing more >> that's what we're seeing in you know you 00:16:48.880 --> 00:16:50.317 know in in the developed world in 00:16:50.400 --> 00:16:53.917 particular uh but remember my capital 00:16:54.000 --> 00:16:57.437 like that the one thing that you know is definitely we spending a lot of it in 00:16:57.520 --> 00:17:00.797 the United States but 50% of it is also all over the world 00:17:00.880 --> 00:17:04.637 >> right >> um and so interesting enough it depends 00:17:04.720 --> 00:17:09.037 on uh demand all over the world and the demand all over the world will only be 00:17:09.120 --> 00:17:13.357 there if there is local surplus all over the world and so that's sort of the way 00:17:13.440 --> 00:17:17.357 I see the equation >> so let's drill down a little more. As AI 00:17:17.440 --> 00:17:21.357 diffuses, obviously organizations, companies, 00:17:21.440 --> 00:17:23.757 governments are going to have to evolve. 00:17:23.840 --> 00:17:27.117 Now getting to the demand side. So how 00:17:27.200 --> 00:17:28.477 do you think the structure of 00:17:28.560 --> 00:17:32.397 organizations is changing in an AI world 00:17:32.480 --> 00:17:35.837 across roles, across teams, management? 00:17:35.920 --> 00:17:39.357 I'm I'm sure um Microsoft has evolved 00:17:39.440 --> 00:17:42.237 itself. So it probably be good to tell 00:17:42.320 --> 00:17:44.557 the audience how do you see this 00:17:44.640 --> 00:17:49.437 diffusion occur in the utilization at the corporate level or at a government 00:17:49.520 --> 00:17:53.357 level that which ultimately then creates that demand which eliminates any fears 00:17:53.440 --> 00:17:55.837 and bubbles. >> Yeah. No, I think it's probably one of 00:17:55.920 --> 00:17:58.157 the the the big challenges with all of 00:17:58.240 --> 00:18:02.717 these new technologies is when uh work 00:18:02.800 --> 00:18:06.637 work artifact and work flow changes. 00:18:06.720 --> 00:18:10.637 uh that means we as firms have to change 00:18:10.720 --> 00:18:15.117 how we work. In fact, [clears throat] I remember meeting um uh the CEO of 00:18:15.200 --> 00:18:17.277 General Ali, you know, a few years back 00:18:17.360 --> 00:18:22.947 and he was describing he had joined um uh the firm, you know, prec 00:18:23.030 --> 00:18:25.997 >> [clears throat] >> era and uh uh and he was describing how, 00:18:26.080 --> 00:18:27.677 for example, they worked with their 00:18:27.760 --> 00:18:30.957 agents in the field uh with faxes, inter 00:18:31.040 --> 00:18:34.317 office memos and um and and suddenly the 00:18:34.400 --> 00:18:38.397 PC showed up and people would then put a spreadsheet in an email and send it 00:18:38.480 --> 00:18:40.717 around and the entire workflow and the 00:18:40.800 --> 00:18:43.197 work process has changed right so 00:18:43.280 --> 00:18:46.077 similarly I think with AI uh you are 00:18:46.160 --> 00:18:51.037 going to start seeing uh actual change in how workflow happens right I mean 00:18:51.120 --> 00:18:54.317 even [clears throat] in fact for me coming to Davos you know 00:18:54.400 --> 00:18:57.037 whatever 50 bilateral meetings I have 00:18:57.120 --> 00:19:00.077 preparing for those uh had a particular 00:19:00.160 --> 00:19:04.957 workflow right which is uh there is to be my field team would prepare notes and 00:19:05.040 --> 00:19:09.037 that would come to my HQ and that would get further refined and nothing had 00:19:09.120 --> 00:19:11.597 really changed right since I joined in 00:19:11.680 --> 00:19:16.637 '92 to essentially even a few years back. Whereas now I just go to co-pilot 00:19:16.720 --> 00:19:20.957 and say hey I'm meeting Larry. Please give me a brief and it comes back and 00:19:21.040 --> 00:19:25.037 gives me by the way the one nice thing is it gives me a 360 right? It