1 00:00:00,080 --> 00:00:02,077 is everything. And so the way it happens 2 00:00:02,160 --> 00:00:06,237 is let's sort of unpack this uh on the 3 00:00:06,320 --> 00:00:08,397 supply side what needs to happen in each 4 00:00:08,480 --> 00:00:11,437 country is the tokens per dollar per 5 00:00:11,520 --> 00:00:14,957 watt have to sort of monotonically get 6 00:00:15,040 --> 00:00:19,197 more efficient and better. Right? So to some degree even what we're trying to do 7 00:00:19,280 --> 00:00:23,837 with the investments the two firms are doing uh around the world is to just say 8 00:00:23,920 --> 00:00:25,517 that like let's make sure that the 9 00:00:25,600 --> 00:00:28,157 supply is there which is uh everything 10 00:00:28,240 --> 00:00:33,357 from the chips on down ultimately to these token factories that get deployed 11 00:00:33,440 --> 00:00:37,517 everywhere. By the way there's not one token factory. This token factory is the 12 00:00:37,600 --> 00:00:41,117 first thing that's going to be diffused all around the world. It's just like 13 00:00:41,200 --> 00:00:44,157 electricity right? you just need a 14 00:00:44,240 --> 00:00:48,877 ubiquitous grid of uh energy and tokens 15 00:00:48,960 --> 00:00:51,517 that then will power the rest of the 16 00:00:51,600 --> 00:00:53,437 economy right so that's I think one side 17 00:00:53,520 --> 00:00:56,877 of it then the demand side of this is a 18 00:00:56,960 --> 00:00:59,917 little bit like every firm has to start 19 00:01:00,000 --> 00:01:03,197 by using it if I look back even you know 20 00:01:03,280 --> 00:01:08,477 when the PCs first came out or the personal computing era started I I loved 21 00:01:08,560 --> 00:01:12,797 you know I think Jobs had a nice metaphor he called it the bicycle for the 22 00:01:12,880 --> 00:01:16,957 uh Bill had a metaphor which I remember was like information at your fingertips. 23 00:01:17,040 --> 00:01:20,637 Right? These two metaphors were great like which allowed us to say that's what 24 00:01:20,720 --> 00:01:22,797 it is. It's a tool that I will use to 25 00:01:22,880 --> 00:01:24,877 get information at my fingertips. I'll 26 00:01:24,960 --> 00:01:28,637 use it as a cognitive amplifier. Now I 27 00:01:28,720 --> 00:01:31,357 think that's what we have but you know 28 00:01:31,440 --> 00:01:33,917 10x 100x right? So in some sense you as 29 00:01:34,000 --> 00:01:37,677 a as every knowledge worker you now have 30 00:01:37,760 --> 00:01:41,837 access to infinite minds. That's the way I think about it. Right? So there's a 31 00:01:41,920 --> 00:01:44,317 Turing award winner uh called Raj Ready 32 00:01:44,400 --> 00:01:49,037 who had this nice metaphor of AI and he had this long before uh even generative 33 00:01:49,120 --> 00:01:53,197 AI he said either either it's a cognitive amplifier or it's a guardian 34 00:01:53,280 --> 00:01:55,997 angel right so if you think of AI as 35 00:01:56,080 --> 00:01:59,037 that um then that in the global 36 00:01:59,120 --> 00:02:03,117 workforce right when a doctor can get to 37 00:02:03,200 --> 00:02:07,117 a patient spend more time with the patient because the AI is doing the 38 00:02:07,200 --> 00:02:09,357 transcription and entering the records 39 00:02:09,440 --> 00:02:12,237 in the EMR system entering the right 40 00:02:12,320 --> 00:02:14,957 billing code so that the health care uh 41 00:02:15,040 --> 00:02:17,117 you know industry is better served 42 00:02:17,200 --> 00:02:20,157 across the payer the provider and uh and 43 00:02:20,240 --> 00:02:23,037 the patient ultimately right that's an 44 00:02:23,120 --> 00:02:25,117 an outcome that I think all of us can 45 00:02:25,200 --> 00:02:28,077 benefit from so I feel ultimately it's 46 00:02:28,160 --> 00:02:30,637 going to require real leadership on the 47 00:02:30,720 --> 00:02:33,197 private sector and the public sector to 48 00:02:33,280 --> 00:02:35,997 ensure the diffusion happens and the one 49 00:02:36,080 --> 00:02:39,117 thing I'll mention Larry is skilling 50 00:02:39,200 --> 00:02:43,117 right so In some sense the thing that 51 00:02:43,200 --> 00:02:46,877 diffusion is very strongly correlated to 52 00:02:46,960 --> 00:02:49,837 one thing alone which is how broadly are 53 00:02:49,920 --> 00:02:54,077 people skilled in using this. Um and 54 00:02:54,160 --> 00:02:56,317 interestingly enough, I think if mobile 55 00:02:56,400 --> 00:02:59,677 has taught us one thing is it it's 56 00:02:59,760 --> 00:03:03,597 actually distinct from what happened in the PC, right? Uh I remember even 57 00:03:03,680 --> 00:03:05,997 growing up in the global south, uh there 58 00:03:06,080 --> 00:03:08,797 used to be a real relationship between 59 00:03:08,880 --> 00:03:12,157 learning Excel skills or word skills and 60 00:03:12,240 --> 00:03:16,397 getting a job. Um you know, right now um 61 00:03:16,480 --> 00:03:20,557 what's the model in in mobile? It's kind of created the same opportunity, but 62 00:03:20,640 --> 00:03:22,717 it's been a lot more consumptionled. 63 00:03:22,800 --> 00:03:27,037 It's these creator economy and what have you, but it has not been about sort of, 64 00:03:27,120 --> 00:03:30,717 oh wow, here's how you get a healthcare job or here is how you get a finance job 65 00:03:30,800 --> 00:03:32,877 or here is how you get, you know, you 66 00:03:32,960 --> 00:03:35,517 get ahead professionally. 