WEBVTT 00:00:00.000 --> 00:00:04.117 And so, does that create that, you know, in more of a bifurcation that a more 00:00:04.200 --> 00:00:06.837 polarization? How do we ensure that that 00:00:06.920 --> 00:00:09.557 that diffusion is spread evenly? How do 00:00:09.640 --> 00:00:14.557 we make sure that we're [clears throat] not leaving major portions of society or 00:00:14.640 --> 00:00:18.357 the world behind? Because I think that's that's [clears throat] going to be the big 00:00:18.440 --> 00:00:21.717 issue for us going forward. Yeah, so it's it's it's interesting, right? This 00:00:21.800 --> 00:00:24.677 is one of those times when 00:00:24.760 --> 00:00:28.557 uh by definition and because of the 00:00:28.640 --> 00:00:30.477 rails that have been established, you 00:00:30.560 --> 00:00:33.277 know, as you said, right? Which is uh 00:00:33.360 --> 00:00:37.717 what's happened with mobile as well as what's happened with the 00:00:37.800 --> 00:00:39.997 uh broad, you know, essentially connectivity. 00:00:40.080 --> 00:00:43.717 >> Right. You have the ability [clears throat] to sort of deliver the 00:00:43.800 --> 00:00:46.157 tokens pretty evenly around the world. 00:00:46.240 --> 00:00:51.357 Right. Uh a lot more so than, let's say, uh the PC era or even the beginning of 00:00:51.440 --> 00:00:52.917 the mobile era, right? Because it took a 00:00:53.000 --> 00:00:55.157 long time for even the most smartphone 00:00:55.240 --> 00:00:58.597 in particular to penetrate um all of the 00:00:58.680 --> 00:01:01.277 world. Whereas now, it's not the case, 00:01:01.360 --> 00:01:04.277 right? These models and their outputs 00:01:04.360 --> 00:01:06.477 are pretty much available everywhere. 00:01:06.560 --> 00:01:09.717 And so, the question to me is 00:01:09.800 --> 00:01:14.077 what's the use cases that make sense, right? So, what in fact one of the demos 00:01:14.160 --> 00:01:16.037 I always go back to, I think this was 00:01:16.120 --> 00:01:18.357 even in the beginning of '23, was a 00:01:18.440 --> 00:01:21.197 rural Indian farmer was able to use a 00:01:21.280 --> 00:01:23.717 bot built on, I think, a very early 00:01:23.800 --> 00:01:26.637 GPT-3 or 2.5 even, 00:01:26.720 --> 00:01:29.157 uh essentially to reason over some farm 00:01:29.240 --> 00:01:34.157 subsidies that he had heard about in a local language and had it even in that 00:01:34.240 --> 00:01:38.077 very early days uh have it even show some agentic 00:01:38.160 --> 00:01:39.677 behavior, right? Like, go complete a 00:01:39.760 --> 00:01:41.837 form for me. So, in some sense, it took 00:01:41.920 --> 00:01:45.397 uh you know, it brought back agency to 00:01:45.480 --> 00:01:48.757 someone uh who perhaps didn't have that 00:01:48.840 --> 00:01:53.157 because the technology was so much more accessible. So, I I do think it's in the 00:01:53.240 --> 00:01:55.637 our hands, even in the global south, to 00:01:55.720 --> 00:01:59.557 use it uh to create, I would say, more 00:01:59.640 --> 00:02:05.027 of that opportunity where there isn't one. Um but I think what the necessary 00:02:05.110 --> 00:02:08.877 [clears throat] conditions still are, do you have uh the 00:02:08.960 --> 00:02:11.557 capital investment being put in? 00:02:11.640 --> 00:02:14.437 Uh do you even have an environment for capital? And because in an interesting 00:02:14.520 --> 00:02:18.117 way, we are, for example, as hyperscalers investing all over, right? 00:02:18.200 --> 00:02:22.037 Including the global south. Uh so, as long as there's an environment which 00:02:22.120 --> 00:02:24.757 attracts the capital investment >> And you see the demand. 00:02:24.840 --> 00:02:27.037 >> And you see And then, yeah, the demand is there. 00:02:27.120 --> 00:02:29.637 >> Yeah. Um and so, the question is, how do 00:02:29.720 --> 00:02:34.397 you have a set of policies that allow for both the capital to come in, for it 00:02:34.480 --> 00:02:37.877 to find nexus where There are certain things, by the way, private capital can 00:02:37.960 --> 00:02:43.037 do, certain things that public capital only can do. For example, the grid. 00:02:43.120 --> 00:02:47.157 Right? It's not I mean, grid in most countries is sort of fundamentally 00:02:47.240 --> 00:02:51.517 driven by governments. >> And public. And so, if you [clears throat] don't have a 00:02:51.600 --> 00:02:54.477 sophisticated or rather, if you don't have 00:02:54.560 --> 00:02:59.197 a real approach to modernizing the grid, uh that will hold things back. I mean, 00:02:59.280 --> 00:03:02.477 there's a lot of talk about behind the meter and so on. And yes, there's some 00:03:02.560 --> 00:03:03.997 amount of that we can do ourselves. 00:03:04.080 --> 00:03:05.997 >> do that in the US. Many countries can't. 00:03:06.080 --> 00:03:07.637 Exactly. And it's not long-term 00:03:07.720 --> 00:03:09.477 scalable, right? I mean, like, to me, a 00:03:09.560 --> 00:03:13.397 long-term scalable solution is to have 00:03:13.480 --> 00:03:17.917 um you know, all of these token factories part of the real economy, 00:03:18.000 --> 00:03:22.037 connected to the grid, connected to the telco network, delivering 00:03:22.120 --> 00:03:26.597 uh just like we deliver bits, you have to deliver tokens plus bits. 00:03:26.680 --> 00:03:30.637 Um and that's kind of what's going to drive an at scale, whether it's in the 00:03:30.720 --> 00:03:34.357 global south or in uh on the developed world. So, so many 00:03:34.440 --> 00:03:37.837 people talk about there may be an AI bubble. I mean, the most important thing 00:03:37.920 --> 00:03:40.797 that we see as an investor is 00:03:40.880 --> 00:03:44.117 the the democratization of technology 00:03:44.200 --> 00:03:46.317 and the diffusion of that technology 00:03:46.400 --> 00:03:49.477 really does then transform the demand. 00:03:49.560 --> 00:03:53.637 And the the companies or the countries that diffuse it fastest are going to be 00:03:53.720 --> 00:03:56.637 the ultimate winners, not the technology creator. 00:03:56.720 --> 00:03:59.677 That's that's you know, it's it's it's 00:03:59.760 --> 00:04:00.717 uh 00:04:00.800 --> 00:04:04.197 the for this not to be a bubble Yep. by 00:04:04.280 --> 00:04:06.837 definition, it requires 00:04:06.920 --> 00:04:10.037 that the benefits of this are much more 00:04:10.120 --> 00:04:11.637 evenly spread. I mean, I think a 00:04:11.720 --> 00:04:15.597 telltale sign of if it's a bubble would 00:04:15.680 --> 00:04:18.477 be if all we are talking about are the 00:04:18.560 --> 00:04:23.317 tech firms. Uh right? If uh all we talk about is 00:04:23.400 --> 00:04:27.437 what's happening to the technology side, that then that's by you know, it's just 00:04:27.520 --> 00:04:31.397 purely supply side. >> Right. Uh ultimately, if we are not 00:04:31.480 --> 00:04:35.637 talking about, "Wow, here is a drug you know, drug that was sort of uh brought 00:04:35.720 --> 00:04:39.917 into the market that's super successful because it was uh AI accelerated the 00:04:40.000 --> 00:04:43.437 clinical trial." It's not even the magical molecule, right? It's kind of 00:04:43.520 --> 00:04:45.757 even the rest of what is 00:04:45.840 --> 00:04:47.957 uh needed in order to make something 00:04:48.040 --> 00:04:50.917 much more relevant, right? Um and so, 00:04:51.000 --> 00:04:55.437 the more we [clears throat] have uh And by the way, it's happening, right? So, 00:04:55.520 --> 00:04:57.117 I'm not sort of saying that that's why 00:04:57.200 --> 00:04:59.997 I'm much more confident that this is a 00:05:00.080 --> 00:05:06.037 technology that will, in fact, build on the rails of cloud and mobile, diffuse 00:05:06.120 --> 00:05:09.317 faster, >> Yep. and bend the productivity [clears throat] 00:05:09.400 --> 00:05:12.637 curve, and bring local surplus and 00:05:12.720 --> 00:05:15.117 economic growth all around the world, 00:05:15.200 --> 00:05:19.797 not just economic growth driven by capital expenses. 00:05:19.880 --> 00:05:25.117 Uh right? Because that's it's a narrow point in time Right now, that's what 00:05:25.200 --> 00:05:26.957 we're seeing more >> That's what we're seeing in you know, 00:05:27.040 --> 00:05:29.757 you know, in in the developed world in particular. 00:05:29.840 --> 00:05:34.117 Uh but remember, my capital, like that the one thing that, you know, is 00:05:34.200 --> 00:05:37.797 definitely is spending a lot of it in the United States, but a 50% of it is 00:05:37.880 --> 00:05:42.157 also all over the world. >> Right. Um and so, interestingly enough, 00:05:42.240 --> 00:05:45.517 it depends on uh demand all over the world. And the 00:05:45.600 --> 00:05:49.557 demand all over the world will only be there if there is local surplus all over 00:05:49.640 --> 00:05:51.437 the world. And so, that's sort of the 00:05:51.520 --> 00:05:53.797 way I see the equation. So, let's drill 00:05:53.880 --> 00:05:57.317 down a little more. As AI diffuses, 00:05:57.400 --> 00:05:59.597 obviously, organizations, companies, 00:05:59.680 --> 00:06:01.997 governments are going to have to evolve. 00:06:02.080 --> 00:06:04.757 Now, getting into the demand side. So, 00:06:04.840 --> 00:06:09.317 how do you think the structure of organizations is changing in an AI 00:06:09.400 --> 00:06:10.717 world? 00:06:10.800 --> 00:06:14.037 Across roles, across teams, management. 00:06:14.120 --> 00:06:18.877 I'm I'm sure um Microsoft has evolved itself. 