knows 00:19:25.120 --> 00:19:29.437 what we're doing with you as a client what we're doing as a client of yours 00:19:29.520 --> 00:19:31.677 and everything in between [clears throat] as an investment. It's 00:19:31.760 --> 00:19:34.957 so it captures even information unlike 00:19:35.040 --> 00:19:39.197 anything else. In fact, what I do is I take that and immediately share that 00:19:39.280 --> 00:19:42.877 back with all my colleagues across all the functions. Right? Think about it. 00:19:42.960 --> 00:19:45.677 It's a complete inversion of how 00:19:45.760 --> 00:19:50.077 information is flowing in the organization. It's not like this classic 00:19:50.160 --> 00:19:53.357 we have an organization, we have departments, we have these 00:19:53.440 --> 00:19:55.437 specializations and the information 00:19:55.520 --> 00:19:58.557 trickles up. No, no, no. It actually it 00:19:58.640 --> 00:20:02.237 flattens the entire information flow. So 00:20:02.320 --> 00:20:04.877 once you start having that you have to 00:20:04.960 --> 00:20:08.317 redesign structurally. Uh so the current 00:20:08.400 --> 00:20:12.237 structure may not make sense. Um because 00:20:12.320 --> 00:20:16.077 you want people to be able to work in a 00:20:16.160 --> 00:20:18.637 way that allows them to have this 00:20:18.720 --> 00:20:23.597 information flow freely. So what all this leads me to if I had to sort of say 00:20:23.680 --> 00:20:25.597 what's the formula? The formula I think 00:20:25.680 --> 00:20:27.677 it starts with the mindset. So the 00:20:27.760 --> 00:20:31.917 mindset we as leaders should have is we 00:20:32.000 --> 00:20:34.957 need to think about changing the work 00:20:35.040 --> 00:20:39.517 the workflow with the technology then that needs skill set. [clears throat] So 00:20:39.600 --> 00:20:43.677 you can't sort of talk about this in the abstract. You got to use it like so if 00:20:43.760 --> 00:20:45.837 I'm not using the >> you have to trust it. 00:20:45.920 --> 00:20:49.997 >> You have to trust it. You have to use it. You have to learn even how to put 00:20:50.080 --> 00:20:53.997 the guard rails to trust it. Right? So you can't again you can't just be afraid 00:20:54.080 --> 00:20:56.877 of it. uh it's going to it's going to be 00:20:56.960 --> 00:20:59.677 diffused. So the question is as a firm 00:20:59.760 --> 00:21:02.877 you have to use it to learn how to even 00:21:02.960 --> 00:21:05.037 uh put the guard rails that allow you to 00:21:05.120 --> 00:21:08.237 be able to trust it. So skills uh so 00:21:08.320 --> 00:21:10.557 mindset skills the other big 00:21:10.640 --> 00:21:14.077 consideration um really is how do you 00:21:14.160 --> 00:21:17.197 make sure you have the data set that 00:21:17.280 --> 00:21:20.317 you're feeding like context like it's 00:21:20.400 --> 00:21:22.877 kind of like you have a new intelligence 00:21:22.960 --> 00:21:25.437 layer but the intelligence layer is only 00:21:25.520 --> 00:21:29.117 as good as the context you give it. So 00:21:29.200 --> 00:21:33.917 people describe it even as context engineering but that is what firms do 00:21:34.000 --> 00:21:37.997 right if you think about what do firms do it's all about the tacit knowledge we 00:21:38.080 --> 00:21:43.357 have by working as people in various department and moving paper and 00:21:43.440 --> 00:21:46.877 information so the question is how do you really have this AI also have that 00:21:46.960 --> 00:21:49.357 context so these are sort of some of the 00:21:49.440 --> 00:21:52.157 new things that have to percolate 00:21:52.240 --> 00:21:56.477 throughout an organization uh to take advantage in fact that's why I think you 00:21:56.560 --> 00:21:59.117 you're going to see that challenge of 00:21:59.200 --> 00:22:03.677 why am I not seeing immediate results in productivity because you have to do the 00:22:03.760 --> 00:22:06.877 hard work. In fact, that's why it's not going to be at some you know it's going 00:22:06.960 --> 00:22:10.077 to there are going to be firmwide differences. They're going to there 00:22:10.160 --> 00:22:13.037 could [clears throat] be sectorwide differences but it's going to 00:22:13.120 --> 00:22:17.997 fundamentally be because of the leadership will in an organization. 