67 00:03:35,600 --> 00:03:38,637 Um, and that needs to come back, right? 68 00:03:38,720 --> 00:03:40,477 People need to say, I pick up this AI 69 00:03:40,560 --> 00:03:43,437 skill and now I'm a better provider of 70 00:03:43,520 --> 00:03:47,857 some product or service in the real economy. So it's it's very easy 71 00:03:47,940 --> 00:03:51,517 [clears throat] to see how mobile and the diffusion of mobile how it 72 00:03:51,600 --> 00:03:53,757 transformed economies especially in the 73 00:03:53,840 --> 00:03:57,117 global south. How does how do this you 74 00:03:57,200 --> 00:03:59,277 know to me I I I just read a research 75 00:03:59,360 --> 00:04:04,237 report that said the applications for AI so far are 76 00:04:04,320 --> 00:04:08,877 heavily weighted towards those who are educated or educated economies. 77 00:04:08,960 --> 00:04:12,957 And so does that create that you know more of a bifurcation a more 78 00:04:13,040 --> 00:04:15,277 polarization? How do we ensure that that 79 00:04:15,360 --> 00:04:18,317 that diffusion is spread evenly? How do 80 00:04:18,400 --> 00:04:19,957 we make sure that we're not 81 00:04:20,040 --> 00:04:25,437 [clears throat] leaving major portions of society or the world behind because I 82 00:04:25,520 --> 00:04:27,837 think that's that's going to [clears throat] be the big issue for us 83 00:04:27,920 --> 00:04:30,077 going forward. >> Yeah. So, it's it's it's interesting, 84 00:04:30,160 --> 00:04:33,837 right? This is one of those times when 85 00:04:33,920 --> 00:04:37,357 uh by definition and because of the 86 00:04:37,440 --> 00:04:41,357 rails that have been established you know as you said right which is 87 00:04:41,440 --> 00:04:44,237 >> uh what's happened with mobile as well 88 00:04:44,320 --> 00:04:48,717 as what's happened with um uh you know essentially connectivity 89 00:04:48,800 --> 00:04:52,317 >> right >> you have the ability to sort of deliver 90 00:04:52,400 --> 00:04:55,677 the tokens pretty evenly around the world >> right 91 00:04:55,760 --> 00:05:00,637 >> a lot more so than let's say uh the PC era or even the beginning of the mobile 92 00:05:00,720 --> 00:05:04,637 era, right? Because it took a long time for even the mo smartphone in particular 93 00:05:04,720 --> 00:05:09,277 to penetrate um all of the world. Whereas now it's 94 00:05:09,360 --> 00:05:11,517 not the case, right? These models and 95 00:05:11,600 --> 00:05:14,637 their outputs are pretty much available 96 00:05:14,720 --> 00:05:18,797 everywhere. And so the question to me is 97 00:05:18,880 --> 00:05:22,557 what's the use cases that make sense, right? It's one, in fact, one of the 98 00:05:22,640 --> 00:05:24,637 demos I always go back to. I think this 99 00:05:24,720 --> 00:05:27,197 was even in the beginning of 23 was a 100 00:05:27,280 --> 00:05:30,077 rural Indian farmer was able to use a 101 00:05:30,160 --> 00:05:33,357 bot built on I think a very early GPT3 102 00:05:33,440 --> 00:05:37,357 or 25 even uh essentially to reason over 103 00:05:37,440 --> 00:05:39,437 some farm subsidies that he had heard 104 00:05:39,520 --> 00:05:41,997 about in a local language and had it 105 00:05:42,080 --> 00:05:45,597 even in that very early days uh have it 106 00:05:45,680 --> 00:05:47,597 even show some agentic behavior, right? 107 00:05:47,680 --> 00:05:49,517 Like go complete a form for me. So in 108 00:05:49,600 --> 00:05:51,837 some sense it took you know it brought 109 00:05:51,920 --> 00:05:56,637 back agency to someone uh who perhaps 110 00:05:56,720 --> 00:06:01,197 didn't have that because the technology was so much more accessible. So I I do 111 00:06:01,280 --> 00:06:03,357 think it's in our hands even in the 112 00:06:03,440 --> 00:06:07,437 global south to use it uh to create I 113 00:06:07,520 --> 00:06:10,077 would say more of that opportunity where 114 00:06:10,160 --> 00:06:13,837 there isn't one. Um but I think what the 115 00:06:13,920 --> 00:06:17,677 necessary [clears throat] conditions still are do you have uh the 116 00:06:17,760 --> 00:06:22,317 capital investment being put in uh do you even have an environment for capital 117 00:06:22,400 --> 00:06:26,317 because in an interesting way we are for example as hyperscalers investing all 118 00:06:26,400 --> 00:06:30,557 over right including the global south uh so as long as there's an environment 119 00:06:30,640 --> 00:06:33,517 which attracts the capital investment >> and you see the demand 120 00:06:33,600 --> 00:06:36,397 >> and you see and then yeah the demand is there 121 00:06:36,480 --> 00:06:40,717 >> um and so the question is how do you have a set of policies that allow for 122 00:06:40,800 --> 00:06:45,277 both the capital to come in for it to find nexus with there are certain things 123 00:06:45,360 --> 00:06:49,197 by the way private capital can do certain things that public capital only 124 00:06:49,280 --> 00:06:52,237 can do for example the grid right it's 125 00:06:52,320 --> 00:06:57,197 not I mean grid in most countries is sort of fundamentally driven by governments 126 00:06:57,280 --> 00:07:00,397 >> and public >> and public and so if you don't have a 127 00:07:00,480 --> 00:07:04,397 sophisticated sort or rather if you don't