00:06:18.960 --> 00:06:20.677 So, I it'd probably be good to tell the 00:06:20.760 --> 00:06:23.357 audience how do you see this diffusion 00:06:23.440 --> 00:06:27.997 occur in the utilization at the corporate level or at a government level 00:06:28.080 --> 00:06:31.597 that which ultimately then creates that demand, which eliminates any fears and 00:06:31.680 --> 00:06:35.957 bubbles. Yeah, now I think it it's probably one of the the big challenges 00:06:36.040 --> 00:06:38.277 with all of these new technologies is 00:06:38.360 --> 00:06:39.597 when uh 00:06:39.680 --> 00:06:44.637 work work artifact and workflow changes, 00:06:44.720 --> 00:06:48.917 uh that means we as firms have to change 00:06:49.000 --> 00:06:52.517 how we work. I In fact, [clears throat] I remember meeting um 00:06:52.600 --> 00:06:56.797 uh the CEO of Generali, you know, a few years back, and he was describing he had 00:06:56.880 --> 00:07:01.087 joined um uh the firm, you know, pre-PC 00:07:01.170 --> 00:07:04.997 [clears throat] era, and uh uh and he was describing how, for example, they 00:07:05.080 --> 00:07:07.837 worked with their agents in the field uh 00:07:07.920 --> 00:07:11.277 with faxes, interoffice memos, and 00:07:11.360 --> 00:07:15.437 uh and and suddenly the PC showed up, and people would then put a spreadsheet 00:07:15.520 --> 00:07:19.717 in an email and send it around, and the entire workflow and the work process 00:07:19.800 --> 00:07:22.437 changed. Right? So, similarly, I think 00:07:22.520 --> 00:07:24.917 with AI, uh you are going to start 00:07:25.000 --> 00:07:29.877 seeing uh actual change in how workflow happens, right? 00:07:29.960 --> 00:07:32.517 In [clears throat] fact, for me, coming to Davos, you know, 00:07:32.600 --> 00:07:37.237 whatever 50 bilateral meetings I have, preparing for those 00:07:37.320 --> 00:07:39.037 uh had a particular workflow, right? 00:07:39.120 --> 00:07:43.517 Which is uh there used to be my field team would prepare notes, and that would 00:07:43.600 --> 00:07:45.357 come to my HQ, and that would get 00:07:45.440 --> 00:07:47.517 further refined. And nothing had really 00:07:47.600 --> 00:07:50.597 changed, right? Since I joined in '92 to 00:07:50.680 --> 00:07:52.637 essentially even a few years back. 00:07:52.720 --> 00:07:56.597 Whereas now, I just go to Copilot and say, "Hey, I'm meeting Larry. Please 00:07:56.680 --> 00:08:01.077 give me a brief." And it comes back and gives me By the way, the one nice thing 00:08:01.160 --> 00:08:05.477 is, it gives me a 360, right? It knows what we're doing with you as a client, 00:08:05.560 --> 00:08:08.547 what we're doing as a client of yours, and everything in between 00:08:08.630 --> 00:08:13.237 [clears throat] as an investment. It's so, it captures even information unlike 00:08:13.320 --> 00:08:17.437 anything else. In fact, what I do is I take that and immediately share that 00:08:17.520 --> 00:08:21.117 back with all my colleagues across all the functions, right? Think about it. 00:08:21.200 --> 00:08:25.597 It's a complete inversion of how information is flowing in the 00:08:25.680 --> 00:08:29.957 organization. It's not like this classic, we have an organization, we 00:08:30.040 --> 00:08:33.677 have departments, we have these specializations, and the information 00:08:33.760 --> 00:08:36.757 trickles up. No, no, no. It actually It 00:08:36.840 --> 00:08:40.077 flattens the entire information flow. 00:08:40.160 --> 00:08:42.957 So, once you start having that, you have 00:08:43.040 --> 00:08:45.797 to redesign structurally. Uh so, the 00:08:45.880 --> 00:08:49.717 current structure may not make sense. 00:08:49.800 --> 00:08:52.797 Um because you want people to be able to 00:08:52.880 --> 00:08:56.557 work in a way that allows them to have 00:08:56.640 --> 00:08:59.437 this information flow freely. So, what 00:08:59.520 --> 00:09:03.637 all this leads me to, if I have to sort of say what's the formula, the formula I 00:09:03.720 --> 00:09:05.637 think it starts with the mindset. So, 00:09:05.720 --> 00:09:09.837 the mindset we as leaders should have is 00:09:09.920 --> 00:09:13.237 we need to think about changing the work 00:09:13.320 --> 00:09:16.397 the workflow with the technology. Then 00:09:16.480 --> 00:09:20.477 that needs skill set. So, you can't sort of talk about this in the abstract. You 00:09:20.560 --> 00:09:24.077 got to use it. Like, so if I'm not using the >> You have to trust it. 00:09:24.160 --> 00:09:28.277 >> You have to trust it, you have to use it, you have to learn even how to put 00:09:28.360 --> 00:09:31.837 the guardrails to trust it, right? So, you can't again, you can't just be 00:09:31.920 --> 00:09:35.117 afraid of it. Uh it's going to it's going to be 00:09:35.200 --> 00:09:40.117 diffused. So, the question is, as a firm, you have to use it to learn how to 00:09:40.200 --> 00:09:43.197 even uh put the guardrails that allow you to 00:09:43.280 --> 00:09:46.437 be able to trust it. So, skills, uh so, 00:09:46.520 --> 00:09:48.717 mindset, skills. The other big 00:09:48.800 --> 00:09:52.237 consideration um really is how do you 00:09:52.320 --> 00:09:55.557 make sure you have the data set that 00:09:55.640 --> 00:09:58.597 you're feeding? Like, context. Like it's 00:09:58.680 --> 00:10:00.957 kind of like you have a new intelligence 00:10:01.040 --> 00:10:03.317 layer, but the intelligence layer is 00:10:03.400 --> 00:10:07.157 only as good as the context you give it. 00:10:07.240 --> 00:10:12.317 So, people describe it even as context engineering, but that is what firms do. 00:10:12.400 --> 00:10:15.997 Right? If you think about what do firms do, it's all about the tacit knowledge 00:10:16.080 --> 00:10:19.077 we have by working as people in various 00:10:19.160 --> 00:10:23.157 departments and moving paper and information. So, the question is how do 00:10:23.240 --> 00:10:25.157 you really have this AI also have that 00:10:25.240 --> 00:10:27.357 context? So, these are sort of some of 00:10:27.440 --> 00:10:32.557 the new things that have to percolate throughout an organization 00:10:32.640 --> 00:10:36.037 to take advantage. In fact, that's why I think you're you're going to see that 00:10:36.120 --> 00:10:40.797 challenge of why am I not seeing immediate results in productivity? 00:10:40.880 --> 00:10:44.197 Because you have to do the hard work. In fact, that's why it's not going to be at 00:10:44.280 --> 00:10:47.517 some, you know, it's going to they're going to be firm-wide differences. 00:10:47.600 --> 00:10:49.437 They're going to they could [clears throat] be sector-wide 00:10:49.520 --> 00:10:53.197 differences, but it's going to fundamentally be because of the 00:10:53.280 --> 00:10:56.397 leadership will in an organization. 00:10:56.480 --> 00:11:01.077 Do you see the applications being used across large companies and medium and 00:11:01.160 --> 00:11:04.677 small companies or is it still the domain of mostly the large companies at 00:11:04.760 --> 00:11:08.157 this moment? >> I think that what you're seeing is it's 00:11:08.240 --> 00:11:13.917 easier the because if you have a green sort of 00:11:14.000 --> 00:11:16.437 you know, you if you start fresh, it's 00:11:16.520 --> 00:11:18.397 easier to adopt these tools and you 00:11:18.480 --> 00:11:21.597 construct your organization knowing that 00:11:21.680 --> 00:11:25.597 these tools exist. So, I would say >> then? It is a barbell. So, small 00:11:25.680 --> 00:11:28.517 companies that are just starting use that platform. 00:11:28.600 --> 00:11:31.617 >> 100%. And I think in fact, I would say even for large organizations, there's 00:11:31.700 --> 00:11:34.677 [clears throat] a fundamental challenge, right? Because unless and until your 00:11:34.760 --> 00:11:38.237 rate of change keeps up with Right. uh 00:11:38.320 --> 00:11:42.757 with with what is possible, uh you're you're going to get schooled by someone 00:11:42.840 --> 00:11:47.557 small being able to achieve scale because of these tools. So, but I think 00:11:47.640 --> 00:11:50.637 scale large organizations have an inherent strength. You have the 00:11:50.720 --> 00:11:53.997 relationships, you have the data, you have 00:11:54.080 --> 00:11:56.437 you have know-how, but the bottom line 00:11:56.520 --> 00:12:01.197 is if you don't translate that with a new production function, 00:12:01.280 --> 00:12:04.917 uh then you really will be stuck. And so, therefore, the change management 00:12:05.000 --> 00:12:08.237 challenge for large organizations is going to be bigger. 00:12:08.320 --> 00:12:12.077 The structural challenge for small organizations of how to overcome scale 00:12:12.160 --> 00:12:15.277 issues are going to be harder. So, it's sort of the two sides. In an interesting 00:12:15.360 --> 00:12:19.637 way, it's going to be a very competitively intense world 00:12:19.720 --> 00:12:21.997 where neither side, like whether you're 00:12:22.080 --> 00:12:27.357 a new entrant or an incumbent, can't take it as like I I can just coast. What 00:12:27.440 --> 00:12:30.757 about country to country? Are you seeing big 00:12:30.840 --> 00:12:32.477 differences in how the applications are 00:12:32.560 --> 00:12:35.637 being used? Is it Is AI still the domain 00:12:35.720 --> 00:12:40.117 of developed countries or is it becoming rapidly a domain of all countries? 00:12:40.200 --> 00:12:45.157 >> I I I'm seeing that two things I'd say, Larry. As I travel around the world, the 00:12:45.240 --> 00:12:48.237 quality of 00:12:48.320 --> 00:12:50.597 whether it's the know-how, the software 00:12:50.680 --> 00:12:54.037 developers, the startups, 00:12:54.120 --> 00:12:57.997 or even large or large organizations, it's not that 00:12:58.080 --> 00:13:01.117 different. It's fascinating. You can show up in Jakarta, you can show up in 00:13:01.200 --> 00:13:05.517 Istanbul, you can show up in Mexico City. It's not that different than 00:13:05.600 --> 00:13:08.037 showing up even in say Seattle or San 00:13:08.120 --> 00:13:13.317 Francisco, right? It's not for the first time just because access to what's 00:13:13.400 --> 00:13:14.557 happening 00:13:14.640 --> 00:13:17.637 uh is there. That said, 00:13:17.720 --> 00:13:21.277 at [clears throat] scale, the commitment 00:13:21.360 --> 00:13:24.277 to using this, the risk capital being 00:13:24.360 --> 00:13:26.837 there, the large companies pushing it 00:13:26.920 --> 00:13:30.317 hard. I mean, I you know, again, the US, 00:13:30.400 --> 00:13:33.757 you know, is In fact, if I compare it, 00:13:33.840 --> 00:13:36.157 uh take financial sector. 00:13:36.240 --> 00:13:38.277 If in financial sector's adoption of the 00:13:38.360 --> 00:13:41.957 cloud versus AI, night and day, right? 