Possible: Satya Nadella on making human and token capital compound

0:00 So what I think we have not yet conceptually gotten right and a shared understanding is what is this future of work gonna look like if you're a tech CEO. You have to be deep inside of what's the tech stack. AI is not a technology, it's the future of the firm. One of the dictums I have is don't use frontier models for non-frontier problems. I think in the AI age, that is going to be everything, right? I think I would be very surprised, Reed, if we were sitting here a year from now If the world is not completely turned on, what is my AI supply chain look like? I couldn't be more delighted to introduce A Special episode.

0:41 Of possible. Sachin Adela. The chairman and CEO of Microsoft. Satya and I have known each other a long time and Part of in this.

0:50 this kind of AI revolution for humanity. Uh I thought this would be a great I mean, We covered all kinds of important topics. Sate as always is elegant, but is

1:04 Cohesive is smart is comprehensive. And above all. Humanist. And what is our AI future. This will be an amazing episode. Actually, one of the things that's great, Satiya, about filming this here is it it reminds me of the earliest days when we were talking about Microsoft and LinkedIn. That's right. Because we did one of our very, very conversations here in the Grey Lick office. So it's like just awesome to be back. I wanna start with something that I don't know as many people realize and appreciate about you, which is with how many books of poetry you have in your house. Um, can you say a little bit about your attraction to poetry, favorite poets, what what the engagement is there? Yeah, I mean I I actually

1:42 Got into it. in different times of my life. Uh I remember you know, uh as a middle schooler we had this standard issue English poetry book, which I've been trying to reclaim and get all my life, but unfortunately is out of print. But it sort of had You're even getting, you know, introduced to Shelley or Wordsworth and uh uh it had even sort of Indian authors like Surujini Nainu writing in English and it it is I don't know, I felt maybe it was my attention span or what have you. I was naturally drawn to poetry as a thing to enjoy and love and and I've always compared it even to code, right, which is its sort of compression in its best form. Um and so whenever I'm bored, I get to you know, go read. I'm not great actually at understanding deeply. I've never studied it. I'm not like so so that's why my reputation of knowing about poetry is far exceeds how my knowledge of poetry. Uh but I still

2:41 You know, continue to um use poetry as perhaps the best expression. of um uh the human experience, right? I mean if you l if you sort of broadly think about literature um as sort of what captures more than even history. Um uh the human experience. I think poetry is the compressed form of it.

3:05 I completely agree. Is there a particular poet That you go back to the third. Yeah, so I the thing that I really I s I would say the poetry that probably speaks to me most deeply is the Urdu poetry. That is sort of because I grew up in Hyderabad in India and Urdu is sort of the in the air. Um and some of the Urdu poets are both modern and sort of um you know, people in the seventeenth, eighteenth century were just extraordinary. Uh in in particular, you know, there's there's this

3:33 Uh but uh whose name goes by Galib uh as his name. Um And he's just uh extraordinary or even a modern poet like Faz. Um I was also very having grown up in here in uh in Hyderabad, I was very influenced by Rumi. Um in fact, um you know, uh my the high school I went to was fascinating. In fact we had um in the number of languages which were all taught was obviously it was English. Um there was Hindi, which was the national language, and then um we had Sanskrit.

4:02 Like basically, you know, uh like Latin here, I guess. And then uh we had the local language, Telugu, which is my mother tongue. Um but we also had Urdu and uh Persian. And so all of them, like in fact when we would break for what was called second language, I I my second language was Sanskrit. Um but You know, the I could see I had classmates who would go to Persian, Urdu, Telugu, Hindi and it was fascinating. Well, among the uh experiences I'm experiencing a little bit of language envy'cause I a joke that I like is, you know, what do you call a person who speaks three languages trilingual, two languages bilingual, one language American. And unfortunately I I resemble this joke.

4:43 Um, all right. So let's uh we're just coming out of build, which was amazing. Um let's kind of g actually start with kind of going back in history. So you know, Microsoft's first product was a basic interpreter. Um and Fifty years later, here it builds.

4:59 frame the company's future around what others can build with AI. So what is the new basic interpreter? No, and And therefore what should we build? Is sort of the two questions that we always ask ourselves. And in the AI era. To me the answer is

5:25 Uh the basic interpreter is the hill climbing machine. Right, because you think you na bring all of those AI, what is it? It is basically taking an objective, an outcome, an eval that you have, and learning how to achieve that by learning uh using data. using some reinforcement reward. And so the The entire conference was about not hey here is a new frontier model. It was about helping every developer.

5:56 every company, whether it's a st AI native startup or an enterprise, building their own hill climbing machine so that they can operate at the frontier. Right. So I think that that's it. The idea, in fact You know, be getting very clear about the evals and the objectives that you care deeply about, knowing how to evaluate them, right? That it's in some sense is the most and keeping that's the new IP. Yes. Because everything else is pretty mechanical. Uh, but knowing what is the set of data that you want to train a model on and how you reward it is probably where the the next level of IP gets created. Well, and one of the things l let's dig into a couple different areas here, because you and I've had a number of conversations, you know, with Microsoft Strategy, and one of them is

6:45 kinda this question about how enterprises keep the advantage and integrity of their own data. And Microsoft is the most natural company in the entire world to do this. So what say a little bit about how enterprises should be thinking about like We need our own frontier intel intelligence, but we also need to maintain control of our data. Yeah. See that I think is the the question which is This economy is going to be shaped going forward.