have a a real approach to 128 00:07:04,480 --> 00:07:08,797 modernizing the grid uh that will hold things back I mean there's a lot of talk 129 00:07:08,880 --> 00:07:12,237 about behind the meter and so on and Yes, there's some amount of that we can 130 00:07:12,320 --> 00:07:14,877 do ourselves. >> We can do that in the US. Many countries can't. 131 00:07:14,960 --> 00:07:16,477 >> Exactly. And it's not long-term 132 00:07:16,560 --> 00:07:18,397 scalable, right? I mean, like to me, a 133 00:07:18,480 --> 00:07:21,917 long-term scalable solution is to have 134 00:07:22,000 --> 00:07:26,717 uh you know, all of these token factories, part of the real economy, 135 00:07:26,800 --> 00:07:31,357 connected to the grid, connected to the telco network, delivering uh just like 136 00:07:31,440 --> 00:07:33,357 we delivered bits, you have to deliver 137 00:07:33,440 --> 00:07:36,397 tokens plus bits. Um and that's kind of 138 00:07:36,480 --> 00:07:40,717 what's going to drive an at scale whether it's in the global south or in 139 00:07:40,800 --> 00:07:44,077 uh on the developed world. >> So so many people talk about there may 140 00:07:44,160 --> 00:07:46,077 be an AI bubble. I mean the most 141 00:07:46,160 --> 00:07:47,437 important thing that we see as an 142 00:07:47,520 --> 00:07:51,597 investor is the the democratization of 143 00:07:51,680 --> 00:07:54,477 technology is and the diffusion of that 144 00:07:54,560 --> 00:07:57,037 technology really does then transform 145 00:07:57,120 --> 00:08:02,157 the demand and the the companies or the countries that diffuse it fastest are 146 00:08:02,240 --> 00:08:03,677 going to be the ultimate winners. not 147 00:08:03,760 --> 00:08:05,517 the technology creator. 148 00:08:05,600 --> 00:08:09,757 >> That's that's you know it's it's it's 149 00:08:09,840 --> 00:08:12,157 for this not to be a bubble 150 00:08:12,240 --> 00:08:12,717 >> y 151 00:08:12,800 --> 00:08:16,957 >> by definition it requires that the 152 00:08:17,040 --> 00:08:19,197 benefits of this are much more evenly 153 00:08:19,280 --> 00:08:22,877 spread. I mean I think a telltel sign of 154 00:08:22,960 --> 00:08:26,077 if it's a bubble would be if all we're 155 00:08:26,160 --> 00:08:29,597 talking about are the tech firms. Uh 156 00:08:29,680 --> 00:08:34,397 right? If uh all we talk about is what's happening to the technology side that 157 00:08:34,480 --> 00:08:38,157 then that's by day you know it's just purely supply side >> right 158 00:08:38,240 --> 00:08:42,557 >> uh ultimately if we are not talking about wow here is a drug comp you know 159 00:08:42,640 --> 00:08:46,237 drug that was sort of uh brought into the market that's super successful 160 00:08:46,320 --> 00:08:50,797 because it was uh AI accelerated the clinical trial it's not even the magical 161 00:08:50,880 --> 00:08:52,797 molecule right it's kind of even the 162 00:08:52,880 --> 00:08:55,837 rest of what is uh needed in order to 163 00:08:55,920 --> 00:08:58,557 make something much more relevant right 164 00:08:58,640 --> 00:09:03,757 um and So the more [clears throat] we have uh and by the way it's happening 165 00:09:03,840 --> 00:09:08,317 right. So I'm not sort of saying that that's why I'm much more confident that 166 00:09:08,400 --> 00:09:10,717 this is a technology that will in fact 167 00:09:10,800 --> 00:09:14,157 build on the rails of cloud and mobile 168 00:09:14,240 --> 00:09:17,327 diffuse faster and bend the productivity 169 00:09:17,410 --> 00:09:21,437 [clears throat] curve and bring local surplus and 170 00:09:21,520 --> 00:09:23,997 economic growth all around the world. 171 00:09:24,080 --> 00:09:28,317 Not just economic growth driven by capital expenses. 172 00:09:28,400 --> 00:09:33,277 uh right because that's it's a narrow point in time uh calculation is 173 00:09:33,360 --> 00:09:35,837 >> right now that's what we're seeing more >> that's what we're seeing you know you 174 00:09:35,920 --> 00:09:37,357 know in in the developed world in 175 00:09:37,440 --> 00:09:40,957 particular uh but remember my capital 176 00:09:41,040 --> 00:09:44,477 like that the one thing that you know is definitely we spending a lot of it in 177 00:09:44,560 --> 00:09:47,757 the United States but 50% of it is also all over the world 178 00:09:47,840 --> 00:09:51,677 >> right >> um and so interesting enough it depends 179 00:09:51,760 --> 00:09:56,077 on uh demand all over the world and the demand all over the world will only be 180 00:09:56,160 --> 00:09:59,597 there if there is local surplus plus all over the world. And so that's sort of 181 00:09:59,680 --> 00:10:04,317 the way I see the equation. >> So let's drill down a little more. As AI 182 00:10:04,400 --> 00:10:08,397 diffuses, obviously organizations, companies, 183 00:10:08,480 --> 00:10:10,797 governments are going to have to evolve. 184 00:10:10,880 --> 00:10:14,077 Now getting to the demand side. So how 185 00:10:14,160 --> 00:10:15,517 do you think the structure of 186 00:10:15,600 --> 00:10:19,437 organizations is changing in an AI world 187 00:10:19,520 --> 00:10:22,797 across roles, across teams, management? 