00:22:18.080 --> 00:22:22.877 >> Do you see the applications being used across large companies and medium and 00:22:22.960 --> 00:22:26.477 small companies or is it still the domain of mostly the large companies at 00:22:26.560 --> 00:22:28.717 this moment? I I think that what you're 00:22:28.800 --> 00:22:32.157 seeing is it's easier the because if you 00:22:32.240 --> 00:22:36.237 have a green sort of um uh you know if 00:22:36.320 --> 00:22:39.037 you start fresh it's easier to adopt 00:22:39.120 --> 00:22:43.997 these tools and you construct your organization knowing that these tools 00:22:44.080 --> 00:22:45.917 exist. So >> is it a barbell then? 00:22:46.000 --> 00:22:50.157 >> It is a barbell. So small companies that are just starting use that platform 00:22:50.240 --> 00:22:53.467 >> 100%. And I think in fact I would say even for large organizations there's 00:22:53.550 --> 00:22:56.717 [clears throat] a fundamental challenge right because unless and until your rate 00:22:56.800 --> 00:22:59.597 of change keeps up with >> right 00:22:59.680 --> 00:23:02.077 >> uh with with what is possible uh you're 00:23:02.160 --> 00:23:04.557 you're going to get schooled by someone 00:23:04.640 --> 00:23:09.277 small being able to achieve scale because of these tools. So but I think 00:23:09.360 --> 00:23:12.557 scale like large organizations have an inherent strength. You have the 00:23:12.640 --> 00:23:14.397 relationships, you have the data, you 00:23:14.480 --> 00:23:17.997 have um you have knowhow, but the bottom 00:23:18.080 --> 00:23:20.557 line is if you don't translate that with 00:23:20.640 --> 00:23:25.437 a new production function, uh then you really will be stuck. And so therefore 00:23:25.520 --> 00:23:29.037 the change management challenge for large organizations is going to be 00:23:29.120 --> 00:23:33.517 bigger. The structural challenge for small organizations of how to overcome 00:23:33.600 --> 00:23:36.717 scale issues is going to be harder. So it's sort of the two sides. in an 00:23:36.800 --> 00:23:38.237 interesting way. It's going to be a very 00:23:38.320 --> 00:23:41.917 competitively intense world uh where 00:23:42.000 --> 00:23:44.077 neither side like whether you're a new 00:23:44.160 --> 00:23:46.557 entrant or an incumbent can't take it as 00:23:46.640 --> 00:23:50.557 like I I can just coast. What about 00:23:50.640 --> 00:23:54.317 country to country? Are you seeing big differences in how the applications are 00:23:54.400 --> 00:23:57.357 being used? Is it is AI still the domain 00:23:57.440 --> 00:24:02.157 of developed countries or is it becoming rapidly a domain of all countries? I I 00:24:02.240 --> 00:24:04.237 I'm seeing there are two things I would 00:24:04.320 --> 00:24:06.717 say Larry as I travel around the world 00:24:06.800 --> 00:24:11.197 the quality of um whether it's the 00:24:11.280 --> 00:24:13.677 knowhow the software developers the 00:24:13.760 --> 00:24:15.277 startups 00:24:15.360 --> 00:24:19.037 um or even large or large organizations 00:24:19.120 --> 00:24:22.557 it's not that different it's fascinating you can show up in Jakarta you can show 00:24:22.640 --> 00:24:24.797 up in Istanbul you can show up in Mexico 00:24:24.880 --> 00:24:27.277 City it's not that different than 00:24:27.360 --> 00:24:29.837 