7:10 By both human capital, And let's call it this token capital, right? That is true for Microsoft, that is true for a new startup, that's gonna be true for any bank that's been in existence for a hundred years, right? No, it doesn't matter. All of us will now need to sort of in fact the interplay between human capital and token capital and compounding the returns of it is what you need to do. So if you sort of frame it that way. then one of the most important thing is not just even thinking of data in its aggregate sense, right? See what is the tacit knowledge of an enterprise or a firm

7:47 It's the unique ways that you are able to operate, pass judgment, have taste. All that's the tacit knowledge, mostly captured today in the tacit knowledge that is there with the human capital. And some artifacts that are digital. So now when it comes to AI The

8:08 The model in some sense is able to extract, if anything, that tacit knowledge of through human trajectories and encoded in a set of weights in a model. So what I claim is that every enterprise now needs to be more mindful about that interplay of humans and their digital estate working together, those trajectories, training essentially the models that they keep as IP versus leak it. Because if you leak it, it's a one way door. You're done in some sense, right? Which is what is unique, what you may have spent a hundred years, right? In fact, we don't even know how to articulate it, right? Nobody sort of has a line item in their balance sheet called tacit knowledge, but we take it for granted that because we have human capital, we have it. Now I believe that can leak.

8:59 And in fact, it is leaking, right? If you look at even the number how the model companies learn, they're essentially setting up these gyms with rewards, which are employing employees who worked at your company previously. I mean that sort of should tell you everything what what should not be happening, which is so that's one of the fundamental reasons why we want this effectively the regime to f change or the paradigm to change, where you welcome the models to come in. They should hill climb inside a machine that you control. Your data is your context you feed the model, you collect in fact these traces or trajectories of how work gets done between humans and agents inside the enterprise. But you have a continuous loop of that.

9:43 And you're not letting that leak. That I think is the fundamental operation. Yep, and actually the related parallel to the tacit knowledge is and this is one of the conversations you and I had Actually at the the Microsoft board, which was what uh is the future role of AI employees.

10:00 Right, because part of the question is to say, hey, we're gonna provision not just You know, kind of uh tools to amplify human work, great, for you know, kind of AI companies, but we're also gonna provision at least specialist employees. But the challenge with that is that one of the things that really matters to enterprises is Your employees

10:20 Embody a lot of You know. Tacit knowledge, how to, what to do. Do you want that in other companies and provision or other places? What's the your and Microsoft view of the future of work? When it comes down to

10:33 How to think about AI as also Maybe even specialist employees. Yeah. I mean I think that that that's right. So the way to think about this, you know, there are two ways I come at this, right? Which is let's let's take one analogy and I'll come back to it, right? If somebody in the early eighties had come to us and said You know what, they're gonna be four billion typis. uh who are gonna wake up every morning and start typing. And we were set. What for? It makes no sense, right? We have a type is pool, we have a slide pool, and we're you know, fine uh, you know

11:03 with that. But except we invented this complete new thing called Knowledge Work, where everybody was typing and creating artifacts and so on. So what I think we have not yet conceptually gotten right under our good understanding, under shared understanding, is what is this future of work gonna look like when you have, let's call it, you know, in let's take Microsoft, we have two hundred thousand employees and we have let's say two million uh agents or twenty million agents. All in a loop. What is happening?

11:37 Uh what is the tacit knowledge that gets created? Um, what is uh you know, the artifacts uh that are going between agents, between agents in humans and so on. All that's now gonna be played out in the next whatever, even multiple years. You can see early forms of this in coding. Right. It's a great place to observe, in fact, the the this even this sort of social change, right? I mean think about we started in a good old IDE. And said he's in s Uh and it's doing code completion. That itself was useful, easy to understand. We've always had spelling correction and IntelliSen was there for in BS code, you know, from fifteen years ago, and and it just got better.

12:23 Then we said, Oh, you know, instead of going out of band and going to a browser and you know Stack Overflow and searching, you can now bring all the coding knowledge to a chat session. Well that was also also easy to understand and you still were in the IDE, you had sort of the chat. Then we said, okay, um, you now have reasoning models and some some you know prime you know, preliminary agent loops and so on. And so you can assign tasks. So we had agent mode, right? So you not only had chat, but you can give it small tasks and you could see it complete, um, and then you could accept the what it did and then you could insert it and what have you. Then came the big breakthrough of total autonomy and agentic loop working for long periods of time where you could literally fire forget, right? Where you could assign a high level intent, it'll go off and do the full PR and you would accept the PR. So that

13:17 Transition Right, is what I think is going to happen across all work. I and now we're seeing it with even in co pilot. We now have chat and we have co work, and now in fact at Bill we l announce something called scout and autopilot. So what is happening in coding will happen even in knowledge work. Interestingly enough, one of the things we launched even at build in GitHub was a new feature called Canvas because what has happened is

13:46 As we've all gotten so good at using these coding agents, in fact, you know, the biggest challenge we now have is I have a hundred CLI sessions open where I'm trying to operate these hundred C you know agents. And Now the cognitive load on me managing this is so high, right? I mean, first of all, I don't I mean they think about it, right? It's a linear chat session in a command line and I have a hundred of them. So guess what? We now are back to

14:15 An ID. Right. So I have a new ID. We give it a new fancy name. It's called an ADE. It's an agentic development environment. That's what the new GitHub app is. The GitHub app looks like an inbox, except it's an inbox of agents that are working across all the repo. in allowing me to do the micro steering of the macro delegation I gave them. Uh, but it's a complete UI for the agents to deal with me and for me to deal with agents. And so I feel so we introduced this new feature called Canvas in GitHub where it can like, for example, You know, sometimes it's easy to have a Kanban board visualization as a way to run down your PRs. Very useful, both for agents and me to interact versus some chat session. So I think that that type of innovation is how work will change. In fact, one of the other fascinating things for me is a line of even AI research would be the models will also get much more tuned.