188 00:10:22,880 --> 00:10:26,397 I'm I'm sure um Microsoft has evolved 189 00:10:26,480 --> 00:10:29,277 itself. So it probably be good to tell 190 00:10:29,360 --> 00:10:31,597 the audience how do you see this 191 00:10:31,680 --> 00:10:36,477 diffusion occur in the utilization at the corporate level or at a government 192 00:10:36,560 --> 00:10:40,237 level that which ultimately then creates that demand which eliminates any fears 193 00:10:40,320 --> 00:10:42,797 it bubbles. >> Yeah. No, I think it it's probably one 194 00:10:42,880 --> 00:10:45,117 of the the the big challenges with all 195 00:10:45,200 --> 00:10:48,637 of these new technologies is when uh 196 00:10:48,720 --> 00:10:52,157 work work artifact and work flow 197 00:10:52,240 --> 00:10:56,957 changes. Uh the means we as firms have 198 00:10:57,040 --> 00:10:59,277 to change how we work. In fact, I 199 00:10:59,360 --> 00:11:02,157 remember meeting um uh the CEO of 200 00:11:02,240 --> 00:11:04,317 General Ali, you know, a few years back 201 00:11:04,400 --> 00:11:09,987 and he was describing he had joined um uh the firm, you know, prec 202 00:11:10,070 --> 00:11:13,037 >> [clears throat] >> era and uh uh and he was describing how, 203 00:11:13,120 --> 00:11:14,717 for example, they worked with their 204 00:11:14,800 --> 00:11:17,997 agents in the field uh with faxes, inter 205 00:11:18,080 --> 00:11:21,277 office memos and um and and suddenly the 206 00:11:21,360 --> 00:11:25,437 PC showed up and people would then put a spreadsheet in an email and send it 207 00:11:25,520 --> 00:11:27,757 around and the entire workflow and the 208 00:11:27,840 --> 00:11:30,237 work process has changed right so 209 00:11:30,320 --> 00:11:33,117 similarly I think with AI uh you are 210 00:11:33,200 --> 00:11:38,077 going to start seeing uh actual change in how workflow happens right I mean 211 00:11:38,160 --> 00:11:41,277 even [clears throat] in fact for me coming to Davos you know 212 00:11:41,360 --> 00:11:44,077 whatever 50 bilateral meetings I have 213 00:11:44,160 --> 00:11:47,117 preparing for those uh had a particular 214 00:11:47,200 --> 00:11:51,997 workflow right which is uh there is to be my field team would prepare notes and 215 00:11:52,080 --> 00:11:56,077 that would come to my HQ and that would get further refined and nothing had 216 00:11:56,160 --> 00:11:58,637 really changed right since I joined in 217 00:11:58,720 --> 00:12:03,677 '92 to essentially even a few years back. Whereas now I just go to co-pilot 218 00:12:03,760 --> 00:12:07,997 and say hey I'm meeting Larry please give me a brief and it comes back and 219 00:12:08,080 --> 00:12:12,237 gives me by the way the one nice thing is it gives me a 360 right it knows what 220 00:12:12,320 --> 00:12:16,797 we're doing with you as a client what we're doing as a client of yours and 221 00:12:16,880 --> 00:12:20,797 everything in between [clears throat] as an investment it's so it captures even 222 00:12:20,880 --> 00:12:23,037 information unlike anything else in fact 223 00:12:23,120 --> 00:12:27,917 what I do is I take that and immediately share that back with all my colleagues 224 00:12:28,000 --> 00:12:32,317 across all the functions right think about it it's a complete inversion of 225 00:12:32,400 --> 00:12:37,117 how information is flowing in the organization. It's not like this classic 226 00:12:37,200 --> 00:12:40,397 we have an organization, we have departments, we have these 227 00:12:40,480 --> 00:12:42,477 specializations and the information 228 00:12:42,560 --> 00:12:45,597 trickles up. No, no, no. It actually it 229 00:12:45,680 --> 00:12:49,277 flattens the entire information flow. So 230 00:12:49,360 --> 00:12:51,917 once you start having that you have to 231 00:12:52,000 --> 00:12:55,357 redesign structurally. Uh so the current 232 00:12:55,440 --> 00:12:59,277 structure may not make sense. um because 233 00:12:59,360 --> 00:13:03,117 you want people to be able to work in a 234 00:13:03,200 --> 00:13:05,597 way that allows them to have this 235 00:13:05,680 --> 00:13:08,557 information flow freely. So what all 236 00:13:08,640 --> 00:13:12,637 this leads me to if I had to sort of say what's the formula the formula I think 237 00:13:12,720 --> 00:13:14,717 it starts with the mindset. So the 238 00:13:14,800 --> 00:13:18,957 mindset we as leaders should have is we 239 00:13:19,040 --> 00:13:21,997 need to think about changing the work 240 00:13:22,080 --> 00:13:25,117 the workflow with the technology then 241 00:13:25,200 --> 00:13:29,357 that needs skill set. So you can't sort of talk about this in the abstract. You 242 00:13:29,440 --> 00:13:32,877 got to use it. Like so if I'm not using the >> you have to trust it. 243 00:13:32,960 --> 00:13:37,037 >> You have to trust it. You have to use it. You have to learn even how to put 244 00:13:37,120 --> 00:13:41,037 the guard rails to trust it. Right? So you can't again you can't just be afraid 245 00:13:41,120 --> 00:13:43,917 of it. Uh it's going to it's going to be 246 00:13:44,000 --> 00:13:46,717 diffused. So the question is as a firm 247 00:13:46,800 --> 00:13:49,917 you have to use it to learn how to even 248 00:13:50,000 --> 00:13:51,997 uh put the guard rails that allow you to 249 00:13:52,080 --> 00:13:55,277 be able to trust it. So skills uh so 250 00:13:55,360 --> 00:13:57,597 mindset skills the other big 251 00:13:57,680 --> 00:14:01,117 consideration u really is how do you 252 