showing up even in say Seattle or San 00:24:29.920 --> 00:24:32.077 Francisco right it's not uh for the 00:24:32.160 --> 00:24:35.197 first time just because access to what's 00:24:35.280 --> 00:24:39.577 happening uh is there that said at 00:24:39.660 --> 00:24:43.517 [clears throat] scale the commitment to 00:24:43.600 --> 00:24:46.557 using this the risk capital being there 00:24:46.640 --> 00:24:49.837 the large companies pushing it hard I 00:24:49.920 --> 00:24:53.437 mean I you know again the US you know is 00:24:53.520 --> 00:24:56.157 in fact if I compare it uh take 00:24:56.240 --> 00:24:59.437 financial sector if financial sector's 00:24:59.520 --> 00:25:01.117 adoption of the cloud 00:25:01.200 --> 00:25:03.997 versus AI night and day, right? Because 00:25:04.080 --> 00:25:07.357 in an interesting way, it's much faster 00:25:07.440 --> 00:25:11.837 uh when it comes to AI versus it was with the cloud and cloud because for a 00:25:11.920 --> 00:25:15.197 variety of reasons, >> regulatory issues too until the 00:25:15.280 --> 00:25:20.877 regulators allowed banks to bring their data off out of campus that was a big 00:25:20.960 --> 00:25:23.677 issue. >> Yeah. So I would say I think wherever [clears throat] 00:25:23.760 --> 00:25:26.637 you know so in the west in particular in 00:25:26.720 --> 00:25:30.717 the US uh there is clearly a real I 00:25:30.800 --> 00:25:33.357 would say more of an energy around it in 00:25:33.440 --> 00:25:36.237 terms of going and using it. Uh but it's 00:25:36.320 --> 00:25:41.597 sort of a lot more uniformly spreading around the world than any technology at 00:25:41.680 --> 00:25:44.237 least I've seen. But are you are [clears throat] you you mentioned about 00:25:44.320 --> 00:25:47.517 the power the grid is that going to be 00:25:47.600 --> 00:25:50.557 one of the determinants of of the 00:25:50.640 --> 00:25:53.117 accessibility if you do not have cheap 00:25:53.200 --> 00:25:56.397 power it the demand is costly 00:25:56.480 --> 00:25:59.597 >> 100%. So if you sort of look at the 00:25:59.680 --> 00:26:01.997 tokens per dollar per watt right which I 00:26:02.080 --> 00:26:03.517 think in some [clears throat] sense I 00:26:03.600 --> 00:26:07.197 would claim that GDP growth in any place 00:26:07.280 --> 00:26:11.117 will be directly correlated like you if you sort of buy my entire argument that 00:26:11.200 --> 00:26:15.037 look we've got a new commodity its tokens >> right 00:26:15.120 --> 00:26:19.677 >> and the job of every economy uh and every firm in the economy is to 00:26:19.760 --> 00:26:21.757 translate these tokens into economic 00:26:21.840 --> 00:26:24.317 growth then if you have a cheaper 00:26:24.400 --> 00:26:29.597 commodity it's better uh And so that's sort of what why there's tokens per 00:26:29.680 --> 00:26:33.277 dollar per watt. And by the way, there are many many elements to this, right? 00:26:33.360 --> 00:26:37.437 Which is uh it's not just um the production side. That's why I think even 00:26:37.520 --> 00:26:40.237 having the grid is important. Um uh 00:26:40.320 --> 00:26:42.317 construction costs, right? So if you 00:26:42.400 --> 00:26:45.437 like if you think about the total TCO uh 00:26:45.520 --> 00:26:49.757 everything it's like the how are you a cheap producer of energy? Can you build 00:26:49.840 --> 00:26:52.317 the data centers? Uh then what's the 00:26:52.400 --> 00:26:55.037 cost curve uh of the silicon and the 00:26:55.120 --> 00:26:57.757 systems? uh the and by the way look at 00:26:57.840 --> 00:27:00.797 the token pricing right token pricing 00:27:00.880 --> 00:27:04.557 basically drops by you know a half uh 00:27:04.640 --> 00:27:07.997 every 3 months uh I mean this is a so 00:27:08.080 --> 00:27:10.797 how so that that's why