00:13:42.040 --> 00:13:45.357 Because in an interesting way, it's much faster 00:13:45.440 --> 00:13:49.957 uh when it comes to AI versus it was with the cloud. And cloud because for a 00:13:50.040 --> 00:13:52.917 variety of reasons, regulatory >> issues, too. 00:13:53.000 --> 00:13:56.117 Until the regulators allowed banks to 00:13:56.200 --> 00:14:00.117 bring their data off out out of campus, that was a big issue. Yeah. So, I would 00:14:00.200 --> 00:14:02.837 say I think [clears throat] wherever, you know, so 00:14:02.920 --> 00:14:06.077 in the West, in particular in the US, 00:14:06.160 --> 00:14:10.637 uh there is clearly a real I would say more of an energy 00:14:10.720 --> 00:14:13.877 around it in terms of going and using it. 00:14:13.960 --> 00:14:17.237 Uh but it's sort of a lot more uniformly 00:14:17.320 --> 00:14:21.317 spreading around the world than any technology at least I've seen. Are you 00:14:21.400 --> 00:14:25.117 Are you you mentioned [clears throat] about power, the grid. 00:14:25.200 --> 00:14:28.477 Is that going to be one of the determinants of of [snorts] 00:14:28.560 --> 00:14:30.957 the accessibility? If you do not have 00:14:31.040 --> 00:14:32.597 cheap power, 00:14:32.680 --> 00:14:35.797 it the demand is costly. 100%. So, if 00:14:35.880 --> 00:14:40.907 you sort of look at the tokens per dollar per watt, right? Which I think in 00:14:40.990 --> 00:14:45.677 [clears throat] some sense, I would claim that GDP growth in any place will 00:14:45.760 --> 00:14:49.357 be directly correlated. Like you if you sort of buy my entire argument that 00:14:49.440 --> 00:14:54.397 look, we've got a new commodity, it it's tokens. Right. And the job of every 00:14:54.480 --> 00:14:57.797 economy and every firm in the economy is to 00:14:57.880 --> 00:14:59.877 translate these tokens into economic 00:14:59.960 --> 00:15:02.437 growth. Then, if you have a cheaper 00:15:02.520 --> 00:15:07.277 commodity, it's better. Uh and so, that's sort of what why this 00:15:07.360 --> 00:15:10.877 tokens per dollar per watt. And by the way, there are many, many elements to 00:15:10.960 --> 00:15:14.077 this, right? Which is it's not just um 00:15:14.160 --> 00:15:18.397 the production side. That's why I think even having the grid is important. 00:15:18.480 --> 00:15:20.717 Construction costs, right? So, if you 00:15:20.800 --> 00:15:25.837 like if you think about the total TCO, uh everything, it's like the how are you 00:15:25.920 --> 00:15:27.677 a cheap producer of energy? Can you 00:15:27.760 --> 00:15:30.277 build the data centers? Uh then what's 00:15:30.360 --> 00:15:34.797 the cost curve of the silicon in the systems? 00:15:34.880 --> 00:15:36.557 And by the way, look at the token 00:15:36.640 --> 00:15:39.557 pricing, right? Token pricing basically 00:15:39.640 --> 00:15:43.397 drops by you know, a half every 3 00:15:43.480 --> 00:15:46.597 months. Uh I mean, this is a So, how So, 00:15:46.680 --> 00:15:49.397 that that's why I think you can sort of 00:15:49.480 --> 00:15:53.037 really plot how you use the tokens to 00:15:53.120 --> 00:15:57.237 create surplus knowing that you have a commodity that's whose prices are just 00:15:57.320 --> 00:16:00.717 going to monotonically come down in a pretty fast curve. We're sitting in 00:16:00.800 --> 00:16:05.517 Europe uh and there is a real fear 00:16:05.600 --> 00:16:09.477 because of the Europe does not have its own power. 00:16:09.560 --> 00:16:12.077 It has to import mostly of its power. 00:16:12.160 --> 00:16:15.997 Um Do you have any messages for Europe 00:16:16.080 --> 00:16:19.437 related to this? Yeah, I mean, I think so, there are two sets of things, right? 00:16:19.520 --> 00:16:21.997 One is, you know, here we are in in 00:16:22.080 --> 00:16:24.117 Switzerland and I look at 00:16:24.200 --> 00:16:26.797 the the pharma or the financial sector, 00:16:26.880 --> 00:16:32.077 you know, obviously Swiss they're they do a big job in in in this country 00:16:32.160 --> 00:16:34.877 as in in Europe, but they're also international brands and international 00:16:34.960 --> 00:16:39.277 operations. So, one thing that whenever I think about Europe is the 00:16:39.360 --> 00:16:43.197 Europeans are producing products and services that actually are going 00:16:43.280 --> 00:16:47.597 everywhere in the world. And so, therefore, uh European competitiveness 00:16:47.680 --> 00:16:51.837 is about the competitiveness of their output globally, not just in Europe. I 00:16:51.920 --> 00:16:53.637 think sometimes when you come to Europe, 00:16:53.720 --> 00:16:55.517 there's a lot of conversation about just 00:16:55.600 --> 00:16:59.357 Europe. Uh but European economy is uh 00:16:59.440 --> 00:17:03.357 thrives and has, you know, thrived in the last whatever 200 years, 300 years, 00:17:03.440 --> 00:17:07.637 the miracle of the West is fundamentally because of what has happened in Europe 00:17:07.720 --> 00:17:11.197 uh is because they were able to produce things that the world needed. And so, I 00:17:11.280 --> 00:17:15.437 would say that's number one. And in order to do that, you again I go back to 00:17:15.520 --> 00:17:19.157 the human capital here is just fantastic and world-class. 00:17:19.240 --> 00:17:21.877 Uh you have to absolutely invest in 00:17:21.960 --> 00:17:26.597 producing uh you know, having the energy and the tokens here, which again, you're 00:17:26.680 --> 00:17:30.757 attracting like as I said, we are investing and others are investing uh 00:17:30.840 --> 00:17:35.317 the data centers here. So, the question is what's that next generation of output 00:17:35.400 --> 00:17:38.797 that comes from here, right? I always think about the German Mittelstand. 00:17:38.880 --> 00:17:43.237 Whenever I go to a jeweler or a dentist in the United States, I'm surrounded by 00:17:43.320 --> 00:17:44.637 German Mittelstand, right? 00:17:44.720 --> 00:17:47.237 >> Yes, totally. Um it's just unbelievable 00:17:47.320 --> 00:17:50.517 engineering prowess of that country. 00:17:50.600 --> 00:17:52.277 Uh and now the question And by the way, 00:17:52.360 --> 00:17:54.837 that's the point. They are producing 00:17:54.920 --> 00:17:58.077 industrial products, which today are 00:17:58.160 --> 00:18:01.357 built in into it all the intelligence as 00:18:01.440 --> 00:18:03.917 well. That data, right? So, I know 00:18:04.000 --> 00:18:05.757 whenever we come to Europe, everyone's 00:18:05.840 --> 00:18:08.397 like talking about sovereignty and data 00:18:08.480 --> 00:18:11.237 this, data that. Guess what? Europe 00:18:11.320 --> 00:18:14.277 actually should be much more concerned 00:18:14.360 --> 00:18:17.117 about access to their industrial 00:18:17.200 --> 00:18:19.637 companies, their financial services 00:18:19.720 --> 00:18:23.037 companies of data from you US and the 00:18:23.120 --> 00:18:27.237 rest of the world. Uh as opposed to just thinking that somehow by protecting 00:18:27.320 --> 00:18:28.837 Europe, you're going to be competitive. 00:18:28.920 --> 00:18:30.997 You are only going to be competitive if 00:18:31.080 --> 00:18:33.557 the products coming out of Europe are 00:18:33.640 --> 00:18:36.317 globally competitive. 00:18:36.400 --> 00:18:38.757 And so, that's I think what needs to 00:18:38.840 --> 00:18:40.877 change. I know Europe has led in 00:18:40.960 --> 00:18:43.637 privacy, that's fantastic, has led in 00:18:43.720 --> 00:18:48.437 many aspects of even safety around AI and what have you, and that's a feature 00:18:48.520 --> 00:18:52.757 that's great. But you also have to complement it with by building locally 00:18:52.840 --> 00:18:55.117 and then also thinking globally, what's 00:18:55.200 --> 00:18:57.477 the contribution this continent will 00:18:57.560 --> 00:19:02.277 make to the rest of the world, which it has historically been a leader in. 00:19:02.360 --> 00:19:05.557 >> A leader. So, do you think the whole idea around 00:19:05.640 --> 00:19:09.077 sovereignty of data, is that being misunderstood? 00:19:09.160 --> 00:19:10.597 I think that 00:19:10.680 --> 00:19:13.717 when people talk about sovereignty, 00:19:13.800 --> 00:19:17.917 first of all, it's very important, clearly in Who owns the data? And in a 00:19:18.000 --> 00:19:20.557 week like this, it's more important. 00:19:20.640 --> 00:19:24.357 Uh but that said, uh 00:19:24.440 --> 00:19:28.477 it is you have to kind of think about how what 00:19:28.560 --> 00:19:32.717 is sovereignty mean? Like for example, in the AI era, the topic that's least 00:19:32.800 --> 00:19:35.117 talked about, but I feel will be most 00:19:35.200 --> 00:19:38.317 talked about in in this this calendar 00:19:38.400 --> 00:19:41.117 year will be the sovereignty of a firm. 00:19:41.200 --> 00:19:43.837 Just imagine, if your firm, 00:19:43.920 --> 00:19:46.717 you're not able to embed the tacit 00:19:46.800 --> 00:19:49.757 knowledge of the firm in a set of 00:19:49.840 --> 00:19:53.797 weights in a model that you control, 00:19:53.880 --> 00:19:56.397 by definition, you have no sovereignty. 00:19:56.480 --> 00:19:58.197 That means you're leaking enterprise 00:19:58.280 --> 00:20:01.517 value to some model company somewhere. 00:20:01.600 --> 00:20:04.997 In fact, that it's sort of fascinating that nobody's talking about that, right? 00:20:05.080 --> 00:20:08.317 It's like everybody's talking about everything else that is sort of, you 00:20:08.400 --> 00:20:11.717 know, outside of that. Whereas the most 00:20:11.800 --> 00:20:15.437 important thing is, it really doesn't matter if you have In fact, the data 00:20:15.520 --> 00:20:19.237 center where it runs is the least important thing, quite honestly. But 00:20:19.320 --> 00:20:22.797 like even there, first of all, the data centers all are all over just because 00:20:22.880 --> 00:20:27.037 speed of light is a real constraint. Uh and so therefore, the data centers will 00:20:27.120 --> 00:20:29.677 be spread. >> Yes. Uh you will have digital, you'll be 00:20:29.760 --> 00:20:33.357 able to encrypt everything, you'll be able to have the keys with you. All of 00:20:33.440 --> 00:20:35.477 these are much more technically solved 00:20:35.560 --> 00:20:38.357 problems. But the one problem that will 00:20:38.440 --> 00:20:41.557 only be solved is by you having much 00:20:41.640 --> 00:20:46.317 more sovereignty over the, you know, tacit knowledge uh and control over the 00:20:46.400 --> 00:20:50.797 models, and it's not a one-way enterprise value transfer. Um and so to 00:20:50.880 --> 00:20:53.277 me, I think sovereignty requires real 00:20:53.360 --> 00:20:55.797 thought on what is it. 00:20:55.880 --> 00:20:58.277 You know, control of destiny means that 00:20:58.360 --> 00:21:00.957 you are your ability to produce 00:21:01.040 --> 00:21:03.597 something that is unique is preserved. 