15:14 The learning how to stay the course. Um And understand human preferences. in steerability, right? Because that's what I want. And when in fact I want models that not only do instruction following, but are also really steerable. Uh and that when you have that, that's when you have confidence in it. So I think the work of the future is about tacit knowledge that gets created by this interplay just like knowledge work got created

15:44 because of digital artifacts And human capital. The new one would be this AI capital and the human capital working together, creating in some sense the digital artifacts. And what do you think are the things that people miss about how important it is to build out Additional Kind of structure.

16:05 for enabling enterprises. So one of them is obviously the enable in humans canvas. You know, eighties, et cetera. But what are the like For example, notions of like what is uh security. Oh, it's a great point. It's a great point. So in fact, the to your point, one is the experience layer. Clearly that's important. Another one which we referenced earlier was hey, we need this hill climbing machine as a concept that needs to be instantiated. But the third is the manageability of it and the security of it, starting with observability, right?

16:37 Things we did even, and we talked about it even yesterday is something called agent three six five. I need to know, I need to have an inventory. I said, Oh, there may be 20 million agents at Microsoft. I first need to know what are these agents, what are they doing, what are their reasoning traces? They need to be fully inspectable, fully auditable. And by the way, when the agents also have this other attribute, they execute they are running. they can generate code and execute. So you need the environment in which they are executing code, with maybe even file system access, network access, to be things that is governed by policy. So therefore you now need to give them identities, you need to give them sandboxes, then you need to set policies to govern them. And so we built this entire thing called agent three six five, which really has, you know, we have extended entra so that you have an identity, we extended defender so that you have security, we extended

17:30 purview so that you can even label the data that it's getting created automatically so that you can have data protection. So I think security, containment, manageability, observability is the way we will have confidence around these agents. The one other thing I'd say uh read also was salient in the developer conference was How important It is. When you're building these long running agents. Right, like it if you think about right, we have always had um In programming languages.

18:02 You know. Programming models for understanding the ver you know, uh the verifiability of a program, right? And it's execute at at runtime. So one of the attributes of these long running agents that we added uh to foundry was something called asserts. So this allows us to assert what are the boundaries, right? So instead of talking about guardrails as a thing that is sort of just a classifier of some form. You really need to now have the ability during execution.

18:34 to really have that execution path not go off rails. And so there's a lot of engineering sophistication now that's emerging. uh as we build out the platform, the runtime, the security layer, the management layer, the observability layer. So let's go to a little bit of the role of CO. Um, and I think

18:55 Uh Fortune recently described you as acting like a startup CEO inside of Microsoft's AI teams. Um But The more general question'cause I think a lot of CEOs seek You know kind of. technology strategy advice about what's going on in the world from you.

19:11 What do you think? The COs should be doing around AI What Um

19:18 Yeah, kinda when they're Like AI brings the kind of a refounding moment to lots of companies because of the nature. And so What's your advice to them? for how they should engage. Great question, because I've been thinking about this, right? Because in some sense, you know, it clearly for if you said of you're a tech CEO, You have to be deep inside of what's the tech stack, and there's no way you can be a tech CEO and not essentially have a fundamental

19:44 uh world view on where the future is g w the going and then to be long before it's conventional wisdom, you have to pass judgment on uh you know where the company's going, right? So that's sort of the our industry's sort of pretty binary transition. So I think there's no hope if you don't have a uh uh the CEO leading uh from the front and taking the shot on goal, uh knowing that these are fairly uh harsh transitions. But The interesting thing that now I've up to now if you're not a tech CEO, you needed to be a great CEO, which means you need to be great at banking or healthcare or whatever it is. And you could always have great partners and

20:26 Technology advisors and what have you. But now I'm changing my prior on that, right? Because I think the because I'm noticing even what's happening and I don't think the the rest of the the the industry and the CEO community has broadly woken up um to this and I'm like perplexed at it because there's still you know, pretty happy doing a press release with a a tech company and saying, Yeah, I've got my AI strategy and, you know, pointing to eight agents they built and some outcome.

20:54 But this is no longer AI is not like a sort of a technology. It's the future of the firm. Right, it'll be like saying, Oh, I don't know what the I about the human capital in my firm, right? So I think that this is where my thing would be that you have to now get a deep understanding.

21:13 Or what's your token capital? Can you answer that question, right? Can you concretely say oh last night All based on all the work that happened across all of our operations we were able to translate that into a set of knowledge that is somehow now part of my token capital. It can be some

21:36 Context. It can be some skill. It can be some weights in a model. It doesn't need to be any one thing, but you need to be able to specify it, you know, it n you need to be able to identify it clearly as something that you own, you control, you created, and you have put in place a system. to have that compound. So I think that that is going to be probably the toughest change. So this change is like unlike how this is like going to a mobile phone era or a PC era or a cloud era where all I needed to do was to have an IT department that knew how to deal with a bunch of vendors and did some smart things to reduce cost or improve my efficiency. It should start there. I'm not saying that that's not the place.

22:22 But this is about what What happens structurally in your industry? When AI is sort of basically knows everything that it needs to know about being in your industry. And if you start there, then I think you will start understanding that this is not just attack. uh it is really about a fundamental change uh to the firm.