I think you can 00:27:10.880 --> 00:27:14.157 sort of really plot how you use the 00:27:14.240 --> 00:27:18.717 tokens to create surplus knowing that you have a commodity that's whose prices 00:27:18.800 --> 00:27:21.917 are just going to monotonically come down in a pretty fast curve 00:27:22.000 --> 00:27:24.957 >> we're sitting in Europe uh and there is 00:27:25.040 --> 00:27:27.197 a real fear 00:27:27.280 --> 00:27:29.277 because of the co Europe does not have 00:27:29.360 --> 00:27:32.317 its own power. It has to import mostly 00:27:32.400 --> 00:27:37.837 of its power. Um do you have any messages for Europe 00:27:37.920 --> 00:27:40.557 related to this? >> Yeah, I mean I think so there are two 00:27:40.640 --> 00:27:42.397 sets of things right. one is you know 00:27:42.480 --> 00:27:44.877 here we are in in Switzerland and I look 00:27:44.960 --> 00:27:47.837 at uh the the pharma or the financial 00:27:47.920 --> 00:27:50.637 sector you know obviously Switz they're 00:27:50.720 --> 00:27:54.877 uh they they do do a big job in in in this country as in in Europe but they're 00:27:54.960 --> 00:27:57.757 also international brands and international operations. So one thing 00:27:57.840 --> 00:28:00.797 that uh whenever I think about Europe is 00:28:00.880 --> 00:28:04.957 the Europeans are producing products and services that actually are going 00:28:05.040 --> 00:28:07.437 everywhere in the world and so therefore 00:28:07.520 --> 00:28:12.637 uh European competitiveness is about the competitiveness of their output globally 00:28:12.720 --> 00:28:15.997 not just in Europe. I think sometimes when you come to Europe there's a lot of 00:28:16.080 --> 00:28:18.637 conversation about just Europe. Uh but 00:28:18.720 --> 00:28:22.557 European economy is thrives and has you 00:28:22.640 --> 00:28:26.237 know thrived in the last whatever 200 years 300 years. the miracle of the west 00:28:26.320 --> 00:28:30.157 is fundamentally because of what has happened in Europe uh is because they 00:28:30.240 --> 00:28:33.597 were able to produce things that the world needed and so I would say that's 00:28:33.680 --> 00:28:35.757 number one and in order to do that you 00:28:35.840 --> 00:28:37.917 again I go back to the human capital 00:28:38.000 --> 00:28:40.717 here is just fantastic and world class 00:28:40.800 --> 00:28:43.757 uh you have to absolutely invest in uh 00:28:43.840 --> 00:28:48.397 producing uh you know having the energy and the tokens here which again you're 00:28:48.480 --> 00:28:52.237 attracting like as I said we're investing and others are investing uh 00:28:52.320 --> 00:28:56.317 the the data centers here so the question is what's that next generation 00:28:56.400 --> 00:29:00.557 of output that comes from here right I always think about the German middlear 00:29:00.640 --> 00:29:05.117 whenever I go to a jeweler or a dentist in the United States I'm surrounded by 00:29:05.200 --> 00:29:07.277 German middle right totally 00:29:07.360 --> 00:29:09.757 >> um it's just unbelievable engineering 00:29:09.840 --> 00:29:13.117 provice of that country uh and now the 00:29:13.200 --> 00:29:14.957 question and by the way that's the point 00:29:15.040 --> 00:29:17.517 that they are producing industrial 00:29:17.600 --> 00:29:21.277 products which today are built in into 00:29:21.360 --> 00:29:24.157 it all the intelligence as well that 00:29:24.240 --> 00:29:26.477 data right so I know whenever we come to 00:29:26.560 --> 00:29:28.557 Europe everyone's like talking about 00:29:28.640 --> 00:29:31.277 sovereignty and data this data that 00:29:31.360 --> 00:29:34.157 guess what Europe actually should be 00:29:34.240 --> 00:29:37.997 much more concerned about access to 00:29:38.080 --> 00:29:40.317 their industrial