00:21:03.680 --> 00:21:05.637 Uh David Ricardo was not wrong, there's 00:21:05.720 --> 00:21:08.557 comparative advantage in countries. Uh 00:21:08.640 --> 00:21:11.597 there is comparative advantage in firms. 00:21:11.680 --> 00:21:15.837 That needs to be preserved even in the AI era. That's what'll give you real 00:21:15.920 --> 00:21:20.357 sovereignty. One last question, I know we're running out of time. 00:21:20.440 --> 00:21:24.357 Um in 5 years or 10 years, is there going to be one dominant model that 00:21:24.440 --> 00:21:28.757 we're all going to be using, or or and how is Microsoft preparing for this? Are 00:21:28.840 --> 00:21:30.637 you going to be Are we going to be using 00:21:30.720 --> 00:21:33.597 one model for for enterprise, one model 00:21:33.680 --> 00:21:36.677 for other other trades? You know, even 00:21:36.760 --> 00:21:38.757 in the last, whatever, four three years, 00:21:38.840 --> 00:21:41.677 four years that we've been at it, um the 00:21:41.760 --> 00:21:44.837 the reality at this point is it's a 00:21:44.920 --> 00:21:50.157 multi-model world, right? I mean, the In fact, if you think about it, 00:21:50.240 --> 00:21:52.237 the in 00:21:52.320 --> 00:21:54.797 both, there are going to be 00:21:54.880 --> 00:21:58.957 multiple models, and the trick is really 00:21:59.040 --> 00:22:02.637 how do you take advantage of these multiple models, 00:22:02.720 --> 00:22:05.077 and in fact, build your own model by 00:22:05.160 --> 00:22:08.077 distilling these, right? Uh so think of 00:22:08.160 --> 00:22:11.277 these models uh that you orchestrate to 00:22:11.360 --> 00:22:15.637 build your own model, and more importantly, you do what is described as 00:22:15.720 --> 00:22:17.637 hard orchestration or harness 00:22:17.720 --> 00:22:20.477 engineering. So, the IP of any 00:22:20.560 --> 00:22:23.717 application or any firm is how do you 00:22:23.800 --> 00:22:28.757 use all these models with context engineering or your data? Yes. Right? 00:22:28.840 --> 00:22:32.757 So, it's not three parts. So, can I bring in all the models, by the way, uh 00:22:32.840 --> 00:22:35.317 which is close source, open source, 00:22:35.400 --> 00:22:38.597 build my own model, orchestrate them, 00:22:38.680 --> 00:22:41.957 and feed it my data to change the 00:22:42.040 --> 00:22:44.597 trajectory of some outcome that I care 00:22:44.680 --> 00:22:49.237 about. That's it. That's the entire picture. So, you can do it in like, oh, 00:22:49.320 --> 00:22:53.717 I produce a particular product or service. Uh first, I got to do better 00:22:53.800 --> 00:22:58.037 better job in sales, or better job in R&D, or better job in finance, or what 00:22:58.120 --> 00:23:02.317 have you, and you take that outcome, and then you say, can I use all the models, 00:23:02.400 --> 00:23:03.997 orchestrate them, and feed it my 00:23:04.080 --> 00:23:06.997 context, and then in as a result of it, 00:23:07.080 --> 00:23:09.757 the reasoning traces are really leading 00:23:09.840 --> 00:23:12.597 to some capability and models that I 00:23:12.680 --> 00:23:17.477 control as my IP. As long as firms can answer that question, they're going to 00:23:17.560 --> 00:23:19.477 be getting ahead. 00:23:19.560 --> 00:23:21.517 Ladies and Gentlemen, let's 00:23:21.600 --> 00:23:25.557 thank Satya, my friend, Thank you. 00:23:25.640 --> 00:23:29.437 for >> [applause] 00:23:29.520 --> 00:23:34.317 >> And hopefully, this is the beginning of many great dialogue and conversations here 00:23:34.400 --> 00:23:38.840 at the World Economic Forum. Thank you, everyone. Thank you. 00:24:15.200 --> 00:24:17.237 It's getting better and better. 00:24:17.320 --> 00:24:19.677 And interestingly enough, you look at 00:24:19.760 --> 00:24:24.717 it, uh the software developer still is got a lot of agency in it, right? So, 00:24:24.800 --> 00:24:28.597 that's why I kind of still think that, you know, going and thinking of these as 00:24:28.680 --> 00:24:32.917 somehow living outside of the realm of human agency is probably not the right 00:24:33.000 --> 00:24:37.157 way to think about it. In fact, the way to perhaps conceive it like if let's say 00:24:37.240 --> 00:24:40.917 in early '80s, if somebody had come to us and said, 00:24:41.000 --> 00:24:45.437 whatever, 4 billion people are going to wake up every morning and start typing. 00:24:45.520 --> 00:24:50.037 You would've said, why, right? You know, we have a like we have a typist pool 00:24:50.120 --> 00:24:53.477 that's good enough, we don't need 4 billion people. But we That's what 00:24:53.560 --> 00:24:55.797 happened. Like we invented this entire 00:24:55.880 --> 00:24:58.477 class of thing called knowledge work, 00:24:58.560 --> 00:25:00.797 where people started really using 00:25:00.880 --> 00:25:04.197 computers uh to go amplify what we were 00:25:04.280 --> 00:25:07.117 trying to achieve uh using software. I 00:25:07.200 --> 00:25:09.117 think in the context of AI, that same 00:25:09.200 --> 00:25:11.677 thing is going to happen. Um it's not 00:25:11.760 --> 00:25:16.597 like, you know, what is hardcore coding is going to remain hardcore coding 00:25:16.680 --> 00:25:20.637 forever. It's just that the levels of abstraction are going to change. Uh but 00:25:20.720 --> 00:25:24.997 we also are going to have code as output, just like documents. In fact, 00:25:25.080 --> 00:25:29.677 one of Bill's things at Microsoft from the day I joined in '92 always was, 00:25:29.760 --> 00:25:31.117 what's the real difference between a 00:25:31.200 --> 00:25:34.317 document, a website, and an application, 00:25:34.400 --> 00:25:37.037 right? It's the lack of sort of software 00:25:37.120 --> 00:25:41.597 that can transform itself. Interestingly enough, AI finally gives us that, right? 00:25:41.680 --> 00:25:45.437 Which is I can write a document, I can just say, no, I don't want it as a 00:25:45.520 --> 00:25:49.007 document, I want it as a website, it'll just transform that document using 00:25:49.090 --> 00:25:52.317 [clears throat] code into a website. I say, oh, I don't like the website, I 00:25:52.400 --> 00:25:54.117 want an app, it'll write more code to 00:25:54.200 --> 00:25:57.317 transform it. So, that a reasoning and 00:25:57.400 --> 00:25:59.477 capab- reasoning capabilities, that 00:25:59.560 --> 00:26:01.717 prediction capabilities, that ability to 00:26:01.800 --> 00:26:04.957 take action, remain long-term coherent, 00:26:05.040 --> 00:26:08.957 is all improving. Um and our job, 00:26:09.040 --> 00:26:12.317 though, is to parlay this. Like take even what 00:26:12.400 --> 00:26:15.397 you at BlackRock are doing, right? When you're 00:26:15.480 --> 00:26:18.957 taking something like, say, Co-pilot plus Aladdin and bringing those things 00:26:19.040 --> 00:26:21.877 together [clears throat] Right. to improve the productivity in 00:26:21.960 --> 00:26:26.397 the firm for the decisions you want to make, right? With your data. I could 00:26:26.480 --> 00:26:31.557 just tell you from at our firm, things that would take 12 hours to compute now 00:26:31.640 --> 00:26:35.597 takes minutes. For us processing 14 trillion dollars of 00:26:35.680 --> 00:26:40.957 other people's money with hundreds of thousands of different um mandates, um 00:26:41.040 --> 00:26:44.157 we could do that instantaneously. And we, you know, that To me, if it wasn't 00:26:44.240 --> 00:26:47.997 for the technology and AI today, we would not be able to function to the 00:26:48.080 --> 00:26:49.437 scale that we're operating. That's 00:26:49.520 --> 00:26:52.797 right. And so, to me, that one firm at a 00:26:52.880 --> 00:26:55.277 time, one country at a time, if we can 00:26:55.360 --> 00:27:00.557 really take these tokens and bend the curve of productivity, then there is 00:27:00.640 --> 00:27:03.557 surplus everywhere, and that's really the goal. 00:27:03.640 --> 00:27:07.277 Well, surplus could be scary, too. Does Does surplus mean 00:27:07.360 --> 00:27:11.517 fewer workers? What do we mean by surplus? And so, you know, the I'm going 00:27:11.600 --> 00:27:15.037 to tie that into my second question about AI diffusion. 00:27:15.120 --> 00:27:18.637 >> Yeah. To me, the the whole realization of AI 00:27:18.720 --> 00:27:20.717 for any society, 00:27:20.800 --> 00:27:23.877 and also for a more balanced world, is 00:27:23.960 --> 00:27:28.197 making sure that it's diffused and accessible and available across the 00:27:28.280 --> 00:27:30.237 world. So, what, you know, can you 00:27:30.320 --> 00:27:33.957 describe how this process of diffusion 00:27:34.040 --> 00:27:36.277 across economies, across companies, 00:27:36.360 --> 00:27:38.117 across people and countries, how does 00:27:38.200 --> 00:27:43.557 that play out? Yeah, I think that this is the real question, right? 00:27:43.640 --> 00:27:44.877 Because one of the 00:27:44.960 --> 00:27:47.197 things right now, the zeitgeist is a 00:27:47.280 --> 00:27:50.597 little bit about the admiration for AI 00:27:50.680 --> 00:27:56.077 in its abstract form, or as as as technology. Uh 00:27:56.160 --> 00:28:00.077 >> [clears throat] >> but I think we as even a global community um 00:28:00.160 --> 00:28:02.397 have to get to a point where we're using 00:28:02.480 --> 00:28:05.997 this to do something useful uh that 00:28:06.080 --> 00:28:10.197 changes uh the outcomes of people and communities and countries and 00:28:10.280 --> 00:28:14.357 industries, right? Otherwise, I don't think uh this makes much sense, right? 