22:45 And one of the things that I think thinking about the nature of the firm Uh is that you've Done a great job in leading Microsoft. One of the many different genius moments and skills is uh going through acquisitions and partnerships, right? So it's you know, whether it's LinkedIn, obviously something close to our hearts, um, you know, GitHub, OpenAI, et cetera.

23:05 Uh and part of what I think Microsoft leads the entire world on is how do you build trust in these other ecosystems? And the world of AI, that's going to be extremely important, especially as the firm changes. So what are some of that the kind of the Um the kind of lessons you've learned, the things that you are advocating for in order to build and maintain that trust. Yeah, I so it's so key because in some sense

23:31 I've always sort of thought about what's long term stable. Right, um, even from a Microsoft perspective. What is long term stable is for us to be a tools and a platform company where we fundamentally are defined by the amount of value that gets created on top of the platform, which should far exceed anything that is captured in the platform, right? It ha that's the only way to have stability. If you do that, then you have trust. Right, because the then the customer, the partner knows that it's not a zero sum.

24:05 Well, especially it's not a game theoretic Z you know, zero sum with these games where, oh, I'm gonna subsidize this until two years or three years only to then eat your lunch type of games that the tech people are really good at. Um and so I've always felt like hey, look, That is all not the way. The way to think about it is to be very principled that you're a platform company. that you will really live and die by your ability to create success on top of the platform. And when they're successful, you're gonna be successful. And that is the equation that builds trust and long term stability for both sides, right? Um

24:48 I think in the AI age that is going to be everything, right? I think I would be very surprised, Reed, if he was sitting here a year from now. If the world is not completely turned on what is my AI supply chain look like Where Із хеппі мі а за фарм. compound the returns of AI that I can uniquely point to as my value in a world where we know that these learning systems by definition don't have boundaries. They have to have boundaries because of mostly structures of markets and society and other mechanisms. Yep.

25:27 So we've talked a lot about chatbots and code, um, which have just seen amazing explosive progress. Um What are some of the next frontiers for LMs over the next few years? Well, I mean Talking about that, in fact, you know, one of the things that I know you have gotten very, very excited about, which I'm quite frankly, you know, uh excited for you, but also it c has caused us to you to examine where you spend your time, and I'll let you speak to it. But it's sort of unbelievable uh to see what's happening in science. Um and and in fact the company that I you know you started with uh Sid and Manus You know, it's just a great example, um, I'd say of

26:11 What has happened in let's call it coding in knowledge work. If it start happening in science in f I would even claim that I wish In fact we you did it in the reverse order. Uh right, because the per m social permission for AI would be so much higher if we had started with some nice discoveries in science that were having great societal benefits.

26:37 Oh, then people would have really thought of this as a thing that is really going to be more helpful. So I'm really excited. uh for you read what what you're doing. Obviously you've spent a lot of time, but maybe you want to talk about that. Well yeah, so I mean it was one of the things that uh I realized over the last month was that Um we're seeing such progress with Manus in Actually, in fact, we've got an internal description of move thirty seven for chemistry,'cause we're seeing chemistry that that

27:04 might actually in fact take shots at really interesting cancers and other things. And you know, it's very early, right? And so, you know, these things take a while with all the IDs, but the the fact that we are already beginning to see like we've got some of the best computational chemists in the world. And they looked at them and said, That's very interesting. We've never seen it before, and that might work. Right. And so that kind of thing. And so you know, Sid and Ujwal and I were talking about this and I said, look, I think I need to get back to founder mode. uh in terms of how to do this and so I need to be able to kind of focus on this and then

27:36 you know, uh part of the you know conversation you and I have had this week is to say, okay Um, it's been 10 years on the Microsoft board. It's been a huge honor and pleasure with, you know, and not just LinkedIn, but obviously OpenAI, GitHub, a whole bunch of things. But you know, at the end of the year I should really be transitioning right now to being founder mode. So like, you know, it's like and you know. Will always

28:02 be working together. So it's like but but you know, it's time to kind of dig back into the company. No, first of all it's a been such a privilege. uh to have you on the Microsoft board, work with you obviously through all the partnerships and LinkedIn and um we will definitely be missed uh on the Microsoft board. But I know we'll be s very connected, but I'm also excited for you. Uh and you're when you say you're going back into founder mode, uh, you know, that means I'm even more curious about what you're going to be building. Uh because it's a as you I think you rightfully captured, this is the moment where I think the impact of these technologies more broadly felt in the societies than need of the R. Yeah, no, exactly. Let's come back to You know, kind of questions around

28:45 The patterns of thinking That happened with AI. Because One of the things that I think Like I kind of roughly think about these things as

28:55 You've got an alien intelligence, right? A different version of A. That has been built to very much heavily mimic human intelligence, which creates a whole bunch of utility for us. But its patterns of reasoning are not the same as ours. Right.

29:11 And People frequently encounter that and they go, Oh, that's scary. And you're like, Well, no, actually that's That's look, you have to pay attention to make sure there's alignment, but it's also wonderful because it enables new things. And so that's part of the thing, like the kinds of chemistry we're doing, like the humans hadn't discovered this chemistry in Manas, right? What are the other kind of

29:30 thinking was but this pattern of reasoning. Right. Amplify human capability. It's a great one. Like you know, I'm not Thought that deeply about sort of

29:41 how it improves the I mean if you sort of sort of say there's You know induction and deduction that we do. Being in this cognitive loop with an AI. Um

29:55 That is fascinating, right? Because my exploration space is changing. Um right. The You know, like even in coding One of the most fascinating um Things that

30:10 one of my colleagues introduced me to is he he wrote a new skill which I have in GitHub Copilot. It's called cognitive coverage. Right? It's fascinating. What he's done is You know, whenever an agent does some work for me. He says Just like how we are test coverage, we now have this new concept called cognitive coverage, where

30:31 We we as humans are going to learn from what it did. And so it's just creates a quiz. No, because I literally think of learning Uh from it it's sort of it it is m matching my ability uh to essentially form a deductible understanding in some sense.