00:14:01,200 --> 00:14:04,237 make sure you have the data set that 253 00:14:04,320 --> 00:14:07,357 you're feeding like context like it's 254 00:14:07,440 --> 00:14:09,917 kind of like you have a new intelligence 255 00:14:10,000 --> 00:14:12,477 layer but the intelligence layer is only 256 00:14:12,560 --> 00:14:16,157 as good as the context you give it. So 257 00:14:16,240 --> 00:14:20,957 people describe it even as context engineering but that is what firms do 258 00:14:21,040 --> 00:14:24,957 right if you think about what do firms do it's all about the tacet knowledge we 259 00:14:25,040 --> 00:14:27,917 have by working as people in various 260 00:14:28,000 --> 00:14:31,997 departments and moving paper and information so the question is how do 261 00:14:32,080 --> 00:14:33,917 you really have this AI also have that 262 00:14:34,000 --> 00:14:36,397 context so these are sort of some of the 263 00:14:36,480 --> 00:14:39,197 new things that have to percolate 264 00:14:39,280 --> 00:14:43,517 throughout an organization uh to take advantage in fact that's why I think you 265 00:14:43,600 --> 00:14:46,157 you're going to see that challenge of 266 00:14:46,240 --> 00:14:50,717 why am I not seeing immediate results in productivity because you have to do the 267 00:14:50,800 --> 00:14:53,917 hard work. In fact, that's why it's not going to be at some you know it's going 268 00:14:54,000 --> 00:14:57,117 to there going to be firmwide differences. They're going to there 269 00:14:57,200 --> 00:15:00,077 could be [clears throat] sectorwide differences but it's going to 270 00:15:00,160 --> 00:15:05,037 fundamentally be because of the leadership will in an organization. 271 00:15:05,120 --> 00:15:09,917 >> Do you see the applications being used across large companies and medium and 272 00:15:10,000 --> 00:15:13,517 small companies or is it still the domain of mostly the large companies at 273 00:15:13,600 --> 00:15:15,757 this moment? I I think that what you're 274 00:15:15,840 --> 00:15:19,197 seeing is it's easier the because if you 275 00:15:19,280 --> 00:15:23,277 have a green sort of um uh you know if 276 00:15:23,360 --> 00:15:26,077 you start fresh it's easier to adopt 277 00:15:26,160 --> 00:15:30,957 these tools and you construct your organization knowing that these tools 278 00:15:31,040 --> 00:15:32,957 exist. So >> is it a barbell then? 279 00:15:33,040 --> 00:15:37,197 >> It is a barbell. So small companies that are just starting use that platform 280 00:15:37,280 --> 00:15:40,507 >> 100%. And I think in fact I would say even for large organization there's 281 00:15:40,590 --> 00:15:43,757 [clears throat] a fundamental challenge right because unless and until your rate 282 00:15:43,840 --> 00:15:46,637 of change keeps up with >> right 283 00:15:46,720 --> 00:15:49,117 >> uh with with what is possible uh you 284 00:15:49,200 --> 00:15:51,597 you're going to get schooled by someone 285 00:15:51,680 --> 00:15:56,317 small being able to achieve scale because of these tools. So but I think 286 00:15:56,400 --> 00:15:59,597 scale large organizations have an inherent strength. You have the 287 00:15:59,680 --> 00:16:01,437 relationships, you have the data, you 288 00:16:01,520 --> 00:16:04,957 have um you have knowhow, but the bottom 289 00:16:05,040 --> 00:16:07,597 line is if you don't translate that with 290 00:16:07,680 --> 00:16:12,477 a new production function, uh then you really will be stuck. And so therefore 291 00:16:12,560 --> 00:16:15,997 the change management challenge for large organizations is going to be 292 00:16:16,080 --> 00:16:20,557 bigger. The structural challenge for small organizations of how to overcome 293 00:16:20,640 --> 00:16:23,757 scale issues is going to be harder. So it's sort of the two sides in an 294 00:16:23,840 --> 00:16:25,277 interesting way. It's going to be a very 295 00:16:25,360 --> 00:16:28,957 competitively intense world uh where 296 00:16:29,040 --> 00:16:31,117 neither side like whether you're a new 297 00:16:31,200 --> 00:16:33,597 entrant or an incumbent can't take it as 298 00:16:33,680 --> 00:16:37,597 like I I can just coast. What about 299 00:16:37,680 --> 00:16:41,357 country to country? Are you seeing big differences in how the applications are 300 00:16:41,440 --> 00:16:44,397 being used? Is it is AI still the domain 301 00:16:44,480 --> 00:16:49,197 of developed countries or is it becoming rapidly a domain of all countries? I I 302 00:16:49,280 --> 00:16:50,877 I'm seeing there are [clears throat] two 303 00:16:50,960 --> 00:16:52,637 things I would say Larry as I travel 304 00:16:52,720 --> 00:16:56,957 around the world the quality of um 305 00:16:57,040 --> 00:16:59,437 whether it's the knowhow the software 306 00:16:59,520 --> 00:17:02,317 developers the startups 307 00:17:02,400 --> 00:17:06,077 um or even large or large organizations 308 00:17:06,160 --> 00:17:09,597 it's not that different it's fascinating you can show up in Jakarta you can show 309 00:17:09,680 --> 00:17:11,757 up in Istanbul you can show up in Mexico 310 00:17:11,840 --> 00:17:14,317 City it's not that different than 311 00:17:14,400 --> 00:17:16,877 showing up even in say Seattle or San 312 00:17:16,960 --> 00:17:19,117 Francisco right it's not uh for the 313 00:17:19,200 --> 00:17:22,157 