companies their 00:29:40.400 --> 00:29:43.197 financial services companies of data 00:29:43.280 --> 00:29:48.237 from you US and the rest of the world uh as opposed to just thinking that somehow 00:29:48.320 --> 00:29:51.597 by protecting Europe you're going to be competitive you are only going to be 00:29:51.680 --> 00:29:56.877 competitive if the products coming out of Europe are globally competitive, 00:29:56.960 --> 00:30:00.637 right? >> Um and so that's I think what needs to 00:30:00.720 --> 00:30:02.717 change. uh you know Europe has led in 00:30:02.800 --> 00:30:05.677 privacy that's fantastic has led in many 00:30:05.760 --> 00:30:10.237 aspects of even safety around AI and what have you and that's a feature uh 00:30:10.320 --> 00:30:14.477 that's great but you also have to complement it with by building locally 00:30:14.560 --> 00:30:16.877 and then also thinking globally what's 00:30:16.960 --> 00:30:19.357 the contribution this continent will 00:30:19.440 --> 00:30:21.677 make uh to the rest of the world which 00:30:21.760 --> 00:30:24.077 it has historically been a leader 00:30:24.160 --> 00:30:29.197 >> a leader so do you think the whole idea around sovereignty of data is that being 00:30:29.280 --> 00:30:33.117 misunderstood I I think that that when people talk 00:30:33.200 --> 00:30:35.437 about sovereignty 00:30:35.520 --> 00:30:41.277 first of all it's very important clearly and in a week like this it's more 00:30:41.360 --> 00:30:42.317 important 00:30:42.400 --> 00:30:46.077 >> uh but that said uh 00:30:46.160 --> 00:30:49.597 >> it is you have to kind of think about 00:30:49.680 --> 00:30:54.157 how what is sovereignty mean like for example in the AI era the topic that's 00:30:54.240 --> 00:30:56.477 least talked about but I feel will be 00:30:56.560 --> 00:30:59.677 most talked about in in this uh this 00:30:59.760 --> 00:31:01.757 calendar year will be the sovereignty of 00:31:01.840 --> 00:31:05.917 a firm. Just imagine if your firm you're 00:31:06.000 --> 00:31:09.517 not able to embed the tacit knowledge of 00:31:09.600 --> 00:31:13.677 the firm in a set of weights in a model 00:31:13.760 --> 00:31:16.717 that you control. By definition, you 00:31:16.800 --> 00:31:18.717 have no sovereignty. That means you're 00:31:18.800 --> 00:31:21.837 leaking enterprise value to some model 00:31:21.920 --> 00:31:25.837 company somewhere. In fact, that it's sort of fascinating that nobody's 00:31:25.920 --> 00:31:28.557 talking about that, right? It's like everybody's talking about everything 00:31:28.640 --> 00:31:31.757 else that is sort of you know outside of 00:31:31.840 --> 00:31:34.637 that whereas the most important thing is 00:31:34.720 --> 00:31:38.957 it really doesn't matter if you in fact the data center where it runs is the 00:31:39.040 --> 00:31:42.477 least important thing quite honestly but like even there first of all the data 00:31:42.560 --> 00:31:46.957 centers all are all over just because speed of light is a real constraint uh 00:31:47.040 --> 00:31:51.197 and so therefore the data centers will be spread yes uh you will have digital 00:31:51.280 --> 00:31:54.797 you'll be able to encrypt everything you'll be able to have the keys with you 00:31:54.880 --> 00:31:56.957 all of these are much more technically 00:31:57.040 --> 00:31:59.837 solve problems. But the one problem that 00:31:59.920 --> 00:32:03.037 will only be solved is by you having 00:32:03.120 --> 00:32:05.357 much more sovereignty over the you know 00:32:05.440 --> 00:32:08.157 tacid knowledge uh and control over the 00:32:08.240 --> 00:32:10.237 models and it's not a one-way enterprise 00:32:10.320 --> 00:32:13.197 value transfer. Um and so to me I think 00:32:13.280 --> 00:32:15.757 sovereignty requires real thought on 00:32:15.840 --> 00:32:18.477 what is it um you know control of 00:32:18.560 --> 00:32:22.237 destiny means that your your ability to 00:32:22.320 --> 00:32:26.797 produce something that is unique is preserved. uh David Ricardo was not 00:32:26.880 --> 00:32:29.117 wrong. There's comparative advantage in 00:32:29.200 --> 00:32:31.277 countries. Uh there is comparative 00:32:31.360 --> 00:32:34.317 advantage in firms that needs to be 00:32:34.400 --> 00:32:38.557 preserved even in the AI era. That's what'll give you real sovereignty. 