00:28:14.440 --> 00:28:16.517 In fact, I would say we would quickly 00:28:16.600 --> 00:28:20.317 lose even the social permission uh to 00:28:20.400 --> 00:28:24.877 actually take something like uh energy, which is a scarce resource, and use it 00:28:24.960 --> 00:28:28.797 to generate these tokens if these tokens are not improving health outcomes, 00:28:28.880 --> 00:28:32.757 education outcomes, public sector efficiency, private sector 00:28:32.840 --> 00:28:34.797 competitiveness across all sectors, 00:28:34.880 --> 00:28:37.357 small and large, right? And that to me 00:28:37.440 --> 00:28:40.237 is ultimately the goal. So, therefore, I 00:28:40.320 --> 00:28:43.477 think really diffusion is everything. 00:28:43.560 --> 00:28:47.837 And so, the way it happens is, let's sort of unpack this. 00:28:47.920 --> 00:28:50.357 Uh on the supply side, what needs to 00:28:50.440 --> 00:28:53.397 happen in each country is the tokens per 00:28:53.480 --> 00:28:57.837 dollar per watt have to sort of monotonically get more 00:28:57.920 --> 00:29:02.037 efficient and better, right? So, to some degree, even what we are trying to do 00:29:02.120 --> 00:29:06.837 with investments the two firms are doing around the world is to just say that 00:29:06.920 --> 00:29:08.877 like let's make sure that the supply is 00:29:08.960 --> 00:29:11.317 there, which is uh everything from the 00:29:11.400 --> 00:29:16.557 chips on down ultimately to these token factories that get deployed everywhere. 00:29:16.640 --> 00:29:20.517 By the way, there's not one token factory. This token factory is the first 00:29:20.600 --> 00:29:23.757 thing that's going to be diffused all around the world. It's just like 00:29:23.840 --> 00:29:26.597 electricity, right? You just need a 00:29:26.680 --> 00:29:31.717 ubiquitous grid of uh energy and tokens 00:29:31.800 --> 00:29:35.917 that then will power the rest of the economy, right? So, that's I think one 00:29:36.000 --> 00:29:39.717 side of it. Then the demand side of this is a little 00:29:39.800 --> 00:29:42.877 bit like every firm has to start by 00:29:42.960 --> 00:29:46.837 using it. If I look back even, you know, when the 00:29:46.920 --> 00:29:51.237 PCs first came out or the personal computing era started, I loved, you 00:29:51.320 --> 00:29:53.197 know, I think Jobs had a nice metaphor. 00:29:53.280 --> 00:29:55.677 He called it the bicycle for the mind. 00:29:55.760 --> 00:29:59.717 Uh Bill had a metaphor which I remember was like information at your fingertips, 00:29:59.800 --> 00:30:03.037 right? These two metaphors were great, like which you know, allowed us to say, 00:30:03.120 --> 00:30:06.677 "That's what it is. It's a tool that I will use to get information at my 00:30:06.760 --> 00:30:08.677 fingertips. I'll use it as a cognitive 00:30:08.760 --> 00:30:12.157 amplifier." Now, I think that that's 00:30:12.240 --> 00:30:15.837 what we have, but you know, 10x, 100x, right? So, in some 00:30:15.920 --> 00:30:18.557 sense, you as a as every knowledge 00:30:18.640 --> 00:30:21.797 worker, you now have access to infinite 00:30:21.880 --> 00:30:26.157 minds. That's the way I think about it, right? So, there's a Turing Award winner 00:30:26.240 --> 00:30:31.117 uh called Raj Reddy who had this nice metaphor of AI and he had this long before 00:30:31.200 --> 00:30:35.157 uh even generative AI. He said he either either it's a cognitive amplifier or 00:30:35.240 --> 00:30:37.397 it's a guardian angel, right? So, if you 00:30:37.480 --> 00:30:39.997 think of AI as that, 00:30:40.080 --> 00:30:43.237 uh then in the global workforce, right? 00:30:43.320 --> 00:30:47.397 When a doctor can get to a patient, spend more time 00:30:47.480 --> 00:30:49.557 with the patient because the AI is doing 00:30:49.640 --> 00:30:54.597 the transcription and entering the records in the EMR system, entering the 00:30:54.680 --> 00:30:57.557 right billing code so that the healthcare 00:30:57.640 --> 00:30:59.797 uh you know, industry is better served 00:30:59.880 --> 00:31:02.717 across the payer, the provider, and uh 00:31:02.800 --> 00:31:04.797 and the patient ultimately, right? 00:31:04.880 --> 00:31:07.397 That's an an outcome that I think all of 00:31:07.480 --> 00:31:12.317 us can benefit from. So, I feel ultimately, it's going to require real 00:31:12.400 --> 00:31:14.277 leadership on the private sector and the 00:31:14.360 --> 00:31:17.597 public sector to ensure the diffusion 00:31:17.680 --> 00:31:21.797 happens. And the one thing I thing I'll mention, Larry, is skilling. 00:31:21.880 --> 00:31:23.877 Right? So, in some sense, 00:31:23.960 --> 00:31:27.437 the thing that diffusion is very 00:31:27.520 --> 00:31:30.557 strongly correlated to one thing alone, 00:31:30.640 --> 00:31:33.757 which is how broadly are people skilled 00:31:33.840 --> 00:31:37.397 in using this. Um and interestingly 00:31:37.480 --> 00:31:41.157 enough, I think if mobile has taught us one thing 00:31:41.240 --> 00:31:45.637 is it it's actually distinct from what happened in the PC, right? 00:31:45.720 --> 00:31:50.117 Uh I remember even growing up in the global south, uh there used to be a real 00:31:50.200 --> 00:31:52.597 relationship between learning Excel 00:31:52.680 --> 00:31:56.197 skills or Word skills and getting a job. 00:31:56.280 --> 00:31:59.117 Um you know, right now, um 00:31:59.200 --> 00:32:03.237 what's the model in in mobile? It's kind of created the same opportunity, but 00:32:03.320 --> 00:32:05.437 it's been a lot more consumption-led. 00:32:05.520 --> 00:32:09.997 It's these creator economy and what have you. But it's not been about sort of oh 00:32:10.080 --> 00:32:13.677 wow, here's how you get a healthcare job or here is how you get a finance job or 00:32:13.760 --> 00:32:18.277 here is how you get you know, you get ahead uh professionally. 00:32:18.360 --> 00:32:21.277 Um and that needs to come back, right? 00:32:21.360 --> 00:32:22.797 People need to say, "Oh, I pick up this 00:32:22.880 --> 00:32:25.837 AI skill and now I'm a better provider 00:32:25.920 --> 00:32:30.537 of some product or service in the real economy." So, it's it's very easy 00:32:30.620 --> 00:32:34.117 [clears throat] to see how mobile and the diffusion of mobile, how it 00:32:34.200 --> 00:32:37.997 transformed economies, especially in the global south. 00:32:38.080 --> 00:32:42.277 Um how does how does this, you know, to me, I I I just read a research report 00:32:42.360 --> 00:32:46.957 that said um the applications for AI so far are 00:32:47.040 --> 00:32:51.637 heavily weighted toward those who are educated or educated economies. 00:32:51.720 --> 00:32:55.597 And so, does that create that, you know, more of a bifurcation and a more 00:32:55.680 --> 00:32:58.277 polarization? How do we ensure that that 00:32:58.360 --> 00:33:02.627 that diffusion is spread evenly? How do we make sure that we're not 00:33:02.710 --> 00:33:07.597 [clears throat] leaving major portions of society or the world behind? 00:33:07.680 --> 00:33:10.357 Because I think that's that's going [clears throat] to be the big issue for 00:33:10.440 --> 00:33:13.597 us going forward. Yeah, so it's it's it's interesting, right? This is one of 00:33:13.680 --> 00:33:16.197 those times when 00:33:16.280 --> 00:33:20.077 uh by definition and because of the 00:33:20.160 --> 00:33:23.837 rails that have been established, you know, I you said it, right? Which is 00:33:23.920 --> 00:33:29.277 uh what's happened with mobile as well as what's happened with the 00:33:29.360 --> 00:33:31.517 uh bro you know, essentially connectivity. 00:33:31.600 --> 00:33:35.237 >> Right. You have the ability [clears throat] to sort of deliver the 00:33:35.320 --> 00:33:37.677 tokens pretty evenly around the world. 00:33:37.760 --> 00:33:42.837 Right. Uh a lot more so than, let's say, uh the PC era or even the beginning of 00:33:42.920 --> 00:33:44.437 the mobile era, right? Because it took a 00:33:44.520 --> 00:33:46.837 long time for even the smartphone in 00:33:46.920 --> 00:33:50.077 particular to penetrate um all of the 00:33:50.160 --> 00:33:52.757 world. Whereas now, it's not the case, 00:33:52.840 --> 00:33:55.797 right? These models and their outputs 00:33:55.880 --> 00:33:57.957 are pretty much available everywhere. 00:33:58.040 --> 00:34:01.237 And so, the question to me is 00:34:01.320 --> 00:34:05.237 what's the use cases that make sense, right? So, what In fact, one of the 00:34:05.320 --> 00:34:07.397 demos I always go back to, I think this 00:34:07.480 --> 00:34:09.877 is even in the beginning of '23, was a 00:34:09.960 --> 00:34:12.717 rural Indian farmer was able to use a 00:34:12.800 --> 00:34:15.237 bot built on, I think, a very early 00:34:15.320 --> 00:34:18.117 GPT-3 or 2.5 even, 00:34:18.200 --> 00:34:20.677 uh essentially to reason over some farm 00:34:20.760 --> 00:34:25.677 subsidies that he had heard about in a local language and had it even in that 00:34:25.760 --> 00:34:29.597 very early days uh have it even show some agentic 00:34:29.680 --> 00:34:31.557 behavior, right? Like go complete a form 00:34:31.640 --> 00:34:33.557 for me. So, in some sense, it took uh 00:34:33.640 --> 00:34:36.917 you know, it brought back agency to 00:34:37.000 --> 00:34:40.237 someone uh who perhaps didn't have that 00:34:40.320 --> 00:34:41.997 because the technology was so much more 00:34:42.080 --> 00:34:44.957 accessible. So, I I do think it's in the 00:34:45.040 --> 00:34:48.397 hands even in the global south to use it 00:34:48.480 --> 00:34:51.357 uh to create, I would say, more of that 00:34:51.440 --> 00:34:56.597 opportunity where there isn't one. Um but I think what the necessary 00:34:56.680 --> 00:35:00.157 [clears throat] conditions still are, do you have 00:35:00.240 --> 00:35:03.037 uh the capital investment being put in? 00:35:03.120 --> 00:35:05.917 Uh do you even have an environment for capital? And because in an interesting 00:35:06.000 --> 00:35:09.637 way, we are, for example, as hyperscalers investing all over, right? 00:35:09.720 --> 00:35:13.357 Including the global south. Uh so, as long as there's an environment 00:35:13.440 --> 00:35:16.277 which attracts the capital investment And you see the demand. 00:35:16.360 --> 00:35:18.517 >> And you see And then yeah, the demand is there. 