30:54 Um of what an agent did. Right. So to your point, it is um um it's a basically it's mimicking, it's sort of an imitation game on one side, but that imitation game does create. So then my ability to then deductively understand it. Uh I think his probably one of the more important human skills we have to develop. So this cognitive coverage is I'm like fascinated by it, right? Which is, oh, I think we're going to have something like that, which is the agents are working, they have to be aligned on one side, but the other side of it is What is new will be us knowing oh, we've cognitively covered what AI did.

31:34 Yes. Well, and I think that point intersected with your earlier one about you know, kind of token capital and AI capital. Is that part of the skill set for the modern you know, kind of human knowledge worker. is to say, okay, how do I

31:48 Strategize on the use of AI. Canvas orchestration. Yeah. but also within kind of capital allocation bounds. Right, because part of what we've seen is people can go crazy on spending lots of tokens in ineffective ways. It's like You know, buying

32:04 You know, go back to bad Pentagon days, toilet seats for a million dollars. And so putting your thinking together. With the cognition together with Token management. And what do you think is part of the question around This skill of blending

32:20 the cognitive coverage. With also token intelligence in terms of how do you amplify the outcome. In fact, I've I've been thinking about like one of the things that um I think one has to study deeply is what are all the things that become more valuable? In the age of let's call it token abundance. One is what you referenced, which is how to use tokens becomes very valuable. Whoever figures out

32:45 that oh I can use tokens more efficiently for an outcome that matters in the world is going to get ahead, right? By definition. So then how does one build the intuition for it, right? Which is, oh, what like this is where What is that outcome? How do I measure it? What's the rubric? In fact, this is where I think the evals, the you know, if it's it's fascinating. How much time needs to be spent, especially for an RL regime, I think it's been the clearest, where if you really want you want to set up the rubric um and the eval dimensions or the rubric's scoring dimensions such that they're really capturing the high taste. that you only can define. Because if you did that, then you could be token efficient, right? In fact, the other side of that token efficiency is

33:35 Um, in some of the examples we even showed at uh build was Let's say you have uh um I don't know, um some you're a retailer or uh you're a packaged goods company and um one of the things you do is handle sort of transactions around uh trade promotions. Right now you get all these claims from all the retailers and you have sort of processed them and the humans are doing it. You can easily automate that using an agentic workflow. And you could say, Oh, I use a frontier model for it.

34:07 But then One of the dictums I have is don't use frontier models for nonfrontier problems, right? So this is not a frontier problem. You're not trying to discover some new material science. This is a repeatable deterministic workflow. Uh But that can benefit from all the mistakes humans can make and claims and so on. So therefore you do need uh you know intelligence in it. But you can take, you know, a model like an MAI5B and use the traces to hill climb in your RLE to perform even outperform even uh a frontier prompt it. Right. So that to me is token efficiency. So that

34:48 type of human understanding of both the limits of the system, the characteristics of the system, I think become high premium at this stage. Yep, I agree. One of the other things that um I think is important for people to grok, as you know, because we've been in a lot of these conversations. There's a lot of uh concern in other countries about, you know, kind of sovereign AI.

35:13 And I think that it may be useful here, given we've just kind of gone into depth about companies and the sovereignty, like the companies, their information, their employees. What are the parallels between what we're doing for companies and how countries should think about kind of also engaging in trust in the AI future. I have really pivoted to companies is because companies exist all over the world. Right. That's the good news here, which is because in some sense, even countries thinking abstractly about sovereignty, they can even make big mistakes where they

35:51 ultimately we could erode their comparative advantage that is naturally there today, embodied in the commercial activity happening in the country, through its company formation and thriving, uh So therefore preserving that Is the best form of sovereignty. Sometimes I think people think, oh, if only I had a firewall or all the data was resident or what have you. You know, I'm not saying those are not considerations, uh, but this is not about even Any of that, right? Which is

36:25 This is about making sure that you have an economy. Uh That means you need to have companies. That means that c those companies have to thrive in a token economy. Uh, that means they need to be able to build that IP. And so therefore, in fact, having partnerships even with companies outside that give you the ability, I think are more important. Then sort of suddenly falling behind some frontier, right? And so I think that therefore, I think that this is one of those places where, again, even the policymakers. Have to think about infrastructure, right? After all, you know, tokens they're electrons on one end and tokens on the other end. So you want to be the cheapest, best environmentally good producers.

37:09 Of those electrons to token conversion machines called data centers, right? So that one I think is going to be very important for every country to prioritize. Uh of course the country should even prioritize whether there's their own semiconductor production and what have you, right? That's all very valid things to do. But beyond that, I think the most important thing is Ricardo was always right on, which is countries have by definition their own comparative advantage. And now they need to amplify that using AI. That means best thing is that whether it's the small business or whether it's the large multinational or even the public sector efficiency in the country is getting better. uh and is operating at the frontier. The worst thing for any country to in the name of sovereignty If they're off frontier.