first time just because access to what's 314 00:17:22,240 --> 00:17:26,617 happening uh is there that said at 315 00:17:26,700 --> 00:17:30,557 [clears throat] scale the commitment to 316 00:17:30,640 --> 00:17:33,597 using this the risk capital being there 317 00:17:33,680 --> 00:17:36,877 the large companies pushing it hard I 318 00:17:36,960 --> 00:17:40,397 mean I you know again the US you know is 319 00:17:40,480 --> 00:17:43,117 in fact if I compare it uh take 320 00:17:43,200 --> 00:17:46,397 financial sector if financial sector's 321 00:17:46,480 --> 00:17:48,157 adoption of the cloud 322 00:17:48,240 --> 00:17:51,037 versus AI night and day, right? Because 323 00:17:51,120 --> 00:17:54,397 in an interesting way, it's much faster 324 00:17:54,480 --> 00:17:58,877 uh when it comes to AI versus it was with the cloud and cloud because for a 325 00:17:58,960 --> 00:18:02,237 variety of reasons >> and regulatory issues too until the 326 00:18:02,320 --> 00:18:07,837 regulators allowed banks to bring their data off out of campus that was a big 327 00:18:07,920 --> 00:18:10,717 issue. >> Yeah. So I would say I think wherever [clears throat] 328 00:18:10,800 --> 00:18:13,677 you know so in the west in particular in 329 00:18:13,760 --> 00:18:17,677 the US uh there is clearly a real I 330 00:18:17,760 --> 00:18:20,397 would say more of an energy around it in 331 00:18:20,480 --> 00:18:23,277 terms of going and using it uh but it's 332 00:18:23,360 --> 00:18:28,557 sort of a lot more uniformly spreading around the world than any technology at 333 00:18:28,640 --> 00:18:30,637 least I've seen >> but are you [clears throat] you 334 00:18:30,720 --> 00:18:33,997 mentioned about the power the grid is 335 00:18:34,080 --> 00:18:35,597 that going to be one of the determinants 336 00:18:35,680 --> 00:18:39,197 of of the accessibility If you do not 337 00:18:39,280 --> 00:18:43,437 have cheap power it the demand is costly 338 00:18:43,520 --> 00:18:46,637 >> 100%. So if you sort of look at the 339 00:18:46,720 --> 00:18:49,037 tokens per dollar per watt right which I 340 00:18:49,120 --> 00:18:50,557 think in some [clears throat] sense I 341 00:18:50,640 --> 00:18:54,157 would claim that GDP growth in any place 342 00:18:54,240 --> 00:18:58,157 will be directly correlated like you if you sort of buy my entire argument that 343 00:18:58,240 --> 00:19:01,997 look we've got a new commodity its tokens >> right 344 00:19:02,080 --> 00:19:06,717 >> and the job of every economy uh and every firm in the economy is to 345 00:19:06,800 --> 00:19:08,717 translate these tokens into economic 346 00:19:08,800 --> 00:19:11,277 growth then if you have a cheaper 347 00:19:11,360 --> 00:19:16,557 commodity it's better uh And so that's sort of what why there's tokens per 348 00:19:16,640 --> 00:19:20,317 dollar per watt. And by the way, there are many many elements to this, right? 349 00:19:20,400 --> 00:19:24,477 Which is uh it's not just um the production side. That's why I think even 350 00:19:24,560 --> 00:19:27,277 having the grid is important. Um uh 351 00:19:27,360 --> 00:19:29,277 construction costs, right? So if you 352 00:19:29,360 --> 00:19:32,237 like if you think about the total TCO 353 00:19:32,320 --> 00:19:36,557 uh everything it's like the how are you a cheap producer of energy? Can you 354 00:19:36,640 --> 00:19:39,037 build the data centers? Uh then what's 355 00:19:39,120 --> 00:19:41,997 the cost curve uh of the silicon and the 356 00:19:42,080 --> 00:19:44,797 systems? uh the and by the way look at 357 00:19:44,880 --> 00:19:47,757 the token pricing right token pricing 358 00:19:47,840 --> 00:19:51,597 basically drops by you know a half uh 359 00:19:51,680 --> 00:19:54,717 every three months uh I mean this is a 360 00:19:54,800 --> 00:19:57,357 so how so that that's why I think you 361 00:19:57,440 --> 00:20:01,197 can sort of really plot how you use the 362 00:20:01,280 --> 00:20:05,757 tokens to create surplus knowing that you have a commodity that's whose prices 363 00:20:05,840 --> 00:20:08,877 are just going to monotonically come down in a pretty fast curve 364 00:20:08,960 --> 00:20:11,997 >> we're sitting in Europe uh and there is 365 00:20:12,080 --> 00:20:14,237 a real fear 366 00:20:14,320 --> 00:20:16,557 because of the Europe does not have its 367 00:20:16,640 --> 00:20:19,437 own power. It has to import mostly of 368 00:20:19,520 --> 00:20:24,797 its power. Um do you have any messages for Europe 369 00:20:24,880 --> 00:20:27,597 related to this? >> Yeah, I mean I think so there are two 370 00:20:27,680 --> 00:20:29,357 sets of things, right? one is you know 371 00:20:29,440 --> 00:20:31,917 here we are in in Switzerland and I look 372 00:20:32,000 --> 00:20:34,877 at uh the the pharma or the financial 373 00:20:34,960 --> 00:20:38,317 sector you know OBC sw they're uh they 374 00:20:38,400 --> 00:20:42,077 they do do a big job in in in this country as in in Europe but they're also 375 00:20:42,160 --> 00:20:45,757 international brands and international operations. So one thing that uh 376 00:20:45,840 --> 00:20:49,917 whenever I think about Europe is the Europeans are producing products and 377 00:20:50,000 --> 00:20:51,917 services that actually are going 378 00:20:52,000 --> 00:20:54,397 everywhere