00:35:18.600 --> 00:35:21.117 >> Yeah. Um and so, the question is how do 00:35:21.200 --> 00:35:25.917 you have a set of policies that allow for both the capital to come in, for it 00:35:26.000 --> 00:35:29.357 to find nexus with There are certain things, by the way, private capital can 00:35:29.440 --> 00:35:31.517 do, certain things that public capital 00:35:31.600 --> 00:35:34.557 only can do. For example, the grid. 00:35:34.640 --> 00:35:38.637 Right? It's not I mean, grid in may most countries is sort of fundamentally 00:35:38.720 --> 00:35:40.397 driven by governments. >> And public. 00:35:40.480 --> 00:35:43.037 >> And public. And so, if you don't have a 00:35:43.120 --> 00:35:44.917 sophisticated or rather, if you don't 00:35:45.000 --> 00:35:47.917 have a real approach to modernizing the 00:35:48.000 --> 00:35:52.077 grid, uh that will hold things back. I mean, there's a lot of talk about behind 00:35:52.160 --> 00:35:55.517 the meter and so on. And yes, there's some amount of that we can do ourselves. 00:35:55.600 --> 00:35:57.557 >> do that in the US. Many countries can't. 00:35:57.640 --> 00:35:59.797 Exact And it's not long-term scalable, 00:35:59.880 --> 00:36:01.557 right? I mean, like to me, a long-term 00:36:01.640 --> 00:36:05.117 scalable solution is to have uh you 00:36:05.200 --> 00:36:08.077 know, all of these token factories part 00:36:08.160 --> 00:36:12.197 of the real economy, connected to the grid, connected to the telco network, 00:36:12.280 --> 00:36:15.557 delivering uh just like we delivered bits, you have 00:36:15.640 --> 00:36:20.477 to deliver tokens plus bits. Um and that's kind of what's going to drive an 00:36:20.560 --> 00:36:25.317 at scale, whether it's in the global south or in uh on the developed world. 00:36:25.400 --> 00:36:28.717 So, so many people talk about there may be an AI bubble. I mean, the most 00:36:28.800 --> 00:36:30.037 important thing that we see as an 00:36:30.120 --> 00:36:34.117 investor is the the the democratization 00:36:34.200 --> 00:36:37.157 of technology and the diffusion of that 00:36:37.240 --> 00:36:41.797 technology really does then transform the demand. And the 00:36:41.880 --> 00:36:45.797 companies or the countries that diffuse it fastest are going to be the ultimate 00:36:45.880 --> 00:36:48.197 winners, not the technology creator. 00:36:48.280 --> 00:36:51.197 That's that's you know, it's it's it's 00:36:51.280 --> 00:36:54.837 uh uh this for this not to be a bubble, 00:36:54.920 --> 00:36:58.357 Yep. by definition, it requires 00:36:58.440 --> 00:37:01.517 that the benefits of this are much more 00:37:01.600 --> 00:37:03.117 evenly spread. I mean, I I think a 00:37:03.200 --> 00:37:07.117 telltale sign of if it's a bubble would 00:37:07.200 --> 00:37:09.957 be if all we're talking about are the 00:37:10.040 --> 00:37:14.837 tech firms. Uh right? If uh all we talk about is 00:37:14.920 --> 00:37:18.957 what's happening to the technology side, that then that's by you know, it's just 00:37:19.040 --> 00:37:22.877 purely supply side. >> Right. Uh ultimately, if we are not 00:37:22.960 --> 00:37:26.877 talking about wow, here is a drug comp you know, drug that was sort of uh 00:37:26.960 --> 00:37:30.517 brought into the market that's super successful because it was uh AI 00:37:30.600 --> 00:37:34.557 accelerated the clinical trial. It's not even the magical molecule, right? It's 00:37:34.640 --> 00:37:37.317 kind of even the rest of what is uh 00:37:37.400 --> 00:37:39.797 needed in order to make something much 00:37:39.880 --> 00:37:45.037 more relevant, right? Um and so, the more we have [clears throat] 00:37:45.120 --> 00:37:47.917 uh And by the way, it's happening, right? So, that I'm not sort of saying 00:37:48.000 --> 00:37:50.717 that that's why I'm much more confident 00:37:50.800 --> 00:37:55.637 that this is a technology that will in fact build on the rails of cloud and 00:37:55.720 --> 00:37:59.997 mobile, diffuse faster, >> Yep. and bend the productivity 00:38:00.080 --> 00:38:04.117 [clears throat] curve, and bring local surplus and 00:38:04.200 --> 00:38:08.797 economic growth all around the world, not just economic growth driven by 00:38:08.880 --> 00:38:11.117 capital expenses. 00:38:11.200 --> 00:38:15.877 Uh right? Because that's it's a narrow point in time uh calculation. 00:38:15.960 --> 00:38:17.437 >> Right now, that's what we're seeing more of. 00:38:17.520 --> 00:38:21.237 >> we're seeing in you know, in in in in in in the developed world in particular. 00:38:21.320 --> 00:38:25.637 Uh but remember, my capital, like that the one thing that, you know, is 00:38:25.720 --> 00:38:29.597 definitely we're spending a lot of it in the United States, but 50% of it is also 00:38:29.680 --> 00:38:33.637 all over the world. >> Right. Um and so, interestingly enough, 00:38:33.720 --> 00:38:37.037 it depends on uh demand all over the world. And the 00:38:37.120 --> 00:38:41.077 demand all over the world will only be there if there is local surplus all over 00:38:41.160 --> 00:38:42.917 the world. And so, that's sort of the 00:38:43.000 --> 00:38:45.317 way I see the equation. So, let's drill 00:38:45.400 --> 00:38:48.837 down a little more. As AI diffuses, 00:38:48.920 --> 00:38:51.077 obviously, organizations, companies, 00:38:51.160 --> 00:38:53.517 governments are going to have to evolve. 00:38:53.600 --> 00:38:56.277 Now getting to the demand side. So, 00:38:56.360 --> 00:38:58.157 how do you think the structure of 00:38:58.240 --> 00:39:02.237 organizations is changing in an AI world 00:39:02.320 --> 00:39:05.517 across roles, across teams, management? 00:39:05.600 --> 00:39:10.397 I'm I'm sure um Microsoft has evolved itself. 00:39:10.480 --> 00:39:12.197 So, what I probably be good to tell the 00:39:12.280 --> 00:39:14.917 audience how do you see this diffusion 00:39:15.000 --> 00:39:19.477 occur and the utilization at the corporate level or at a government level 00:39:19.560 --> 00:39:23.117 that which ultimately then creates that demand which eliminates any fears of 00:39:23.200 --> 00:39:26.837 bubbles. Yeah, now I think it it's probably one of the the the big 00:39:26.920 --> 00:39:28.357 challenges with all of these new 00:39:28.440 --> 00:39:31.117 technologies is when uh 00:39:31.200 --> 00:39:36.157 work work artifact and workflow changes, 00:39:36.240 --> 00:39:40.437 uh that means we as firms have to change 00:39:40.520 --> 00:39:44.037 how we work. In fact, I remember meeting um 00:39:44.120 --> 00:39:48.317 uh the CEO of Generali, you know, a few years back and he was describing he had 00:39:48.400 --> 00:39:52.657 joined um the firm, you know, pre-PC era 00:39:52.740 --> 00:39:56.917 [clears throat] and uh and he was describing how, for example, they worked 00:39:57.000 --> 00:39:59.557 with their agents in the field with 00:39:59.640 --> 00:40:03.037 faxes, interoffice memos and 00:40:03.120 --> 00:40:07.077 and and suddenly the PC showed up and people would then put a spreadsheet in 00:40:07.160 --> 00:40:11.197 an email and send it around and the entire workflow and the work process 00:40:11.280 --> 00:40:13.957 changed. Right? So, similarly, I think 00:40:14.040 --> 00:40:17.437 with AI, you are going to start seeing 00:40:17.520 --> 00:40:20.317 actual change in how workflow happens. 00:40:20.400 --> 00:40:23.917 Right? I mean, even >> [clears throat] >> in fact, for me coming to Davos, you 00:40:24.000 --> 00:40:28.957 know, whatever 50 bilateral meetings I have, preparing for those 00:40:29.040 --> 00:40:33.637 had a particular workflow, right? Which is there is to be my field team would 00:40:33.720 --> 00:40:37.997 prepare notes and that would come to my HQ and that would get further refined 00:40:38.080 --> 00:40:40.117 and nothing had really changed right? 00:40:40.200 --> 00:40:45.437 Since I joined in '92 to essentially even a few years back. Whereas now, I 00:40:45.520 --> 00:40:49.197 just go to Copilot and say, "Hey, I'm meeting Larry, please give me a brief." 00:40:49.280 --> 00:40:53.437 And it comes back and gives me By the way, the one nice thing is it gives me a 00:40:53.520 --> 00:40:57.837 360, right? It knows what we are doing with you as a client, what we are doing 00:40:57.920 --> 00:41:00.637 as a client of yours and everything in between [clears throat] as an 00:41:00.720 --> 00:41:05.477 investment. It's so it captures even information unlike anything else. In 00:41:05.560 --> 00:41:09.997 fact, what I do is I take that and immediately share that back with all of 00:41:10.080 --> 00:41:11.957 my colleagues across all the functions. 00:41:12.040 --> 00:41:16.837 Right? Think about it. It's a complete inversion of how information is flowing 00:41:16.920 --> 00:41:18.877 in the organization. It's not like this 00:41:18.960 --> 00:41:21.677 classic we have an organization, we have 00:41:21.760 --> 00:41:24.157 departments, we have the specializations 00:41:24.240 --> 00:41:26.477 and the information trickles up. No, no, 00:41:26.560 --> 00:41:29.997 no, it actually it flattens the entire 00:41:30.080 --> 00:41:33.037 information flow. So, once you start 00:41:33.120 --> 00:41:35.237 having that, you have to redesign 00:41:35.320 --> 00:41:39.117 structurally. So, the current structure 00:41:39.200 --> 00:41:42.797 may not make sense. Um because you want 00:41:42.880 --> 00:41:46.677 people to be able to work in a way that 00:41:46.760 --> 00:41:48.917 allows them to have this information 00:41:49.000 --> 00:41:52.077 flow freely. So, what all this leads me 00:41:52.160 --> 00:41:53.717 to if I had to sort of say what's the 00:41:53.800 --> 00:41:55.997 formula, the formula I think it starts 00:41:56.080 --> 00:41:59.117 with the mindset. So, the mindset we as 00:41:59.200 --> 00:42:02.357 leaders should have is we need to think 00:42:02.440 --> 00:42:06.037 about changing the work the workflow 00:42:06.120 --> 00:42:10.277 with the technology. Then that needs skill set. So, you can't sort of talk 00:42:10.360 --> 00:42:14.517 about this in the abstract. You got to use it. Like so, if I'm not using the 00:42:14.600 --> 00:42:17.837 You have to trust it. You have to trust it, you have to use it, you have to 00:42:17.920 --> 00:42:20.797 learn even how to put the guardrails to 00:42:20.880 --> 00:42:25.037 trust it, right? So, you can't again you can't just be afraid of it. 00:42:25.120 --> 00:42:27.237 It's going to It's going to be diffused. 