37:58 Then That makes no sense because you're falling behind. you have to but at the same time being dependent on one frontier model also makes no sense because then you're not sovereign. So what's the The way to solve it is to be able to say, No, we will use models

38:14 To hill climb on our own one firm at a time and at an economy and aggregate. That's I think the equation. The the gesture at Silicon actually um I think is a good also um bring up both for companies we're building, Maya and Cobalt.

38:31 Um, but also, of course, partnering well with NVIDIA and AMD. So Uh first, what's the strategic job of Microsoft's own silicon? What might Companies or countries also learn from that. Yeah, so it's interesting. If you think about it, right, we want

38:47 It's a great way to observe it, even because I w I mean, if you look at what NVIDIA has done or what AMD has done, or what Intel has done, they've built general purpose technology. Which you know, like in fact when I look at what we're doing with GPUs today, we're of course using GPUs to do But we're also accelerating other workloads. In fact, one of the exciting announcements that build was using uh GPUs to accelerate Nvidia GPUs to accelerate our fabric data warehouse, right? In fact one of the things that's happening with the agent tech workloads is we need no more performance on everything. And so That's a great that's because it's the general purpose nature, right? GPUs have co you know, Nvidia has CUDA, CUDA can be used as a programming model on top of those to accelerate a variety of workloads. In fact, we're using the older chips of Nvidia to accelerate, and this also works out economically for us, right? Which is it's smart for us to take a fleet.

39:42 and keep using that fleet over a lifetime where we are not only using it for some cutting edge AI, but we're also using it to in fact make an old workload even better performing. Like that's great for NVIDIA, great for us. But that also speaks to what's happened in terms of the new workloads, right? The new workloads of AI Are these data parallels, synchronous workloads, training, inference, as well as these new agent runtime workloads, which have very different call patterns, very different and they're highly constant. They didn't exist three years ago, right? At any scale, and now they exist at scale. So it behooves us to start thinking. Whether it's not even before we even get to the semiconductors, I'm building my data center center. My civil engineering is influenced, my cooling system, my mechanical systems. In fact, the DC to AC that they go we're trying to make sure that the electrons are coming in in kilowatts, uh right, hundreds of kilowatts, straight to the silicon without any losses, right? So we're trying to minimize even the power distribution in a data center. So we can optimize to the nth degree for these workloads because they're s at such scale. And that's what we're doing with Maya, right? Maya, for example, is being co-designed with our MAI models and the OpenAI models.

40:56 To get the best performance out of them. We're designing Cobalt, which is our ARM based uh core for compute. And we're designing it for, for example, using all the agentic traces of GitHub, right? Coding, you know, the call pattern of a coding agent is pretty different than human apps or even asynchronous human apps. And so therefore, we're optimizing and getting massive latency gains, performance gains, and what have you. And so. We're gonna be a systems company that continuously to optimizes for the new at scale workloads that we have while using general purpose technology from our partners uh to maximize the utility of those. And that flexibility, by the way, uh I think is what really is good. And that that's where I think your question was so good, which is countries should think of that, right? Which is if you really think oh there's one thing that answers. If I said oh everything is Maya and everything is cobalt, that's probably not the right thing for Microsoft. Uh but at the same time, if we said we're open to innovation from the outside, we will innovate inside, we will in fact benchmark everything, we'll be principle about it ultimately for better economics. Yes.'Cause because creating the

42:04 Efficient capital token factories that create human prosperity. is the goal. Exactly. And enabling many companies to do it. So Uh different thread. One of the things that I know from various conversations with you that you're very thoughtful on

42:18 is the topic of children. in the modern age because obviously we're creating products for tutors, co workers, et cetera, et cetera. And one of the things we're all exploring together is What should we be doing as an industry to Navigate

42:35 Kind of being of helping children elevate the right way and also keeping them safe. What are some of the principles that You know, Microsoft's thinking about you're thinking about as ways to kind of Be good. As it regards, you know.

42:50 The next generation of humanity through Children. There is obviously important things that we have to do around child safety, right? So when Any digital technology comes out, I think we have to now think as first class, right? There are AI safety issues. round cyber or bioweapons alignment, but it's also child safety. So I think that that one thing that we want to make sure is some of the

43:18 challenges uh of uh current sort of set of let's call it chatbots, right uh and they're conversations with children in particular is something that we need to be very mindful of and make sure that we're not uh having children uh not have that agency uh that they need to have in order to interact with this on their terms versus uh be Persuaded, for example, right? So those are very important things. But the other

43:48 thing that you're pulling on, which I think is super important, is what does it mean to even be a child in a world like this where there is all this abundance of tokens? And that I think is the the question, right? How does should what should how should learning happen? Uh how should we inspire uh children, what's their sort of ability to go have a new pedagogical system even that they can enter. Uh because I think even like if you take the traditional ways, right? The anxiety. That let's say Uh I I had growing up on learning.

44:24 Interestingly enough That's a Sort of. Um an artifact. Of the scarcity

44:32 uh of opportunity, scarcity of good learning, uh and a variety of things which may or may not be true going forward. So one of the first things I think is creating an a learning environment Where Students and children in particular from the earliest of ages don't develop these phobias for math or science or what have you. In fact, because everyone's m by definition a lot more curious. It's just that contact with the world is what, you know, erodes that curiosity and confidence that children have innately. How do we develop that even further by giving them the ability to explore, uh knowing that there's no anxiety, because after all, the expertise is always going to be there in abundance. It's really your cognitive coverage of that expertise that's more at a premium.