in the world and so therefore 379 00:20:54,480 --> 00:20:57,037 uh European competitiveness is about the 380 00:20:57,120 --> 00:21:01,437 competitiveness of their output globally not just in Europe. I think sometimes 381 00:21:01,520 --> 00:21:03,037 when you come to Europe there's a lot of 382 00:21:03,120 --> 00:21:05,677 conversation about just Europe. Uh but 383 00:21:05,760 --> 00:21:09,597 European economy is thrives and has you 384 00:21:09,680 --> 00:21:13,277 know thrived in the last whatever 200 years 300 years. the miracle of the west 385 00:21:13,360 --> 00:21:17,117 is fundamentally because of what has happened in Europe uh is because they 386 00:21:17,200 --> 00:21:20,637 were able to produce things that the world needed and so I would say that's 387 00:21:20,720 --> 00:21:22,797 number one and in order to do that you 388 00:21:22,880 --> 00:21:24,957 again I go back to the human capital 389 00:21:25,040 --> 00:21:27,757 here is just fantastic and world class 390 00:21:27,840 --> 00:21:30,717 uh you have to absolutely invest in uh 391 00:21:30,800 --> 00:21:35,437 producing uh you know having the energy and the tokens here which again you're 392 00:21:35,520 --> 00:21:39,277 attracting like as I said we're investing and others are investing uh 393 00:21:39,360 --> 00:21:43,357 the the data centers here so the question is what's that next generation 394 00:21:43,440 --> 00:21:47,357 of output that comes from here. Right. I always think about the German middle 395 00:21:47,440 --> 00:21:51,277 star whenever I go to a jeweler or a dentist in the United States. I'm 396 00:21:51,360 --> 00:21:53,677 surrounded by German middle. Right. 397 00:21:53,760 --> 00:21:56,717 Totally. >> Um it's just unbelievable engineering 398 00:21:56,800 --> 00:22:00,157 provice of that country. uh and now the 399 00:22:00,240 --> 00:22:01,917 question and by the way that's the point 400 00:22:02,000 --> 00:22:04,477 that they are producing industrial 401 00:22:04,560 --> 00:22:08,237 products which today are built in into 402 00:22:08,320 --> 00:22:11,117 it all the intelligence as well that 403 00:22:11,200 --> 00:22:13,517 data right so I know whenever we come to 404 00:22:13,600 --> 00:22:15,597 Europe everyone's like talking about 405 00:22:15,680 --> 00:22:18,317 sovereignty and data this data that 406 00:22:18,400 --> 00:22:21,117 guess what Europe actually should be 407 00:22:21,200 --> 00:22:25,037 much more concerned about access to 408 00:22:25,120 --> 00:22:27,357 their industrial companies their 409 00:22:27,440 --> 00:22:30,157 financial services companies of data 410 00:22:30,240 --> 00:22:35,517 from US and the rest of the world. Uh as opposed to just thinking that somehow by 411 00:22:35,600 --> 00:22:38,637 protecting Europe you're going to be competitive. You are only going to be 412 00:22:38,720 --> 00:22:43,917 competitive if the products coming out of Europe are globally competitive, 413 00:22:44,000 --> 00:22:47,677 right? >> Um and so that's I think what needs to 414 00:22:47,760 --> 00:22:49,757 change. Uh you know Europe has led in 415 00:22:49,840 --> 00:22:52,717 privacy that's fantastic has led in many 416 00:22:52,800 --> 00:22:57,197 aspects of even safety around AI and what have you. And that's a feature uh 417 00:22:57,280 --> 00:23:01,437 that's great. But you also have to complement it with by building locally 418 00:23:01,520 --> 00:23:03,837 and then also thinking globally what's 419 00:23:03,920 --> 00:23:06,397 the contribution this continent will 420 00:23:06,480 --> 00:23:08,717 make uh to the rest of the world which 421 00:23:08,800 --> 00:23:11,117 it has historically been a leader 422 00:23:11,200 --> 00:23:13,997 >> a leader. So do you think the whole idea 423 00:23:14,080 --> 00:23:17,757 around sovereignty of data is that being misunderstood? 424 00:23:17,840 --> 00:23:20,157 I I think that that when people talk 425 00:23:20,240 --> 00:23:25,357 about sovereignty first of all it's very important clearly 426 00:23:25,440 --> 00:23:28,237 and who wants to >> and in a week like this it's more 427 00:23:28,320 --> 00:23:29,357 important 428 00:23:29,440 --> 00:23:35,357 >> uh but that said uh it is you have to 429 00:23:35,440 --> 00:23:39,117 kind of think about how what is sovereignty mean like for example in the 430 00:23:39,200 --> 00:23:41,837 AI era the topic that's least talked 431 00:23:41,920 --> 00:23:44,237 about but I feel will be most talked 432 00:23:44,320 --> 00:23:47,677 about in in this uh this calendar will 433 00:23:47,760 --> 00:23:50,157 be the sovereignty of a firm. Just 434 00:23:50,240 --> 00:23:53,677 imagine if your firm you're not able to 435 00:23:53,760 --> 00:23:57,597 embed the tacit knowledge of the firm in 436 00:23:57,680 --> 00:24:01,277 a set of weights in a model that you 437 00:24:01,360 --> 00:24:03,997 control. By definition, you have no 438 00:24:04,080 --> 00:24:06,397 sovereignty. That means you're leaking 439 00:24:06,480 --> 00:24:11,197 enterprise value through some model company somewhere. In fact, that it's 440 00:24:11,280 --> 00:24:14,157 sort of fascinating that nobody's talking about that, right? It's like 441 00:24:14,240 --> 00:24:15,597 everybody's talking about everything 442 00:24:15,680 --> 00:24:18,717 else that is sort of