00:42:27.320 --> 00:42:29.677 So, the question is as a firm, you have 00:42:29.760 --> 00:42:34.837 to use it to learn how to even put the guardrails that allow you to be 00:42:34.920 --> 00:42:39.677 able to trust it. So, skills, so mindset, skills. The 00:42:39.760 --> 00:42:41.757 other big consideration 00:42:41.840 --> 00:42:45.557 really is how do you make sure you have 00:42:45.640 --> 00:42:47.797 the data set that you're feeding? Like 00:42:47.880 --> 00:42:51.037 context. Like it's kind of like you have 00:42:51.120 --> 00:42:53.517 a new intelligence layer. But the 00:42:53.600 --> 00:42:56.637 intelligence layer is only as good as 00:42:56.720 --> 00:42:59.157 the context you give it. So, people 00:42:59.240 --> 00:43:01.277 describe it even as context engineering. 00:43:01.360 --> 00:43:04.117 But that is what firms do. Right? If you 00:43:04.200 --> 00:43:05.837 think about what do firms do, it's all 00:43:05.920 --> 00:43:08.557 about the tacit knowledge we have by 00:43:08.640 --> 00:43:13.717 working as people in various departments and moving paper and information. So, 00:43:13.800 --> 00:43:17.637 the question is how do you really have this AI also have that context? So, 00:43:17.720 --> 00:43:20.157 these are sort of some of the new things 00:43:20.240 --> 00:43:25.237 that have to percolate throughout an organization to take advantage. In fact, 00:43:25.320 --> 00:43:29.517 that's why I think you're you're going to see that challenge of why am I not 00:43:29.600 --> 00:43:33.197 seeing immediate results in productivity? Because you have to do the 00:43:33.280 --> 00:43:36.477 hard work. In fact, that's why it's not going to be at some, you know, it's 00:43:36.560 --> 00:43:39.797 going to There're going to be firm-wide differences. There are going to There 00:43:39.880 --> 00:43:42.717 could be [clears throat] sector-wide differences, but it's going to 00:43:42.800 --> 00:43:47.877 fundamentally be because of the leadership will in an organization. 00:43:47.960 --> 00:43:52.557 Do you see the applications being used across large companies and medium and 00:43:52.640 --> 00:43:56.157 small companies or is it still the domain of mostly the large companies at 00:43:56.240 --> 00:43:59.637 this moment? >> I think that what you're seeing is it's 00:43:59.720 --> 00:44:05.397 easier the because if you have a green sort of 00:44:05.480 --> 00:44:07.917 you know, you if you start fresh it's 00:44:08.000 --> 00:44:10.117 easier to adopt these tools and you 00:44:10.200 --> 00:44:15.077 construct your organization knowing that these tools exist. So, is it a barbell 00:44:15.160 --> 00:44:19.997 then? It is a barbell. So, small companies that are just starting use that platform. 00:44:20.080 --> 00:44:23.177 >> 100% and I think in fact, I would say even for large organizations, there's 00:44:23.260 --> 00:44:26.157 [clears throat] a fundamental challenge, right? Because unless and until your 00:44:26.240 --> 00:44:30.037 rate of change keeps up with Right. what 00:44:30.120 --> 00:44:34.877 with what is possible, you're you're going to get schooled by someone small 00:44:34.960 --> 00:44:40.077 being able to achieve scale because of these tools. So, but I think scale Large 00:44:40.160 --> 00:44:41.757 organizations have an inherent strength. 00:44:41.840 --> 00:44:45.477 You have the relationships, you have the data, you have 00:44:45.560 --> 00:44:47.917 you have know-how, but the bottom line 00:44:48.000 --> 00:44:50.397 is if you don't translate that with a 00:44:50.480 --> 00:44:55.277 new production function then you really will be stuck. And so, therefore, the 00:44:55.360 --> 00:44:59.757 change management challenge for large organizations is going to be bigger. 00:44:59.840 --> 00:45:03.557 The structural challenge for small organizations of how to overcome scale 00:45:03.640 --> 00:45:06.797 issues are going to be harder. So, it's sort of the two sides. In an interesting 00:45:06.880 --> 00:45:11.717 way, it's going to be a very competitively intense world where 00:45:11.800 --> 00:45:13.797 neither side, like whether you're a new 00:45:13.880 --> 00:45:15.957 entrant or an incumbent, can't take it 00:45:16.040 --> 00:45:20.397 as like I I can just coast. What about 00:45:20.480 --> 00:45:23.957 country to country? Are you seeing big differences in how the applications are 00:45:24.040 --> 00:45:27.957 being used? Is it Is AI still the domain of developed 00:45:28.040 --> 00:45:31.597 countries or is it becoming rapidly a domain of all countries? 00:45:31.680 --> 00:45:35.717 >> I I'm seeing There are two things I'd say, Larry. As I travel around the 00:45:35.800 --> 00:45:39.797 world, the quality of 00:45:39.880 --> 00:45:42.077 whether it's the know-how, the software 00:45:42.160 --> 00:45:46.517 developers, the startups or even large 00:45:46.600 --> 00:45:50.797 or large organizations, it's not that different. It's fascinating. You can 00:45:50.880 --> 00:45:54.477 show up in Jakarta, you can show up in Istanbul, you can show up in Mexico 00:45:54.560 --> 00:45:57.037 City. It's not that different than 00:45:57.120 --> 00:45:59.517 showing up even in say Seattle or San 00:45:59.600 --> 00:46:02.037 Francisco, right? It's not for the first 00:46:02.120 --> 00:46:04.797 time just because access to what's 00:46:04.880 --> 00:46:09.157 happening is there. That said 00:46:09.240 --> 00:46:12.757 at [clears throat] scale, the commitment 00:46:12.840 --> 00:46:15.797 to using this, the risk capital being 00:46:15.880 --> 00:46:18.357 there, the large companies pushing it 00:46:18.440 --> 00:46:21.797 hard. I mean, I you know, again, the US, 00:46:21.880 --> 00:46:25.237 you know, is In fact, if I compare it 00:46:25.320 --> 00:46:27.637 take financial sector. 00:46:27.720 --> 00:46:29.797 If in financial sector's adoption of the 00:46:29.880 --> 00:46:33.477 cloud versus AI night and day, right? 00:46:33.560 --> 00:46:36.837 Because in an interesting way, it's much faster 00:46:36.920 --> 00:46:41.277 when it comes to AI versus it was with the cloud. And cloud because of a 00:46:41.360 --> 00:46:44.477 variety of reasons >> And regulatory issues, too. 00:46:44.560 --> 00:46:47.597 Until the regulators allowed banks to 00:46:47.680 --> 00:46:51.637 bring their data off out out of campus, that was a big issue. Yeah. So, I would 00:46:51.720 --> 00:46:54.357 say I think wherever, [clears throat] you know, so 00:46:54.440 --> 00:46:57.557 in the West, in particular in the US, 00:46:57.640 --> 00:47:02.077 there is clearly a real, I'd say, more of an energy 00:47:02.160 --> 00:47:04.357 around it in terms of going and using 00:47:04.440 --> 00:47:07.317 it. But it's sort of a lot more 00:47:07.400 --> 00:47:12.237 uniformly spreading around the world than any technology at least I've seen. 00:47:12.320 --> 00:47:16.637 Are you >> [clears throat] >> Are you You mentioned about power, the grid. 00:47:16.720 --> 00:47:19.997 Is that going to be one of the determinants of of 00:47:20.080 --> 00:47:22.437 the accessibility? If you do not have 00:47:22.520 --> 00:47:24.077 cheap power 00:47:24.160 --> 00:47:27.397 if the demand is costly 100%. So, if you 00:47:27.480 --> 00:47:32.477 sort of look at the tokens per dollar per watt, right? Which I think in some 00:47:32.560 --> 00:47:37.237 [clears throat] sense, I would claim that GDP growth in any place will be 00:47:37.320 --> 00:47:40.877 directly correlated. Like you if you sort of buy my entire argument that 00:47:40.960 --> 00:47:45.877 look, we've got a new commodity, it's tokens Right. and the job of every 00:47:45.960 --> 00:47:51.397 economy and every firm in the economy is to translate these tokens into economic 00:47:51.480 --> 00:47:54.797 growth. Then if you have a cheaper commodity, 00:47:54.880 --> 00:47:58.757 it's better. And so, that's sort of what why this 00:47:58.840 --> 00:48:02.397 tokens per dollar per watt. And by the way, there are many, many elements to 00:48:02.480 --> 00:48:05.677 this, right? Which is it's not just the 00:48:05.760 --> 00:48:09.717 production side. That's why I think even having the grid is important. 00:48:09.800 --> 00:48:12.077 Uh construction costs, right? So, if you 00:48:12.160 --> 00:48:14.717 like if you think about the total TCO 00:48:14.800 --> 00:48:17.397 everything, it's like how are you a 00:48:17.480 --> 00:48:19.557 cheap producer of energy? Can you build 00:48:19.640 --> 00:48:22.397 the data centers? Then what's the cost 00:48:22.480 --> 00:48:26.437 curve of the silicon in the systems? And 00:48:26.520 --> 00:48:29.077 by the way, look at the token pricing, 00:48:29.160 --> 00:48:32.397 right? Token pricing basically drops by, 00:48:32.480 --> 00:48:35.997 you know, a half every 3 months. 00:48:36.080 --> 00:48:38.397 I mean, this is a So, how So, that 00:48:38.480 --> 00:48:40.917 that's why I think you can sort of 00:48:41.000 --> 00:48:44.557 really plot how you use the tokens to 00:48:44.640 --> 00:48:48.717 create surplus knowing that you have a commodity that's whose prices are just 00:48:48.800 --> 00:48:50.397 going to monotonically come down in a 00:48:50.480 --> 00:48:52.197 pretty fast curve. We're sitting in 00:48:52.280 --> 00:48:56.997 Europe. And there is a real fear 00:48:57.080 --> 00:49:00.957 because of the Europe does not have its own power. 00:49:01.040 --> 00:49:03.557 It has to import mostly of its power. 00:49:03.640 --> 00:49:07.517 Um Do you have any messages for Europe 00:49:07.600 --> 00:49:10.957 related to this? Yeah, I mean, I think So, there are two sets of things, right? 