45:27 Right. as a five year old, I think I may have approached life very differently. Uh and so how do we as a society create the necessary conditions for that? I think it'll be probably very important. And I think it's one of the things, you know, I know from conversations with you and Densley is like this is one of our responsibilities as a tech industry. Right. This is like it's a no no we can't abrogate it. This is like given the ubiquity of the AI technology, we have to be responsible for the next

45:59 Human generation. Exactly. What both sort of the unintended consequences is something we think about from day one and really build in safety guardrails and what have you. Then the great advantages of new technology Right, have to be democratized. Uh, and then I think there needs to be structural change, right? I don't think you can say education remains exactly the same and we value the same credentials. I don't know. I don't think so. Uh something's got to change. So One of the things we haven't had a chance to talk about yet, which is very natural in this context, is Pope Leo's encyclical. Which I thought was actually, in fact, a magnificent part of leadership on the behaviour on the behalf of the church. I mean Pope Francis had actually gotten me engaged and helping them talk about AI Ten, eleven years ago. Right. So like the church has been

46:50 Uh amazingly Front footed on this. And actually, part of the thing that didn't surprise me at all in the encyclical was the humanism of it. Right,'cause people thought, Oh, it's about religion, it's about how you how you pray and it's like actually in fact the the the at least the parts of the church I've interfaced with have been humanists, right? And um

47:10 Do you have any reflections on the Pope's encyclical? See. the Pope weigh in. And from what I understand there's historical precedent on this, right? I believe the Pope at the time of the Industrial Revolution also had weighed in on the condition of labor and what should it do and what have you. And so to have the Pope Sort of. Come out.

47:31 In defense of what I think all of us could deep be deeply care about, which is human dignity and human agency. in the age of AI, uh I think is so important and I'm glad uh that he has advocated what he thinks is important. Um The other side of this to me is

47:55 What is the society like if I look at what is at least describing what what when I think about some of the greatest ways technological advances were harnessed. to create great prosperity. The story of the West It's pretty unbelievable, right? There's a beautiful book, in fact, that Joel Mokyar and a couple of other authors have written called Two It's called I think Two paths to prosperity, which describes the thousand year history of China and the West, essentially.

48:27 And You know, I'm paraphrasing uh here, but fundamentally some of the constructs, cultural, societal constructs in the West on how to use even the scientific revolution, the industrial revolution, this and they that necessated a real change in how the society was organized, so that it could fundamentally take advantage of this new uh is sort of really massive. Uh right. That in fact defined the modern world. And so one of the things I feel we now need is a similar coming together from sort of both the moral philosophy. I think the Pope basically sort of said this needs to be the moral philosophy that guides uh us going forward. You combine that with even what is the market.

49:18 What is the what is democracy? Uh, and then what is the scientific slash technological revolution? So if we can somehow get into a virtuous cycle where the morality And the scientific sort of breakthroughs the political system And the markets.

49:37 Ал реінфорсing і ча. then we will have abundance and we will have many stakeholders all benefiting. And if we don't, we are going to lose social permission, right? So I just don't think I think this is what the narrow understanding of the success of the West as just a technological breakthrough. uh I think is sort of not the case, right? It's a m unbelievable coming together uh of a multiplitude of sort of forces in a virtuous cycle. Um it also had really bad parts to it. Um right. Uh we know that. And so you have to avoid that, right, which is and so that I think was also some things that the Pope himself wrote in the encyclical, which I thought was great, which is even to think about sort of what are the bad parts. How do we not repeat it. What is the way to be

50:26 you know, advocating for this positive cycle. Uh I think it's beautifully captured. And I thought it was great that it was kind of A focus on how do you keep humans at the center, how do you elevate human dignity. How do you Address needs not just of the wealthy countries. But the entire world is I think, you know, a great, you know, beacon in terms of how we try to think about it. You know, I think deeply about that, right? For example, I've always always dr you know, you know, been like someone who cared deeply about the global south, in some sense finally having their moment where there can be real catch up growth.

51:00 Um and so I think that there's a real danger now in the age of AI for even that convergence growth to slow and in fact go the other way. And so what are the again the global structures Because by the way, if someone w sitting in the United States in you know in Palo Alto may think that somehow it doesn't impact them, but there's no such thing, right? You know, we share this planet and our destinies are a lot more tied than we think we are, uh just because of, you know, being far away from what's happening. Well, um last question before we get to rapid fire. Um Is you and I both know. Um

51:37 You know, in the US and in Europe, there's a lot of AI backlash. Um now part of how as you know I've I've been trying to address it is like with books like Superag trying to say no No, this is an opportunity to gain agency. The transition will be difficult. But embracing the agency and the transformation

51:56 Ultimately you have to. But if you do it with forethought and and kind of like leaning into it. It can be greatly helpful.

52:05 Uh what do you think? We should be trying to help people in the US and the West understand about why it is that actually embracing AI is more important. And it doesn't mean that there aren't i genuine issues in the backlash and obviously work transition, all the rest will be real issues, but How do we help people see this could be an important part of their future?