00:32:38.640 --> 00:32:42.077 >> One last question. I know we're running out of time. 00:32:42.160 --> 00:32:46.077 Um in 5 years or 10 years, is there going to be one dominant model that 00:32:46.160 --> 00:32:50.477 we're all going to be using or are and how is Microsoft preparing for this? So 00:32:50.560 --> 00:32:51.677 are you going to be are we going to be 00:32:51.760 --> 00:32:55.037 using one model for for enterprise, one 00:32:55.120 --> 00:32:57.917 model for other other traits? 00:32:58.000 --> 00:33:00.157 >> You know, even in the last whatever 3 00:33:00.240 --> 00:33:02.317 years, four years that we've been at it, 00:33:02.400 --> 00:33:06.557 um the the reality at this point is it's 00:33:06.640 --> 00:33:10.077 a multimodel world, right? I mean the in 00:33:10.160 --> 00:33:14.477 fact if you think about it the in both 00:33:14.560 --> 00:33:18.397 there are going to be multiple models 00:33:18.480 --> 00:33:21.597 and the trick is really how do you take 00:33:21.680 --> 00:33:24.557 advantage of these multiple models and 00:33:24.640 --> 00:33:27.037 in fact build your own model by 00:33:27.120 --> 00:33:29.837 distilling these right uh so think of 00:33:29.920 --> 00:33:33.117 these models uh that you orchestrate to 00:33:33.200 --> 00:33:37.997 build your own model and more importantly you do what is described as 00:33:38.080 --> 00:33:39.517 orchest orchestration or harness 00:33:39.600 --> 00:33:42.317 engineering. So the IP of any 00:33:42.400 --> 00:33:45.517 application or any firm is how do you 00:33:45.600 --> 00:33:50.317 use all these models with context engineering or your data. Yes. 00:33:50.400 --> 00:33:54.477 >> Right. So it's that three parts. So can I bring in all the models by the way uh 00:33:54.560 --> 00:33:57.037 which is closed source, open source, 00:33:57.120 --> 00:34:00.797 build my own model, orchestrate them and 00:34:00.880 --> 00:34:04.397 feed it my data to change the trajectory 00:34:04.480 --> 00:34:07.117 of some outcome that I care about. 00:34:07.200 --> 00:34:09.597 That's it. That's the entire picture. So 00:34:09.680 --> 00:34:14.237 you can do it in like oh I produce a particular product or service. Uh first 00:34:14.320 --> 00:34:18.797 I got to do better better better job in sales or better job in R&D or better job 00:34:18.880 --> 00:34:22.717 in finance or what have you. And you take that outcome and then you say can I 00:34:22.800 --> 00:34:25.197 use all the models orchestrate them and 00:34:25.280 --> 00:34:27.597 feed it my context and then in as a 00:34:27.680 --> 00:34:30.557 result of it the reasoning traces are 00:34:30.640 --> 00:34:33.437 really leading to some capability and 00:34:33.520 --> 00:34:36.637 models that I control as my IP. As long 00:34:36.720 --> 00:34:41.117 as firms can answer that question, they're going to be getting ahead. 00:34:41.200 --> 00:34:43.597 >> Ladies and gentlemen, let's uh thank 00:34:43.680 --> 00:34:50.360 Satya, my friend. Thank you [applause] for 00:34:51.200 --> 00:34:54.957 and hopefully this is the beginning of many great dialogue and conversations 00:34:55.040 --> 00:34:58.077 here at the World Academic Forum. Thank you everyone. 00:34:58.160 --> 00:35:01.320 >> Thank you.