you know outside of 443 00:24:18,800 --> 00:24:21,677 that whereas the most important thing is 444 00:24:21,760 --> 00:24:25,757 it really doesn't matter if you have in fact the data center where it runs is 445 00:24:25,840 --> 00:24:29,277 the least important thing quite honestly but like even there first of all the 446 00:24:29,360 --> 00:24:32,877 data centers all are all over just because speed of light is a real 447 00:24:32,960 --> 00:24:37,517 constraint uh and so therefore the data centers will be spread yes uh you will 448 00:24:37,600 --> 00:24:40,877 have digital you'll be able to encrypt everything you'll be able to have the 449 00:24:40,960 --> 00:24:43,197 keys with you all of these are much more 450 00:24:43,280 --> 00:24:45,677 techn technically solve problems but the 451 00:24:45,760 --> 00:24:48,877 one problem that will only be solved is 452 00:24:48,960 --> 00:24:51,597 by you having much more sovereignty over 453 00:24:51,680 --> 00:24:54,317 the you know tacid knowledge uh and 454 00:24:54,400 --> 00:24:56,157 control over the models and it's not a 455 00:24:56,240 --> 00:24:59,197 one-way enterprise value transfer um and 456 00:24:59,280 --> 00:25:01,757 so to me I think sovereignty requires 457 00:25:01,840 --> 00:25:05,037 real thought on what is it um you know 458 00:25:05,120 --> 00:25:08,237 control of destiny means that your your 459 00:25:08,320 --> 00:25:10,477 ability to produce something that is 460 00:25:10,560 --> 00:25:13,597 unique is preserved uh David Ricard was 461 00:25:13,680 --> 00:25:15,757 not wrong. There's comparative advantage 462 00:25:15,840 --> 00:25:18,237 in countries. Uh there is comparative 463 00:25:18,320 --> 00:25:21,357 advantage in firms that needs to be 464 00:25:21,440 --> 00:25:25,597 preserved even in the AI era. That's what'll give you real sovereignty. 465 00:25:25,680 --> 00:25:29,037 >> One last question. I know we're running out of time. 466 00:25:29,120 --> 00:25:33,117 Um in 5 years or 10 years, is there going to be one dominant model that 467 00:25:33,200 --> 00:25:37,677 we're all going to be using or are and how is Microsoft preparing for this? Are 468 00:25:37,760 --> 00:25:39,357 you going to be are we going to be using 469 00:25:39,440 --> 00:25:42,317 one model for for enterprise, one model 470 00:25:42,400 --> 00:25:44,957 for other other traits? 471 00:25:45,040 --> 00:25:47,197 >> You know, even in the last whatever 3 472 00:25:47,280 --> 00:25:49,357 years, four years that we've been at it, 473 00:25:49,440 --> 00:25:53,597 um the the reality at this point is it's 474 00:25:53,680 --> 00:25:57,117 a multimodel world, right? I mean the in 475 00:25:57,200 --> 00:26:01,437 fact if you think about it the in both 476 00:26:01,520 --> 00:26:05,357 there are going to be multiple models 477 00:26:05,440 --> 00:26:08,637 and the trick is really how do you take 478 00:26:08,720 --> 00:26:11,517 advantage of these multiple models and 479 00:26:11,600 --> 00:26:13,997 in fact build your own model by 480 00:26:14,080 --> 00:26:16,877 distilling these right uh so think of 481 00:26:16,960 --> 00:26:20,077 these models uh that you orchestrate to 482 00:26:20,160 --> 00:26:21,757 build your own model and more 483 00:26:21,840 --> 00:26:25,037 importantly you do what is described as 484 00:26:25,120 --> 00:26:27,837 orchestration or harness engineering. So 485 00:26:27,920 --> 00:26:31,917 the IP of any application or any firm is 486 00:26:32,000 --> 00:26:35,197 how do you use all these models with 487 00:26:35,280 --> 00:26:37,277 context engineering or your data? Yes. 488 00:26:37,360 --> 00:26:41,517 >> Right. So it's that three parts. So can I bring in all the models by the way uh 489 00:26:41,600 --> 00:26:44,077 which is close source, open source, 490 00:26:44,160 --> 00:26:47,837 build my own model, orchestrate them and 491 00:26:47,920 --> 00:26:51,437 feed it my data to change the trajectory 492 00:26:51,520 --> 00:26:54,157 of some outcome that I care about. 493 00:26:54,240 --> 00:26:56,637 That's it. That's the entire picture. So 494 00:26:56,720 --> 00:26:58,797 you can do it in like oh I produce a 495 00:26:58,880 --> 00:27:01,197 particular product or service. Uh first 496 00:27:01,280 --> 00:27:05,997 I got to do better better job in sales or better job in R&D or better job in 497 00:27:06,080 --> 00:27:09,917 finance or what have you. And you take that outcome and then you say can I use 498 00:27:10,000 --> 00:27:12,477 all the models orchestrate them and feed 499 00:27:12,560 --> 00:27:15,037 it my context and then in as a result of 500 00:27:15,120 --> 00:27:17,997 it the reasoning traces are really 501 00:27:18,080 --> 00:27:20,877 leading to some capability and models 502 00:27:20,960 --> 00:27:23,837 that I control as my IP. As long as 503 00:27:23,920 --> 00:27:28,157 firms can answer that question, they're going to be getting ahead. 504 00:27:28,240 --> 00:27:30,637 >> Ladies and gentlemen, let's uh thank 505 00:27:30,720 --> 00:27:37,400 Satya, my friend. Thank you [applause] for 506 00:27:38,160 --> 00:27:41,997 and hopefully this is the beginning of many great dialogue and conversations 507 00:27:42,080 --> 00:27:45,117 here at the World Economic Forum. Thank you everyone. 508 00:27:45,200 --> 00:27:48,360 >> Thank you.