52:27 Yeah, it's I think Read at least now. I've come to the conclusion that Um There needs

52:35 Tangible practical, well understood, um outcomes. That

52:45 speak for themselves. Because I think what has happened, and this is one of those places where Quite frankly, our industry even, you know, the way we t have talked about it. I mean when you go out and say, hey you know, all economic opportunity will go away for knowledge workers or you know, white collar jobs are gone or you know And and you

53:06 Uh and then you're saying, Oh, I'm excited about building that technology, right? Why would anyone want you to be successful, right? Uh I mean I don't want you to be successful. I mean this just makes no s econom you know no social sense. So I feel now Um think when you know, when you have someone in a college commencement be booed because they're saying AI isn't

53:30 you know means we have now cross over to people don't believe us. And and rightfully so. So therefore I think what do we need to do now is time to do the hard work. The hard work is if you're building a data center. Let's make sure that that community believes that this data center is great for them. It's the for their tax base, for their community effort, their real estate value, their schools, uh, their water use, right? Their electricity prices. It can't be again like, oh, I said something. No, it has to be real. Right. That's kind of what the way we earn social permission. Same thing I I would say with employment. We can't abstractly even say hey, lump of labor fallacy, always there's gonna be new jobs.

54:12 What are the new jobs? What are the wages of the new jobs that I can now go apply for, train myself for, and and how do I really start a new company or what have you, right? I think unless we really get clear, or the third thing which we unpacked a lot, every firm. needs to participate in the frontier ecosystem. Oh, it's not like, oh, I'm just a feeder of data to some foundation model. Like that is like talk about sovereignty and dignity both being lost, right? At simultaneously, right, by for countries, communities, and companies. So I think now We have to go all the way and say, Okay, this is a positive sum. This is, in fact, the challenges of some of the technology. We are going to really actively work it. We can articulate the tangible benefits. And this is where, again, what you will do at Manas and others are also going to be very, very helpful because the world needs more proof points that this technology is ultimately helping.

55:12 helping human condition in our societies broadly, not narrowly. Yeah. Nope. AI for humanity. So uh you don't have to answer rapidly, but we ask the same questions all our guests. Um so the first one is, is there a movie? Song or book. That filled you with optimism. For the future.

55:30 It's this uh Yeah. Parallel paths to prosperity. Right, because I I've the reason why I like that is because it's a good call to action for the next thousand years. What's the path to prosperity? There was a blueprint.

55:44 Um at least at at the part of the world got it right in the last thousand. An entire planet get it. uh right for the next thousand. I think that this is where Uh some of our very best work has to be done. Yeah.

55:59 Agreed. What's a question That you wish people would ask you more often. That's a good one. I would love for people to ask me what am I not excited about? Because I'm excited about a lot of things. Uh, but I'm not excited, for example, about us losing permission on uh AI by you know saying all the wrong things or doing the wrong things even and not having a a complete thought on how to truly have a positive sum construct.

56:26 Yep. A hundred percent. So where do you see progress or momentum outside of your industry and given that Microsoft powers a lot of the world's industry. Um But you know, uh it could be robotics, AI, or et cetera. But where do you see progress that inspires you?

56:42 I mean it I mean Yeah. Yeah. The work in bio I mean, if I think about it, right, one of the most complex systems

56:52 Um, that we have to have a better understanding of is human biology. So anything, any tool that can help humans. Take care of humans. is probably the thing that will have uh it's it's awe inspiring. There's this one thing uh we j I recently came across, right, which is this for immunotherapy, I believe there's a test. Um that is uh, you know, basically a a complex, costly test that figures out whether a particular immunotherapy will work on that tumor or not.

57:27 Um, and so Providence and uh some researchers at UW and Microsoft research came together and built this thing called GigaTime, uh, which is a cool model, which basically is a simulation of that test and reduces the cost of what could get done only at sort of, you know, for it took a lot of time and a lot of money. now can be done by any tertiary sort of hospital in a z you know in any city. And that type Of economic sort of availability of sort of medicine and and uh and medical practice, I think it's just breakthrough.

58:02 So last question. Can you leave us with a final thought on what you think is possible to achieve that everything breaks humanity's way in the next fifteen years? And what's our first step? Mm. I think

58:13 If Everything breaks our way. I've always gone back, like what's the dream? Um of the world.

58:23 Compounding. at ten percent. GDP growth. Right. Um

58:29 Dack. Is what can happen, right? I mean one thought experiment is if the industrial revolution had reached all corners of the world At the same time. And every country

58:41 could express their comparative advantage. Fully. Right, that's the maximalist positive sum construct. Can we do it, right? Because we are kind of captive to this what we'll describe as hey That's not how the world works. History is about dominance and dominant powers and and I'm not saying we will defy all that, but the bottom line is

59:06 Since you asked me to dream, I'm dreaming that if humanity can get back past their bounded rationality. And only sort of say, oh, history repeats itself and we're only never going to get better than, you know, I know, fighting these wars and and what have you, and say, no, no, no, let's maybe uh we can change the course. Uh then the first step would be to accept that that possibility exists is what I would say is what'll get us down. Otherwise we're going to back to relitigating, oh we are let me look at history and then just try to match. Beautiful.

59:41 Satya, always a pleasure, and I'll see you next week at the board meeting. Thank you so much, Reed. Thank you so much. This is awesome. Yeah. Such a fun conversation. Yes, exactly. Possible is produced by Pilate Media. It's hosted by R Finger and me, Reed Hoffman. Our showrunner is Sean Young. Possible is produced by Tanasa Delos, Katie Sanders,

1:00:00 Spencer Strossmore. Emozu. Amon Surrey. Lexi Kevin Danny Garrison.

1:00:06 Trent Barbosa. And to Fadswa? Nemo Rundway. Special thanks to Surya, Yalamanchili, Sayida Sabieva. Ian Alice, Greg Biotto, Parth Patill.

1:00:15 And Ben Ralis.

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