00:49:11.040 --> 00:49:13.477 One is you know, here we are in in 00:49:13.560 --> 00:49:18.317 Switzerland and I look at the the pharma or the financial sector, 00:49:18.400 --> 00:49:22.757 you know, obviously they're they they do do a big job in in 00:49:22.840 --> 00:49:25.877 in this country as in in Europe, but they're also international brands and 00:49:25.960 --> 00:49:30.597 international operations. So, one thing that whenever I think about Europe is 00:49:30.680 --> 00:49:34.717 the Europeans are producing products and services that actually are going 00:49:34.800 --> 00:49:37.517 everywhere in the world. And so, therefore, 00:49:37.600 --> 00:49:41.717 European competitiveness is about the competitiveness of their output 00:49:41.800 --> 00:49:45.197 globally, not just in Europe. I think sometimes when you come to Europe, 00:49:45.280 --> 00:49:47.077 there's a lot of conversation about just 00:49:47.160 --> 00:49:50.917 Europe. But European economy is 00:49:51.000 --> 00:49:54.877 thrives and has, you know, thrived in the last whatever 200 years, 300 years. 00:49:54.960 --> 00:49:59.157 The miracle of the West is fundamentally because of what has happened in Europe, 00:49:59.240 --> 00:50:02.717 is because they were able to produce things that the world needed. And so I 00:50:02.800 --> 00:50:06.357 would say that's number one. And in order to do that, you again, I go back 00:50:06.440 --> 00:50:08.317 to the human capital here is just 00:50:08.400 --> 00:50:13.437 fantastic, it's world-class. You have to absolutely invest in 00:50:13.520 --> 00:50:18.117 producing, you know, having the energy and the tokens here, which again, you're 00:50:18.200 --> 00:50:22.317 attracting like as I said, we are investing and others are investing 00:50:22.400 --> 00:50:26.357 the data centers here. So the question is, what's that next generation of 00:50:26.440 --> 00:50:29.797 output that comes from here, right? I always think about the German 00:50:29.880 --> 00:50:33.877 Mittelstand. Whenever I go to a jeweler or a dentist in the United States, I'm 00:50:33.960 --> 00:50:35.957 surrounded by German Mittelstand, right? 00:50:36.040 --> 00:50:38.757 Yes. Totally. It's just unbelievable 00:50:38.840 --> 00:50:42.277 engineering prowess of that country. 00:50:42.360 --> 00:50:43.757 And now the question And by the way, 00:50:43.840 --> 00:50:46.317 that's the point. They are producing 00:50:46.400 --> 00:50:49.557 industrial products, which today are 00:50:49.640 --> 00:50:52.877 built in into it all the intelligence as 00:50:52.960 --> 00:50:55.437 well. That data, right? So I know 00:50:55.520 --> 00:50:57.277 whenever we come to Europe, everyone's 00:50:57.360 --> 00:50:59.917 like talking about sovereignty and data 00:51:00.000 --> 00:51:02.757 this, data that. Guess what? Europe 00:51:02.840 --> 00:51:05.757 actually should be much more concerned 00:51:05.840 --> 00:51:08.637 about access to their industrial 00:51:08.720 --> 00:51:11.117 companies, their financial services 00:51:11.200 --> 00:51:14.517 companies of data from you US and the 00:51:14.600 --> 00:51:18.757 rest of the world. As opposed to just thinking that somehow by protecting 00:51:18.840 --> 00:51:20.357 Europe, you're going to be competitive. 00:51:20.440 --> 00:51:25.077 You are only going to be competitive if the products coming out of Europe are 00:51:25.160 --> 00:51:26.677 globally competitive. 00:51:26.760 --> 00:51:30.117 >> Right. And so that's I think what needs 00:51:30.200 --> 00:51:32.277 to change. And you know, Europe has led 00:51:32.360 --> 00:51:35.117 in privacy, that's fantastic, has led in 00:51:35.200 --> 00:51:39.797 many aspects of even safety around AI and what have you. And that's a feature 00:51:39.880 --> 00:51:44.277 that's great. But you also have to complement it with by building locally 00:51:44.360 --> 00:51:48.997 and then also thinking globally. What's the contribution this continent will 00:51:49.080 --> 00:51:52.237 make to the rest of the world, which it has 00:51:52.320 --> 00:51:54.757 historically been a leader in. 00:51:54.840 --> 00:51:58.917 >> So do you think the whole idea around sovereignty of data, is that being 00:51:59.000 --> 00:52:02.877 misunderstood? I I think that that when people talk 00:52:02.960 --> 00:52:07.677 about sovereignty, first of all, it's very important, 00:52:07.760 --> 00:52:09.757 clearly Who owns the data? And in a week 00:52:09.840 --> 00:52:12.797 like this, it's more important. Uh 00:52:12.880 --> 00:52:15.837 but that said, uh 00:52:15.920 --> 00:52:19.997 it is you have to kind of think about how what 00:52:20.080 --> 00:52:24.237 is sovereignty mean. Like for example, in the AI era, the topic that's least 00:52:24.320 --> 00:52:26.637 talked about, but I feel will be most 00:52:26.720 --> 00:52:29.797 talked about in in this this calendar 00:52:29.880 --> 00:52:32.637 year, will be the sovereignty of a firm. 00:52:32.720 --> 00:52:35.357 Just imagine, if your firm 00:52:35.440 --> 00:52:38.237 you're not able to embed the tacit 00:52:38.320 --> 00:52:42.597 knowledge of the firm in a set of weights 00:52:42.680 --> 00:52:45.237 in a model that you control, 00:52:45.320 --> 00:52:47.837 by definition, you have no sovereignty. 00:52:47.920 --> 00:52:49.677 That means you're leaking enterprise 00:52:49.760 --> 00:52:52.997 value to some model company somewhere. 00:52:53.080 --> 00:52:56.437 In fact, that it's sort of fascinating that nobody's talking about that, right? 00:52:56.520 --> 00:52:59.797 It's like everybody's talking about everything else that is sort of, you 00:52:59.880 --> 00:53:03.157 know, outside of that. Whereas the most 00:53:03.240 --> 00:53:06.917 important thing is, it really doesn't matter if you have In fact, the data 00:53:07.000 --> 00:53:10.677 center, where it runs, is the least important thing, quite honestly. But 00:53:10.760 --> 00:53:14.317 like even there, first of all, the data centers all are all over just because 00:53:14.400 --> 00:53:16.797 speed of light is a real constraint. 00:53:16.880 --> 00:53:21.077 And so therefore, the data centers will be spread. You will have digital You'll 00:53:21.160 --> 00:53:24.837 be able to encrypt everything. You'll be able to have the keys with you. All of 00:53:24.920 --> 00:53:26.957 these are much more technically solved 00:53:27.040 --> 00:53:29.837 problems. But the one problem that will 00:53:29.920 --> 00:53:33.037 only be solved is by you having much 00:53:33.120 --> 00:53:37.797 more sovereignty over the you know, tacit knowledge and control over the 00:53:37.880 --> 00:53:42.557 models. And it's not a one-way enterprise value transfer. And so to me, 00:53:42.640 --> 00:53:44.797 I think sovereignty requires real 00:53:44.880 --> 00:53:47.277 thought on what is it? 00:53:47.360 --> 00:53:49.717 You know, control of destiny means that 00:53:49.800 --> 00:53:52.797 your your ability to produce something 00:53:52.880 --> 00:53:57.117 that is unique is preserved. David Ricardo was not wrong. There's 00:53:57.200 --> 00:53:59.757 comparative advantage in countries. 00:53:59.840 --> 00:54:03.077 There is comparative advantage in firms. 00:54:03.160 --> 00:54:07.277 That needs to be preserved even in the AI era. That's what will give you real 00:54:07.360 --> 00:54:11.797 sovereignty. One last question. I know we're running out of time. 00:54:11.880 --> 00:54:15.837 Um in 5 years or 10 years, is there going to be one dominant model that 00:54:15.920 --> 00:54:20.237 we're all going to be using or or And how is Microsoft preparing for this? Are 00:54:20.320 --> 00:54:22.117 you going to be Are we going to be using 00:54:22.200 --> 00:54:25.077 one model for for enterprise, one model 00:54:25.160 --> 00:54:28.157 for other other trades? You know, even 00:54:28.240 --> 00:54:30.757 in the last whatever 3 years, 4 years 00:54:30.840 --> 00:54:32.677 that we've been at it, 00:54:32.760 --> 00:54:36.357 the the reality at this point is it's a 00:54:36.440 --> 00:54:41.677 multi-model world, right? I mean, the In fact, if you think about it, 00:54:41.760 --> 00:54:46.277 the in both there are going to be 00:54:46.360 --> 00:54:48.157 multiple models. 00:54:48.240 --> 00:54:51.277 And the trick is really how do you take 00:54:51.360 --> 00:54:54.117 advantage of these multiple models 00:54:54.200 --> 00:54:56.557 and in fact, build your own model by 00:54:56.640 --> 00:54:59.557 distilling these, right? So think of 00:54:59.640 --> 00:55:02.757 these models that you orchestrate to 00:55:02.840 --> 00:55:04.397 build your own model. And more 00:55:04.480 --> 00:55:07.677 importantly, you do what is described as 00:55:07.760 --> 00:55:10.597 orchestration or harness engineering. So 00:55:10.680 --> 00:55:14.677 the IP of any application or any firm is 00:55:14.760 --> 00:55:17.917 how do you use all these models with 00:55:18.000 --> 00:55:20.077 context engineering or your data? Yes. 00:55:20.160 --> 00:55:24.197 Right? So it's that three parts. So can I bring in all the models, by the way, 00:55:24.280 --> 00:55:26.797 which is close source, open source, 00:55:26.880 --> 00:55:30.037 build my own model, orchestrate them, 00:55:30.120 --> 00:55:33.437 and feed it my data to change the 00:55:33.520 --> 00:55:36.077 trajectory of some outcome that I care 00:55:36.160 --> 00:55:38.437 about. That's it. That's the entire 00:55:38.520 --> 00:55:40.797 picture. So you can do it in like, oh, I 00:55:40.880 --> 00:55:43.397 produce a particular product or service. 00:55:43.480 --> 00:55:48.557 First, I got to do better better job in sales or better job in R&D or better job 00:55:48.640 --> 00:55:52.237 in finance or what have you. And you take that outcome, and then you say, can 00:55:52.320 --> 00:55:54.757 I use all the models, orchestrate them, 00:55:54.840 --> 00:55:57.197 and feed it my context? And then in as a 00:55:57.280 --> 00:56:00.277 result of it, the reasoning traces are 00:56:00.360 --> 00:56:03.117 really leading to some capability and 00:56:03.200 --> 00:56:06.397 models that I control as my IP. As long 00:56:06.480 --> 00:56:10.957 as firms can answer that question, they're going to be getting ahead. 00:56:11.040 --> 00:56:15.827 Ladies and gentlemen, let's thank Satya, my friend, 00:56:15.910 --> 00:56:19.440 >> [applause] >> for 00:56:20.960 --> 00:56:25.797 And hopefully this is the beginning of many great dialogue and conversations here 00:56:25.880 --> 00:56:30.280 at the World Economic Forum. Thank you everyone. Thank you. 01:09:28.480 --> 01:09:30.640 >> Mhm. 01:12:21.240 --> 01:12:23.400 >> Mhm.